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PHD Project - Driver energy prediction
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Diss/02_code/00_RawData_Python/sklearn-rerun_JZ.ipynb

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{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Setup\n",
"\n",
"`TRAINING_RANGE` und `TEST_RANGE` müssen je nach Länge des Datensatzes angepasst werden.\n",
"\n",
"**Keine Anpassung erforderlich** (Siehe Datensatz herunterladen)\n",
"- 30% Training-Daten (0-30%)\n",
"- 70% Test-Daten (30%-100%)"
]
},
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"416"
]
},
"execution_count": 1,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"INPUT_FILE = 'data.csv'\n",
"TARGET_COLUMN = 'flt_obd_speed'\n",
"# Still contains positional information and acceleration; however we currently train\n",
"# sample by sample without knowledge of previous or other data, so it should not be\n",
"# possible for the Regressor to simply \"calculate\" the speed.\n",
"EXCLUDED_COLUMNS = ('flt_gps_speed', 'flt_obd_engine_load', 'flt_obd_engine_rpm',\n",
" 'flt_obd_maf', 'flt_obd_accelerator_pedal','flt_time','flt_time_system_clock',\n",
" 'flt_time_utc','flt_ax','flt_ay','flt_az','flt_gx','flt_gy','flt_gz','flt_compass',\n",
" 'flt_number_of_satelites','flt_accuracy','flt_gps_bearing','flt_calc_dist_gps',\n",
" 'flt_calc_dist_vt','flt_calc_ax_vt','flt_timeIP',\n",
" 'weat_latitude','weat_longitude','weat_distanceIP','weat_timeIP','weat_join_idx',\n",
" 'hAccel_1','hAccel_2','hAccel_3','flt_mAccel_1','flt_mAccel_2','flt_mAccel_3',\n",
" 'flt_mGier_1','flt_mGier_2','flt_mGier_3','rot_Accel_1','rot_Accel_2','rot_Accel_3',\n",
" 'rot_Gier_1','rot_Gier_2','rot_Gier_3','rot_Accel_flt_1','rot_Accel_flt_2','rot_Accel_flt_3',\n",
" 'rot_Gier_flt_1','rot_Gier_flt_2','rot_Gier_flt_3'\n",
" )\n",
"# See explanation below the feature importance plot\n",
"OVERFITTING_COLUMNS = ('weat_temperature', 'weat_humidity', 'join_idx', 'weat_windBearing', 'weat_windSpeed',\n",
" #'latitude', 'longitude', 'flt_latitude', 'flt_longitude',\n",
" 'ors_percentage_cumsum', 'flt_obd_air_temperature',\n",
" 'mb_step_weight')\n",
"# Since there are a lot of fields containing those\n",
"# Note: This breaks the map plotting\n",
"OVERFITTING_SUBWORDS = ('distance', 'remainDistance', 'remainDistanze', 'cumsumDistance', 'segDistance', 'time', 'remainTime')\n",
"\n",
"from runsql import runsql\n",
"DATA_COLUMNS = [c['Field']\n",
" for c in runsql('show columns from computeddata')\n",
" if c['Type'] == 'double'\n",
" and c['Field'] != TARGET_COLUMN\n",
" #and c['Field'] not in EXCLUDED_COLUMNS\n",
" #and c['Field'] not in OVERFITTING_COLUMNS\n",
" #and not any([w in c['Field'] for w in OVERFITTING_SUBWORDS])\n",
" ]\n",
"len(DATA_COLUMNS)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Datensatz herunterladen\n",
"\n",
"`SETUP_ID` anpassen, Rest läuft automatisch.\n",
"\n",
"Einige Datensätze besitzen keinen Eintrag für `flt_obd_speed`. Für eine Liste der Datensätze *mit* diesem Wert kann beispielsweise folgende SQL-Abfrage verwendet werden (Achtung, braucht (prinzipbedingt) sehr lange!):\n",
"\n",
"```sql\n",
"select setup_id s, count(*) n\n",
"from computeddata\n",
"group by s\n",
"having not exists (\n",
" select *\n",
" from computeddata\n",
" where setup_id = s\n",
" and flt_obd_speed is null)\n",
"order by n asc\n",
"```"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [],
"source": [
"SETUP_ID = 868\n",
"import csv\n",
"from runsql import runsql\n",
"reader = runsql('select * from computeddata where setup_id = {} order by distance asc'.format(SETUP_ID))\n",
"reader_data = list(reader) # list(...) so that following cells can be repeated"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [],
"source": [
"import math\n",
"data = []\n",
"target = []\n",
"for row in reader_data:\n",
" data += [[float(row[c]) if row[c] != '' else math.nan for c in DATA_COLUMNS]]\n",
" target += [float(row[TARGET_COLUMN])] # Errors if NaN in TARGET_COLUMN"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [],
"source": [
"tr_st = 0\n",
"tr_ed = math.floor(len(data)*0.3)\n",
"TRAINING_RANGE = (tr_st, tr_ed)\n",
"TEST_RANGE = (tr_ed, len(data)) # TEST_RANGE = (len(data)-tr_ed, len(data))"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Leere Zellen füllen\n",
"\n",
"Da nicht alle Datensätze alle Spalten haben – gäbe sicherlich bessere Strategien, aber das funktioniert erstaunlich gut (wahrscheinlich sind die \"wichtigen\" Spalten immer vorhanden)."
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"(7228, 416)"
]
},
"execution_count": 5,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"from sklearn.impute import SimpleImputer\n",
"imp = SimpleImputer(strategy='constant', fill_value=0) # Other strategies remove fully null columns\n",
"data = imp.fit_transform(data)\n",
"import numpy as np\n",
"np.shape(data)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Analyze INPUT DATA\n",
"Eingangsdaten analysieren"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {
"scrolled": false
},
"outputs": [
{
"data": {
"text/html": [
"<div><i>Table length=7228</i>\n",
"<table id=\"table140522945280080\" class=\"table-striped table-bordered table-condensed\">\n",
"<thead><tr><th>distance</th><th>latitude</th><th>longitude</th><th>time</th><th>join_idx</th><th>curvature</th><th>radius</th><th>phiSegment</th><th>flt_DB_counter</th><th>flt_setup_id</th><th>flt_time</th><th>flt_time_system_clock</th><th>flt_time_utc</th><th>flt_latitude</th><th>flt_longitude</th><th>flt_altitude</th><th>flt_gps_speed</th><th>flt_ax</th><th>flt_ay</th><th>flt_az</th><th>flt_gx</th><th>flt_gy</th><th>flt_gz</th><th>flt_compass</th><th>flt_number_of_satelites</th><th>flt_accuracy</th><th>flt_gps_bearing</th><th>flt_obd_engine_load</th><th>flt_obd_engine_rpm</th><th>flt_obd_maf</th><th>flt_obd_accelerator_pedal</th><th>flt_obd_air_temperature</th><th>flt_calc_dist_gps</th><th>flt_calc_dist_vt</th><th>flt_calc_ax_vt</th><th>flt_go_elevation</th><th>flt_go_eleResolution</th><th>flt_distanceIP</th><th>flt_timeIP</th><th>flt_osm_trafficSignal</th><th>flt_osm_w_wood</th><th>flt_join_idx</th><th>flt_curvature</th><th>flt_radius</th><th>flt_phiSegment</th><th>hr_latitude</th><th>hr_longitude</th><th>hr_elevation</th><th>hr_distance</th><th>hr_SpeedLimit</th><th>hr_LinkID</th><th>hr_shapeFirstPoint</th><th>hr_shapeLastPoint</th><th>hr_lengthSegemnt</th><th>hr_remainDistanze</th><th>hr_remainTime</th><th>hr_actualManeuver</th><th>hr_traficSpeed</th><th>hr_traficTime</th><th>hr_baseSpeed</th><th>hr_baseTime</th><th>hr_JamFactor</th><th>hr_FunctionalRoadClass</th><th>hr_consumption</th><th>hr_mTravelTime</th><th>hr_mLenght</th><th>hr_mFirstPoint</th><th>hr_mLastPoint</th><th>hr_mNextManeuver</th><th>hr_mTrafficTime</th><th>hr_mStartAngle</th><th>hr_leg_firtPoint</th><th>hr_leg_lastPoint</th><th>hr_leg_length</th><th>hr_leg_travelTime</th><th>hr_leg_trafficTime</th><th>hr_leg_baseTime</th><th>hr_leg_spot</th><th>hr_leg_shapeIndex</th><th>hr_IdxNP</th><th>hr_NearestPoint_1</th><th>hr_NearestPoint_2</th><th>hr_PointOnRoute_1</th><th>hr_PointOnRoute_2</th><th>hr_Dist2Origin</th><th>hr_Dist2Route</th><th>hr_distance_lldist</th><th>hr_osm_trafficSignal</th><th>hr_osm_w_wood</th><th>hr_distanceIP</th><th>hr_join_idx</th><th>hr_curvature</th><th>hr_radius</th><th>hr_phiSegment</th><th>go_start_latitude</th><th>go_start_longitude</th><th>go_end_latitude</th><th>go_end_longitude</th><th>go_distance</th><th>go_duration</th><th>go_latitude</th><th>go_longitude</th><th>go_routing_flag</th><th>go_mean_velocity_calc_pre</th><th>go_mean_velocity_calc</th><th>go_cum_distance</th><th>go_IdxNP</th><th>go_NearestPoint_1</th><th>go_NearestPoint_2</th><th>go_PointOnRoute_1</th><th>go_PointOnRoute_2</th><th>go_Dist2Origin</th><th>go_Dist2Route</th><th>go_distanceIP</th><th>go_join_idx</th><th>go_curvature</th><th>go_radius</th><th>go_phiSegment</th><th>osrm_latitude</th><th>osrm_longitude</th><th>osrm_seg_datasources</th><th>osrm_seg_weight</th><th>osrm_seg_distance</th><th>osrm_seg_duration</th><th>osrm_seg_nodeID</th><th>osrm_step_weight</th><th>osrm_step_duration</th><th>osrm_step_distance</th><th>osrm_mn_bearing_before</th><th>osrm_mn_bearing_after</th><th>osrm_mn_exit</th><th>osrm_i_lanes_valid_1</th><th>osrm_i_lanes_valid_2</th><th>osrm_i_lanes_valid_3</th><th>osrm_i_lanes_valid_4</th><th>osrm_i_lanes_valid_5</th><th>osrm_i_lanes_valid_6</th><th>osrm_i_bearings_1</th><th>osrm_i_bearings_2</th><th>osrm_i_bearings_3</th><th>osrm_i_bearings_4</th><th>osrm_i_bearings_5</th><th>osrm_i_bearings_6</th><th>osrm_i_entry_1</th><th>osrm_i_entry_2</th><th>osrm_i_entry_3</th><th>osrm_i_entry_4</th><th>osrm_i_entry_5</th><th>osrm_i_entry_6</th><th>osrm_i_in</th><th>osrm_i_out</th><th>osrm_i_laneNumber</th><th>osrm_seg_speed</th><th>osrm_segDistance_lldist</th><th>osrm_seg_cumsumDistance</th><th>osrm_IdxNP</th><th>osrm_NearestPoint_1</th><th>osrm_NearestPoint_2</th><th>osrm_PointOnRoute_1</th><th>osrm_PointOnRoute_2</th><th>osrm_Dist2Origin</th><th>osrm_Dist2Route</th><th>osrm_distanceIP</th><th>osrm_join_idx</th><th>osrm_curvature</th><th>osrm_radius</th><th>osrm_phiSegment</th><th>ors_latitude</th><th>ors_longitude</th><th>ors_elevation</th><th>ors_long_distance</th><th>ors_long_duration</th><th>ors_ascent_route</th><th>ors_descent_route</th><th>ors_detourfactor</th><th>ors_percentage</th><th>ors_avgspeed</th><th>ors_seg_distance</th><th>ors_seg_duration</th><th>ors_type</th><th>ors_maneuver_bearing_before</th><th>ors_maneuver_bearing_after</th><th>ors_seg_speed</th><th>ors_long_speed</th><th>ors_distance_lldist</th><th>ors_seg_distance_cumsum</th><th>ors_long_distance_cumsum</th><th>ors_percentage_cumsum</th><th>ors_IdxNP</th><th>ors_NearestPoint_1</th><th>ors_NearestPoint_2</th><th>ors_PointOnRoute_1</th><th>ors_PointOnRoute_2</th><th>ors_Dist2Origin</th><th>ors_Dist2Route</th><th>ors_distanceIP</th><th>ors_join_idx</th><th>ors_curvature</th><th>ors_radius</th><th>ors_phiSegment</th><th>osm_w_lanes</th><th>osm_w_lanes_forward</th><th>osm_w_lanes_backward</th><th>osm_w_maxspeed</th><th>osm_w_maxspeed_forward</th><th>osm_w_maxspeed_backward</th><th>osm_Node_ID_osrm</th><th>osm_Way_ID</th><th>osm_Way_direction</th><th>osm_Calc_Lanes</th><th>osm_w_maxspeed_new</th><th>osm_latitude</th><th>osm_longitude</th><th>osm_distanceIP</th><th>osm_IdxNP</th><th>osm_NearestPoint_1</th><th>osm_NearestPoint_2</th><th>osm_PointOnRoute_1</th><th>osm_PointOnRoute_2</th><th>osm_Dist2Origin</th><th>osm_Dist2Route</th><th>osm_f_filt</th><th>osm_join_idx</th><th>osm_curvature</th><th>osm_radius</th><th>osm_phiSegment</th><th>tt_latitude</th><th>tt_longitude</th><th>tt_sec_Motorway</th><th>tt_sec_traffic</th><th>tt_calc_speedInKmPerH</th><th>tt_calc_distance</th><th>tt_calc_time</th><th>tt_IdxNP</th><th>tt_NearestPoint_1</th><th>tt_NearestPoint_2</th><th>tt_PointOnRoute_1</th><th>tt_PointOnRoute_2</th><th>tt_Dist2Origin</th><th>tt_Dist2Route</th><th>tt_distanceIP</th><th>tt_join_idx</th><th>tt_curvature</th><th>tt_radius</th><th>tt_phiSegment</th><th>weat_temperature</th><th>weat_precipIntensity</th><th>weat_humidity</th><th>weat_windSpeed</th><th>weat_windBearing</th><th>weat_visibility</th><th>weat_cloudCover</th><th>weat_sunriseTime</th><th>weat_sunsetTime</th><th>weat_latitude</th><th>weat_longitude</th><th>weat_distanceIP</th><th>weat_timeIP</th><th>weat_join_idx</th><th>weat_curvature</th><th>weat_radius</th><th>weat_phiSegment</th><th>mb_latitude</th><th>mb_longitude</th><th>mb_seg_speed</th><th>mb_seg_distance</th><th>mb_seg_duration</th><th>mb_step_weight</th><th>mb_step_duration</th><th>mb_step_distance</th><th>mb_mn_bearing_before</th><th>mb_mn_bearing_after</th><th>mb_mn_exit</th><th>mb_mn_modifier</th><th>mb_i_bearings_1</th><th>mb_i_bearings_2</th><th>mb_i_bearings_3</th><th>mb_i_bearings_4</th><th>mb_i_bearings_5</th><th>mb_i_bearings_6</th><th>mb_i_bearings_7</th><th>mb_i_bearings_8</th><th>mb_i_entry_1</th><th>mb_i_entry_2</th><th>mb_i_entry_3</th><th>mb_i_entry_4</th><th>mb_i_entry_5</th><th>mb_i_entry_6</th><th>mb_i_entry_7</th><th>mb_i_entry_8</th><th>mb_i_in</th><th>mb_i_out</th><th>mb_i_laneNumber</th><th>mb_seg_speed_calc</th><th>mb_segDistance_lldist</th><th>mb_seg_cumsumDistance</th><th>mb_IdxNP</th><th>mb_NearestPoint_1</th><th>mb_NearestPoint_2</th><th>mb_PointOnRoute_1</th><th>mb_PointOnRoute_2</th><th>mb_Dist2Origin</th><th>mb_Dist2Route</th><th>mb_distanceIP</th><th>mb_seg_congestion_calc</th><th>mb_join_idx</th><th>mb_curvature</th><th>mb_radius</th><th>mb_phiSegment</th><th>gh_latitude</th><th>gh_longitude</th><th>gh_elevation</th><th>gh_distance_lldist</th><th>gh_distance</th><th>gh_time</th><th>gh_avgspeed</th><th>gh_sign</th><th>gh_IdxNP</th><th>gh_NearestPoint_1</th><th>gh_NearestPoint_2</th><th>gh_PointOnRoute_1</th><th>gh_PointOnRoute_2</th><th>gh_Dist2Origin</th><th>gh_Dist2Route</th><th>gh_distanceIP</th><th>gh_join_idx</th><th>gh_curvature</th><th>gh_radius</th><th>gh_phiSegment</th><th>mq_latitude</th><th>mq_longitude</th><th>mq_distance_lldist</th><th>mq_distance</th><th>mq_duration</th><th>mq_avgspeed</th><th>mq_avgspeed_leg</th><th>mq_IdxNP</th><th>mq_NearestPoint_1</th><th>mq_NearestPoint_2</th><th>mq_PointOnRoute_1</th><th>mq_PointOnRoute_2</th><th>mq_Dist2Origin</th><th>mq_Dist2Route</th><th>mq_distanceIP</th><th>mq_join_idx</th><th>mq_curvature</th><th>mq_radius</th><th>mq_phiSegment</th><th>bg_latitude</th><th>bg_longitude</th><th>bg_distance</th><th>bg_duration</th><th>bg_avgspeed</th><th>bg_avgspeed_subleg</th><th>bg_avgspeed_leg</th><th>bg_roadShiedType</th><th>bg_distance_lldist</th><th>bg_IdxNP</th><th>bg_NearestPoint_1</th><th>bg_NearestPoint_2</th><th>bg_PointOnRoute_1</th><th>bg_PointOnRoute_2</th><th>bg_Dist2Origin</th><th>bg_Dist2Route</th><th>bg_distanceIP</th><th>bg_join_idx</th><th>bg_curvature</th><th>bg_radius</th><th>bg_phiSegment</th><th>ei_latitude</th><th>ei_longitude</th><th>ei_distance_lldist</th><th>ei_Cumul_Kilometers</th><th>ei_Cumul_TravelTime</th><th>ei_distance</th><th>ei_time</th><th>ei_avgspeed</th><th>ei_IdxNP</th><th>ei_NearestPoint_1</th><th>ei_NearestPoint_2</th><th>ei_PointOnRoute_1</th><th>ei_PointOnRoute_2</th><th>ei_Dist2Origin</th><th>ei_Dist2Route</th><th>ei_distanceIP</th><th>ei_join_idx</th><th>ei_curvature</th><th>ei_radius</th><th>ei_phiSegment</th><th>go_alpha</th><th>hr_alpha</th><th>ors_alpha</th><th>go_alpha_filt</th><th>hr_alpha_filt</th><th>ors_alpha_filt</th><th>hAccel_1</th><th>hAccel_2</th><th>hAccel_3</th><th>flt_mAccel_1</th><th>flt_mAccel_2</th><th>flt_mAccel_3</th><th>flt_mGier_1</th><th>flt_mGier_2</th><th>flt_mGier_3</th><th>rot_Accel_1</th><th>rot_Accel_2</th><th>rot_Accel_3</th><th>rot_Gier_1</th><th>rot_Gier_2</th><th>rot_Gier_3</th><th>rot_Accel_flt_1</th><th>rot_Accel_flt_2</th><th>rot_Accel_flt_3</th><th>rot_Gier_flt_1</th><th>rot_Gier_flt_2</th><th>rot_Gier_flt_3</th></tr></thead>\n",
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"<tr><td>5.0</td><td>48.743660011792</td><td>11.4365881471774</td><td>1.28682987369109</td><td>2.0</td><td>-0.118087213821873</td><td>10000.0</td><td>-0.0122338546400346</td><td>15425442.0</td><td>868.0</td><td>1544811290480.0</td><td>24808923.0</td><td>1544811290951.0</td><td>48.743648173883</td><td>11.4366031062737</td><td>409.825890418449</td><td>0.0</td><td>-0.488417148590088</td><td>1.67594122886658</td><td>9.55765342712402</td><td>0.00366519158706069</td><td>0.0134390350431204</td><td>0.098960168659687</td><td>201.90998840332</td><td>10.0</td><td>4.0</td><td>0.0</td><td>44.0</td><td>836.0</td><td>10.02</td><td>14.5</td><td>0.0</td><td>6.7134258229817</td><td>1.49694452683131</td><td>0.0</td><td>368.086729749395</td><td>19.087904</td><td>6.7134258229817</td><td>1.946</td><td>0.0</td><td>0.0</td><td>2.0</td><td>-0.229402046349957</td><td>10000.0</td><td>-0.0240652900167473</td><td>0.0</td><td>0.0</td><td>414.0</td><td>-124.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>36219.0</td><td>2152.33333333333</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>-124.353740605073</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>-1.18070170061091e-07</td><td>10000.0</td><td>-1.00139465407458e-08</td><td>48.7437194</td><td>11.4366254</td><td>48.7407914</td><td>11.4379452</td><td>340.0</td><td>72.0</td><td>48.7437194</td><td>11.4366254</td><td>0.0</td><td>4.72222222222222</td><td>4.22857142857143</td><td>340.0</td><td>2.0</td><td>48.7436669947126</td><td>11.4365793231374</td><td>48.7436669947126</td><td>11.4365793231374</td><td>3.98928801573629</td><td>6.73581189226087</td><td>3.98928801573629</td><td>2.0</td><td>-1.94567828041113e-08</td><td>10000.0</td><td>-2.15210477773033e-09</td><td>48.743646</td><td>11.436655</td><td>1.0</td><td>4.3</td><td>9.66172615225224</td><td>4.3</td><td>466244469.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>1.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>2.24691305866331</td><td>28.8334351384618</td><td>28.8415704155264</td><td>3.0</td><td>48.743648173883</td><td>11.4366031062737</td><td>48.743648173883</td><td>11.4366031062737</td><td>6.7134258229817</td><td>3.81278695212838</td><td>6.7134258229817</td><td>2.0</td><td>0.0446834577738649</td><td>22.3796467504147</td><td>0.00444825745776588</td><td>48.7435</td><td>11.43661</td><td>368.5</td><td>919.2</td><td>126.5</td><td>1.6</td><td>2.2</td><td>1.2</td><td>2.59</td><td>26.16</td><td>0.0</td><td>0.0</td><td>11.0</td><td>255.0</td><td>0.0</td><td>4.17098445595855</td><td>7.26640316205534</td><td>0.0</td><td>0.0</td><td>919.2</td><td>2.59</td><td>3.0</td><td>48.743648173883</td><td>11.4366031062737</td><td>48.743648173883</td><td>11.4366031062737</td><td>6.7134258229817</td><td>16.4839362868523</td><td>6.7134258229817</td><td>2.0</td><td>-0.0665863721547957</td><td>8397.31116181848</td><td>0.000917619611676535</td><td>2.0</td><td>0.0</td><td>0.0</td><td>20.0</td><td>0.0</td><td>0.0</td><td>466244469.0</td><td>201078447.0</td><td>0.0</td><td>2.0</td><td>20.0</td><td>48.743646</td><td>11.436655</td><td>6.7134258229817</td><td>3.0</td><td>48.743648173883</td><td>11.4366031062737</td><td>48.743648173883</td><td>11.4366031062737</td><td>6.7134258229817</td><td>3.81278695212838</td><td>3.81278695212838</td><td>2.0</td><td>0.0446834577738649</td><td>22.3796467504147</td><td>0.00444825745776588</td><td>48.74371</td><td>11.43667</td><td>0.0</td><td>0.0</td><td>12.0789473684211</td><td>0.0</td><td>0.0</td><td>3.0</td><td>48.743648173883</td><td>11.4366031062737</td><td>48.743648173883</td><td>11.4366031062737</td><td>6.7134258229817</td><td>8.44518411472761</td><td>6.7134258229817</td><td>2.0</td><td>0.00174903866906076</td><td>571.742648609988</td><td>0.000174165933515809</td><td>-0.950100189930144</td><td>0.0</td><td>0.69</td><td>1.76969814855808</td><td>99.9892769416047</td><td>9.46110678862036</td><td>1.0</td><td>1544770869.98194</td><td>1544800767.01003</td><td>48.743648173883</td><td>11.4366031062737</td><td>6.7134258229817</td><td>1.946</td><td>2.0</td><td>-0.229402046349957</td><td>10000.0</td><td>-0.0240652900167473</td><td>48.7435</td><td>11.43661</td><td>0.0</td><td>0.0</td><td>0.0</td><td>73.9</td><td>73.7</td><td>161.1</td><td>0.0</td><td>255.0</td><td>0.0</td><td>3.0</td><td>255.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>1.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>6.11753061330511</td><td>0.0</td><td>0.0</td><td>3.0</td><td>48.743648173883</td><td>11.4366031062737</td><td>48.743648173883</td><td>11.4366031062737</td><td>6.7134258229817</td><td>16.4839362868523</td><td>6.7134258229817</td><td>0.0</td><td>2.0</td><td>0.547290352880163</td><td>1.82719873896167</td><td>0.0537059395229452</td><td>48.743532</td><td>11.436782</td><td>368.0</td><td>22.1798374251795</td><td>0.0</td><td>0.0</td><td>21.1299820289998</td><td>0.0</td><td>3.0</td><td>48.743648173883</td><td>11.4366031062737</td><td>48.743648173883</td><td>11.4366031062737</td><td>6.7134258229817</td><td>18.4103310994318</td><td>6.7134258229817</td><td>2.0</td><td>-0.301926524691915</td><td>10000.0</td><td>-0.0292445958201256</td><td>0.0</td><td>0.0</td><td>26914.4483882672</td><td>0.0</td><td>0.0</td><td>48.28</td><td>28.452</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>2.75392256456889e-08</td><td>10000.0</td><td>7.62568235573323e-09</td><td>48.74354</td><td>11.43675</td><td>0.459</td><td>52.0</td><td>31.7769230769231</td><td>17.2114285714286</td><td>25.4629213483146</td><td>0.0</td><td>23.4951242518761</td><td>3.0</td><td>48.743648173883</td><td>11.4366031062737</td><td>48.743648173883</td><td>11.4366031062737</td><td>6.7134258229817</td><td>16.1461130673699</td><td>6.7134258229817</td><td>2.0</td><td>0.956806287850118</td><td>1.04514367741941</td><td>0.0915489093635408</td><td>0.0</td><td>0.0</td><td>3.20470261877408</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>-2.30817947802479e-06</td><td>10000.0</td><td>-2.05260108107448e-07</td><td>0.0123132369591054</td><td>0.0</td><td>-0.000394770104368787</td><td>0.0122753821688151</td><td>-3.72869319289494e-06</td><td>-0.0198366269937724</td><td>-0.0269397981513654</td><td>0.00931239233799909</td><td>-9.80926089931977</td><td>-0.488417148590088</td><td>1.67594122886658</td><td>9.55765342712402</td><td>0.00366519158706069</td><td>0.0134390350431204</td><td>0.098960168659687</td><td>0.285998897438362</td><td>-0.132003439593311</td><td>-9.83048269370201</td><td>-0.00976889747553611</td><td>-0.00525418888235728</td><td>0.0993182682829033</td><td>0.565435314209628</td><td>-0.172681164156471</td><td>-14.9019058437669</td><td>0.00500402931229131</td><td>0.0029062661334533</td><td>0.0694993957818311</td></tr>\n",
"<tr><td>10.0</td><td>48.7436454613238</td><td>11.4365591501146</td><td>3.48184654584225</td><td>3.0</td><td>-0.645687711891759</td><td>10000.0</td><td>-0.0619033803749528</td><td>15425459.0</td><td>868.0</td><td>1544811292461.0</td><td>24810904.0</td><td>1544811293000.0</td><td>48.7436424877221</td><td>11.4365464657345</td><td>411.206918184896</td><td>0.0</td><td>-0.469263523817062</td><td>1.39821374416351</td><td>9.50019264221191</td><td>-0.00244346098043025</td><td>0.0122173046693206</td><td>0.0659734457731247</td><td>192.050003051758</td><td>10.0</td><td>4.0</td><td>0.0</td><td>44.0</td><td>831.0</td><td>3.63</td><td>14.5</td><td>0.0</td><td>10.9871100025198</td><td>2.74291670984692</td><td>0.0</td><td>368.148299045848</td><td>19.087904</td><td>10.9871100025198</td><td>3.927</td><td>0.0</td><td>0.0</td><td>3.0</td><td>-0.160303245237615</td><td>10000.0</td><td>-0.016532581992672</td><td>0.0</td><td>0.0</td><td>414.0</td><td>-118.833333333333</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>36213.8333333333</td><td>2150.61111111111</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>-119.172334746528</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>-7.6567965179289e-08</td><td>10000.0</td><td>-1.65743142702731e-09</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>4.72222222222222</td><td>4.22857142857143</td><td>362.849315068493</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>-1.29647082163552e-08</td><td>10000.0</td><td>-1.66871282104217e-09</td><td>0.0</td><td>0.0</td><td>0.0</td><td>4.3</td><td>0.0</td><td>0.0</td><td>466244469.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>1.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>2.24691305866331</td><td>31.9723886490775</td><td>31.9814095736695</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0317477590756731</td><td>31.498286256919</td><td>0.00315407443237575</td><td>0.0</td><td>0.0</td><td>368.498026149376</td><td>907.415384615385</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>26.16</td><td>0.0</td><td>0.0</td><td>11.0</td><td>0.0</td><td>0.0</td><td>4.17098445595855</td><td>7.26640316205534</td><td>2.06476655680674</td><td>2.06410256410256</td><td>919.2</td><td>2.59</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.055489301077692</td><td>18.0214920628145</td><td>0.00550732688091044</td><td>2.0</td><td>0.0</td><td>0.0</td><td>20.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>2.0</td><td>20.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0317477590756731</td><td>31.498286256919</td><td>0.00315407443237575</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>12.0789473684211</td><td>4.55357142857143</td><td>1.35714285714286</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.00124098662004355</td><td>805.810445014668</td><td>0.000123346606186591</td><td>-0.950164002399872</td><td>0.0</td><td>0.69</td><td>1.76950599474287</td><td>99.9824526696327</td><td>9.46181135260947</td><td>1.0</td><td>1544770869.97044</td><td>1544800767.01641</td><td>48.7436424877221</td><td>11.4365464657345</td><td>10.9871100025198</td><td>3.927</td><td>3.0</td><td>-0.160303245237615</td><td>10000.0</td><td>-0.016532581992672</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>73.9</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>1.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>6.11753061330511</td><td>2.06425353019078</td><td>2.0648359538819</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.133600747497228</td><td>7.48498828469955</td><td>0.013135995293465</td><td>0.0</td><td>0.0</td><td>368.001369863014</td><td>25.2940813051306</td><td>0.0</td><td>0.0</td><td>21.1299820289998</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>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"<tr><td>15.0</td><td>48.7436203018653</td><td>11.4365037424583</td><td>6.55025872896082</td><td>4.0</td><td>-0.283126727032737</td><td>10000.0</td><td>-0.0273476259000356</td><td>15425501.0</td><td>868.0</td><td>1544811297498.0</td><td>24815941.0</td><td>1544811298000.0</td><td>48.7436159558468</td><td>11.4364900812436</td><td>412.0974196575</td><td>0.0</td><td>-1.18752408027649</td><td>2.29843354225159</td><td>9.04050540924072</td><td>-0.0146607663482428</td><td>0.0610865242779255</td><td>0.257785141468048</td><td>102.220001220703</td><td>10.0</td><td>4.0</td><td>0.0</td><td>86.0</td><td>942.0</td><td>5.63</td><td>14.5</td><td>0.0</td><td>16.2535720141688</td><td>4.27722235520681</td><td>0.896057283349523</td><td>368.207876036763</td><td>19.087904</td><td>16.2535720141688</td><td>8.964</td><td>0.0</td><td>0.0</td><td>4.0</td><td>-0.100094552615527</td><td>10000.0</td><td>-0.00982017296901295</td><td>0.0</td><td>0.0</td><td>414.0</td><td>-113.666666666667</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>36208.6666666667</td><td>2148.88888888889</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>-113.990928887983</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>-7.25423786383477e-08</td><td>10000.0</td><td>-5.06674786377662e-09</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>4.72222222222222</td><td>4.22857142857143</td><td>385.698630136986</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>-4.30923156727901e-09</td><td>10000.0</td><td>-2.11584081506061e-09</td><td>0.0</td><td>0.0</td><td>0.0</td><td>4.3</td><td>0.0</td><td>0.0</td><td>466244469.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>1.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>2.24691305866331</td><td>35.1113421596933</td><td>35.1212487318126</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0190772575444906</td><td>52.4184357968355</td><td>0.00188826592232102</td><td>0.0</td><td>0.0</td><td>368.496143372151</td><td>895.630769230769</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>26.16</td><td>0.0</td><td>0.0</td><td>11.0</td><td>0.0</td><td>0.0</td><td>4.17098445595855</td><td>7.26640316205534</td><td>4.12953311361348</td><td>4.12820512820513</td><td>919.2</td><td>2.59</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0390710683547581</td><td>25.5943852663158</td><td>0.00387038899277894</td><td>2.0</td><td>0.0</td><td>0.0</td><td>20.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>2.0</td><td>20.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0190772575444906</td><td>52.4184357968355</td><td>0.00188826592232102</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>12.0789473684211</td><td>9.10714285714286</td><td>2.71428571428571</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.00072245499180825</td><td>1384.16926768628</td><td>7.14785774188735e-05</td><td>-0.950242673597029</td><td>0.0</td><td>0.69</td><td>1.76926920520918</td><td>99.9740451517108</td><td>9.46267958089966</td><td>1.0</td><td>1544770869.95627</td><td>1544800767.02428</td><td>48.7436159558468</td><td>11.4364900812436</td><td>16.2535720141688</td><td>8.964</td><td>4.0</td><td>-0.100094552615527</td><td>10000.0</td><td>-0.00982017296901295</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>73.9</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>1.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>6.11753061330511</td><td>4.12850706038156</td><td>4.1296719077638</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0980965543320802</td><td>10.1940378987105</td><td>0.00976066114502093</td><td>0.0</td><td>0.0</td><td>368.002739726027</td><td>28.4083251850817</td><td>0.0</td><td>0.0</td><td>21.1299820289998</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>-0.0749404882812655</td><td>10000.0</td><td>-0.00727036989787782</td><td>48.743492</td><td>11.436567</td><td>0.0</td><td>0.1577</td><td>39.0</td><td>14.5569230769231</td><td>25.6208450704225</td><td>8.0</td><td>48.7436177452335</td><td>11.4364989089468</td><td>48.7436183980582</td><td>11.4365001431627</td><td>15.3383305112246</td><td>14.8852468893247</td><td>15.4543456707984</td><td>4.0</td><td>0.130078538012526</td><td>7.68766668565116</td><td>0.0126925127372926</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>31.7769230769231</td><td>17.2114285714286</td><td>25.4629213483146</td><td>0.0</td><td>29.7627144677918</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.052050864963979</td><td>19.2119705185804</td><td>0.00504063080917179</td><td>0.0</td><td>0.0</td><td>9.61410785632223</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>-7.69085183344749e-07</td><td>10000.0</td><td>-8.69068033393053e-08</td><td>0.0114808820953246</td><td>0.0</td><td>-0.000358795831445069</td><td>0.0116291835517889</td><td>1.39140964805174e-06</td><td>0.00300955679382559</td><td>-0.00630851682305905</td><td>0.000311748121391916</td><td>-9.80933666552677</td><td>-1.18752408027649</td><td>2.29843354225159</td><td>9.04050540924072</td><td>-0.0146607663482428</td><td>0.0610865242779255</td><td>0.257785141468048</td><td>1.09530094901062</td><td>0.475972995307667</td><td>-10.1755683330469</td><td>0.00291540816497373</td><td>0.00679080768737105</td><td>0.265226442886379</td><td>0.211771886402737</td><td>-0.062091969396048</td><td>-8.89039787045779</td><td>0.011756586387218</td><td>0.000730703525049424</td><td>0.0883675689058716</td></tr>\n",
"<tr><td>20.0</td><td>48.7436491772175</td><td>11.4364942496414</td><td>11.5705030238529</td><td>5.0</td><td>-0.0544416952955614</td><td>10000.0</td><td>-0.00537709144886619</td><td>15425526.0</td><td>868.0</td><td>1544811300511.0</td><td>24818954.0</td><td>1544811301000.0</td><td>48.7436572857324</td><td>11.4364933047138</td><td>412.275207405219</td><td>2.02618</td><td>-0.277727395296097</td><td>1.13006317615509</td><td>10.0269165039063</td><td>0.00610865233466029</td><td>0.0183259565383196</td><td>0.0354301854968071</td><td>100.5</td><td>10.0</td><td>4.0</td><td>0.0</td><td>30.0</td><td>943.0</td><td>4.88</td><td>14.5</td><td>0.0</td><td>20.9042840418851</td><td>10.1159719626109</td><td>0.0</td><td>368.265282969543</td><td>19.087904</td><td>20.9042840418851</td><td>11.977</td><td>0.0</td><td>0.0</td><td>5.0</td><td>-0.0439128055117069</td><td>10000.0</td><td>-0.00438556138998388</td><td>0.0</td><td>0.0</td><td>414.0</td><td>-108.5</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>36203.5</td><td>2147.16666666667</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>-108.809523029439</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>1.59058649074888e-07</td><td>10000.0</td><td>2.4545472840003e-09</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>4.72222222222222</td><td>4.22857142857143</td><td>408.547945205479</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>-4.71123742382979e-08</td><td>10000.0</td><td>-2.34883145658848e-09</td><td>0.0</td><td>0.0</td><td>0.0</td><td>4.3</td><td>0.0</td><td>0.0</td><td>466244469.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>1.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>2.24691305866331</td><td>38.250295670309</td><td>38.2610878899557</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0073001825338261</td><td>136.982826874836</td><td>0.000711879479372874</td><td>0.0</td><td>0.0</td><td>368.494349392917</td><td>883.846153846154</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>26.16</td><td>0.0</td><td>0.0</td><td>11.0</td><td>0.0</td><td>0.0</td><td>4.17098445595855</td><td>7.26640316205534</td><td>6.19429967042022</td><td>6.19230769230769</td><td>919.2</td><td>2.59</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.025398295273641</td><td>39.3727213464471</td><td>0.00251057738196863</td><td>2.0</td><td>0.0</td><td>0.0</td><td>20.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>2.0</td><td>20.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0073001825338261</td><td>136.982826874836</td><td>0.000711879479372874</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>12.0789473684211</td><td>13.6607142857143</td><td>4.07142857142857</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.000197748299506019</td><td>5056.92873333576</td><td>1.90018869102858e-05</td><td>-0.950312178816112</td><td>0.0</td><td>0.69</td><td>1.76906010280574</td><td>99.9666225055534</td><td>9.46344628971228</td><td>1.0</td><td>1544770869.94376</td><td>1544800767.03123</td><td>48.7436572857324</td><td>11.4364933047138</td><td>20.9042840418851</td><td>11.977</td><td>5.0</td><td>-0.0439128055117069</td><td>10000.0</td><td>-0.00438556138998388</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>73.9</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>1.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>6.11753061330511</td><td>6.19276059057234</td><td>6.19450786164569</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0714983528847025</td><td>13.9863364658993</td><td>0.00707441699932281</td><td>0.0</td><td>0.0</td><td>368.004109589041</td><td>31.5225690650328</td><td>0.0</td><td>0.0</td><td>21.1299820289998</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>-0.022633488118729</td><td>10000.0</td><td>-0.00222073208994162</td><td>0.0</td><td>0.0</td><td>2.07487049219376</td><td>0.0</td><td>0.0</td><td>14.5569230769231</td><td>25.6208450704225</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0708554186585251</td><td>14.1132465734468</td><td>0.00703603511878876</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>31.7769230769231</td><td>17.2114285714286</td><td>25.4629213483146</td><td>0.0</td><td>32.8965095757497</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0156038536523969</td><td>64.0867294891412</td><td>0.00153174110451861</td><td>0.0</td><td>0.0</td><td>12.8188104750963</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>-2.83017490413514e-07</td><td>10000.0</td><td>-3.01637618607195e-08</td><td>0.0110113793433333</td><td>0.0</td><td>-0.000341491317457937</td><td>0.0109755263374201</td><td>2.26300227677264e-06</td><td>0.00574611812749976</td><td>-0.0385930667320229</td><td>-0.00110137018103655</td><td>-9.80940913894643</td><td>-0.277727395296097</td><td>1.13006317615509</td><td>10.0269165039063</td><td>0.00610865233466029</td><td>0.0183259565383196</td><td>0.0354301854968071</td><td>-0.37429996996993</td><td>-0.266411673082185</td><td>-9.50105790975882</td><td>0.00891885202720506</td><td>-0.00845302524945271</td><td>0.0384376742711786</td><td>0.0957407643272133</td><td>-0.200592625117117</td><td>-8.13836116880453</td><td>0.0125247792765472</td><td>-0.00357387413653213</td><td>0.0333486709761538</td></tr>\n",
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d><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>-0.00949807917970845</td><td>10000.0</td><td>-0.000934982663961143</td><td>0.0</td><td>0.0</td><td>4.14974098438751</td><td>0.0</td><td>0.0</td><td>14.5569230769231</td><td>25.6208450704225</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0557569869615068</td><td>17.9349719363335</td><td>0.0055425095756466</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>31.7769230769231</td><td>17.2114285714286</td><td>25.4629213483146</td><td>0.0</td><td>36.0303046837075</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.00636401147539832</td><td>157.133593314992</td><td>0.000624942289233116</td><td>0.0</td><td>0.0</td><td>16.0235130938704</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>1.99940084836565e-07</td><td>10000.0</td><td>1.82948595276704e-08</td><td>0.0105063251545888</td><td>0.0</td><td>-0.00032464188517238</td><td>0.0102473231831724</td><td>1.74468453455492e-06</td><td>0.00412702954490857</td><td>-0.0781430465416734</td><td>-0.000788133686909745</td><td>-9.80948494207009</td><td>0.0287304203957319</td><td>1.54186594486237</td><td>9.98860931396484</td><td>0.0146607663482428</td><td>-0.0109955742955208</td><td>-0.0916297882795334</td><td>-0.00843259491174531</td><td>-0.625583477728552</td><td>-9.45520998145342</td><td>0.00806766411230781</td><td>-0.0132200359565762</td><td>-0.092152060580521</td><td>0.0273271530253762</td><td>-0.355015475052592</td><td>-8.54026341670872</td><td>0.00847443732427935</td><td>-0.00851107271491372</td><td>-0.0301408279789142</td></tr>\n",
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r>\n",
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"<tr><td>36110.0</td><td>48.4940565365702</td><td>11.3574223130018</td><td>1819.91121717151</td><td>7223.0</td><td>-0.0138980228686826</td><td>10000.0</td><td>-0.00140275415648898</td><td>15455837.0</td><td>868.0</td><td>1544813108698.0</td><td>26631917.0</td><td>1544813114000.0</td><td>48.4940470951323</td><td>11.3574084024918</td><td>516.680995627032</td><td>5.07136</td><td>0.239420175552368</td><td>0.488417148590088</td><td>10.1035308837891</td><td>0.0134390350431204</td><td>-0.00366519158706069</td><td>-0.0342084541916847</td><td>112.919998168945</td><td>10.0</td><td>4.0</td><td>241.780822753906</td><td>20.0</td><td>819.0</td><td>18.77</td><td>14.5</td><td>-3.0</td><td>36111.4672708376</td><td>36791.096111536</td><td>-0.556668945472827</td><td>466.195128928865</td><td>19.087904</td><td>36111.4672708376</td><td>1820.164</td><td>0.0</td><td>0.0</td><td>7223.0</td><td>-0.014036915076068</td><td>10000.0</td><td>-0.0014159824390383</td><td>0.0</td><td>0.0</td><td>512.094391227282</td><td>35991.0769230769</td><td>50.00000148</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>157.0</td><td>10.0</td><td>0.0</td><td>7.7777781</td><td>0.0</td><td>7.7777781</td><td>0.0</td><td>-1.0</td><td>5.0</td><td>48.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>35999.5796726575</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.000485996807585161</td><td>2057.62747278625</td><td>4.82409614259527e-05</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>5.75</td><td>5.75</td><td>35898.4285714286</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>2.33901199904329e-08</td><td>10000.0</td><td>8.47832284754078e-09</td><td>0.0</td><td>0.0</td><td>0.0</td><td>9.9</td><td>0.0</td><td>0.0</td><td>5196637536.0</td><td>48.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>1.0</td><td>1.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>2.0</td><td>6.12102054494306</td><td>36176.0098414576</td><td>36186.2168072735</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>-9.71756373227245e-08</td><td>10000.0</td><td>-8.84008571431305e-10</td><td>0.0</td><td>0.0</td><td>3119.67232142991</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>51.95</td><td>0.0</td><td>0.0</td><td>10.0</td><td>0.0</td><td>0.0</td><td>11.1071428571429</td><td>14.4315196998124</td><td>36094.1499350485</td><td>42259.2</td><td>35541.6</td><td>99.99</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>3.88113499087244e-08</td><td>10000.0</td><td>5.75842526306056e-09</td><td>3.0</td><td>0.0</td><td>0.0</td><td>50.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>1.0</td><td>50.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>-9.71756373227245e-08</td><td>10000.0</td><td>-8.84008571431305e-10</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>16.7142857142857</td><td>155.714285714286</td><td>31.9285714285714</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>-0.00056476135241485</td><td>10000.0</td><td>-5.59694285360008e-05</td><td>-1.91981551028741</td><td>0.0</td><td>0.740777457931279</td><td>1.67</td><td>80.8609121850469</td><td>10.01</td><td>1.0</td><td>1544770823.71603</td><td>1544800852.61251</td><td>48.4940470951323</td><td>11.3574084024918</td><td>36111.4672708376</td><td>1820.164</td><td>7223.0</td><td>-0.014036915076068</td><td>10000.0</td><td>-0.0014159824390383</td><td>0.0</td><td>0.0</td><td>6.1</td><td>0.0</td><td>0.0</td><td>48.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>1.0</td><td>1.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>2.0</td><td>6.12102054494306</td><td>35943.5018480061</td><td>35952.0330497901</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>-1.13326141622205e-07</td><td>10000.0</td><td>-1.18866146512774e-08</td><td>0.0</td><td>0.0</td><td>468.336</td><td>35879.4358560951</td><td>0.0</td><td>0.0</td><td>26.0002359628895</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.000158559532628354</td><td>6306.76550755759</td><td>1.61583278258053e-05</td><td>0.0</td><td>0.0</td><td>40474.1383434653</td><td>0.0</td><td>0.0</td><td>17.1553846153846</td><td>28.452</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>2.9203936155267e-07</td><td>10000.0</td><td>3.31949518999321e-08</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>21.0</td><td>22.23</td><td>34.4866242038217</td><td>0.0</td><td>41121.6107187925</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>-0.000271809387385056</td><td>10000.0</td><td>-2.66640920189704e-05</td><td>0.0</td><td>0.0</td><td>35501.1835596516</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>39.8444307566163</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>-1.85459383861658e-06</td><td>10000.0</td><td>-1.89293539573055e-07</td><td>0.00356895224561042</td><td>-0.00890519152566214</td><td>1.52595055211668</td><td>0.00887208680952535</td><td>-0.00770396844545407</td><td>1.70967160301318</td><td>-0.727268219662609</td><td>-0.138951500446163</td><td>-9.8096139107336</td><td>0.239420175552368</td><td>0.488417148590088</td><td>10.1035308837891</td><td>0.0134390350431204</td><td>-0.00366519158706069</td><td>-0.0342084541916847</td><td>-1.0790532560427</td><td>-0.692337615143047</td><td>-9.58430991020596</td><td>0.00238845130689498</td><td>-0.0128878564556819</td><td>-0.0345319864296423</td><td>-1.10222045814621</td><td>-0.639738541433638</td><td>-9.82262327225138</td><td>-0.0027292955397199</td><td>0.00288670405737579</td><td>-0.0195602248573346</td></tr>\n",
"<tr><td>36115.0</td><td>48.4940309552407</td><td>11.3573671083047</td><td>1820.89155848153</td><td>7224.0</td><td>-0.0298837554036445</td><td>10000.0</td><td>-0.00300795199999502</td><td>15455855.0</td><td>868.0</td><td>1544813109691.0</td><td>26632910.0</td><td>1544813115000.0</td><td>48.4940250667831</td><td>11.3573520425856</td><td>516.619668482659</td><td>4.26989</td><td>-0.143652096390724</td><td>0.316034615039825</td><td>9.720458984375</td><td>0.00488692196086049</td><td>0.00122173049021512</td><td>0.0109955742955208</td><td>113.689994812012</td><td>10.0</td><td>4.0</td><td>242.192794799805</td><td>18.0</td><td>828.0</td><td>8.55</td><td>14.5</td><td>-3.0</td><td>36116.2888764505</td><td>36795.6473616759</td><td>-0.839207762057145</td><td>466.212973765859</td><td>19.087904</td><td>36116.2888764505</td><td>1821.157</td><td>0.0</td><td>0.0</td><td>7224.0</td><td>-0.0306138183852148</td><td>10000.0</td><td>-0.00308519372599808</td><td>0.0</td><td>0.0</td><td>512.049864092611</td><td>35996.3846153846</td><td>50.00000148</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>157.0</td><td>10.0</td><td>0.0</td><td>7.7777781</td><td>0.0</td><td>7.7777781</td><td>0.0</td><td>-1.0</td><td>5.0</td><td>48.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>36004.827943511</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.000103362526031869</td><td>9690.33835784856</td><td>9.98108276789127e-06</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>5.75</td><td>5.75</td><td>35900.0714285714</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>1.23098692189036e-07</td><td>10000.0</td><td>4.92222874411442e-09</td><td>0.0</td><td>0.0</td><td>0.0</td><td>9.9</td><td>0.0</td><td>0.0</td><td>5196637536.0</td><td>48.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>1.0</td><td>1.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>2.0</td><td>6.12102054494306</td><td>36182.0679425199</td><td>36192.276617613</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>-5.47774757930361e-08</td><td>10000.0</td><td>-6.20790099626772e-09</td><td>0.0</td><td>0.0</td><td>3231.09079241211</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>51.95</td><td>0.0</td><td>0.0</td><td>10.0</td><td>0.0</td><td>0.0</td><td>11.1071428571429</td><td>14.4315196998124</td><td>36101.9836282451</td><td>42352.5</td><td>35541.6</td><td>99.99</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>-2.23511031844433e-08</td><td>10000.0</td><td>2.31194119177034e-09</td><td>3.0</td><td>0.0</td><td>0.0</td><td>50.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>1.0</td><td>50.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>-5.47774757930361e-08</td><td>10000.0</td><td>-6.20790099626772e-09</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>16.7142857142857</td><td>158.285714285714</td><td>32.3214285714286</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>-9.00587695402776e-05</td><td>10000.0</td><td>-8.52158337372696e-06</td><td>-1.91972377070817</td><td>0.0</td><td>0.74077926302491</td><td>1.67</td><td>80.8558504899192</td><td>10.01</td><td>1.0</td><td>1544770823.7015</td><td>1544800852.6241</td><td>48.4940250667831</td><td>11.3573520425856</td><td>36116.2888764505</td><td>1821.157</td><td>7224.0</td><td>-0.0306138183852148</td><td>10000.0</td><td>-0.00308519372599808</td><td>0.0</td><td>0.0</td><td>6.1</td><td>0.0</td><td>0.0</td><td>48.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>1.0</td><td>1.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>2.0</td><td>6.12102054494306</td><td>35949.5599490684</td><td>35958.0928601296</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>-1.74418049191846e-07</td><td>10000.0</td><td>-1.05364718349803e-08</td><td>0.0</td><td>0.0</td><td>468.214</td><td>35884.2179736249</td><td>0.0</td><td>0.0</td><td>26.0002359628895</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.000445112523202846</td><td>2246.62077202815</td><td>4.48193851631674e-05</td><td>0.0</td><td>0.0</td><td>40478.4842978665</td><td>0.0</td><td>0.0</td><td>17.1553846153846</td><td>28.452</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>6.61295773132593e-07</td><td>10000.0</td><td>6.52474878214732e-08</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>21.0</td><td>22.23</td><td>34.4866242038217</td><td>0.0</td><td>41126.6693668508</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.000254479471064258</td><td>3929.5863892081</td><td>2.59765568945943e-05</td><td>0.0</td><td>0.0</td><td>35504.4087438459</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>39.8444307566163</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>-2.47324466192903e-06</td><td>10000.0</td><td>-2.45640967871146e-07</td><td>0.010796425728985</td><td>-0.00636487208542326</td><td>1.52715682901742</td><td>0.0179158635493524</td><td>-0.0049914465844796</td><td>1.77834372628108</td><td>-0.957424173418601</td><td>-0.0464607682892896</td><td>-9.80842564420407</td><td>-0.143652096390724</td><td>0.316034615039825</td><td>9.720458984375</td><td>0.00488692196086049</td><td>0.00122173049021512</td><td>0.0109955742955208</td><td>-1.10890277031324</td><td>-0.29027091609998</td><td>-9.98512852197938</td><td>-0.00193697023140012</td><td>-0.00498615513723019</td><td>0.0108472894771331</td><td>-1.10268822552666</td><td>-0.287080881184078</td><td>-9.91139088028638</td><td>-0.00627454617794993</td><td>-0.00194797214075882</td><td>0.0269558346376725</td></tr>\n",
"<tr><td>36120.0</td><td>48.4940086969898</td><td>11.3573081543781</td><td>1822.19059023874</td><td>7225.0</td><td>-0.0501337064091558</td><td>10000.0</td><td>-0.00503037640077838</td><td>15455874.0</td><td>868.0</td><td>1544813110788.0</td><td>26634007.0</td><td>1544813116000.0</td><td>48.4940076927188</td><td>11.357305461879</td><td>516.613684551592</td><td>3.46429</td><td>-0.976834297180176</td><td>0.325611442327499</td><td>9.50019264221191</td><td>-0.0146607663482428</td><td>0.0109955742955208</td><td>0.182037845253944</td><td>107.339996337891</td><td>10.0</td><td>4.0</td><td>231.608734130859</td><td>18.0</td><td>828.0</td><td>16.13</td><td>14.5</td><td>-3.0</td><td>36120.2276738396</td><td>36799.7611121337</td><td>-0.759647439018171</td><td>466.266957992038</td><td>19.087904</td><td>36120.2276738396</td><td>1822.254</td><td>0.0</td><td>0.0</td><td>7225.0</td><td>-0.0536806213820719</td><td>10000.0</td><td>-0.00540068896214191</td><td>0.0</td><td>0.0</td><td>512.018039302425</td><td>36001.6923076923</td><td>50.00000148</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>157.0</td><td>10.0</td><td>0.0</td><td>7.7777781</td><td>0.0</td><td>7.7777781</td><td>0.0</td><td>-1.0</td><td>5.0</td><td>48.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>36010.0762143645</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>-0.000282517384540092</td><td>10000.0</td><td>-2.86133127419765e-05</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>5.75</td><td>5.75</td><td>35901.7142857143</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>4.00542541949583e-08</td><td>10000.0</td><td>5.11764708182275e-09</td><td>0.0</td><td>0.0</td><td>0.0</td><td>9.9</td><td>0.0</td><td>0.0</td><td>5196637536.0</td><td>48.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>1.0</td><td>1.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>2.0</td><td>6.12102054494306</td><td>36188.1260435821</td><td>36198.3364279525</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>-5.51566739250804e-08</td><td>10000.0</td><td>-6.81521347499166e-09</td><td>0.0</td><td>0.0</td><td>3345.59315476336</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>51.95</td><td>0.0</td><td>0.0</td><td>10.0</td><td>0.0</td><td>0.0</td><td>11.1071428571429</td><td>14.4315196998124</td><td>36109.8173214414</td><td>42445.8</td><td>35541.6</td><td>99.99</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>8.34810136937058e-08</td><td>10000.0</td><td>7.90350910199252e-09</td><td>3.0</td><td>0.0</td><td>0.0</td><td>50.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>1.0</td><td>50.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>-5.51566739250804e-08</td><td>10000.0</td><td>-6.81521347499166e-09</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>16.7142857142857</td><td>160.857142857143</td><td>32.7142857142857</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.000380577187301807</td><td>2627.59179350492</td><td>3.85624569292714e-05</td><td>-1.91964850377225</td><td>0.0</td><td>0.740780726998011</td><td>1.67</td><td>80.85171495628</td><td>10.01</td><td>1.0</td><td>1544770823.68962</td><td>1544800852.63358</td><td>48.4940076927188</td><td>11.357305461879</td><td>36120.2276738396</td><td>1822.254</td><td>7225.0</td><td>-0.0536806213820719</td><td>10000.0</td><td>-0.00540068896214191</td><td>0.0</td><td>0.0</td><td>6.1</td><td>0.0</td><td>0.0</td><td>48.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>1.0</td><td>1.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>2.0</td><td>6.12102054494306</td><td>35955.6180501306</td><td>35964.1526704691</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>-3.28558931742048e-08</td><td>10000.0</td><td>-7.25125242503898e-09</td><td>0.0</td><td>0.0</td><td>468.092</td><td>35889.0000911547</td><td>0.0</td><td>0.0</td><td>26.0002359628895</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.000743738849434001</td><td>1344.55712065055</td><td>7.470076216829e-05</td><td>0.0</td><td>0.0</td><td>40482.8302522678</td><td>0.0</td><td>0.0</td><td>17.1553846153846</td><td>28.452</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>1.00828721431536e-06</td><td>10000.0</td><td>1.02780672367128e-07</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>21.0</td><td>22.23</td><td>34.4866242038217</td><td>0.0</td><td>41131.7280149092</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.000793333411563306</td><td>1260.50403283131</td><td>7.98736454780766e-05</td><td>0.0</td><td>0.0</td><td>35507.6339280402</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>39.8444307566163</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>-2.999702342634e-06</td><td>10000.0</td><td>-2.99093144904199e-07</td><td>0.0185050216442515</td><td>-0.00360784483098134</td><td>1.52831513283897</td><td>0.0222369871350534</td><td>-0.00300797711605981</td><td>1.66721808389264</td><td>-1.01624171562092</td><td>0.0595883068737276</td><td>-9.80757465790094</td><td>-0.976834297180176</td><td>0.325611442327499</td><td>9.50019264221191</td><td>-0.0146607663482428</td><td>0.0109955742955208</td><td>0.182037845253944</td><td>-0.940479813326332</td><td>0.533622621920316</td><td>-10.173900083374</td><td>-0.02840514058222</td><td>0.0133905294115835</td><td>0.18024277943731</td><td>-1.0105720909769</td><td>0.0220502465696756</td><td>-9.9865660976856</td><td>-0.00912061926272279</td><td>-0.00538678413555656</td><td>0.0628600177075434</td></tr>\n",
"<tr><td>36125.0</td><td>48.493979044084</td><td>11.3572577788383</td><td>1824.21553999896</td><td>7226.0</td><td>-0.0566631968557421</td><td>10000.0</td><td>-0.00566404874489389</td><td>15455928.0</td><td>868.0</td><td>1544813113777.0</td><td>26636996.0</td><td>1544813119000.0</td><td>48.4939904026395</td><td>11.3572716133274</td><td>516.568674703383</td><td>0.0</td><td>-0.0670376494526863</td><td>-0.172382518649101</td><td>9.94072532653809</td><td>0.00733038317412138</td><td>-0.0109955742955208</td><td>-0.0207694191485643</td><td>78.9099960327148</td><td>9.0</td><td>4.0</td><td>222.467391967773</td><td>18.0</td><td>828.0</td><td>7.69</td><td>14.5</td><td>-3.0</td><td>36123.3768936482</td><td>36806.60444508</td><td>-1.0019036461657</td><td>466.35949366301</td><td>19.087904</td><td>36123.3768936482</td><td>1825.243</td><td>0.0</td><td>0.0</td><td>7226.0</td><td>-0.0704008546978647</td><td>10000.0</td><td>-0.0070547924360653</td><td>48.4939765</td><td>11.3572661</td><td>512.0</td><td>36007.0</td><td>50.00000148</td><td>-541471227.0</td><td>806.0</td><td>807.0</td><td>69.0</td><td>157.0</td><td>10.0</td><td>519.0</td><td>7.7777781</td><td>9.0</td><td>7.7777781</td><td>10.0</td><td>-1.0</td><td>5.0</td><td>48.0</td><td>1.0</td><td>9.0</td><td>807.0</td><td>807.0</td><td>520.0</td><td>1.0</td><td>230.0</td><td>0.0</td><td>808.0</td><td>148.0</td><td>24.0</td><td>23.0</td><td>24.0</td><td>0.5185185</td><td>804.0</td><td>1826.0</td><td>48.4939904026395</td><td>11.3572716133274</td><td>48.4939904026395</td><td>11.3572716133274</td><td>36123.3768936482</td><td>1.5983965184853</td><td>36015.324485218</td><td>0.0</td><td>0.0</td><td>36123.3768936482</td><td>7226.0</td><td>-0.000658830383402704</td><td>10000.0</td><td>-6.6229359455706e-05</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>5.75</td><td>5.75</td><td>35903.3571428571</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>1.78832586115381e-09</td><td>10000.0</td><td>5.22855530207027e-09</td><td>0.0</td><td>0.0</td><td>0.0</td><td>9.9</td><td>0.0</td><td>0.0</td><td>5196637536.0</td><td>48.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>1.0</td><td>1.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>2.0</td><td>6.12102054494306</td><td>36194.1841446444</td><td>36204.396238292</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>1.77785477098711e-09</td><td>10000.0</td><td>-7.24299628867827e-09</td><td>0.0</td><td>0.0</td><td>3463.22148437651</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>51.95</td><td>0.0</td><td>0.0</td><td>10.0</td><td>0.0</td><td>0.0</td><td>11.1071428571429</td><td>14.4315196998124</td><td>36117.6510146377</td><td>42539.1000000001</td><td>35541.6</td><td>99.99</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>2.52458146740573e-08</td><td>10000.0</td><td>2.80103228088254e-10</td><td>3.0</td><td>0.0</td><td>0.0</td><td>50.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>1.0</td><td>50.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>1.77785477098711e-09</td><td>10000.0</td><td>-7.24299628867827e-09</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>16.7142857142857</td><td>163.428571428571</td><td>33.1071428571429</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.000867682080367725</td><td>1152.49564598648</td><td>8.7278345969678e-05</td><td>-1.91958811501167</td><td>0.0</td><td>0.740781890628238</td><td>1.67</td><td>80.8484080471435</td><td>10.01</td><td>1.0</td><td>1544770823.68012</td><td>1544800852.64115</td><td>48.4939904026395</td><td>11.3572716133274</td><td>36123.3768936482</td><td>1825.243</td><td>7226.0</td><td>-0.0704008546978647</td><td>10000.0</td><td>-0.0070547924360653</td><td>0.0</td><td>0.0</td><td>6.1</td><td>0.0</td><td>0.0</td><td>48.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>1.0</td><td>1.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>2.0</td><td>6.12102054494306</td><td>35961.6761511929</td><td>35970.2124808086</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>-7.76154744078209e-08</td><td>10000.0</td><td>-6.99112598045495e-09</td><td>48.493967</td><td>11.357284</td><td>467.97</td><td>35893.7822086844</td><td>71.766</td><td>8073.0</td><td>32.0026755852843</td><td>2.0</td><td>1822.0</td><td>48.4939904026395</td><td>11.3572716133274</td><td>48.4939905778229</td><td>11.3572719562815</td><td>36123.3449857072</td><td>2.76787334562422</td><td>36123.3768936482</td><td>7226.0</td><td>0.00106303282974866</td><td>940.704580241524</td><td>0.000106650040878573</td><td>0.0</td><td>0.0</td><td>40487.176206669</td><td>0.0</td><td>0.0</td><td>17.1553846153846</td><td>28.452</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>1.38369929966599e-06</td><td>10000.0</td><td>1.36120190947366e-07</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>21.0</td><td>22.23</td><td>34.4866242038217</td><td>0.0</td><td>41136.7866629675</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0013704929741289</td><td>729.664735677926</td><td>0.000137649088572885</td><td>0.0</td><td>0.0</td><td>35510.8591122345</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>39.8444307566163</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>-3.52349827159281e-06</td><td>10000.0</td><td>-3.54098178232812e-07</td><td>0.0266934923842082</td><td>-0.000634134192526544</td><td>1.5294279700708</td><td>0.0198869191420092</td><td>-0.00178874812435793</td><td>1.31332119074227</td><td>-0.855770324184758</td><td>0.111542794653641</td><td>-9.80806018767528</td><td>-0.0670376494526863</td><td>-0.172382518649101</td><td>9.94072532653809</td><td>0.00733038317412138</td><td>-0.0109955742955208</td><td>-0.0207694191485643</td><td>-1.64007271882869</td><td>-0.300028462271993</td><td>-9.88167994761888</td><td>-0.00690800964727605</td><td>-0.00582274878239578</td><td>-0.0228993655516209</td><td>-0.82581224514471</td><td>0.189145552689433</td><td>-10.0225052497104</td><td>-0.00913796876625599</td><td>-0.00645971524083978</td><td>0.0715674259210277</td></tr>\n",
"<tr><td>36130.0</td><td>48.4939694137251</td><td>11.3572322859319</td><td>1829.33621509764</td><td>7227.0</td><td>-0.056623105735224</td><td>10000.0</td><td>-0.00566790533279996</td><td>15456110.0</td><td>868.0</td><td>1544813123714.0</td><td>26646933.0</td><td>1544813129000.0</td><td>48.4939552345631</td><td>11.3572287793272</td><td>516.280680220879</td><td>0.0</td><td>-0.78529816865921</td><td>1.48440504074097</td><td>9.59596061706543</td><td>0.00244346098043025</td><td>0.00366519158706069</td><td>0.0268780700862408</td><td>8.34000015258789</td><td>8.0</td><td>4.0</td><td>222.467391967773</td><td>2.0</td><td>953.0</td><td>13.52</td><td>14.5</td><td>-3.0</td><td>36128.4023150731</td><td>36815.9979171885</td><td>0.0</td><td>466.492992834383</td><td>19.087904</td><td>36128.4023150731</td><td>1835.18</td><td>0.0</td><td>0.0</td><td>7227.0</td><td>-0.0930131572675051</td><td>10000.0</td><td>-0.00942142143901802</td><td>0.0</td><td>0.0</td><td>511.996829328612</td><td>36012.3076923077</td><td>50.00000148</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>157.0</td><td>10.0</td><td>0.0</td><td>7.7777781</td><td>0.0</td><td>7.7777781</td><td>0.0</td><td>-1.0</td><td>5.0</td><td>48.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>36020.5727560715</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>-0.00101243873651327</td><td>10000.0</td><td>-0.000101567129630762</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>5.75</td><td>5.75</td><td>35905.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>1.7005751341119e-07</td><td>10000.0</td><td>9.69548543219796e-09</td><td>0.0</td><td>0.0</td><td>0.0</td><td>9.9</td><td>0.0</td><td>0.0</td><td>5196637536.0</td><td>48.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>1.0</td><td>1.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>2.0</td><td>6.12102054494306</td><td>36200.2422457066</td><td>36210.4560486315</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>-1.04699504943255e-07</td><td>10000.0</td><td>-5.30854712744824e-09</td><td>0.0</td><td>0.0</td><td>3584.01785714443</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>51.95</td><td>0.0</td><td>0.0</td><td>10.0</td><td>0.0</td><td>0.0</td><td>11.1071428571429</td><td>14.4315196998124</td><td>36125.4847078342</td><td>42632.3999999999</td><td>35541.6</td><td>99.99</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>-3.83465653268911e-08</td><td>10000.0</td><td>1.54059471917377e-09</td><td>3.0</td><td>0.0</td><td>0.0</td><td>50.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>1.0</td><td>50.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>-1.04699504943255e-07</td><td>10000.0</td><td>-5.30854712744824e-09</td><td>48.49403</td><td>11.35718</td><td>0.0</td><td>0.0</td><td>16.7142857142857</td><td>166.0</td><td>33.5</td><td>1829.0</td><td>48.4939552345631</td><td>11.3572287793272</td><td>48.493961416713</td><td>11.3572363090598</td><td>36127.5189030374</td><td>8.68185746441715</td><td>36128.4023150731</td><td>7227.0</td><td>0.00139203991245897</td><td>718.370325310476</td><td>0.000139776242855112</td><td>-1.91949136196197</td><td>0.0</td><td>0.740783734856378</td><td>1.67</td><td>80.843130271765</td><td>10.01</td><td>1.0</td><td>1544770823.66496</td><td>1544800852.65324</td><td>48.4939552345631</td><td>11.3572287793272</td><td>36128.4023150731</td><td>1835.18</td><td>7227.0</td><td>-0.0930131572675051</td><td>10000.0</td><td>-0.00942142143901802</td><td>0.0</td><td>0.0</td><td>6.1</td><td>0.0</td><td>0.0</td><td>48.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>1.0</td><td>1.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>2.0</td><td>6.12102054494306</td><td>35967.7342522551</td><td>35976.2722911481</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>1.76112211230816e-08</td><td>10000.0</td><td>-4.29215598620602e-09</td><td>0.0</td><td>0.0</td><td>467.848</td><td>35898.5643262142</td><td>0.0</td><td>0.0</td><td>32.0026755852843</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.00141225674696499</td><td>708.086587807193</td><td>0.000141621060906121</td><td>48.493843</td><td>11.357029</td><td>40491.5221610702</td><td>0.0</td><td>0.0</td><td>17.1553846153846</td><td>28.452</td><td>1823.0</td><td>48.4939552345631</td><td>11.3572287793272</td><td>48.4939552345631</td><td>11.3572287793272</td><td>36128.4023150731</td><td>19.2995105222252</td><td>36128.4023150731</td><td>7227.0</td><td>1.71067334171332e-06</td><td>10000.0</td><td>1.73981971563207e-07</td><td>48.493962</td><td>11.357232</td><td>0.0</td><td>0.0</td><td>21.0</td><td>22.23</td><td>34.4866242038217</td><td>0.0</td><td>41141.8453110259</td><td>1823.0</td><td>48.4939552345631</td><td>11.3572287793272</td><td>48.4939595382721</td><td>11.3572340211569</td><td>36127.7873270401</td><td>0.311626571116366</td><td>36128.4023150731</td><td>7227.0</td><td>0.00201601359782632</td><td>496.028405759663</td><td>0.000202288496097199</td><td>48.4940366768798</td><td>11.3571913926126</td><td>35514.0842964288</td><td>42.6828562567867</td><td>38.1822459249206</td><td>0.234741534167327</td><td>0.667420294042685</td><td>21.1028825101006</td><td>1823.0</td><td>48.4939552345631</td><td>11.3572287793272</td><td>48.4939696925584</td><td>11.3572463888708</td><td>36126.3363076114</td><td>8.47944647818023</td><td>36128.4023150731</td><td>7227.0</td><td>-4.0746749905627e-06</td><td>10000.0</td><td>-4.10506655340407e-07</td><td>0.0353602006330053</td><td>0.00255621501741205</td><td>1.53049768597642</td><td>0.0110456021581722</td><td>-0.00117447070660329</td><td>0.727910960496715</td><td>-0.493339098220102</td><td>0.0799709368291782</td><td>-9.80940156995523</td><td>-0.78529816865921</td><td>1.48440504074097</td><td>9.59596061706543</td><td>0.00244346098043025</td><td>0.00366519158706069</td><td>0.0268780700862408</td><td>0.131526704447494</td><td>0.188029429662826</td><td>-9.82745013233327</td><td>-0.00282923919173314</td><td>-0.00286389035945735</td><td>0.0269374891201572</td><td>-0.566139101113244</td><td>0.188098537061459</td><td>-10.0123742061199</td><td>-0.00563899639867496</td><td>-0.00519217308017079</td><td>0.0494020270730009</td></tr>\n",
"<tr><td>36135.0</td><td>48.4940105661686</td><td>11.3572265430113</td><td>1837.57304569241</td><td>7228.0</td><td>0.0</td><td>10000.0</td><td>0.0</td><td>15456273.0</td><td>868.0</td><td>1544813132761.0</td><td>26655980.0</td><td>1544813138000.0</td><td>48.4940366768798</td><td>11.3571913926126</td><td>515.895603237607</td><td>0.0</td><td>-0.593762040138245</td><td>1.01514148712158</td><td>9.64384460449219</td><td>0.00122173049021512</td><td>0.0</td><td>0.00244346098043025</td><td>0.779999971389771</td><td>8.0</td><td>4.0</td><td>222.467391967773</td><td>18.0</td><td>827.0</td><td>6.99</td><td>14.5</td><td>-3.0</td><td>36138.8908448501</td><td>36820.9930560986</td><td>0.0</td><td>466.669867561766</td><td>19.087904</td><td>36138.8908448501</td><td>1844.227</td><td>0.0</td><td>0.0</td><td>7228.0</td><td>0.0</td><td>10000.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>512.009610431538</td><td>36017.6153846154</td><td>50.00000148</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>157.0</td><td>10.0</td><td>0.0</td><td>7.7777781</td><td>0.0</td><td>7.7777781</td><td>0.0</td><td>-1.0</td><td>5.0</td><td>48.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>36025.821026925</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>10000.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>5.75</td><td>5.75</td><td>35906.6428571429</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>10000.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>9.9</td><td>0.0</td><td>0.0</td><td>5196637536.0</td><td>48.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>1.0</td><td>1.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>2.0</td><td>6.12102054494306</td><td>36206.3003467689</td><td>36216.515858971</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>10000.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>3708.02434895997</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>51.95</td><td>0.0</td><td>0.0</td><td>10.0</td><td>0.0</td><td>0.0</td><td>11.1071428571429</td><td>14.4315196998124</td><td>36133.3184010307</td><td>42725.7</td><td>35541.6</td><td>99.99</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>10000.0</td><td>0.0</td><td>3.0</td><td>0.0</td><td>0.0</td><td>50.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>1.0</td><td>50.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>10000.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>16.7142857142857</td><td>168.571428571429</td><td>33.8928571428571</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>10000.0</td><td>0.0</td><td>-1.91928789617554</td><td>0.0</td><td>0.740787533770754</td><td>1.67</td><td>80.8321122176761</td><td>10.01</td><td>1.0</td><td>1544770823.63332</td><td>1544800852.67849</td><td>48.4940366768798</td><td>11.3571913926126</td><td>36138.8908448501</td><td>1844.227</td><td>7228.0</td><td>0.0</td><td>10000.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>6.1</td><td>0.0</td><td>0.0</td><td>48.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>1.0</td><td>1.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>2.0</td><td>6.12102054494306</td><td>35973.7923533174</td><td>35982.3321014876</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>10000.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>467.726</td><td>35903.346443744</td><td>0.0</td><td>0.0</td><td>32.0026755852843</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>10000.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>40495.8681154714</td><td>0.0</td><td>0.0</td><td>17.1553846153846</td><td>28.452</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>10000.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>21.0</td><td>22.23</td><td>34.4866242038217</td><td>0.0</td><td>41146.9039590842</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>10000.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>35517.3094806231</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>21.1028825101006</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>10000.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>-0.00178927821995634</td><td>-0.000887889115206045</td><td>0.00142472617143394</td><td>-0.0102776659783162</td><td>-0.0117651969430476</td><td>-9.80998429656552</td><td>-0.593762040138245</td><td>1.01514148712158</td><td>9.64384460449219</td><td>0.00122173049021512</td><td>0.0</td><td>0.00244346098043025</td><td>-0.357494815502513</td><td>0.0614930164362291</td><td>-9.89096183747265</td><td>-0.000710413272626475</td><td>-0.0012060015584706</td><td>0.00234606056542644</td><td>-0.264558179693369</td><td>0.0758538572761902</td><td>-9.97173845690303</td><td>0.000238685097183029</td><td>-0.0024982680467088</td><td>0.0071301850944708</td></tr>\n",
"</table></div>"
],
"text/plain": [
"<Table length=7228>\n",
"distance latitude ... rot_Gier_flt_2 rot_Gier_flt_3 \n",
"float64 float64 ... float64 float64 \n",
"-------- ---------------- ... -------------------- -------------------\n",
" 0.0 48.7436851684512 ... 0.00124893632174478 0.00147046360145099\n",
" 5.0 48.743660011792 ... 0.0029062661334533 0.0694993957818311\n",
" 10.0 48.7436454613238 ... 0.00300525107095361 0.103801841905125\n",
" 15.0 48.7436203018653 ... 0.000730703525049424 0.0883675689058716\n",
" 20.0 48.7436491772175 ... -0.00357387413653213 0.0333486709761538\n",
" 25.0 48.7436932112327 ... -0.00851107271491372 -0.0301408279789142\n",
" ... ... ... ... ...\n",
" 36105.0 48.4940887159834 ... 0.00740829081028163 -0.0548438650170325\n",
" 36110.0 48.4940565365702 ... 0.00288670405737579 -0.0195602248573346\n",
" 36115.0 48.4940309552407 ... -0.00194797214075882 0.0269558346376725\n",
" 36120.0 48.4940086969898 ... -0.00538678413555656 0.0628600177075434\n",
" 36125.0 48.493979044084 ... -0.00645971524083978 0.0715674259210277\n",
" 36130.0 48.4939694137251 ... -0.00519217308017079 0.0494020270730009\n",
" 36135.0 48.4940105661686 ... -0.0024982680467088 0.0071301850944708"
]
},
"execution_count": 6,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# Convert to Table\n",
"import sys\n",
"from astropy.table import Table\n",
"t = Table(data, names=DATA_COLUMNS)\n",
"lat = t['latitude']\n",
"lng = t['longitude']\n",
"# Subsampling ... use points every 50m for plotting\n",
"lat = lat[::10]\n",
"lng = lng[::10]\n",
"# determine range to print based on min, max lat and lon of the data\n",
"margin = 0 # buffer to add to the range\n",
"lat_min = min(lat) - margin\n",
"lat_max = max(lat) + margin\n",
"lon_min = min(lng) - margin\n",
"lon_max = max(lng) + margin\n",
"t"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"['distance',\n",
" 'latitude',\n",
" 'longitude',\n",
" 'time',\n",
" 'join_idx',\n",
" 'curvature',\n",
" 'radius',\n",
" 'phiSegment',\n",
" 'flt_DB_counter',\n",
" 'flt_setup_id',\n",
" 'flt_time',\n",
" 'flt_time_system_clock',\n",
" 'flt_time_utc',\n",
" 'flt_latitude',\n",
" 'flt_longitude',\n",
" 'flt_altitude',\n",
" 'flt_gps_speed',\n",
" 'flt_ax',\n",
" 'flt_ay',\n",
" 'flt_az',\n",
" 'flt_gx',\n",
" 'flt_gy',\n",
" 'flt_gz',\n",
" 'flt_compass',\n",
" 'flt_number_of_satelites',\n",
" 'flt_accuracy',\n",
" 'flt_gps_bearing',\n",
" 'flt_obd_engine_load',\n",
" 'flt_obd_engine_rpm',\n",
" 'flt_obd_maf',\n",
" 'flt_obd_accelerator_pedal',\n",
" 'flt_obd_air_temperature',\n",
" 'flt_calc_dist_gps',\n",
" 'flt_calc_dist_vt',\n",
" 'flt_calc_ax_vt',\n",
" 'flt_go_elevation',\n",
" 'flt_go_eleResolution',\n",
" 'flt_distanceIP',\n",
" 'flt_timeIP',\n",
" 'flt_osm_trafficSignal',\n",
" 'flt_osm_w_wood',\n",
" 'flt_join_idx',\n",
" 'flt_curvature',\n",
" 'flt_radius',\n",
" 'flt_phiSegment',\n",
" 'hr_latitude',\n",
" 'hr_longitude',\n",
" 'hr_elevation',\n",
" 'hr_distance',\n",
" 'hr_SpeedLimit',\n",
" 'hr_LinkID',\n",
" 'hr_shapeFirstPoint',\n",
" 'hr_shapeLastPoint',\n",
" 'hr_lengthSegemnt',\n",
" 'hr_remainDistanze',\n",
" 'hr_remainTime',\n",
" 'hr_actualManeuver',\n",
" 'hr_traficSpeed',\n",
" 'hr_traficTime',\n",
" 'hr_baseSpeed',\n",
" 'hr_baseTime',\n",
" 'hr_JamFactor',\n",
" 'hr_FunctionalRoadClass',\n",
" 'hr_consumption',\n",
" 'hr_mTravelTime',\n",
" 'hr_mLenght',\n",
" 'hr_mFirstPoint',\n",
" 'hr_mLastPoint',\n",
" 'hr_mNextManeuver',\n",
" 'hr_mTrafficTime',\n",
" 'hr_mStartAngle',\n",
" 'hr_leg_firtPoint',\n",
" 'hr_leg_lastPoint',\n",
" 'hr_leg_length',\n",
" 'hr_leg_travelTime',\n",
" 'hr_leg_trafficTime',\n",
" 'hr_leg_baseTime',\n",
" 'hr_leg_spot',\n",
" 'hr_leg_shapeIndex',\n",
" 'hr_IdxNP',\n",
" 'hr_NearestPoint_1',\n",
" 'hr_NearestPoint_2',\n",
" 'hr_PointOnRoute_1',\n",
" 'hr_PointOnRoute_2',\n",
" 'hr_Dist2Origin',\n",
" 'hr_Dist2Route',\n",
" 'hr_distance_lldist',\n",
" 'hr_osm_trafficSignal',\n",
" 'hr_osm_w_wood',\n",
" 'hr_distanceIP',\n",
" 'hr_join_idx',\n",
" 'hr_curvature',\n",
" 'hr_radius',\n",
" 'hr_phiSegment',\n",
" 'go_start_latitude',\n",
" 'go_start_longitude',\n",
" 'go_end_latitude',\n",
" 'go_end_longitude',\n",
" 'go_distance',\n",
" 'go_duration',\n",
" 'go_latitude',\n",
" 'go_longitude',\n",
" 'go_routing_flag',\n",
" 'go_mean_velocity_calc_pre',\n",
" 'go_mean_velocity_calc',\n",
" 'go_cum_distance',\n",
" 'go_IdxNP',\n",
" 'go_NearestPoint_1',\n",
" 'go_NearestPoint_2',\n",
" 'go_PointOnRoute_1',\n",
" 'go_PointOnRoute_2',\n",
" 'go_Dist2Origin',\n",
" 'go_Dist2Route',\n",
" 'go_distanceIP',\n",
" 'go_join_idx',\n",
" 'go_curvature',\n",
" 'go_radius',\n",
" 'go_phiSegment',\n",
" 'osrm_latitude',\n",
" 'osrm_longitude',\n",
" 'osrm_seg_datasources',\n",
" 'osrm_seg_weight',\n",
" 'osrm_seg_distance',\n",
" 'osrm_seg_duration',\n",
" 'osrm_seg_nodeID',\n",
" 'osrm_step_weight',\n",
" 'osrm_step_duration',\n",
" 'osrm_step_distance',\n",
" 'osrm_mn_bearing_before',\n",
" 'osrm_mn_bearing_after',\n",
" 'osrm_mn_exit',\n",
" 'osrm_i_lanes_valid_1',\n",
" 'osrm_i_lanes_valid_2',\n",
" 'osrm_i_lanes_valid_3',\n",
" 'osrm_i_lanes_valid_4',\n",
" 'osrm_i_lanes_valid_5',\n",
" 'osrm_i_lanes_valid_6',\n",
" 'osrm_i_bearings_1',\n",
" 'osrm_i_bearings_2',\n",
" 'osrm_i_bearings_3',\n",
" 'osrm_i_bearings_4',\n",
" 'osrm_i_bearings_5',\n",
" 'osrm_i_bearings_6',\n",
" 'osrm_i_entry_1',\n",
" 'osrm_i_entry_2',\n",
" 'osrm_i_entry_3',\n",
" 'osrm_i_entry_4',\n",
" 'osrm_i_entry_5',\n",
" 'osrm_i_entry_6',\n",
" 'osrm_i_in',\n",
" 'osrm_i_out',\n",
" 'osrm_i_laneNumber',\n",
" 'osrm_seg_speed',\n",
" 'osrm_segDistance_lldist',\n",
" 'osrm_seg_cumsumDistance',\n",
" 'osrm_IdxNP',\n",
" 'osrm_NearestPoint_1',\n",
" 'osrm_NearestPoint_2',\n",
" 'osrm_PointOnRoute_1',\n",
" 'osrm_PointOnRoute_2',\n",
" 'osrm_Dist2Origin',\n",
" 'osrm_Dist2Route',\n",
" 'osrm_distanceIP',\n",
" 'osrm_join_idx',\n",
" 'osrm_curvature',\n",
" 'osrm_radius',\n",
" 'osrm_phiSegment',\n",
" 'ors_latitude',\n",
" 'ors_longitude',\n",
" 'ors_elevation',\n",
" 'ors_long_distance',\n",
" 'ors_long_duration',\n",
" 'ors_ascent_route',\n",
" 'ors_descent_route',\n",
" 'ors_detourfactor',\n",
" 'ors_percentage',\n",
" 'ors_avgspeed',\n",
" 'ors_seg_distance',\n",
" 'ors_seg_duration',\n",
" 'ors_type',\n",
" 'ors_maneuver_bearing_before',\n",
" 'ors_maneuver_bearing_after',\n",
" 'ors_seg_speed',\n",
" 'ors_long_speed',\n",
" 'ors_distance_lldist',\n",
" 'ors_seg_distance_cumsum',\n",
" 'ors_long_distance_cumsum',\n",
" 'ors_percentage_cumsum',\n",
" 'ors_IdxNP',\n",
" 'ors_NearestPoint_1',\n",
" 'ors_NearestPoint_2',\n",
" 'ors_PointOnRoute_1',\n",
" 'ors_PointOnRoute_2',\n",
" 'ors_Dist2Origin',\n",
" 'ors_Dist2Route',\n",
" 'ors_distanceIP',\n",
" 'ors_join_idx',\n",
" 'ors_curvature',\n",
" 'ors_radius',\n",
" 'ors_phiSegment',\n",
" 'osm_w_lanes',\n",
" 'osm_w_lanes_forward',\n",
" 'osm_w_lanes_backward',\n",
" 'osm_w_maxspeed',\n",
" 'osm_w_maxspeed_forward',\n",
" 'osm_w_maxspeed_backward',\n",
" 'osm_Node_ID_osrm',\n",
" 'osm_Way_ID',\n",
" 'osm_Way_direction',\n",
" 'osm_Calc_Lanes',\n",
" 'osm_w_maxspeed_new',\n",
" 'osm_latitude',\n",
" 'osm_longitude',\n",
" 'osm_distanceIP',\n",
" 'osm_IdxNP',\n",
" 'osm_NearestPoint_1',\n",
" 'osm_NearestPoint_2',\n",
" 'osm_PointOnRoute_1',\n",
" 'osm_PointOnRoute_2',\n",
" 'osm_Dist2Origin',\n",
" 'osm_Dist2Route',\n",
" 'osm_f_filt',\n",
" 'osm_join_idx',\n",
" 'osm_curvature',\n",
" 'osm_radius',\n",
" 'osm_phiSegment',\n",
" 'tt_latitude',\n",
" 'tt_longitude',\n",
" 'tt_sec_Motorway',\n",
" 'tt_sec_traffic',\n",
" 'tt_calc_speedInKmPerH',\n",
" 'tt_calc_distance',\n",
" 'tt_calc_time',\n",
" 'tt_IdxNP',\n",
" 'tt_NearestPoint_1',\n",
" 'tt_NearestPoint_2',\n",
" 'tt_PointOnRoute_1',\n",
" 'tt_PointOnRoute_2',\n",
" 'tt_Dist2Origin',\n",
" 'tt_Dist2Route',\n",
" 'tt_distanceIP',\n",
" 'tt_join_idx',\n",
" 'tt_curvature',\n",
" 'tt_radius',\n",
" 'tt_phiSegment',\n",
" 'weat_temperature',\n",
" 'weat_precipIntensity',\n",
" 'weat_humidity',\n",
" 'weat_windSpeed',\n",
" 'weat_windBearing',\n",
" 'weat_visibility',\n",
" 'weat_cloudCover',\n",
" 'weat_sunriseTime',\n",
" 'weat_sunsetTime',\n",
" 'weat_latitude',\n",
" 'weat_longitude',\n",
" 'weat_distanceIP',\n",
" 'weat_timeIP',\n",
" 'weat_join_idx',\n",
" 'weat_curvature',\n",
" 'weat_radius',\n",
" 'weat_phiSegment',\n",
" 'mb_latitude',\n",
" 'mb_longitude',\n",
" 'mb_seg_speed',\n",
" 'mb_seg_distance',\n",
" 'mb_seg_duration',\n",
" 'mb_step_weight',\n",
" 'mb_step_duration',\n",
" 'mb_step_distance',\n",
" 'mb_mn_bearing_before',\n",
" 'mb_mn_bearing_after',\n",
" 'mb_mn_exit',\n",
" 'mb_mn_modifier',\n",
" 'mb_i_bearings_1',\n",
" 'mb_i_bearings_2',\n",
" 'mb_i_bearings_3',\n",
" 'mb_i_bearings_4',\n",
" 'mb_i_bearings_5',\n",
" 'mb_i_bearings_6',\n",
" 'mb_i_bearings_7',\n",
" 'mb_i_bearings_8',\n",
" 'mb_i_entry_1',\n",
" 'mb_i_entry_2',\n",
" 'mb_i_entry_3',\n",
" 'mb_i_entry_4',\n",
" 'mb_i_entry_5',\n",
" 'mb_i_entry_6',\n",
" 'mb_i_entry_7',\n",
" 'mb_i_entry_8',\n",
" 'mb_i_in',\n",
" 'mb_i_out',\n",
" 'mb_i_laneNumber',\n",
" 'mb_seg_speed_calc',\n",
" 'mb_segDistance_lldist',\n",
" 'mb_seg_cumsumDistance',\n",
" 'mb_IdxNP',\n",
" 'mb_NearestPoint_1',\n",
" 'mb_NearestPoint_2',\n",
" 'mb_PointOnRoute_1',\n",
" 'mb_PointOnRoute_2',\n",
" 'mb_Dist2Origin',\n",
" 'mb_Dist2Route',\n",
" 'mb_distanceIP',\n",
" 'mb_seg_congestion_calc',\n",
" 'mb_join_idx',\n",
" 'mb_curvature',\n",
" 'mb_radius',\n",
" 'mb_phiSegment',\n",
" 'gh_latitude',\n",
" 'gh_longitude',\n",
" 'gh_elevation',\n",
" 'gh_distance_lldist',\n",
" 'gh_distance',\n",
" 'gh_time',\n",
" 'gh_avgspeed',\n",
" 'gh_sign',\n",
" 'gh_IdxNP',\n",
" 'gh_NearestPoint_1',\n",
" 'gh_NearestPoint_2',\n",
" 'gh_PointOnRoute_1',\n",
" 'gh_PointOnRoute_2',\n",
" 'gh_Dist2Origin',\n",
" 'gh_Dist2Route',\n",
" 'gh_distanceIP',\n",
" 'gh_join_idx',\n",
" 'gh_curvature',\n",
" 'gh_radius',\n",
" 'gh_phiSegment',\n",
" 'mq_latitude',\n",
" 'mq_longitude',\n",
" 'mq_distance_lldist',\n",
" 'mq_distance',\n",
" 'mq_duration',\n",
" 'mq_avgspeed',\n",
" 'mq_avgspeed_leg',\n",
" 'mq_IdxNP',\n",
" 'mq_NearestPoint_1',\n",
" 'mq_NearestPoint_2',\n",
" 'mq_PointOnRoute_1',\n",
" 'mq_PointOnRoute_2',\n",
" 'mq_Dist2Origin',\n",
" 'mq_Dist2Route',\n",
" 'mq_distanceIP',\n",
" 'mq_join_idx',\n",
" 'mq_curvature',\n",
" 'mq_radius',\n",
" 'mq_phiSegment',\n",
" 'bg_latitude',\n",
" 'bg_longitude',\n",
" 'bg_distance',\n",
" 'bg_duration',\n",
" 'bg_avgspeed',\n",
" 'bg_avgspeed_subleg',\n",
" 'bg_avgspeed_leg',\n",
" 'bg_roadShiedType',\n",
" 'bg_distance_lldist',\n",
" 'bg_IdxNP',\n",
" 'bg_NearestPoint_1',\n",
" 'bg_NearestPoint_2',\n",
" 'bg_PointOnRoute_1',\n",
" 'bg_PointOnRoute_2',\n",
" 'bg_Dist2Origin',\n",
" 'bg_Dist2Route',\n",
" 'bg_distanceIP',\n",
" 'bg_join_idx',\n",
" 'bg_curvature',\n",
" 'bg_radius',\n",
" 'bg_phiSegment',\n",
" 'ei_latitude',\n",
" 'ei_longitude',\n",
" 'ei_distance_lldist',\n",
" 'ei_Cumul_Kilometers',\n",
" 'ei_Cumul_TravelTime',\n",
" 'ei_distance',\n",
" 'ei_time',\n",
" 'ei_avgspeed',\n",
" 'ei_IdxNP',\n",
" 'ei_NearestPoint_1',\n",
" 'ei_NearestPoint_2',\n",
" 'ei_PointOnRoute_1',\n",
" 'ei_PointOnRoute_2',\n",
" 'ei_Dist2Origin',\n",
" 'ei_Dist2Route',\n",
" 'ei_distanceIP',\n",
" 'ei_join_idx',\n",
" 'ei_curvature',\n",
" 'ei_radius',\n",
" 'ei_phiSegment',\n",
" 'go_alpha',\n",
" 'hr_alpha',\n",
" 'ors_alpha',\n",
" 'go_alpha_filt',\n",
" 'hr_alpha_filt',\n",
" 'ors_alpha_filt',\n",
" 'hAccel_1',\n",
" 'hAccel_2',\n",
" 'hAccel_3',\n",
" 'flt_mAccel_1',\n",
" 'flt_mAccel_2',\n",
" 'flt_mAccel_3',\n",
" 'flt_mGier_1',\n",
" 'flt_mGier_2',\n",
" 'flt_mGier_3',\n",
" 'rot_Accel_1',\n",
" 'rot_Accel_2',\n",
" 'rot_Accel_3',\n",
" 'rot_Gier_1',\n",
" 'rot_Gier_2',\n",
" 'rot_Gier_3',\n",
" 'rot_Accel_flt_1',\n",
" 'rot_Accel_flt_2',\n",
" 'rot_Accel_flt_3',\n",
" 'rot_Gier_flt_1',\n",
" 'rot_Gier_flt_2',\n",
" 'rot_Gier_flt_3']"
]
},
"execution_count": 7,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"t.colnames"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {},
"outputs": [],
"source": [
"# Calculation ZOOM LEVEL\n",
"width = 640\n",
"height = 640\n",
"tileSize= 256*4\n",
"\n",
"# Converts given lat/lon in WGS84 Datum to XY in Spherical Mercator EPSG:900913\"\n",
"originShift = 2 * math.pi * 6378137/2.0; # 20037508.342789244\n",
"xExtent_min = lon_min * originShift / 180;\n",
"yExtent_min = math.log(math.tan((90 + lat_min) * math.pi / 360 )) / (math.pi / 180);\n",
"yExtent_min = yExtent_min * originShift / 180;\n",
"xExtent_max = lon_max * originShift / 180;\n",
"yExtent_max = math.log(math.tan((90 + lat_max) * math.pi / 360 )) / (math.pi / 180);\n",
"yExtent_max = yExtent_max * originShift / 180;\n",
"\n",
"minResX = (xExtent_max-xExtent_min)/width;\n",
"minResY = (yExtent_max-yExtent_min)/height;\n",
"minRes = max([minResX, minResY]);\n",
"initialResolution = 2 * math.pi * 6378137 / tileSize; # 156543.03392804062 for tileSize 256 pixels\n",
"zoomlevel = math.floor(math.log2(initialResolution/minRes));\n",
"\n",
"# Enforce valid zoom levels\n",
"if zoomlevel < 0:\n",
" zoomlevel = 0\n",
"if zoomlevel > 19: \n",
" zoomlevel = 19"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"'\\nfig = go.Figure(go.Scattermapbox(\\n mode = \"markers+lines+text\",\\n lon = Tab[0][1],\\n lat = Tab[0][0],\\n marker = {\\'size\\': 8, \\'color\\':\\'rgb(180,50,50)\\',\\'opacity\\' : 0.25},\\n text=\\'TomTom HCP3 Routing - route shape\\',\\n name=\\'TomTom HCP3 Routing - route shape\\'\\n ))\\nif Tab[i][3] != 0:\\n fig.add_trace(go.Scattermapbox(\\n mode = \"markers+text\",\\n lon = Tab[0][3],\\n lat = Tab[0][2],\\n marker = {\\'size\\':28,\\'color\\':\\'rgb(0,0,200)\\',\\'opacity\\':0.8},\\n text=\\'TomTom HCP3 Routing - charging station\\',\\n name=\\'TomTom HCP3 Routing - charging station\\'\\n ))\\nfig.add_trace(go.Scattermapbox(\\n mode = \"markers\",\\n lon = [str(lng_d)],\\n lat = [str(lat_d)],\\n marker = {\\'size\\': 25, \\'color\\':\\'rgb(180,50,50)\\',\\'opacity\\' : 0.8},\\n text=\\'TomTom HCP3 Routing - destination\\',\\n name=\\'TomTom HCP3 Routing - destination\\'\\n ))\\nfig.add_trace(go.Scattermapbox(\\n mode = \"markers\",\\n lon = [str(lng_s)],\\n lat = [str(lat_s)],\\n marker = {\\'size\\': 25, \\'color\\':\\'rgb(180,50,50)\\',\\'opacity\\' : 0.8},\\n text=\\'TomTom HCP3 Routing - start\\',\\n name=\\'TomTom HCP3 Routing - start\\'\\n ))\\nif select[\\'TT_360Range\\']:\\n try:\\n fig.add_trace(go.Scattermapbox(\\n mode = \"markers+lines+text\",\\n lon = (dfp_r[\\'longitude\\'].astype(float)),\\n lat = (dfp_r[\\'latitude\\'].astype(float)),\\n marker = {\\'size\\': 8, \\'color\\':\\'rgb(180,50,50)\\',\\'opacity\\' : 0.25},\\n text=\\'TomTom HCP3 Routing - range polygon - raw\\',\\n name=\\'TomTom HCP3 Routing - range polygon - raw\\'\\n ))\\n \\n fig.add_trace(go.Scattermapbox(\\n mode = \"markers+lines+text\",\\n lon = (dfp[\\'longitude\\'].astype(float)),\\n lat = (dfp[\\'latitude\\'].astype(float)),\\n marker = {\\'size\\': 8, \\'color\\':\\'rgb(50,180,50)\\',\\'opacity\\' : 0.25},\\n text=\\'TomTom HCP3 Routing - range polygon - detailed\\',\\n name=\\'TomTom HCP3 Routing - range polygon - detailed\\'\\n ))\\n except:\\n print(\"Error fig RangeOnMap \")\\n pass\\nfig.update_layout(\\n margin ={\\'l\\':0,\\'t\\':0,\\'b\\':0,\\'r\\':0},\\n mapbox = {\\n #\\'center\\': {\\'lon\\': lng_s, \\'lat\\': lat_s},\\n \\'style\\': \"stamen-terrain\",\\n \\'center\\': {\\'lon\\': (lng_d+lng_s)/2, \\'lat\\': (lat_d+lat_s)/2},\\n \\'zoom\\': 6})\\n\\nfig.show()\\n'"
]
},
"execution_count": 9,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"import gmplot \n",
"\n",
"######################################\n",
"### Google Plot ###\n",
"######################################\n",
"apikey = 'AIzaSyClu2yvJQjVAQIqs1v6eSEXSgwUNVeDLZM' # (your API key here)\n",
"\n",
"gmap = gmplot.GoogleMapPlotter((lat[0]+lat[-1])/2,\n",
" (lng[0]+lng[-1])/2,\n",
" 7,\n",
" apikey=apikey) \n",
"\n",
"color = ['#B22222','#1E90FF','#C0C0C0','#008000','#BDB76B','#FF8C00','#7FFFD4','#807673','#B22222','#B22222','#1E90FF','#C0C0C0','#008000','#BDB76B','#FF8C00','#7FFFD4','#807673','#B22222','#B22222','#1E90FF','#C0C0C0','#008000','#BDB76B','#FF8C00','#7FFFD4','#807673','#B22222']\n",
"for i in range(1):#len(SETUP_ID)):\n",
" gmap.plot(\n",
" (lat),\n",
" (lng),\n",
" color=color[i],\n",
" edge_width=12-2*i,\n",
" label=('Setup ID: %d' % (SETUP_ID)),\n",
" alpha=1-(i/10)\n",
" )\n",
"'''\n",
" if Tab[i][3] != 0:\n",
" acc_d = 0\n",
" for j in range(len(Tab[i][2])): # iterate through charging stations\n",
" acc_d = acc_d+Tab[i][18][j]/1000\n",
" gmap.marker(\n",
" (Tab[i][2][j]),\n",
" (Tab[i][3][j]),\n",
" color=color[i],\n",
" label=('%d'%(j+1)),\n",
" info_window=('<div id=\"content\">' + '<div id=\"siteNotice\">' + \"</div>\" + '<h1 id=\"firstHeading\" class=\"firstHeading\">' + ('%d - %s Charging' % (j+1,Tab[i][15])) + '</h1>' + '<div id=\"bodyContent\">' + (\"charging time %.2f [min] <br>arrival energy %.2f [kWh] (%.2f %%)<br>target energy %.2f [kWh] (%.2f %%)<br>calculated power %.2f kW <br>Distance of the leg %.2f [km] <br>Acc distance of legs %.2f [km] <br>Charging Name: %s <br>Charging Info: <br> %s\" % (Tab[i][10][j],Tab[i][11][j],Tab[i][11][j]/par['maxChargeInkWh']*100,Tab[i][12][j],Tab[i][12][j]/par['maxChargeInkWh']*100,Tab[i][13][j],Tab[i][18][j]/1000,acc_d,Tab[i][19][j],Tab[i][20][j])) + \"</div>\" + \"</div>\"),\n",
" marker=True,\n",
" title=('%d - %s charging' % (j+1,Tab[i][15])),\n",
" )\n",
"if select['TT_360Range']:\n",
" try:\n",
" gmap.polygon( \n",
" (dfp_r['latitude'].astype(float)),\n",
" (dfp_r['longitude'].astype(float)),\n",
" face_color='#eb8c34', \n",
" edge_color='#73563c',\n",
" edge_width=7,\n",
" label=\"TomTom 360 Range / RangeOnMap - raw\",\n",
" alpha=0.25\n",
" )\n",
" gmap.polygon( \n",
" (dfp['latitude'].astype(float)),\n",
" (dfp['longitude'].astype(float)),\n",
" face_color='#87CEEB', \n",
" edge_color='#3380B3',\n",
" edge_width=7,\n",
" label=\"TomTom 360 Range / RangeOnMap - detailed\",\n",
" alpha=0.5\n",
" )\n",
" except:\n",
" print(\"Error GMap RangeOnMap \")\n",
" pass\n",
"'''\n",
"gmap.marker(\n",
" lat[0],\n",
" lng[0],\n",
" label='S'\n",
" )\n",
"gmap.marker(\n",
" lat[-1], \n",
" lng[-1],\n",
" label='D'\n",
" )\n",
"\n",
" # Pass the absolute path \n",
" #gmap1.draw( \"C:\\\\Users\\\\user\\\\Desktop\\\\map11.html\" ) \n",
" # Draw the map:\n",
"gmap.draw('Routing_onMap.html')\n",
"\n",
"\n",
"##############################################################################################\n",
"\n",
"\n",
"#df,df2 = TomTom_HCP3_Routing(lat_s,lng_s,lat_d,lng_d,cfg,par)\n",
"#TomTom_HCP3\n",
"'''\n",
"fig = go.Figure(go.Scattermapbox(\n",
" mode = \"markers+lines+text\",\n",
" lon = Tab[0][1],\n",
" lat = Tab[0][0],\n",
" marker = {'size': 8, 'color':'rgb(180,50,50)','opacity' : 0.25},\n",
" text='TomTom HCP3 Routing - route shape',\n",
" name='TomTom HCP3 Routing - route shape'\n",
" ))\n",
"if Tab[i][3] != 0:\n",
" fig.add_trace(go.Scattermapbox(\n",
" mode = \"markers+text\",\n",
" lon = Tab[0][3],\n",
" lat = Tab[0][2],\n",
" marker = {'size':28,'color':'rgb(0,0,200)','opacity':0.8},\n",
" text='TomTom HCP3 Routing - charging station',\n",
" name='TomTom HCP3 Routing - charging station'\n",
" ))\n",
"fig.add_trace(go.Scattermapbox(\n",
" mode = \"markers\",\n",
" lon = [str(lng_d)],\n",
" lat = [str(lat_d)],\n",
" marker = {'size': 25, 'color':'rgb(180,50,50)','opacity' : 0.8},\n",
" text='TomTom HCP3 Routing - destination',\n",
" name='TomTom HCP3 Routing - destination'\n",
" ))\n",
"fig.add_trace(go.Scattermapbox(\n",
" mode = \"markers\",\n",
" lon = [str(lng_s)],\n",
" lat = [str(lat_s)],\n",
" marker = {'size': 25, 'color':'rgb(180,50,50)','opacity' : 0.8},\n",
" text='TomTom HCP3 Routing - start',\n",
" name='TomTom HCP3 Routing - start'\n",
" ))\n",
"if select['TT_360Range']:\n",
" try:\n",
" fig.add_trace(go.Scattermapbox(\n",
" mode = \"markers+lines+text\",\n",
" lon = (dfp_r['longitude'].astype(float)),\n",
" lat = (dfp_r['latitude'].astype(float)),\n",
" marker = {'size': 8, 'color':'rgb(180,50,50)','opacity' : 0.25},\n",
" text='TomTom HCP3 Routing - range polygon - raw',\n",
" name='TomTom HCP3 Routing - range polygon - raw'\n",
" ))\n",
" \n",
" fig.add_trace(go.Scattermapbox(\n",
" mode = \"markers+lines+text\",\n",
" lon = (dfp['longitude'].astype(float)),\n",
" lat = (dfp['latitude'].astype(float)),\n",
" marker = {'size': 8, 'color':'rgb(50,180,50)','opacity' : 0.25},\n",
" text='TomTom HCP3 Routing - range polygon - detailed',\n",
" name='TomTom HCP3 Routing - range polygon - detailed'\n",
" ))\n",
" except:\n",
" print(\"Error fig RangeOnMap \")\n",
" pass\n",
"fig.update_layout(\n",
" margin ={'l':0,'t':0,'b':0,'r':0},\n",
" mapbox = {\n",
" #'center': {'lon': lng_s, 'lat': lat_s},\n",
" 'style': \"stamen-terrain\",\n",
" 'center': {'lon': (lng_d+lng_s)/2, 'lat': (lat_d+lat_s)/2},\n",
" 'zoom': 6})\n",
"\n",
"fig.show()\n",
"'''"
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {},
"outputs": [
{
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n=t(\"./core\");n.register([t(\"./bar\"),t(\"./box\"),t(\"./heatmap\"),t(\"./histogram\"),t(\"./histogram2d\"),t(\"./histogram2dcontour\"),t(\"./contour\"),t(\"./scatterternary\"),t(\"./violin\"),t(\"./funnel\"),t(\"./waterfall\"),t(\"./image\"),t(\"./pie\"),t(\"./sunburst\"),t(\"./treemap\"),t(\"./icicle\"),t(\"./funnelarea\"),t(\"./scatter3d\"),t(\"./surface\"),t(\"./isosurface\"),t(\"./volume\"),t(\"./mesh3d\"),t(\"./cone\"),t(\"./streamtube\"),t(\"./scattergeo\"),t(\"./choropleth\"),t(\"./scattergl\"),t(\"./splom\"),t(\"./pointcloud\"),t(\"./heatmapgl\"),t(\"./parcoords\"),t(\"./parcats\"),t(\"./scattermapbox\"),t(\"./choroplethmapbox\"),t(\"./densitymapbox\"),t(\"./sankey\"),t(\"./indicator\"),t(\"./table\"),t(\"./carpet\"),t(\"./scattercarpet\"),t(\"./contourcarpet\"),t(\"./ohlc\"),t(\"./candlestick\"),t(\"./scatterpolar\"),t(\"./scatterpolargl\"),t(\"./barpolar\"),t(\"./scattersmith\"),t(\"./aggregate\"),t(\"./filter\"),t(\"./groupby\"),t(\"./sort\"),t(\"./calendars\")]),e.exports=n},{\"./aggregate\":2,\"./bar\":3,\"./barpolar\":4,\"./box\":5,\"./calendars\":6,\"./candlestick\":7,\"./carpet\":8,\"./choropleth\":9,\"./choroplethmapbox\":10,\"./cone\":11,\"./contour\":12,\"./contourcarpet\":13,\"./core\":14,\"./densitymapbox\":15,\"./filter\":16,\"./funnel\":17,\"./funnelarea\":18,\"./groupby\":19,\"./heatmap\":20,\"./heatmapgl\":21,\"./histogram\":22,\"./histogram2d\":23,\"./histogram2dcontour\":24,\"./icicle\":25,\"./image\":26,\"./indicator\":28,\"./isosurface\":29,\"./mesh3d\":30,\"./ohlc\":31,\"./parcats\":32,\"./parcoords\":33,\"./pie\":34,\"./pointcloud\":35,\"./sankey\":36,\"./scatter3d\":37,\"./scattercarpet\":38,\"./scattergeo\":39,\"./scattergl\":40,\"./scattermapbox\":41,\"./scatterpolar\":42,\"./scatterpolargl\":43,\"./scattersmith\":44,\"./scatterternary\":45,\"./sort\":46,\"./splom\":47,\"./streamtube\":48,\"./sunburst\":49,\"./surface\":50,\"./table\":51,\"./treemap\":52,\"./violin\":53,\"./volume\":54,\"./waterfall\":55}],28:[function(t,e,r){\"use 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r=L(8/(3*y)),i=e/r;return[t/(r*(1-n(i)/y)),i]},mt.invert=function(t,e){var r=2-n(e)/L(2*y/3);return[t*L(6*y)/(2*r),d(e)*S((4-r*r)/3)]},gt.invert=function(t,e){var r=L(y*(4+y))/2;return[t*r/(1+L(1-e*e*(4+y)/(4*y))),e*r/2]},vt.invert=function(t,e){var r=e*L((4+y)/y)/2,n=S(r),i=o(n);return[t/(2/L(y*(4+y))*(1+i)),S((n+r*(i+2))/(2+x))]},yt.invert=function(t,e){var r=L(2+y),n=e*r/2;return[r*t/(1+o(n)),n]},xt.invert=function(t,e){var r=1+x,n=L(r/2);return[2*t*n/(1+o(e*=n)),S((e+m(e))/r)]};var bt=3+2*w;function _t(t,e){var r=m(t/=2),n=o(t),a=L(o(e)),s=o(e/=2),l=m(e)/(s+w*n*a),u=L(2/(1+l*l)),f=L((w*s+(n+r)*a)/(w*s+(n-r)*a));return[bt*(u*(f-1/f)-2*c(f)),bt*(u*l*(f+1/f)-2*i(l))]}_t.invert=function(t,e){if(!(r=D.invert(t/1.2,1.065*e)))return null;var r,a=r[0],s=r[1],l=20;t/=bt,e/=bt;do{var h=a/2,p=s/2,d=m(h),g=o(h),y=m(p),b=o(p),T=o(s),k=L(T),A=y/(b+w*g*k),M=A*A,S=L(2/(1+M)),E=(w*b+(g+d)*k)/(w*b+(g-d)*k),C=L(E),P=C-1/C,I=C+1/C,O=S*P-2*c(C)-t,z=S*A*I-2*i(A)-e,R=y&&_*k*d*M/y,F=(w*g*b+k)/(2*(b+w*g*k)*(b+w*g*k)*k),B=-.5*A*S*S*S,N=B*R,j=B*F,U=(U=2*b+w*k*(g-d))*U*C,V=(w*g*b*k+T)/U,H=-w*d*y/(k*U),q=P*N-2*V/C+S*(V+V/E),G=P*j-2*H/C+S*(H+H/E),Y=A*I*N-2*R/(1+M)+S*I*R+S*A*(V-V/E),W=A*I*j-2*F/(1+M)+S*I*F+S*A*(H-H/E),X=G*Y-W*q;if(!X)break;var Z=(z*G-O*W)/X,J=(O*Y-z*q)/X;a-=Z,s=u(-x,f(x,s-J))}while((n(Z)>v||n(J)>v)&&--l>0);return n(n(s)-x)<v?[0,s]:l&&[a,s]};var wt=o(35*M);function Tt(t,e){var r=g(e/2);return[t*wt*L(1-r*r),(1+wt)*r]}function kt(t,e){var r=e/2,n=o(r);return[2*t/T*o(e)*n*n,T*g(r)]}function At(t){var e=1-t,r=i(y,0)[0]-i(-y,0)[0],n=L(2*(i(0,x)[1]-i(0,-x)[1])/r);function i(r,n){var i=o(n),a=m(n);return[i/(e+t*i)*r,e*n+t*a]}function a(t,e){var r=i(t,e);return[r[0]*n,r[1]/n]}function s(t){return a(0,t)[1]}return a.invert=function(r,i){var a=V(s,i);return[r/n*(t+e/o(a)),a]},a}function Mt(t){return[t[0]/2,S(g(t[1]/2*M))*A]}function St(t){return[2*t[0],2*i(m(t[1]*M))*A]}function Et(t,r){var i=2*y/r,s=t*t;function l(r,l){var c=e.geoAzimuthalEquidistantRaw(r,l),u=c[0],f=c[1],h=u*u+f*f;if(h>s){var d=L(h),g=a(f,u),b=i*p(g/i),_=g-b,w=t*o(_),T=(t*m(_)-_*m(w))/(x-w),k=Lt(_,T),A=(y-t)/Ct(k,w,y);u=d;var M,S=50;do{u-=M=(t+Ct(k,w,u)*A-d)/(k(u)*A)}while(n(M)>v&&--S>0);f=_*m(u),u<x&&(f-=T*(u-x));var E=m(b),C=o(b);c[0]=u*C-f*E,c[1]=u*E+f*C}return c}return l.invert=function(r,l){var c=r*r+l*l;if(c>s){var u=L(c),f=a(l,r),h=i*p(f/i),d=f-h;r=u*o(d),l=u*m(d);for(var g=r-x,v=m(r),b=l/v,_=r<x?1/0:0,w=10;;){var T=t*m(b),k=t*o(b),A=m(k),M=x-k,S=(T-b*A)/M,E=Lt(b,S);if(n(_)<1e-12||!--w)break;b-=_=(b*v-S*g-l)/(v-2*g*(M*(k+b*T*o(k)-A)-T*(T-b*A))/(M*M))}r=(u=t+Ct(E,k,r)*(y-t)/Ct(E,k,y))*o(f=h+b),l=u*m(f)}return e.geoAzimuthalEquidistantRaw.invert(r,l)},l}function Lt(t,e){return function(r){var n=t*o(r);return r<x&&(n-=e),L(1+n*n)}}function 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float fontSize, charStep, em, align, baseline;\\n\\t\\t\\tuniform vec4 viewport;\\n\\t\\t\\tuniform vec4 color;\\n\\t\\t\\tuniform vec2 atlasSize, atlasDim, scale, translate, positionOffset;\\n\\t\\t\\tvarying vec2 charCoord, charId;\\n\\t\\t\\tvarying float charWidth;\\n\\t\\t\\tvarying vec4 fontColor;\\n\\t\\t\\tvoid main () {\\n\\t\\t\\t\\tvec2 offset = floor(em * (vec2(align + charOffset, baseline)\\n\\t\\t\\t\\t\\t+ vec2(positionOffset.x, -positionOffset.y)))\\n\\t\\t\\t\\t\\t/ (viewport.zw * scale.xy);\\n\\n\\t\\t\\t\\tvec2 position = (position + translate) * scale;\\n\\t\\t\\t\\tposition += offset * scale;\\n\\n\\t\\t\\t\\tcharCoord = position * viewport.zw + viewport.xy;\\n\\n\\t\\t\\t\\tgl_Position = vec4(position * 2. - 1., 0, 1);\\n\\n\\t\\t\\t\\tgl_PointSize = charStep;\\n\\n\\t\\t\\t\\tcharId.x = mod(char, atlasDim.x);\\n\\t\\t\\t\\tcharId.y = floor(char / atlasDim.x);\\n\\n\\t\\t\\t\\tcharWidth = width * em;\\n\\n\\t\\t\\t\\tfontColor = color / 255.;\\n\\t\\t\\t}\",frag:\"\\n\\t\\t\\tprecision highp float;\\n\\t\\t\\tuniform float fontSize, charStep, opacity;\\n\\t\\t\\tuniform vec2 atlasSize;\\n\\t\\t\\tuniform vec4 viewport;\\n\\t\\t\\tuniform sampler2D atlas;\\n\\t\\t\\tvarying vec4 fontColor;\\n\\t\\t\\tvarying vec2 charCoord, charId;\\n\\t\\t\\tvarying float charWidth;\\n\\n\\t\\t\\tfloat lightness(vec4 color) {\\n\\t\\t\\t\\treturn color.r * 0.299 + color.g * 0.587 + color.b * 0.114;\\n\\t\\t\\t}\\n\\n\\t\\t\\tvoid main () {\\n\\t\\t\\t\\tvec2 uv = gl_FragCoord.xy - charCoord + charStep * .5;\\n\\t\\t\\t\\tfloat halfCharStep = floor(charStep * .5 + .5);\\n\\n\\t\\t\\t\\t// invert y and shift by 1px (FF expecially needs that)\\n\\t\\t\\t\\tuv.y = charStep - uv.y;\\n\\n\\t\\t\\t\\t// ignore points outside of character bounding box\\n\\t\\t\\t\\tfloat halfCharWidth = ceil(charWidth * .5);\\n\\t\\t\\t\\tif (floor(uv.x) > halfCharStep + halfCharWidth ||\\n\\t\\t\\t\\t\\tfloor(uv.x) < halfCharStep - halfCharWidth) return;\\n\\n\\t\\t\\t\\tuv += charId * charStep;\\n\\t\\t\\t\\tuv = uv / atlasSize;\\n\\n\\t\\t\\t\\tvec4 color = fontColor;\\n\\t\\t\\t\\tvec4 mask = texture2D(atlas, uv);\\n\\n\\t\\t\\t\\tfloat maskY = lightness(mask);\\n\\t\\t\\t\\t// float colorY = lightness(color);\\n\\t\\t\\t\\tcolor.a *= maskY;\\n\\t\\t\\t\\tcolor.a *= opacity;\\n\\n\\t\\t\\t\\t// color.a += .1;\\n\\n\\t\\t\\t\\t// antialiasing, see yiq color space y-channel formula\\n\\t\\t\\t\\t// color.rgb += (1. - color.rgb) * (1. - mask.rgb);\\n\\n\\t\\t\\t\\tgl_FragColor = color;\\n\\t\\t\\t}\"});return{regl:t,draw:e,atlas:{}}},T.prototype.update=function(t){var e=this;if(\"string\"==typeof t)t={text:t};else if(!t)return;null!=(t=i(t,{position:\"position positions coord coords coordinates\",font:\"font fontFace fontface typeface cssFont css-font family fontFamily\",fontSize:\"fontSize fontsize size font-size\",text:\"text texts chars characters value values symbols\",align:\"align alignment textAlign textbaseline\",baseline:\"baseline textBaseline textbaseline\",direction:\"dir direction textDirection\",color:\"color colour fill fill-color fillColor textColor textcolor\",kerning:\"kerning kern\",range:\"range dataBox\",viewport:\"vp viewport viewBox viewbox viewPort\",opacity:\"opacity alpha transparency visible visibility opaque\",offset:\"offset positionOffset padding shift indent indentation\"},!0)).opacity&&(Array.isArray(t.opacity)?this.opacity=t.opacity.map((function(t){return parseFloat(t)})):this.opacity=parseFloat(t.opacity)),null!=t.viewport&&(this.viewport=f(t.viewport),this.viewportArray=[this.viewport.x,this.viewport.y,this.viewport.width,this.viewport.height]),null==this.viewport&&(this.viewport={x:0,y:0,width:this.gl.drawingBufferWidth,height:this.gl.drawingBufferHeight},this.viewportArray=[this.viewport.x,this.viewport.y,this.viewport.width,this.viewport.height]),null!=t.kerning&&(this.kerning=t.kerning),null!=t.offset&&(\"number\"==typeof t.offset&&(t.offset=[t.offset,0]),this.positionOffset=y(t.offset)),t.direction&&(this.direction=t.direction),t.range&&(this.range=t.range,this.scale=[1/(t.range[2]-t.range[0]),1/(t.range[3]-t.range[1])],this.translate=[-t.range[0],-t.range[1]]),t.scale&&(this.scale=t.scale),t.translate&&(this.translate=t.translate),this.scale||(this.scale=[1/this.viewport.width,1/this.viewport.height]),this.translate||(this.translate=[0,0]),this.font.length||t.font||(t.font=T.baseFontSize+\"px sans-serif\");var r,a=!1,o=!1;if(t.font&&(Array.isArray(t.font)?t.font:[t.font]).forEach((function(t,r){if(\"string\"==typeof t)try{t=n.parse(t)}catch(e){t=n.parse(T.baseFontSize+\"px \"+t)}else t=n.parse(n.stringify(t));var i=n.stringify({size:T.baseFontSize,family:t.family,stretch:_?t.stretch:void 0,variant:t.variant,weight:t.weight,style:t.style}),s=p(t.size),l=Math.round(s[0]*d(s[1]));if(l!==e.fontSize[r]&&(o=!0,e.fontSize[r]=l),!(e.font[r]&&i==e.font[r].baseString||(a=!0,e.font[r]=T.fonts[i],e.font[r]))){var c=t.family.join(\", \"),u=[t.style];t.style!=t.variant&&u.push(t.variant),t.variant!=t.weight&&u.push(t.weight),_&&t.weight!=t.stretch&&u.push(t.stretch),e.font[r]={baseString:i,family:c,weight:t.weight,stretch:t.stretch,style:t.style,variant:t.variant,width:{},kerning:{},metrics:v(c,{origin:\"top\",fontSize:T.baseFontSize,fontStyle:u.join(\" \")})},T.fonts[i]=e.font[r]}})),(a||o)&&this.font.forEach((function(r,i){var a=n.stringify({size:e.fontSize[i],family:r.family,stretch:_?r.stretch:void 0,variant:r.variant,weight:r.weight,style:r.style});if(e.fontAtlas[i]=e.shader.atlas[a],!e.fontAtlas[i]){var o=r.metrics;e.shader.atlas[a]=e.fontAtlas[i]={fontString:a,step:2*Math.ceil(e.fontSize[i]*o.bottom*.5),em:e.fontSize[i],cols:0,rows:0,height:0,width:0,chars:[],ids:{},texture:e.regl.texture()}}null==t.text&&(t.text=e.text)})),\"string\"==typeof t.text&&t.position&&t.position.length>2){for(var s=Array(.5*t.position.length),h=0;h<s.length;h++)s[h]=t.text;t.text=s}if(null!=t.text||a){if(this.textOffsets=[0],Array.isArray(t.text)){this.count=t.text[0].length,this.counts=[this.count];for(var b=1;b<t.text.length;b++)this.textOffsets[b]=this.textOffsets[b-1]+t.text[b-1].length,this.count+=t.text[b].length,this.counts.push(t.text[b].length);this.text=t.text.join(\"\")}else this.text=t.text,this.count=this.text.length,this.counts=[this.count];r=[],this.font.forEach((function(t,n){T.atlasContext.font=t.baseString;for(var i=e.fontAtlas[n],a=0;a<e.text.length;a++){var o=e.text.charAt(a);if(null==i.ids[o]&&(i.ids[o]=i.chars.length,i.chars.push(o),r.push(o)),null==t.width[o]&&(t.width[o]=T.atlasContext.measureText(o).width/T.baseFontSize,e.kerning)){var s=[];for(var l in t.width)s.push(l+o,o+l);g(t.kerning,m(t.family,{pairs:s}))}}}))}if(t.position)if(t.position.length>2){for(var w=!t.position[0].length,k=u.mallocFloat(2*this.count),A=0,M=0;A<this.counts.length;A++){var S=this.counts[A];if(w)for(var E=0;E<S;E++)k[M++]=t.position[2*A],k[M++]=t.position[2*A+1];else for(var L=0;L<S;L++)k[M++]=t.position[A][0],k[M++]=t.position[A][1]}this.position.call?this.position({type:\"float\",data:k}):this.position=this.regl.buffer({type:\"float\",data:k}),u.freeFloat(k)}else this.position.destroy&&this.position.destroy(),this.position={constant:t.position};if(t.text||a){var C=u.mallocUint8(this.count),P=u.mallocFloat(2*this.count);this.textWidth=[];for(var I=0,O=0;I<this.counts.length;I++){for(var z=this.counts[I],D=this.font[I]||this.font[0],R=this.fontAtlas[I]||this.fontAtlas[0],F=0;F<z;F++){var B=this.text.charAt(O),N=this.text.charAt(O-1);if(C[O]=R.ids[B],P[2*O]=D.width[B],F){var j=P[2*O-2],U=P[2*O],V=P[2*O-1]+.5*j+.5*U;if(this.kerning){var H=D.kerning[N+B];H&&(V+=.001*H)}P[2*O+1]=V}else P[2*O+1]=.5*P[2*O];O++}this.textWidth.push(P.length?.5*P[2*O-2]+P[2*O-1]:0)}t.align||(t.align=this.align),this.charBuffer({data:C,type:\"uint8\",usage:\"stream\"}),this.sizeBuffer({data:P,type:\"float\",usage:\"stream\"}),u.freeUint8(C),u.freeFloat(P),r.length&&this.font.forEach((function(t,r){var n=e.fontAtlas[r],i=n.step,a=Math.floor(T.maxAtlasSize/i),o=Math.min(a,n.chars.length),s=Math.ceil(n.chars.length/o),l=x(o*i),u=x(s*i);n.width=l,n.height=u,n.rows=s,n.cols=o,n.em&&n.texture({data:c({canvas:T.atlasCanvas,font:n.fontString,chars:n.chars,shape:[l,u],step:[i,i]})})}))}if(t.align&&(this.align=t.align,this.alignOffset=this.textWidth.map((function(t,r){var n=Array.isArray(e.align)?e.align.length>1?e.align[r]:e.align[0]:e.align;if(\"number\"==typeof n)return n;switch(n){case\"right\":case\"end\":return-t;case\"center\":case\"centre\":case\"middle\":return.5*-t}return 0}))),null==this.baseline&&null==t.baseline&&(t.baseline=0),null!=t.baseline&&(this.baseline=t.baseline,Array.isArray(this.baseline)||(this.baseline=[this.baseline]),this.baselineOffset=this.baseline.map((function(t,r){var n=(e.font[r]||e.font[0]).metrics,i=0;return i+=.5*n.bottom,i+=\"number\"==typeof t?t-n.baseline:-n[t],i*=-1}))),null!=t.color)if(t.color||(t.color=\"transparent\"),\"string\"!=typeof t.color&&isNaN(t.color)){var q;if(\"number\"==typeof t.color[0]&&t.color.length>this.counts.length){var G=t.color.length;q=u.mallocUint8(G);for(var Y=(t.color.subarray||t.color.slice).bind(t.color),W=0;W<G;W+=4)q.set(l(Y(W,W+4),\"uint8\"),W)}else{var X=t.color.length;q=u.mallocUint8(4*X);for(var Z=0;Z<X;Z++)q.set(l(t.color[Z]||0,\"uint8\"),4*Z)}this.color=q}else this.color=l(t.color,\"uint8\");if(t.position||t.text||t.color||t.baseline||t.align||t.font||t.offset||t.opacity)if(this.color.length>4||this.baselineOffset.length>1||this.align&&this.align.length>1||this.fontAtlas.length>1||this.positionOffset.length>2){var J=Math.max(.5*this.position.length||0,.25*this.color.length||0,this.baselineOffset.length||0,this.alignOffset.length||0,this.font.length||0,this.opacity.length||0,.5*this.positionOffset.length||0);this.batch=Array(J);for(var K=0;K<this.batch.length;K++)this.batch[K]={count:this.counts.length>1?this.counts[K]:this.counts[0],offset:this.textOffsets.length>1?this.textOffsets[K]:this.textOffsets[0],color:this.color?this.color.length<=4?this.color:this.color.subarray(4*K,4*K+4):[0,0,0,255],opacity:Array.isArray(this.opacity)?this.opacity[K]:this.opacity,baseline:null!=this.baselineOffset[K]?this.baselineOffset[K]:this.baselineOffset[0],align:this.align?null!=this.alignOffset[K]?this.alignOffset[K]:this.alignOffset[0]:0,atlas:this.fontAtlas[K]||this.fontAtlas[0],positionOffset:this.positionOffset.length>2?this.positionOffset.subarray(2*K,2*K+2):this.positionOffset}}else this.count?this.batch=[{count:this.count,offset:0,color:this.color||[0,0,0,255],opacity:Array.isArray(this.opacity)?this.opacity[0]:this.opacity,baseline:this.baselineOffset[0],align:this.alignOffset?this.alignOffset[0]:0,atlas:this.fontAtlas[0],positionOffset:this.positionOffset}]:this.batch=[]},T.prototype.destroy=function(){},T.prototype.kerning=!0,T.prototype.position={constant:new Float32Array(2)},T.prototype.translate=null,T.prototype.scale=null,T.prototype.font=null,T.prototype.text=\"\",T.prototype.positionOffset=[0,0],T.prototype.opacity=1,T.prototype.color=new Uint8Array([0,0,0,255]),T.prototype.alignOffset=[0,0],T.maxAtlasSize=1024,T.atlasCanvas=document.createElement(\"canvas\"),T.atlasContext=T.atlasCanvas.getContext(\"2d\",{alpha:!1}),T.baseFontSize=64,T.fonts={},e.exports=T},{\"bit-twiddle\":81,\"color-normalize\":89,\"css-font\":99,\"detect-kerning\":125,\"es6-weak-map\":183,\"flatten-vertex-data\":191,\"font-atlas\":192,\"font-measure\":193,\"gl-util/context\":226,\"is-plain-obj\":236,\"object-assign\":247,\"parse-rect\":249,\"parse-unit\":251,\"pick-by-alias\":253,regl:283,\"to-px\":314,\"typedarray-pool\":327}],226:[function(t,e,r){(function(r){(function(){\"use strict\";var n=t(\"pick-by-alias\");function i(t){if(t.container)if(t.container==document.body)document.body.style.width||(t.canvas.width=t.width||t.pixelRatio*r.innerWidth),document.body.style.height||(t.canvas.height=t.height||t.pixelRatio*r.innerHeight);else{var 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r=e.parse(t[1],1,Bt);if(!r)return null;var n=[],i=null;e.expectedType&&\"value\"!==e.expectedType.kind&&(i=e.expectedType);for(var a=1;a<t.length;a+=2){var o=1===a?-1/0:t[a],s=t[a+1],l=a,c=a+1;if(\"number\"!=typeof o)return e.error('Input/output pairs for \"step\" expressions must be defined using literal numeric values (not computed expressions) for the input values.',l);if(n.length&&n[n.length-1][0]>=o)return e.error('Input/output pairs for \"step\" expressions must be arranged with input values in strictly ascending order.',l);var u=e.parse(s,c,i);if(!u)return null;i=i||u.type,n.push([o,u])}return new He(i,r,n)},He.prototype.evaluate=function(t){var e=this.labels,r=this.outputs;if(1===e.length)return r[0].evaluate(t);var n=this.input.evaluate(t);if(n<=e[0])return r[0].evaluate(t);var i=e.length;return n>=e[i-1]?r[i-1].evaluate(t):r[Ve(e,n)].evaluate(t)},He.prototype.eachChild=function(t){t(this.input);for(var e=0,r=this.outputs;e<r.length;e+=1){t(r[e])}},He.prototype.outputDefined=function(){return this.outputs.every((function(t){return t.outputDefined()}))},He.prototype.serialize=function(){for(var t=[\"step\",this.input.serialize()],e=0;e<this.labels.length;e++)e>0&&t.push(this.labels[e]),t.push(this.outputs[e].serialize());return t};var Ge=Object.freeze({__proto__:null,number:qe,color:function(t,e,r){return new te(qe(t.r,e.r,r),qe(t.g,e.g,r),qe(t.b,e.b,r),qe(t.a,e.a,r))},array:function(t,e,r){return t.map((function(t,n){return qe(t,e[n],r)}))}}),Ye=6/29,We=3*Ye*Ye,Xe=Math.PI/180,Ze=180/Math.PI;function Je(t){return t>.008856451679035631?Math.pow(t,1/3):t/We+4/29}function Ke(t){return t>Ye?t*t*t:We*(t-4/29)}function Qe(t){return 255*(t<=.0031308?12.92*t:1.055*Math.pow(t,1/2.4)-.055)}function $e(t){return(t/=255)<=.04045?t/12.92:Math.pow((t+.055)/1.055,2.4)}function tr(t){var e=$e(t.r),r=$e(t.g),n=$e(t.b),i=Je((.4124564*e+.3575761*r+.1804375*n)/.95047),a=Je((.2126729*e+.7151522*r+.072175*n)/1);return{l:116*a-16,a:500*(i-a),b:200*(a-Je((.0193339*e+.119192*r+.9503041*n)/1.08883)),alpha:t.a}}function er(t){var e=(t.l+16)/116,r=isNaN(t.a)?e:e+t.a/500,n=isNaN(t.b)?e:e-t.b/200;return e=1*Ke(e),r=.95047*Ke(r),n=1.08883*Ke(n),new te(Qe(3.2404542*r-1.5371385*e-.4985314*n),Qe(-.969266*r+1.8760108*e+.041556*n),Qe(.0556434*r-.2040259*e+1.0572252*n),t.alpha)}function rr(t,e,r){var n=e-t;return t+r*(n>180||n<-180?n-360*Math.round(n/360):n)}var nr={forward:tr,reverse:er,interpolate:function(t,e,r){return{l:qe(t.l,e.l,r),a:qe(t.a,e.a,r),b:qe(t.b,e.b,r),alpha:qe(t.alpha,e.alpha,r)}}},ir={forward:function(t){var e=tr(t),r=e.l,n=e.a,i=e.b,a=Math.atan2(i,n)*Ze;return{h:a<0?a+360:a,c:Math.sqrt(n*n+i*i),l:r,alpha:t.a}},reverse:function(t){var e=t.h*Xe,r=t.c;return er({l:t.l,a:Math.cos(e)*r,b:Math.sin(e)*r,alpha:t.alpha})},interpolate:function(t,e,r){return{h:rr(t.h,e.h,r),c:qe(t.c,e.c,r),l:qe(t.l,e.l,r),alpha:qe(t.alpha,e.alpha,r)}}},ar=Object.freeze({__proto__:null,lab:nr,hcl:ir}),or=function(t,e,r,n,i){this.type=t,this.operator=e,this.interpolation=r,this.input=n,this.labels=[],this.outputs=[];for(var a=0,o=i;a<o.length;a+=1){var s=o[a],l=s[0],c=s[1];this.labels.push(l),this.outputs.push(c)}};function sr(t,e,r,n){var i=n-r,a=t-r;return 0===i?0:1===e?a/i:(Math.pow(e,a)-1)/(Math.pow(e,i)-1)}or.interpolationFactor=function(t,e,n,i){var a=0;if(\"exponential\"===t.name)a=sr(e,t.base,n,i);else if(\"linear\"===t.name)a=sr(e,1,n,i);else if(\"cubic-bezier\"===t.name){var o=t.controlPoints;a=new r(o[0],o[1],o[2],o[3]).solve(sr(e,1,n,i))}return a},or.parse=function(t,e){var r=t[0],n=t[1],i=t[2],a=t.slice(3);if(!Array.isArray(n)||0===n.length)return e.error(\"Expected an interpolation type expression.\",1);if(\"linear\"===n[0])n={name:\"linear\"};else if(\"exponential\"===n[0]){var o=n[1];if(\"number\"!=typeof o)return e.error(\"Exponential interpolation requires a numeric base.\",1,1);n={name:\"exponential\",base:o}}else{if(\"cubic-bezier\"!==n[0])return e.error(\"Unknown interpolation type \"+String(n[0]),1,0);var s=n.slice(1);if(4!==s.length||s.some((function(t){return\"number\"!=typeof t||t<0||t>1})))return e.error(\"Cubic bezier interpolation requires four numeric arguments with values between 0 and 1.\",1);n={name:\"cubic-bezier\",controlPoints:s}}if(t.length-1<4)return e.error(\"Expected at least 4 arguments, but found only \"+(t.length-1)+\".\");if((t.length-1)%2!=0)return e.error(\"Expected an even number of arguments.\");if(!(i=e.parse(i,2,Bt)))return null;var l=[],c=null;\"interpolate-hcl\"===r||\"interpolate-lab\"===r?c=Ut:e.expectedType&&\"value\"!==e.expectedType.kind&&(c=e.expectedType);for(var u=0;u<a.length;u+=2){var f=a[u],h=a[u+1],p=u+3,d=u+4;if(\"number\"!=typeof f)return e.error('Input/output pairs for 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a=Ve(e,n),o=e[a],s=e[a+1],l=or.interpolationFactor(this.interpolation,n,o,s),c=r[a].evaluate(t),u=r[a+1].evaluate(t);return\"interpolate\"===this.operator?Ge[this.type.kind.toLowerCase()](c,u,l):\"interpolate-hcl\"===this.operator?ir.reverse(ir.interpolate(ir.forward(c),ir.forward(u),l)):nr.reverse(nr.interpolate(nr.forward(c),nr.forward(u),l))},or.prototype.eachChild=function(t){t(this.input);for(var e=0,r=this.outputs;e<r.length;e+=1){t(r[e])}},or.prototype.outputDefined=function(){return this.outputs.every((function(t){return t.outputDefined()}))},or.prototype.serialize=function(){var t;t=\"linear\"===this.interpolation.name?[\"linear\"]:\"exponential\"===this.interpolation.name?1===this.interpolation.base?[\"linear\"]:[\"exponential\",this.interpolation.base]:[\"cubic-bezier\"].concat(this.interpolation.controlPoints);for(var e=[this.operator,t,this.input.serialize()],r=0;r<this.labels.length;r++)e.push(this.labels[r],this.outputs[r].serialize());return e};var lr=function(t,e){this.type=t,this.args=e};lr.parse=function(t,e){if(t.length<2)return e.error(\"Expectected at least one argument.\");var r=null,n=e.expectedType;n&&\"value\"!==n.kind&&(r=n);for(var i=[],a=0,o=t.slice(1);a<o.length;a+=1){var s=o[a],l=e.parse(s,1+i.length,r,void 0,{typeAnnotation:\"omit\"});if(!l)return null;r=r||l.type,i.push(l)}var c=n&&i.some((function(t){return Jt(n,t.type)}));return new lr(c?Ht:r,i)},lr.prototype.evaluate=function(t){for(var e,r=null,n=0,i=0,a=this.args;i<a.length;i+=1){if(n++,(r=a[i].evaluate(t))&&r instanceof ie&&!r.available&&(e||(e=r.name),r=null,n===this.args.length&&(r=e)),null!==r)break}return r},lr.prototype.eachChild=function(t){this.args.forEach(t)},lr.prototype.outputDefined=function(){return this.args.every((function(t){return t.outputDefined()}))},lr.prototype.serialize=function(){var t=[\"coalesce\"];return this.eachChild((function(e){t.push(e.serialize())})),t};var cr=function(t,e){this.type=e.type,this.bindings=[].concat(t),this.result=e};cr.prototype.evaluate=function(t){return this.result.evaluate(t)},cr.prototype.eachChild=function(t){for(var e=0,r=this.bindings;e<r.length;e+=1){t(r[e][1])}t(this.result)},cr.parse=function(t,e){if(t.length<4)return e.error(\"Expected at least 3 arguments, but found \"+(t.length-1)+\" instead.\");for(var r=[],n=1;n<t.length-1;n+=2){var i=t[n];if(\"string\"!=typeof i)return e.error(\"Expected string, but found \"+typeof i+\" instead.\",n);if(/[^a-zA-Z0-9_]/.test(i))return e.error(\"Variable names must contain only alphanumeric characters or '_'.\",n);var a=e.parse(t[n+1],n+1);if(!a)return null;r.push([i,a])}var o=e.parse(t[t.length-1],t.length-1,e.expectedType,r);return o?new cr(r,o):null},cr.prototype.outputDefined=function(){return this.result.outputDefined()},cr.prototype.serialize=function(){for(var t=[\"let\"],e=0,r=this.bindings;e<r.length;e+=1){var n=r[e],i=n[0],a=n[1];t.push(i,a.serialize())}return t.push(this.result.serialize()),t};var ur=function(t,e,r){this.type=t,this.index=e,this.input=r};ur.parse=function(t,e){if(3!==t.length)return e.error(\"Expected 2 arguments, but found \"+(t.length-1)+\" instead.\");var r=e.parse(t[1],1,Bt),n=e.parse(t[2],2,Wt(e.expectedType||Ht));if(!r||!n)return null;var i=n.type;return new ur(i.itemType,r,n)},ur.prototype.evaluate=function(t){var e=this.index.evaluate(t),r=this.input.evaluate(t);if(e<0)throw new ue(\"Array index out of bounds: \"+e+\" < 0.\");if(e>=r.length)throw new ue(\"Array index out of bounds: \"+e+\" > \"+(r.length-1)+\".\");if(e!==Math.floor(e))throw new ue(\"Array index must be an integer, but found \"+e+\" instead.\");return r[e]},ur.prototype.eachChild=function(t){t(this.index),t(this.input)},ur.prototype.outputDefined=function(){return!1},ur.prototype.serialize=function(){return[\"at\",this.index.serialize(),this.input.serialize()]};var fr=function(t,e){this.type=jt,this.needle=t,this.haystack=e};fr.parse=function(t,e){if(3!==t.length)return e.error(\"Expected 2 arguments, but found \"+(t.length-1)+\" instead.\");var r=e.parse(t[1],1,Ht),n=e.parse(t[2],2,Ht);return r&&n?Kt(r.type,[jt,Nt,Bt,Ft,Ht])?new fr(r,n):e.error(\"Expected first argument to be of type boolean, string, number or null, but found \"+Xt(r.type)+\" instead\"):null},fr.prototype.evaluate=function(t){var e=this.needle.evaluate(t),r=this.haystack.evaluate(t);if(!r)return!1;if(!Qt(e,[\"boolean\",\"string\",\"number\",\"null\"]))throw new ue(\"Expected first argument to be of type boolean, string, number or null, but found \"+Xt(se(e))+\" instead.\");if(!Qt(r,[\"string\",\"array\"]))throw new ue(\"Expected second argument to be of type array or string, but found \"+Xt(se(r))+\" instead.\");return r.indexOf(e)>=0},fr.prototype.eachChild=function(t){t(this.needle),t(this.haystack)},fr.prototype.outputDefined=function(){return!0},fr.prototype.serialize=function(){return[\"in\",this.needle.serialize(),this.haystack.serialize()]};var hr=function(t,e,r){this.type=Bt,this.needle=t,this.haystack=e,this.fromIndex=r};hr.parse=function(t,e){if(t.length<=2||t.length>=5)return e.error(\"Expected 3 or 4 arguments, but found \"+(t.length-1)+\" instead.\");var r=e.parse(t[1],1,Ht),n=e.parse(t[2],2,Ht);if(!r||!n)return null;if(!Kt(r.type,[jt,Nt,Bt,Ft,Ht]))return e.error(\"Expected first argument to be of type boolean, string, number or null, but found \"+Xt(r.type)+\" instead\");if(4===t.length){var i=e.parse(t[3],3,Bt);return i?new hr(r,n,i):null}return new hr(r,n)},hr.prototype.evaluate=function(t){var e=this.needle.evaluate(t),r=this.haystack.evaluate(t);if(!Qt(e,[\"boolean\",\"string\",\"number\",\"null\"]))throw new ue(\"Expected first argument to be of type boolean, string, number or null, but found \"+Xt(se(e))+\" instead.\");if(!Qt(r,[\"string\",\"array\"]))throw new ue(\"Expected second argument to be of type array or string, but found \"+Xt(se(r))+\" instead.\");if(this.fromIndex){var n=this.fromIndex.evaluate(t);return r.indexOf(e,n)}return r.indexOf(e)},hr.prototype.eachChild=function(t){t(this.needle),t(this.haystack),this.fromIndex&&t(this.fromIndex)},hr.prototype.outputDefined=function(){return!1},hr.prototype.serialize=function(){if(null!=this.fromIndex&&void 0!==this.fromIndex){var t=this.fromIndex.serialize();return[\"index-of\",this.needle.serialize(),this.haystack.serialize(),t]}return[\"index-of\",this.needle.serialize(),this.haystack.serialize()]};var pr=function(t,e,r,n,i,a){this.inputType=t,this.type=e,this.input=r,this.cases=n,this.outputs=i,this.otherwise=a};pr.parse=function(t,e){if(t.length<5)return e.error(\"Expected at least 4 arguments, but found only \"+(t.length-1)+\".\");if(t.length%2!=1)return e.error(\"Expected an even number of 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m?\"value\"!==d.type.kind&&e.concat(1).checkSubtype(r,d.type)?null:new pr(r,n,d,i,a,m):null},pr.prototype.evaluate=function(t){var e=this.input.evaluate(t);return(se(e)===this.inputType&&this.outputs[this.cases[e]]||this.otherwise).evaluate(t)},pr.prototype.eachChild=function(t){t(this.input),this.outputs.forEach(t),t(this.otherwise)},pr.prototype.outputDefined=function(){return this.outputs.every((function(t){return t.outputDefined()}))&&this.otherwise.outputDefined()},pr.prototype.serialize=function(){for(var t=this,e=[\"match\",this.input.serialize()],r=[],n={},i=0,a=Object.keys(this.cases).sort();i<a.length;i+=1){var o=a[i];void 0===(f=n[this.cases[o]])?(n[this.cases[o]]=r.length,r.push([this.cases[o],[o]])):r[f][1].push(o)}for(var s=function(e){return\"number\"===t.inputType.kind?Number(e):e},l=0,c=r;l<c.length;l+=1){var u=c[l],f=u[0],h=u[1];1===h.length?e.push(s(h[0])):e.push(h.map(s)),e.push(this.outputs[outputIndex$1].serialize())}return e.push(this.otherwise.serialize()),e};var dr=function(t,e,r){this.type=t,this.branches=e,this.otherwise=r};dr.parse=function(t,e){if(t.length<4)return e.error(\"Expected at least 3 arguments, but found only \"+(t.length-1)+\".\");if(t.length%2!=0)return e.error(\"Expected an odd number of arguments.\");var r;e.expectedType&&\"value\"!==e.expectedType.kind&&(r=e.expectedType);for(var n=[],i=1;i<t.length-1;i+=2){var a=e.parse(t[i],i,jt);if(!a)return null;var o=e.parse(t[i+1],i+1,r);if(!o)return null;n.push([a,o]),r=r||o.type}var s=e.parse(t[t.length-1],t.length-1,r);return s?new dr(r,n,s):null},dr.prototype.evaluate=function(t){for(var e=0,r=this.branches;e<r.length;e+=1){var n=r[e],i=n[0],a=n[1];if(i.evaluate(t))return a.evaluate(t)}return this.otherwise.evaluate(t)},dr.prototype.eachChild=function(t){for(var e=0,r=this.branches;e<r.length;e+=1){var n=r[e],i=n[0],a=n[1];t(i),t(a)}t(this.otherwise)},dr.prototype.outputDefined=function(){return this.branches.every((function(t){t[0];return 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or?a.interpolation:void 0;return Ir(new Zr(n?\"camera\":\"composite\",t.value,a.labels,o))}Zr.prototype.evaluateWithoutErrorHandling=function(t,e,r,n,i,a){return this._styleExpression.evaluateWithoutErrorHandling(t,e,r,n,i,a)},Zr.prototype.evaluate=function(t,e,r,n,i,a){return this._styleExpression.evaluate(t,e,r,n,i,a)},Zr.prototype.interpolationFactor=function(t,e,r){return this.interpolationType?or.interpolationFactor(this.interpolationType,t,e,r):0};var Kr=function(t,e){this._parameters=t,this._specification=e,It(this,function t(e,r){var n,i,a,o=\"color\"===r.type,s=e.stops&&\"object\"==typeof e.stops[0][0],l=s||void 0!==e.property,c=s||!l,u=e.type||(Rr(r)?\"exponential\":\"interval\");if(o&&((e=It({},e)).stops&&(e.stops=e.stops.map((function(t){return[t[0],te.parse(t[1])]}))),e.default?e.default=te.parse(e.default):e.default=te.parse(r.default)),e.colorSpace&&\"rgb\"!==e.colorSpace&&!ar[e.colorSpace])throw new Error(\"Unknown color space: 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n&&r<n.minimum?[new Ct(e,r,r+\" is less than the minimum value \"+n.minimum)]:\"maximum\"in n&&r>n.maximum?[new Ct(e,r,r+\" is greater than the maximum value \"+n.maximum)]:[]}function en(t){var e,r,n,i=t.valueSpec,a=Ot(t.value.type),o={},s=\"categorical\"!==a&&void 0===t.value.property,l=!s,c=\"array\"===Fr(t.value.stops)&&\"array\"===Fr(t.value.stops[0])&&\"object\"===Fr(t.value.stops[0][0]),u=Qr({key:t.key,value:t.value,valueSpec:t.styleSpec.function,style:t.style,styleSpec:t.styleSpec,objectElementValidators:{stops:function(t){if(\"identity\"===a)return[new Ct(t.key,t.value,'identity function may not have a \"stops\" property')];var e=[],r=t.value;e=e.concat($r({key:t.key,value:r,valueSpec:t.valueSpec,style:t.style,styleSpec:t.styleSpec,arrayElementValidator:f})),\"array\"===Fr(r)&&0===r.length&&e.push(new Ct(t.key,r,\"array must have at least one stop\"));return e},default:function(t){return kn({key:t.key,value:t.value,valueSpec:i,style:t.style,styleSpec:t.styleSpec})}}});return\"identity\"===a&&s&&u.push(new Ct(t.key,t.value,'missing required property \"property\"')),\"identity\"===a||t.value.stops||u.push(new Ct(t.key,t.value,'missing required property \"stops\"')),\"exponential\"===a&&t.valueSpec.expression&&!Rr(t.valueSpec)&&u.push(new Ct(t.key,t.value,\"exponential functions not supported\")),t.styleSpec.$version>=8&&(l&&!zr(t.valueSpec)?u.push(new Ct(t.key,t.value,\"property functions not supported\")):s&&!Dr(t.valueSpec)&&u.push(new Ct(t.key,t.value,\"zoom functions not supported\"))),\"categorical\"!==a&&!c||void 0!==t.value.property||u.push(new Ct(t.key,t.value,'\"property\" property is required')),u;function f(t){var e=[],a=t.value,s=t.key;if(\"array\"!==Fr(a))return[new Ct(s,a,\"array expected, \"+Fr(a)+\" found\")];if(2!==a.length)return[new Ct(s,a,\"array length 2 expected, length \"+a.length+\" found\")];if(c){if(\"object\"!==Fr(a[0]))return[new Ct(s,a,\"object expected, \"+Fr(a[0])+\" found\")];if(void 0===a[0].zoom)return[new Ct(s,a,\"object stop key must have zoom\")];if(void 0===a[0].value)return[new Ct(s,a,\"object stop key must have value\")];if(n&&n>Ot(a[0].zoom))return[new Ct(s,a[0].zoom,\"stop zoom values must appear in ascending order\")];Ot(a[0].zoom)!==n&&(n=Ot(a[0].zoom),r=void 0,o={}),e=e.concat(Qr({key:s+\"[0]\",value:a[0],valueSpec:{zoom:{}},style:t.style,styleSpec:t.styleSpec,objectElementValidators:{zoom:tn,value:h}}))}else e=e.concat(h({key:s+\"[0]\",value:a[0],valueSpec:{},style:t.style,styleSpec:t.styleSpec},a));return Yr(zt(a[1]))?e.concat([new Ct(s+\"[1]\",a[1],\"expressions are not allowed in function stops.\")]):e.concat(kn({key:s+\"[1]\",value:a[1],valueSpec:i,style:t.style,styleSpec:t.styleSpec}))}function h(t,n){var s=Fr(t.value),l=Ot(t.value),c=null!==t.value?t.value:n;if(e){if(s!==e)return[new Ct(t.key,c,s+\" stop domain type must match previous stop domain type \"+e)]}else e=s;if(\"number\"!==s&&\"string\"!==s&&\"boolean\"!==s)return[new Ct(t.key,c,\"stop domain value must be a number, string, or boolean\")];if(\"number\"!==s&&\"categorical\"!==a){var u=\"number expected, \"+s+\" found\";return zr(i)&&void 0===a&&(u+='\\nIf you intended to use a categorical function, specify `\"type\": \"categorical\"`.'),[new Ct(t.key,c,u)]}return\"categorical\"!==a||\"number\"!==s||isFinite(l)&&Math.floor(l)===l?\"categorical\"!==a&&\"number\"===s&&void 0!==r&&l<r?[new Ct(t.key,c,\"stop domain values must appear in ascending order\")]:(r=l,\"categorical\"===a&&l in o?[new Ct(t.key,c,\"stop domain values must be unique\")]:(o[l]=!0,[])):[new Ct(t.key,c,\"integer expected, found \"+l)]}}function rn(t){var e=(\"property\"===t.expressionContext?Jr:Wr)(zt(t.value),t.valueSpec);if(\"error\"===e.result)return e.value.map((function(e){return new Ct(\"\"+t.key+e.key,t.value,e.message)}));var r=e.value.expression||e.value._styleExpression.expression;if(\"property\"===t.expressionContext&&\"text-font\"===t.propertyKey&&!r.outputDefined())return[new Ct(t.key,t.value,'Invalid data expression for \"'+t.propertyKey+'\". Output values must be contained as literals within the expression.')];if(\"property\"===t.expressionContext&&\"layout\"===t.propertyType&&!Be(r))return[new Ct(t.key,t.value,'\"feature-state\" data expressions are not supported with layout properties.')];if(\"filter\"===t.expressionContext&&!Be(r))return[new Ct(t.key,t.value,'\"feature-state\" data expressions are not supported with filters.')];if(t.expressionContext&&0===t.expressionContext.indexOf(\"cluster\")){if(!Ne(r,[\"zoom\",\"feature-state\"]))return[new Ct(t.key,t.value,'\"zoom\" and \"feature-state\" expressions are not supported with cluster properties.')];if(\"cluster-initial\"===t.expressionContext&&!Fe(r))return[new Ct(t.key,t.value,\"Feature data expressions are not supported with initial expression part of cluster properties.\")]}return[]}function nn(t){var e=t.key,r=t.value,n=t.valueSpec,i=[];return Array.isArray(n.values)?-1===n.values.indexOf(Ot(r))&&i.push(new Ct(e,r,\"expected one of [\"+n.values.join(\", \")+\"], 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on={type:\"boolean\",default:!1,transition:!1,\"property-type\":\"data-driven\",expression:{interpolated:!1,parameters:[\"zoom\",\"feature\"]}};function sn(t){if(null==t)return{filter:function(){return!0},needGeometry:!1};an(t)||(t=cn(t));var e=Wr(t,on);if(\"error\"===e.result)throw new Error(e.value.map((function(t){return t.key+\": \"+t.message})).join(\", \"));return{filter:function(t,r,n){return e.value.evaluate(t,r,{},n)},needGeometry:function t(e){if(!Array.isArray(e))return!1;if(\"within\"===e[0])return!0;for(var r=1;r<e.length;r++)if(t(e[r]))return!0;return!1}(t)}}function ln(t,e){return t<e?-1:t>e?1:0}function cn(t){if(!t)return!0;var e,r=t[0];return t.length<=1?\"any\"!==r:\"==\"===r?un(t[1],t[2],\"==\"):\"!=\"===r?pn(un(t[1],t[2],\"==\")):\"<\"===r||\">\"===r||\"<=\"===r||\">=\"===r?un(t[1],t[2],r):\"any\"===r?(e=t.slice(1),[\"any\"].concat(e.map(cn))):\"all\"===r?[\"all\"].concat(t.slice(1).map(cn)):\"none\"===r?[\"all\"].concat(t.slice(1).map(cn).map(pn)):\"in\"===r?fn(t[1],t.slice(2)):\"!in\"===r?pn(fn(t[1],t.slice(2))):\"has\"===r?hn(t[1]):\"!has\"===r?pn(hn(t[1])):\"within\"!==r||t}function un(t,e,r){switch(t){case\"$type\":return[\"filter-type-\"+r,e];case\"$id\":return[\"filter-id-\"+r,e];default:return[\"filter-\"+r,t,e]}}function fn(t,e){if(0===e.length)return!1;switch(t){case\"$type\":return[\"filter-type-in\",[\"literal\",e]];case\"$id\":return[\"filter-id-in\",[\"literal\",e]];default:return e.length>200&&!e.some((function(t){return typeof t!=typeof e[0]}))?[\"filter-in-large\",t,[\"literal\",e.sort(ln)]]:[\"filter-in-small\",t,[\"literal\",e]]}}function hn(t){switch(t){case\"$type\":return!0;case\"$id\":return[\"filter-has-id\"];default:return[\"filter-has\",t]}}function pn(t){return[\"!\",t]}function dn(t){return an(zt(t.value))?rn(It({},t,{expressionContext:\"filter\",valueSpec:{value:\"boolean\"}})):function t(e){var r=e.value,n=e.key;if(\"array\"!==Fr(r))return[new Ct(n,r,\"array expected, \"+Fr(r)+\" found\")];var i,a=e.styleSpec,o=[];if(r.length<1)return[new Ct(n,r,\"filter array must have at least 1 element\")];switch(o=o.concat(nn({key:n+\"[0]\",value:r[0],valueSpec:a.filter_operator,style:e.style,styleSpec:e.styleSpec})),Ot(r[0])){case\"<\":case\"<=\":case\">\":case\">=\":r.length>=2&&\"$type\"===Ot(r[1])&&o.push(new Ct(n,r,'\"$type\" cannot be use with operator \"'+r[0]+'\"'));case\"==\":case\"!=\":3!==r.length&&o.push(new Ct(n,r,'filter array for operator \"'+r[0]+'\" must have 3 elements'));case\"in\":case\"!in\":r.length>=2&&\"string\"!==(i=Fr(r[1]))&&o.push(new Ct(n+\"[1]\",r[1],\"string expected, \"+i+\" 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r=t.key,n=t.style,i=t.styleSpec,a=t.value,o=t.objectKey,s=i[e+\"_\"+t.layerType];if(!s)return[];var l=o.match(/^(.*)-transition$/);if(\"paint\"===e&&l&&s[l[1]]&&s[l[1]].transition)return kn({key:r,value:a,valueSpec:i.transition,style:n,styleSpec:i});var c,u=t.valueSpec||s[o];if(!u)return[new Ct(r,a,'unknown property \"'+o+'\"')];if(\"string\"===Fr(a)&&zr(u)&&!u.tokens&&(c=/^{([^}]+)}$/.exec(a)))return[new Ct(r,a,'\"'+o+'\" does not support interpolation syntax\\nUse an identity property function instead: `{ \"type\": \"identity\", \"property\": '+JSON.stringify(c[1])+\" }`.\")];var f=[];return\"symbol\"===t.layerType&&(\"text-field\"===o&&n&&!n.glyphs&&f.push(new Ct(r,a,'use of \"text-field\" requires a style \"glyphs\" property')),\"text-font\"===o&&Br(zt(a))&&\"identity\"===Ot(a.type)&&f.push(new Ct(r,a,'\"text-font\" does not support identity 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null!=hi.applyArabicShaping&&null!=hi.processBidirectionalText&&null!=hi.processStyledBidirectionalText},getPluginURL:function(){return oi}},pi=function(t,e){this.zoom=t,e?(this.now=e.now,this.fadeDuration=e.fadeDuration,this.zoomHistory=e.zoomHistory,this.transition=e.transition):(this.now=0,this.fadeDuration=0,this.zoomHistory=new Gn,this.transition={})};pi.prototype.isSupportedScript=function(t){return function(t,e){for(var r=0,n=t;r<n.length;r+=1){if(!Qn(n[r].charCodeAt(0),e))return!1}return!0}(t,hi.isLoaded())},pi.prototype.crossFadingFactor=function(){return 0===this.fadeDuration?1:Math.min((this.now-this.zoomHistory.lastIntegerZoomTime)/this.fadeDuration,1)},pi.prototype.getCrossfadeParameters=function(){var t=this.zoom,e=t-Math.floor(t),r=this.crossFadingFactor();return t>this.zoomHistory.lastIntegerZoom?{fromScale:2,toScale:1,t:e+(1-e)*r}:{fromScale:.5,toScale:1,t:1-(1-r)*e}};var di=function(t,e){this.property=t,this.value=e,this.expression=function(t,e){if(Br(t))return new Kr(t,e);if(Yr(t)){var r=Jr(t,e);if(\"error\"===r.result)throw new Error(r.value.map((function(t){return t.key+\": \"+t.message})).join(\", \"));return r.value}var n=t;return\"string\"==typeof t&&\"color\"===e.type&&(n=te.parse(t)),{kind:\"constant\",evaluate:function(){return n}}}(void 0===e?t.specification.default:e,t.specification)};di.prototype.isDataDriven=function(){return\"source\"===this.expression.kind||\"composite\"===this.expression.kind},di.prototype.possiblyEvaluate=function(t,e,r){return this.property.possiblyEvaluate(this,t,e,r)};var mi=function(t){this.property=t,this.value=new di(t,void 0)};mi.prototype.transitioned=function(t,e){return new vi(this.property,this.value,e,u({},t.transition,this.transition),t.now)},mi.prototype.untransitioned=function(){return new vi(this.property,this.value,null,{},0)};var gi=function(t){this._properties=t,this._values=Object.create(t.defaultTransitionablePropertyValues)};gi.prototype.getValue=function(t){return x(this._values[t].value.value)},gi.prototype.setValue=function(t,e){this._values.hasOwnProperty(t)||(this._values[t]=new mi(this._values[t].property)),this._values[t].value=new di(this._values[t].property,null===e?void 0:x(e))},gi.prototype.getTransition=function(t){return x(this._values[t].transition)},gi.prototype.setTransition=function(t,e){this._values.hasOwnProperty(t)||(this._values[t]=new mi(this._values[t].property)),this._values[t].transition=x(e)||void 0},gi.prototype.serialize=function(){for(var t={},e=0,r=Object.keys(this._values);e<r.length;e+=1){var n=r[e],i=this.getValue(n);void 0!==i&&(t[n]=i);var a=this.getTransition(n);void 0!==a&&(t[n+\"-transition\"]=a)}return t},gi.prototype.transitioned=function(t,e){for(var r=new yi(this._properties),n=0,i=Object.keys(this._values);n<i.length;n+=1){var a=i[n];r._values[a]=this._values[a].transitioned(t,e._values[a])}return r},gi.prototype.untransitioned=function(){for(var t=new yi(this._properties),e=0,r=Object.keys(this._values);e<r.length;e+=1){var n=r[e];t._values[n]=this._values[n].untransitioned()}return t};var vi=function(t,e,r,n,i){this.property=t,this.value=e,this.begin=i+n.delay||0,this.end=this.begin+n.duration||0,t.specification.transition&&(n.delay||n.duration)&&(this.prior=r)};vi.prototype.possiblyEvaluate=function(t,e,r){var n=t.now||0,i=this.value.possiblyEvaluate(t,e,r),a=this.prior;if(a){if(n>this.end)return this.prior=null,i;if(this.value.isDataDriven())return this.prior=null,i;if(n<this.begin)return a.possiblyEvaluate(t,e,r);var o=(n-this.begin)/(this.end-this.begin);return this.property.interpolate(a.possiblyEvaluate(t,e,r),i,function(t){if(t<=0)return 0;if(t>=1)return 1;var e=t*t,r=e*t;return 4*(t<.5?r:3*(t-e)+r-.75)}(o))}return i};var yi=function(t){this._properties=t,this._values=Object.create(t.defaultTransitioningPropertyValues)};yi.prototype.possiblyEvaluate=function(t,e,r){for(var n=new _i(this._properties),i=0,a=Object.keys(this._values);i<a.length;i+=1){var o=a[i];n._values[o]=this._values[o].possiblyEvaluate(t,e,r)}return n},yi.prototype.hasTransition=function(){for(var t=0,e=Object.keys(this._values);t<e.length;t+=1){var r=e[t];if(this._values[r].prior)return!0}return!1};var xi=function(t){this._properties=t,this._values=Object.create(t.defaultPropertyValues)};xi.prototype.getValue=function(t){return x(this._values[t].value)},xi.prototype.setValue=function(t,e){this._values[t]=new di(this._values[t].property,null===e?void 0:x(e))},xi.prototype.serialize=function(){for(var t={},e=0,r=Object.keys(this._values);e<r.length;e+=1){var n=r[e],i=this.getValue(n);void 0!==i&&(t[n]=i)}return t},xi.prototype.possiblyEvaluate=function(t,e,r){for(var n=new _i(this._properties),i=0,a=Object.keys(this._values);i<a.length;i+=1){var o=a[i];n._values[o]=this._values[o].possiblyEvaluate(t,e,r)}return n};var bi=function(t,e,r){this.property=t,this.value=e,this.parameters=r};bi.prototype.isConstant=function(){return\"constant\"===this.value.kind},bi.prototype.constantOr=function(t){return\"constant\"===this.value.kind?this.value.value:t},bi.prototype.evaluate=function(t,e,r,n){return this.property.evaluate(this.value,this.parameters,t,e,r,n)};var _i=function(t){this._properties=t,this._values=Object.create(t.defaultPossiblyEvaluatedValues)};_i.prototype.get=function(t){return this._values[t]};var wi=function(t){this.specification=t};wi.prototype.possiblyEvaluate=function(t,e){return t.expression.evaluate(e)},wi.prototype.interpolate=function(t,e,r){var n=Ge[this.specification.type];return n?n(t,e,r):t};var Ti=function(t,e){this.specification=t,this.overrides=e};Ti.prototype.possiblyEvaluate=function(t,e,r,n){return\"constant\"===t.expression.kind||\"camera\"===t.expression.kind?new bi(this,{kind:\"constant\",value:t.expression.evaluate(e,null,{},r,n)},e):new bi(this,t.expression,e)},Ti.prototype.interpolate=function(t,e,r){if(\"constant\"!==t.value.kind||\"constant\"!==e.value.kind)return t;if(void 0===t.value.value||void 0===e.value.value)return new bi(this,{kind:\"constant\",value:void 0},t.parameters);var n=Ge[this.specification.type];return n?new bi(this,{kind:\"constant\",value:n(t.value.value,e.value.value,r)},t.parameters):t},Ti.prototype.evaluate=function(t,e,r,n,i,a){return\"constant\"===t.kind?t.value:t.evaluate(e,r,n,i,a)};var ki=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.possiblyEvaluate=function(t,e,r,n){if(void 0===t.value)return new bi(this,{kind:\"constant\",value:void 0},e);if(\"constant\"===t.expression.kind){var i=t.expression.evaluate(e,null,{},r,n),a=\"resolvedImage\"===t.property.specification.type&&\"string\"!=typeof i?i.name:i,o=this._calculate(a,a,a,e);return new bi(this,{kind:\"constant\",value:o},e)}if(\"camera\"===t.expression.kind){var s=this._calculate(t.expression.evaluate({zoom:e.zoom-1}),t.expression.evaluate({zoom:e.zoom}),t.expression.evaluate({zoom:e.zoom+1}),e);return new bi(this,{kind:\"constant\",value:s},e)}return new bi(this,t.expression,e)},e.prototype.evaluate=function(t,e,r,n,i,a){if(\"source\"===t.kind){var o=t.evaluate(e,r,n,i,a);return this._calculate(o,o,o,e)}return\"composite\"===t.kind?this._calculate(t.evaluate({zoom:Math.floor(e.zoom)-1},r,n),t.evaluate({zoom:Math.floor(e.zoom)},r,n),t.evaluate({zoom:Math.floor(e.zoom)+1},r,n),e):t.value},e.prototype._calculate=function(t,e,r,n){return n.zoom>n.zoomHistory.lastIntegerZoom?{from:t,to:e}:{from:r,to:e}},e.prototype.interpolate=function(t){return t},e}(Ti),Ai=function(t){this.specification=t};Ai.prototype.possiblyEvaluate=function(t,e,r,n){if(void 0!==t.value){if(\"constant\"===t.expression.kind){var i=t.expression.evaluate(e,null,{},r,n);return this._calculate(i,i,i,e)}return this._calculate(t.expression.evaluate(new pi(Math.floor(e.zoom-1),e)),t.expression.evaluate(new pi(Math.floor(e.zoom),e)),t.expression.evaluate(new pi(Math.floor(e.zoom+1),e)),e)}},Ai.prototype._calculate=function(t,e,r,n){return n.zoom>n.zoomHistory.lastIntegerZoom?{from:t,to:e}:{from:r,to:e}},Ai.prototype.interpolate=function(t){return t};var Mi=function(t){this.specification=t};Mi.prototype.possiblyEvaluate=function(t,e,r,n){return!!t.expression.evaluate(e,null,{},r,n)},Mi.prototype.interpolate=function(){return!1};var Si=function(t){for(var e in this.properties=t,this.defaultPropertyValues={},this.defaultTransitionablePropertyValues={},this.defaultTransitioningPropertyValues={},this.defaultPossiblyEvaluatedValues={},this.overridableProperties=[],t){var r=t[e];r.specification.overridable&&this.overridableProperties.push(e);var n=this.defaultPropertyValues[e]=new di(r,void 0),i=this.defaultTransitionablePropertyValues[e]=new mi(r);this.defaultTransitioningPropertyValues[e]=i.untransitioned(),this.defaultPossiblyEvaluatedValues[e]=n.possiblyEvaluate({})}};Nn(\"DataDrivenProperty\",Ti),Nn(\"DataConstantProperty\",wi),Nn(\"CrossFadedDataDrivenProperty\",ki),Nn(\"CrossFadedProperty\",Ai),Nn(\"ColorRampProperty\",Mi);var Ei=function(t){function e(e,r){if(t.call(this),this.id=e.id,this.type=e.type,this._featureFilter={filter:function(){return!0},needGeometry:!1},\"custom\"!==e.type&&(e=e,this.metadata=e.metadata,this.minzoom=e.minzoom,this.maxzoom=e.maxzoom,\"background\"!==e.type&&(this.source=e.source,this.sourceLayer=e[\"source-layer\"],this.filter=e.filter),r.layout&&(this._unevaluatedLayout=new xi(r.layout)),r.paint)){for(var n in this._transitionablePaint=new gi(r.paint),e.paint)this.setPaintProperty(n,e.paint[n],{validate:!1});for(var i in e.layout)this.setLayoutProperty(i,e.layout[i],{validate:!1});this._transitioningPaint=this._transitionablePaint.untransitioned(),this.paint=new _i(r.paint)}}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.getCrossfadeParameters=function(){return this._crossfadeParameters},e.prototype.getLayoutProperty=function(t){return\"visibility\"===t?this.visibility:this._unevaluatedLayout.getValue(t)},e.prototype.setLayoutProperty=function(t,e,r){if(void 0===r&&(r={}),null!=e){var n=\"layers.\"+this.id+\".layout.\"+t;if(this._validate(In,n,t,e,r))return}\"visibility\"!==t?this._unevaluatedLayout.setValue(t,e):this.visibility=e},e.prototype.getPaintProperty=function(t){return g(t,\"-transition\")?this._transitionablePaint.getTransition(t.slice(0,-\"-transition\".length)):this._transitionablePaint.getValue(t)},e.prototype.setPaintProperty=function(t,e,r){if(void 0===r&&(r={}),null!=e){var n=\"layers.\"+this.id+\".paint.\"+t;if(this._validate(Pn,n,t,e,r))return!1}if(g(t,\"-transition\"))return this._transitionablePaint.setTransition(t.slice(0,-\"-transition\".length),e||void 0),!1;var i=this._transitionablePaint._values[t],a=\"cross-faded-data-driven\"===i.property.specification[\"property-type\"],o=i.value.isDataDriven(),s=i.value;this._transitionablePaint.setValue(t,e),this._handleSpecialPaintPropertyUpdate(t);var l=this._transitionablePaint._values[t].value;return l.isDataDriven()||o||a||this._handleOverridablePaintPropertyUpdate(t,s,l)},e.prototype._handleSpecialPaintPropertyUpdate=function(t){},e.prototype._handleOverridablePaintPropertyUpdate=function(t,e,r){return!1},e.prototype.isHidden=function(t){return!!(this.minzoom&&t<this.minzoom)||(!!(this.maxzoom&&t>=this.maxzoom)||\"none\"===this.visibility)},e.prototype.updateTransitions=function(t){this._transitioningPaint=this._transitionablePaint.transitioned(t,this._transitioningPaint)},e.prototype.hasTransition=function(){return this._transitioningPaint.hasTransition()},e.prototype.recalculate=function(t,e){t.getCrossfadeParameters&&(this._crossfadeParameters=t.getCrossfadeParameters()),this._unevaluatedLayout&&(this.layout=this._unevaluatedLayout.possiblyEvaluate(t,void 0,e)),this.paint=this._transitioningPaint.possiblyEvaluate(t,void 0,e)},e.prototype.serialize=function(){var t={id:this.id,type:this.type,source:this.source,\"source-layer\":this.sourceLayer,metadata:this.metadata,minzoom:this.minzoom,maxzoom:this.maxzoom,filter:this.filter,layout:this._unevaluatedLayout&&this._unevaluatedLayout.serialize(),paint:this._transitionablePaint&&this._transitionablePaint.serialize()};return this.visibility&&(t.layout=t.layout||{},t.layout.visibility=this.visibility),y(t,(function(t,e){return!(void 0===t||\"layout\"===e&&!Object.keys(t).length||\"paint\"===e&&!Object.keys(t).length)}))},e.prototype._validate=function(t,e,r,n,i){return void 0===i&&(i={}),(!i||!1!==i.validate)&&On(this,t.call(Ln,{key:e,layerType:this.type,objectKey:r,value:n,styleSpec:Lt,style:{glyphs:!0,sprite:!0}}))},e.prototype.is3D=function(){return!1},e.prototype.isTileClipped=function(){return!1},e.prototype.hasOffscreenPass=function(){return!1},e.prototype.resize=function(){},e.prototype.isStateDependent=function(){for(var t in this.paint._values){var e=this.paint.get(t);if(e instanceof bi&&zr(e.property.specification)&&((\"source\"===e.value.kind||\"composite\"===e.value.kind)&&e.value.isStateDependent))return!0}return!1},e}(Et),Li={Int8:Int8Array,Uint8:Uint8Array,Int16:Int16Array,Uint16:Uint16Array,Int32:Int32Array,Uint32:Uint32Array,Float32:Float32Array},Ci=function(t,e){this._structArray=t,this._pos1=e*this.size,this._pos2=this._pos1/2,this._pos4=this._pos1/4,this._pos8=this._pos1/8},Pi=function(){this.isTransferred=!1,this.capacity=-1,this.resize(0)};function Ii(t,e){void 0===e&&(e=1);var r=0,n=0;return{members:t.map((function(t){var i,a=(i=t.type,Li[i].BYTES_PER_ELEMENT),o=r=Oi(r,Math.max(e,a)),s=t.components||1;return n=Math.max(n,a),r+=a*s,{name:t.name,type:t.type,components:s,offset:o}})),size:Oi(r,Math.max(n,e)),alignment:e}}function Oi(t,e){return Math.ceil(t/e)*e}Pi.serialize=function(t,e){return t._trim(),e&&(t.isTransferred=!0,e.push(t.arrayBuffer)),{length:t.length,arrayBuffer:t.arrayBuffer}},Pi.deserialize=function(t){var e=Object.create(this.prototype);return e.arrayBuffer=t.arrayBuffer,e.length=t.length,e.capacity=t.arrayBuffer.byteLength/e.bytesPerElement,e._refreshViews(),e},Pi.prototype._trim=function(){this.length!==this.capacity&&(this.capacity=this.length,this.arrayBuffer=this.arrayBuffer.slice(0,this.length*this.bytesPerElement),this._refreshViews())},Pi.prototype.clear=function(){this.length=0},Pi.prototype.resize=function(t){this.reserve(t),this.length=t},Pi.prototype.reserve=function(t){if(t>this.capacity){this.capacity=Math.max(t,Math.floor(5*this.capacity),128),this.arrayBuffer=new ArrayBuffer(this.capacity*this.bytesPerElement);var e=this.uint8;this._refreshViews(),e&&this.uint8.set(e)}},Pi.prototype._refreshViews=function(){throw new Error(\"_refreshViews() must be implemented by each concrete StructArray layout\")};var zi=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.int16=new Int16Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e){var r=this.length;return this.resize(r+1),this.emplace(r,t,e)},e.prototype.emplace=function(t,e,r){var n=2*t;return this.int16[n+0]=e,this.int16[n+1]=r,t},e}(Pi);zi.prototype.bytesPerElement=4,Nn(\"StructArrayLayout2i4\",zi);var Di=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.int16=new Int16Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e,r,n){var i=this.length;return this.resize(i+1),this.emplace(i,t,e,r,n)},e.prototype.emplace=function(t,e,r,n,i){var a=4*t;return this.int16[a+0]=e,this.int16[a+1]=r,this.int16[a+2]=n,this.int16[a+3]=i,t},e}(Pi);Di.prototype.bytesPerElement=8,Nn(\"StructArrayLayout4i8\",Di);var Ri=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.int16=new Int16Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e,r,n,i,a){var o=this.length;return this.resize(o+1),this.emplace(o,t,e,r,n,i,a)},e.prototype.emplace=function(t,e,r,n,i,a,o){var s=6*t;return this.int16[s+0]=e,this.int16[s+1]=r,this.int16[s+2]=n,this.int16[s+3]=i,this.int16[s+4]=a,this.int16[s+5]=o,t},e}(Pi);Ri.prototype.bytesPerElement=12,Nn(\"StructArrayLayout2i4i12\",Ri);var Fi=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.int16=new Int16Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e,r,n,i,a){var o=this.length;return this.resize(o+1),this.emplace(o,t,e,r,n,i,a)},e.prototype.emplace=function(t,e,r,n,i,a,o){var s=4*t,l=8*t;return this.int16[s+0]=e,this.int16[s+1]=r,this.uint8[l+4]=n,this.uint8[l+5]=i,this.uint8[l+6]=a,this.uint8[l+7]=o,t},e}(Pi);Fi.prototype.bytesPerElement=8,Nn(\"StructArrayLayout2i4ub8\",Fi);var Bi=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.uint16=new Uint16Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e,r,n,i,a,o,s,l,c){var u=this.length;return this.resize(u+1),this.emplace(u,t,e,r,n,i,a,o,s,l,c)},e.prototype.emplace=function(t,e,r,n,i,a,o,s,l,c,u){var f=9*t,h=18*t;return this.uint16[f+0]=e,this.uint16[f+1]=r,this.uint16[f+2]=n,this.uint16[f+3]=i,this.uint16[f+4]=a,this.uint16[f+5]=o,this.uint16[f+6]=s,this.uint16[f+7]=l,this.uint8[h+16]=c,this.uint8[h+17]=u,t},e}(Pi);Bi.prototype.bytesPerElement=18,Nn(\"StructArrayLayout8ui2ub18\",Bi);var Ni=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.int16=new Int16Array(this.arrayBuffer),this.uint16=new Uint16Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e,r,n,i,a,o,s,l,c,u,f){var h=this.length;return this.resize(h+1),this.emplace(h,t,e,r,n,i,a,o,s,l,c,u,f)},e.prototype.emplace=function(t,e,r,n,i,a,o,s,l,c,u,f,h){var p=12*t;return this.int16[p+0]=e,this.int16[p+1]=r,this.int16[p+2]=n,this.int16[p+3]=i,this.uint16[p+4]=a,this.uint16[p+5]=o,this.uint16[p+6]=s,this.uint16[p+7]=l,this.int16[p+8]=c,this.int16[p+9]=u,this.int16[p+10]=f,this.int16[p+11]=h,t},e}(Pi);Ni.prototype.bytesPerElement=24,Nn(\"StructArrayLayout4i4ui4i24\",Ni);var ji=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.float32=new Float32Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e,r){var n=this.length;return this.resize(n+1),this.emplace(n,t,e,r)},e.prototype.emplace=function(t,e,r,n){var i=3*t;return this.float32[i+0]=e,this.float32[i+1]=r,this.float32[i+2]=n,t},e}(Pi);ji.prototype.bytesPerElement=12,Nn(\"StructArrayLayout3f12\",ji);var Ui=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.uint32=new Uint32Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t){var e=this.length;return this.resize(e+1),this.emplace(e,t)},e.prototype.emplace=function(t,e){var r=1*t;return this.uint32[r+0]=e,t},e}(Pi);Ui.prototype.bytesPerElement=4,Nn(\"StructArrayLayout1ul4\",Ui);var Vi=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.int16=new Int16Array(this.arrayBuffer),this.uint32=new Uint32Array(this.arrayBuffer),this.uint16=new Uint16Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e,r,n,i,a,o,s,l){var c=this.length;return this.resize(c+1),this.emplace(c,t,e,r,n,i,a,o,s,l)},e.prototype.emplace=function(t,e,r,n,i,a,o,s,l,c){var u=10*t,f=5*t;return this.int16[u+0]=e,this.int16[u+1]=r,this.int16[u+2]=n,this.int16[u+3]=i,this.int16[u+4]=a,this.int16[u+5]=o,this.uint32[f+3]=s,this.uint16[u+8]=l,this.uint16[u+9]=c,t},e}(Pi);Vi.prototype.bytesPerElement=20,Nn(\"StructArrayLayout6i1ul2ui20\",Vi);var Hi=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.int16=new Int16Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e,r,n,i,a){var o=this.length;return this.resize(o+1),this.emplace(o,t,e,r,n,i,a)},e.prototype.emplace=function(t,e,r,n,i,a,o){var s=6*t;return this.int16[s+0]=e,this.int16[s+1]=r,this.int16[s+2]=n,this.int16[s+3]=i,this.int16[s+4]=a,this.int16[s+5]=o,t},e}(Pi);Hi.prototype.bytesPerElement=12,Nn(\"StructArrayLayout2i2i2i12\",Hi);var qi=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.float32=new Float32Array(this.arrayBuffer),this.int16=new Int16Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e,r,n,i){var a=this.length;return this.resize(a+1),this.emplace(a,t,e,r,n,i)},e.prototype.emplace=function(t,e,r,n,i,a){var o=4*t,s=8*t;return this.float32[o+0]=e,this.float32[o+1]=r,this.float32[o+2]=n,this.int16[s+6]=i,this.int16[s+7]=a,t},e}(Pi);qi.prototype.bytesPerElement=16,Nn(\"StructArrayLayout2f1f2i16\",qi);var Gi=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.float32=new Float32Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e,r,n){var i=this.length;return this.resize(i+1),this.emplace(i,t,e,r,n)},e.prototype.emplace=function(t,e,r,n,i){var a=12*t,o=3*t;return this.uint8[a+0]=e,this.uint8[a+1]=r,this.float32[o+1]=n,this.float32[o+2]=i,t},e}(Pi);Gi.prototype.bytesPerElement=12,Nn(\"StructArrayLayout2ub2f12\",Gi);var Yi=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.uint16=new Uint16Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e,r){var n=this.length;return this.resize(n+1),this.emplace(n,t,e,r)},e.prototype.emplace=function(t,e,r,n){var i=3*t;return this.uint16[i+0]=e,this.uint16[i+1]=r,this.uint16[i+2]=n,t},e}(Pi);Yi.prototype.bytesPerElement=6,Nn(\"StructArrayLayout3ui6\",Yi);var Wi=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.int16=new Int16Array(this.arrayBuffer),this.uint16=new Uint16Array(this.arrayBuffer),this.uint32=new Uint32Array(this.arrayBuffer),this.float32=new Float32Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e,r,n,i,a,o,s,l,c,u,f,h,p,d,m,g){var v=this.length;return this.resize(v+1),this.emplace(v,t,e,r,n,i,a,o,s,l,c,u,f,h,p,d,m,g)},e.prototype.emplace=function(t,e,r,n,i,a,o,s,l,c,u,f,h,p,d,m,g,v){var y=24*t,x=12*t,b=48*t;return this.int16[y+0]=e,this.int16[y+1]=r,this.uint16[y+2]=n,this.uint16[y+3]=i,this.uint32[x+2]=a,this.uint32[x+3]=o,this.uint32[x+4]=s,this.uint16[y+10]=l,this.uint16[y+11]=c,this.uint16[y+12]=u,this.float32[x+7]=f,this.float32[x+8]=h,this.uint8[b+36]=p,this.uint8[b+37]=d,this.uint8[b+38]=m,this.uint32[x+10]=g,this.int16[y+22]=v,t},e}(Pi);Wi.prototype.bytesPerElement=48,Nn(\"StructArrayLayout2i2ui3ul3ui2f3ub1ul1i48\",Wi);var Xi=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.int16=new Int16Array(this.arrayBuffer),this.uint16=new Uint16Array(this.arrayBuffer),this.uint32=new Uint32Array(this.arrayBuffer),this.float32=new Float32Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e,r,n,i,a,o,s,l,c,u,f,h,p,d,m,g,v,y,x,b,_,w,T,k,A,M,S){var E=this.length;return this.resize(E+1),this.emplace(E,t,e,r,n,i,a,o,s,l,c,u,f,h,p,d,m,g,v,y,x,b,_,w,T,k,A,M,S)},e.prototype.emplace=function(t,e,r,n,i,a,o,s,l,c,u,f,h,p,d,m,g,v,y,x,b,_,w,T,k,A,M,S,E){var L=34*t,C=17*t;return this.int16[L+0]=e,this.int16[L+1]=r,this.int16[L+2]=n,this.int16[L+3]=i,this.int16[L+4]=a,this.int16[L+5]=o,this.int16[L+6]=s,this.int16[L+7]=l,this.uint16[L+8]=c,this.uint16[L+9]=u,this.uint16[L+10]=f,this.uint16[L+11]=h,this.uint16[L+12]=p,this.uint16[L+13]=d,this.uint16[L+14]=m,this.uint16[L+15]=g,this.uint16[L+16]=v,this.uint16[L+17]=y,this.uint16[L+18]=x,this.uint16[L+19]=b,this.uint16[L+20]=_,this.uint16[L+21]=w,this.uint16[L+22]=T,this.uint32[C+12]=k,this.float32[C+13]=A,this.float32[C+14]=M,this.float32[C+15]=S,this.float32[C+16]=E,t},e}(Pi);Xi.prototype.bytesPerElement=68,Nn(\"StructArrayLayout8i15ui1ul4f68\",Xi);var Zi=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.float32=new Float32Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t){var e=this.length;return this.resize(e+1),this.emplace(e,t)},e.prototype.emplace=function(t,e){var r=1*t;return this.float32[r+0]=e,t},e}(Pi);Zi.prototype.bytesPerElement=4,Nn(\"StructArrayLayout1f4\",Zi);var Ji=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.int16=new Int16Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e,r){var n=this.length;return this.resize(n+1),this.emplace(n,t,e,r)},e.prototype.emplace=function(t,e,r,n){var i=3*t;return this.int16[i+0]=e,this.int16[i+1]=r,this.int16[i+2]=n,t},e}(Pi);Ji.prototype.bytesPerElement=6,Nn(\"StructArrayLayout3i6\",Ji);var Ki=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.uint32=new Uint32Array(this.arrayBuffer),this.uint16=new Uint16Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e,r){var n=this.length;return this.resize(n+1),this.emplace(n,t,e,r)},e.prototype.emplace=function(t,e,r,n){var i=2*t,a=4*t;return this.uint32[i+0]=e,this.uint16[a+2]=r,this.uint16[a+3]=n,t},e}(Pi);Ki.prototype.bytesPerElement=8,Nn(\"StructArrayLayout1ul2ui8\",Ki);var Qi=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.uint16=new Uint16Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e){var r=this.length;return this.resize(r+1),this.emplace(r,t,e)},e.prototype.emplace=function(t,e,r){var n=2*t;return this.uint16[n+0]=e,this.uint16[n+1]=r,t},e}(Pi);Qi.prototype.bytesPerElement=4,Nn(\"StructArrayLayout2ui4\",Qi);var $i=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.uint16=new Uint16Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t){var e=this.length;return this.resize(e+1),this.emplace(e,t)},e.prototype.emplace=function(t,e){var r=1*t;return this.uint16[r+0]=e,t},e}(Pi);$i.prototype.bytesPerElement=2,Nn(\"StructArrayLayout1ui2\",$i);var ta=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.float32=new Float32Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e){var r=this.length;return this.resize(r+1),this.emplace(r,t,e)},e.prototype.emplace=function(t,e,r){var n=2*t;return this.float32[n+0]=e,this.float32[n+1]=r,t},e}(Pi);ta.prototype.bytesPerElement=8,Nn(\"StructArrayLayout2f8\",ta);var ea=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.float32=new Float32Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e,r,n){var i=this.length;return this.resize(i+1),this.emplace(i,t,e,r,n)},e.prototype.emplace=function(t,e,r,n,i){var a=4*t;return this.float32[a+0]=e,this.float32[a+1]=r,this.float32[a+2]=n,this.float32[a+3]=i,t},e}(Pi);ea.prototype.bytesPerElement=16,Nn(\"StructArrayLayout4f16\",ea);var ra=function(t){function e(){t.apply(this,arguments)}t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e;var r={anchorPointX:{configurable:!0},anchorPointY:{configurable:!0},x1:{configurable:!0},y1:{configurable:!0},x2:{configurable:!0},y2:{configurable:!0},featureIndex:{configurable:!0},sourceLayerIndex:{configurable:!0},bucketIndex:{configurable:!0},anchorPoint:{configurable:!0}};return r.anchorPointX.get=function(){return this._structArray.int16[this._pos2+0]},r.anchorPointY.get=function(){return this._structArray.int16[this._pos2+1]},r.x1.get=function(){return this._structArray.int16[this._pos2+2]},r.y1.get=function(){return this._structArray.int16[this._pos2+3]},r.x2.get=function(){return this._structArray.int16[this._pos2+4]},r.y2.get=function(){return this._structArray.int16[this._pos2+5]},r.featureIndex.get=function(){return this._structArray.uint32[this._pos4+3]},r.sourceLayerIndex.get=function(){return this._structArray.uint16[this._pos2+8]},r.bucketIndex.get=function(){return this._structArray.uint16[this._pos2+9]},r.anchorPoint.get=function(){return new i(this.anchorPointX,this.anchorPointY)},Object.defineProperties(e.prototype,r),e}(Ci);ra.prototype.size=20;var na=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.get=function(t){return new ra(this,t)},e}(Vi);Nn(\"CollisionBoxArray\",na);var ia=function(t){function e(){t.apply(this,arguments)}t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e;var r={anchorX:{configurable:!0},anchorY:{configurable:!0},glyphStartIndex:{configurable:!0},numGlyphs:{configurable:!0},vertexStartIndex:{configurable:!0},lineStartIndex:{configurable:!0},lineLength:{configurable:!0},segment:{configurable:!0},lowerSize:{configurable:!0},upperSize:{configurable:!0},lineOffsetX:{configurable:!0},lineOffsetY:{configurable:!0},writingMode:{configurable:!0},placedOrientation:{configurable:!0},hidden:{configurable:!0},crossTileID:{configurable:!0},associatedIconIndex:{configurable:!0}};return r.anchorX.get=function(){return this._structArray.int16[this._pos2+0]},r.anchorY.get=function(){return this._structArray.int16[this._pos2+1]},r.glyphStartIndex.get=function(){return this._structArray.uint16[this._pos2+2]},r.numGlyphs.get=function(){return this._structArray.uint16[this._pos2+3]},r.vertexStartIndex.get=function(){return this._structArray.uint32[this._pos4+2]},r.lineStartIndex.get=function(){return this._structArray.uint32[this._pos4+3]},r.lineLength.get=function(){return this._structArray.uint32[this._pos4+4]},r.segment.get=function(){return this._structArray.uint16[this._pos2+10]},r.lowerSize.get=function(){return this._structArray.uint16[this._pos2+11]},r.upperSize.get=function(){return this._structArray.uint16[this._pos2+12]},r.lineOffsetX.get=function(){return this._structArray.float32[this._pos4+7]},r.lineOffsetY.get=function(){return this._structArray.float32[this._pos4+8]},r.writingMode.get=function(){return this._structArray.uint8[this._pos1+36]},r.placedOrientation.get=function(){return this._structArray.uint8[this._pos1+37]},r.placedOrientation.set=function(t){this._structArray.uint8[this._pos1+37]=t},r.hidden.get=function(){return this._structArray.uint8[this._pos1+38]},r.hidden.set=function(t){this._structArray.uint8[this._pos1+38]=t},r.crossTileID.get=function(){return this._structArray.uint32[this._pos4+10]},r.crossTileID.set=function(t){this._structArray.uint32[this._pos4+10]=t},r.associatedIconIndex.get=function(){return this._structArray.int16[this._pos2+22]},Object.defineProperties(e.prototype,r),e}(Ci);ia.prototype.size=48;var aa=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.get=function(t){return new ia(this,t)},e}(Wi);Nn(\"PlacedSymbolArray\",aa);var oa=function(t){function e(){t.apply(this,arguments)}t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e;var r={anchorX:{configurable:!0},anchorY:{configurable:!0},rightJustifiedTextSymbolIndex:{configurable:!0},centerJustifiedTextSymbolIndex:{configurable:!0},leftJustifiedTextSymbolIndex:{configurable:!0},verticalPlacedTextSymbolIndex:{configurable:!0},placedIconSymbolIndex:{configurable:!0},verticalPlacedIconSymbolIndex:{configurable:!0},key:{configurable:!0},textBoxStartIndex:{configurable:!0},textBoxEndIndex:{configurable:!0},verticalTextBoxStartIndex:{configurable:!0},verticalTextBoxEndIndex:{configurable:!0},iconBoxStartIndex:{configurable:!0},iconBoxEndIndex:{configurable:!0},verticalIconBoxStartIndex:{configurable:!0},verticalIconBoxEndIndex:{configurable:!0},featureIndex:{configurable:!0},numHorizontalGlyphVertices:{configurable:!0},numVerticalGlyphVertices:{configurable:!0},numIconVertices:{configurable:!0},numVerticalIconVertices:{configurable:!0},useRuntimeCollisionCircles:{configurable:!0},crossTileID:{configurable:!0},textBoxScale:{configurable:!0},textOffset0:{configurable:!0},textOffset1:{configurable:!0},collisionCircleDiameter:{configurable:!0}};return r.anchorX.get=function(){return this._structArray.int16[this._pos2+0]},r.anchorY.get=function(){return this._structArray.int16[this._pos2+1]},r.rightJustifiedTextSymbolIndex.get=function(){return this._structArray.int16[this._pos2+2]},r.centerJustifiedTextSymbolIndex.get=function(){return this._structArray.int16[this._pos2+3]},r.leftJustifiedTextSymbolIndex.get=function(){return this._structArray.int16[this._pos2+4]},r.verticalPlacedTextSymbolIndex.get=function(){return this._structArray.int16[this._pos2+5]},r.placedIconSymbolIndex.get=function(){return this._structArray.int16[this._pos2+6]},r.verticalPlacedIconSymbolIndex.get=function(){return this._structArray.int16[this._pos2+7]},r.key.get=function(){return this._structArray.uint16[this._pos2+8]},r.textBoxStartIndex.get=function(){return this._structArray.uint16[this._pos2+9]},r.textBoxEndIndex.get=function(){return this._structArray.uint16[this._pos2+10]},r.verticalTextBoxStartIndex.get=function(){return this._structArray.uint16[this._pos2+11]},r.verticalTextBoxEndIndex.get=function(){return this._structArray.uint16[this._pos2+12]},r.iconBoxStartIndex.get=function(){return this._structArray.uint16[this._pos2+13]},r.iconBoxEndIndex.get=function(){return this._structArray.uint16[this._pos2+14]},r.verticalIconBoxStartIndex.get=function(){return this._structArray.uint16[this._pos2+15]},r.verticalIconBoxEndIndex.get=function(){return this._structArray.uint16[this._pos2+16]},r.featureIndex.get=function(){return this._structArray.uint16[this._pos2+17]},r.numHorizontalGlyphVertices.get=function(){return this._structArray.uint16[this._pos2+18]},r.numVerticalGlyphVertices.get=function(){return this._structArray.uint16[this._pos2+19]},r.numIconVertices.get=function(){return this._structArray.uint16[this._pos2+20]},r.numVerticalIconVertices.get=function(){return this._structArray.uint16[this._pos2+21]},r.useRuntimeCollisionCircles.get=function(){return 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c=t.readVarint();n=7&c,a=c>>3}if(a--,1===n||2===n)o+=t.readSVarint(),s+=t.readSVarint(),1===n&&(e&&l.push(e),e=[]),e.push(new i(o,s));else{if(7!==n)throw new Error(\"unknown command \"+n);e&&e.push(e[0].clone())}}return e&&l.push(e),l},ws.prototype.bbox=function(){var t=this._pbf;t.pos=this._geometry;for(var e=t.readVarint()+t.pos,r=1,n=0,i=0,a=0,o=1/0,s=-1/0,l=1/0,c=-1/0;t.pos<e;){if(n<=0){var u=t.readVarint();r=7&u,n=u>>3}if(n--,1===r||2===r)(i+=t.readSVarint())<o&&(o=i),i>s&&(s=i),(a+=t.readSVarint())<l&&(l=a),a>c&&(c=a);else if(7!==r)throw new Error(\"unknown command \"+r)}return[o,l,s,c]},ws.prototype.toGeoJSON=function(t,e,r){var n,i,a=this.extent*Math.pow(2,r),o=this.extent*t,s=this.extent*e,l=this.loadGeometry(),c=ws.types[this.type];function u(t){for(var e=0;e<t.length;e++){var r=t[e],n=180-360*(r.y+s)/a;t[e]=[360*(r.x+o)/a-180,360/Math.PI*Math.atan(Math.exp(n*Math.PI/180))-90]}}switch(this.type){case 1:var f=[];for(n=0;n<l.length;n++)f[n]=l[n][0];u(l=f);break;case 2:for(n=0;n<l.length;n++)u(l[n]);break;case 3:for(l=function(t){var e=t.length;if(e<=1)return[t];for(var r,n,i=[],a=0;a<e;a++){var o=ks(t[a]);0!==o&&(void 0===n&&(n=o<0),n===o<0?(r&&i.push(r),r=[t[a]]):r.push(t[a]))}r&&i.push(r);return i}(l),n=0;n<l.length;n++)for(i=0;i<l[n].length;i++)u(l[n][i])}1===l.length?l=l[0]:c=\"Multi\"+c;var h={type:\"Feature\",geometry:{type:c,coordinates:l},properties:this.properties};return\"id\"in this&&(h.id=this.id),h};var As=Ms;function Ms(t,e){this.version=1,this.name=null,this.extent=4096,this.length=0,this._pbf=t,this._keys=[],this._values=[],this._features=[],t.readFields(Ss,this,e),this.length=this._features.length}function Ss(t,e,r){15===t?e.version=r.readVarint():1===t?e.name=r.readString():5===t?e.extent=r.readVarint():2===t?e._features.push(r.pos):3===t?e._keys.push(r.readString()):4===t&&e._values.push(function(t){var e=null,r=t.readVarint()+t.pos;for(;t.pos<r;){var n=t.readVarint()>>3;e=1===n?t.readString():2===n?t.readFloat():3===n?t.readDouble():4===n?t.readVarint64():5===n?t.readVarint():6===n?t.readSVarint():7===n?t.readBoolean():null}return e}(r))}function Es(t,e,r){if(3===t){var n=new As(r,r.readVarint()+r.pos);n.length&&(e[n.name]=n)}}Ms.prototype.feature=function(t){if(t<0||t>=this._features.length)throw new Error(\"feature index out of bounds\");this._pbf.pos=this._features[t];var e=this._pbf.readVarint()+this._pbf.pos;return new _s(this._pbf,e,this.extent,this._keys,this._values)};var Ls={VectorTile:function(t,e){this.layers=t.readFields(Es,{},e)},VectorTileFeature:_s,VectorTileLayer:As},Cs=Ls.VectorTileFeature.types,Ps=Math.pow(2,13);function Is(t,e,r,n,i,a,o,s){t.emplaceBack(e,r,2*Math.floor(n*Ps)+o,i*Ps*2,a*Ps*2,Math.round(s))}var Os=function(t){this.zoom=t.zoom,this.overscaling=t.overscaling,this.layers=t.layers,this.layerIds=this.layers.map((function(t){return t.id})),this.index=t.index,this.hasPattern=!1,this.layoutVertexArray=new Ri,this.indexArray=new Yi,this.programConfigurations=new Ua(bs,t.layers,t.zoom),this.segments=new pa,this.stateDependentLayerIds=this.layers.filter((function(t){return t.isStateDependent()})).map((function(t){return t.id}))};function zs(t,e){return t.x===e.x&&(t.x<0||t.x>8192)||t.y===e.y&&(t.y<0||t.y>8192)}function Ds(t){return t.every((function(t){return t.x<0}))||t.every((function(t){return t.x>8192}))||t.every((function(t){return t.y<0}))||t.every((function(t){return t.y>8192}))}Os.prototype.populate=function(t,e,r){this.features=[],this.hasPattern=ds(\"fill-extrusion\",this.layers,e);for(var n=0,i=t;n<i.length;n+=1){var a=i[n],o=a.feature,s=a.id,l=a.index,c=a.sourceLayerIndex,u=this.layers[0]._featureFilter.needGeometry,f={type:o.type,id:s,properties:o.properties,geometry:u?Ya(o):[]};if(this.layers[0]._featureFilter.filter(new pi(this.zoom),f,r)){var h={id:s,sourceLayerIndex:c,index:l,geometry:u?f.geometry:Ya(o),properties:o.properties,type:o.type,patterns:{}};void 0!==o.id&&(h.id=o.id),this.hasPattern?this.features.push(ms(\"fill-extrusion\",this.layers,h,this.zoom,e)):this.addFeature(h,h.geometry,l,r,{}),e.featureIndex.insert(o,h.geometry,l,c,this.index,!0)}}},Os.prototype.addFeatures=function(t,e,r){for(var n=0,i=this.features;n<i.length;n+=1){var a=i[n],o=a.geometry;this.addFeature(a,o,a.index,e,r)}},Os.prototype.update=function(t,e,r){this.stateDependentLayers.length&&this.programConfigurations.updatePaintArrays(t,e,this.stateDependentLayers,r)},Os.prototype.isEmpty=function(){return 0===this.layoutVertexArray.length},Os.prototype.uploadPending=function(){return!this.uploaded||this.programConfigurations.needsUpload},Os.prototype.upload=function(t){this.uploaded||(this.layoutVertexBuffer=t.createVertexBuffer(this.layoutVertexArray,bs),this.indexBuffer=t.createIndexBuffer(this.indexArray)),this.programConfigurations.upload(t),this.uploaded=!0},Os.prototype.destroy=function(){this.layoutVertexBuffer&&(this.layoutVertexBuffer.destroy(),this.indexBuffer.destroy(),this.programConfigurations.destroy(),this.segments.destroy())},Os.prototype.addFeature=function(t,e,r,n,i){for(var a=0,o=hs(e,500);a<o.length;a+=1){for(var s=o[a],l=0,c=0,u=s;c<u.length;c+=1){l+=u[c].length}for(var f=this.segments.prepareSegment(4,this.layoutVertexArray,this.indexArray),h=0,p=s;h<p.length;h+=1){var d=p[h];if(0!==d.length&&!Ds(d))for(var m=0,g=0;g<d.length;g++){var v=d[g];if(g>=1){var y=d[g-1];if(!zs(v,y)){f.vertexLength+4>pa.MAX_VERTEX_ARRAY_LENGTH&&(f=this.segments.prepareSegment(4,this.layoutVertexArray,this.indexArray));var x=v.sub(y)._perp()._unit(),b=y.dist(v);m+b>32768&&(m=0),Is(this.layoutVertexArray,v.x,v.y,x.x,x.y,0,0,m),Is(this.layoutVertexArray,v.x,v.y,x.x,x.y,0,1,m),m+=b,Is(this.layoutVertexArray,y.x,y.y,x.x,x.y,0,0,m),Is(this.layoutVertexArray,y.x,y.y,x.x,x.y,0,1,m);var _=f.vertexLength;this.indexArray.emplaceBack(_,_+2,_+1),this.indexArray.emplaceBack(_+1,_+2,_+3),f.vertexLength+=4,f.primitiveLength+=2}}}}if(f.vertexLength+l>pa.MAX_VERTEX_ARRAY_LENGTH&&(f=this.segments.prepareSegment(l,this.layoutVertexArray,this.indexArray)),\"Polygon\"===Cs[t.type]){for(var w=[],T=[],k=f.vertexLength,A=0,M=s;A<M.length;A+=1){var S=M[A];if(0!==S.length){S!==s[0]&&T.push(w.length/2);for(var E=0;E<S.length;E++){var L=S[E];Is(this.layoutVertexArray,L.x,L.y,0,0,1,1,0),w.push(L.x),w.push(L.y)}}}for(var C=Do(w,T),P=0;P<C.length;P+=3)this.indexArray.emplaceBack(k+C[P],k+C[P+2],k+C[P+1]);f.primitiveLength+=C.length/3,f.vertexLength+=l}}this.programConfigurations.populatePaintArrays(this.layoutVertexArray.length,t,r,i,n)},Nn(\"FillExtrusionBucket\",Os,{omit:[\"layers\",\"features\"]});var Rs={paint:new Si({\"fill-extrusion-opacity\":new wi(Lt[\"paint_fill-extrusion\"][\"fill-extrusion-opacity\"]),\"fill-extrusion-color\":new Ti(Lt[\"paint_fill-extrusion\"][\"fill-extrusion-color\"]),\"fill-extrusion-translate\":new wi(Lt[\"paint_fill-extrusion\"][\"fill-extrusion-translate\"]),\"fill-extrusion-translate-anchor\":new wi(Lt[\"paint_fill-extrusion\"][\"fill-extrusion-translate-anchor\"]),\"fill-extrusion-pattern\":new ki(Lt[\"paint_fill-extrusion\"][\"fill-extrusion-pattern\"]),\"fill-extrusion-height\":new Ti(Lt[\"paint_fill-extrusion\"][\"fill-extrusion-height\"]),\"fill-extrusion-base\":new Ti(Lt[\"paint_fill-extrusion\"][\"fill-extrusion-base\"]),\"fill-extrusion-vertical-gradient\":new wi(Lt[\"paint_fill-extrusion\"][\"fill-extrusion-vertical-gradient\"])})},Fs=function(t){function e(e){t.call(this,e,Rs)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.createBucket=function(t){return new Os(t)},e.prototype.queryRadius=function(){return so(this.paint.get(\"fill-extrusion-translate\"))},e.prototype.is3D=function(){return!0},e.prototype.queryIntersectsFeature=function(t,e,r,n,a,o,s,l){var c=lo(t,this.paint.get(\"fill-extrusion-translate\"),this.paint.get(\"fill-extrusion-translate-anchor\"),o.angle,s),u=this.paint.get(\"fill-extrusion-height\").evaluate(e,r),f=this.paint.get(\"fill-extrusion-base\").evaluate(e,r),h=function(t,e,r,n){for(var a=[],o=0,s=t;o<s.length;o+=1){var l=s[o],c=[l.x,l.y,n,1];xo(c,c,e),a.push(new i(c[0]/c[3],c[1]/c[3]))}return a}(c,l,0,0),p=function(t,e,r,n){for(var a=[],o=[],s=n[8]*e,l=n[9]*e,c=n[10]*e,u=n[11]*e,f=n[8]*r,h=n[9]*r,p=n[10]*r,d=n[11]*r,m=0,g=t;m<g.length;m+=1){for(var v=g[m],y=[],x=[],b=0,_=v;b<_.length;b+=1){var w=_[b],T=w.x,k=w.y,A=n[0]*T+n[4]*k+n[12],M=n[1]*T+n[5]*k+n[13],S=n[2]*T+n[6]*k+n[14],E=n[3]*T+n[7]*k+n[15],L=S+c,C=E+u,P=A+f,I=M+h,O=S+p,z=E+d,D=new i((A+s)/C,(M+l)/C);D.z=L/C,y.push(D);var R=new i(P/z,I/z);R.z=O/z,x.push(R)}a.push(y),o.push(x)}return[a,o]}(n,f,u,l);return function(t,e,r){var n=1/0;Ka(r,e)&&(n=Ns(r,e[0]));for(var i=0;i<e.length;i++)for(var a=e[i],o=t[i],s=0;s<a.length-1;s++){var l=a[s],c=a[s+1],u=o[s],f=o[s+1],h=[l,c,f,u,l];Za(r,h)&&(n=Math.min(n,Ns(r,h)))}return n!==1/0&&n}(p[0],p[1],h)},e}(Ei);function Bs(t,e){return t.x*e.x+t.y*e.y}function Ns(t,e){if(1===t.length){for(var r,n=0,i=e[n++];!r||i.equals(r);)if(!(r=e[n++]))return 1/0;for(;n<e.length;n++){var a=e[n],o=t[0],s=r.sub(i),l=a.sub(i),c=o.sub(i),u=Bs(s,s),f=Bs(s,l),h=Bs(l,l),p=Bs(c,s),d=Bs(c,l),m=u*h-f*f,g=(h*p-f*d)/m,v=(u*d-f*p)/m,y=1-g-v,x=i.z*y+r.z*g+a.z*v;if(isFinite(x))return x}return 1/0}for(var b=1/0,_=0,w=e;_<w.length;_+=1){var T=w[_];b=Math.min(b,T.z)}return b}var js=Ii([{name:\"a_pos_normal\",components:2,type:\"Int16\"},{name:\"a_data\",components:4,type:\"Uint8\"}],4).members,Us=Ls.VectorTileFeature.types,Vs=Math.cos(Math.PI/180*37.5),Hs=Math.pow(2,14)/.5,qs=function(t){this.zoom=t.zoom,this.overscaling=t.overscaling,this.layers=t.layers,this.layerIds=this.layers.map((function(t){return t.id})),this.index=t.index,this.hasPattern=!1,this.patternFeatures=[],this.layoutVertexArray=new Fi,this.indexArray=new Yi,this.programConfigurations=new Ua(js,t.layers,t.zoom),this.segments=new pa,this.stateDependentLayerIds=this.layers.filter((function(t){return t.isStateDependent()})).map((function(t){return t.id}))};qs.prototype.populate=function(t,e,r){this.hasPattern=ds(\"line\",this.layers,e);for(var n=this.layers[0].layout.get(\"line-sort-key\"),i=[],a=0,o=t;a<o.length;a+=1){var s=o[a],l=s.feature,c=s.id,u=s.index,f=s.sourceLayerIndex,h=this.layers[0]._featureFilter.needGeometry,p={type:l.type,id:c,properties:l.properties,geometry:h?Ya(l):[]};if(this.layers[0]._featureFilter.filter(new pi(this.zoom),p,r)){h||(p.geometry=Ya(l));var d=n?n.evaluate(p,{},r):void 0,m={id:c,properties:l.properties,type:l.type,sourceLayerIndex:f,index:u,geometry:p.geometry,patterns:{},sortKey:d};i.push(m)}}n&&i.sort((function(t,e){return t.sortKey-e.sortKey}));for(var g=0,v=i;g<v.length;g+=1){var y=v[g],x=y,b=x.geometry,_=x.index,w=x.sourceLayerIndex;if(this.hasPattern){var T=ms(\"line\",this.layers,y,this.zoom,e);this.patternFeatures.push(T)}else this.addFeature(y,b,_,r,{});var k=t[_].feature;e.featureIndex.insert(k,b,_,w,this.index)}},qs.prototype.update=function(t,e,r){this.stateDependentLayers.length&&this.programConfigurations.updatePaintArrays(t,e,this.stateDependentLayers,r)},qs.prototype.addFeatures=function(t,e,r){for(var n=0,i=this.patternFeatures;n<i.length;n+=1){var a=i[n];this.addFeature(a,a.geometry,a.index,e,r)}},qs.prototype.isEmpty=function(){return 0===this.layoutVertexArray.length},qs.prototype.uploadPending=function(){return!this.uploaded||this.programConfigurations.needsUpload},qs.prototype.upload=function(t){this.uploaded||(this.layoutVertexBuffer=t.createVertexBuffer(this.layoutVertexArray,js),this.indexBuffer=t.createIndexBuffer(this.indexArray)),this.programConfigurations.upload(t),this.uploaded=!0},qs.prototype.destroy=function(){this.layoutVertexBuffer&&(this.layoutVertexBuffer.destroy(),this.indexBuffer.destroy(),this.programConfigurations.destroy(),this.segments.destroy())},qs.prototype.addFeature=function(t,e,r,n,i){for(var a=this.layers[0].layout,o=a.get(\"line-join\").evaluate(t,{}),s=a.get(\"line-cap\"),l=a.get(\"line-miter-limit\"),c=a.get(\"line-round-limit\"),u=0,f=e;u<f.length;u+=1){var h=f[u];this.addLine(h,t,o,s,l,c)}this.programConfigurations.populatePaintArrays(this.layoutVertexArray.length,t,r,i,n)},qs.prototype.addLine=function(t,e,r,n,i,a){if(this.distance=0,this.scaledDistance=0,this.totalDistance=0,e.properties&&e.properties.hasOwnProperty(\"mapbox_clip_start\")&&e.properties.hasOwnProperty(\"mapbox_clip_end\")){this.clipStart=+e.properties.mapbox_clip_start,this.clipEnd=+e.properties.mapbox_clip_end;for(var o=0;o<t.length-1;o++)this.totalDistance+=t[o].dist(t[o+1]);this.updateScaledDistance()}for(var s=\"Polygon\"===Us[e.type],l=t.length;l>=2&&t[l-1].equals(t[l-2]);)l--;for(var c=0;c<l-1&&t[c].equals(t[c+1]);)c++;if(!(l<(s?3:2))){\"bevel\"===r&&(i=1.05);var u,f=this.overscaling<=16?122880/(512*this.overscaling):0,h=this.segments.prepareSegment(10*l,this.layoutVertexArray,this.indexArray),p=void 0,d=void 0,m=void 0,g=void 0;this.e1=this.e2=-1,s&&(u=t[l-2],g=t[c].sub(u)._unit()._perp());for(var v=c;v<l;v++)if(!(d=v===l-1?s?t[c+1]:void 0:t[v+1])||!t[v].equals(d)){g&&(m=g),u&&(p=u),u=t[v],g=d?d.sub(u)._unit()._perp():m;var y=(m=m||g).add(g);0===y.x&&0===y.y||y._unit();var x=m.x*g.x+m.y*g.y,b=y.x*g.x+y.y*g.y,_=0!==b?1/b:1/0,w=2*Math.sqrt(2-2*b),T=b<Vs&&p&&d,k=m.x*g.y-m.y*g.x>0;if(T&&v>c){var A=u.dist(p);if(A>2*f){var M=u.sub(u.sub(p)._mult(f/A)._round());this.updateDistance(p,M),this.addCurrentVertex(M,m,0,0,h),p=M}}var S=p&&d,E=S?r:s?\"butt\":n;if(S&&\"round\"===E&&(_<a?E=\"miter\":_<=2&&(E=\"fakeround\")),\"miter\"===E&&_>i&&(E=\"bevel\"),\"bevel\"===E&&(_>2&&(E=\"flipbevel\"),_<i&&(E=\"miter\")),p&&this.updateDistance(p,u),\"miter\"===E)y._mult(_),this.addCurrentVertex(u,y,0,0,h);else if(\"flipbevel\"===E){if(_>100)y=g.mult(-1);else{var L=_*m.add(g).mag()/m.sub(g).mag();y._perp()._mult(L*(k?-1:1))}this.addCurrentVertex(u,y,0,0,h),this.addCurrentVertex(u,y.mult(-1),0,0,h)}else if(\"bevel\"===E||\"fakeround\"===E){var C=-Math.sqrt(_*_-1),P=k?C:0,I=k?0:C;if(p&&this.addCurrentVertex(u,m,P,I,h),\"fakeround\"===E)for(var O=Math.round(180*w/Math.PI/20),z=1;z<O;z++){var D=z/O;if(.5!==D){var R=D-.5;D+=D*R*(D-1)*((1.0904+x*(x*(3.55645-1.43519*x)-3.2452))*R*R+(.848013+x*(.215638*x-1.06021)))}var F=g.sub(m)._mult(D)._add(m)._unit()._mult(k?-1:1);this.addHalfVertex(u,F.x,F.y,!1,k,0,h)}d&&this.addCurrentVertex(u,g,-P,-I,h)}else if(\"butt\"===E)this.addCurrentVertex(u,y,0,0,h);else if(\"square\"===E){var B=p?1:-1;this.addCurrentVertex(u,y,B,B,h)}else\"round\"===E&&(p&&(this.addCurrentVertex(u,m,0,0,h),this.addCurrentVertex(u,m,1,1,h,!0)),d&&(this.addCurrentVertex(u,g,-1,-1,h,!0),this.addCurrentVertex(u,g,0,0,h)));if(T&&v<l-1){var N=u.dist(d);if(N>2*f){var j=u.add(d.sub(u)._mult(f/N)._round());this.updateDistance(u,j),this.addCurrentVertex(j,g,0,0,h),u=j}}}}},qs.prototype.addCurrentVertex=function(t,e,r,n,i,a){void 0===a&&(a=!1);var o=e.x+e.y*r,s=e.y-e.x*r,l=-e.x+e.y*n,c=-e.y-e.x*n;this.addHalfVertex(t,o,s,a,!1,r,i),this.addHalfVertex(t,l,c,a,!0,-n,i),this.distance>Hs/2&&0===this.totalDistance&&(this.distance=0,this.addCurrentVertex(t,e,r,n,i,a))},qs.prototype.addHalfVertex=function(t,e,r,n,i,a,o){var s=t.x,l=t.y,c=.5*this.scaledDistance;this.layoutVertexArray.emplaceBack((s<<1)+(n?1:0),(l<<1)+(i?1:0),Math.round(63*e)+128,Math.round(63*r)+128,1+(0===a?0:a<0?-1:1)|(63&c)<<2,c>>6);var u=o.vertexLength++;this.e1>=0&&this.e2>=0&&(this.indexArray.emplaceBack(this.e1,this.e2,u),o.primitiveLength++),i?this.e2=u:this.e1=u},qs.prototype.updateScaledDistance=function(){this.scaledDistance=this.totalDistance>0?(this.clipStart+(this.clipEnd-this.clipStart)*this.distance/this.totalDistance)*(Hs-1):this.distance},qs.prototype.updateDistance=function(t,e){this.distance+=t.dist(e),this.updateScaledDistance()},Nn(\"LineBucket\",qs,{omit:[\"layers\",\"patternFeatures\"]});var Gs=new Si({\"line-cap\":new 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e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.possiblyEvaluate=function(e,r){return r=new pi(Math.floor(r.zoom),{now:r.now,fadeDuration:r.fadeDuration,zoomHistory:r.zoomHistory,transition:r.transition}),t.prototype.possiblyEvaluate.call(this,e,r)},e.prototype.evaluate=function(e,r,n,i){return r=u({},r,{zoom:Math.floor(r.zoom)}),t.prototype.evaluate.call(this,e,r,n,i)},e}(Ti))(Ys.paint.properties[\"line-width\"].specification);Ws.useIntegerZoom=!0;var Xs=function(t){function e(e){t.call(this,e,Ys)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._handleSpecialPaintPropertyUpdate=function(t){\"line-gradient\"===t&&this._updateGradient()},e.prototype._updateGradient=function(){var 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o=t[a],s=[],l=0;l<o.length;l++){var c=o[l-1],u=o[l],f=o[l+1],h=0===l?n:u.sub(c)._unit()._perp(),p=l===o.length-1?n:f.sub(u)._unit()._perp(),d=h._add(p)._unit(),m=d.x*p.x+d.y*p.y;d._mult(1/m),s.push(d._mult(e)._add(u))}r.push(s)}return r}(n,u*s)),function(t,e,r){for(var n=0;n<e.length;n++){var i=e[n];if(t.length>=3)for(var a=0;a<i.length;a++)if(io(t,i[a]))return!0;if(Qa(t,i,r))return!0}return!1}(l,n,c)},e.prototype.isTileClipped=function(){return!0},e}(Ei);function Zs(t,e){return e>0?e+2*t:t}var 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nl=function(t,e,r,n,i){var a,o,s=8*i-n-1,l=(1<<s)-1,c=l>>1,u=-7,f=r?i-1:0,h=r?-1:1,p=t[e+f];for(f+=h,a=p&(1<<-u)-1,p>>=-u,u+=s;u>0;a=256*a+t[e+f],f+=h,u-=8);for(o=a&(1<<-u)-1,a>>=-u,u+=n;u>0;o=256*o+t[e+f],f+=h,u-=8);if(0===a)a=1-c;else{if(a===l)return o?NaN:1/0*(p?-1:1);o+=Math.pow(2,n),a-=c}return(p?-1:1)*o*Math.pow(2,a-n)},il=function(t,e,r,n,i,a){var o,s,l,c=8*a-i-1,u=(1<<c)-1,f=u>>1,h=23===i?Math.pow(2,-24)-Math.pow(2,-77):0,p=n?0:a-1,d=n?1:-1,m=e<0||0===e&&1/e<0?1:0;for(e=Math.abs(e),isNaN(e)||e===1/0?(s=isNaN(e)?1:0,o=u):(o=Math.floor(Math.log(e)/Math.LN2),e*(l=Math.pow(2,-o))<1&&(o--,l*=2),(e+=o+f>=1?h/l:h*Math.pow(2,1-f))*l>=2&&(o++,l/=2),o+f>=u?(s=0,o=u):o+f>=1?(s=(e*l-1)*Math.pow(2,i),o+=f):(s=e*Math.pow(2,f-1)*Math.pow(2,i),o=0));i>=8;t[r+p]=255&s,p+=d,s/=256,i-=8);for(o=o<<i|s,c+=i;c>0;t[r+p]=255&o,p+=d,o/=256,c-=8);t[r+p-d]|=128*m},al=ol;function ol(t){this.buf=ArrayBuffer.isView&&ArrayBuffer.isView(t)?t:new 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e=ll(this);for(t=t||[];this.pos<e;)t.push(this.readSFixed32());return t},readPackedFixed64:function(t){if(this.type!==ol.Bytes)return t.push(this.readFixed64());var e=ll(this);for(t=t||[];this.pos<e;)t.push(this.readFixed64());return t},readPackedSFixed64:function(t){if(this.type!==ol.Bytes)return t.push(this.readSFixed64());var e=ll(this);for(t=t||[];this.pos<e;)t.push(this.readSFixed64());return t},skip:function(t){var e=7&t;if(e===ol.Varint)for(;this.buf[this.pos++]>127;);else if(e===ol.Bytes)this.pos=this.readVarint()+this.pos;else if(e===ol.Fixed32)this.pos+=4;else{if(e!==ol.Fixed64)throw new Error(\"Unimplemented type: \"+e);this.pos+=8}},writeTag:function(t,e){this.writeVarint(t<<3|e)},realloc:function(t){for(var e=this.length||16;e<this.pos+t;)e*=2;if(e!==this.length){var r=new Uint8Array(e);r.set(this.buf),this.buf=r,this.length=e}},finish:function(){return 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r=(7&t)<<4;if(e.buf[e.pos++]|=r|((t>>>=3)?128:0),!t)return;if(e.buf[e.pos++]=127&t|((t>>>=7)?128:0),!t)return;if(e.buf[e.pos++]=127&t|((t>>>=7)?128:0),!t)return;if(e.buf[e.pos++]=127&t|((t>>>=7)?128:0),!t)return;if(e.buf[e.pos++]=127&t|((t>>>=7)?128:0),!t)return;e.buf[e.pos++]=127&t}(n,e)}(t,this):(this.realloc(4),this.buf[this.pos++]=127&t|(t>127?128:0),t<=127||(this.buf[this.pos++]=127&(t>>>=7)|(t>127?128:0),t<=127||(this.buf[this.pos++]=127&(t>>>=7)|(t>127?128:0),t<=127||(this.buf[this.pos++]=t>>>7&127))))},writeSVarint:function(t){this.writeVarint(t<0?2*-t-1:2*t)},writeBoolean:function(t){this.writeVarint(Boolean(t))},writeString:function(t){t=String(t),this.realloc(4*t.length),this.pos++;var e=this.pos;this.pos=function(t,e,r){for(var n,i,a=0;a<e.length;a++){if((n=e.charCodeAt(a))>55295&&n<57344){if(!i){n>56319||a+1===e.length?(t[r++]=239,t[r++]=191,t[r++]=189):i=n;continue}if(n<56320){t[r++]=239,t[r++]=191,t[r++]=189,i=n;continue}n=i-55296<<10|n-56320|65536,i=null}else i&&(t[r++]=239,t[r++]=191,t[r++]=189,i=null);n<128?t[r++]=n:(n<2048?t[r++]=n>>6|192:(n<65536?t[r++]=n>>12|224:(t[r++]=n>>18|240,t[r++]=n>>12&63|128),t[r++]=n>>6&63|128),t[r++]=63&n|128)}return r}(this.buf,t,this.pos);var r=this.pos-e;r>=128&&ul(e,r,this),this.pos=e-1,this.writeVarint(r),this.pos+=r},writeFloat:function(t){this.realloc(4),il(this.buf,t,this.pos,!0,23,4),this.pos+=4},writeDouble:function(t){this.realloc(8),il(this.buf,t,this.pos,!0,52,8),this.pos+=8},writeBytes:function(t){var e=t.length;this.writeVarint(e),this.realloc(e);for(var r=0;r<e;r++)this.buf[this.pos++]=t[r]},writeRawMessage:function(t,e){this.pos++;var r=this.pos;t(e,this);var n=this.pos-r;n>=128&&ul(r,n,this),this.pos=r-1,this.writeVarint(n),this.pos+=n},writeMessage:function(t,e,r){this.writeTag(t,ol.Bytes),this.writeRawMessage(e,r)},writePackedVarint:function(t,e){e.length&&this.writeMessage(t,fl,e)},writePackedSVarint:function(t,e){e.length&&this.writeMessage(t,hl,e)},writePackedBoolean:function(t,e){e.length&&this.writeMessage(t,ml,e)},writePackedFloat:function(t,e){e.length&&this.writeMessage(t,pl,e)},writePackedDouble:function(t,e){e.length&&this.writeMessage(t,dl,e)},writePackedFixed32:function(t,e){e.length&&this.writeMessage(t,gl,e)},writePackedSFixed32:function(t,e){e.length&&this.writeMessage(t,vl,e)},writePackedFixed64:function(t,e){e.length&&this.writeMessage(t,yl,e)},writePackedSFixed64:function(t,e){e.length&&this.writeMessage(t,xl,e)},writeBytesField:function(t,e){this.writeTag(t,ol.Bytes),this.writeBytes(e)},writeFixed32Field:function(t,e){this.writeTag(t,ol.Fixed32),this.writeFixed32(e)},writeSFixed32Field:function(t,e){this.writeTag(t,ol.Fixed32),this.writeSFixed32(e)},writeFixed64Field:function(t,e){this.writeTag(t,ol.Fixed64),this.writeFixed64(e)},writeSFixed64Field:function(t,e){this.writeTag(t,ol.Fixed64),this.writeSFixed64(e)},writeVarintField:function(t,e){this.writeTag(t,ol.Varint),this.writeVarint(e)},writeSVarintField:function(t,e){this.writeTag(t,ol.Varint),this.writeSVarint(e)},writeStringField:function(t,e){this.writeTag(t,ol.Bytes),this.writeString(e)},writeFloatField:function(t,e){this.writeTag(t,ol.Fixed32),this.writeFloat(e)},writeDoubleField:function(t,e){this.writeTag(t,ol.Fixed64),this.writeDouble(e)},writeBooleanField:function(t,e){this.writeVarintField(t,Boolean(e))}};function Tl(t,e,r){1===t&&r.readMessage(kl,e)}function kl(t,e,r){if(3===t){var n=r.readMessage(Al,{}),i=n.id,a=n.bitmap,o=n.width,s=n.height,l=n.left,c=n.top,u=n.advance;e.push({id:i,bitmap:new So({width:o+6,height:s+6},a),metrics:{width:o,height:s,left:l,top:c,advance:u}})}}function Al(t,e,r){1===t?e.id=r.readVarint():2===t?e.bitmap=r.readBytes():3===t?e.width=r.readVarint():4===t?e.height=r.readVarint():5===t?e.left=r.readSVarint():6===t?e.top=r.readSVarint():7===t&&(e.advance=r.readVarint())}function Ml(t){for(var e=0,r=0,n=0,i=t;n<i.length;n+=1){var a=i[n];e+=a.w*a.h,r=Math.max(r,a.w)}t.sort((function(t,e){return e.h-t.h}));for(var o=[{x:0,y:0,w:Math.max(Math.ceil(Math.sqrt(e/.95)),r),h:1/0}],s=0,l=0,c=0,u=t;c<u.length;c+=1)for(var f=u[c],h=o.length-1;h>=0;h--){var p=o[h];if(!(f.w>p.w||f.h>p.h)){if(f.x=p.x,f.y=p.y,l=Math.max(l,f.y+f.h),s=Math.max(s,f.x+f.w),f.w===p.w&&f.h===p.h){var d=o.pop();h<o.length&&(o[h]=d)}else 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Eo({width:o||1,height:s||1});for(var c in t){var u=t[c],f=r[c].paddedRect;Eo.copy(u.data,l,{x:0,y:0},{x:f.x+1,y:f.y+1},u.data)}for(var h in e){var p=e[h],d=n[h].paddedRect,m=d.x+1,g=d.y+1,v=p.data.width,y=p.data.height;Eo.copy(p.data,l,{x:0,y:0},{x:m,y:g},p.data),Eo.copy(p.data,l,{x:0,y:y-1},{x:m,y:g-1},{width:v,height:1}),Eo.copy(p.data,l,{x:0,y:0},{x:m,y:g+y},{width:v,height:1}),Eo.copy(p.data,l,{x:v-1,y:0},{x:m-1,y:g},{width:1,height:y}),Eo.copy(p.data,l,{x:0,y:0},{x:m+v,y:g},{width:1,height:y})}this.image=l,this.iconPositions=r,this.patternPositions=n};Ll.prototype.addImages=function(t,e,r){for(var n in t){var i=t[n],a={x:0,y:0,w:i.data.width+2,h:i.data.height+2};r.push(a),e[n]=new Sl(a,i),i.hasRenderCallback&&this.haveRenderCallbacks.push(n)}},Ll.prototype.patchUpdatedImages=function(t,e){for(var r in t.dispatchRenderCallbacks(this.haveRenderCallbacks),t.updatedImages)this.patchUpdatedImage(this.iconPositions[r],t.getImage(r),e),this.patchUpdatedImage(this.patternPositions[r],t.getImage(r),e)},Ll.prototype.patchUpdatedImage=function(t,e,r){if(t&&e&&t.version!==e.version){t.version=e.version;var n=t.tl,i=n[0],a=n[1];r.update(e.data,void 0,{x:i,y:a})}},Nn(\"ImagePosition\",Sl),Nn(\"ImageAtlas\",Ll);var Cl={horizontal:1,vertical:2,horizontalOnly:3};var Pl=function(){this.scale=1,this.fontStack=\"\",this.imageName=null};Pl.forText=function(t,e){var r=new Pl;return r.scale=t||1,r.fontStack=e,r},Pl.forImage=function(t){var e=new Pl;return e.imageName=t,e};var Il=function(){this.text=\"\",this.sectionIndex=[],this.sections=[],this.imageSectionID=null};function Ol(t,e,r,n,i,a,o,s,l,c,u,f,h,p,d,m){var g,v=Il.fromFeature(t,i);f===Cl.vertical&&v.verticalizePunctuation();var y=hi.processBidirectionalText,x=hi.processStyledBidirectionalText;if(y&&1===v.sections.length){g=[];for(var b=0,_=y(v.toString(),jl(v,c,a,e,n,p,d));b<_.length;b+=1){var w=_[b],T=new Il;T.text=w,T.sections=v.sections;for(var k=0;k<w.length;k++)T.sectionIndex.push(0);g.push(T)}}else if(x){g=[];for(var A=0,M=x(v.text,v.sectionIndex,jl(v,c,a,e,n,p,d));A<M.length;A+=1){var S=M[A],E=new Il;E.text=S[0],E.sectionIndex=S[1],E.sections=v.sections,g.push(E)}}else g=function(t,e){for(var r=[],n=t.text,i=0,a=0,o=e;a<o.length;a+=1){var s=o[a];r.push(t.substring(i,s)),i=s}return i<n.length&&r.push(t.substring(i,n.length)),r}(v,jl(v,c,a,e,n,p,d));var L=[],C={positionedLines:L,text:v.toString(),top:u[1],bottom:u[1],left:u[0],right:u[0],writingMode:f,iconsInText:!1,verticalizable:!1};return function(t,e,r,n,i,a,o,s,l,c,u,f){for(var h=0,p=-17,d=0,m=0,g=\"right\"===s?1:\"left\"===s?0:.5,v=0,y=0,x=i;y<x.length;y+=1){var b=x[y];b.trim();var _=b.getMaxScale(),w=24*(_-1),T={positionedGlyphs:[],lineOffset:0};t.positionedLines[v]=T;var k=T.positionedGlyphs,A=0;if(b.length()){for(var M=0;M<b.length();M++){var S=b.getSection(M),E=b.getSectionIndex(M),L=b.getCharCode(M),C=0,P=null,I=null,O=null,z=24,D=!(l===Cl.horizontal||!u&&!Zn(L)||u&&(zl[L]||(Y=L,Yn.Arabic(Y)||Yn[\"Arabic Supplement\"](Y)||Yn[\"Arabic Extended-A\"](Y)||Yn[\"Arabic Presentation Forms-A\"](Y)||Yn[\"Arabic Presentation Forms-B\"](Y))));if(S.imageName){var R=n[S.imageName];if(!R)continue;O=S.imageName,t.iconsInText=t.iconsInText||!0,I=R.paddedRect;var F=R.displaySize;S.scale=24*S.scale/f,P={width:F[0],height:F[1],left:1,top:-3,advance:D?F[1]:F[0]};var B=24-F[1]*S.scale;C=w+B,z=P.advance;var N=D?F[0]*S.scale-24*_:F[1]*S.scale-24*_;N>0&&N>A&&(A=N)}else{var j=r[S.fontStack],U=j&&j[L];if(U&&U.rect)I=U.rect,P=U.metrics;else{var V=e[S.fontStack],H=V&&V[L];if(!H)continue;P=H.metrics}C=24*(_-S.scale)}D?(t.verticalizable=!0,k.push({glyph:L,imageName:O,x:h,y:p+C,vertical:D,scale:S.scale,fontStack:S.fontStack,sectionIndex:E,metrics:P,rect:I}),h+=z*S.scale+c):(k.push({glyph:L,imageName:O,x:h,y:p+C,vertical:D,scale:S.scale,fontStack:S.fontStack,sectionIndex:E,metrics:P,rect:I}),h+=P.advance*S.scale+c)}if(0!==k.length){var q=h-c;d=Math.max(q,d),Vl(k,0,k.length-1,g,A)}h=0;var G=a*_+A;T.lineOffset=Math.max(A,w),p+=G,m=Math.max(G,m),++v}else p+=a,++v}var Y;var W=p- -17,X=Ul(o),Z=X.horizontalAlign,J=X.verticalAlign;(function(t,e,r,n,i,a,o,s,l){var c=(e-r)*i,u=0;u=a!==o?-s*n- -17:(-n*l+.5)*o;for(var f=0,h=t;f<h.length;f+=1)for(var p=h[f],d=0,m=p.positionedGlyphs;d<m.length;d+=1){var g=m[d];g.x+=c,g.y+=u}})(t.positionedLines,g,Z,J,d,m,a,W,i.length),t.top+=-J*W,t.bottom=t.top+W,t.left+=-Z*d,t.right=t.left+d}(C,e,r,n,g,o,s,l,f,c,h,m),!function(t){for(var e=0,r=t;e<r.length;e+=1){if(0!==r[e].positionedGlyphs.length)return!1}return!0}(L)&&C}Il.fromFeature=function(t,e){for(var r=new Il,n=0;n<t.sections.length;n++){var i=t.sections[n];i.image?r.addImageSection(i):r.addTextSection(i,e)}return r},Il.prototype.length=function(){return this.text.length},Il.prototype.getSection=function(t){return this.sections[this.sectionIndex[t]]},Il.prototype.getSectionIndex=function(t){return this.sectionIndex[t]},Il.prototype.getCharCode=function(t){return this.text.charCodeAt(t)},Il.prototype.verticalizePunctuation=function(){this.text=function(t){for(var e=\"\",r=0;r<t.length;r++){var n=t.charCodeAt(r+1)||null,i=t.charCodeAt(r-1)||null;(!n||!Jn(n)||rl[t[r+1]])&&(!i||!Jn(i)||rl[t[r-1]])&&rl[t[r]]?e+=rl[t[r]]:e+=t[r]}return e}(this.text)},Il.prototype.trim=function(){for(var t=0,e=0;e<this.text.length&&zl[this.text.charCodeAt(e)];e++)t++;for(var 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e=this.data,r=this.compare,n=this.length>>1,i=e[t];t<n;){var a=1+(t<<1),o=e[a],s=a+1;if(s<this.length&&r(e[s],o)<0&&(a=s,o=e[s]),r(o,i)>=0)break;e[t]=o,t=a}e[t]=i};var pc=Number.POSITIVE_INFINITY;function dc(t,e){return e[1]!==pc?function(t,e,r){var n=0,i=0;switch(e=Math.abs(e),r=Math.abs(r),t){case\"top-right\":case\"top-left\":case\"top\":i=r-7;break;case\"bottom-right\":case\"bottom-left\":case\"bottom\":i=7-r}switch(t){case\"top-right\":case\"bottom-right\":case\"right\":n=-e;break;case\"top-left\":case\"bottom-left\":case\"left\":n=e}return[n,i]}(t,e[0],e[1]):function(t,e){var r=0,n=0;e<0&&(e=0);var i=e/Math.sqrt(2);switch(t){case\"top-right\":case\"top-left\":n=i-7;break;case\"bottom-right\":case\"bottom-left\":n=7-i;break;case\"bottom\":n=7-e;break;case\"top\":n=e-7}switch(t){case\"top-right\":case\"bottom-right\":r=-i;break;case\"top-left\":case\"bottom-left\":r=i;break;case\"left\":r=e;break;case\"right\":r=-e}return[r,n]}(t,e[0])}function mc(t){switch(t){case\"right\":case\"top-right\":case\"bottom-right\":return\"right\";case\"left\":case\"top-left\":case\"bottom-left\":return\"left\"}return\"center\"}function gc(t,e,r,n,a,o,s,l,c,u,f,h,p,d,m){var g=function(t,e,r,n,a,o,s,l){for(var c=n.layout.get(\"text-rotate\").evaluate(o,{})*Math.PI/180,u=[],f=0,h=e.positionedLines;f<h.length;f+=1)for(var p=h[f],d=0,m=p.positionedGlyphs;d<m.length;d+=1){var g=m[d];if(g.rect){var v=g.rect||{},y=4,x=!0,b=1,_=0,w=(a||l)&&g.vertical,T=g.metrics.advance*g.scale/2;if(l&&e.verticalizable){var k=24*(g.scale-1),A=(24-g.metrics.width*g.scale)/2;_=p.lineOffset/2-(g.imageName?-A:k)}if(g.imageName){var M=s[g.imageName];x=M.sdf,y=1/(b=M.pixelRatio)}var S=a?[g.x+T,g.y]:[0,0],E=a?[0,0]:[g.x+T+r[0],g.y+r[1]-_],L=[0,0];w&&(L=E,E=[0,0]);var C=(g.metrics.left-y)*g.scale-T+E[0],P=(-g.metrics.top-y)*g.scale+E[1],I=C+v.w*g.scale/b,O=P+v.h*g.scale/b,z=new i(C,P),D=new i(I,P),R=new i(C,O),F=new i(I,O);if(w){var B=new i(-T,T- -17),N=-Math.PI/2,j=12-T,U=g.imageName?j:0,V=new i(22-j,-U),H=new(Function.prototype.bind.apply(i,[null].concat(L)));z._rotateAround(N,B)._add(V)._add(H),D._rotateAround(N,B)._add(V)._add(H),R._rotateAround(N,B)._add(V)._add(H),F._rotateAround(N,B)._add(V)._add(H)}if(c){var q=Math.sin(c),G=Math.cos(c),Y=[G,-q,q,G];z._matMult(Y),D._matMult(Y),R._matMult(Y),F._matMult(Y)}var W=new i(0,0),X=new i(0,0);u.push({tl:z,tr:D,bl:R,br:F,tex:v,writingMode:e.writingMode,glyphOffset:S,sectionIndex:g.sectionIndex,isSDF:x,pixelOffsetTL:W,pixelOffsetBR:X,minFontScaleX:0,minFontScaleY:0})}}return u}(0,r,l,a,o,s,n,t.allowVerticalPlacement),v=t.textSizeData,y=null;\"source\"===v.kind?(y=[128*a.layout.get(\"text-size\").evaluate(s,{})])[0]>32640&&_(t.layerIds[0]+': Value for \"text-size\" is >= 255. Reduce your \"text-size\".'):\"composite\"===v.kind&&((y=[128*d.compositeTextSizes[0].evaluate(s,{},m),128*d.compositeTextSizes[1].evaluate(s,{},m)])[0]>32640||y[1]>32640)&&_(t.layerIds[0]+': Value for \"text-size\" is >= 255. Reduce your \"text-size\".'),t.addSymbols(t.text,g,y,l,o,s,u,e,c.lineStartIndex,c.lineLength,p,m);for(var x=0,b=f;x<b.length;x+=1){h[b[x]]=t.text.placedSymbolArray.length-1}return 4*g.length}function vc(t){for(var e in t)return t[e];return null}function yc(t,e,r,n){var i=t.compareText;if(e in i){for(var a=i[e],o=a.length-1;o>=0;o--)if(n.dist(a[o])<r)return!0}else i[e]=[];return i[e].push(n),!1}var xc=Ls.VectorTileFeature.types,bc=[{name:\"a_fade_opacity\",components:1,type:\"Uint8\",offset:0}];function _c(t,e,r,n,i,a,o,s,l,c,u,f,h){var p=s?Math.min(32640,Math.round(s[0])):0,d=s?Math.min(32640,Math.round(s[1])):0;t.emplaceBack(e,r,Math.round(32*n),Math.round(32*i),a,o,(p<<1)+(l?1:0),d,16*c,16*u,256*f,256*h)}function wc(t,e,r){t.emplaceBack(e.x,e.y,r),t.emplaceBack(e.x,e.y,r),t.emplaceBack(e.x,e.y,r),t.emplaceBack(e.x,e.y,r)}function Tc(t){for(var e=0,r=t.sections;e<r.length;e+=1){if($n(r[e].text))return!0}return!1}var kc=function(t){this.layoutVertexArray=new Ni,this.indexArray=new Yi,this.programConfigurations=t,this.segments=new pa,this.dynamicLayoutVertexArray=new ji,this.opacityVertexArray=new Ui,this.placedSymbolArray=new aa};kc.prototype.isEmpty=function(){return 0===this.layoutVertexArray.length&&0===this.indexArray.length&&0===this.dynamicLayoutVertexArray.length&&0===this.opacityVertexArray.length},kc.prototype.upload=function(t,e,r,n){this.isEmpty()||(r&&(this.layoutVertexBuffer=t.createVertexBuffer(this.layoutVertexArray,Js.members),this.indexBuffer=t.createIndexBuffer(this.indexArray,e),this.dynamicLayoutVertexBuffer=t.createVertexBuffer(this.dynamicLayoutVertexArray,Ks.members,!0),this.opacityVertexBuffer=t.createVertexBuffer(this.opacityVertexArray,bc,!0),this.opacityVertexBuffer.itemSize=1),(r||n)&&this.programConfigurations.upload(t))},kc.prototype.destroy=function(){this.layoutVertexBuffer&&(this.layoutVertexBuffer.destroy(),this.indexBuffer.destroy(),this.programConfigurations.destroy(),this.segments.destroy(),this.dynamicLayoutVertexBuffer.destroy(),this.opacityVertexBuffer.destroy())},Nn(\"SymbolBuffers\",kc);var Ac=function(t,e,r){this.layoutVertexArray=new t,this.layoutAttributes=e,this.indexArray=new r,this.segments=new pa,this.collisionVertexArray=new Gi};Ac.prototype.upload=function(t){this.layoutVertexBuffer=t.createVertexBuffer(this.layoutVertexArray,this.layoutAttributes),this.indexBuffer=t.createIndexBuffer(this.indexArray),this.collisionVertexBuffer=t.createVertexBuffer(this.collisionVertexArray,Qs.members,!0)},Ac.prototype.destroy=function(){this.layoutVertexBuffer&&(this.layoutVertexBuffer.destroy(),this.indexBuffer.destroy(),this.segments.destroy(),this.collisionVertexBuffer.destroy())},Nn(\"CollisionBuffers\",Ac);var Mc=function(t){this.collisionBoxArray=t.collisionBoxArray,this.zoom=t.zoom,this.overscaling=t.overscaling,this.layers=t.layers,this.layerIds=this.layers.map((function(t){return t.id})),this.index=t.index,this.pixelRatio=t.pixelRatio,this.sourceLayerIndex=t.sourceLayerIndex,this.hasPattern=!1,this.hasRTLText=!1,this.sortKeyRanges=[],this.collisionCircleArray=[],this.placementInvProjMatrix=ho([]),this.placementViewportMatrix=ho([]);var e=this.layers[0]._unevaluatedLayout._values;this.textSizeData=Gl(this.zoom,e[\"text-size\"]),this.iconSizeData=Gl(this.zoom,e[\"icon-size\"]);var r=this.layers[0].layout,n=r.get(\"symbol-sort-key\"),i=r.get(\"symbol-z-order\");this.sortFeaturesByKey=\"viewport-y\"!==i&&void 0!==n.constantOr(1);var a=\"viewport-y\"===i||\"auto\"===i&&!this.sortFeaturesByKey;this.sortFeaturesByY=a&&(r.get(\"text-allow-overlap\")||r.get(\"icon-allow-overlap\")||r.get(\"text-ignore-placement\")||r.get(\"icon-ignore-placement\")),\"point\"===r.get(\"symbol-placement\")&&(this.writingModes=r.get(\"text-writing-mode\").map((function(t){return Cl[t]}))),this.stateDependentLayerIds=this.layers.filter((function(t){return t.isStateDependent()})).map((function(t){return t.id})),this.sourceID=t.sourceID};Mc.prototype.createArrays=function(){this.text=new kc(new Ua(Js.members,this.layers,this.zoom,(function(t){return/^text/.test(t)}))),this.icon=new kc(new Ua(Js.members,this.layers,this.zoom,(function(t){return/^icon/.test(t)}))),this.glyphOffsetArray=new la,this.lineVertexArray=new ca,this.symbolInstances=new sa},Mc.prototype.calculateGlyphDependencies=function(t,e,r,n,i){for(var a=0;a<t.length;a++)if(e[t.charCodeAt(a)]=!0,(r||n)&&i){var o=rl[t.charAt(a)];o&&(e[o.charCodeAt(0)]=!0)}},Mc.prototype.populate=function(t,e,r){var n=this.layers[0],i=n.layout,a=i.get(\"text-font\"),o=i.get(\"text-field\"),s=i.get(\"icon-image\"),l=(\"constant\"!==o.value.kind||o.value.value instanceof ne&&!o.value.value.isEmpty()||o.value.value.toString().length>0)&&(\"constant\"!==a.value.kind||a.value.value.length>0),c=\"constant\"!==s.value.kind||!!s.value.value||Object.keys(s.parameters).length>0,u=i.get(\"symbol-sort-key\");if(this.features=[],l||c){for(var f=e.iconDependencies,h=e.glyphDependencies,p=e.availableImages,d=new pi(this.zoom),m=0,g=t;m<g.length;m+=1){var v=g[m],y=v.feature,x=v.id,b=v.index,_=v.sourceLayerIndex,w=n._featureFilter.needGeometry,T={type:y.type,id:x,properties:y.properties,geometry:w?Ya(y):[]};if(n._featureFilter.filter(d,T,r)){w||(T.geometry=Ya(y));var k=void 0;if(l){var A=n.getValueAndResolveTokens(\"text-field\",T,r,p),M=ne.factory(A);Tc(M)&&(this.hasRTLText=!0),(!this.hasRTLText||\"unavailable\"===ui()||this.hasRTLText&&hi.isParsed())&&(k=el(M,n,T))}var S=void 0;if(c){var E=n.getValueAndResolveTokens(\"icon-image\",T,r,p);S=E instanceof ie?E:ie.fromString(E)}if(k||S){var L=this.sortFeaturesByKey?u.evaluate(T,{},r):void 0,C={id:x,text:k,icon:S,index:b,sourceLayerIndex:_,geometry:Ya(y),properties:y.properties,type:xc[y.type],sortKey:L};if(this.features.push(C),S&&(f[S.name]=!0),k){var P=a.evaluate(T,{},r).join(\",\"),I=\"map\"===i.get(\"text-rotation-alignment\")&&\"point\"!==i.get(\"symbol-placement\");this.allowVerticalPlacement=this.writingModes&&this.writingModes.indexOf(Cl.vertical)>=0;for(var O=0,z=k.sections;O<z.length;O+=1){var D=z[O];if(D.image)f[D.image.name]=!0;else{var R=Wn(k.toString()),F=D.fontStack||P,B=h[F]=h[F]||{};this.calculateGlyphDependencies(D.text,B,I,this.allowVerticalPlacement,R)}}}}}}\"line\"===i.get(\"symbol-placement\")&&(this.features=function(t){var e={},r={},n=[],i=0;function a(e){n.push(t[e]),i++}function o(t,e,i){var a=r[t];return delete r[t],r[e]=a,n[a].geometry[0].pop(),n[a].geometry[0]=n[a].geometry[0].concat(i[0]),a}function s(t,r,i){var a=e[r];return delete e[r],e[t]=a,n[a].geometry[0].shift(),n[a].geometry[0]=i[0].concat(n[a].geometry[0]),a}function l(t,e,r){var n=r?e[0][e[0].length-1]:e[0][0];return t+\":\"+n.x+\":\"+n.y}for(var c=0;c<t.length;c++){var u=t[c],f=u.geometry,h=u.text?u.text.toString():null;if(h){var p=l(h,f),d=l(h,f,!0);if(p in r&&d in e&&r[p]!==e[d]){var m=s(p,d,f),g=o(p,d,n[m].geometry);delete e[p],delete r[d],r[l(h,n[g].geometry,!0)]=g,n[m].geometry=null}else p in r?o(p,d,f):d in e?s(p,d,f):(a(c),e[p]=i-1,r[d]=i-1)}else a(c)}return n.filter((function(t){return t.geometry}))}(this.features)),this.sortFeaturesByKey&&this.features.sort((function(t,e){return t.sortKey-e.sortKey}))}},Mc.prototype.update=function(t,e,r){this.stateDependentLayers.length&&(this.text.programConfigurations.updatePaintArrays(t,e,this.layers,r),this.icon.programConfigurations.updatePaintArrays(t,e,this.layers,r))},Mc.prototype.isEmpty=function(){return 0===this.symbolInstances.length&&!this.hasRTLText},Mc.prototype.uploadPending=function(){return!this.uploaded||this.text.programConfigurations.needsUpload||this.icon.programConfigurations.needsUpload},Mc.prototype.upload=function(t){!this.uploaded&&this.hasDebugData()&&(this.textCollisionBox.upload(t),this.iconCollisionBox.upload(t)),this.text.upload(t,this.sortFeaturesByY,!this.uploaded,this.text.programConfigurations.needsUpload),this.icon.upload(t,this.sortFeaturesByY,!this.uploaded,this.icon.programConfigurations.needsUpload),this.uploaded=!0},Mc.prototype.destroyDebugData=function(){this.textCollisionBox.destroy(),this.iconCollisionBox.destroy()},Mc.prototype.destroy=function(){this.text.destroy(),this.icon.destroy(),this.hasDebugData()&&this.destroyDebugData()},Mc.prototype.addToLineVertexArray=function(t,e){var r=this.lineVertexArray.length;if(void 0!==t.segment){for(var n=t.dist(e[t.segment+1]),i=t.dist(e[t.segment]),a={},o=t.segment+1;o<e.length;o++)a[o]={x:e[o].x,y:e[o].y,tileUnitDistanceFromAnchor:n},o<e.length-1&&(n+=e[o+1].dist(e[o]));for(var s=t.segment||0;s>=0;s--)a[s]={x:e[s].x,y:e[s].y,tileUnitDistanceFromAnchor:i},s>0&&(i+=e[s-1].dist(e[s]));for(var l=0;l<e.length;l++){var c=a[l];this.lineVertexArray.emplaceBack(c.x,c.y,c.tileUnitDistanceFromAnchor)}}return{lineStartIndex:r,lineLength:this.lineVertexArray.length-r}},Mc.prototype.addSymbols=function(t,e,r,n,i,a,o,s,l,c,u,f){for(var h=t.indexArray,p=t.layoutVertexArray,d=t.segments.prepareSegment(4*e.length,p,h,a.sortKey),m=this.glyphOffsetArray.length,g=d.vertexLength,v=this.allowVerticalPlacement&&o===Cl.vertical?Math.PI/2:0,y=a.text&&a.text.sections,x=0;x<e.length;x++){var b=e[x],_=b.tl,w=b.tr,T=b.bl,k=b.br,A=b.tex,M=b.pixelOffsetTL,S=b.pixelOffsetBR,E=b.minFontScaleX,L=b.minFontScaleY,C=b.glyphOffset,P=b.isSDF,I=b.sectionIndex,O=d.vertexLength,z=C[1];_c(p,s.x,s.y,_.x,z+_.y,A.x,A.y,r,P,M.x,M.y,E,L),_c(p,s.x,s.y,w.x,z+w.y,A.x+A.w,A.y,r,P,S.x,M.y,E,L),_c(p,s.x,s.y,T.x,z+T.y,A.x,A.y+A.h,r,P,M.x,S.y,E,L),_c(p,s.x,s.y,k.x,z+k.y,A.x+A.w,A.y+A.h,r,P,S.x,S.y,E,L),wc(t.dynamicLayoutVertexArray,s,v),h.emplaceBack(O,O+1,O+2),h.emplaceBack(O+1,O+2,O+3),d.vertexLength+=4,d.primitiveLength+=2,this.glyphOffsetArray.emplaceBack(C[0]),x!==e.length-1&&I===e[x+1].sectionIndex||t.programConfigurations.populatePaintArrays(p.length,a,a.index,{},f,y&&y[I])}t.placedSymbolArray.emplaceBack(s.x,s.y,m,this.glyphOffsetArray.length-m,g,l,c,s.segment,r?r[0]:0,r?r[1]:0,n[0],n[1],o,0,!1,0,u)},Mc.prototype._addCollisionDebugVertex=function(t,e,r,n,i,a){return e.emplaceBack(0,0),t.emplaceBack(r.x,r.y,n,i,Math.round(a.x),Math.round(a.y))},Mc.prototype.addCollisionDebugVertices=function(t,e,r,n,a,o,s){var l=a.segments.prepareSegment(4,a.layoutVertexArray,a.indexArray),c=l.vertexLength,u=a.layoutVertexArray,f=a.collisionVertexArray,h=s.anchorX,p=s.anchorY;this._addCollisionDebugVertex(u,f,o,h,p,new i(t,e)),this._addCollisionDebugVertex(u,f,o,h,p,new i(r,e)),this._addCollisionDebugVertex(u,f,o,h,p,new i(r,n)),this._addCollisionDebugVertex(u,f,o,h,p,new i(t,n)),l.vertexLength+=4;var d=a.indexArray;d.emplaceBack(c,c+1),d.emplaceBack(c+1,c+2),d.emplaceBack(c+2,c+3),d.emplaceBack(c+3,c),l.primitiveLength+=4},Mc.prototype.addDebugCollisionBoxes=function(t,e,r,n){for(var i=t;i<e;i++){var a=this.collisionBoxArray.get(i),o=a.x1,s=a.y1,l=a.x2,c=a.y2;this.addCollisionDebugVertices(o,s,l,c,n?this.textCollisionBox:this.iconCollisionBox,a.anchorPoint,r)}},Mc.prototype.generateCollisionDebugBuffers=function(){this.hasDebugData()&&this.destroyDebugData(),this.textCollisionBox=new Ac(Hi,$s.members,Qi),this.iconCollisionBox=new Ac(Hi,$s.members,Qi);for(var t=0;t<this.symbolInstances.length;t++){var e=this.symbolInstances.get(t);this.addDebugCollisionBoxes(e.textBoxStartIndex,e.textBoxEndIndex,e,!0),this.addDebugCollisionBoxes(e.verticalTextBoxStartIndex,e.verticalTextBoxEndIndex,e,!0),this.addDebugCollisionBoxes(e.iconBoxStartIndex,e.iconBoxEndIndex,e,!1),this.addDebugCollisionBoxes(e.verticalIconBoxStartIndex,e.verticalIconBoxEndIndex,e,!1)}},Mc.prototype._deserializeCollisionBoxesForSymbol=function(t,e,r,n,i,a,o,s,l){for(var c={},u=e;u<r;u++){var f=t.get(u);c.textBox={x1:f.x1,y1:f.y1,x2:f.x2,y2:f.y2,anchorPointX:f.anchorPointX,anchorPointY:f.anchorPointY},c.textFeatureIndex=f.featureIndex;break}for(var h=n;h<i;h++){var p=t.get(h);c.verticalTextBox={x1:p.x1,y1:p.y1,x2:p.x2,y2:p.y2,anchorPointX:p.anchorPointX,anchorPointY:p.anchorPointY},c.verticalTextFeatureIndex=p.featureIndex;break}for(var d=a;d<o;d++){var m=t.get(d);c.iconBox={x1:m.x1,y1:m.y1,x2:m.x2,y2:m.y2,anchorPointX:m.anchorPointX,anchorPointY:m.anchorPointY},c.iconFeatureIndex=m.featureIndex;break}for(var g=s;g<l;g++){var v=t.get(g);c.verticalIconBox={x1:v.x1,y1:v.y1,x2:v.x2,y2:v.y2,anchorPointX:v.anchorPointX,anchorPointY:v.anchorPointY},c.verticalIconFeatureIndex=v.featureIndex;break}return c},Mc.prototype.deserializeCollisionBoxes=function(t){this.collisionArrays=[];for(var e=0;e<this.symbolInstances.length;e++){var r=this.symbolInstances.get(e);this.collisionArrays.push(this._deserializeCollisionBoxesForSymbol(t,r.textBoxStartIndex,r.textBoxEndIndex,r.verticalTextBoxStartIndex,r.verticalTextBoxEndIndex,r.iconBoxStartIndex,r.iconBoxEndIndex,r.verticalIconBoxStartIndex,r.verticalIconBoxEndIndex))}},Mc.prototype.hasTextData=function(){return this.text.segments.get().length>0},Mc.prototype.hasIconData=function(){return this.icon.segments.get().length>0},Mc.prototype.hasDebugData=function(){return this.textCollisionBox&&this.iconCollisionBox},Mc.prototype.hasTextCollisionBoxData=function(){return this.hasDebugData()&&this.textCollisionBox.segments.get().length>0},Mc.prototype.hasIconCollisionBoxData=function(){return this.hasDebugData()&&this.iconCollisionBox.segments.get().length>0},Mc.prototype.addIndicesForPlacedSymbol=function(t,e){for(var r=t.placedSymbolArray.get(e),n=r.vertexStartIndex+4*r.numGlyphs,i=r.vertexStartIndex;i<n;i+=4)t.indexArray.emplaceBack(i,i+1,i+2),t.indexArray.emplaceBack(i+1,i+2,i+3)},Mc.prototype.getSortedSymbolIndexes=function(t){if(this.sortedAngle===t&&void 0!==this.symbolInstanceIndexes)return this.symbolInstanceIndexes;for(var e=Math.sin(t),r=Math.cos(t),n=[],i=[],a=[],o=0;o<this.symbolInstances.length;++o){a.push(o);var s=this.symbolInstances.get(o);n.push(0|Math.round(e*s.anchorX+r*s.anchorY)),i.push(s.featureIndex)}return a.sort((function(t,e){return n[t]-n[e]||i[e]-i[t]})),a},Mc.prototype.addToSortKeyRanges=function(t,e){var r=this.sortKeyRanges[this.sortKeyRanges.length-1];r&&r.sortKey===e?r.symbolInstanceEnd=t+1:this.sortKeyRanges.push({sortKey:e,symbolInstanceStart:t,symbolInstanceEnd:t+1})},Mc.prototype.sortFeatures=function(t){var e=this;if(this.sortFeaturesByY&&this.sortedAngle!==t&&!(this.text.segments.get().length>1||this.icon.segments.get().length>1)){this.symbolInstanceIndexes=this.getSortedSymbolIndexes(t),this.sortedAngle=t,this.text.indexArray.clear(),this.icon.indexArray.clear(),this.featureSortOrder=[];for(var r=0,n=this.symbolInstanceIndexes;r<n.length;r+=1){var i=n[r],a=this.symbolInstances.get(i);this.featureSortOrder.push(a.featureIndex),[a.rightJustifiedTextSymbolIndex,a.centerJustifiedTextSymbolIndex,a.leftJustifiedTextSymbolIndex].forEach((function(t,r,n){t>=0&&n.indexOf(t)===r&&e.addIndicesForPlacedSymbol(e.text,t)})),a.verticalPlacedTextSymbolIndex>=0&&this.addIndicesForPlacedSymbol(this.text,a.verticalPlacedTextSymbolIndex),a.placedIconSymbolIndex>=0&&this.addIndicesForPlacedSymbol(this.icon,a.placedIconSymbolIndex),a.verticalPlacedIconSymbolIndex>=0&&this.addIndicesForPlacedSymbol(this.icon,a.verticalPlacedIconSymbolIndex)}this.text.indexBuffer&&this.text.indexBuffer.updateData(this.text.indexArray),this.icon.indexBuffer&&this.icon.indexBuffer.updateData(this.icon.indexArray)}},Nn(\"SymbolBucket\",Mc,{omit:[\"layers\",\"collisionBoxArray\",\"features\",\"compareText\"]}),Mc.MAX_GLYPHS=65535,Mc.addDynamicAttributes=wc;var Sc=new Si({\"symbol-placement\":new wi(Lt.layout_symbol[\"symbol-placement\"]),\"symbol-spacing\":new wi(Lt.layout_symbol[\"symbol-spacing\"]),\"symbol-avoid-edges\":new wi(Lt.layout_symbol[\"symbol-avoid-edges\"]),\"symbol-sort-key\":new Ti(Lt.layout_symbol[\"symbol-sort-key\"]),\"symbol-z-order\":new wi(Lt.layout_symbol[\"symbol-z-order\"]),\"icon-allow-overlap\":new wi(Lt.layout_symbol[\"icon-allow-overlap\"]),\"icon-ignore-placement\":new wi(Lt.layout_symbol[\"icon-ignore-placement\"]),\"icon-optional\":new wi(Lt.layout_symbol[\"icon-optional\"]),\"icon-rotation-alignment\":new wi(Lt.layout_symbol[\"icon-rotation-alignment\"]),\"icon-size\":new Ti(Lt.layout_symbol[\"icon-size\"]),\"icon-text-fit\":new wi(Lt.layout_symbol[\"icon-text-fit\"]),\"icon-text-fit-padding\":new wi(Lt.layout_symbol[\"icon-text-fit-padding\"]),\"icon-image\":new Ti(Lt.layout_symbol[\"icon-image\"]),\"icon-rotate\":new Ti(Lt.layout_symbol[\"icon-rotate\"]),\"icon-padding\":new wi(Lt.layout_symbol[\"icon-padding\"]),\"icon-keep-upright\":new wi(Lt.layout_symbol[\"icon-keep-upright\"]),\"icon-offset\":new Ti(Lt.layout_symbol[\"icon-offset\"]),\"icon-anchor\":new Ti(Lt.layout_symbol[\"icon-anchor\"]),\"icon-pitch-alignment\":new wi(Lt.layout_symbol[\"icon-pitch-alignment\"]),\"text-pitch-alignment\":new wi(Lt.layout_symbol[\"text-pitch-alignment\"]),\"text-rotation-alignment\":new wi(Lt.layout_symbol[\"text-rotation-alignment\"]),\"text-field\":new Ti(Lt.layout_symbol[\"text-field\"]),\"text-font\":new Ti(Lt.layout_symbol[\"text-font\"]),\"text-size\":new Ti(Lt.layout_symbol[\"text-size\"]),\"text-max-width\":new Ti(Lt.layout_symbol[\"text-max-width\"]),\"text-line-height\":new wi(Lt.layout_symbol[\"text-line-height\"]),\"text-letter-spacing\":new Ti(Lt.layout_symbol[\"text-letter-spacing\"]),\"text-justify\":new Ti(Lt.layout_symbol[\"text-justify\"]),\"text-radial-offset\":new Ti(Lt.layout_symbol[\"text-radial-offset\"]),\"text-variable-anchor\":new wi(Lt.layout_symbol[\"text-variable-anchor\"]),\"text-anchor\":new Ti(Lt.layout_symbol[\"text-anchor\"]),\"text-max-angle\":new wi(Lt.layout_symbol[\"text-max-angle\"]),\"text-writing-mode\":new wi(Lt.layout_symbol[\"text-writing-mode\"]),\"text-rotate\":new Ti(Lt.layout_symbol[\"text-rotate\"]),\"text-padding\":new wi(Lt.layout_symbol[\"text-padding\"]),\"text-keep-upright\":new wi(Lt.layout_symbol[\"text-keep-upright\"]),\"text-transform\":new Ti(Lt.layout_symbol[\"text-transform\"]),\"text-offset\":new Ti(Lt.layout_symbol[\"text-offset\"]),\"text-allow-overlap\":new wi(Lt.layout_symbol[\"text-allow-overlap\"]),\"text-ignore-placement\":new wi(Lt.layout_symbol[\"text-ignore-placement\"]),\"text-optional\":new wi(Lt.layout_symbol[\"text-optional\"])}),Ec={paint:new Si({\"icon-opacity\":new Ti(Lt.paint_symbol[\"icon-opacity\"]),\"icon-color\":new Ti(Lt.paint_symbol[\"icon-color\"]),\"icon-halo-color\":new Ti(Lt.paint_symbol[\"icon-halo-color\"]),\"icon-halo-width\":new Ti(Lt.paint_symbol[\"icon-halo-width\"]),\"icon-halo-blur\":new Ti(Lt.paint_symbol[\"icon-halo-blur\"]),\"icon-translate\":new wi(Lt.paint_symbol[\"icon-translate\"]),\"icon-translate-anchor\":new wi(Lt.paint_symbol[\"icon-translate-anchor\"]),\"text-opacity\":new Ti(Lt.paint_symbol[\"text-opacity\"]),\"text-color\":new Ti(Lt.paint_symbol[\"text-color\"],{runtimeType:Ut,getOverride:function(t){return t.textColor},hasOverride:function(t){return!!t.textColor}}),\"text-halo-color\":new Ti(Lt.paint_symbol[\"text-halo-color\"]),\"text-halo-width\":new Ti(Lt.paint_symbol[\"text-halo-width\"]),\"text-halo-blur\":new Ti(Lt.paint_symbol[\"text-halo-blur\"]),\"text-translate\":new wi(Lt.paint_symbol[\"text-translate\"]),\"text-translate-anchor\":new wi(Lt.paint_symbol[\"text-translate-anchor\"])}),layout:Sc},Lc=function(t){this.type=t.property.overrides?t.property.overrides.runtimeType:Ft,this.defaultValue=t};Lc.prototype.evaluate=function(t){if(t.formattedSection){var e=this.defaultValue.property.overrides;if(e&&e.hasOverride(t.formattedSection))return e.getOverride(t.formattedSection)}return t.feature&&t.featureState?this.defaultValue.evaluate(t.feature,t.featureState):this.defaultValue.property.specification.default},Lc.prototype.eachChild=function(t){this.defaultValue.isConstant()||t(this.defaultValue.value._styleExpression.expression)},Lc.prototype.outputDefined=function(){return!1},Lc.prototype.serialize=function(){return null},Nn(\"FormatSectionOverride\",Lc,{omit:[\"defaultValue\"]});var Cc=function(t){function e(e){t.call(this,e,Ec)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.recalculate=function(e,r){if(t.prototype.recalculate.call(this,e,r),\"auto\"===this.layout.get(\"icon-rotation-alignment\")&&(\"point\"!==this.layout.get(\"symbol-placement\")?this.layout._values[\"icon-rotation-alignment\"]=\"map\":this.layout._values[\"icon-rotation-alignment\"]=\"viewport\"),\"auto\"===this.layout.get(\"text-rotation-alignment\")&&(\"point\"!==this.layout.get(\"symbol-placement\")?this.layout._values[\"text-rotation-alignment\"]=\"map\":this.layout._values[\"text-rotation-alignment\"]=\"viewport\"),\"auto\"===this.layout.get(\"text-pitch-alignment\")&&(this.layout._values[\"text-pitch-alignment\"]=this.layout.get(\"text-rotation-alignment\")),\"auto\"===this.layout.get(\"icon-pitch-alignment\")&&(this.layout._values[\"icon-pitch-alignment\"]=this.layout.get(\"icon-rotation-alignment\")),\"point\"===this.layout.get(\"symbol-placement\")){var n=this.layout.get(\"text-writing-mode\");if(n){for(var i=[],a=0,o=n;a<o.length;a+=1){var s=o[a];i.indexOf(s)<0&&i.push(s)}this.layout._values[\"text-writing-mode\"]=i}else this.layout._values[\"text-writing-mode\"]=[\"horizontal\"]}this._setPaintOverrides()},e.prototype.getValueAndResolveTokens=function(t,e,r,n){var i=this.layout.get(t).evaluate(e,{},r,n),a=this._unevaluatedLayout._values[t];return a.isDataDriven()||Yr(a.value)||!i?i:function(t,e){return e.replace(/{([^{}]+)}/g,(function(e,r){return r in t?String(t[r]):\"\"}))}(e.properties,i)},e.prototype.createBucket=function(t){return new Mc(t)},e.prototype.queryRadius=function(){return 0},e.prototype.queryIntersectsFeature=function(){return!1},e.prototype._setPaintOverrides=function(){for(var t=0,r=Ec.paint.overridableProperties;t<r.length;t+=1){var n=r[t];if(e.hasPaintOverride(this.layout,n)){var i=this.paint.get(n),a=new Lc(i),o=new Gr(a,i.property.specification),s=null;s=\"constant\"===i.value.kind||\"source\"===i.value.kind?new Xr(\"source\",o):new Zr(\"composite\",o,i.value.zoomStops,i.value._interpolationType),this.paint._values[n]=new bi(i.property,s,i.parameters)}}},e.prototype._handleOverridablePaintPropertyUpdate=function(t,r,n){return!(!this.layout||r.isDataDriven()||n.isDataDriven())&&e.hasPaintOverride(this.layout,t)},e.hasPaintOverride=function(t,e){var r=t.get(\"text-field\"),n=Ec.paint.properties[e],i=!1,a=function(t){for(var e=0,r=t;e<r.length;e+=1){var a=r[e];if(n.overrides&&n.overrides.hasOverride(a))return void(i=!0)}};if(\"constant\"===r.value.kind&&r.value.value instanceof ne)a(r.value.value.sections);else if(\"source\"===r.value.kind){var o=function(t){if(!i)if(t instanceof ce&&se(t.value)===Gt){var e=t.value;a(e.sections)}else t instanceof pe?a(t.sections):t.eachChild(o)},s=r.value;s._styleExpression&&o(s._styleExpression.expression)}return i},e}(Ei),Pc={paint:new Si({\"background-color\":new wi(Lt.paint_background[\"background-color\"]),\"background-pattern\":new Ai(Lt.paint_background[\"background-pattern\"]),\"background-opacity\":new wi(Lt.paint_background[\"background-opacity\"])})},Ic=function(t){function e(e){t.call(this,e,Pc)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e}(Ei),Oc={paint:new Si({\"raster-opacity\":new wi(Lt.paint_raster[\"raster-opacity\"]),\"raster-hue-rotate\":new wi(Lt.paint_raster[\"raster-hue-rotate\"]),\"raster-brightness-min\":new wi(Lt.paint_raster[\"raster-brightness-min\"]),\"raster-brightness-max\":new wi(Lt.paint_raster[\"raster-brightness-max\"]),\"raster-saturation\":new wi(Lt.paint_raster[\"raster-saturation\"]),\"raster-contrast\":new wi(Lt.paint_raster[\"raster-contrast\"]),\"raster-resampling\":new wi(Lt.paint_raster[\"raster-resampling\"]),\"raster-fade-duration\":new wi(Lt.paint_raster[\"raster-fade-duration\"])})},zc=function(t){function e(e){t.call(this,e,Oc)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e}(Ei);var Dc=function(t){function e(e){t.call(this,e,{}),this.implementation=e}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.is3D=function(){return\"3d\"===this.implementation.renderingMode},e.prototype.hasOffscreenPass=function(){return void 0!==this.implementation.prerender},e.prototype.recalculate=function(){},e.prototype.updateTransitions=function(){},e.prototype.hasTransition=function(){},e.prototype.serialize=function(){},e.prototype.onAdd=function(t){this.implementation.onAdd&&this.implementation.onAdd(t,t.painter.context.gl)},e.prototype.onRemove=function(t){this.implementation.onRemove&&this.implementation.onRemove(t,t.painter.context.gl)},e}(Ei),Rc={circle:_o,heatmap:Po,hillshade:Oo,fill:xs,\"fill-extrusion\":Fs,line:Xs,symbol:Cc,background:Ic,raster:zc};var Fc=self.HTMLImageElement,Bc=self.HTMLCanvasElement,Nc=self.HTMLVideoElement,jc=self.ImageData,Uc=self.ImageBitmap,Vc=function(t,e,r,n){this.context=t,this.format=r,this.texture=t.gl.createTexture(),this.update(e,n)};Vc.prototype.update=function(t,e,r){var n=t.width,i=t.height,a=!(this.size&&this.size[0]===n&&this.size[1]===i||r),o=this.context,s=o.gl;if(this.useMipmap=Boolean(e&&e.useMipmap),s.bindTexture(s.TEXTURE_2D,this.texture),o.pixelStoreUnpackFlipY.set(!1),o.pixelStoreUnpack.set(1),o.pixelStoreUnpackPremultiplyAlpha.set(this.format===s.RGBA&&(!e||!1!==e.premultiply)),a)this.size=[n,i],t instanceof Fc||t instanceof Bc||t instanceof Nc||t instanceof jc||Uc&&t instanceof Uc?s.texImage2D(s.TEXTURE_2D,0,this.format,this.format,s.UNSIGNED_BYTE,t):s.texImage2D(s.TEXTURE_2D,0,this.format,n,i,0,this.format,s.UNSIGNED_BYTE,t.data);else{var l=r||{x:0,y:0},c=l.x,u=l.y;t instanceof Fc||t instanceof Bc||t instanceof Nc||t instanceof jc||Uc&&t instanceof Uc?s.texSubImage2D(s.TEXTURE_2D,0,c,u,s.RGBA,s.UNSIGNED_BYTE,t):s.texSubImage2D(s.TEXTURE_2D,0,c,u,n,i,s.RGBA,s.UNSIGNED_BYTE,t.data)}this.useMipmap&&this.isSizePowerOfTwo()&&s.generateMipmap(s.TEXTURE_2D)},Vc.prototype.bind=function(t,e,r){var n=this.context.gl;n.bindTexture(n.TEXTURE_2D,this.texture),r!==n.LINEAR_MIPMAP_NEAREST||this.isSizePowerOfTwo()||(r=n.LINEAR),t!==this.filter&&(n.texParameteri(n.TEXTURE_2D,n.TEXTURE_MAG_FILTER,t),n.texParameteri(n.TEXTURE_2D,n.TEXTURE_MIN_FILTER,r||t),this.filter=t),e!==this.wrap&&(n.texParameteri(n.TEXTURE_2D,n.TEXTURE_WRAP_S,e),n.texParameteri(n.TEXTURE_2D,n.TEXTURE_WRAP_T,e),this.wrap=e)},Vc.prototype.isSizePowerOfTwo=function(){return this.size[0]===this.size[1]&&Math.log(this.size[0])/Math.LN2%1==0},Vc.prototype.destroy=function(){this.context.gl.deleteTexture(this.texture),this.texture=null};var Hc=function(t){var e=this;this._callback=t,this._triggered=!1,\"undefined\"!=typeof MessageChannel&&(this._channel=new MessageChannel,this._channel.port2.onmessage=function(){e._triggered=!1,e._callback()})};Hc.prototype.trigger=function(){var t=this;this._triggered||(this._triggered=!0,this._channel?this._channel.port1.postMessage(!0):setTimeout((function(){t._triggered=!1,t._callback()}),0))},Hc.prototype.remove=function(){delete this._channel,this._callback=function(){}};var qc=function(t,e,r){this.target=t,this.parent=e,this.mapId=r,this.callbacks={},this.tasks={},this.taskQueue=[],this.cancelCallbacks={},m([\"receive\",\"process\"],this),this.invoker=new Hc(this.process),this.target.addEventListener(\"message\",this.receive,!1),this.globalScope=k()?t:self};function Gc(t,e,r){var n=2*Math.PI*6378137/256/Math.pow(2,r);return[t*n-2*Math.PI*6378137/2,e*n-2*Math.PI*6378137/2]}qc.prototype.send=function(t,e,r,n,i){var a=this;void 0===i&&(i=!1);var o=Math.round(1e18*Math.random()).toString(36).substring(0,10);r&&(this.callbacks[o]=r);var s=S(this.globalScope)?void 0:[];return this.target.postMessage({id:o,type:t,hasCallback:!!r,targetMapId:n,mustQueue:i,sourceMapId:this.mapId,data:Hn(e,s)},s),{cancel:function(){r&&delete a.callbacks[o],a.target.postMessage({id:o,type:\"<cancel>\",targetMapId:n,sourceMapId:a.mapId})}}},qc.prototype.receive=function(t){var e=t.data,r=e.id;if(r&&(!e.targetMapId||this.mapId===e.targetMapId))if(\"<cancel>\"===e.type){delete this.tasks[r];var n=this.cancelCallbacks[r];delete this.cancelCallbacks[r],n&&n()}else k()||e.mustQueue?(this.tasks[r]=e,this.taskQueue.push(r),this.invoker.trigger()):this.processTask(r,e)},qc.prototype.process=function(){if(this.taskQueue.length){var t=this.taskQueue.shift(),e=this.tasks[t];delete this.tasks[t],this.taskQueue.length&&this.invoker.trigger(),e&&this.processTask(t,e)}},qc.prototype.processTask=function(t,e){var r=this;if(\"<response>\"===e.type){var n=this.callbacks[t];delete this.callbacks[t],n&&(e.error?n(qn(e.error)):n(null,qn(e.data)))}else{var i=!1,a=S(this.globalScope)?void 0:[],o=e.hasCallback?function(e,n){i=!0,delete r.cancelCallbacks[t],r.target.postMessage({id:t,type:\"<response>\",sourceMapId:r.mapId,error:e?Hn(e):null,data:Hn(n,a)},a)}:function(t){i=!0},s=null,l=qn(e.data);if(this.parent[e.type])s=this.parent[e.type](e.sourceMapId,l,o);else if(this.parent.getWorkerSource){var c=e.type.split(\".\");s=this.parent.getWorkerSource(e.sourceMapId,c[0],l.source)[c[1]](l,o)}else o(new Error(\"Could not find function \"+e.type));!i&&s&&s.cancel&&(this.cancelCallbacks[t]=s.cancel)}},qc.prototype.remove=function(){this.invoker.remove(),this.target.removeEventListener(\"message\",this.receive,!1)};var Yc=function(t,e){t&&(e?this.setSouthWest(t).setNorthEast(e):4===t.length?this.setSouthWest([t[0],t[1]]).setNorthEast([t[2],t[3]]):this.setSouthWest(t[0]).setNorthEast(t[1]))};Yc.prototype.setNorthEast=function(t){return this._ne=t instanceof Wc?new Wc(t.lng,t.lat):Wc.convert(t),this},Yc.prototype.setSouthWest=function(t){return this._sw=t instanceof Wc?new Wc(t.lng,t.lat):Wc.convert(t),this},Yc.prototype.extend=function(t){var e,r,n=this._sw,i=this._ne;if(t instanceof Wc)e=t,r=t;else{if(!(t instanceof Yc)){if(Array.isArray(t)){if(4===t.length||t.every(Array.isArray)){var a=t;return this.extend(Yc.convert(a))}var o=t;return this.extend(Wc.convert(o))}return this}if(e=t._sw,r=t._ne,!e||!r)return this}return n||i?(n.lng=Math.min(e.lng,n.lng),n.lat=Math.min(e.lat,n.lat),i.lng=Math.max(r.lng,i.lng),i.lat=Math.max(r.lat,i.lat)):(this._sw=new Wc(e.lng,e.lat),this._ne=new Wc(r.lng,r.lat)),this},Yc.prototype.getCenter=function(){return new Wc((this._sw.lng+this._ne.lng)/2,(this._sw.lat+this._ne.lat)/2)},Yc.prototype.getSouthWest=function(){return this._sw},Yc.prototype.getNorthEast=function(){return this._ne},Yc.prototype.getNorthWest=function(){return new Wc(this.getWest(),this.getNorth())},Yc.prototype.getSouthEast=function(){return new Wc(this.getEast(),this.getSouth())},Yc.prototype.getWest=function(){return this._sw.lng},Yc.prototype.getSouth=function(){return this._sw.lat},Yc.prototype.getEast=function(){return this._ne.lng},Yc.prototype.getNorth=function(){return this._ne.lat},Yc.prototype.toArray=function(){return[this._sw.toArray(),this._ne.toArray()]},Yc.prototype.toString=function(){return\"LngLatBounds(\"+this._sw.toString()+\", \"+this._ne.toString()+\")\"},Yc.prototype.isEmpty=function(){return!(this._sw&&this._ne)},Yc.prototype.contains=function(t){var e=Wc.convert(t),r=e.lng,n=e.lat,i=this._sw.lat<=n&&n<=this._ne.lat,a=this._sw.lng<=r&&r<=this._ne.lng;return this._sw.lng>this._ne.lng&&(a=this._sw.lng>=r&&r>=this._ne.lng),i&&a},Yc.convert=function(t){return!t||t instanceof Yc?t:new Yc(t)};var Wc=function(t,e){if(isNaN(t)||isNaN(e))throw new Error(\"Invalid LngLat object: (\"+t+\", \"+e+\")\");if(this.lng=+t,this.lat=+e,this.lat>90||this.lat<-90)throw new Error(\"Invalid LngLat latitude value: must be between -90 and 90\")};Wc.prototype.wrap=function(){return new Wc(c(this.lng,-180,180),this.lat)},Wc.prototype.toArray=function(){return[this.lng,this.lat]},Wc.prototype.toString=function(){return\"LngLat(\"+this.lng+\", \"+this.lat+\")\"},Wc.prototype.distanceTo=function(t){var e=Math.PI/180,r=this.lat*e,n=t.lat*e,i=Math.sin(r)*Math.sin(n)+Math.cos(r)*Math.cos(n)*Math.cos((t.lng-this.lng)*e);return 6371008.8*Math.acos(Math.min(i,1))},Wc.prototype.toBounds=function(t){void 0===t&&(t=0);var e=360*t/40075017,r=e/Math.cos(Math.PI/180*this.lat);return new Yc(new Wc(this.lng-r,this.lat-e),new Wc(this.lng+r,this.lat+e))},Wc.convert=function(t){if(t instanceof Wc)return t;if(Array.isArray(t)&&(2===t.length||3===t.length))return new Wc(Number(t[0]),Number(t[1]));if(!Array.isArray(t)&&\"object\"==typeof t&&null!==t)return new Wc(Number(\"lng\"in t?t.lng:t.lon),Number(t.lat));throw new Error(\"`LngLatLike` argument must be specified as a LngLat instance, an object {lng: <lng>, lat: <lat>}, an object {lon: <lng>, lat: <lat>}, or an array of [<lng>, <lat>]\")};var Xc=2*Math.PI*6371008.8;function Zc(t){return Xc*Math.cos(t*Math.PI/180)}function Jc(t){return(180+t)/360}function Kc(t){return(180-180/Math.PI*Math.log(Math.tan(Math.PI/4+t*Math.PI/360)))/360}function Qc(t,e){return t/Zc(e)}function $c(t){var e=180-360*t;return 360/Math.PI*Math.atan(Math.exp(e*Math.PI/180))-90}var tu=function(t,e,r){void 0===r&&(r=0),this.x=+t,this.y=+e,this.z=+r};tu.fromLngLat=function(t,e){void 0===e&&(e=0);var r=Wc.convert(t);return new tu(Jc(r.lng),Kc(r.lat),Qc(e,r.lat))},tu.prototype.toLngLat=function(){return new Wc(360*this.x-180,$c(this.y))},tu.prototype.toAltitude=function(){return t=this.z,e=this.y,t*Zc($c(e));var t,e},tu.prototype.meterInMercatorCoordinateUnits=function(){return 1/Xc*(t=$c(this.y),1/Math.cos(t*Math.PI/180));var t};var eu=function(t,e,r){this.z=t,this.x=e,this.y=r,this.key=iu(0,t,t,e,r)};eu.prototype.equals=function(t){return this.z===t.z&&this.x===t.x&&this.y===t.y},eu.prototype.url=function(t,e){var r,n,i,a,o,s=(r=this.x,n=this.y,i=this.z,a=Gc(256*r,256*(n=Math.pow(2,i)-n-1),i),o=Gc(256*(r+1),256*(n+1),i),a[0]+\",\"+a[1]+\",\"+o[0]+\",\"+o[1]),l=function(t,e,r){for(var n,i=\"\",a=t;a>0;a--)i+=(e&(n=1<<a-1)?1:0)+(r&n?2:0);return i}(this.z,this.x,this.y);return t[(this.x+this.y)%t.length].replace(\"{prefix}\",(this.x%16).toString(16)+(this.y%16).toString(16)).replace(\"{z}\",String(this.z)).replace(\"{x}\",String(this.x)).replace(\"{y}\",String(\"tms\"===e?Math.pow(2,this.z)-this.y-1:this.y)).replace(\"{quadkey}\",l).replace(\"{bbox-epsg-3857}\",s)},eu.prototype.getTilePoint=function(t){var e=Math.pow(2,this.z);return new i(8192*(t.x*e-this.x),8192*(t.y*e-this.y))},eu.prototype.toString=function(){return this.z+\"/\"+this.x+\"/\"+this.y};var ru=function(t,e){this.wrap=t,this.canonical=e,this.key=iu(t,e.z,e.z,e.x,e.y)},nu=function(t,e,r,n,i){this.overscaledZ=t,this.wrap=e,this.canonical=new eu(r,+n,+i),this.key=iu(e,t,r,n,i)};function iu(t,e,r,n,i){(t*=2)<0&&(t=-1*t-1);var a=1<<r;return(a*a*t+a*i+n).toString(36)+r.toString(36)+e.toString(36)}nu.prototype.equals=function(t){return this.overscaledZ===t.overscaledZ&&this.wrap===t.wrap&&this.canonical.equals(t.canonical)},nu.prototype.scaledTo=function(t){var e=this.canonical.z-t;return t>this.canonical.z?new nu(t,this.wrap,this.canonical.z,this.canonical.x,this.canonical.y):new nu(t,this.wrap,t,this.canonical.x>>e,this.canonical.y>>e)},nu.prototype.calculateScaledKey=function(t,e){var r=this.canonical.z-t;return t>this.canonical.z?iu(this.wrap*+e,t,this.canonical.z,this.canonical.x,this.canonical.y):iu(this.wrap*+e,t,t,this.canonical.x>>r,this.canonical.y>>r)},nu.prototype.isChildOf=function(t){if(t.wrap!==this.wrap)return!1;var e=this.canonical.z-t.canonical.z;return 0===t.overscaledZ||t.overscaledZ<this.overscaledZ&&t.canonical.x===this.canonical.x>>e&&t.canonical.y===this.canonical.y>>e},nu.prototype.children=function(t){if(this.overscaledZ>=t)return[new nu(this.overscaledZ+1,this.wrap,this.canonical.z,this.canonical.x,this.canonical.y)];var e=this.canonical.z+1,r=2*this.canonical.x,n=2*this.canonical.y;return[new nu(e,this.wrap,e,r,n),new nu(e,this.wrap,e,r+1,n),new nu(e,this.wrap,e,r,n+1),new nu(e,this.wrap,e,r+1,n+1)]},nu.prototype.isLessThan=function(t){return this.wrap<t.wrap||!(this.wrap>t.wrap)&&(this.overscaledZ<t.overscaledZ||!(this.overscaledZ>t.overscaledZ)&&(this.canonical.x<t.canonical.x||!(this.canonical.x>t.canonical.x)&&this.canonical.y<t.canonical.y))},nu.prototype.wrapped=function(){return new nu(this.overscaledZ,0,this.canonical.z,this.canonical.x,this.canonical.y)},nu.prototype.unwrapTo=function(t){return new nu(this.overscaledZ,t,this.canonical.z,this.canonical.x,this.canonical.y)},nu.prototype.overscaleFactor=function(){return Math.pow(2,this.overscaledZ-this.canonical.z)},nu.prototype.toUnwrapped=function(){return new ru(this.wrap,this.canonical)},nu.prototype.toString=function(){return this.overscaledZ+\"/\"+this.canonical.x+\"/\"+this.canonical.y},nu.prototype.getTilePoint=function(t){return this.canonical.getTilePoint(new tu(t.x-this.wrap,t.y))},Nn(\"CanonicalTileID\",eu),Nn(\"OverscaledTileID\",nu,{omit:[\"posMatrix\"]});var au=function(t,e,r){if(this.uid=t,e.height!==e.width)throw new RangeError(\"DEM tiles must be square\");if(r&&\"mapbox\"!==r&&\"terrarium\"!==r)return _('\"'+r+'\" is not a valid encoding type. Valid types include \"mapbox\" and \"terrarium\".');this.stride=e.height;var n=this.dim=e.height-2;this.data=new Uint32Array(e.data.buffer),this.encoding=r||\"mapbox\";for(var i=0;i<n;i++)this.data[this._idx(-1,i)]=this.data[this._idx(0,i)],this.data[this._idx(n,i)]=this.data[this._idx(n-1,i)],this.data[this._idx(i,-1)]=this.data[this._idx(i,0)],this.data[this._idx(i,n)]=this.data[this._idx(i,n-1)];this.data[this._idx(-1,-1)]=this.data[this._idx(0,0)],this.data[this._idx(n,-1)]=this.data[this._idx(n-1,0)],this.data[this._idx(-1,n)]=this.data[this._idx(0,n-1)],this.data[this._idx(n,n)]=this.data[this._idx(n-1,n-1)]};au.prototype.get=function(t,e){var r=new Uint8Array(this.data.buffer),n=4*this._idx(t,e);return(\"terrarium\"===this.encoding?this._unpackTerrarium:this._unpackMapbox)(r[n],r[n+1],r[n+2])},au.prototype.getUnpackVector=function(){return\"terrarium\"===this.encoding?[256,1,1/256,32768]:[6553.6,25.6,.1,1e4]},au.prototype._idx=function(t,e){if(t<-1||t>=this.dim+1||e<-1||e>=this.dim+1)throw new RangeError(\"out of range source coordinates for DEM data\");return(e+1)*this.stride+(t+1)},au.prototype._unpackMapbox=function(t,e,r){return(256*t*256+256*e+r)/10-1e4},au.prototype._unpackTerrarium=function(t,e,r){return 256*t+e+r/256-32768},au.prototype.getPixels=function(){return new Eo({width:this.stride,height:this.stride},new Uint8Array(this.data.buffer))},au.prototype.backfillBorder=function(t,e,r){if(this.dim!==t.dim)throw new Error(\"dem dimension mismatch\");var n=e*this.dim,i=e*this.dim+this.dim,a=r*this.dim,o=r*this.dim+this.dim;switch(e){case-1:n=i-1;break;case 1:i=n+1}switch(r){case-1:a=o-1;break;case 1:o=a+1}for(var s=-e*this.dim,l=-r*this.dim,c=a;c<o;c++)for(var u=n;u<i;u++)this.data[this._idx(u,c)]=t.data[this._idx(u+s,c+l)]},Nn(\"DEMData\",au);var ou=function(t){this._stringToNumber={},this._numberToString=[];for(var e=0;e<t.length;e++){var r=t[e];this._stringToNumber[r]=e,this._numberToString[e]=r}};ou.prototype.encode=function(t){return this._stringToNumber[t]},ou.prototype.decode=function(t){return this._numberToString[t]};var su=function(t,e,r,n,i){this.type=\"Feature\",this._vectorTileFeature=t,t._z=e,t._x=r,t._y=n,this.properties=t.properties,this.id=i},lu={geometry:{configurable:!0}};lu.geometry.get=function(){return void 0===this._geometry&&(this._geometry=this._vectorTileFeature.toGeoJSON(this._vectorTileFeature._x,this._vectorTileFeature._y,this._vectorTileFeature._z).geometry),this._geometry},lu.geometry.set=function(t){this._geometry=t},su.prototype.toJSON=function(){var t={geometry:this.geometry};for(var e in this)\"_geometry\"!==e&&\"_vectorTileFeature\"!==e&&(t[e]=this[e]);return t},Object.defineProperties(su.prototype,lu);var cu=function(){this.state={},this.stateChanges={},this.deletedStates={}};cu.prototype.updateState=function(t,e,r){var n=String(e);if(this.stateChanges[t]=this.stateChanges[t]||{},this.stateChanges[t][n]=this.stateChanges[t][n]||{},u(this.stateChanges[t][n],r),null===this.deletedStates[t])for(var i in this.deletedStates[t]={},this.state[t])i!==n&&(this.deletedStates[t][i]=null);else if(this.deletedStates[t]&&null===this.deletedStates[t][n])for(var a in this.deletedStates[t][n]={},this.state[t][n])r[a]||(this.deletedStates[t][n][a]=null);else for(var o in r){this.deletedStates[t]&&this.deletedStates[t][n]&&null===this.deletedStates[t][n][o]&&delete this.deletedStates[t][n][o]}},cu.prototype.removeFeatureState=function(t,e,r){if(!(null===this.deletedStates[t])){var n=String(e);if(this.deletedStates[t]=this.deletedStates[t]||{},r&&void 0!==e)null!==this.deletedStates[t][n]&&(this.deletedStates[t][n]=this.deletedStates[t][n]||{},this.deletedStates[t][n][r]=null);else if(void 0!==e){if(this.stateChanges[t]&&this.stateChanges[t][n])for(r in this.deletedStates[t][n]={},this.stateChanges[t][n])this.deletedStates[t][n][r]=null;else this.deletedStates[t][n]=null}else this.deletedStates[t]=null}},cu.prototype.getState=function(t,e){var r=String(e),n=this.state[t]||{},i=this.stateChanges[t]||{},a=u({},n[r],i[r]);if(null===this.deletedStates[t])return{};if(this.deletedStates[t]){var o=this.deletedStates[t][e];if(null===o)return{};for(var s in o)delete a[s]}return a},cu.prototype.initializeTileState=function(t,e){t.setFeatureState(this.state,e)},cu.prototype.coalesceChanges=function(t,e){var r={};for(var n in this.stateChanges){this.state[n]=this.state[n]||{};var i={};for(var a in this.stateChanges[n])this.state[n][a]||(this.state[n][a]={}),u(this.state[n][a],this.stateChanges[n][a]),i[a]=this.state[n][a];r[n]=i}for(var o in this.deletedStates){this.state[o]=this.state[o]||{};var s={};if(null===this.deletedStates[o])for(var l in this.state[o])s[l]={},this.state[o][l]={};else for(var c in this.deletedStates[o]){if(null===this.deletedStates[o][c])this.state[o][c]={};else for(var f=0,h=Object.keys(this.deletedStates[o][c]);f<h.length;f+=1){var p=h[f];delete this.state[o][c][p]}s[c]=this.state[o][c]}r[o]=r[o]||{},u(r[o],s)}if(this.stateChanges={},this.deletedStates={},0!==Object.keys(r).length)for(var d in t){t[d].setFeatureState(r,e)}};var uu=function(t,e){this.tileID=t,this.x=t.canonical.x,this.y=t.canonical.y,this.z=t.canonical.z,this.grid=new zn(8192,16,0),this.grid3D=new zn(8192,16,0),this.featureIndexArray=new fa,this.promoteId=e};function fu(t,e,r,n,i){return v(t,(function(t,a){var o=e instanceof _i?e.get(a):null;return o&&o.evaluate?o.evaluate(r,n,i):o}))}function hu(t){for(var e=1/0,r=1/0,n=-1/0,i=-1/0,a=0,o=t;a<o.length;a+=1){var s=o[a];e=Math.min(e,s.x),r=Math.min(r,s.y),n=Math.max(n,s.x),i=Math.max(i,s.y)}return{minX:e,minY:r,maxX:n,maxY:i}}function pu(t,e){return e-t}uu.prototype.insert=function(t,e,r,n,i,a){var o=this.featureIndexArray.length;this.featureIndexArray.emplaceBack(r,n,i);for(var s=a?this.grid3D:this.grid,l=0;l<e.length;l++){for(var c=e[l],u=[1/0,1/0,-1/0,-1/0],f=0;f<c.length;f++){var h=c[f];u[0]=Math.min(u[0],h.x),u[1]=Math.min(u[1],h.y),u[2]=Math.max(u[2],h.x),u[3]=Math.max(u[3],h.y)}u[0]<8192&&u[1]<8192&&u[2]>=0&&u[3]>=0&&s.insert(o,u[0],u[1],u[2],u[3])}},uu.prototype.loadVTLayers=function(){return this.vtLayers||(this.vtLayers=new Ls.VectorTile(new al(this.rawTileData)).layers,this.sourceLayerCoder=new ou(this.vtLayers?Object.keys(this.vtLayers).sort():[\"_geojsonTileLayer\"])),this.vtLayers},uu.prototype.query=function(t,e,r,n){var a=this;this.loadVTLayers();for(var o=t.params||{},s=8192/t.tileSize/t.scale,l=sn(o.filter),c=t.queryGeometry,u=t.queryPadding*s,f=hu(c),h=this.grid.query(f.minX-u,f.minY-u,f.maxX+u,f.maxY+u),p=hu(t.cameraQueryGeometry),d=this.grid3D.query(p.minX-u,p.minY-u,p.maxX+u,p.maxY+u,(function(e,r,n,a){return function(t,e,r,n,a){for(var o=0,s=t;o<s.length;o+=1){var l=s[o];if(e<=l.x&&r<=l.y&&n>=l.x&&a>=l.y)return!0}var c=[new i(e,r),new i(e,a),new i(n,a),new i(n,r)];if(t.length>2)for(var u=0,f=c;u<f.length;u+=1){if(io(t,f[u]))return!0}for(var h=0;h<t.length-1;h++){if(ao(t[h],t[h+1],c))return!0}return!1}(t.cameraQueryGeometry,e-u,r-u,n+u,a+u)})),m=0,g=d;m<g.length;m+=1){var v=g[m];h.push(v)}h.sort(pu);for(var y,x={},b=function(i){var u=h[i];if(u!==y){y=u;var f=a.featureIndexArray.get(u),p=null;a.loadMatchingFeature(x,f.bucketIndex,f.sourceLayerIndex,f.featureIndex,l,o.layers,o.availableImages,e,r,n,(function(e,r,n){return p||(p=Ya(e)),r.queryIntersectsFeature(c,e,n,p,a.z,t.transform,s,t.pixelPosMatrix)}))}},_=0;_<h.length;_++)b(_);return x},uu.prototype.loadMatchingFeature=function(t,e,r,n,i,a,o,s,l,c,u){var f=this.bucketLayerIDs[e];if(!a||function(t,e){for(var r=0;r<t.length;r++)if(e.indexOf(t[r])>=0)return!0;return!1}(a,f)){var h=this.sourceLayerCoder.decode(r),p=this.vtLayers[h].feature(n);if(i.filter(new pi(this.tileID.overscaledZ),p))for(var d=this.getId(p,h),m=0;m<f.length;m++){var g=f[m];if(!(a&&a.indexOf(g)<0)){var v=s[g];if(v){var y={};void 0!==d&&c&&(y=c.getState(v.sourceLayer||\"_geojsonTileLayer\",d));var x=l[g];x.paint=fu(x.paint,v.paint,p,y,o),x.layout=fu(x.layout,v.layout,p,y,o);var b=!u||u(p,v,y);if(b){var _=new su(p,this.z,this.x,this.y,d);_.layer=x;var w=t[g];void 0===w&&(w=t[g]=[]),w.push({featureIndex:n,feature:_,intersectionZ:b})}}}}}},uu.prototype.lookupSymbolFeatures=function(t,e,r,n,i,a,o,s){var l={};this.loadVTLayers();for(var c=sn(i),u=0,f=t;u<f.length;u+=1){var h=f[u];this.loadMatchingFeature(l,r,n,h,c,a,o,s,e)}return l},uu.prototype.hasLayer=function(t){for(var e=0,r=this.bucketLayerIDs;e<r.length;e+=1)for(var n=0,i=r[e];n<i.length;n+=1){if(t===i[n])return!0}return!1},uu.prototype.getId=function(t,e){var r=t.id;if(this.promoteId){var n=\"string\"==typeof this.promoteId?this.promoteId:this.promoteId[e];\"boolean\"==typeof(r=t.properties[n])&&(r=Number(r))}return r},Nn(\"FeatureIndex\",uu,{omit:[\"rawTileData\",\"sourceLayerCoder\"]});var du=function(t,e){this.tileID=t,this.uid=h(),this.uses=0,this.tileSize=e,this.buckets={},this.expirationTime=null,this.queryPadding=0,this.hasSymbolBuckets=!1,this.hasRTLText=!1,this.dependencies={},this.expiredRequestCount=0,this.state=\"loading\"};du.prototype.registerFadeDuration=function(t){var e=t+this.timeAdded;e<R.now()||this.fadeEndTime&&e<this.fadeEndTime||(this.fadeEndTime=e)},du.prototype.wasRequested=function(){return\"errored\"===this.state||\"loaded\"===this.state||\"reloading\"===this.state},du.prototype.loadVectorData=function(t,e,r){if(this.hasData()&&this.unloadVectorData(),this.state=\"loaded\",t){for(var n in t.featureIndex&&(this.latestFeatureIndex=t.featureIndex,t.rawTileData?(this.latestRawTileData=t.rawTileData,this.latestFeatureIndex.rawTileData=t.rawTileData):this.latestRawTileData&&(this.latestFeatureIndex.rawTileData=this.latestRawTileData)),this.collisionBoxArray=t.collisionBoxArray,this.buckets=function(t,e){var r={};if(!e)return r;for(var n=function(){var t=a[i],n=t.layerIds.map((function(t){return e.getLayer(t)})).filter(Boolean);if(0!==n.length){t.layers=n,t.stateDependentLayerIds&&(t.stateDependentLayers=t.stateDependentLayerIds.map((function(t){return n.filter((function(e){return e.id===t}))[0]})));for(var o=0,s=n;o<s.length;o+=1){var l=s[o];r[l.id]=t}}},i=0,a=t;i<a.length;i+=1)n();return r}(t.buckets,e.style),this.hasSymbolBuckets=!1,this.buckets){var i=this.buckets[n];if(i instanceof Mc){if(this.hasSymbolBuckets=!0,!r)break;i.justReloaded=!0}}if(this.hasRTLText=!1,this.hasSymbolBuckets)for(var a in this.buckets){var o=this.buckets[a];if(o instanceof Mc&&o.hasRTLText){this.hasRTLText=!0,hi.isLoading()||hi.isLoaded()||\"deferred\"!==ui()||fi();break}}for(var s in this.queryPadding=0,this.buckets){var l=this.buckets[s];this.queryPadding=Math.max(this.queryPadding,e.style.getLayer(s).queryRadius(l))}t.imageAtlas&&(this.imageAtlas=t.imageAtlas),t.glyphAtlasImage&&(this.glyphAtlasImage=t.glyphAtlasImage)}else this.collisionBoxArray=new na},du.prototype.unloadVectorData=function(){for(var t in this.buckets)this.buckets[t].destroy();this.buckets={},this.imageAtlasTexture&&this.imageAtlasTexture.destroy(),this.imageAtlas&&(this.imageAtlas=null),this.glyphAtlasTexture&&this.glyphAtlasTexture.destroy(),this.latestFeatureIndex=null,this.state=\"unloaded\"},du.prototype.getBucket=function(t){return this.buckets[t.id]},du.prototype.upload=function(t){for(var e in this.buckets){var r=this.buckets[e];r.uploadPending()&&r.upload(t)}var n=t.gl;this.imageAtlas&&!this.imageAtlas.uploaded&&(this.imageAtlasTexture=new Vc(t,this.imageAtlas.image,n.RGBA),this.imageAtlas.uploaded=!0),this.glyphAtlasImage&&(this.glyphAtlasTexture=new Vc(t,this.glyphAtlasImage,n.ALPHA),this.glyphAtlasImage=null)},du.prototype.prepare=function(t){this.imageAtlas&&this.imageAtlas.patchUpdatedImages(t,this.imageAtlasTexture)},du.prototype.queryRenderedFeatures=function(t,e,r,n,i,a,o,s,l,c){return this.latestFeatureIndex&&this.latestFeatureIndex.rawTileData?this.latestFeatureIndex.query({queryGeometry:n,cameraQueryGeometry:i,scale:a,tileSize:this.tileSize,pixelPosMatrix:c,transform:s,params:o,queryPadding:this.queryPadding*l},t,e,r):{}},du.prototype.querySourceFeatures=function(t,e){var r=this.latestFeatureIndex;if(r&&r.rawTileData){var n=r.loadVTLayers(),i=e?e.sourceLayer:\"\",a=n._geojsonTileLayer||n[i];if(a)for(var o=sn(e&&e.filter),s=this.tileID.canonical,l=s.z,c=s.x,u=s.y,f={z:l,x:c,y:u},h=0;h<a.length;h++){var p=a.feature(h);if(o.filter(new pi(this.tileID.overscaledZ),p)){var d=r.getId(p,i),m=new su(p,l,c,u,d);m.tile=f,t.push(m)}}}},du.prototype.hasData=function(){return\"loaded\"===this.state||\"reloading\"===this.state||\"expired\"===this.state},du.prototype.patternsLoaded=function(){return this.imageAtlas&&!!Object.keys(this.imageAtlas.patternPositions).length},du.prototype.setExpiryData=function(t){var e=this.expirationTime;if(t.cacheControl){var r=A(t.cacheControl);r[\"max-age\"]&&(this.expirationTime=Date.now()+1e3*r[\"max-age\"])}else t.expires&&(this.expirationTime=new Date(t.expires).getTime());if(this.expirationTime){var n=Date.now(),i=!1;if(this.expirationTime>n)i=!1;else if(e)if(this.expirationTime<e)i=!0;else{var a=this.expirationTime-e;a?this.expirationTime=n+Math.max(a,3e4):i=!0}else i=!0;i?(this.expiredRequestCount++,this.state=\"expired\"):this.expiredRequestCount=0}},du.prototype.getExpiryTimeout=function(){if(this.expirationTime)return this.expiredRequestCount?1e3*(1<<Math.min(this.expiredRequestCount-1,31)):Math.min(this.expirationTime-(new Date).getTime(),Math.pow(2,31)-1)},du.prototype.setFeatureState=function(t,e){if(this.latestFeatureIndex&&this.latestFeatureIndex.rawTileData&&0!==Object.keys(t).length){var r=this.latestFeatureIndex.loadVTLayers();for(var n in this.buckets)if(e.style.hasLayer(n)){var i=this.buckets[n],a=i.layers[0].sourceLayer||\"_geojsonTileLayer\",o=r[a],s=t[a];if(o&&s&&0!==Object.keys(s).length){i.update(s,o,this.imageAtlas&&this.imageAtlas.patternPositions||{});var l=e&&e.style&&e.style.getLayer(n);l&&(this.queryPadding=Math.max(this.queryPadding,l.queryRadius(i)))}}}},du.prototype.holdingForFade=function(){return void 0!==this.symbolFadeHoldUntil},du.prototype.symbolFadeFinished=function(){return!this.symbolFadeHoldUntil||this.symbolFadeHoldUntil<R.now()},du.prototype.clearFadeHold=function(){this.symbolFadeHoldUntil=void 0},du.prototype.setHoldDuration=function(t){this.symbolFadeHoldUntil=R.now()+t},du.prototype.setDependencies=function(t,e){for(var r={},n=0,i=e;n<i.length;n+=1){r[i[n]]=!0}this.dependencies[t]=r},du.prototype.hasDependency=function(t,e){for(var r=0,n=t;r<n.length;r+=1){var i=n[r],a=this.dependencies[i];if(a)for(var o=0,s=e;o<s.length;o+=1){if(a[s[o]])return!0}}return!1};var 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r},t.makeRequest=yt,t.mapObject=v,t.mercatorXfromLng=Jc,t.mercatorYfromLat=Kc,t.mercatorZfromAltitude=Qc,t.mul=mo,t.multiply=po,t.mvt=Ls,t.normalize=function(t,e){var r=e[0],n=e[1],i=e[2],a=r*r+n*n+i*i;return a>0&&(a=1/Math.sqrt(a)),t[0]=e[0]*a,t[1]=e[1]*a,t[2]=e[2]*a,t},t.number=qe,t.offscreenCanvasSupported=pt,t.ortho=function(t,e,r,n,i,a,o){var s=1/(e-r),l=1/(n-i),c=1/(a-o);return t[0]=-2*s,t[1]=0,t[2]=0,t[3]=0,t[4]=0,t[5]=-2*l,t[6]=0,t[7]=0,t[8]=0,t[9]=0,t[10]=2*c,t[11]=0,t[12]=(e+r)*s,t[13]=(i+n)*l,t[14]=(o+a)*c,t[15]=1,t},t.parseGlyphPBF=function(t){return new al(t).readFields(Tl,[])},t.pbf=al,t.performSymbolLayout=function(t,e,r,n,i,a,o){t.createArrays();var s=512*t.overscaling;t.tilePixelRatio=8192/s,t.compareText={},t.iconsNeedLinear=!1;var l=t.layers[0].layout,c=t.layers[0]._unevaluatedLayout._values,u={};if(\"composite\"===t.textSizeData.kind){var f=t.textSizeData,h=f.minZoom,p=f.maxZoom;u.compositeTextSizes=[c[\"text-size\"].possiblyEvaluate(new 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g=(c+1)%2;(0===c?r-i<=d:n-i<=m)&&(o.push(f),o.push(p-1),o.push(g)),(0===c?r+i>=d:n+i>=m)&&(o.push(p+1),o.push(u),o.push(g))}}return s}(this.ids,this.coords,t,e,r,this.nodeSize)};var j={minZoom:0,maxZoom:16,radius:40,extent:512,nodeSize:64,log:!1,generateId:!1,reduce:null,map:function(t){return t}},U=function(t){this.options=X(Object.create(j),t),this.trees=new Array(this.options.maxZoom+1)};function V(t,e,r,n,i){return{x:t,y:e,zoom:1/0,id:r,parentId:-1,numPoints:n,properties:i}}function H(t,e){var r=t.geometry.coordinates,n=r[0],i=r[1];return{x:Y(n),y:W(i),zoom:1/0,index:e,parentId:-1}}function q(t){return{type:\"Feature\",id:t.id,properties:G(t),geometry:{type:\"Point\",coordinates:[(n=t.x,360*(n-.5)),(e=t.y,r=(180-360*e)*Math.PI/180,360*Math.atan(Math.exp(r))/Math.PI-90)]}};var e,r,n}function G(t){var e=t.numPoints,r=e>=1e4?Math.round(e/1e3)+\"k\":e>=1e3?Math.round(e/100)/10+\"k\":e;return 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r=0;r<e.length;r+=3)t.minX=Math.min(t.minX,e[r]),t.minY=Math.min(t.minY,e[r+1]),t.maxX=Math.max(t.maxX,e[r]),t.maxY=Math.max(t.maxY,e[r+1])}function tt(t,e,r,n){if(e.geometry){var i=e.geometry.coordinates,a=e.geometry.type,o=Math.pow(r.tolerance/((1<<r.maxZoom)*r.extent),2),s=[],l=e.id;if(r.promoteId?l=e.properties[r.promoteId]:r.generateId&&(l=n||0),\"Point\"===a)et(i,s);else if(\"MultiPoint\"===a)for(var c=0;c<i.length;c++)et(i[c],s);else if(\"LineString\"===a)rt(i,s,o,!1);else if(\"MultiLineString\"===a){if(r.lineMetrics){for(c=0;c<i.length;c++)s=[],rt(i[c],s,o,!1),t.push(Q(l,\"LineString\",s,e.properties));return}nt(i,s,o,!1)}else if(\"Polygon\"===a)nt(i,s,o,!0);else{if(\"MultiPolygon\"!==a){if(\"GeometryCollection\"===a){for(c=0;c<e.geometry.geometries.length;c++)tt(t,{id:l,geometry:e.geometry.geometries[c],properties:e.properties},r,n);return}throw new Error(\"Input data is not a valid GeoJSON object.\")}for(c=0;c<i.length;c++){var 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u=t[c],f=u.geometry,h=u.type,p=0===i?u.minX:u.minY,d=0===i?u.maxX:u.maxY;if(p>=r&&d<n)l.push(u);else if(!(d<r||p>=n)){var m=[];if(\"Point\"===h||\"MultiPoint\"===h)st(f,m,r,n,i);else if(\"LineString\"===h)lt(f,m,r,n,i,!1,s.lineMetrics);else if(\"MultiLineString\"===h)ut(f,m,r,n,i,!1);else if(\"Polygon\"===h)ut(f,m,r,n,i,!0);else if(\"MultiPolygon\"===h)for(var g=0;g<f.length;g++){var v=[];ut(f[g],v,r,n,i,!0),v.length&&m.push(v)}if(m.length){if(s.lineMetrics&&\"LineString\"===h){for(g=0;g<m.length;g++)l.push(Q(u.id,h,m[g],u.tags));continue}\"LineString\"!==h&&\"MultiLineString\"!==h||(1===m.length?(h=\"LineString\",m=m[0]):h=\"MultiLineString\"),\"Point\"!==h&&\"MultiPoint\"!==h||(h=3===m.length?\"Point\":\"MultiPoint\"),l.push(Q(u.id,h,m,u.tags))}}}return l.length?l:null}function st(t,e,r,n,i){for(var a=0;a<t.length;a+=3){var o=t[a+i];o>=r&&o<=n&&(e.push(t[a]),e.push(t[a+1]),e.push(t[a+2]))}}function lt(t,e,r,n,i,a,o){for(var 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r=[],n=0;n<t.length;n++){var i,a=t[n],o=a.type;if(\"Point\"===o||\"MultiPoint\"===o||\"LineString\"===o)i=mt(a.geometry,e);else if(\"MultiLineString\"===o||\"Polygon\"===o){i=[];for(var s=0;s<a.geometry.length;s++)i.push(mt(a.geometry[s],e))}else if(\"MultiPolygon\"===o)for(i=[],s=0;s<a.geometry.length;s++){for(var l=[],c=0;c<a.geometry[s].length;c++)l.push(mt(a.geometry[s][c],e));i.push(l)}r.push(Q(a.id,o,i,a.tags))}return r}function mt(t,e){var r=[];r.size=t.size,void 0!==t.start&&(r.start=t.start,r.end=t.end);for(var n=0;n<t.length;n+=3)r.push(t[n]+e,t[n+1],t[n+2]);return r}function gt(t,e){if(t.transformed)return t;var r,n,i,a=1<<t.z,o=t.x,s=t.y;for(r=0;r<t.features.length;r++){var l=t.features[r],c=l.geometry,u=l.type;if(l.geometry=[],1===u)for(n=0;n<c.length;n+=2)l.geometry.push(vt(c[n],c[n+1],e,a,o,s));else for(n=0;n<c.length;n++){var f=[];for(i=0;i<c[n].length;i+=2)f.push(vt(c[n][i],c[n][i+1],e,a,o,s));l.geometry.push(f)}}return t.transformed=!0,t}function 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u={},e.tags)u[f]=e.tags[f];u.mapbox_clip_start=i.start/i.size,u.mapbox_clip_end=i.end/i.size}var h={geometry:o,type:\"Polygon\"===a||\"MultiPolygon\"===a?3:\"LineString\"===a||\"MultiLineString\"===a?2:1,tags:u};null!==e.id&&(h.id=e.id),t.features.push(h)}}function bt(t,e,r,n,i,a){var o=n*n;if(n>0&&e.size<(i?o:n))r.numPoints+=e.length/3;else{for(var s=[],l=0;l<e.length;l+=3)(0===n||e[l+2]>o)&&(r.numSimplified++,s.push(e[l]),s.push(e[l+1])),r.numPoints++;i&&function(t,e){for(var r=0,n=0,i=t.length,a=i-2;n<i;a=n,n+=2)r+=(t[n]-t[a])*(t[n+1]+t[a+1]);if(r>0===e)for(n=0,i=t.length;n<i/2;n+=2){var o=t[n],s=t[n+1];t[n]=t[i-2-n],t[n+1]=t[i-1-n],t[i-2-n]=o,t[i-1-n]=s}}(s,a),t.push(s)}}function _t(t,e){var r=(e=this.options=function(t,e){for(var r in e)t[r]=e[r];return t}(Object.create(this.options),e)).debug;if(r&&console.time(\"preprocess data\"),e.maxZoom<0||e.maxZoom>24)throw new Error(\"maxZoom should be in the 0-24 range\");if(e.promoteId&&e.generateId)throw new Error(\"promoteId and generateId cannot be used together.\");var n=function(t,e){var r=[];if(\"FeatureCollection\"===t.type)for(var n=0;n<t.features.length;n++)tt(r,t.features[n],e,n);else\"Feature\"===t.type?tt(r,t,e):tt(r,{geometry:t},e);return r}(t,e);this.tiles={},this.tileCoords=[],r&&(console.timeEnd(\"preprocess data\"),console.log(\"index: maxZoom: %d, maxPoints: %d\",e.indexMaxZoom,e.indexMaxPoints),console.time(\"generate tiles\"),this.stats={},this.total=0),(n=function(t,e){var r=e.buffer/e.extent,n=t,i=ot(t,1,-1-r,r,0,-1,2,e),a=ot(t,1,1-r,2+r,0,-1,2,e);return(i||a)&&(n=ot(t,1,-r,1+r,0,-1,2,e)||[],i&&(n=dt(i,1).concat(n)),a&&(n=n.concat(dt(a,-1)))),n}(n,e)).length&&this.splitTile(n,0,0,0),r&&(n.length&&console.log(\"features: %d, points: %d\",this.tiles[0].numFeatures,this.tiles[0].numPoints),console.timeEnd(\"generate tiles\"),console.log(\"tiles generated:\",this.total,JSON.stringify(this.stats)))}function wt(t,e,r){return 32*((1<<t)*r+e)+t}function Tt(t,e){var r=t.tileID.canonical;if(!this._geoJSONIndex)return e(null,null);var n=this._geoJSONIndex.getTile(r.z,r.x,r.y);if(!n)return e(null,null);var i=new g(n.features),a=_(i);0===a.byteOffset&&a.byteLength===a.buffer.byteLength||(a=new Uint8Array(a)),e(null,{vectorTile:i,rawData:a.buffer})}U.prototype.load=function(t){var e=this.options,r=e.log,n=e.minZoom,i=e.maxZoom,a=e.nodeSize;r&&console.time(\"total time\");var o=\"prepare \"+t.length+\" points\";r&&console.time(o),this.points=t;for(var s=[],l=0;l<t.length;l++)t[l].geometry&&s.push(H(t[l],l));this.trees[i+1]=new N(s,Z,J,a,Float32Array),r&&console.timeEnd(o);for(var c=i;c>=n;c--){var u=+Date.now();s=this._cluster(s,c),this.trees[c]=new N(s,Z,J,a,Float32Array),r&&console.log(\"z%d: %d clusters in %dms\",c,s.length,+Date.now()-u)}return r&&console.timeEnd(\"total time\"),this},U.prototype.getClusters=function(t,e){var r=((t[0]+180)%360+360)%360-180,n=Math.max(-90,Math.min(90,t[1])),i=180===t[2]?180:((t[2]+180)%360+360)%360-180,a=Math.max(-90,Math.min(90,t[3]));if(t[2]-t[0]>=360)r=-180,i=180;else if(r>i){var o=this.getClusters([r,n,180,a],e),s=this.getClusters([-180,n,i,a],e);return o.concat(s)}for(var l=this.trees[this._limitZoom(e)],c=[],u=0,f=l.range(Y(r),W(a),Y(i),W(n));u<f.length;u+=1){var h=f[u],p=l.points[h];c.push(p.numPoints?q(p):this.points[p.index])}return c},U.prototype.getChildren=function(t){var e=this._getOriginId(t),r=this._getOriginZoom(t),n=\"No cluster with the specified id.\",i=this.trees[r];if(!i)throw new Error(n);var a=i.points[e];if(!a)throw new Error(n);for(var o=this.options.radius/(this.options.extent*Math.pow(2,r-1)),s=[],l=0,c=i.within(a.x,a.y,o);l<c.length;l+=1){var u=c[l],f=i.points[u];f.parentId===t&&s.push(f.numPoints?q(f):this.points[f.index])}if(0===s.length)throw new Error(n);return s},U.prototype.getLeaves=function(t,e,r){e=e||10,r=r||0;var n=[];return this._appendLeaves(n,t,e,r,0),n},U.prototype.getTile=function(t,e,r){var n=this.trees[this._limitZoom(t)],i=Math.pow(2,t),a=this.options,o=a.extent,s=a.radius/o,l=(r-s)/i,c=(r+1+s)/i,u={features:[]};return this._addTileFeatures(n.range((e-s)/i,l,(e+1+s)/i,c),n.points,e,r,i,u),0===e&&this._addTileFeatures(n.range(1-s/i,l,1,c),n.points,i,r,i,u),e===i-1&&this._addTileFeatures(n.range(0,l,s/i,c),n.points,-1,r,i,u),u.features.length?u:null},U.prototype.getClusterExpansionZoom=function(t){for(var e=this._getOriginZoom(t)-1;e<=this.options.maxZoom;){var r=this.getChildren(t);if(e++,1!==r.length)break;t=r[0].properties.cluster_id}return e},U.prototype._appendLeaves=function(t,e,r,n,i){for(var a=0,o=this.getChildren(e);a<o.length;a+=1){var s=o[a],l=s.properties;if(l&&l.cluster?i+l.point_count<=n?i+=l.point_count:i=this._appendLeaves(t,l.cluster_id,r,n,i):i<n?i++:t.push(s),t.length===r)break}return i},U.prototype._addTileFeatures=function(t,e,r,n,i,a){for(var o=0,s=t;o<s.length;o+=1){var l=e[s[o]],c=l.numPoints,u={type:1,geometry:[[Math.round(this.options.extent*(l.x*i-r)),Math.round(this.options.extent*(l.y*i-n))]],tags:c?G(l):this.points[l.index].properties},f=void 0;c?f=l.id:this.options.generateId?f=l.index:this.points[l.index].id&&(f=this.points[l.index].id),void 0!==f&&(u.id=f),a.features.push(u)}},U.prototype._limitZoom=function(t){return Math.max(this.options.minZoom,Math.min(t,this.options.maxZoom+1))},U.prototype._cluster=function(t,e){for(var r=[],n=this.options,i=n.radius,a=n.extent,o=n.reduce,s=i/(a*Math.pow(2,e)),l=0;l<t.length;l++){var c=t[l];if(!(c.zoom<=e)){c.zoom=e;for(var u=this.trees[e+1],f=u.within(c.x,c.y,s),h=c.numPoints||1,p=c.x*h,d=c.y*h,m=o&&h>1?this._map(c,!0):null,g=(l<<5)+(e+1)+this.points.length,v=0,y=f;v<y.length;v+=1){var x=y[v],b=u.points[x];if(!(b.zoom<=e)){b.zoom=e;var _=b.numPoints||1;p+=b.x*_,d+=b.y*_,h+=_,b.parentId=g,o&&(m||(m=this._map(c,!0)),o(m,this._map(b)))}}1===h?r.push(c):(c.parentId=g,r.push(V(p/h,d/h,g,h,m)))}}return r},U.prototype._getOriginId=function(t){return t-this.points.length>>5},U.prototype._getOriginZoom=function(t){return(t-this.points.length)%32},U.prototype._map=function(t,e){if(t.numPoints)return e?X({},t.properties):t.properties;var r=this.points[t.index].properties,n=this.options.map(r);return e&&n===r?X({},n):n},_t.prototype.options={maxZoom:14,indexMaxZoom:5,indexMaxPoints:1e5,tolerance:3,extent:4096,buffer:64,lineMetrics:!1,promoteId:null,generateId:!1,debug:0},_t.prototype.splitTile=function(t,e,r,n,i,a,o){for(var s=[t,e,r,n],l=this.options,c=l.debug;s.length;){n=s.pop(),r=s.pop(),e=s.pop(),t=s.pop();var u=1<<e,f=wt(e,r,n),h=this.tiles[f];if(!h&&(c>1&&console.time(\"creation\"),h=this.tiles[f]=yt(t,e,r,n,l),this.tileCoords.push({z:e,x:r,y:n}),c)){c>1&&(console.log(\"tile z%d-%d-%d (features: %d, points: %d, simplified: %d)\",e,r,n,h.numFeatures,h.numPoints,h.numSimplified),console.timeEnd(\"creation\"));var p=\"z\"+e;this.stats[p]=(this.stats[p]||0)+1,this.total++}if(h.source=t,i){if(e===l.maxZoom||e===i)continue;var d=1<<i-e;if(r!==Math.floor(a/d)||n!==Math.floor(o/d))continue}else if(e===l.indexMaxZoom||h.numPoints<=l.indexMaxPoints)continue;if(h.source=null,0!==t.length){c>1&&console.time(\"clipping\");var m,g,v,y,x,b,_=.5*l.buffer/l.extent,w=.5-_,T=.5+_,k=1+_;m=g=v=y=null,x=ot(t,u,r-_,r+T,0,h.minX,h.maxX,l),b=ot(t,u,r+w,r+k,0,h.minX,h.maxX,l),t=null,x&&(m=ot(x,u,n-_,n+T,1,h.minY,h.maxY,l),g=ot(x,u,n+w,n+k,1,h.minY,h.maxY,l),x=null),b&&(v=ot(b,u,n-_,n+T,1,h.minY,h.maxY,l),y=ot(b,u,n+w,n+k,1,h.minY,h.maxY,l),b=null),c>1&&console.timeEnd(\"clipping\"),s.push(m||[],e+1,2*r,2*n),s.push(g||[],e+1,2*r,2*n+1),s.push(v||[],e+1,2*r+1,2*n),s.push(y||[],e+1,2*r+1,2*n+1)}}},_t.prototype.getTile=function(t,e,r){var n=this.options,i=n.extent,a=n.debug;if(t<0||t>24)return null;var o=1<<t,s=wt(t,e=(e%o+o)%o,r);if(this.tiles[s])return gt(this.tiles[s],i);a>1&&console.log(\"drilling down to z%d-%d-%d\",t,e,r);for(var l,c=t,u=e,f=r;!l&&c>0;)c--,u=Math.floor(u/2),f=Math.floor(f/2),l=this.tiles[wt(c,u,f)];return l&&l.source?(a>1&&console.log(\"found parent tile z%d-%d-%d\",c,u,f),a>1&&console.time(\"drilling down\"),this.splitTile(l.source,c,u,f,t,e,r),a>1&&console.timeEnd(\"drilling down\"),this.tiles[s]?gt(this.tiles[s],i):null):null};var kt=function(e){function r(t,r,n,i){e.call(this,t,r,n,Tt),i&&(this.loadGeoJSON=i)}return e&&(r.__proto__=e),r.prototype=Object.create(e&&e.prototype),r.prototype.constructor=r,r.prototype.loadData=function(t,e){this._pendingCallback&&this._pendingCallback(null,{abandoned:!0}),this._pendingCallback=e,this._pendingLoadDataParams=t,this._state&&\"Idle\"!==this._state?this._state=\"NeedsLoadData\":(this._state=\"Coalescing\",this._loadData())},r.prototype._loadData=function(){var e=this;if(this._pendingCallback&&this._pendingLoadDataParams){var r=this._pendingCallback,n=this._pendingLoadDataParams;delete this._pendingCallback,delete this._pendingLoadDataParams;var i=!!(n&&n.request&&n.request.collectResourceTiming)&&new t.RequestPerformance(n.request);this.loadGeoJSON(n,(function(a,o){if(a||!o)return r(a);if(\"object\"!=typeof o)return r(new Error(\"Input data given to '\"+n.source+\"' is not a valid GeoJSON object.\"));f(o,!0);try{e._geoJSONIndex=n.cluster?new U(function(e){var r=e.superclusterOptions,n=e.clusterProperties;if(!n||!r)return r;for(var i={},a={},o={accumulated:null,zoom:0},s={properties:null},l=Object.keys(n),c=0,u=l;c<u.length;c+=1){var f=u[c],h=n[f],p=h[0],d=h[1],m=t.createExpression(d),g=t.createExpression(\"string\"==typeof p?[p,[\"accumulated\"],[\"get\",f]]:p);i[f]=m.value,a[f]=g.value}return r.map=function(t){s.properties=t;for(var e={},r=0,n=l;r<n.length;r+=1){var a=n[r];e[a]=i[a].evaluate(o,s)}return e},r.reduce=function(t,e){s.properties=e;for(var r=0,n=l;r<n.length;r+=1){var i=n[r];o.accumulated=t[i],t[i]=a[i].evaluate(o,s)}},r}(n)).load(o.features):function(t,e){return new _t(t,e)}(o,n.geojsonVtOptions)}catch(a){return r(a)}e.loaded={};var s={};if(i){var l=i.finish();l&&(s.resourceTiming={},s.resourceTiming[n.source]=JSON.parse(JSON.stringify(l)))}r(null,s)}))}},r.prototype.coalesce=function(){\"Coalescing\"===this._state?this._state=\"Idle\":\"NeedsLoadData\"===this._state&&(this._state=\"Coalescing\",this._loadData())},r.prototype.reloadTile=function(t,r){var n=this.loaded,i=t.uid;return n&&n[i]?e.prototype.reloadTile.call(this,t,r):this.loadTile(t,r)},r.prototype.loadGeoJSON=function(e,r){if(e.request)t.getJSON(e.request,r);else{if(\"string\"!=typeof e.data)return r(new Error(\"Input data given to '\"+e.source+\"' is not a valid GeoJSON object.\"));try{return r(null,JSON.parse(e.data))}catch(t){return r(new Error(\"Input data given to '\"+e.source+\"' is not a valid GeoJSON 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t.Point(r.clientX-n.left-e.clientLeft,r.clientY-n.top-e.clientTop)},r.touchPos=function(e,r){for(var n=e.getBoundingClientRect(),i=[],a=0;a<r.length;a++)i.push(new t.Point(r[a].clientX-n.left-e.clientLeft,r[a].clientY-n.top-e.clientTop));return i},r.mouseButton=function(e){return void 0!==t.window.InstallTrigger&&2===e.button&&e.ctrlKey&&t.window.navigator.platform.toUpperCase().indexOf(\"MAC\")>=0?0:e.button},r.remove=function(t){t.parentNode&&t.parentNode.removeChild(t)};var h=function(e){function r(){e.call(this),this.images={},this.updatedImages={},this.callbackDispatchedThisFrame={},this.loaded=!1,this.requestors=[],this.patterns={},this.atlasImage=new t.RGBAImage({width:1,height:1}),this.dirty=!0}return e&&(r.__proto__=e),r.prototype=Object.create(e&&e.prototype),r.prototype.constructor=r,r.prototype.isLoaded=function(){return this.loaded},r.prototype.setLoaded=function(t){if(this.loaded!==t&&(this.loaded=t,t)){for(var e=0,r=this.requestors;e<r.length;e+=1){var n=r[e],i=n.ids,a=n.callback;this._notify(i,a)}this.requestors=[]}},r.prototype.getImage=function(t){return this.images[t]},r.prototype.addImage=function(t,e){this._validate(t,e)&&(this.images[t]=e)},r.prototype._validate=function(e,r){var n=!0;return this._validateStretch(r.stretchX,r.data&&r.data.width)||(this.fire(new t.ErrorEvent(new Error('Image \"'+e+'\" has invalid \"stretchX\" value'))),n=!1),this._validateStretch(r.stretchY,r.data&&r.data.height)||(this.fire(new t.ErrorEvent(new Error('Image \"'+e+'\" has invalid \"stretchY\" value'))),n=!1),this._validateContent(r.content,r)||(this.fire(new t.ErrorEvent(new Error('Image \"'+e+'\" has invalid \"content\" value'))),n=!1),n},r.prototype._validateStretch=function(t,e){if(!t)return!0;for(var r=0,n=0,i=t;n<i.length;n+=1){var a=i[n];if(a[0]<r||a[1]<a[0]||e<a[1])return!1;r=a[1]}return!0},r.prototype._validateContent=function(t,e){return!t||4===t.length&&(!(t[0]<0||e.data.width<t[0])&&(!(t[1]<0||e.data.height<t[1])&&(!(t[2]<0||e.data.width<t[2])&&(!(t[3]<0||e.data.height<t[3])&&(!(t[2]<t[0])&&!(t[3]<t[1]))))))},r.prototype.updateImage=function(t,e){var r=this.images[t];e.version=r.version+1,this.images[t]=e,this.updatedImages[t]=!0},r.prototype.removeImage=function(t){var e=this.images[t];delete this.images[t],delete this.patterns[t],e.userImage&&e.userImage.onRemove&&e.userImage.onRemove()},r.prototype.listImages=function(){return Object.keys(this.images)},r.prototype.getImages=function(t,e){var r=!0;if(!this.isLoaded())for(var n=0,i=t;n<i.length;n+=1){var a=i[n];this.images[a]||(r=!1)}this.isLoaded()||r?this._notify(t,e):this.requestors.push({ids:t,callback:e})},r.prototype._notify=function(e,r){for(var n={},i=0,a=e;i<a.length;i+=1){var o=a[i];this.images[o]||this.fire(new t.Event(\"styleimagemissing\",{id:o}));var s=this.images[o];s?n[o]={data:s.data.clone(),pixelRatio:s.pixelRatio,sdf:s.sdf,version:s.version,stretchX:s.stretchX,stretchY:s.stretchY,content:s.content,hasRenderCallback:Boolean(s.userImage&&s.userImage.render)}:t.warnOnce('Image \"'+o+'\" could not be loaded. Please make sure you have added the image with map.addImage() or a \"sprite\" property in your style. You can provide missing images by listening for the \"styleimagemissing\" map event.')}r(null,n)},r.prototype.getPixelSize=function(){var t=this.atlasImage;return{width:t.width,height:t.height}},r.prototype.getPattern=function(e){var r=this.patterns[e],n=this.getImage(e);if(!n)return null;if(r&&r.position.version===n.version)return r.position;if(r)r.position.version=n.version;else{var i={w:n.data.width+2,h:n.data.height+2,x:0,y:0},a=new t.ImagePosition(i,n);this.patterns[e]={bin:i,position:a}}return this._updatePatternAtlas(),this.patterns[e].position},r.prototype.bind=function(e){var r=e.gl;this.atlasTexture?this.dirty&&(this.atlasTexture.update(this.atlasImage),this.dirty=!1):this.atlasTexture=new t.Texture(e,this.atlasImage,r.RGBA),this.atlasTexture.bind(r.LINEAR,r.CLAMP_TO_EDGE)},r.prototype._updatePatternAtlas=function(){var e=[];for(var r in this.patterns)e.push(this.patterns[r].bin);var n=t.potpack(e),i=n.w,a=n.h,o=this.atlasImage;for(var s in o.resize({width:i||1,height:a||1}),this.patterns){var l=this.patterns[s].bin,c=l.x+1,u=l.y+1,f=this.images[s].data,h=f.width,p=f.height;t.RGBAImage.copy(f,o,{x:0,y:0},{x:c,y:u},{width:h,height:p}),t.RGBAImage.copy(f,o,{x:0,y:p-1},{x:c,y:u-1},{width:h,height:1}),t.RGBAImage.copy(f,o,{x:0,y:0},{x:c,y:u+p},{width:h,height:1}),t.RGBAImage.copy(f,o,{x:h-1,y:0},{x:c-1,y:u},{width:1,height:p}),t.RGBAImage.copy(f,o,{x:0,y:0},{x:c+h,y:u},{width:1,height:p})}this.dirty=!0},r.prototype.beginFrame=function(){this.callbackDispatchedThisFrame={}},r.prototype.dispatchRenderCallbacks=function(t){for(var e=0,r=t;e<r.length;e+=1){var n=r[e];if(!this.callbackDispatchedThisFrame[n]){this.callbackDispatchedThisFrame[n]=!0;var i=this.images[n];f(i)&&this.updateImage(n,i)}}},r}(t.Evented);var p=g,d=g,m=1e20;function g(t,e,r,n,i,a){this.fontSize=t||24,this.buffer=void 0===e?3:e,this.cutoff=n||.25,this.fontFamily=i||\"sans-serif\",this.fontWeight=a||\"normal\",this.radius=r||8;var o=this.size=this.fontSize+2*this.buffer;this.canvas=document.createElement(\"canvas\"),this.canvas.width=this.canvas.height=o,this.ctx=this.canvas.getContext(\"2d\"),this.ctx.font=this.fontWeight+\" \"+this.fontSize+\"px \"+this.fontFamily,this.ctx.textBaseline=\"middle\",this.ctx.fillStyle=\"black\",this.gridOuter=new Float64Array(o*o),this.gridInner=new Float64Array(o*o),this.f=new Float64Array(o),this.d=new Float64Array(o),this.z=new Float64Array(o+1),this.v=new Int16Array(o),this.middle=Math.round(o/2*(navigator.userAgent.indexOf(\"Gecko/\")>=0?1.2:1))}function v(t,e,r,n,i,a,o){for(var s=0;s<e;s++){for(var l=0;l<r;l++)n[l]=t[l*e+s];for(y(n,i,a,o,r),l=0;l<r;l++)t[l*e+s]=i[l]}for(l=0;l<r;l++){for(s=0;s<e;s++)n[s]=t[l*e+s];for(y(n,i,a,o,e),s=0;s<e;s++)t[l*e+s]=Math.sqrt(i[s])}}function y(t,e,r,n,i){r[0]=0,n[0]=-m,n[1]=+m;for(var a=1,o=0;a<i;a++){for(var s=(t[a]+a*a-(t[r[o]]+r[o]*r[o]))/(2*a-2*r[o]);s<=n[o];)o--,s=(t[a]+a*a-(t[r[o]]+r[o]*r[o]))/(2*a-2*r[o]);r[++o]=a,n[o]=s,n[o+1]=+m}for(a=0,o=0;a<i;a++){for(;n[o+1]<a;)o++;e[a]=(a-r[o])*(a-r[o])+t[r[o]]}}g.prototype.draw=function(t){this.ctx.clearRect(0,0,this.size,this.size),this.ctx.fillText(t,this.buffer,this.middle);for(var e=this.ctx.getImageData(0,0,this.size,this.size),r=new Uint8ClampedArray(this.size*this.size),n=0;n<this.size*this.size;n++){var i=e.data[4*n+3]/255;this.gridOuter[n]=1===i?0:0===i?m:Math.pow(Math.max(0,.5-i),2),this.gridInner[n]=1===i?m:0===i?0:Math.pow(Math.max(0,i-.5),2)}for(v(this.gridOuter,this.size,this.size,this.f,this.d,this.v,this.z),v(this.gridInner,this.size,this.size,this.f,this.d,this.v,this.z),n=0;n<this.size*this.size;n++){var a=this.gridOuter[n]-this.gridInner[n];r[n]=Math.max(0,Math.min(255,Math.round(255-255*(a/this.radius+this.cutoff))))}return r},p.default=d;var x=function(t,e){this.requestManager=t,this.localIdeographFontFamily=e,this.entries={}};x.prototype.setURL=function(t){this.url=t},x.prototype.getGlyphs=function(e,r){var n=this,i=[];for(var a in e)for(var o=0,s=e[a];o<s.length;o+=1){var l=s[o];i.push({stack:a,id:l})}t.asyncAll(i,(function(t,e){var r=t.stack,i=t.id,a=n.entries[r];a||(a=n.entries[r]={glyphs:{},requests:{},ranges:{}});var o=a.glyphs[i];if(void 0===o){if(o=n._tinySDF(a,r,i))return a.glyphs[i]=o,void e(null,{stack:r,id:i,glyph:o});var s=Math.floor(i/256);if(256*s>65535)e(new Error(\"glyphs > 65535 not supported\"));else if(a.ranges[s])e(null,{stack:r,id:i,glyph:o});else{var l=a.requests[s];l||(l=a.requests[s]=[],x.loadGlyphRange(r,s,n.url,n.requestManager,(function(t,e){if(e){for(var r in e)n._doesCharSupportLocalGlyph(+r)||(a.glyphs[+r]=e[+r]);a.ranges[s]=!0}for(var i=0,o=l;i<o.length;i+=1){(0,o[i])(t,e)}delete a.requests[s]}))),l.push((function(t,n){t?e(t):n&&e(null,{stack:r,id:i,glyph:n[i]||null})}))}}else e(null,{stack:r,id:i,glyph:o})}),(function(t,e){if(t)r(t);else if(e){for(var n={},i=0,a=e;i<a.length;i+=1){var o=a[i],s=o.stack,l=o.id,c=o.glyph;(n[s]||(n[s]={}))[l]=c&&{id:c.id,bitmap:c.bitmap.clone(),metrics:c.metrics}}r(null,n)}}))},x.prototype._doesCharSupportLocalGlyph=function(e){return!!this.localIdeographFontFamily&&(t.isChar[\"CJK Unified Ideographs\"](e)||t.isChar[\"Hangul Syllables\"](e)||t.isChar.Hiragana(e)||t.isChar.Katakana(e))},x.prototype._tinySDF=function(e,r,n){var i=this.localIdeographFontFamily;if(i&&this._doesCharSupportLocalGlyph(n)){var a=e.tinySDF;if(!a){var o=\"400\";/bold/i.test(r)?o=\"900\":/medium/i.test(r)?o=\"500\":/light/i.test(r)&&(o=\"200\"),a=e.tinySDF=new x.TinySDF(24,3,8,.25,i,o)}return{id:n,bitmap:new t.AlphaImage({width:30,height:30},a.draw(String.fromCharCode(n))),metrics:{width:24,height:24,left:0,top:-8,advance:24}}}},x.loadGlyphRange=function(e,r,n,i,a){var o=256*r,s=o+255,l=i.transformRequest(i.normalizeGlyphsURL(n).replace(\"{fontstack}\",e).replace(\"{range}\",o+\"-\"+s),t.ResourceType.Glyphs);t.getArrayBuffer(l,(function(e,r){if(e)a(e);else if(r){for(var n={},i=0,o=t.parseGlyphPBF(r);i<o.length;i+=1){var s=o[i];n[s.id]=s}a(null,n)}}))},x.TinySDF=p;var b=function(){this.specification=t.styleSpec.light.position};b.prototype.possiblyEvaluate=function(e,r){return t.sphericalToCartesian(e.expression.evaluate(r))},b.prototype.interpolate=function(e,r,n){return{x:t.number(e.x,r.x,n),y:t.number(e.y,r.y,n),z:t.number(e.z,r.z,n)}};var _=new t.Properties({anchor:new t.DataConstantProperty(t.styleSpec.light.anchor),position:new b,color:new t.DataConstantProperty(t.styleSpec.light.color),intensity:new t.DataConstantProperty(t.styleSpec.light.intensity)}),w=function(e){function r(r){e.call(this),this._transitionable=new t.Transitionable(_),this.setLight(r),this._transitioning=this._transitionable.untransitioned()}return e&&(r.__proto__=e),r.prototype=Object.create(e&&e.prototype),r.prototype.constructor=r,r.prototype.getLight=function(){return this._transitionable.serialize()},r.prototype.setLight=function(e,r){if(void 0===r&&(r={}),!this._validate(t.validateLight,e,r))for(var n in e){var i=e[n];t.endsWith(n,\"-transition\")?this._transitionable.setTransition(n.slice(0,-\"-transition\".length),i):this._transitionable.setValue(n,i)}},r.prototype.updateTransitions=function(t){this._transitioning=this._transitionable.transitioned(t,this._transitioning)},r.prototype.hasTransition=function(){return this._transitioning.hasTransition()},r.prototype.recalculate=function(t){this.properties=this._transitioning.possiblyEvaluate(t)},r.prototype._validate=function(e,r,n){return(!n||!1!==n.validate)&&t.emitValidationErrors(this,e.call(t.validateStyle,t.extend({value:r,style:{glyphs:!0,sprite:!0},styleSpec:t.styleSpec})))},r}(t.Evented),T=function(t,e){this.width=t,this.height=e,this.nextRow=0,this.data=new Uint8Array(this.width*this.height),this.dashEntry={}};T.prototype.getDash=function(t,e){var r=t.join(\",\")+String(e);return this.dashEntry[r]||(this.dashEntry[r]=this.addDash(t,e)),this.dashEntry[r]},T.prototype.getDashRanges=function(t,e,r){var n=[],i=t.length%2==1?-t[t.length-1]*r:0,a=t[0]*r,o=!0;n.push({left:i,right:a,isDash:o,zeroLength:0===t[0]});for(var s=t[0],l=1;l<t.length;l++){o=!o;var c=t[l];i=s*r,a=(s+=c)*r,n.push({left:i,right:a,isDash:o,zeroLength:0===c})}return n},T.prototype.addRoundDash=function(t,e,r){for(var n=e/2,i=-r;i<=r;i++)for(var a=this.nextRow+r+i,o=this.width*a,s=0,l=t[s],c=0;c<this.width;c++){c/l.right>1&&(l=t[++s]);var u=Math.abs(c-l.left),f=Math.abs(c-l.right),h=Math.min(u,f),p=void 0,d=i/r*(n+1);if(l.isDash){var m=n-Math.abs(d);p=Math.sqrt(h*h+m*m)}else p=n-Math.sqrt(h*h+d*d);this.data[o+c]=Math.max(0,Math.min(255,p+128))}},T.prototype.addRegularDash=function(t){for(var e=t.length-1;e>=0;--e){var r=t[e],n=t[e+1];r.zeroLength?t.splice(e,1):n&&n.isDash===r.isDash&&(n.left=r.left,t.splice(e,1))}var i=t[0],a=t[t.length-1];i.isDash===a.isDash&&(i.left=a.left-this.width,a.right=i.right+this.width);for(var o=this.width*this.nextRow,s=0,l=t[s],c=0;c<this.width;c++){c/l.right>1&&(l=t[++s]);var u=Math.abs(c-l.left),f=Math.abs(c-l.right),h=Math.min(u,f),p=l.isDash?h:-h;this.data[o+c]=Math.max(0,Math.min(255,p+128))}},T.prototype.addDash=function(e,r){var n=r?7:0,i=2*n+1;if(this.nextRow+i>this.height)return t.warnOnce(\"LineAtlas out of space\"),null;for(var a=0,o=0;o<e.length;o++)a+=e[o];if(0!==a){var s=this.width/a,l=this.getDashRanges(e,this.width,s);r?this.addRoundDash(l,s,n):this.addRegularDash(l)}var c={y:(this.nextRow+n+.5)/this.height,height:2*n/this.height,width:a};return this.nextRow+=i,this.dirty=!0,c},T.prototype.bind=function(t){var e=t.gl;this.texture?(e.bindTexture(e.TEXTURE_2D,this.texture),this.dirty&&(this.dirty=!1,e.texSubImage2D(e.TEXTURE_2D,0,0,0,this.width,this.height,e.ALPHA,e.UNSIGNED_BYTE,this.data))):(this.texture=e.createTexture(),e.bindTexture(e.TEXTURE_2D,this.texture),e.texParameteri(e.TEXTURE_2D,e.TEXTURE_WRAP_S,e.REPEAT),e.texParameteri(e.TEXTURE_2D,e.TEXTURE_WRAP_T,e.REPEAT),e.texParameteri(e.TEXTURE_2D,e.TEXTURE_MIN_FILTER,e.LINEAR),e.texParameteri(e.TEXTURE_2D,e.TEXTURE_MAG_FILTER,e.LINEAR),e.texImage2D(e.TEXTURE_2D,0,e.ALPHA,this.width,this.height,0,e.ALPHA,e.UNSIGNED_BYTE,this.data))};var k=function e(r,n){this.workerPool=r,this.actors=[],this.currentActor=0,this.id=t.uniqueId();for(var i=this.workerPool.acquire(this.id),a=0;a<i.length;a++){var o=i[a],s=new e.Actor(o,n,this.id);s.name=\"Worker \"+a,this.actors.push(s)}};function A(e,r,n){var i=function(i,a){if(i)return n(i);if(a){var o=t.pick(t.extend(a,e),[\"tiles\",\"minzoom\",\"maxzoom\",\"attribution\",\"mapbox_logo\",\"bounds\",\"scheme\",\"tileSize\",\"encoding\"]);a.vector_layers&&(o.vectorLayers=a.vector_layers,o.vectorLayerIds=o.vectorLayers.map((function(t){return t.id}))),o.tiles=r.canonicalizeTileset(o,e.url),n(null,o)}};return e.url?t.getJSON(r.transformRequest(r.normalizeSourceURL(e.url),t.ResourceType.Source),i):t.browser.frame((function(){return i(null,e)}))}k.prototype.broadcast=function(e,r,n){n=n||function(){},t.asyncAll(this.actors,(function(t,n){t.send(e,r,n)}),n)},k.prototype.getActor=function(){return this.currentActor=(this.currentActor+1)%this.actors.length,this.actors[this.currentActor]},k.prototype.remove=function(){this.actors.forEach((function(t){t.remove()})),this.actors=[],this.workerPool.release(this.id)},k.Actor=t.Actor;var M=function(e,r,n){this.bounds=t.LngLatBounds.convert(this.validateBounds(e)),this.minzoom=r||0,this.maxzoom=n||24};M.prototype.validateBounds=function(t){return Array.isArray(t)&&4===t.length?[Math.max(-180,t[0]),Math.max(-90,t[1]),Math.min(180,t[2]),Math.min(90,t[3])]:[-180,-90,180,90]},M.prototype.contains=function(e){var r=Math.pow(2,e.z),n=Math.floor(t.mercatorXfromLng(this.bounds.getWest())*r),i=Math.floor(t.mercatorYfromLat(this.bounds.getNorth())*r),a=Math.ceil(t.mercatorXfromLng(this.bounds.getEast())*r),o=Math.ceil(t.mercatorYfromLat(this.bounds.getSouth())*r);return e.x>=n&&e.x<a&&e.y>=i&&e.y<o};var S=function(e){function r(r,n,i,a){if(e.call(this),this.id=r,this.dispatcher=i,this.type=\"vector\",this.minzoom=0,this.maxzoom=22,this.scheme=\"xyz\",this.tileSize=512,this.reparseOverscaled=!0,this.isTileClipped=!0,this._loaded=!1,t.extend(this,t.pick(n,[\"url\",\"scheme\",\"tileSize\",\"promoteId\"])),this._options=t.extend({type:\"vector\"},n),this._collectResourceTiming=n.collectResourceTiming,512!==this.tileSize)throw new Error(\"vector tile sources must have a tileSize of 512\");this.setEventedParent(a)}return e&&(r.__proto__=e),r.prototype=Object.create(e&&e.prototype),r.prototype.constructor=r,r.prototype.load=function(){var e=this;this._loaded=!1,this.fire(new t.Event(\"dataloading\",{dataType:\"source\"})),this._tileJSONRequest=A(this._options,this.map._requestManager,(function(r,n){e._tileJSONRequest=null,e._loaded=!0,r?e.fire(new t.ErrorEvent(r)):n&&(t.extend(e,n),n.bounds&&(e.tileBounds=new M(n.bounds,e.minzoom,e.maxzoom)),t.postTurnstileEvent(n.tiles,e.map._requestManager._customAccessToken),t.postMapLoadEvent(n.tiles,e.map._getMapId(),e.map._requestManager._skuToken,e.map._requestManager._customAccessToken),e.fire(new t.Event(\"data\",{dataType:\"source\",sourceDataType:\"metadata\"})),e.fire(new t.Event(\"data\",{dataType:\"source\",sourceDataType:\"content\"})))}))},r.prototype.loaded=function(){return this._loaded},r.prototype.hasTile=function(t){return!this.tileBounds||this.tileBounds.contains(t.canonical)},r.prototype.onAdd=function(t){this.map=t,this.load()},r.prototype.onRemove=function(){this._tileJSONRequest&&(this._tileJSONRequest.cancel(),this._tileJSONRequest=null)},r.prototype.serialize=function(){return t.extend({},this._options)},r.prototype.loadTile=function(e,r){var n=this.map._requestManager.normalizeTileURL(e.tileID.canonical.url(this.tiles,this.scheme)),i={request:this.map._requestManager.transformRequest(n,t.ResourceType.Tile),uid:e.uid,tileID:e.tileID,zoom:e.tileID.overscaledZ,tileSize:this.tileSize*e.tileID.overscaleFactor(),type:this.type,source:this.id,pixelRatio:t.browser.devicePixelRatio,showCollisionBoxes:this.map.showCollisionBoxes,promoteId:this.promoteId};function a(n,i){return delete e.request,e.aborted?r(null):n&&404!==n.status?r(n):(i&&i.resourceTiming&&(e.resourceTiming=i.resourceTiming),this.map._refreshExpiredTiles&&i&&e.setExpiryData(i),e.loadVectorData(i,this.map.painter),t.cacheEntryPossiblyAdded(this.dispatcher),r(null),void(e.reloadCallback&&(this.loadTile(e,e.reloadCallback),e.reloadCallback=null)))}i.request.collectResourceTiming=this._collectResourceTiming,e.actor&&\"expired\"!==e.state?\"loading\"===e.state?e.reloadCallback=r:e.request=e.actor.send(\"reloadTile\",i,a.bind(this)):(e.actor=this.dispatcher.getActor(),e.request=e.actor.send(\"loadTile\",i,a.bind(this)))},r.prototype.abortTile=function(t){t.request&&(t.request.cancel(),delete t.request),t.actor&&t.actor.send(\"abortTile\",{uid:t.uid,type:this.type,source:this.id},void 0)},r.prototype.unloadTile=function(t){t.unloadVectorData(),t.actor&&t.actor.send(\"removeTile\",{uid:t.uid,type:this.type,source:this.id},void 0)},r.prototype.hasTransition=function(){return!1},r}(t.Evented),E=function(e){function r(r,n,i,a){e.call(this),this.id=r,this.dispatcher=i,this.setEventedParent(a),this.type=\"raster\",this.minzoom=0,this.maxzoom=22,this.roundZoom=!0,this.scheme=\"xyz\",this.tileSize=512,this._loaded=!1,this._options=t.extend({type:\"raster\"},n),t.extend(this,t.pick(n,[\"url\",\"scheme\",\"tileSize\"]))}return e&&(r.__proto__=e),r.prototype=Object.create(e&&e.prototype),r.prototype.constructor=r,r.prototype.load=function(){var e=this;this._loaded=!1,this.fire(new t.Event(\"dataloading\",{dataType:\"source\"})),this._tileJSONRequest=A(this._options,this.map._requestManager,(function(r,n){e._tileJSONRequest=null,e._loaded=!0,r?e.fire(new t.ErrorEvent(r)):n&&(t.extend(e,n),n.bounds&&(e.tileBounds=new M(n.bounds,e.minzoom,e.maxzoom)),t.postTurnstileEvent(n.tiles),t.postMapLoadEvent(n.tiles,e.map._getMapId(),e.map._requestManager._skuToken),e.fire(new t.Event(\"data\",{dataType:\"source\",sourceDataType:\"metadata\"})),e.fire(new t.Event(\"data\",{dataType:\"source\",sourceDataType:\"content\"})))}))},r.prototype.loaded=function(){return this._loaded},r.prototype.onAdd=function(t){this.map=t,this.load()},r.prototype.onRemove=function(){this._tileJSONRequest&&(this._tileJSONRequest.cancel(),this._tileJSONRequest=null)},r.prototype.serialize=function(){return t.extend({},this._options)},r.prototype.hasTile=function(t){return!this.tileBounds||this.tileBounds.contains(t.canonical)},r.prototype.loadTile=function(e,r){var n=this,i=this.map._requestManager.normalizeTileURL(e.tileID.canonical.url(this.tiles,this.scheme),this.tileSize);e.request=t.getImage(this.map._requestManager.transformRequest(i,t.ResourceType.Tile),(function(i,a){if(delete e.request,e.aborted)e.state=\"unloaded\",r(null);else if(i)e.state=\"errored\",r(i);else if(a){n.map._refreshExpiredTiles&&e.setExpiryData(a),delete a.cacheControl,delete a.expires;var o=n.map.painter.context,s=o.gl;e.texture=n.map.painter.getTileTexture(a.width),e.texture?e.texture.update(a,{useMipmap:!0}):(e.texture=new t.Texture(o,a,s.RGBA,{useMipmap:!0}),e.texture.bind(s.LINEAR,s.CLAMP_TO_EDGE,s.LINEAR_MIPMAP_NEAREST),o.extTextureFilterAnisotropic&&s.texParameterf(s.TEXTURE_2D,o.extTextureFilterAnisotropic.TEXTURE_MAX_ANISOTROPY_EXT,o.extTextureFilterAnisotropicMax)),e.state=\"loaded\",t.cacheEntryPossiblyAdded(n.dispatcher),r(null)}}))},r.prototype.abortTile=function(t,e){t.request&&(t.request.cancel(),delete t.request),e()},r.prototype.unloadTile=function(t,e){t.texture&&this.map.painter.saveTileTexture(t.texture),e()},r.prototype.hasTransition=function(){return!1},r}(t.Evented),L=function(e){function r(r,n,i,a){e.call(this,r,n,i,a),this.type=\"raster-dem\",this.maxzoom=22,this._options=t.extend({type:\"raster-dem\"},n),this.encoding=n.encoding||\"mapbox\"}return e&&(r.__proto__=e),r.prototype=Object.create(e&&e.prototype),r.prototype.constructor=r,r.prototype.serialize=function(){return{type:\"raster-dem\",url:this.url,tileSize:this.tileSize,tiles:this.tiles,bounds:this.bounds,encoding:this.encoding}},r.prototype.loadTile=function(e,r){var n=this.map._requestManager.normalizeTileURL(e.tileID.canonical.url(this.tiles,this.scheme),this.tileSize);function i(t,n){t&&(e.state=\"errored\",r(t)),n&&(e.dem=n,e.needsHillshadePrepare=!0,e.state=\"loaded\",r(null))}e.request=t.getImage(this.map._requestManager.transformRequest(n,t.ResourceType.Tile),function(n,a){if(delete e.request,e.aborted)e.state=\"unloaded\",r(null);else if(n)e.state=\"errored\",r(n);else if(a){this.map._refreshExpiredTiles&&e.setExpiryData(a),delete a.cacheControl,delete a.expires;var o=t.window.ImageBitmap&&a instanceof t.window.ImageBitmap&&t.offscreenCanvasSupported()?a:t.browser.getImageData(a,1),s={uid:e.uid,coord:e.tileID,source:this.id,rawImageData:o,encoding:this.encoding};e.actor&&\"expired\"!==e.state||(e.actor=this.dispatcher.getActor(),e.actor.send(\"loadDEMTile\",s,i.bind(this)))}}.bind(this)),e.neighboringTiles=this._getNeighboringTiles(e.tileID)},r.prototype._getNeighboringTiles=function(e){var r=e.canonical,n=Math.pow(2,r.z),i=(r.x-1+n)%n,a=0===r.x?e.wrap-1:e.wrap,o=(r.x+1+n)%n,s=r.x+1===n?e.wrap+1:e.wrap,l={};return l[new t.OverscaledTileID(e.overscaledZ,a,r.z,i,r.y).key]={backfilled:!1},l[new t.OverscaledTileID(e.overscaledZ,s,r.z,o,r.y).key]={backfilled:!1},r.y>0&&(l[new t.OverscaledTileID(e.overscaledZ,a,r.z,i,r.y-1).key]={backfilled:!1},l[new t.OverscaledTileID(e.overscaledZ,e.wrap,r.z,r.x,r.y-1).key]={backfilled:!1},l[new t.OverscaledTileID(e.overscaledZ,s,r.z,o,r.y-1).key]={backfilled:!1}),r.y+1<n&&(l[new t.OverscaledTileID(e.overscaledZ,a,r.z,i,r.y+1).key]={backfilled:!1},l[new t.OverscaledTileID(e.overscaledZ,e.wrap,r.z,r.x,r.y+1).key]={backfilled:!1},l[new t.OverscaledTileID(e.overscaledZ,s,r.z,o,r.y+1).key]={backfilled:!1}),l},r.prototype.unloadTile=function(t){t.demTexture&&this.map.painter.saveTileTexture(t.demTexture),t.fbo&&(t.fbo.destroy(),delete t.fbo),t.dem&&delete t.dem,delete t.neighboringTiles,t.state=\"unloaded\",t.actor&&t.actor.send(\"removeDEMTile\",{uid:t.uid,source:this.id})},r}(E),C=function(e){function r(r,n,i,a){e.call(this),this.id=r,this.type=\"geojson\",this.minzoom=0,this.maxzoom=18,this.tileSize=512,this.isTileClipped=!0,this.reparseOverscaled=!0,this._removed=!1,this._loaded=!1,this.actor=i.getActor(),this.setEventedParent(a),this._data=n.data,this._options=t.extend({},n),this._collectResourceTiming=n.collectResourceTiming,this._resourceTiming=[],void 0!==n.maxzoom&&(this.maxzoom=n.maxzoom),n.type&&(this.type=n.type),n.attribution&&(this.attribution=n.attribution),this.promoteId=n.promoteId;var o=t.EXTENT/this.tileSize;this.workerOptions=t.extend({source:this.id,cluster:n.cluster||!1,geojsonVtOptions:{buffer:(void 0!==n.buffer?n.buffer:128)*o,tolerance:(void 0!==n.tolerance?n.tolerance:.375)*o,extent:t.EXTENT,maxZoom:this.maxzoom,lineMetrics:n.lineMetrics||!1,generateId:n.generateId||!1},superclusterOptions:{maxZoom:void 0!==n.clusterMaxZoom?Math.min(n.clusterMaxZoom,this.maxzoom-1):this.maxzoom-1,extent:t.EXTENT,radius:(n.clusterRadius||50)*o,log:!1,generateId:n.generateId||!1},clusterProperties:n.clusterProperties},n.workerOptions)}return e&&(r.__proto__=e),r.prototype=Object.create(e&&e.prototype),r.prototype.constructor=r,r.prototype.load=function(){var e=this;this.fire(new t.Event(\"dataloading\",{dataType:\"source\"})),this._updateWorkerData((function(r){if(r)e.fire(new t.ErrorEvent(r));else{var n={dataType:\"source\",sourceDataType:\"metadata\"};e._collectResourceTiming&&e._resourceTiming&&e._resourceTiming.length>0&&(n.resourceTiming=e._resourceTiming,e._resourceTiming=[]),e.fire(new t.Event(\"data\",n))}}))},r.prototype.onAdd=function(t){this.map=t,this.load()},r.prototype.setData=function(e){var r=this;return this._data=e,this.fire(new t.Event(\"dataloading\",{dataType:\"source\"})),this._updateWorkerData((function(e){if(e)r.fire(new t.ErrorEvent(e));else{var n={dataType:\"source\",sourceDataType:\"content\"};r._collectResourceTiming&&r._resourceTiming&&r._resourceTiming.length>0&&(n.resourceTiming=r._resourceTiming,r._resourceTiming=[]),r.fire(new t.Event(\"data\",n))}})),this},r.prototype.getClusterExpansionZoom=function(t,e){return this.actor.send(\"geojson.getClusterExpansionZoom\",{clusterId:t,source:this.id},e),this},r.prototype.getClusterChildren=function(t,e){return this.actor.send(\"geojson.getClusterChildren\",{clusterId:t,source:this.id},e),this},r.prototype.getClusterLeaves=function(t,e,r,n){return this.actor.send(\"geojson.getClusterLeaves\",{source:this.id,clusterId:t,limit:e,offset:r},n),this},r.prototype._updateWorkerData=function(e){var r=this;this._loaded=!1;var n=t.extend({},this.workerOptions),i=this._data;\"string\"==typeof i?(n.request=this.map._requestManager.transformRequest(t.browser.resolveURL(i),t.ResourceType.Source),n.request.collectResourceTiming=this._collectResourceTiming):n.data=JSON.stringify(i),this.actor.send(this.type+\".loadData\",n,(function(t,i){r._removed||i&&i.abandoned||(r._loaded=!0,i&&i.resourceTiming&&i.resourceTiming[r.id]&&(r._resourceTiming=i.resourceTiming[r.id].slice(0)),r.actor.send(r.type+\".coalesce\",{source:n.source},null),e(t))}))},r.prototype.loaded=function(){return this._loaded},r.prototype.loadTile=function(e,r){var n=this,i=e.actor?\"reloadTile\":\"loadTile\";e.actor=this.actor;var a={type:this.type,uid:e.uid,tileID:e.tileID,zoom:e.tileID.overscaledZ,maxZoom:this.maxzoom,tileSize:this.tileSize,source:this.id,pixelRatio:t.browser.devicePixelRatio,showCollisionBoxes:this.map.showCollisionBoxes,promoteId:this.promoteId};e.request=this.actor.send(i,a,(function(t,a){return delete e.request,e.unloadVectorData(),e.aborted?r(null):t?r(t):(e.loadVectorData(a,n.map.painter,\"reloadTile\"===i),r(null))}))},r.prototype.abortTile=function(t){t.request&&(t.request.cancel(),delete t.request),t.aborted=!0},r.prototype.unloadTile=function(t){t.unloadVectorData(),this.actor.send(\"removeTile\",{uid:t.uid,type:this.type,source:this.id})},r.prototype.onRemove=function(){this._removed=!0,this.actor.send(\"removeSource\",{type:this.type,source:this.id})},r.prototype.serialize=function(){return t.extend({},this._options,{type:this.type,data:this._data})},r.prototype.hasTransition=function(){return!1},r}(t.Evented),P=t.createLayout([{name:\"a_pos\",type:\"Int16\",components:2},{name:\"a_texture_pos\",type:\"Int16\",components:2}]),I=function(e){function r(t,r,n,i){e.call(this),this.id=t,this.dispatcher=n,this.coordinates=r.coordinates,this.type=\"image\",this.minzoom=0,this.maxzoom=22,this.tileSize=512,this.tiles={},this._loaded=!1,this.setEventedParent(i),this.options=r}return e&&(r.__proto__=e),r.prototype=Object.create(e&&e.prototype),r.prototype.constructor=r,r.prototype.load=function(e,r){var n=this;this._loaded=!1,this.fire(new t.Event(\"dataloading\",{dataType:\"source\"})),this.url=this.options.url,t.getImage(this.map._requestManager.transformRequest(this.url,t.ResourceType.Image),(function(i,a){n._loaded=!0,i?n.fire(new t.ErrorEvent(i)):a&&(n.image=a,e&&(n.coordinates=e),r&&r(),n._finishLoading())}))},r.prototype.loaded=function(){return this._loaded},r.prototype.updateImage=function(t){var e=this;return this.image&&t.url?(this.options.url=t.url,this.load(t.coordinates,(function(){e.texture=null})),this):this},r.prototype._finishLoading=function(){this.map&&(this.setCoordinates(this.coordinates),this.fire(new t.Event(\"data\",{dataType:\"source\",sourceDataType:\"metadata\"})))},r.prototype.onAdd=function(t){this.map=t,this.load()},r.prototype.setCoordinates=function(e){var r=this;this.coordinates=e;var n=e.map(t.MercatorCoordinate.fromLngLat);this.tileID=function(e){for(var r=1/0,n=1/0,i=-1/0,a=-1/0,o=0,s=e;o<s.length;o+=1){var l=s[o];r=Math.min(r,l.x),n=Math.min(n,l.y),i=Math.max(i,l.x),a=Math.max(a,l.y)}var c=i-r,u=a-n,f=Math.max(c,u),h=Math.max(0,Math.floor(-Math.log(f)/Math.LN2)),p=Math.pow(2,h);return new t.CanonicalTileID(h,Math.floor((r+i)/2*p),Math.floor((n+a)/2*p))}(n),this.minzoom=this.maxzoom=this.tileID.z;var i=n.map((function(t){return r.tileID.getTilePoint(t)._round()}));return this._boundsArray=new t.StructArrayLayout4i8,this._boundsArray.emplaceBack(i[0].x,i[0].y,0,0),this._boundsArray.emplaceBack(i[1].x,i[1].y,t.EXTENT,0),this._boundsArray.emplaceBack(i[3].x,i[3].y,0,t.EXTENT),this._boundsArray.emplaceBack(i[2].x,i[2].y,t.EXTENT,t.EXTENT),this.boundsBuffer&&(this.boundsBuffer.destroy(),delete this.boundsBuffer),this.fire(new t.Event(\"data\",{dataType:\"source\",sourceDataType:\"content\"})),this},r.prototype.prepare=function(){if(0!==Object.keys(this.tiles).length&&this.image){var e=this.map.painter.context,r=e.gl;for(var n in this.boundsBuffer||(this.boundsBuffer=e.createVertexBuffer(this._boundsArray,P.members)),this.boundsSegments||(this.boundsSegments=t.SegmentVector.simpleSegment(0,0,4,2)),this.texture||(this.texture=new t.Texture(e,this.image,r.RGBA),this.texture.bind(r.LINEAR,r.CLAMP_TO_EDGE)),this.tiles){var i=this.tiles[n];\"loaded\"!==i.state&&(i.state=\"loaded\",i.texture=this.texture)}}},r.prototype.loadTile=function(t,e){this.tileID&&this.tileID.equals(t.tileID.canonical)?(this.tiles[String(t.tileID.wrap)]=t,t.buckets={},e(null)):(t.state=\"errored\",e(null))},r.prototype.serialize=function(){return{type:\"image\",url:this.options.url,coordinates:this.coordinates}},r.prototype.hasTransition=function(){return!1},r}(t.Evented);var O=function(e){function r(t,r,n,i){e.call(this,t,r,n,i),this.roundZoom=!0,this.type=\"video\",this.options=r}return e&&(r.__proto__=e),r.prototype=Object.create(e&&e.prototype),r.prototype.constructor=r,r.prototype.load=function(){var e=this;this._loaded=!1;var r=this.options;this.urls=[];for(var n=0,i=r.urls;n<i.length;n+=1){var a=i[n];this.urls.push(this.map._requestManager.transformRequest(a,t.ResourceType.Source).url)}t.getVideo(this.urls,(function(r,n){e._loaded=!0,r?e.fire(new t.ErrorEvent(r)):n&&(e.video=n,e.video.loop=!0,e.video.addEventListener(\"playing\",(function(){e.map.triggerRepaint()})),e.map&&e.video.play(),e._finishLoading())}))},r.prototype.pause=function(){this.video&&this.video.pause()},r.prototype.play=function(){this.video&&this.video.play()},r.prototype.seek=function(e){if(this.video){var r=this.video.seekable;e<r.start(0)||e>r.end(0)?this.fire(new t.ErrorEvent(new t.ValidationError(\"sources.\"+this.id,null,\"Playback for this video can be set only between the \"+r.start(0)+\" and \"+r.end(0)+\"-second mark.\"))):this.video.currentTime=e}},r.prototype.getVideo=function(){return this.video},r.prototype.onAdd=function(t){this.map||(this.map=t,this.load(),this.video&&(this.video.play(),this.setCoordinates(this.coordinates)))},r.prototype.prepare=function(){if(!(0===Object.keys(this.tiles).length||this.video.readyState<2)){var e=this.map.painter.context,r=e.gl;for(var n in this.boundsBuffer||(this.boundsBuffer=e.createVertexBuffer(this._boundsArray,P.members)),this.boundsSegments||(this.boundsSegments=t.SegmentVector.simpleSegment(0,0,4,2)),this.texture?this.video.paused||(this.texture.bind(r.LINEAR,r.CLAMP_TO_EDGE),r.texSubImage2D(r.TEXTURE_2D,0,0,0,r.RGBA,r.UNSIGNED_BYTE,this.video)):(this.texture=new t.Texture(e,this.video,r.RGBA),this.texture.bind(r.LINEAR,r.CLAMP_TO_EDGE)),this.tiles){var i=this.tiles[n];\"loaded\"!==i.state&&(i.state=\"loaded\",i.texture=this.texture)}}},r.prototype.serialize=function(){return{type:\"video\",urls:this.urls,coordinates:this.coordinates}},r.prototype.hasTransition=function(){return this.video&&!this.video.paused},r}(I),z=function(e){function r(r,n,i,a){e.call(this,r,n,i,a),n.coordinates?Array.isArray(n.coordinates)&&4===n.coordinates.length&&!n.coordinates.some((function(t){return!Array.isArray(t)||2!==t.length||t.some((function(t){return\"number\"!=typeof t}))}))||this.fire(new t.ErrorEvent(new t.ValidationError(\"sources.\"+r,null,'\"coordinates\" property must be an array of 4 longitude/latitude array pairs'))):this.fire(new t.ErrorEvent(new t.ValidationError(\"sources.\"+r,null,'missing required property \"coordinates\"'))),n.animate&&\"boolean\"!=typeof n.animate&&this.fire(new t.ErrorEvent(new t.ValidationError(\"sources.\"+r,null,'optional \"animate\" property must be a boolean value'))),n.canvas?\"string\"==typeof n.canvas||n.canvas instanceof t.window.HTMLCanvasElement||this.fire(new t.ErrorEvent(new t.ValidationError(\"sources.\"+r,null,'\"canvas\" must be either a string representing the ID of the canvas element from which to read, or an HTMLCanvasElement instance'))):this.fire(new t.ErrorEvent(new t.ValidationError(\"sources.\"+r,null,'missing required property \"canvas\"'))),this.options=n,this.animate=void 0===n.animate||n.animate}return e&&(r.__proto__=e),r.prototype=Object.create(e&&e.prototype),r.prototype.constructor=r,r.prototype.load=function(){this._loaded=!0,this.canvas||(this.canvas=this.options.canvas instanceof t.window.HTMLCanvasElement?this.options.canvas:t.window.document.getElementById(this.options.canvas)),this.width=this.canvas.width,this.height=this.canvas.height,this._hasInvalidDimensions()?this.fire(new t.ErrorEvent(new Error(\"Canvas dimensions cannot be less than or equal to zero.\"))):(this.play=function(){this._playing=!0,this.map.triggerRepaint()},this.pause=function(){this._playing&&(this.prepare(),this._playing=!1)},this._finishLoading())},r.prototype.getCanvas=function(){return this.canvas},r.prototype.onAdd=function(t){this.map=t,this.load(),this.canvas&&this.animate&&this.play()},r.prototype.onRemove=function(){this.pause()},r.prototype.prepare=function(){var e=!1;if(this.canvas.width!==this.width&&(this.width=this.canvas.width,e=!0),this.canvas.height!==this.height&&(this.height=this.canvas.height,e=!0),!this._hasInvalidDimensions()&&0!==Object.keys(this.tiles).length){var r=this.map.painter.context,n=r.gl;for(var i in this.boundsBuffer||(this.boundsBuffer=r.createVertexBuffer(this._boundsArray,P.members)),this.boundsSegments||(this.boundsSegments=t.SegmentVector.simpleSegment(0,0,4,2)),this.texture?(e||this._playing)&&this.texture.update(this.canvas,{premultiply:!0}):this.texture=new t.Texture(r,this.canvas,n.RGBA,{premultiply:!0}),this.tiles){var a=this.tiles[i];\"loaded\"!==a.state&&(a.state=\"loaded\",a.texture=this.texture)}}},r.prototype.serialize=function(){return{type:\"canvas\",coordinates:this.coordinates}},r.prototype.hasTransition=function(){return this._playing},r.prototype._hasInvalidDimensions=function(){for(var t=0,e=[this.canvas.width,this.canvas.height];t<e.length;t+=1){var 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e=this.gl;e.framebufferTexture2D(e.FRAMEBUFFER,e.COLOR_ATTACHMENT0,e.TEXTURE_2D,t,0),this.current=t,this.dirty=!1}},e}(_t),Tt=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.set=function(t){if(t!==this.current||this.dirty){this.context.bindFramebuffer.set(this.parent);var e=this.gl;e.framebufferRenderbuffer(e.FRAMEBUFFER,e.DEPTH_ATTACHMENT,e.RENDERBUFFER,t),this.current=t,this.dirty=!1}},e}(_t),kt=function(t,e,r,n){this.context=t,this.width=e,this.height=r;var i=t.gl,a=this.framebuffer=i.createFramebuffer();this.colorAttachment=new wt(t,a),n&&(this.depthAttachment=new Tt(t,a))};kt.prototype.destroy=function(){var t=this.context.gl,e=this.colorAttachment.get();if(e&&t.deleteTexture(e),this.depthAttachment){var r=this.depthAttachment.get();r&&t.deleteRenderbuffer(r)}t.deleteFramebuffer(this.framebuffer)};var At=function(t,e,r){this.func=t,this.mask=e,this.range=r};At.ReadOnly=!1,At.ReadWrite=!0,At.disabled=new At(519,At.ReadOnly,[0,1]);var Mt=function(t,e,r,n,i,a){this.test=t,this.ref=e,this.mask=r,this.fail=n,this.depthFail=i,this.pass=a};Mt.disabled=new Mt({func:519,mask:0},0,0,7680,7680,7680);var St=function(t,e,r){this.blendFunction=t,this.blendColor=e,this.mask=r};St.disabled=new St(St.Replace=[1,0],t.Color.transparent,[!1,!1,!1,!1]),St.unblended=new St(St.Replace,t.Color.transparent,[!0,!0,!0,!0]),St.alphaBlended=new St([1,771],t.Color.transparent,[!0,!0,!0,!0]);var Et=function(t,e,r){this.enable=t,this.mode=e,this.frontFace=r};Et.disabled=new Et(!1,1029,2305),Et.backCCW=new Et(!0,1029,2305);var Lt=function(t){this.gl=t,this.extVertexArrayObject=this.gl.getExtension(\"OES_vertex_array_object\"),this.clearColor=new q(this),this.clearDepth=new G(this),this.clearStencil=new Y(this),this.colorMask=new W(this),this.depthMask=new X(this),this.stencilMask=new Z(this),this.stencilFunc=new J(this),this.stencilOp=new K(this),this.stencilTest=new Q(this),this.depthRange=new $(this),this.depthTest=new tt(this),this.depthFunc=new et(this),this.blend=new rt(this),this.blendFunc=new nt(this),this.blendColor=new it(this),this.blendEquation=new at(this),this.cullFace=new ot(this),this.cullFaceSide=new st(this),this.frontFace=new lt(this),this.program=new ct(this),this.activeTexture=new ut(this),this.viewport=new ft(this),this.bindFramebuffer=new ht(this),this.bindRenderbuffer=new pt(this),this.bindTexture=new dt(this),this.bindVertexBuffer=new mt(this),this.bindElementBuffer=new gt(this),this.bindVertexArrayOES=this.extVertexArrayObject&&new vt(this),this.pixelStoreUnpack=new yt(this),this.pixelStoreUnpackPremultiplyAlpha=new xt(this),this.pixelStoreUnpackFlipY=new bt(this),this.extTextureFilterAnisotropic=t.getExtension(\"EXT_texture_filter_anisotropic\")||t.getExtension(\"MOZ_EXT_texture_filter_anisotropic\")||t.getExtension(\"WEBKIT_EXT_texture_filter_anisotropic\"),this.extTextureFilterAnisotropic&&(this.extTextureFilterAnisotropicMax=t.getParameter(this.extTextureFilterAnisotropic.MAX_TEXTURE_MAX_ANISOTROPY_EXT)),this.extTextureHalfFloat=t.getExtension(\"OES_texture_half_float\"),this.extTextureHalfFloat&&(t.getExtension(\"OES_texture_half_float_linear\"),this.extRenderToTextureHalfFloat=t.getExtension(\"EXT_color_buffer_half_float\")),this.extTimerQuery=t.getExtension(\"EXT_disjoint_timer_query\")};Lt.prototype.setDefault=function(){this.unbindVAO(),this.clearColor.setDefault(),this.clearDepth.setDefault(),this.clearStencil.setDefault(),this.colorMask.setDefault(),this.depthMask.setDefault(),this.stencilMask.setDefault(),this.stencilFunc.setDefault(),this.stencilOp.setDefault(),this.stencilTest.setDefault(),this.depthRange.setDefault(),this.depthTest.setDefault(),this.depthFunc.setDefault(),this.blend.setDefault(),this.blendFunc.setDefault(),this.blendColor.setDefault(),this.blendEquation.setDefault(),this.cullFace.setDefault(),this.cullFaceSide.setDefault(),this.frontFace.setDefault(),this.program.setDefault(),this.activeTexture.setDefault(),this.bindFramebuffer.setDefault(),this.pixelStoreUnpack.setDefault(),this.pixelStoreUnpackPremultiplyAlpha.setDefault(),this.pixelStoreUnpackFlipY.setDefault()},Lt.prototype.setDirty=function(){this.clearColor.dirty=!0,this.clearDepth.dirty=!0,this.clearStencil.dirty=!0,this.colorMask.dirty=!0,this.depthMask.dirty=!0,this.stencilMask.dirty=!0,this.stencilFunc.dirty=!0,this.stencilOp.dirty=!0,this.stencilTest.dirty=!0,this.depthRange.dirty=!0,this.depthTest.dirty=!0,this.depthFunc.dirty=!0,this.blend.dirty=!0,this.blendFunc.dirty=!0,this.blendColor.dirty=!0,this.blendEquation.dirty=!0,this.cullFace.dirty=!0,this.cullFaceSide.dirty=!0,this.frontFace.dirty=!0,this.program.dirty=!0,this.activeTexture.dirty=!0,this.viewport.dirty=!0,this.bindFramebuffer.dirty=!0,this.bindRenderbuffer.dirty=!0,this.bindTexture.dirty=!0,this.bindVertexBuffer.dirty=!0,this.bindElementBuffer.dirty=!0,this.extVertexArrayObject&&(this.bindVertexArrayOES.dirty=!0),this.pixelStoreUnpack.dirty=!0,this.pixelStoreUnpackPremultiplyAlpha.dirty=!0,this.pixelStoreUnpackFlipY.dirty=!0},Lt.prototype.createIndexBuffer=function(t,e){return new j(this,t,e)},Lt.prototype.createVertexBuffer=function(t,e,r){return new V(this,t,e,r)},Lt.prototype.createRenderbuffer=function(t,e,r){var n=this.gl,i=n.createRenderbuffer();return this.bindRenderbuffer.set(i),n.renderbufferStorage(n.RENDERBUFFER,t,e,r),this.bindRenderbuffer.set(null),i},Lt.prototype.createFramebuffer=function(t,e,r){return new kt(this,t,e,r)},Lt.prototype.clear=function(t){var e=t.color,r=t.depth,n=this.gl,i=0;e&&(i|=n.COLOR_BUFFER_BIT,this.clearColor.set(e),this.colorMask.set([!0,!0,!0,!0])),void 0!==r&&(i|=n.DEPTH_BUFFER_BIT,this.depthRange.set([0,1]),this.clearDepth.set(r),this.depthMask.set(!0)),n.clear(i)},Lt.prototype.setCullFace=function(t){!1===t.enable?this.cullFace.set(!1):(this.cullFace.set(!0),this.cullFaceSide.set(t.mode),this.frontFace.set(t.frontFace))},Lt.prototype.setDepthMode=function(t){t.func!==this.gl.ALWAYS||t.mask?(this.depthTest.set(!0),this.depthFunc.set(t.func),this.depthMask.set(t.mask),this.depthRange.set(t.range)):this.depthTest.set(!1)},Lt.prototype.setStencilMode=function(t){t.test.func!==this.gl.ALWAYS||t.mask?(this.stencilTest.set(!0),this.stencilMask.set(t.mask),this.stencilOp.set([t.fail,t.depthFail,t.pass]),this.stencilFunc.set({func:t.test.func,ref:t.ref,mask:t.test.mask})):this.stencilTest.set(!1)},Lt.prototype.setColorMode=function(e){t.deepEqual(e.blendFunction,St.Replace)?this.blend.set(!1):(this.blend.set(!0),this.blendFunc.set(e.blendFunction),this.blendColor.set(e.blendColor)),this.colorMask.set(e.mask)},Lt.prototype.unbindVAO=function(){this.extVertexArrayObject&&this.bindVertexArrayOES.set(null)};var Ct=function(e){function r(r,n,i){var a=this;e.call(this),this.id=r,this.dispatcher=i,this.on(\"data\",(function(t){\"source\"===t.dataType&&\"metadata\"===t.sourceDataType&&(a._sourceLoaded=!0),a._sourceLoaded&&!a._paused&&\"source\"===t.dataType&&\"content\"===t.sourceDataType&&(a.reload(),a.transform&&a.update(a.transform))})),this.on(\"error\",(function(){a._sourceErrored=!0})),this._source=function(e,r,n,i){var a=new D[r.type](e,r,n,i);if(a.id!==e)throw new Error(\"Expected Source id to be \"+e+\" instead of \"+a.id);return t.bindAll([\"load\",\"abort\",\"unload\",\"serialize\",\"prepare\"],a),a}(r,n,i,this),this._tiles={},this._cache=new N(0,this._unloadTile.bind(this)),this._timers={},this._cacheTimers={},this._maxTileCacheSize=null,this._loadedParentTiles={},this._coveredTiles={},this._state=new t.SourceFeatureState}return e&&(r.__proto__=e),r.prototype=Object.create(e&&e.prototype),r.prototype.constructor=r,r.prototype.onAdd=function(t){this.map=t,this._maxTileCacheSize=t?t._maxTileCacheSize:null,this._source&&this._source.onAdd&&this._source.onAdd(t)},r.prototype.onRemove=function(t){this._source&&this._source.onRemove&&this._source.onRemove(t)},r.prototype.loaded=function(){if(this._sourceErrored)return!0;if(!this._sourceLoaded)return!1;if(!this._source.loaded())return!1;for(var t in this._tiles){var e=this._tiles[t];if(\"loaded\"!==e.state&&\"errored\"!==e.state)return!1}return!0},r.prototype.getSource=function(){return this._source},r.prototype.pause=function(){this._paused=!0},r.prototype.resume=function(){if(this._paused){var t=this._shouldReloadOnResume;this._paused=!1,this._shouldReloadOnResume=!1,t&&this.reload(),this.transform&&this.update(this.transform)}},r.prototype._loadTile=function(t,e){return this._source.loadTile(t,e)},r.prototype._unloadTile=function(t){if(this._source.unloadTile)return this._source.unloadTile(t,(function(){}))},r.prototype._abortTile=function(t){if(this._source.abortTile)return this._source.abortTile(t,(function(){}))},r.prototype.serialize=function(){return this._source.serialize()},r.prototype.prepare=function(t){for(var e in this._source.prepare&&this._source.prepare(),this._state.coalesceChanges(this._tiles,this.map?this.map.painter:null),this._tiles){var r=this._tiles[e];r.upload(t),r.prepare(this.map.style.imageManager)}},r.prototype.getIds=function(){return t.values(this._tiles).map((function(t){return t.tileID})).sort(Pt).map((function(t){return t.key}))},r.prototype.getRenderableIds=function(e){var r=this,n=[];for(var i in this._tiles)this._isIdRenderable(i,e)&&n.push(this._tiles[i]);return e?n.sort((function(e,n){var i=e.tileID,a=n.tileID,o=new t.Point(i.canonical.x,i.canonical.y)._rotate(r.transform.angle),s=new t.Point(a.canonical.x,a.canonical.y)._rotate(r.transform.angle);return i.overscaledZ-a.overscaledZ||s.y-o.y||s.x-o.x})).map((function(t){return t.tileID.key})):n.map((function(t){return t.tileID})).sort(Pt).map((function(t){return t.key}))},r.prototype.hasRenderableParent=function(t){var e=this.findLoadedParent(t,0);return!!e&&this._isIdRenderable(e.tileID.key)},r.prototype._isIdRenderable=function(t,e){return this._tiles[t]&&this._tiles[t].hasData()&&!this._coveredTiles[t]&&(e||!this._tiles[t].holdingForFade())},r.prototype.reload=function(){if(this._paused)this._shouldReloadOnResume=!0;else for(var t in this._cache.reset(),this._tiles)\"errored\"!==this._tiles[t].state&&this._reloadTile(t,\"reloading\")},r.prototype._reloadTile=function(t,e){var r=this._tiles[t];r&&(\"loading\"!==r.state&&(r.state=e),this._loadTile(r,this._tileLoaded.bind(this,r,t,e)))},r.prototype._tileLoaded=function(e,r,n,i){if(i)return e.state=\"errored\",void(404!==i.status?this._source.fire(new t.ErrorEvent(i,{tile:e})):this.update(this.transform));e.timeAdded=t.browser.now(),\"expired\"===n&&(e.refreshedUponExpiration=!0),this._setTileReloadTimer(r,e),\"raster-dem\"===this.getSource().type&&e.dem&&this._backfillDEM(e),this._state.initializeTileState(e,this.map?this.map.painter:null),this._source.fire(new t.Event(\"data\",{dataType:\"source\",tile:e,coord:e.tileID}))},r.prototype._backfillDEM=function(t){for(var e=this.getRenderableIds(),r=0;r<e.length;r++){var n=e[r];if(t.neighboringTiles&&t.neighboringTiles[n]){var i=this.getTileByID(n);a(t,i),a(i,t)}}function a(t,e){t.needsHillshadePrepare=!0;var r=e.tileID.canonical.x-t.tileID.canonical.x,n=e.tileID.canonical.y-t.tileID.canonical.y,i=Math.pow(2,t.tileID.canonical.z),a=e.tileID.key;0===r&&0===n||Math.abs(n)>1||(Math.abs(r)>1&&(1===Math.abs(r+i)?r+=i:1===Math.abs(r-i)&&(r-=i)),e.dem&&t.dem&&(t.dem.backfillBorder(e.dem,r,n),t.neighboringTiles&&t.neighboringTiles[a]&&(t.neighboringTiles[a].backfilled=!0)))}},r.prototype.getTile=function(t){return this.getTileByID(t.key)},r.prototype.getTileByID=function(t){return this._tiles[t]},r.prototype._retainLoadedChildren=function(t,e,r,n){for(var i in this._tiles){var a=this._tiles[i];if(!(n[i]||!a.hasData()||a.tileID.overscaledZ<=e||a.tileID.overscaledZ>r)){for(var o=a.tileID;a&&a.tileID.overscaledZ>e+1;){var s=a.tileID.scaledTo(a.tileID.overscaledZ-1);(a=this._tiles[s.key])&&a.hasData()&&(o=s)}for(var l=o;l.overscaledZ>e;)if(t[(l=l.scaledTo(l.overscaledZ-1)).key]){n[o.key]=o;break}}}},r.prototype.findLoadedParent=function(t,e){if(t.key in this._loadedParentTiles){var r=this._loadedParentTiles[t.key];return r&&r.tileID.overscaledZ>=e?r:null}for(var n=t.overscaledZ-1;n>=e;n--){var i=t.scaledTo(n),a=this._getLoadedTile(i);if(a)return a}},r.prototype._getLoadedTile=function(t){var e=this._tiles[t.key];return e&&e.hasData()?e:this._cache.getByKey(t.wrapped().key)},r.prototype.updateCacheSize=function(t){var e=(Math.ceil(t.width/this._source.tileSize)+1)*(Math.ceil(t.height/this._source.tileSize)+1),r=Math.floor(5*e),n=\"number\"==typeof this._maxTileCacheSize?Math.min(this._maxTileCacheSize,r):r;this._cache.setMaxSize(n)},r.prototype.handleWrapJump=function(t){var e=(t-(void 0===this._prevLng?t:this._prevLng))/360,r=Math.round(e);if(this._prevLng=t,r){var n={};for(var i in this._tiles){var a=this._tiles[i];a.tileID=a.tileID.unwrapTo(a.tileID.wrap+r),n[a.tileID.key]=a}for(var o in this._tiles=n,this._timers)clearTimeout(this._timers[o]),delete this._timers[o];for(var s in this._tiles){var l=this._tiles[s];this._setTileReloadTimer(s,l)}}},r.prototype.update=function(e){var n=this;if(this.transform=e,this._sourceLoaded&&!this._paused){var i;this.updateCacheSize(e),this.handleWrapJump(this.transform.center.lng),this._coveredTiles={},this.used?this._source.tileID?i=e.getVisibleUnwrappedCoordinates(this._source.tileID).map((function(e){return new t.OverscaledTileID(e.canonical.z,e.wrap,e.canonical.z,e.canonical.x,e.canonical.y)})):(i=e.coveringTiles({tileSize:this._source.tileSize,minzoom:this._source.minzoom,maxzoom:this._source.maxzoom,roundZoom:this._source.roundZoom,reparseOverscaled:this._source.reparseOverscaled}),this._source.hasTile&&(i=i.filter((function(t){return n._source.hasTile(t)})))):i=[];var a=e.coveringZoomLevel(this._source),o=Math.max(a-r.maxOverzooming,this._source.minzoom),s=Math.max(a+r.maxUnderzooming,this._source.minzoom),l=this._updateRetainedTiles(i,a);if(It(this._source.type)){for(var c={},u={},f=0,h=Object.keys(l);f<h.length;f+=1){var p=h[f],d=l[p],m=this._tiles[p];if(m&&!(m.fadeEndTime&&m.fadeEndTime<=t.browser.now())){var g=this.findLoadedParent(d,o);g&&(this._addTile(g.tileID),c[g.tileID.key]=g.tileID),u[p]=d}}for(var v in this._retainLoadedChildren(u,a,s,l),c)l[v]||(this._coveredTiles[v]=!0,l[v]=c[v])}for(var y in l)this._tiles[y].clearFadeHold();for(var x=0,b=t.keysDifference(this._tiles,l);x<b.length;x+=1){var _=b[x],w=this._tiles[_];w.hasSymbolBuckets&&!w.holdingForFade()?w.setHoldDuration(this.map._fadeDuration):w.hasSymbolBuckets&&!w.symbolFadeFinished()||this._removeTile(_)}this._updateLoadedParentTileCache()}},r.prototype.releaseSymbolFadeTiles=function(){for(var t in this._tiles)this._tiles[t].holdingForFade()&&this._removeTile(t)},r.prototype._updateRetainedTiles=function(t,e){for(var n={},i={},a=Math.max(e-r.maxOverzooming,this._source.minzoom),o=Math.max(e+r.maxUnderzooming,this._source.minzoom),s={},l=0,c=t;l<c.length;l+=1){var u=c[l],f=this._addTile(u);n[u.key]=u,f.hasData()||e<this._source.maxzoom&&(s[u.key]=u)}this._retainLoadedChildren(s,e,o,n);for(var h=0,p=t;h<p.length;h+=1){var d=p[h],m=this._tiles[d.key];if(!m.hasData()){if(e+1>this._source.maxzoom){var g=d.children(this._source.maxzoom)[0],v=this.getTile(g);if(v&&v.hasData()){n[g.key]=g;continue}}else{var y=d.children(this._source.maxzoom);if(n[y[0].key]&&n[y[1].key]&&n[y[2].key]&&n[y[3].key])continue}for(var x=m.wasRequested(),b=d.overscaledZ-1;b>=a;--b){var _=d.scaledTo(b);if(i[_.key])break;if(i[_.key]=!0,!(m=this.getTile(_))&&x&&(m=this._addTile(_)),m&&(n[_.key]=_,x=m.wasRequested(),m.hasData()))break}}}return n},r.prototype._updateLoadedParentTileCache=function(){for(var t in this._loadedParentTiles={},this._tiles){for(var e=[],r=void 0,n=this._tiles[t].tileID;n.overscaledZ>0;){if(n.key in this._loadedParentTiles){r=this._loadedParentTiles[n.key];break}e.push(n.key);var i=n.scaledTo(n.overscaledZ-1);if(r=this._getLoadedTile(i))break;n=i}for(var a=0,o=e;a<o.length;a+=1){var s=o[a];this._loadedParentTiles[s]=r}}},r.prototype._addTile=function(e){var r=this._tiles[e.key];if(r)return r;(r=this._cache.getAndRemove(e))&&(this._setTileReloadTimer(e.key,r),r.tileID=e,this._state.initializeTileState(r,this.map?this.map.painter:null),this._cacheTimers[e.key]&&(clearTimeout(this._cacheTimers[e.key]),delete this._cacheTimers[e.key],this._setTileReloadTimer(e.key,r)));var n=Boolean(r);return n||(r=new t.Tile(e,this._source.tileSize*e.overscaleFactor()),this._loadTile(r,this._tileLoaded.bind(this,r,e.key,r.state))),r?(r.uses++,this._tiles[e.key]=r,n||this._source.fire(new t.Event(\"dataloading\",{tile:r,coord:r.tileID,dataType:\"source\"})),r):null},r.prototype._setTileReloadTimer=function(t,e){var r=this;t in this._timers&&(clearTimeout(this._timers[t]),delete this._timers[t]);var n=e.getExpiryTimeout();n&&(this._timers[t]=setTimeout((function(){r._reloadTile(t,\"expired\"),delete r._timers[t]}),n))},r.prototype._removeTile=function(t){var e=this._tiles[t];e&&(e.uses--,delete this._tiles[t],this._timers[t]&&(clearTimeout(this._timers[t]),delete this._timers[t]),e.uses>0||(e.hasData()&&\"reloading\"!==e.state?this._cache.add(e.tileID,e,e.getExpiryTimeout()):(e.aborted=!0,this._abortTile(e),this._unloadTile(e))))},r.prototype.clearTiles=function(){for(var t in this._shouldReloadOnResume=!1,this._paused=!1,this._tiles)this._removeTile(t);this._cache.reset()},r.prototype.tilesIn=function(e,r,n){var i=this,a=[],o=this.transform;if(!o)return a;for(var s=n?o.getCameraQueryGeometry(e):e,l=e.map((function(t){return o.pointCoordinate(t)})),c=s.map((function(t){return o.pointCoordinate(t)})),u=this.getIds(),f=1/0,h=1/0,p=-1/0,d=-1/0,m=0,g=c;m<g.length;m+=1){var v=g[m];f=Math.min(f,v.x),h=Math.min(h,v.y),p=Math.max(p,v.x),d=Math.max(d,v.y)}for(var y=function(e){var n=i._tiles[u[e]];if(!n.holdingForFade()){var s=n.tileID,m=Math.pow(2,o.zoom-n.tileID.overscaledZ),g=r*n.queryPadding*t.EXTENT/n.tileSize/m,v=[s.getTilePoint(new t.MercatorCoordinate(f,h)),s.getTilePoint(new t.MercatorCoordinate(p,d))];if(v[0].x-g<t.EXTENT&&v[0].y-g<t.EXTENT&&v[1].x+g>=0&&v[1].y+g>=0){var y=l.map((function(t){return s.getTilePoint(t)})),x=c.map((function(t){return s.getTilePoint(t)}));a.push({tile:n,tileID:s,queryGeometry:y,cameraQueryGeometry:x,scale:m})}}},x=0;x<u.length;x++)y(x);return a},r.prototype.getVisibleCoordinates=function(t){for(var e=this,r=this.getRenderableIds(t).map((function(t){return e._tiles[t].tileID})),n=0,i=r;n<i.length;n+=1){var a=i[n];a.posMatrix=this.transform.calculatePosMatrix(a.toUnwrapped())}return r},r.prototype.hasTransition=function(){if(this._source.hasTransition())return!0;if(It(this._source.type))for(var e in this._tiles){var r=this._tiles[e];if(void 0!==r.fadeEndTime&&r.fadeEndTime>=t.browser.now())return!0}return!1},r.prototype.setFeatureState=function(t,e,r){t=t||\"_geojsonTileLayer\",this._state.updateState(t,e,r)},r.prototype.removeFeatureState=function(t,e,r){t=t||\"_geojsonTileLayer\",this._state.removeFeatureState(t,e,r)},r.prototype.getFeatureState=function(t,e){return t=t||\"_geojsonTileLayer\",this._state.getState(t,e)},r.prototype.setDependencies=function(t,e,r){var n=this._tiles[t];n&&n.setDependencies(e,r)},r.prototype.reloadTilesForDependencies=function(t,e){for(var r in this._tiles){this._tiles[r].hasDependency(t,e)&&this._reloadTile(r,\"reloading\")}this._cache.filter((function(r){return!r.hasDependency(t,e)}))},r}(t.Evented);function Pt(t,e){var r=Math.abs(2*t.wrap)-+(t.wrap<0),n=Math.abs(2*e.wrap)-+(e.wrap<0);return t.overscaledZ-e.overscaledZ||n-r||e.canonical.y-t.canonical.y||e.canonical.x-t.canonical.x}function It(t){return\"raster\"===t||\"image\"===t||\"video\"===t}function Ot(){return new t.window.Worker(Zi.workerUrl)}Ct.maxOverzooming=10,Ct.maxUnderzooming=3;var zt=\"mapboxgl_preloaded_worker_pool\",Dt=function(){this.active={}};Dt.prototype.acquire=function(t){if(!this.workers)for(this.workers=[];this.workers.length<Dt.workerCount;)this.workers.push(new Ot);return this.active[t]=!0,this.workers.slice()},Dt.prototype.release=function(t){delete this.active[t],0===this.numActive()&&(this.workers.forEach((function(t){t.terminate()})),this.workers=null)},Dt.prototype.isPreloaded=function(){return!!this.active[zt]},Dt.prototype.numActive=function(){return Object.keys(this.active).length};var Rt,Ft=Math.floor(t.browser.hardwareConcurrency/2);function Bt(){return Rt||(Rt=new Dt),Rt}function Nt(e,r){var n={};for(var i in e)\"ref\"!==i&&(n[i]=e[i]);return t.refProperties.forEach((function(t){t in r&&(n[t]=r[t])})),n}function jt(t){t=t.slice();for(var e=Object.create(null),r=0;r<t.length;r++)e[t[r].id]=t[r];for(var n=0;n<t.length;n++)\"ref\"in t[n]&&(t[n]=Nt(t[n],e[t[n].ref]));return t}Dt.workerCount=Math.max(Math.min(Ft,6),1);var Ut={setStyle:\"setStyle\",addLayer:\"addLayer\",removeLayer:\"removeLayer\",setPaintProperty:\"setPaintProperty\",setLayoutProperty:\"setLayoutProperty\",setFilter:\"setFilter\",addSource:\"addSource\",removeSource:\"removeSource\",setGeoJSONSourceData:\"setGeoJSONSourceData\",setLayerZoomRange:\"setLayerZoomRange\",setLayerProperty:\"setLayerProperty\",setCenter:\"setCenter\",setZoom:\"setZoom\",setBearing:\"setBearing\",setPitch:\"setPitch\",setSprite:\"setSprite\",setGlyphs:\"setGlyphs\",setTransition:\"setTransition\",setLight:\"setLight\"};function Vt(t,e,r){r.push({command:Ut.addSource,args:[t,e[t]]})}function Ht(t,e,r){e.push({command:Ut.removeSource,args:[t]}),r[t]=!0}function qt(t,e,r,n){Ht(t,r,n),Vt(t,e,r)}function Gt(e,r,n){var i;for(i in e[n])if(e[n].hasOwnProperty(i)&&\"data\"!==i&&!t.deepEqual(e[n][i],r[n][i]))return!1;for(i in r[n])if(r[n].hasOwnProperty(i)&&\"data\"!==i&&!t.deepEqual(e[n][i],r[n][i]))return!1;return!0}function Yt(e,r,n,i,a,o){var s;for(s in r=r||{},e=e||{})e.hasOwnProperty(s)&&(t.deepEqual(e[s],r[s])||n.push({command:o,args:[i,s,r[s],a]}));for(s in r)r.hasOwnProperty(s)&&!e.hasOwnProperty(s)&&(t.deepEqual(e[s],r[s])||n.push({command:o,args:[i,s,r[s],a]}))}function Wt(t){return t.id}function Xt(t,e){return t[e.id]=e,t}function Zt(e,r){if(!e)return[{command:Ut.setStyle,args:[r]}];var n=[];try{if(!t.deepEqual(e.version,r.version))return[{command:Ut.setStyle,args:[r]}];t.deepEqual(e.center,r.center)||n.push({command:Ut.setCenter,args:[r.center]}),t.deepEqual(e.zoom,r.zoom)||n.push({command:Ut.setZoom,args:[r.zoom]}),t.deepEqual(e.bearing,r.bearing)||n.push({command:Ut.setBearing,args:[r.bearing]}),t.deepEqual(e.pitch,r.pitch)||n.push({command:Ut.setPitch,args:[r.pitch]}),t.deepEqual(e.sprite,r.sprite)||n.push({command:Ut.setSprite,args:[r.sprite]}),t.deepEqual(e.glyphs,r.glyphs)||n.push({command:Ut.setGlyphs,args:[r.glyphs]}),t.deepEqual(e.transition,r.transition)||n.push({command:Ut.setTransition,args:[r.transition]}),t.deepEqual(e.light,r.light)||n.push({command:Ut.setLight,args:[r.light]});var i={},a=[];!function(e,r,n,i){var a;for(a in r=r||{},e=e||{})e.hasOwnProperty(a)&&(r.hasOwnProperty(a)||Ht(a,n,i));for(a in r)r.hasOwnProperty(a)&&(e.hasOwnProperty(a)?t.deepEqual(e[a],r[a])||(\"geojson\"===e[a].type&&\"geojson\"===r[a].type&&Gt(e,r,a)?n.push({command:Ut.setGeoJSONSourceData,args:[a,r[a].data]}):qt(a,r,n,i)):Vt(a,r,n))}(e.sources,r.sources,a,i);var o=[];e.layers&&e.layers.forEach((function(t){i[t.source]?n.push({command:Ut.removeLayer,args:[t.id]}):o.push(t)})),n=n.concat(a),function(e,r,n){r=r||[];var i,a,o,s,l,c,u,f=(e=e||[]).map(Wt),h=r.map(Wt),p=e.reduce(Xt,{}),d=r.reduce(Xt,{}),m=f.slice(),g=Object.create(null);for(i=0,a=0;i<f.length;i++)o=f[i],d.hasOwnProperty(o)?a++:(n.push({command:Ut.removeLayer,args:[o]}),m.splice(m.indexOf(o,a),1));for(i=0,a=0;i<h.length;i++)o=h[h.length-1-i],m[m.length-1-i]!==o&&(p.hasOwnProperty(o)?(n.push({command:Ut.removeLayer,args:[o]}),m.splice(m.lastIndexOf(o,m.length-a),1)):a++,c=m[m.length-i],n.push({command:Ut.addLayer,args:[d[o],c]}),m.splice(m.length-i,0,o),g[o]=!0);for(i=0;i<h.length;i++)if(s=p[o=h[i]],l=d[o],!g[o]&&!t.deepEqual(s,l))if(t.deepEqual(s.source,l.source)&&t.deepEqual(s[\"source-layer\"],l[\"source-layer\"])&&t.deepEqual(s.type,l.type)){for(u in Yt(s.layout,l.layout,n,o,null,Ut.setLayoutProperty),Yt(s.paint,l.paint,n,o,null,Ut.setPaintProperty),t.deepEqual(s.filter,l.filter)||n.push({command:Ut.setFilter,args:[o,l.filter]}),t.deepEqual(s.minzoom,l.minzoom)&&t.deepEqual(s.maxzoom,l.maxzoom)||n.push({command:Ut.setLayerZoomRange,args:[o,l.minzoom,l.maxzoom]}),s)s.hasOwnProperty(u)&&\"layout\"!==u&&\"paint\"!==u&&\"filter\"!==u&&\"metadata\"!==u&&\"minzoom\"!==u&&\"maxzoom\"!==u&&(0===u.indexOf(\"paint.\")?Yt(s[u],l[u],n,o,u.slice(6),Ut.setPaintProperty):t.deepEqual(s[u],l[u])||n.push({command:Ut.setLayerProperty,args:[o,u,l[u]]}));for(u in l)l.hasOwnProperty(u)&&!s.hasOwnProperty(u)&&\"layout\"!==u&&\"paint\"!==u&&\"filter\"!==u&&\"metadata\"!==u&&\"minzoom\"!==u&&\"maxzoom\"!==u&&(0===u.indexOf(\"paint.\")?Yt(s[u],l[u],n,o,u.slice(6),Ut.setPaintProperty):t.deepEqual(s[u],l[u])||n.push({command:Ut.setLayerProperty,args:[o,u,l[u]]}))}else n.push({command:Ut.removeLayer,args:[o]}),c=m[m.lastIndexOf(o)+1],n.push({command:Ut.addLayer,args:[l,c]})}(o,r.layers,n)}catch(t){console.warn(\"Unable to compute style diff:\",t),n=[{command:Ut.setStyle,args:[r]}]}return n}var Jt=function(t,e){this.reset(t,e)};Jt.prototype.reset=function(t,e){this.points=t||[],this._distances=[0];for(var r=1;r<this.points.length;r++)this._distances[r]=this._distances[r-1]+this.points[r].dist(this.points[r-1]);this.length=this._distances[this._distances.length-1],this.padding=Math.min(e||0,.5*this.length),this.paddedLength=this.length-2*this.padding},Jt.prototype.lerp=function(e){if(1===this.points.length)return this.points[0];e=t.clamp(e,0,1);for(var r=1,n=this._distances[r],i=e*this.paddedLength+this.padding;n<i&&r<this._distances.length;)n=this._distances[++r];var a=r-1,o=this._distances[a],s=n-o,l=s>0?(i-o)/s:0;return this.points[a].mult(1-l).add(this.points[r].mult(l))};var Kt=function(t,e,r){var n=this.boxCells=[],i=this.circleCells=[];this.xCellCount=Math.ceil(t/r),this.yCellCount=Math.ceil(e/r);for(var a=0;a<this.xCellCount*this.yCellCount;a++)n.push([]),i.push([]);this.circleKeys=[],this.boxKeys=[],this.bboxes=[],this.circles=[],this.width=t,this.height=e,this.xScale=this.xCellCount/t,this.yScale=this.yCellCount/e,this.boxUid=0,this.circleUid=0};function Qt(e,r,n,i,a){var o=t.create();return r?(t.scale(o,o,[1/a,1/a,1]),n||t.rotateZ(o,o,i.angle)):t.multiply(o,i.labelPlaneMatrix,e),o}function $t(e,r,n,i,a){if(r){var o=t.clone(e);return t.scale(o,o,[a,a,1]),n||t.rotateZ(o,o,-i.angle),o}return i.glCoordMatrix}function te(e,r){var n=[e.x,e.y,0,1];fe(n,n,r);var i=n[3];return{point:new t.Point(n[0]/i,n[1]/i),signedDistanceFromCamera:i}}function ee(t,e){return.5+t/e*.5}function re(t,e){var r=t[0]/t[3],n=t[1]/t[3];return r>=-e[0]&&r<=e[0]&&n>=-e[1]&&n<=e[1]}function ne(e,r,n,i,a,o,s,l){var c=i?e.textSizeData:e.iconSizeData,u=t.evaluateSizeForZoom(c,n.transform.zoom),f=[256/n.width*2+1,256/n.height*2+1],h=i?e.text.dynamicLayoutVertexArray:e.icon.dynamicLayoutVertexArray;h.clear();for(var p=e.lineVertexArray,d=i?e.text.placedSymbolArray:e.icon.placedSymbolArray,m=n.transform.width/n.transform.height,g=!1,v=0;v<d.length;v++){var y=d.get(v);if(y.hidden||y.writingMode===t.WritingMode.vertical&&!g)ue(y.numGlyphs,h);else{g=!1;var x=[y.anchorX,y.anchorY,0,1];if(t.transformMat4(x,x,r),re(x,f)){var b=x[3],_=ee(n.transform.cameraToCenterDistance,b),w=t.evaluateSizeForFeature(c,u,y),T=s?w/_:w*_,k=new t.Point(y.anchorX,y.anchorY),A=te(k,a).point,M={},S=oe(y,T,!1,l,r,a,o,e.glyphOffsetArray,p,h,A,k,M,m);g=S.useVertical,(S.notEnoughRoom||g||S.needsFlipping&&oe(y,T,!0,l,r,a,o,e.glyphOffsetArray,p,h,A,k,M,m).notEnoughRoom)&&ue(y.numGlyphs,h)}else ue(y.numGlyphs,h)}}i?e.text.dynamicLayoutVertexBuffer.updateData(h):e.icon.dynamicLayoutVertexBuffer.updateData(h)}function ie(t,e,r,n,i,a,o,s,l,c,u){var f=s.glyphStartIndex+s.numGlyphs,h=s.lineStartIndex,p=s.lineStartIndex+s.lineLength,d=e.getoffsetX(s.glyphStartIndex),m=e.getoffsetX(f-1),g=le(t*d,r,n,i,a,o,s.segment,h,p,l,c,u);if(!g)return null;var v=le(t*m,r,n,i,a,o,s.segment,h,p,l,c,u);return v?{first:g,last:v}:null}function ae(e,r,n,i){if(e===t.WritingMode.horizontal&&Math.abs(n.y-r.y)>Math.abs(n.x-r.x)*i)return{useVertical:!0};return(e===t.WritingMode.vertical?r.y<n.y:r.x>n.x)?{needsFlipping:!0}:null}function oe(e,r,n,i,a,o,s,l,c,u,f,h,p,d){var m,g=r/24,v=e.lineOffsetX*g,y=e.lineOffsetY*g;if(e.numGlyphs>1){var x=e.glyphStartIndex+e.numGlyphs,b=e.lineStartIndex,_=e.lineStartIndex+e.lineLength,w=ie(g,l,v,y,n,f,h,e,c,o,p);if(!w)return{notEnoughRoom:!0};var T=te(w.first.point,s).point,k=te(w.last.point,s).point;if(i&&!n){var A=ae(e.writingMode,T,k,d);if(A)return A}m=[w.first];for(var M=e.glyphStartIndex+1;M<x-1;M++)m.push(le(g*l.getoffsetX(M),v,y,n,f,h,e.segment,b,_,c,o,p));m.push(w.last)}else{if(i&&!n){var S=te(h,a).point,E=e.lineStartIndex+e.segment+1,L=new t.Point(c.getx(E),c.gety(E)),C=te(L,a),P=C.signedDistanceFromCamera>0?C.point:se(h,L,S,1,a),I=ae(e.writingMode,S,P,d);if(I)return I}var O=le(g*l.getoffsetX(e.glyphStartIndex),v,y,n,f,h,e.segment,e.lineStartIndex,e.lineStartIndex+e.lineLength,c,o,p);if(!O)return{notEnoughRoom:!0};m=[O]}for(var z=0,D=m;z<D.length;z+=1){var R=D[z];t.addDynamicAttributes(u,R.point,R.angle)}return{}}function se(t,e,r,n,i){var a=te(t.add(t.sub(e)._unit()),i).point,o=r.sub(a);return r.add(o._mult(n/o.mag()))}function le(e,r,n,i,a,o,s,l,c,u,f,h){var p=i?e-r:e+r,d=p>0?1:-1,m=0;i&&(d*=-1,m=Math.PI),d<0&&(m+=Math.PI);for(var g=d>0?l+s:l+s+1,v=a,y=a,x=0,b=0,_=Math.abs(p),w=[];x+b<=_;){if((g+=d)<l||g>=c)return null;if(y=v,w.push(v),void 0===(v=h[g])){var T=new t.Point(u.getx(g),u.gety(g)),k=te(T,f);if(k.signedDistanceFromCamera>0)v=h[g]=k.point;else{var A=g-d;v=se(0===x?o:new t.Point(u.getx(A),u.gety(A)),T,y,_-x+1,f)}}x+=b,b=y.dist(v)}var M=(_-x)/b,S=v.sub(y),E=S.mult(M)._add(y);E._add(S._unit()._perp()._mult(n*d));var L=m+Math.atan2(v.y-y.y,v.x-y.x);return w.push(E),{point:E,angle:L,path:w}}Kt.prototype.keysLength=function(){return this.boxKeys.length+this.circleKeys.length},Kt.prototype.insert=function(t,e,r,n,i){this._forEachCell(e,r,n,i,this._insertBoxCell,this.boxUid++),this.boxKeys.push(t),this.bboxes.push(e),this.bboxes.push(r),this.bboxes.push(n),this.bboxes.push(i)},Kt.prototype.insertCircle=function(t,e,r,n){this._forEachCell(e-n,r-n,e+n,r+n,this._insertCircleCell,this.circleUid++),this.circleKeys.push(t),this.circles.push(e),this.circles.push(r),this.circles.push(n)},Kt.prototype._insertBoxCell=function(t,e,r,n,i,a){this.boxCells[i].push(a)},Kt.prototype._insertCircleCell=function(t,e,r,n,i,a){this.circleCells[i].push(a)},Kt.prototype._query=function(t,e,r,n,i,a){if(r<0||t>this.width||n<0||e>this.height)return!i&&[];var o=[];if(t<=0&&e<=0&&this.width<=r&&this.height<=n){if(i)return!0;for(var s=0;s<this.boxKeys.length;s++)o.push({key:this.boxKeys[s],x1:this.bboxes[4*s],y1:this.bboxes[4*s+1],x2:this.bboxes[4*s+2],y2:this.bboxes[4*s+3]});for(var l=0;l<this.circleKeys.length;l++){var c=this.circles[3*l],u=this.circles[3*l+1],f=this.circles[3*l+2];o.push({key:this.circleKeys[l],x1:c-f,y1:u-f,x2:c+f,y2:u+f})}return a?o.filter(a):o}var h={hitTest:i,seenUids:{box:{},circle:{}}};return this._forEachCell(t,e,r,n,this._queryCell,o,h,a),i?o.length>0:o},Kt.prototype._queryCircle=function(t,e,r,n,i){var a=t-r,o=t+r,s=e-r,l=e+r;if(o<0||a>this.width||l<0||s>this.height)return!n&&[];var c=[],u={hitTest:n,circle:{x:t,y:e,radius:r},seenUids:{box:{},circle:{}}};return this._forEachCell(a,s,o,l,this._queryCellCircle,c,u,i),n?c.length>0:c},Kt.prototype.query=function(t,e,r,n,i){return this._query(t,e,r,n,!1,i)},Kt.prototype.hitTest=function(t,e,r,n,i){return this._query(t,e,r,n,!0,i)},Kt.prototype.hitTestCircle=function(t,e,r,n){return this._queryCircle(t,e,r,!0,n)},Kt.prototype._queryCell=function(t,e,r,n,i,a,o,s){var l=o.seenUids,c=this.boxCells[i];if(null!==c)for(var u=this.bboxes,f=0,h=c;f<h.length;f+=1){var p=h[f];if(!l.box[p]){l.box[p]=!0;var d=4*p;if(t<=u[d+2]&&e<=u[d+3]&&r>=u[d+0]&&n>=u[d+1]&&(!s||s(this.boxKeys[p]))){if(o.hitTest)return a.push(!0),!0;a.push({key:this.boxKeys[p],x1:u[d],y1:u[d+1],x2:u[d+2],y2:u[d+3]})}}}var m=this.circleCells[i];if(null!==m)for(var g=this.circles,v=0,y=m;v<y.length;v+=1){var x=y[v];if(!l.circle[x]){l.circle[x]=!0;var b=3*x;if(this._circleAndRectCollide(g[b],g[b+1],g[b+2],t,e,r,n)&&(!s||s(this.circleKeys[x]))){if(o.hitTest)return a.push(!0),!0;var _=g[b],w=g[b+1],T=g[b+2];a.push({key:this.circleKeys[x],x1:_-T,y1:w-T,x2:_+T,y2:w+T})}}}},Kt.prototype._queryCellCircle=function(t,e,r,n,i,a,o,s){var l=o.circle,c=o.seenUids,u=this.boxCells[i];if(null!==u)for(var f=this.bboxes,h=0,p=u;h<p.length;h+=1){var d=p[h];if(!c.box[d]){c.box[d]=!0;var m=4*d;if(this._circleAndRectCollide(l.x,l.y,l.radius,f[m+0],f[m+1],f[m+2],f[m+3])&&(!s||s(this.boxKeys[d])))return a.push(!0),!0}}var g=this.circleCells[i];if(null!==g)for(var v=this.circles,y=0,x=g;y<x.length;y+=1){var b=x[y];if(!c.circle[b]){c.circle[b]=!0;var _=3*b;if(this._circlesCollide(v[_],v[_+1],v[_+2],l.x,l.y,l.radius)&&(!s||s(this.circleKeys[b])))return a.push(!0),!0}}},Kt.prototype._forEachCell=function(t,e,r,n,i,a,o,s){for(var l=this._convertToXCellCoord(t),c=this._convertToYCellCoord(e),u=this._convertToXCellCoord(r),f=this._convertToYCellCoord(n),h=l;h<=u;h++)for(var p=c;p<=f;p++){var d=this.xCellCount*p+h;if(i.call(this,t,e,r,n,d,a,o,s))return}},Kt.prototype._convertToXCellCoord=function(t){return Math.max(0,Math.min(this.xCellCount-1,Math.floor(t*this.xScale)))},Kt.prototype._convertToYCellCoord=function(t){return Math.max(0,Math.min(this.yCellCount-1,Math.floor(t*this.yScale)))},Kt.prototype._circlesCollide=function(t,e,r,n,i,a){var o=n-t,s=i-e,l=r+a;return l*l>o*o+s*s},Kt.prototype._circleAndRectCollide=function(t,e,r,n,i,a,o){var s=(a-n)/2,l=Math.abs(t-(n+s));if(l>s+r)return!1;var c=(o-i)/2,u=Math.abs(e-(i+c));if(u>c+r)return!1;if(l<=s||u<=c)return!0;var f=l-s,h=u-c;return f*f+h*h<=r*r};var ce=new Float32Array([-1/0,-1/0,0,-1/0,-1/0,0,-1/0,-1/0,0,-1/0,-1/0,0]);function ue(t,e){for(var r=0;r<t;r++){var n=e.length;e.resize(n+4),e.float32.set(ce,3*n)}}function fe(t,e,r){var n=e[0],i=e[1];return t[0]=r[0]*n+r[4]*i+r[12],t[1]=r[1]*n+r[5]*i+r[13],t[3]=r[3]*n+r[7]*i+r[15],t}var he=function(t,e,r){void 0===e&&(e=new Kt(t.width+200,t.height+200,25)),void 0===r&&(r=new Kt(t.width+200,t.height+200,25)),this.transform=t,this.grid=e,this.ignoredGrid=r,this.pitchfactor=Math.cos(t._pitch)*t.cameraToCenterDistance,this.screenRightBoundary=t.width+100,this.screenBottomBoundary=t.height+100,this.gridRightBoundary=t.width+200,this.gridBottomBoundary=t.height+200};function pe(e,r,n){return r*(t.EXTENT/(e.tileSize*Math.pow(2,n-e.tileID.overscaledZ)))}he.prototype.placeCollisionBox=function(t,e,r,n,i){var a=this.projectAndGetPerspectiveRatio(n,t.anchorPointX,t.anchorPointY),o=r*a.perspectiveRatio,s=t.x1*o+a.point.x,l=t.y1*o+a.point.y,c=t.x2*o+a.point.x,u=t.y2*o+a.point.y;return!this.isInsideGrid(s,l,c,u)||!e&&this.grid.hitTest(s,l,c,u,i)?{box:[],offscreen:!1}:{box:[s,l,c,u],offscreen:this.isOffscreen(s,l,c,u)}},he.prototype.placeCollisionCircles=function(e,r,n,i,a,o,s,l,c,u,f,h,p){var d=[],m=new t.Point(r.anchorX,r.anchorY),g=te(m,o),v=ee(this.transform.cameraToCenterDistance,g.signedDistanceFromCamera),y=(u?a/v:a*v)/t.ONE_EM,x=te(m,s).point,b=ie(y,i,r.lineOffsetX*y,r.lineOffsetY*y,!1,x,m,r,n,s,{}),_=!1,w=!1,T=!0;if(b){for(var k=.5*h*v+p,A=new t.Point(-100,-100),M=new t.Point(this.screenRightBoundary,this.screenBottomBoundary),S=new Jt,E=b.first,L=b.last,C=[],P=E.path.length-1;P>=1;P--)C.push(E.path[P]);for(var I=1;I<L.path.length;I++)C.push(L.path[I]);var O=2.5*k;if(l){var z=C.map((function(t){return te(t,l)}));C=z.some((function(t){return t.signedDistanceFromCamera<=0}))?[]:z.map((function(t){return t.point}))}var D=[];if(C.length>0){for(var R=C[0].clone(),F=C[0].clone(),B=1;B<C.length;B++)R.x=Math.min(R.x,C[B].x),R.y=Math.min(R.y,C[B].y),F.x=Math.max(F.x,C[B].x),F.y=Math.max(F.y,C[B].y);D=R.x>=A.x&&F.x<=M.x&&R.y>=A.y&&F.y<=M.y?[C]:F.x<A.x||R.x>M.x||F.y<A.y||R.y>M.y?[]:t.clipLine([C],A.x,A.y,M.x,M.y)}for(var N=0,j=D;N<j.length;N+=1){var U=j[N];S.reset(U,.25*k);var V=0;V=S.length<=.5*k?1:Math.ceil(S.paddedLength/O)+1;for(var H=0;H<V;H++){var q=H/Math.max(V-1,1),G=S.lerp(q),Y=G.x+100,W=G.y+100;d.push(Y,W,k,0);var X=Y-k,Z=W-k,J=Y+k,K=W+k;if(T=T&&this.isOffscreen(X,Z,J,K),w=w||this.isInsideGrid(X,Z,J,K),!e&&this.grid.hitTestCircle(Y,W,k,f)&&(_=!0,!c))return{circles:[],offscreen:!1,collisionDetected:_}}}}return{circles:!c&&_||!w?[]:d,offscreen:T,collisionDetected:_}},he.prototype.queryRenderedSymbols=function(e){if(0===e.length||0===this.grid.keysLength()&&0===this.ignoredGrid.keysLength())return{};for(var r=[],n=1/0,i=1/0,a=-1/0,o=-1/0,s=0,l=e;s<l.length;s+=1){var c=l[s],u=new t.Point(c.x+100,c.y+100);n=Math.min(n,u.x),i=Math.min(i,u.y),a=Math.max(a,u.x),o=Math.max(o,u.y),r.push(u)}for(var f={},h={},p=0,d=this.grid.query(n,i,a,o).concat(this.ignoredGrid.query(n,i,a,o));p<d.length;p+=1){var m=d[p],g=m.key;if(void 0===f[g.bucketInstanceId]&&(f[g.bucketInstanceId]={}),!f[g.bucketInstanceId][g.featureIndex]){var v=[new t.Point(m.x1,m.y1),new t.Point(m.x2,m.y1),new t.Point(m.x2,m.y2),new t.Point(m.x1,m.y2)];t.polygonIntersectsPolygon(r,v)&&(f[g.bucketInstanceId][g.featureIndex]=!0,void 0===h[g.bucketInstanceId]&&(h[g.bucketInstanceId]=[]),h[g.bucketInstanceId].push(g.featureIndex))}}return h},he.prototype.insertCollisionBox=function(t,e,r,n,i){var a={bucketInstanceId:r,featureIndex:n,collisionGroupID:i};(e?this.ignoredGrid:this.grid).insert(a,t[0],t[1],t[2],t[3])},he.prototype.insertCollisionCircles=function(t,e,r,n,i){for(var a=e?this.ignoredGrid:this.grid,o={bucketInstanceId:r,featureIndex:n,collisionGroupID:i},s=0;s<t.length;s+=4)a.insertCircle(o,t[s],t[s+1],t[s+2])},he.prototype.projectAndGetPerspectiveRatio=function(e,r,n){var i=[r,n,0,1];return fe(i,i,e),{point:new t.Point((i[0]/i[3]+1)/2*this.transform.width+100,(-i[1]/i[3]+1)/2*this.transform.height+100),perspectiveRatio:.5+this.transform.cameraToCenterDistance/i[3]*.5}},he.prototype.isOffscreen=function(t,e,r,n){return r<100||t>=this.screenRightBoundary||n<100||e>this.screenBottomBoundary},he.prototype.isInsideGrid=function(t,e,r,n){return r>=0&&t<this.gridRightBoundary&&n>=0&&e<this.gridBottomBoundary},he.prototype.getViewportMatrix=function(){var e=t.identity([]);return t.translate(e,e,[-100,-100,0]),e};var de=function(t,e,r,n){this.opacity=t?Math.max(0,Math.min(1,t.opacity+(t.placed?e:-e))):n&&r?1:0,this.placed=r};de.prototype.isHidden=function(){return 0===this.opacity&&!this.placed};var me=function(t,e,r,n,i){this.text=new de(t?t.text:null,e,r,i),this.icon=new de(t?t.icon:null,e,n,i)};me.prototype.isHidden=function(){return this.text.isHidden()&&this.icon.isHidden()};var ge=function(t,e,r){this.text=t,this.icon=e,this.skipFade=r},ve=function(){this.invProjMatrix=t.create(),this.viewportMatrix=t.create(),this.circles=[]},ye=function(t,e,r,n,i){this.bucketInstanceId=t,this.featureIndex=e,this.sourceLayerIndex=r,this.bucketIndex=n,this.tileID=i},xe=function(t){this.crossSourceCollisions=t,this.maxGroupID=0,this.collisionGroups={}};function be(e,r,n,i,a){var o=t.getAnchorAlignment(e),s=-(o.horizontalAlign-.5)*r,l=-(o.verticalAlign-.5)*n,c=t.evaluateVariableOffset(e,i);return new t.Point(s+c[0]*a,l+c[1]*a)}function _e(e,r,n,i,a,o){var s=e.x1,l=e.x2,c=e.y1,u=e.y2,f=e.anchorPointX,h=e.anchorPointY,p=new t.Point(r,n);return i&&p._rotate(a?o:-o),{x1:s+p.x,y1:c+p.y,x2:l+p.x,y2:u+p.y,anchorPointX:f,anchorPointY:h}}xe.prototype.get=function(t){if(this.crossSourceCollisions)return{ID:0,predicate:null};if(!this.collisionGroups[t]){var e=++this.maxGroupID;this.collisionGroups[t]={ID:e,predicate:function(t){return t.collisionGroupID===e}}}return this.collisionGroups[t]};var we=function(t,e,r,n){this.transform=t.clone(),this.collisionIndex=new he(this.transform),this.placements={},this.opacities={},this.variableOffsets={},this.stale=!1,this.commitTime=0,this.fadeDuration=e,this.retainedQueryData={},this.collisionGroups=new xe(r),this.collisionCircleArrays={},this.prevPlacement=n,n&&(n.prevPlacement=void 0),this.placedOrientations={}};function Te(t,e,r,n,i){t.emplaceBack(e?1:0,r?1:0,n||0,i||0),t.emplaceBack(e?1:0,r?1:0,n||0,i||0),t.emplaceBack(e?1:0,r?1:0,n||0,i||0),t.emplaceBack(e?1:0,r?1:0,n||0,i||0)}we.prototype.getBucketParts=function(e,r,n,i){var a=n.getBucket(r),o=n.latestFeatureIndex;if(a&&o&&r.id===a.layerIds[0]){var s=n.collisionBoxArray,l=a.layers[0].layout,c=Math.pow(2,this.transform.zoom-n.tileID.overscaledZ),u=n.tileSize/t.EXTENT,f=this.transform.calculatePosMatrix(n.tileID.toUnwrapped()),h=\"map\"===l.get(\"text-pitch-alignment\"),p=\"map\"===l.get(\"text-rotation-alignment\"),d=pe(n,1,this.transform.zoom),m=Qt(f,h,p,this.transform,d),g=null;if(h){var v=$t(f,h,p,this.transform,d);g=t.multiply([],this.transform.labelPlaneMatrix,v)}this.retainedQueryData[a.bucketInstanceId]=new ye(a.bucketInstanceId,o,a.sourceLayerIndex,a.index,n.tileID);var y={bucket:a,layout:l,posMatrix:f,textLabelPlaneMatrix:m,labelToScreenMatrix:g,scale:c,textPixelRatio:u,holdingForFade:n.holdingForFade(),collisionBoxArray:s,partiallyEvaluatedTextSize:t.evaluateSizeForZoom(a.textSizeData,this.transform.zoom),collisionGroup:this.collisionGroups.get(a.sourceID)};if(i)for(var x=0,b=a.sortKeyRanges;x<b.length;x+=1){var _=b[x],w=_.sortKey,T=_.symbolInstanceStart,k=_.symbolInstanceEnd;e.push({sortKey:w,symbolInstanceStart:T,symbolInstanceEnd:k,parameters:y})}else e.push({symbolInstanceStart:0,symbolInstanceEnd:a.symbolInstances.length,parameters:y})}},we.prototype.attemptAnchorPlacement=function(t,e,r,n,i,a,o,s,l,c,u,f,h,p,d){var m,g=[f.textOffset0,f.textOffset1],v=be(t,r,n,g,i),y=this.collisionIndex.placeCollisionBox(_e(e,v.x,v.y,a,o,this.transform.angle),u,s,l,c.predicate);if(d&&0===this.collisionIndex.placeCollisionBox(_e(d,v.x,v.y,a,o,this.transform.angle),u,s,l,c.predicate).box.length)return;if(y.box.length>0)return this.prevPlacement&&this.prevPlacement.variableOffsets[f.crossTileID]&&this.prevPlacement.placements[f.crossTileID]&&this.prevPlacement.placements[f.crossTileID].text&&(m=this.prevPlacement.variableOffsets[f.crossTileID].anchor),this.variableOffsets[f.crossTileID]={textOffset:g,width:r,height:n,anchor:t,textBoxScale:i,prevAnchor:m},this.markUsedJustification(h,t,f,p),h.allowVerticalPlacement&&(this.markUsedOrientation(h,p,f),this.placedOrientations[f.crossTileID]=p),{shift:v,placedGlyphBoxes:y}},we.prototype.placeLayerBucketPart=function(e,r,n){var i=this,a=e.parameters,o=a.bucket,s=a.layout,l=a.posMatrix,c=a.textLabelPlaneMatrix,u=a.labelToScreenMatrix,f=a.textPixelRatio,h=a.holdingForFade,p=a.collisionBoxArray,d=a.partiallyEvaluatedTextSize,m=a.collisionGroup,g=s.get(\"text-optional\"),v=s.get(\"icon-optional\"),y=s.get(\"text-allow-overlap\"),x=s.get(\"icon-allow-overlap\"),b=\"map\"===s.get(\"text-rotation-alignment\"),_=\"map\"===s.get(\"text-pitch-alignment\"),w=\"none\"!==s.get(\"icon-text-fit\"),T=\"viewport-y\"===s.get(\"symbol-z-order\"),k=y&&(x||!o.hasIconData()||v),A=x&&(y||!o.hasTextData()||g);!o.collisionArrays&&p&&o.deserializeCollisionBoxes(p);var M=function(e,a){if(!r[e.crossTileID])if(h)i.placements[e.crossTileID]=new ge(!1,!1,!1);else{var p,T=!1,M=!1,S=!0,E=null,L={box:null,offscreen:null},C={box:null,offscreen:null},P=null,I=null,O=0,z=0,D=0;a.textFeatureIndex?O=a.textFeatureIndex:e.useRuntimeCollisionCircles&&(O=e.featureIndex),a.verticalTextFeatureIndex&&(z=a.verticalTextFeatureIndex);var R=a.textBox;if(R){var F=function(r){var n=t.WritingMode.horizontal;if(o.allowVerticalPlacement&&!r&&i.prevPlacement){var a=i.prevPlacement.placedOrientations[e.crossTileID];a&&(i.placedOrientations[e.crossTileID]=a,n=a,i.markUsedOrientation(o,n,e))}return n},B=function(r,n){if(o.allowVerticalPlacement&&e.numVerticalGlyphVertices>0&&a.verticalTextBox)for(var i=0,s=o.writingModes;i<s.length;i+=1){if(s[i]===t.WritingMode.vertical?(L=n(),C=L):L=r(),L&&L.box&&L.box.length)break}else L=r()};if(s.get(\"text-variable-anchor\")){var N=s.get(\"text-variable-anchor\");if(i.prevPlacement&&i.prevPlacement.variableOffsets[e.crossTileID]){var j=i.prevPlacement.variableOffsets[e.crossTileID];N.indexOf(j.anchor)>0&&(N=N.filter((function(t){return t!==j.anchor}))).unshift(j.anchor)}var U=function(t,r,n){for(var a=t.x2-t.x1,s=t.y2-t.y1,c=e.textBoxScale,u=w&&!x?r:null,h={box:[],offscreen:!1},p=y?2*N.length:N.length,d=0;d<p;++d){var g=N[d%N.length],v=d>=N.length,k=i.attemptAnchorPlacement(g,t,a,s,c,b,_,f,l,m,v,e,o,n,u);if(k&&(h=k.placedGlyphBoxes)&&h.box&&h.box.length){T=!0,E=k.shift;break}}return h};B((function(){return U(R,a.iconBox,t.WritingMode.horizontal)}),(function(){var r=a.verticalTextBox,n=L&&L.box&&L.box.length;return o.allowVerticalPlacement&&!n&&e.numVerticalGlyphVertices>0&&r?U(r,a.verticalIconBox,t.WritingMode.vertical):{box:null,offscreen:null}})),L&&(T=L.box,S=L.offscreen);var V=F(L&&L.box);if(!T&&i.prevPlacement){var H=i.prevPlacement.variableOffsets[e.crossTileID];H&&(i.variableOffsets[e.crossTileID]=H,i.markUsedJustification(o,H.anchor,e,V))}}else{var q=function(t,r){var n=i.collisionIndex.placeCollisionBox(t,y,f,l,m.predicate);return n&&n.box&&n.box.length&&(i.markUsedOrientation(o,r,e),i.placedOrientations[e.crossTileID]=r),n};B((function(){return q(R,t.WritingMode.horizontal)}),(function(){var r=a.verticalTextBox;return o.allowVerticalPlacement&&e.numVerticalGlyphVertices>0&&r?q(r,t.WritingMode.vertical):{box:null,offscreen:null}})),F(L&&L.box&&L.box.length)}}if(T=(p=L)&&p.box&&p.box.length>0,S=p&&p.offscreen,e.useRuntimeCollisionCircles){var G=o.text.placedSymbolArray.get(e.centerJustifiedTextSymbolIndex),Y=t.evaluateSizeForFeature(o.textSizeData,d,G),W=s.get(\"text-padding\"),X=e.collisionCircleDiameter;P=i.collisionIndex.placeCollisionCircles(y,G,o.lineVertexArray,o.glyphOffsetArray,Y,l,c,u,n,_,m.predicate,X,W),T=y||P.circles.length>0&&!P.collisionDetected,S=S&&P.offscreen}if(a.iconFeatureIndex&&(D=a.iconFeatureIndex),a.iconBox){var Z=function(t){var e=w&&E?_e(t,E.x,E.y,b,_,i.transform.angle):t;return i.collisionIndex.placeCollisionBox(e,x,f,l,m.predicate)};M=C&&C.box&&C.box.length&&a.verticalIconBox?(I=Z(a.verticalIconBox)).box.length>0:(I=Z(a.iconBox)).box.length>0,S=S&&I.offscreen}var J=g||0===e.numHorizontalGlyphVertices&&0===e.numVerticalGlyphVertices,K=v||0===e.numIconVertices;if(J||K?K?J||(M=M&&T):T=M&&T:M=T=M&&T,T&&p&&p.box&&(C&&C.box&&z?i.collisionIndex.insertCollisionBox(p.box,s.get(\"text-ignore-placement\"),o.bucketInstanceId,z,m.ID):i.collisionIndex.insertCollisionBox(p.box,s.get(\"text-ignore-placement\"),o.bucketInstanceId,O,m.ID)),M&&I&&i.collisionIndex.insertCollisionBox(I.box,s.get(\"icon-ignore-placement\"),o.bucketInstanceId,D,m.ID),P&&(T&&i.collisionIndex.insertCollisionCircles(P.circles,s.get(\"text-ignore-placement\"),o.bucketInstanceId,O,m.ID),n)){var Q=o.bucketInstanceId,$=i.collisionCircleArrays[Q];void 0===$&&($=i.collisionCircleArrays[Q]=new ve);for(var tt=0;tt<P.circles.length;tt+=4)$.circles.push(P.circles[tt+0]),$.circles.push(P.circles[tt+1]),$.circles.push(P.circles[tt+2]),$.circles.push(P.collisionDetected?1:0)}i.placements[e.crossTileID]=new ge(T||k,M||A,S||o.justReloaded),r[e.crossTileID]=!0}};if(T)for(var S=o.getSortedSymbolIndexes(this.transform.angle),E=S.length-1;E>=0;--E){var L=S[E];M(o.symbolInstances.get(L),o.collisionArrays[L])}else for(var C=e.symbolInstanceStart;C<e.symbolInstanceEnd;C++)M(o.symbolInstances.get(C),o.collisionArrays[C]);if(n&&o.bucketInstanceId in this.collisionCircleArrays){var P=this.collisionCircleArrays[o.bucketInstanceId];t.invert(P.invProjMatrix,l),P.viewportMatrix=this.collisionIndex.getViewportMatrix()}o.justReloaded=!1},we.prototype.markUsedJustification=function(e,r,n,i){var a,o={left:n.leftJustifiedTextSymbolIndex,center:n.centerJustifiedTextSymbolIndex,right:n.rightJustifiedTextSymbolIndex};a=i===t.WritingMode.vertical?n.verticalPlacedTextSymbolIndex:o[t.getAnchorJustification(r)];for(var s=0,l=[n.leftJustifiedTextSymbolIndex,n.centerJustifiedTextSymbolIndex,n.rightJustifiedTextSymbolIndex,n.verticalPlacedTextSymbolIndex];s<l.length;s+=1){var c=l[s];c>=0&&(e.text.placedSymbolArray.get(c).crossTileID=a>=0&&c!==a?0:n.crossTileID)}},we.prototype.markUsedOrientation=function(e,r,n){for(var i=r===t.WritingMode.horizontal||r===t.WritingMode.horizontalOnly?r:0,a=r===t.WritingMode.vertical?r:0,o=0,s=[n.leftJustifiedTextSymbolIndex,n.centerJustifiedTextSymbolIndex,n.rightJustifiedTextSymbolIndex];o<s.length;o+=1){var l=s[o];e.text.placedSymbolArray.get(l).placedOrientation=i}n.verticalPlacedTextSymbolIndex&&(e.text.placedSymbolArray.get(n.verticalPlacedTextSymbolIndex).placedOrientation=a)},we.prototype.commit=function(t){this.commitTime=t,this.zoomAtLastRecencyCheck=this.transform.zoom;var e=this.prevPlacement,r=!1;this.prevZoomAdjustment=e?e.zoomAdjustment(this.transform.zoom):0;var n=e?e.symbolFadeChange(t):1,i=e?e.opacities:{},a=e?e.variableOffsets:{},o=e?e.placedOrientations:{};for(var s in this.placements){var l=this.placements[s],c=i[s];c?(this.opacities[s]=new me(c,n,l.text,l.icon),r=r||l.text!==c.text.placed||l.icon!==c.icon.placed):(this.opacities[s]=new me(null,n,l.text,l.icon,l.skipFade),r=r||l.text||l.icon)}for(var u in i){var f=i[u];if(!this.opacities[u]){var h=new me(f,n,!1,!1);h.isHidden()||(this.opacities[u]=h,r=r||f.text.placed||f.icon.placed)}}for(var p in a)this.variableOffsets[p]||!this.opacities[p]||this.opacities[p].isHidden()||(this.variableOffsets[p]=a[p]);for(var d in o)this.placedOrientations[d]||!this.opacities[d]||this.opacities[d].isHidden()||(this.placedOrientations[d]=o[d]);r?this.lastPlacementChangeTime=t:\"number\"!=typeof this.lastPlacementChangeTime&&(this.lastPlacementChangeTime=e?e.lastPlacementChangeTime:t)},we.prototype.updateLayerOpacities=function(t,e){for(var r={},n=0,i=e;n<i.length;n+=1){var a=i[n],o=a.getBucket(t);o&&a.latestFeatureIndex&&t.id===o.layerIds[0]&&this.updateBucketOpacities(o,r,a.collisionBoxArray)}},we.prototype.updateBucketOpacities=function(e,r,n){var i=this;e.hasTextData()&&e.text.opacityVertexArray.clear(),e.hasIconData()&&e.icon.opacityVertexArray.clear(),e.hasIconCollisionBoxData()&&e.iconCollisionBox.collisionVertexArray.clear(),e.hasTextCollisionBoxData()&&e.textCollisionBox.collisionVertexArray.clear();var a=e.layers[0].layout,o=new me(null,0,!1,!1,!0),s=a.get(\"text-allow-overlap\"),l=a.get(\"icon-allow-overlap\"),c=a.get(\"text-variable-anchor\"),u=\"map\"===a.get(\"text-rotation-alignment\"),f=\"map\"===a.get(\"text-pitch-alignment\"),h=\"none\"!==a.get(\"icon-text-fit\"),p=new me(null,0,s&&(l||!e.hasIconData()||a.get(\"icon-optional\")),l&&(s||!e.hasTextData()||a.get(\"text-optional\")),!0);!e.collisionArrays&&n&&(e.hasIconCollisionBoxData()||e.hasTextCollisionBoxData())&&e.deserializeCollisionBoxes(n);for(var d=function(t,e,r){for(var n=0;n<e/4;n++)t.opacityVertexArray.emplaceBack(r)},m=function(n){var a=e.symbolInstances.get(n),s=a.numHorizontalGlyphVertices,l=a.numVerticalGlyphVertices,m=a.crossTileID,g=r[m],v=i.opacities[m];g?v=o:v||(v=p,i.opacities[m]=v),r[m]=!0;var y=s>0||l>0,x=a.numIconVertices>0,b=i.placedOrientations[a.crossTileID],_=b===t.WritingMode.vertical,w=b===t.WritingMode.horizontal||b===t.WritingMode.horizontalOnly;if(y){var T=Pe(v.text),k=_?Ie:T;d(e.text,s,k);var A=w?Ie:T;d(e.text,l,A);var M=v.text.isHidden();[a.rightJustifiedTextSymbolIndex,a.centerJustifiedTextSymbolIndex,a.leftJustifiedTextSymbolIndex].forEach((function(t){t>=0&&(e.text.placedSymbolArray.get(t).hidden=M||_?1:0)})),a.verticalPlacedTextSymbolIndex>=0&&(e.text.placedSymbolArray.get(a.verticalPlacedTextSymbolIndex).hidden=M||w?1:0);var S=i.variableOffsets[a.crossTileID];S&&i.markUsedJustification(e,S.anchor,a,b);var E=i.placedOrientations[a.crossTileID];E&&(i.markUsedJustification(e,\"left\",a,E),i.markUsedOrientation(e,E,a))}if(x){var L=Pe(v.icon),C=!(h&&a.verticalPlacedIconSymbolIndex&&_);if(a.placedIconSymbolIndex>=0){var P=C?L:Ie;d(e.icon,a.numIconVertices,P),e.icon.placedSymbolArray.get(a.placedIconSymbolIndex).hidden=v.icon.isHidden()}if(a.verticalPlacedIconSymbolIndex>=0){var I=C?Ie:L;d(e.icon,a.numVerticalIconVertices,I),e.icon.placedSymbolArray.get(a.verticalPlacedIconSymbolIndex).hidden=v.icon.isHidden()}}if(e.hasIconCollisionBoxData()||e.hasTextCollisionBoxData()){var O=e.collisionArrays[n];if(O){var z=new t.Point(0,0);if(O.textBox||O.verticalTextBox){var D=!0;if(c){var R=i.variableOffsets[m];R?(z=be(R.anchor,R.width,R.height,R.textOffset,R.textBoxScale),u&&z._rotate(f?i.transform.angle:-i.transform.angle)):D=!1}O.textBox&&Te(e.textCollisionBox.collisionVertexArray,v.text.placed,!D||_,z.x,z.y),O.verticalTextBox&&Te(e.textCollisionBox.collisionVertexArray,v.text.placed,!D||w,z.x,z.y)}var F=Boolean(!w&&O.verticalIconBox);O.iconBox&&Te(e.iconCollisionBox.collisionVertexArray,v.icon.placed,F,h?z.x:0,h?z.y:0),O.verticalIconBox&&Te(e.iconCollisionBox.collisionVertexArray,v.icon.placed,!F,h?z.x:0,h?z.y:0)}}},g=0;g<e.symbolInstances.length;g++)m(g);if(e.sortFeatures(this.transform.angle),this.retainedQueryData[e.bucketInstanceId]&&(this.retainedQueryData[e.bucketInstanceId].featureSortOrder=e.featureSortOrder),e.hasTextData()&&e.text.opacityVertexBuffer&&e.text.opacityVertexBuffer.updateData(e.text.opacityVertexArray),e.hasIconData()&&e.icon.opacityVertexBuffer&&e.icon.opacityVertexBuffer.updateData(e.icon.opacityVertexArray),e.hasIconCollisionBoxData()&&e.iconCollisionBox.collisionVertexBuffer&&e.iconCollisionBox.collisionVertexBuffer.updateData(e.iconCollisionBox.collisionVertexArray),e.hasTextCollisionBoxData()&&e.textCollisionBox.collisionVertexBuffer&&e.textCollisionBox.collisionVertexBuffer.updateData(e.textCollisionBox.collisionVertexArray),e.bucketInstanceId in this.collisionCircleArrays){var v=this.collisionCircleArrays[e.bucketInstanceId];e.placementInvProjMatrix=v.invProjMatrix,e.placementViewportMatrix=v.viewportMatrix,e.collisionCircleArray=v.circles,delete this.collisionCircleArrays[e.bucketInstanceId]}},we.prototype.symbolFadeChange=function(t){return 0===this.fadeDuration?1:(t-this.commitTime)/this.fadeDuration+this.prevZoomAdjustment},we.prototype.zoomAdjustment=function(t){return Math.max(0,(this.transform.zoom-t)/1.5)},we.prototype.hasTransitions=function(t){return this.stale||t-this.lastPlacementChangeTime<this.fadeDuration},we.prototype.stillRecent=function(t,e){var r=this.zoomAtLastRecencyCheck===e?1-this.zoomAdjustment(e):1;return this.zoomAtLastRecencyCheck=e,this.commitTime+this.fadeDuration*r>t},we.prototype.setStale=function(){this.stale=!0};var ke=Math.pow(2,25),Ae=Math.pow(2,24),Me=Math.pow(2,17),Se=Math.pow(2,16),Ee=Math.pow(2,9),Le=Math.pow(2,8),Ce=Math.pow(2,1);function Pe(t){if(0===t.opacity&&!t.placed)return 0;if(1===t.opacity&&t.placed)return 4294967295;var e=t.placed?1:0,r=Math.floor(127*t.opacity);return r*ke+e*Ae+r*Me+e*Se+r*Ee+e*Le+r*Ce+e}var Ie=0,Oe=function(t){this._sortAcrossTiles=\"viewport-y\"!==t.layout.get(\"symbol-z-order\")&&void 0!==t.layout.get(\"symbol-sort-key\").constantOr(1),this._currentTileIndex=0,this._currentPartIndex=0,this._seenCrossTileIDs={},this._bucketParts=[]};Oe.prototype.continuePlacement=function(t,e,r,n,i){for(var a=this._bucketParts;this._currentTileIndex<t.length;){var o=t[this._currentTileIndex];if(e.getBucketParts(a,n,o,this._sortAcrossTiles),this._currentTileIndex++,i())return!0}for(this._sortAcrossTiles&&(this._sortAcrossTiles=!1,a.sort((function(t,e){return t.sortKey-e.sortKey})));this._currentPartIndex<a.length;){var s=a[this._currentPartIndex];if(e.placeLayerBucketPart(s,this._seenCrossTileIDs,r),this._currentPartIndex++,i())return!0}return!1};var ze=function(t,e,r,n,i,a,o){this.placement=new we(t,i,a,o),this._currentPlacementIndex=e.length-1,this._forceFullPlacement=r,this._showCollisionBoxes=n,this._done=!1};ze.prototype.isDone=function(){return this._done},ze.prototype.continuePlacement=function(e,r,n){for(var i=this,a=t.browser.now(),o=function(){var e=t.browser.now()-a;return!i._forceFullPlacement&&e>2};this._currentPlacementIndex>=0;){var s=r[e[this._currentPlacementIndex]],l=this.placement.collisionIndex.transform.zoom;if(\"symbol\"===s.type&&(!s.minzoom||s.minzoom<=l)&&(!s.maxzoom||s.maxzoom>l)){if(this._inProgressLayer||(this._inProgressLayer=new Oe(s)),this._inProgressLayer.continuePlacement(n[s.source],this.placement,this._showCollisionBoxes,s,o))return;delete this._inProgressLayer}this._currentPlacementIndex--}this._done=!0},ze.prototype.commit=function(t){return this.placement.commit(t),this.placement};var De=512/t.EXTENT/2,Re=function(t,e,r){this.tileID=t,this.indexedSymbolInstances={},this.bucketInstanceId=r;for(var n=0;n<e.length;n++){var i=e.get(n),a=i.key;this.indexedSymbolInstances[a]||(this.indexedSymbolInstances[a]=[]),this.indexedSymbolInstances[a].push({crossTileID:i.crossTileID,coord:this.getScaledCoordinates(i,t)})}};Re.prototype.getScaledCoordinates=function(e,r){var n=r.canonical.z-this.tileID.canonical.z,i=De/Math.pow(2,n);return{x:Math.floor((r.canonical.x*t.EXTENT+e.anchorX)*i),y:Math.floor((r.canonical.y*t.EXTENT+e.anchorY)*i)}},Re.prototype.findMatches=function(t,e,r){for(var n=this.tileID.canonical.z<e.canonical.z?1:Math.pow(2,this.tileID.canonical.z-e.canonical.z),i=0;i<t.length;i++){var a=t.get(i);if(!a.crossTileID){var o=this.indexedSymbolInstances[a.key];if(o)for(var s=this.getScaledCoordinates(a,e),l=0,c=o;l<c.length;l+=1){var u=c[l];if(Math.abs(u.coord.x-s.x)<=n&&Math.abs(u.coord.y-s.y)<=n&&!r[u.crossTileID]){r[u.crossTileID]=!0,a.crossTileID=u.crossTileID;break}}}}};var Fe=function(){this.maxCrossTileID=0};Fe.prototype.generate=function(){return++this.maxCrossTileID};var Be=function(){this.indexes={},this.usedCrossTileIDs={},this.lng=0};Be.prototype.handleWrapJump=function(t){var e=Math.round((t-this.lng)/360);if(0!==e)for(var r in this.indexes){var n=this.indexes[r],i={};for(var a in n){var o=n[a];o.tileID=o.tileID.unwrapTo(o.tileID.wrap+e),i[o.tileID.key]=o}this.indexes[r]=i}this.lng=t},Be.prototype.addBucket=function(t,e,r){if(this.indexes[t.overscaledZ]&&this.indexes[t.overscaledZ][t.key]){if(this.indexes[t.overscaledZ][t.key].bucketInstanceId===e.bucketInstanceId)return!1;this.removeBucketCrossTileIDs(t.overscaledZ,this.indexes[t.overscaledZ][t.key])}for(var n=0;n<e.symbolInstances.length;n++){e.symbolInstances.get(n).crossTileID=0}this.usedCrossTileIDs[t.overscaledZ]||(this.usedCrossTileIDs[t.overscaledZ]={});var i=this.usedCrossTileIDs[t.overscaledZ];for(var a in this.indexes){var o=this.indexes[a];if(Number(a)>t.overscaledZ)for(var s in o){var l=o[s];l.tileID.isChildOf(t)&&l.findMatches(e.symbolInstances,t,i)}else{var c=o[t.scaledTo(Number(a)).key];c&&c.findMatches(e.symbolInstances,t,i)}}for(var u=0;u<e.symbolInstances.length;u++){var f=e.symbolInstances.get(u);f.crossTileID||(f.crossTileID=r.generate(),i[f.crossTileID]=!0)}return void 0===this.indexes[t.overscaledZ]&&(this.indexes[t.overscaledZ]={}),this.indexes[t.overscaledZ][t.key]=new Re(t,e.symbolInstances,e.bucketInstanceId),!0},Be.prototype.removeBucketCrossTileIDs=function(t,e){for(var r in e.indexedSymbolInstances)for(var n=0,i=e.indexedSymbolInstances[r];n<i.length;n+=1){var a=i[n];delete this.usedCrossTileIDs[t][a.crossTileID]}},Be.prototype.removeStaleBuckets=function(t){var e=!1;for(var r in this.indexes){var n=this.indexes[r];for(var i in n)t[n[i].bucketInstanceId]||(this.removeBucketCrossTileIDs(r,n[i]),delete n[i],e=!0)}return e};var Ne=function(){this.layerIndexes={},this.crossTileIDs=new Fe,this.maxBucketInstanceId=0,this.bucketsInCurrentPlacement={}};Ne.prototype.addLayer=function(t,e,r){var n=this.layerIndexes[t.id];void 0===n&&(n=this.layerIndexes[t.id]=new Be);var i=!1,a={};n.handleWrapJump(r);for(var o=0,s=e;o<s.length;o+=1){var l=s[o],c=l.getBucket(t);c&&t.id===c.layerIds[0]&&(c.bucketInstanceId||(c.bucketInstanceId=++this.maxBucketInstanceId),n.addBucket(l.tileID,c,this.crossTileIDs)&&(i=!0),a[c.bucketInstanceId]=!0)}return n.removeStaleBuckets(a)&&(i=!0),i},Ne.prototype.pruneUnusedLayers=function(t){var e={};for(var r in t.forEach((function(t){e[t]=!0})),this.layerIndexes)e[r]||delete this.layerIndexes[r]};var je=function(e,r){return t.emitValidationErrors(e,r&&r.filter((function(t){return\"source.canvas\"!==t.identifier})))},Ue=t.pick(Ut,[\"addLayer\",\"removeLayer\",\"setPaintProperty\",\"setLayoutProperty\",\"setFilter\",\"addSource\",\"removeSource\",\"setLayerZoomRange\",\"setLight\",\"setTransition\",\"setGeoJSONSourceData\"]),Ve=t.pick(Ut,[\"setCenter\",\"setZoom\",\"setBearing\",\"setPitch\"]),He=function(){var e={},r=t.styleSpec.$version;for(var n in t.styleSpec.$root){var i=t.styleSpec.$root[n];if(i.required){var a=null;null!=(a=\"version\"===n?r:\"array\"===i.type?[]:{})&&(e[n]=a)}}return e}(),qe=function(e){function r(n,i){var a=this;void 0===i&&(i={}),e.call(this),this.map=n,this.dispatcher=new k(Bt(),this),this.imageManager=new h,this.imageManager.setEventedParent(this),this.glyphManager=new x(n._requestManager,i.localIdeographFontFamily),this.lineAtlas=new T(256,512),this.crossTileSymbolIndex=new Ne,this._layers={},this._serializedLayers={},this._order=[],this.sourceCaches={},this.zoomHistory=new t.ZoomHistory,this._loaded=!1,this._availableImages=[],this._resetUpdates(),this.dispatcher.broadcast(\"setReferrer\",t.getReferrer());var o=this;this._rtlTextPluginCallback=r.registerForPluginStateChange((function(e){var r={pluginStatus:e.pluginStatus,pluginURL:e.pluginURL};o.dispatcher.broadcast(\"syncRTLPluginState\",r,(function(e,r){if((t.triggerPluginCompletionEvent(e),r)&&r.every((function(t){return t})))for(var n in o.sourceCaches)o.sourceCaches[n].reload()}))})),this.on(\"data\",(function(t){if(\"source\"===t.dataType&&\"metadata\"===t.sourceDataType){var e=a.sourceCaches[t.sourceId];if(e){var r=e.getSource();if(r&&r.vectorLayerIds)for(var n in a._layers){var i=a._layers[n];i.source===r.id&&a._validateLayer(i)}}}}))}return e&&(r.__proto__=e),r.prototype=Object.create(e&&e.prototype),r.prototype.constructor=r,r.prototype.loadURL=function(e,r){var n=this;void 0===r&&(r={}),this.fire(new t.Event(\"dataloading\",{dataType:\"style\"}));var i=\"boolean\"==typeof r.validate?r.validate:!t.isMapboxURL(e);e=this.map._requestManager.normalizeStyleURL(e,r.accessToken);var a=this.map._requestManager.transformRequest(e,t.ResourceType.Style);this._request=t.getJSON(a,(function(e,r){n._request=null,e?n.fire(new t.ErrorEvent(e)):r&&n._load(r,i)}))},r.prototype.loadJSON=function(e,r){var n=this;void 0===r&&(r={}),this.fire(new t.Event(\"dataloading\",{dataType:\"style\"})),this._request=t.browser.frame((function(){n._request=null,n._load(e,!1!==r.validate)}))},r.prototype.loadEmpty=function(){this.fire(new t.Event(\"dataloading\",{dataType:\"style\"})),this._load(He,!1)},r.prototype._load=function(e,r){if(!r||!je(this,t.validateStyle(e))){for(var n in this._loaded=!0,this.stylesheet=e,e.sources)this.addSource(n,e.sources[n],{validate:!1});e.sprite?this._loadSprite(e.sprite):this.imageManager.setLoaded(!0),this.glyphManager.setURL(e.glyphs);var i=jt(this.stylesheet.layers);this._order=i.map((function(t){return t.id})),this._layers={},this._serializedLayers={};for(var a=0,o=i;a<o.length;a+=1){var s=o[a];(s=t.createStyleLayer(s)).setEventedParent(this,{layer:{id:s.id}}),this._layers[s.id]=s,this._serializedLayers[s.id]=s.serialize()}this.dispatcher.broadcast(\"setLayers\",this._serializeLayers(this._order)),this.light=new w(this.stylesheet.light),this.fire(new t.Event(\"data\",{dataType:\"style\"})),this.fire(new t.Event(\"style.load\"))}},r.prototype._loadSprite=function(e){var r=this;this._spriteRequest=function(e,r,n){var i,a,o,s=t.browser.devicePixelRatio>1?\"@2x\":\"\",l=t.getJSON(r.transformRequest(r.normalizeSpriteURL(e,s,\".json\"),t.ResourceType.SpriteJSON),(function(t,e){l=null,o||(o=t,i=e,u())})),c=t.getImage(r.transformRequest(r.normalizeSpriteURL(e,s,\".png\"),t.ResourceType.SpriteImage),(function(t,e){c=null,o||(o=t,a=e,u())}));function u(){if(o)n(o);else if(i&&a){var e=t.browser.getImageData(a),r={};for(var s in i){var l=i[s],c=l.width,u=l.height,f=l.x,h=l.y,p=l.sdf,d=l.pixelRatio,m=l.stretchX,g=l.stretchY,v=l.content,y=new t.RGBAImage({width:c,height:u});t.RGBAImage.copy(e,y,{x:f,y:h},{x:0,y:0},{width:c,height:u}),r[s]={data:y,pixelRatio:d,sdf:p,stretchX:m,stretchY:g,content:v}}n(null,r)}}return{cancel:function(){l&&(l.cancel(),l=null),c&&(c.cancel(),c=null)}}}(e,this.map._requestManager,(function(e,n){if(r._spriteRequest=null,e)r.fire(new t.ErrorEvent(e));else if(n)for(var i in n)r.imageManager.addImage(i,n[i]);r.imageManager.setLoaded(!0),r._availableImages=r.imageManager.listImages(),r.dispatcher.broadcast(\"setImages\",r._availableImages),r.fire(new t.Event(\"data\",{dataType:\"style\"}))}))},r.prototype._validateLayer=function(e){var r=this.sourceCaches[e.source];if(r){var n=e.sourceLayer;if(n){var i=r.getSource();(\"geojson\"===i.type||i.vectorLayerIds&&-1===i.vectorLayerIds.indexOf(n))&&this.fire(new t.ErrorEvent(new Error('Source layer \"'+n+'\" does not exist on source \"'+i.id+'\" as specified by style layer \"'+e.id+'\"')))}}},r.prototype.loaded=function(){if(!this._loaded)return!1;if(Object.keys(this._updatedSources).length)return!1;for(var t in this.sourceCaches)if(!this.sourceCaches[t].loaded())return!1;return!!this.imageManager.isLoaded()},r.prototype._serializeLayers=function(t){for(var e=[],r=0,n=t;r<n.length;r+=1){var i=n[r],a=this._layers[i];\"custom\"!==a.type&&e.push(a.serialize())}return e},r.prototype.hasTransitions=function(){if(this.light&&this.light.hasTransition())return!0;for(var t in this.sourceCaches)if(this.sourceCaches[t].hasTransition())return!0;for(var e in this._layers)if(this._layers[e].hasTransition())return!0;return!1},r.prototype._checkLoaded=function(){if(!this._loaded)throw new Error(\"Style is not done loading\")},r.prototype.update=function(e){if(this._loaded){var r=this._changed;if(this._changed){var n=Object.keys(this._updatedLayers),i=Object.keys(this._removedLayers);for(var a in(n.length||i.length)&&this._updateWorkerLayers(n,i),this._updatedSources){var o=this._updatedSources[a];\"reload\"===o?this._reloadSource(a):\"clear\"===o&&this._clearSource(a)}for(var s in this._updateTilesForChangedImages(),this._updatedPaintProps)this._layers[s].updateTransitions(e);this.light.updateTransitions(e),this._resetUpdates()}for(var l in this.sourceCaches)this.sourceCaches[l].used=!1;for(var c=0,u=this._order;c<u.length;c+=1){var f=u[c],h=this._layers[f];h.recalculate(e,this._availableImages),!h.isHidden(e.zoom)&&h.source&&(this.sourceCaches[h.source].used=!0)}this.light.recalculate(e),this.z=e.zoom,r&&this.fire(new t.Event(\"data\",{dataType:\"style\"}))}},r.prototype._updateTilesForChangedImages=function(){var t=Object.keys(this._changedImages);if(t.length){for(var e in this.sourceCaches)this.sourceCaches[e].reloadTilesForDependencies([\"icons\",\"patterns\"],t);this._changedImages={}}},r.prototype._updateWorkerLayers=function(t,e){this.dispatcher.broadcast(\"updateLayers\",{layers:this._serializeLayers(t),removedIds:e})},r.prototype._resetUpdates=function(){this._changed=!1,this._updatedLayers={},this._removedLayers={},this._updatedSources={},this._updatedPaintProps={},this._changedImages={}},r.prototype.setState=function(e){var r=this;if(this._checkLoaded(),je(this,t.validateStyle(e)))return!1;(e=t.clone$1(e)).layers=jt(e.layers);var n=Zt(this.serialize(),e).filter((function(t){return!(t.command in Ve)}));if(0===n.length)return!1;var i=n.filter((function(t){return!(t.command in Ue)}));if(i.length>0)throw new Error(\"Unimplemented: \"+i.map((function(t){return t.command})).join(\", \")+\".\");return n.forEach((function(t){\"setTransition\"!==t.command&&r[t.command].apply(r,t.args)})),this.stylesheet=e,!0},r.prototype.addImage=function(e,r){if(this.getImage(e))return this.fire(new t.ErrorEvent(new Error(\"An image with this name already exists.\")));this.imageManager.addImage(e,r),this._availableImages=this.imageManager.listImages(),this._changedImages[e]=!0,this._changed=!0,this.fire(new t.Event(\"data\",{dataType:\"style\"}))},r.prototype.updateImage=function(t,e){this.imageManager.updateImage(t,e)},r.prototype.getImage=function(t){return this.imageManager.getImage(t)},r.prototype.removeImage=function(e){if(!this.getImage(e))return this.fire(new t.ErrorEvent(new Error(\"No image with this name exists.\")));this.imageManager.removeImage(e),this._availableImages=this.imageManager.listImages(),this._changedImages[e]=!0,this._changed=!0,this.fire(new t.Event(\"data\",{dataType:\"style\"}))},r.prototype.listImages=function(){return this._checkLoaded(),this.imageManager.listImages()},r.prototype.addSource=function(e,r,n){var i=this;if(void 0===n&&(n={}),this._checkLoaded(),void 0!==this.sourceCaches[e])throw new Error(\"There is already a source with this ID\");if(!r.type)throw new Error(\"The type property must be defined, but the only the following properties were given: \"+Object.keys(r).join(\", \")+\".\");if(!([\"vector\",\"raster\",\"geojson\",\"video\",\"image\"].indexOf(r.type)>=0)||!this._validate(t.validateStyle.source,\"sources.\"+e,r,null,n)){this.map&&this.map._collectResourceTiming&&(r.collectResourceTiming=!0);var a=this.sourceCaches[e]=new Ct(e,r,this.dispatcher);a.style=this,a.setEventedParent(this,(function(){return{isSourceLoaded:i.loaded(),source:a.serialize(),sourceId:e}})),a.onAdd(this.map),this._changed=!0}},r.prototype.removeSource=function(e){if(this._checkLoaded(),void 0===this.sourceCaches[e])throw new Error(\"There is no source with this ID\");for(var r in this._layers)if(this._layers[r].source===e)return this.fire(new t.ErrorEvent(new Error('Source \"'+e+'\" cannot be removed while layer \"'+r+'\" is using it.')));var n=this.sourceCaches[e];delete this.sourceCaches[e],delete this._updatedSources[e],n.fire(new t.Event(\"data\",{sourceDataType:\"metadata\",dataType:\"source\",sourceId:e})),n.setEventedParent(null),n.clearTiles(),n.onRemove&&n.onRemove(this.map),this._changed=!0},r.prototype.setGeoJSONSourceData=function(t,e){this._checkLoaded(),this.sourceCaches[t].getSource().setData(e),this._changed=!0},r.prototype.getSource=function(t){return this.sourceCaches[t]&&this.sourceCaches[t].getSource()},r.prototype.addLayer=function(e,r,n){void 0===n&&(n={}),this._checkLoaded();var i=e.id;if(this.getLayer(i))this.fire(new t.ErrorEvent(new Error('Layer with id \"'+i+'\" already exists on this map')));else{var a;if(\"custom\"===e.type){if(je(this,t.validateCustomStyleLayer(e)))return;a=t.createStyleLayer(e)}else{if(\"object\"==typeof e.source&&(this.addSource(i,e.source),e=t.clone$1(e),e=t.extend(e,{source:i})),this._validate(t.validateStyle.layer,\"layers.\"+i,e,{arrayIndex:-1},n))return;a=t.createStyleLayer(e),this._validateLayer(a),a.setEventedParent(this,{layer:{id:i}}),this._serializedLayers[a.id]=a.serialize()}var o=r?this._order.indexOf(r):this._order.length;if(r&&-1===o)this.fire(new t.ErrorEvent(new Error('Layer with id \"'+r+'\" does not exist on this map.')));else{if(this._order.splice(o,0,i),this._layerOrderChanged=!0,this._layers[i]=a,this._removedLayers[i]&&a.source&&\"custom\"!==a.type){var s=this._removedLayers[i];delete this._removedLayers[i],s.type!==a.type?this._updatedSources[a.source]=\"clear\":(this._updatedSources[a.source]=\"reload\",this.sourceCaches[a.source].pause())}this._updateLayer(a),a.onAdd&&a.onAdd(this.map)}}},r.prototype.moveLayer=function(e,r){if(this._checkLoaded(),this._changed=!0,this._layers[e]){if(e!==r){var n=this._order.indexOf(e);this._order.splice(n,1);var i=r?this._order.indexOf(r):this._order.length;r&&-1===i?this.fire(new t.ErrorEvent(new Error('Layer with id \"'+r+'\" does not exist on this map.'))):(this._order.splice(i,0,e),this._layerOrderChanged=!0)}}else this.fire(new t.ErrorEvent(new Error(\"The layer '\"+e+\"' does not exist in the map's style and cannot be moved.\")))},r.prototype.removeLayer=function(e){this._checkLoaded();var r=this._layers[e];if(r){r.setEventedParent(null);var n=this._order.indexOf(e);this._order.splice(n,1),this._layerOrderChanged=!0,this._changed=!0,this._removedLayers[e]=r,delete this._layers[e],delete this._serializedLayers[e],delete this._updatedLayers[e],delete this._updatedPaintProps[e],r.onRemove&&r.onRemove(this.map)}else this.fire(new t.ErrorEvent(new Error(\"The layer '\"+e+\"' does not exist in the map's style and cannot be removed.\")))},r.prototype.getLayer=function(t){return this._layers[t]},r.prototype.hasLayer=function(t){return t in this._layers},r.prototype.setLayerZoomRange=function(e,r,n){this._checkLoaded();var i=this.getLayer(e);i?i.minzoom===r&&i.maxzoom===n||(null!=r&&(i.minzoom=r),null!=n&&(i.maxzoom=n),this._updateLayer(i)):this.fire(new t.ErrorEvent(new Error(\"The layer '\"+e+\"' does not exist in the map's style and cannot have zoom extent.\")))},r.prototype.setFilter=function(e,r,n){void 0===n&&(n={}),this._checkLoaded();var i=this.getLayer(e);if(i){if(!t.deepEqual(i.filter,r))return null==r?(i.filter=void 0,void this._updateLayer(i)):void(this._validate(t.validateStyle.filter,\"layers.\"+i.id+\".filter\",r,null,n)||(i.filter=t.clone$1(r),this._updateLayer(i)))}else this.fire(new t.ErrorEvent(new Error(\"The layer '\"+e+\"' does not exist in the map's style and cannot be filtered.\")))},r.prototype.getFilter=function(e){return t.clone$1(this.getLayer(e).filter)},r.prototype.setLayoutProperty=function(e,r,n,i){void 0===i&&(i={}),this._checkLoaded();var a=this.getLayer(e);a?t.deepEqual(a.getLayoutProperty(r),n)||(a.setLayoutProperty(r,n,i),this._updateLayer(a)):this.fire(new t.ErrorEvent(new Error(\"The layer '\"+e+\"' does not exist in the map's style and cannot be styled.\")))},r.prototype.getLayoutProperty=function(e,r){var n=this.getLayer(e);if(n)return n.getLayoutProperty(r);this.fire(new t.ErrorEvent(new Error(\"The layer '\"+e+\"' does not exist in the map's style.\")))},r.prototype.setPaintProperty=function(e,r,n,i){void 0===i&&(i={}),this._checkLoaded();var a=this.getLayer(e);a?t.deepEqual(a.getPaintProperty(r),n)||(a.setPaintProperty(r,n,i)&&this._updateLayer(a),this._changed=!0,this._updatedPaintProps[e]=!0):this.fire(new t.ErrorEvent(new Error(\"The layer '\"+e+\"' does not exist in the map's style and cannot be styled.\")))},r.prototype.getPaintProperty=function(t,e){return this.getLayer(t).getPaintProperty(e)},r.prototype.setFeatureState=function(e,r){this._checkLoaded();var n=e.source,i=e.sourceLayer,a=this.sourceCaches[n];if(void 0!==a){var o=a.getSource().type;\"geojson\"===o&&i?this.fire(new t.ErrorEvent(new Error(\"GeoJSON sources cannot have a sourceLayer parameter.\"))):\"vector\"!==o||i?(void 0===e.id&&this.fire(new t.ErrorEvent(new Error(\"The feature id parameter must be provided.\"))),a.setFeatureState(i,e.id,r)):this.fire(new t.ErrorEvent(new Error(\"The sourceLayer parameter must be provided for vector source types.\")))}else this.fire(new t.ErrorEvent(new Error(\"The source '\"+n+\"' does not exist in the map's style.\")))},r.prototype.removeFeatureState=function(e,r){this._checkLoaded();var n=e.source,i=this.sourceCaches[n];if(void 0!==i){var a=i.getSource().type,o=\"vector\"===a?e.sourceLayer:void 0;\"vector\"!==a||o?r&&\"string\"!=typeof e.id&&\"number\"!=typeof e.id?this.fire(new t.ErrorEvent(new Error(\"A feature id is requred to remove its specific state property.\"))):i.removeFeatureState(o,e.id,r):this.fire(new t.ErrorEvent(new Error(\"The sourceLayer parameter must be provided for vector source types.\")))}else this.fire(new t.ErrorEvent(new Error(\"The source '\"+n+\"' does not exist in the map's style.\")))},r.prototype.getFeatureState=function(e){this._checkLoaded();var r=e.source,n=e.sourceLayer,i=this.sourceCaches[r];if(void 0!==i){if(\"vector\"!==i.getSource().type||n)return void 0===e.id&&this.fire(new t.ErrorEvent(new Error(\"The feature id parameter must be provided.\"))),i.getFeatureState(n,e.id);this.fire(new t.ErrorEvent(new Error(\"The sourceLayer parameter must be provided for vector source types.\")))}else this.fire(new t.ErrorEvent(new Error(\"The source '\"+r+\"' does not exist in the map's style.\")))},r.prototype.getTransition=function(){return t.extend({duration:300,delay:0},this.stylesheet&&this.stylesheet.transition)},r.prototype.serialize=function(){return t.filterObject({version:this.stylesheet.version,name:this.stylesheet.name,metadata:this.stylesheet.metadata,light:this.stylesheet.light,center:this.stylesheet.center,zoom:this.stylesheet.zoom,bearing:this.stylesheet.bearing,pitch:this.stylesheet.pitch,sprite:this.stylesheet.sprite,glyphs:this.stylesheet.glyphs,transition:this.stylesheet.transition,sources:t.mapObject(this.sourceCaches,(function(t){return t.serialize()})),layers:this._serializeLayers(this._order)},(function(t){return void 0!==t}))},r.prototype._updateLayer=function(t){this._updatedLayers[t.id]=!0,t.source&&!this._updatedSources[t.source]&&\"raster\"!==this.sourceCaches[t.source].getSource().type&&(this._updatedSources[t.source]=\"reload\",this.sourceCaches[t.source].pause()),this._changed=!0},r.prototype._flattenAndSortRenderedFeatures=function(t){for(var e=this,r=function(t){return\"fill-extrusion\"===e._layers[t].type},n={},i=[],a=this._order.length-1;a>=0;a--){var o=this._order[a];if(r(o)){n[o]=a;for(var s=0,l=t;s<l.length;s+=1){var c=l[s][o];if(c)for(var u=0,f=c;u<f.length;u+=1){var h=f[u];i.push(h)}}}}i.sort((function(t,e){return e.intersectionZ-t.intersectionZ}));for(var p=[],d=this._order.length-1;d>=0;d--){var m=this._order[d];if(r(m))for(var g=i.length-1;g>=0;g--){var v=i[g].feature;if(n[v.layer.id]<d)break;p.push(v),i.pop()}else for(var y=0,x=t;y<x.length;y+=1){var b=x[y][m];if(b)for(var _=0,w=b;_<w.length;_+=1){var T=w[_];p.push(T.feature)}}}return p},r.prototype.queryRenderedFeatures=function(e,r,n){r&&r.filter&&this._validate(t.validateStyle.filter,\"queryRenderedFeatures.filter\",r.filter,null,r);var i={};if(r&&r.layers){if(!Array.isArray(r.layers))return this.fire(new t.ErrorEvent(new Error(\"parameters.layers must be an Array.\"))),[];for(var a=0,o=r.layers;a<o.length;a+=1){var s=o[a],l=this._layers[s];if(!l)return this.fire(new t.ErrorEvent(new Error(\"The layer '\"+s+\"' does not exist in the map's style and cannot be queried for features.\"))),[];i[l.source]=!0}}var c=[];for(var u in r.availableImages=this._availableImages,this.sourceCaches)r.layers&&!i[u]||c.push(F(this.sourceCaches[u],this._layers,this._serializedLayers,e,r,n));return this.placement&&c.push(function(t,e,r,n,i,a,o){for(var s={},l=a.queryRenderedSymbols(n),c=[],u=0,f=Object.keys(l).map(Number);u<f.length;u+=1){var h=f[u];c.push(o[h])}c.sort(B);for(var p=function(){var r=m[d],n=r.featureIndex.lookupSymbolFeatures(l[r.bucketInstanceId],e,r.bucketIndex,r.sourceLayerIndex,i.filter,i.layers,i.availableImages,t);for(var a in n){var o=s[a]=s[a]||[],c=n[a];c.sort((function(t,e){var n=r.featureSortOrder;if(n){var i=n.indexOf(t.featureIndex);return n.indexOf(e.featureIndex)-i}return e.featureIndex-t.featureIndex}));for(var u=0,f=c;u<f.length;u+=1){var h=f[u];o.push(h)}}},d=0,m=c;d<m.length;d+=1)p();var g=function(e){s[e].forEach((function(n){var i=n.feature,a=t[e],o=r[a.source].getFeatureState(i.layer[\"source-layer\"],i.id);i.source=i.layer.source,i.layer[\"source-layer\"]&&(i.sourceLayer=i.layer[\"source-layer\"]),i.state=o}))};for(var v in s)g(v);return s}(this._layers,this._serializedLayers,this.sourceCaches,e,r,this.placement.collisionIndex,this.placement.retainedQueryData)),this._flattenAndSortRenderedFeatures(c)},r.prototype.querySourceFeatures=function(e,r){r&&r.filter&&this._validate(t.validateStyle.filter,\"querySourceFeatures.filter\",r.filter,null,r);var n=this.sourceCaches[e];return n?function(t,e){for(var r=t.getRenderableIds().map((function(e){return t.getTileByID(e)})),n=[],i={},a=0;a<r.length;a++){var o=r[a],s=o.tileID.canonical.key;i[s]||(i[s]=!0,o.querySourceFeatures(n,e))}return n}(n,r):[]},r.prototype.addSourceType=function(t,e,n){return r.getSourceType(t)?n(new Error('A source type called \"'+t+'\" already exists.')):(r.setSourceType(t,e),e.workerSourceURL?void this.dispatcher.broadcast(\"loadWorkerSource\",{name:t,url:e.workerSourceURL},n):n(null,null))},r.prototype.getLight=function(){return this.light.getLight()},r.prototype.setLight=function(e,r){void 0===r&&(r={}),this._checkLoaded();var n=this.light.getLight(),i=!1;for(var a in e)if(!t.deepEqual(e[a],n[a])){i=!0;break}if(i){var o={now:t.browser.now(),transition:t.extend({duration:300,delay:0},this.stylesheet.transition)};this.light.setLight(e,r),this.light.updateTransitions(o)}},r.prototype._validate=function(e,r,n,i,a){return void 0===a&&(a={}),(!a||!1!==a.validate)&&je(this,e.call(t.validateStyle,t.extend({key:r,style:this.serialize(),value:n,styleSpec:t.styleSpec},i)))},r.prototype._remove=function(){for(var e in this._request&&(this._request.cancel(),this._request=null),this._spriteRequest&&(this._spriteRequest.cancel(),this._spriteRequest=null),t.evented.off(\"pluginStateChange\",this._rtlTextPluginCallback),this._layers){this._layers[e].setEventedParent(null)}for(var r in this.sourceCaches)this.sourceCaches[r].clearTiles(),this.sourceCaches[r].setEventedParent(null);this.imageManager.setEventedParent(null),this.setEventedParent(null),this.dispatcher.remove()},r.prototype._clearSource=function(t){this.sourceCaches[t].clearTiles()},r.prototype._reloadSource=function(t){this.sourceCaches[t].resume(),this.sourceCaches[t].reload()},r.prototype._updateSources=function(t){for(var e in this.sourceCaches)this.sourceCaches[e].update(t)},r.prototype._generateCollisionBoxes=function(){for(var t in this.sourceCaches)this._reloadSource(t)},r.prototype._updatePlacement=function(e,r,n,i,a){void 0===a&&(a=!1);for(var o=!1,s=!1,l={},c=0,u=this._order;c<u.length;c+=1){var f=u[c],h=this._layers[f];if(\"symbol\"===h.type){if(!l[h.source]){var p=this.sourceCaches[h.source];l[h.source]=p.getRenderableIds(!0).map((function(t){return p.getTileByID(t)})).sort((function(t,e){return e.tileID.overscaledZ-t.tileID.overscaledZ||(t.tileID.isLessThan(e.tileID)?-1:1)}))}var d=this.crossTileSymbolIndex.addLayer(h,l[h.source],e.center.lng);o=o||d}}if(this.crossTileSymbolIndex.pruneUnusedLayers(this._order),((a=a||this._layerOrderChanged||0===n)||!this.pauseablePlacement||this.pauseablePlacement.isDone()&&!this.placement.stillRecent(t.browser.now(),e.zoom))&&(this.pauseablePlacement=new ze(e,this._order,a,r,n,i,this.placement),this._layerOrderChanged=!1),this.pauseablePlacement.isDone()?this.placement.setStale():(this.pauseablePlacement.continuePlacement(this._order,this._layers,l),this.pauseablePlacement.isDone()&&(this.placement=this.pauseablePlacement.commit(t.browser.now()),s=!0),o&&this.pauseablePlacement.placement.setStale()),s||o)for(var m=0,g=this._order;m<g.length;m+=1){var v=g[m],y=this._layers[v];\"symbol\"===y.type&&this.placement.updateLayerOpacities(y,l[y.source])}return!this.pauseablePlacement.isDone()||this.placement.hasTransitions(t.browser.now())},r.prototype._releaseSymbolFadeTiles=function(){for(var t in this.sourceCaches)this.sourceCaches[t].releaseSymbolFadeTiles()},r.prototype.getImages=function(t,e,r){this.imageManager.getImages(e.icons,r),this._updateTilesForChangedImages();var n=this.sourceCaches[e.source];n&&n.setDependencies(e.tileID.key,e.type,e.icons)},r.prototype.getGlyphs=function(t,e,r){this.glyphManager.getGlyphs(e.stacks,r)},r.prototype.getResource=function(e,r,n){return t.makeRequest(r,n)},r}(t.Evented);qe.getSourceType=function(t){return D[t]},qe.setSourceType=function(t,e){D[t]=e},qe.registerForPluginStateChange=t.registerForPluginStateChange;var Ge=t.createLayout([{name:\"a_pos\",type:\"Int16\",components:2}]),Ye=yr(\"#ifdef GL_ES\\nprecision mediump float;\\n#else\\n#if !defined(lowp)\\n#define lowp\\n#endif\\n#if !defined(mediump)\\n#define mediump\\n#endif\\n#if !defined(highp)\\n#define highp\\n#endif\\n#endif\",\"#ifdef GL_ES\\nprecision highp float;\\n#else\\n#if !defined(lowp)\\n#define lowp\\n#endif\\n#if !defined(mediump)\\n#define mediump\\n#endif\\n#if !defined(highp)\\n#define highp\\n#endif\\n#endif\\nvec2 unpack_float(const float packedValue) {int packedIntValue=int(packedValue);int v0=packedIntValue/256;return vec2(v0,packedIntValue-v0*256);}vec2 unpack_opacity(const float packedOpacity) {int intOpacity=int(packedOpacity)/2;return vec2(float(intOpacity)/127.0,mod(packedOpacity,2.0));}vec4 decode_color(const vec2 encodedColor) {return vec4(unpack_float(encodedColor[0])/255.0,unpack_float(encodedColor[1])/255.0\\n);}float unpack_mix_vec2(const vec2 packedValue,const float t) {return mix(packedValue[0],packedValue[1],t);}vec4 unpack_mix_color(const vec4 packedColors,const float t) {vec4 minColor=decode_color(vec2(packedColors[0],packedColors[1]));vec4 maxColor=decode_color(vec2(packedColors[2],packedColors[3]));return mix(minColor,maxColor,t);}vec2 get_pattern_pos(const vec2 pixel_coord_upper,const vec2 pixel_coord_lower,const vec2 pattern_size,const float tile_units_to_pixels,const vec2 pos) {vec2 offset=mod(mod(mod(pixel_coord_upper,pattern_size)*256.0,pattern_size)*256.0+pixel_coord_lower,pattern_size);return (tile_units_to_pixels*pos+offset)/pattern_size;}\"),We=yr(\"uniform vec4 u_color;uniform float u_opacity;void main() {gl_FragColor=u_color*u_opacity;\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"attribute vec2 a_pos;uniform mat4 u_matrix;void main() {gl_Position=u_matrix*vec4(a_pos,0,1);}\"),Xe=yr(\"uniform vec2 u_pattern_tl_a;uniform vec2 u_pattern_br_a;uniform vec2 u_pattern_tl_b;uniform vec2 u_pattern_br_b;uniform vec2 u_texsize;uniform float u_mix;uniform float u_opacity;uniform sampler2D u_image;varying vec2 v_pos_a;varying vec2 v_pos_b;void main() {vec2 imagecoord=mod(v_pos_a,1.0);vec2 pos=mix(u_pattern_tl_a/u_texsize,u_pattern_br_a/u_texsize,imagecoord);vec4 color1=texture2D(u_image,pos);vec2 imagecoord_b=mod(v_pos_b,1.0);vec2 pos2=mix(u_pattern_tl_b/u_texsize,u_pattern_br_b/u_texsize,imagecoord_b);vec4 color2=texture2D(u_image,pos2);gl_FragColor=mix(color1,color2,u_mix)*u_opacity;\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"uniform mat4 u_matrix;uniform vec2 u_pattern_size_a;uniform vec2 u_pattern_size_b;uniform vec2 u_pixel_coord_upper;uniform vec2 u_pixel_coord_lower;uniform float u_scale_a;uniform float u_scale_b;uniform float u_tile_units_to_pixels;attribute vec2 a_pos;varying vec2 v_pos_a;varying vec2 v_pos_b;void main() {gl_Position=u_matrix*vec4(a_pos,0,1);v_pos_a=get_pattern_pos(u_pixel_coord_upper,u_pixel_coord_lower,u_scale_a*u_pattern_size_a,u_tile_units_to_pixels,a_pos);v_pos_b=get_pattern_pos(u_pixel_coord_upper,u_pixel_coord_lower,u_scale_b*u_pattern_size_b,u_tile_units_to_pixels,a_pos);}\"),Ze=yr(\"varying vec3 v_data;\\n#pragma mapbox: define highp vec4 color\\n#pragma mapbox: define mediump float radius\\n#pragma mapbox: define lowp float blur\\n#pragma mapbox: define lowp float opacity\\n#pragma mapbox: define highp vec4 stroke_color\\n#pragma mapbox: define mediump float stroke_width\\n#pragma mapbox: define lowp float stroke_opacity\\nvoid main() {\\n#pragma mapbox: initialize highp vec4 color\\n#pragma mapbox: initialize mediump float radius\\n#pragma mapbox: initialize lowp float blur\\n#pragma mapbox: initialize lowp float opacity\\n#pragma mapbox: initialize highp vec4 stroke_color\\n#pragma mapbox: initialize mediump float stroke_width\\n#pragma mapbox: initialize lowp float stroke_opacity\\nvec2 extrude=v_data.xy;float extrude_length=length(extrude);lowp float antialiasblur=v_data.z;float antialiased_blur=-max(blur,antialiasblur);float opacity_t=smoothstep(0.0,antialiased_blur,extrude_length-1.0);float color_t=stroke_width < 0.01 ? 0.0 : smoothstep(antialiased_blur,0.0,extrude_length-radius/(radius+stroke_width));gl_FragColor=opacity_t*mix(color*opacity,stroke_color*stroke_opacity,color_t);\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"uniform mat4 u_matrix;uniform bool u_scale_with_map;uniform bool u_pitch_with_map;uniform vec2 u_extrude_scale;uniform lowp float u_device_pixel_ratio;uniform highp float u_camera_to_center_distance;attribute vec2 a_pos;varying vec3 v_data;\\n#pragma mapbox: define highp vec4 color\\n#pragma mapbox: define mediump float radius\\n#pragma mapbox: define lowp float blur\\n#pragma mapbox: define lowp float opacity\\n#pragma mapbox: define highp vec4 stroke_color\\n#pragma mapbox: define mediump float stroke_width\\n#pragma mapbox: define lowp float stroke_opacity\\nvoid main(void) {\\n#pragma mapbox: initialize highp vec4 color\\n#pragma mapbox: initialize mediump float radius\\n#pragma mapbox: initialize lowp float blur\\n#pragma mapbox: initialize lowp float opacity\\n#pragma mapbox: initialize highp vec4 stroke_color\\n#pragma mapbox: initialize mediump float stroke_width\\n#pragma mapbox: initialize lowp float stroke_opacity\\nvec2 extrude=vec2(mod(a_pos,2.0)*2.0-1.0);vec2 circle_center=floor(a_pos*0.5);if (u_pitch_with_map) {vec2 corner_position=circle_center;if (u_scale_with_map) {corner_position+=extrude*(radius+stroke_width)*u_extrude_scale;} else {vec4 projected_center=u_matrix*vec4(circle_center,0,1);corner_position+=extrude*(radius+stroke_width)*u_extrude_scale*(projected_center.w/u_camera_to_center_distance);}gl_Position=u_matrix*vec4(corner_position,0,1);} else {gl_Position=u_matrix*vec4(circle_center,0,1);if (u_scale_with_map) {gl_Position.xy+=extrude*(radius+stroke_width)*u_extrude_scale*u_camera_to_center_distance;} else {gl_Position.xy+=extrude*(radius+stroke_width)*u_extrude_scale*gl_Position.w;}}lowp float antialiasblur=1.0/u_device_pixel_ratio/(radius+stroke_width);v_data=vec3(extrude.x,extrude.y,antialiasblur);}\"),Je=yr(\"void main() {gl_FragColor=vec4(1.0);}\",\"attribute vec2 a_pos;uniform mat4 u_matrix;void main() {gl_Position=u_matrix*vec4(a_pos,0,1);}\"),Ke=yr(\"uniform highp float u_intensity;varying vec2 v_extrude;\\n#pragma mapbox: define highp float weight\\n#define GAUSS_COEF 0.3989422804014327\\nvoid main() {\\n#pragma mapbox: initialize highp float weight\\nfloat d=-0.5*3.0*3.0*dot(v_extrude,v_extrude);float val=weight*u_intensity*GAUSS_COEF*exp(d);gl_FragColor=vec4(val,1.0,1.0,1.0);\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"uniform mat4 u_matrix;uniform float u_extrude_scale;uniform float u_opacity;uniform float u_intensity;attribute vec2 a_pos;varying vec2 v_extrude;\\n#pragma mapbox: define highp float weight\\n#pragma mapbox: define mediump float radius\\nconst highp float ZERO=1.0/255.0/16.0;\\n#define GAUSS_COEF 0.3989422804014327\\nvoid main(void) {\\n#pragma mapbox: initialize highp float weight\\n#pragma mapbox: initialize mediump float radius\\nvec2 unscaled_extrude=vec2(mod(a_pos,2.0)*2.0-1.0);float S=sqrt(-2.0*log(ZERO/weight/u_intensity/GAUSS_COEF))/3.0;v_extrude=S*unscaled_extrude;vec2 extrude=v_extrude*radius*u_extrude_scale;vec4 pos=vec4(floor(a_pos*0.5)+extrude,0,1);gl_Position=u_matrix*pos;}\"),Qe=yr(\"uniform sampler2D u_image;uniform sampler2D u_color_ramp;uniform float u_opacity;varying vec2 v_pos;void main() {float t=texture2D(u_image,v_pos).r;vec4 color=texture2D(u_color_ramp,vec2(t,0.5));gl_FragColor=color*u_opacity;\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(0.0);\\n#endif\\n}\",\"uniform mat4 u_matrix;uniform vec2 u_world;attribute vec2 a_pos;varying vec2 v_pos;void main() {gl_Position=u_matrix*vec4(a_pos*u_world,0,1);v_pos.x=a_pos.x;v_pos.y=1.0-a_pos.y;}\"),$e=yr(\"varying float v_placed;varying float v_notUsed;void main() {float alpha=0.5;gl_FragColor=vec4(1.0,0.0,0.0,1.0)*alpha;if (v_placed > 0.5) {gl_FragColor=vec4(0.0,0.0,1.0,0.5)*alpha;}if (v_notUsed > 0.5) {gl_FragColor*=.1;}}\",\"attribute vec2 a_pos;attribute vec2 a_anchor_pos;attribute vec2 a_extrude;attribute vec2 a_placed;attribute vec2 a_shift;uniform mat4 u_matrix;uniform vec2 u_extrude_scale;uniform float u_camera_to_center_distance;varying float v_placed;varying float v_notUsed;void main() {vec4 projectedPoint=u_matrix*vec4(a_anchor_pos,0,1);highp float camera_to_anchor_distance=projectedPoint.w;highp float collision_perspective_ratio=clamp(0.5+0.5*(u_camera_to_center_distance/camera_to_anchor_distance),0.0,4.0);gl_Position=u_matrix*vec4(a_pos,0.0,1.0);gl_Position.xy+=(a_extrude+a_shift)*u_extrude_scale*gl_Position.w*collision_perspective_ratio;v_placed=a_placed.x;v_notUsed=a_placed.y;}\"),tr=yr(\"varying float v_radius;varying vec2 v_extrude;varying float v_perspective_ratio;varying float v_collision;void main() {float alpha=0.5*min(v_perspective_ratio,1.0);float stroke_radius=0.9*max(v_perspective_ratio,1.0);float distance_to_center=length(v_extrude);float distance_to_edge=abs(distance_to_center-v_radius);float opacity_t=smoothstep(-stroke_radius,0.0,-distance_to_edge);vec4 color=mix(vec4(0.0,0.0,1.0,0.5),vec4(1.0,0.0,0.0,1.0),v_collision);gl_FragColor=color*alpha*opacity_t;}\",\"attribute vec2 a_pos;attribute float a_radius;attribute vec2 a_flags;uniform mat4 u_matrix;uniform mat4 u_inv_matrix;uniform vec2 u_viewport_size;uniform float u_camera_to_center_distance;varying float v_radius;varying vec2 v_extrude;varying float v_perspective_ratio;varying float v_collision;vec3 toTilePosition(vec2 screenPos) {vec4 rayStart=u_inv_matrix*vec4(screenPos,-1.0,1.0);vec4 rayEnd =u_inv_matrix*vec4(screenPos, 1.0,1.0);rayStart.xyz/=rayStart.w;rayEnd.xyz /=rayEnd.w;highp float t=(0.0-rayStart.z)/(rayEnd.z-rayStart.z);return mix(rayStart.xyz,rayEnd.xyz,t);}void main() {vec2 quadCenterPos=a_pos;float radius=a_radius;float collision=a_flags.x;float vertexIdx=a_flags.y;vec2 quadVertexOffset=vec2(mix(-1.0,1.0,float(vertexIdx >=2.0)),mix(-1.0,1.0,float(vertexIdx >=1.0 && vertexIdx <=2.0)));vec2 quadVertexExtent=quadVertexOffset*radius;vec3 tilePos=toTilePosition(quadCenterPos);vec4 clipPos=u_matrix*vec4(tilePos,1.0);highp float camera_to_anchor_distance=clipPos.w;highp float collision_perspective_ratio=clamp(0.5+0.5*(u_camera_to_center_distance/camera_to_anchor_distance),0.0,4.0);float padding_factor=1.2;v_radius=radius;v_extrude=quadVertexExtent*padding_factor;v_perspective_ratio=collision_perspective_ratio;v_collision=collision;gl_Position=vec4(clipPos.xyz/clipPos.w,1.0)+vec4(quadVertexExtent*padding_factor/u_viewport_size*2.0,0.0,0.0);}\"),er=yr(\"uniform highp vec4 u_color;uniform sampler2D u_overlay;varying vec2 v_uv;void main() {vec4 overlay_color=texture2D(u_overlay,v_uv);gl_FragColor=mix(u_color,overlay_color,overlay_color.a);}\",\"attribute vec2 a_pos;varying vec2 v_uv;uniform mat4 u_matrix;uniform float u_overlay_scale;void main() {v_uv=a_pos/8192.0;gl_Position=u_matrix*vec4(a_pos*u_overlay_scale,0,1);}\"),rr=yr(\"#pragma mapbox: define highp vec4 color\\n#pragma mapbox: define lowp float opacity\\nvoid main() {\\n#pragma mapbox: initialize highp vec4 color\\n#pragma mapbox: initialize lowp float opacity\\ngl_FragColor=color*opacity;\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"attribute vec2 a_pos;uniform mat4 u_matrix;\\n#pragma mapbox: define highp vec4 color\\n#pragma mapbox: define lowp float opacity\\nvoid main() {\\n#pragma mapbox: initialize highp vec4 color\\n#pragma mapbox: initialize lowp float opacity\\ngl_Position=u_matrix*vec4(a_pos,0,1);}\"),nr=yr(\"varying vec2 v_pos;\\n#pragma mapbox: define highp vec4 outline_color\\n#pragma mapbox: define lowp float opacity\\nvoid main() {\\n#pragma mapbox: initialize highp vec4 outline_color\\n#pragma mapbox: initialize lowp float opacity\\nfloat dist=length(v_pos-gl_FragCoord.xy);float alpha=1.0-smoothstep(0.0,1.0,dist);gl_FragColor=outline_color*(alpha*opacity);\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"attribute vec2 a_pos;uniform mat4 u_matrix;uniform vec2 u_world;varying vec2 v_pos;\\n#pragma mapbox: define highp vec4 outline_color\\n#pragma mapbox: define lowp float opacity\\nvoid main() {\\n#pragma mapbox: initialize highp vec4 outline_color\\n#pragma mapbox: initialize lowp float opacity\\ngl_Position=u_matrix*vec4(a_pos,0,1);v_pos=(gl_Position.xy/gl_Position.w+1.0)/2.0*u_world;}\"),ir=yr(\"uniform vec2 u_texsize;uniform sampler2D u_image;uniform float u_fade;varying vec2 v_pos_a;varying vec2 v_pos_b;varying vec2 v_pos;\\n#pragma mapbox: define lowp float opacity\\n#pragma mapbox: define lowp vec4 pattern_from\\n#pragma mapbox: define lowp vec4 pattern_to\\nvoid main() {\\n#pragma mapbox: initialize lowp float opacity\\n#pragma mapbox: initialize mediump vec4 pattern_from\\n#pragma mapbox: initialize mediump vec4 pattern_to\\nvec2 pattern_tl_a=pattern_from.xy;vec2 pattern_br_a=pattern_from.zw;vec2 pattern_tl_b=pattern_to.xy;vec2 pattern_br_b=pattern_to.zw;vec2 imagecoord=mod(v_pos_a,1.0);vec2 pos=mix(pattern_tl_a/u_texsize,pattern_br_a/u_texsize,imagecoord);vec4 color1=texture2D(u_image,pos);vec2 imagecoord_b=mod(v_pos_b,1.0);vec2 pos2=mix(pattern_tl_b/u_texsize,pattern_br_b/u_texsize,imagecoord_b);vec4 color2=texture2D(u_image,pos2);float dist=length(v_pos-gl_FragCoord.xy);float alpha=1.0-smoothstep(0.0,1.0,dist);gl_FragColor=mix(color1,color2,u_fade)*alpha*opacity;\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"uniform mat4 u_matrix;uniform vec2 u_world;uniform vec2 u_pixel_coord_upper;uniform vec2 u_pixel_coord_lower;uniform vec3 u_scale;attribute vec2 a_pos;varying vec2 v_pos_a;varying vec2 v_pos_b;varying vec2 v_pos;\\n#pragma mapbox: define lowp float opacity\\n#pragma mapbox: define lowp vec4 pattern_from\\n#pragma mapbox: define lowp vec4 pattern_to\\n#pragma mapbox: define lowp float pixel_ratio_from\\n#pragma mapbox: define lowp float pixel_ratio_to\\nvoid main() {\\n#pragma mapbox: initialize lowp float opacity\\n#pragma mapbox: initialize mediump vec4 pattern_from\\n#pragma mapbox: initialize mediump vec4 pattern_to\\n#pragma mapbox: initialize lowp float pixel_ratio_from\\n#pragma mapbox: initialize lowp float pixel_ratio_to\\nvec2 pattern_tl_a=pattern_from.xy;vec2 pattern_br_a=pattern_from.zw;vec2 pattern_tl_b=pattern_to.xy;vec2 pattern_br_b=pattern_to.zw;float tileRatio=u_scale.x;float fromScale=u_scale.y;float toScale=u_scale.z;gl_Position=u_matrix*vec4(a_pos,0,1);vec2 display_size_a=(pattern_br_a-pattern_tl_a)/pixel_ratio_from;vec2 display_size_b=(pattern_br_b-pattern_tl_b)/pixel_ratio_to;v_pos_a=get_pattern_pos(u_pixel_coord_upper,u_pixel_coord_lower,fromScale*display_size_a,tileRatio,a_pos);v_pos_b=get_pattern_pos(u_pixel_coord_upper,u_pixel_coord_lower,toScale*display_size_b,tileRatio,a_pos);v_pos=(gl_Position.xy/gl_Position.w+1.0)/2.0*u_world;}\"),ar=yr(\"uniform vec2 u_texsize;uniform float u_fade;uniform sampler2D u_image;varying vec2 v_pos_a;varying vec2 v_pos_b;\\n#pragma mapbox: define lowp float opacity\\n#pragma mapbox: define lowp vec4 pattern_from\\n#pragma mapbox: define lowp vec4 pattern_to\\nvoid main() {\\n#pragma mapbox: initialize lowp float opacity\\n#pragma mapbox: initialize mediump vec4 pattern_from\\n#pragma mapbox: initialize mediump vec4 pattern_to\\nvec2 pattern_tl_a=pattern_from.xy;vec2 pattern_br_a=pattern_from.zw;vec2 pattern_tl_b=pattern_to.xy;vec2 pattern_br_b=pattern_to.zw;vec2 imagecoord=mod(v_pos_a,1.0);vec2 pos=mix(pattern_tl_a/u_texsize,pattern_br_a/u_texsize,imagecoord);vec4 color1=texture2D(u_image,pos);vec2 imagecoord_b=mod(v_pos_b,1.0);vec2 pos2=mix(pattern_tl_b/u_texsize,pattern_br_b/u_texsize,imagecoord_b);vec4 color2=texture2D(u_image,pos2);gl_FragColor=mix(color1,color2,u_fade)*opacity;\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"uniform mat4 u_matrix;uniform vec2 u_pixel_coord_upper;uniform vec2 u_pixel_coord_lower;uniform vec3 u_scale;attribute vec2 a_pos;varying vec2 v_pos_a;varying vec2 v_pos_b;\\n#pragma mapbox: define lowp float opacity\\n#pragma mapbox: define lowp vec4 pattern_from\\n#pragma mapbox: define lowp vec4 pattern_to\\n#pragma mapbox: define lowp float pixel_ratio_from\\n#pragma mapbox: define lowp float pixel_ratio_to\\nvoid main() {\\n#pragma mapbox: initialize lowp float opacity\\n#pragma mapbox: initialize mediump vec4 pattern_from\\n#pragma mapbox: initialize mediump vec4 pattern_to\\n#pragma mapbox: initialize lowp float pixel_ratio_from\\n#pragma mapbox: initialize lowp float pixel_ratio_to\\nvec2 pattern_tl_a=pattern_from.xy;vec2 pattern_br_a=pattern_from.zw;vec2 pattern_tl_b=pattern_to.xy;vec2 pattern_br_b=pattern_to.zw;float tileZoomRatio=u_scale.x;float fromScale=u_scale.y;float toScale=u_scale.z;vec2 display_size_a=(pattern_br_a-pattern_tl_a)/pixel_ratio_from;vec2 display_size_b=(pattern_br_b-pattern_tl_b)/pixel_ratio_to;gl_Position=u_matrix*vec4(a_pos,0,1);v_pos_a=get_pattern_pos(u_pixel_coord_upper,u_pixel_coord_lower,fromScale*display_size_a,tileZoomRatio,a_pos);v_pos_b=get_pattern_pos(u_pixel_coord_upper,u_pixel_coord_lower,toScale*display_size_b,tileZoomRatio,a_pos);}\"),or=yr(\"varying vec4 v_color;void main() {gl_FragColor=v_color;\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"uniform mat4 u_matrix;uniform vec3 u_lightcolor;uniform lowp vec3 u_lightpos;uniform lowp float u_lightintensity;uniform float u_vertical_gradient;uniform lowp float u_opacity;attribute vec2 a_pos;attribute vec4 a_normal_ed;varying vec4 v_color;\\n#pragma mapbox: define highp float base\\n#pragma mapbox: define highp float height\\n#pragma mapbox: define highp vec4 color\\nvoid main() {\\n#pragma mapbox: initialize highp float base\\n#pragma mapbox: initialize highp float height\\n#pragma mapbox: initialize highp vec4 color\\nvec3 normal=a_normal_ed.xyz;base=max(0.0,base);height=max(0.0,height);float t=mod(normal.x,2.0);gl_Position=u_matrix*vec4(a_pos,t > 0.0 ? height : base,1);float colorvalue=color.r*0.2126+color.g*0.7152+color.b*0.0722;v_color=vec4(0.0,0.0,0.0,1.0);vec4 ambientlight=vec4(0.03,0.03,0.03,1.0);color+=ambientlight;float directional=clamp(dot(normal/16384.0,u_lightpos),0.0,1.0);directional=mix((1.0-u_lightintensity),max((1.0-colorvalue+u_lightintensity),1.0),directional);if (normal.y !=0.0) {directional*=((1.0-u_vertical_gradient)+(u_vertical_gradient*clamp((t+base)*pow(height/150.0,0.5),mix(0.7,0.98,1.0-u_lightintensity),1.0)));}v_color.r+=clamp(color.r*directional*u_lightcolor.r,mix(0.0,0.3,1.0-u_lightcolor.r),1.0);v_color.g+=clamp(color.g*directional*u_lightcolor.g,mix(0.0,0.3,1.0-u_lightcolor.g),1.0);v_color.b+=clamp(color.b*directional*u_lightcolor.b,mix(0.0,0.3,1.0-u_lightcolor.b),1.0);v_color*=u_opacity;}\"),sr=yr(\"uniform vec2 u_texsize;uniform float u_fade;uniform sampler2D u_image;varying vec2 v_pos_a;varying vec2 v_pos_b;varying vec4 v_lighting;\\n#pragma mapbox: define lowp float base\\n#pragma mapbox: define lowp float height\\n#pragma mapbox: define lowp vec4 pattern_from\\n#pragma mapbox: define lowp vec4 pattern_to\\n#pragma mapbox: define lowp float pixel_ratio_from\\n#pragma mapbox: define lowp float pixel_ratio_to\\nvoid main() {\\n#pragma mapbox: initialize lowp float base\\n#pragma mapbox: initialize lowp float height\\n#pragma mapbox: initialize mediump vec4 pattern_from\\n#pragma mapbox: initialize mediump vec4 pattern_to\\n#pragma mapbox: initialize lowp float pixel_ratio_from\\n#pragma mapbox: initialize lowp float pixel_ratio_to\\nvec2 pattern_tl_a=pattern_from.xy;vec2 pattern_br_a=pattern_from.zw;vec2 pattern_tl_b=pattern_to.xy;vec2 pattern_br_b=pattern_to.zw;vec2 imagecoord=mod(v_pos_a,1.0);vec2 pos=mix(pattern_tl_a/u_texsize,pattern_br_a/u_texsize,imagecoord);vec4 color1=texture2D(u_image,pos);vec2 imagecoord_b=mod(v_pos_b,1.0);vec2 pos2=mix(pattern_tl_b/u_texsize,pattern_br_b/u_texsize,imagecoord_b);vec4 color2=texture2D(u_image,pos2);vec4 mixedColor=mix(color1,color2,u_fade);gl_FragColor=mixedColor*v_lighting;\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"uniform mat4 u_matrix;uniform vec2 u_pixel_coord_upper;uniform vec2 u_pixel_coord_lower;uniform float u_height_factor;uniform vec3 u_scale;uniform float u_vertical_gradient;uniform lowp float u_opacity;uniform vec3 u_lightcolor;uniform lowp vec3 u_lightpos;uniform lowp float u_lightintensity;attribute vec2 a_pos;attribute vec4 a_normal_ed;varying vec2 v_pos_a;varying vec2 v_pos_b;varying vec4 v_lighting;\\n#pragma mapbox: define lowp float base\\n#pragma mapbox: define lowp float height\\n#pragma mapbox: define lowp vec4 pattern_from\\n#pragma mapbox: define lowp vec4 pattern_to\\n#pragma mapbox: define lowp float pixel_ratio_from\\n#pragma mapbox: define lowp float pixel_ratio_to\\nvoid main() {\\n#pragma mapbox: initialize lowp float base\\n#pragma mapbox: initialize lowp float height\\n#pragma mapbox: initialize mediump vec4 pattern_from\\n#pragma mapbox: initialize mediump vec4 pattern_to\\n#pragma mapbox: initialize lowp float pixel_ratio_from\\n#pragma mapbox: initialize lowp float pixel_ratio_to\\nvec2 pattern_tl_a=pattern_from.xy;vec2 pattern_br_a=pattern_from.zw;vec2 pattern_tl_b=pattern_to.xy;vec2 pattern_br_b=pattern_to.zw;float tileRatio=u_scale.x;float fromScale=u_scale.y;float toScale=u_scale.z;vec3 normal=a_normal_ed.xyz;float edgedistance=a_normal_ed.w;vec2 display_size_a=(pattern_br_a-pattern_tl_a)/pixel_ratio_from;vec2 display_size_b=(pattern_br_b-pattern_tl_b)/pixel_ratio_to;base=max(0.0,base);height=max(0.0,height);float t=mod(normal.x,2.0);float z=t > 0.0 ? height : base;gl_Position=u_matrix*vec4(a_pos,z,1);vec2 pos=normal.x==1.0 && normal.y==0.0 && normal.z==16384.0\\n? a_pos\\n: vec2(edgedistance,z*u_height_factor);v_pos_a=get_pattern_pos(u_pixel_coord_upper,u_pixel_coord_lower,fromScale*display_size_a,tileRatio,pos);v_pos_b=get_pattern_pos(u_pixel_coord_upper,u_pixel_coord_lower,toScale*display_size_b,tileRatio,pos);v_lighting=vec4(0.0,0.0,0.0,1.0);float directional=clamp(dot(normal/16383.0,u_lightpos),0.0,1.0);directional=mix((1.0-u_lightintensity),max((0.5+u_lightintensity),1.0),directional);if (normal.y !=0.0) {directional*=((1.0-u_vertical_gradient)+(u_vertical_gradient*clamp((t+base)*pow(height/150.0,0.5),mix(0.7,0.98,1.0-u_lightintensity),1.0)));}v_lighting.rgb+=clamp(directional*u_lightcolor,mix(vec3(0.0),vec3(0.3),1.0-u_lightcolor),vec3(1.0));v_lighting*=u_opacity;}\"),lr=yr(\"#ifdef GL_ES\\nprecision highp float;\\n#endif\\nuniform sampler2D u_image;varying vec2 v_pos;uniform vec2 u_dimension;uniform float u_zoom;uniform float u_maxzoom;uniform vec4 u_unpack;float getElevation(vec2 coord,float bias) {vec4 data=texture2D(u_image,coord)*255.0;data.a=-1.0;return dot(data,u_unpack)/4.0;}void main() {vec2 epsilon=1.0/u_dimension;float a=getElevation(v_pos+vec2(-epsilon.x,-epsilon.y),0.0);float b=getElevation(v_pos+vec2(0,-epsilon.y),0.0);float c=getElevation(v_pos+vec2(epsilon.x,-epsilon.y),0.0);float d=getElevation(v_pos+vec2(-epsilon.x,0),0.0);float e=getElevation(v_pos,0.0);float f=getElevation(v_pos+vec2(epsilon.x,0),0.0);float g=getElevation(v_pos+vec2(-epsilon.x,epsilon.y),0.0);float h=getElevation(v_pos+vec2(0,epsilon.y),0.0);float i=getElevation(v_pos+vec2(epsilon.x,epsilon.y),0.0);float exaggeration=u_zoom < 2.0 ? 0.4 : u_zoom < 4.5 ? 0.35 : 0.3;vec2 deriv=vec2((c+f+f+i)-(a+d+d+g),(g+h+h+i)-(a+b+b+c))/ pow(2.0,(u_zoom-u_maxzoom)*exaggeration+19.2562-u_zoom);gl_FragColor=clamp(vec4(deriv.x/2.0+0.5,deriv.y/2.0+0.5,1.0,1.0),0.0,1.0);\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"uniform mat4 u_matrix;uniform vec2 u_dimension;attribute vec2 a_pos;attribute vec2 a_texture_pos;varying vec2 v_pos;void main() {gl_Position=u_matrix*vec4(a_pos,0,1);highp vec2 epsilon=1.0/u_dimension;float scale=(u_dimension.x-2.0)/u_dimension.x;v_pos=(a_texture_pos/8192.0)*scale+epsilon;}\"),cr=yr(\"uniform sampler2D u_image;varying vec2 v_pos;uniform vec2 u_latrange;uniform vec2 u_light;uniform vec4 u_shadow;uniform vec4 u_highlight;uniform vec4 u_accent;\\n#define PI 3.141592653589793\\nvoid main() {vec4 pixel=texture2D(u_image,v_pos);vec2 deriv=((pixel.rg*2.0)-1.0);float scaleFactor=cos(radians((u_latrange[0]-u_latrange[1])*(1.0-v_pos.y)+u_latrange[1]));float slope=atan(1.25*length(deriv)/scaleFactor);float aspect=deriv.x !=0.0 ? atan(deriv.y,-deriv.x) : PI/2.0*(deriv.y > 0.0 ? 1.0 :-1.0);float intensity=u_light.x;float azimuth=u_light.y+PI;float base=1.875-intensity*1.75;float maxValue=0.5*PI;float scaledSlope=intensity !=0.5 ? ((pow(base,slope)-1.0)/(pow(base,maxValue)-1.0))*maxValue : slope;float accent=cos(scaledSlope);vec4 accent_color=(1.0-accent)*u_accent*clamp(intensity*2.0,0.0,1.0);float shade=abs(mod((aspect+azimuth)/PI+0.5,2.0)-1.0);vec4 shade_color=mix(u_shadow,u_highlight,shade)*sin(scaledSlope)*clamp(intensity*2.0,0.0,1.0);gl_FragColor=accent_color*(1.0-shade_color.a)+shade_color;\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"uniform mat4 u_matrix;attribute vec2 a_pos;attribute vec2 a_texture_pos;varying vec2 v_pos;void main() {gl_Position=u_matrix*vec4(a_pos,0,1);v_pos=a_texture_pos/8192.0;}\"),ur=yr(\"uniform lowp float u_device_pixel_ratio;varying vec2 v_width2;varying vec2 v_normal;varying float v_gamma_scale;\\n#pragma mapbox: define highp vec4 color\\n#pragma mapbox: define lowp float blur\\n#pragma mapbox: define lowp float opacity\\nvoid main() {\\n#pragma mapbox: initialize highp vec4 color\\n#pragma mapbox: initialize lowp float blur\\n#pragma mapbox: initialize lowp float opacity\\nfloat dist=length(v_normal)*v_width2.s;float blur2=(blur+1.0/u_device_pixel_ratio)*v_gamma_scale;float alpha=clamp(min(dist-(v_width2.t-blur2),v_width2.s-dist)/blur2,0.0,1.0);gl_FragColor=color*(alpha*opacity);\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"\\n#define scale 0.015873016\\nattribute vec2 a_pos_normal;attribute vec4 a_data;uniform mat4 u_matrix;uniform mediump float u_ratio;uniform vec2 u_units_to_pixels;uniform lowp float u_device_pixel_ratio;varying vec2 v_normal;varying vec2 v_width2;varying float v_gamma_scale;varying highp float v_linesofar;\\n#pragma mapbox: define highp vec4 color\\n#pragma mapbox: define lowp float blur\\n#pragma mapbox: define lowp float opacity\\n#pragma mapbox: define mediump float gapwidth\\n#pragma mapbox: define lowp float offset\\n#pragma mapbox: define mediump float width\\nvoid main() {\\n#pragma mapbox: initialize highp vec4 color\\n#pragma mapbox: initialize lowp float blur\\n#pragma mapbox: initialize lowp float opacity\\n#pragma mapbox: initialize mediump float gapwidth\\n#pragma mapbox: initialize lowp float offset\\n#pragma mapbox: initialize mediump float width\\nfloat ANTIALIASING=1.0/u_device_pixel_ratio/2.0;vec2 a_extrude=a_data.xy-128.0;float a_direction=mod(a_data.z,4.0)-1.0;v_linesofar=(floor(a_data.z/4.0)+a_data.w*64.0)*2.0;vec2 pos=floor(a_pos_normal*0.5);mediump vec2 normal=a_pos_normal-2.0*pos;normal.y=normal.y*2.0-1.0;v_normal=normal;gapwidth=gapwidth/2.0;float halfwidth=width/2.0;offset=-1.0*offset;float inset=gapwidth+(gapwidth > 0.0 ? ANTIALIASING : 0.0);float outset=gapwidth+halfwidth*(gapwidth > 0.0 ? 2.0 : 1.0)+(halfwidth==0.0 ? 0.0 : ANTIALIASING);mediump vec2 dist=outset*a_extrude*scale;mediump float u=0.5*a_direction;mediump float t=1.0-abs(u);mediump vec2 offset2=offset*a_extrude*scale*normal.y*mat2(t,-u,u,t);vec4 projected_extrude=u_matrix*vec4(dist/u_ratio,0.0,0.0);gl_Position=u_matrix*vec4(pos+offset2/u_ratio,0.0,1.0)+projected_extrude;float extrude_length_without_perspective=length(dist);float extrude_length_with_perspective=length(projected_extrude.xy/gl_Position.w*u_units_to_pixels);v_gamma_scale=extrude_length_without_perspective/extrude_length_with_perspective;v_width2=vec2(outset,inset);}\"),fr=yr(\"uniform lowp float u_device_pixel_ratio;uniform sampler2D u_image;varying vec2 v_width2;varying vec2 v_normal;varying float v_gamma_scale;varying highp float v_lineprogress;\\n#pragma mapbox: define lowp float blur\\n#pragma mapbox: define lowp float opacity\\nvoid main() {\\n#pragma mapbox: initialize lowp float blur\\n#pragma mapbox: initialize lowp float opacity\\nfloat dist=length(v_normal)*v_width2.s;float blur2=(blur+1.0/u_device_pixel_ratio)*v_gamma_scale;float alpha=clamp(min(dist-(v_width2.t-blur2),v_width2.s-dist)/blur2,0.0,1.0);vec4 color=texture2D(u_image,vec2(v_lineprogress,0.5));gl_FragColor=color*(alpha*opacity);\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"\\n#define MAX_LINE_DISTANCE 32767.0\\n#define scale 0.015873016\\nattribute vec2 a_pos_normal;attribute vec4 a_data;uniform mat4 u_matrix;uniform mediump float u_ratio;uniform lowp float u_device_pixel_ratio;uniform vec2 u_units_to_pixels;varying vec2 v_normal;varying vec2 v_width2;varying float v_gamma_scale;varying highp float v_lineprogress;\\n#pragma mapbox: define lowp float blur\\n#pragma mapbox: define lowp float opacity\\n#pragma mapbox: define mediump float gapwidth\\n#pragma mapbox: define lowp float offset\\n#pragma mapbox: define mediump float width\\nvoid main() {\\n#pragma mapbox: initialize lowp float blur\\n#pragma mapbox: initialize lowp float opacity\\n#pragma mapbox: initialize mediump float gapwidth\\n#pragma mapbox: initialize lowp float offset\\n#pragma mapbox: initialize mediump float width\\nfloat ANTIALIASING=1.0/u_device_pixel_ratio/2.0;vec2 a_extrude=a_data.xy-128.0;float a_direction=mod(a_data.z,4.0)-1.0;v_lineprogress=(floor(a_data.z/4.0)+a_data.w*64.0)*2.0/MAX_LINE_DISTANCE;vec2 pos=floor(a_pos_normal*0.5);mediump vec2 normal=a_pos_normal-2.0*pos;normal.y=normal.y*2.0-1.0;v_normal=normal;gapwidth=gapwidth/2.0;float halfwidth=width/2.0;offset=-1.0*offset;float inset=gapwidth+(gapwidth > 0.0 ? ANTIALIASING : 0.0);float outset=gapwidth+halfwidth*(gapwidth > 0.0 ? 2.0 : 1.0)+(halfwidth==0.0 ? 0.0 : ANTIALIASING);mediump vec2 dist=outset*a_extrude*scale;mediump float u=0.5*a_direction;mediump float t=1.0-abs(u);mediump vec2 offset2=offset*a_extrude*scale*normal.y*mat2(t,-u,u,t);vec4 projected_extrude=u_matrix*vec4(dist/u_ratio,0.0,0.0);gl_Position=u_matrix*vec4(pos+offset2/u_ratio,0.0,1.0)+projected_extrude;float extrude_length_without_perspective=length(dist);float extrude_length_with_perspective=length(projected_extrude.xy/gl_Position.w*u_units_to_pixels);v_gamma_scale=extrude_length_without_perspective/extrude_length_with_perspective;v_width2=vec2(outset,inset);}\"),hr=yr(\"uniform lowp float u_device_pixel_ratio;uniform vec2 u_texsize;uniform float u_fade;uniform mediump vec3 u_scale;uniform sampler2D u_image;varying vec2 v_normal;varying vec2 v_width2;varying float v_linesofar;varying float v_gamma_scale;varying float v_width;\\n#pragma mapbox: define lowp vec4 pattern_from\\n#pragma mapbox: define lowp vec4 pattern_to\\n#pragma mapbox: define lowp float pixel_ratio_from\\n#pragma mapbox: define lowp float pixel_ratio_to\\n#pragma mapbox: define lowp float blur\\n#pragma mapbox: define lowp float opacity\\nvoid main() {\\n#pragma mapbox: initialize mediump vec4 pattern_from\\n#pragma mapbox: initialize mediump vec4 pattern_to\\n#pragma mapbox: initialize lowp float pixel_ratio_from\\n#pragma mapbox: initialize lowp float pixel_ratio_to\\n#pragma mapbox: initialize lowp float blur\\n#pragma mapbox: initialize lowp float opacity\\nvec2 pattern_tl_a=pattern_from.xy;vec2 pattern_br_a=pattern_from.zw;vec2 pattern_tl_b=pattern_to.xy;vec2 pattern_br_b=pattern_to.zw;float tileZoomRatio=u_scale.x;float fromScale=u_scale.y;float toScale=u_scale.z;vec2 display_size_a=(pattern_br_a-pattern_tl_a)/pixel_ratio_from;vec2 display_size_b=(pattern_br_b-pattern_tl_b)/pixel_ratio_to;vec2 pattern_size_a=vec2(display_size_a.x*fromScale/tileZoomRatio,display_size_a.y);vec2 pattern_size_b=vec2(display_size_b.x*toScale/tileZoomRatio,display_size_b.y);float aspect_a=display_size_a.y/v_width;float aspect_b=display_size_b.y/v_width;float dist=length(v_normal)*v_width2.s;float blur2=(blur+1.0/u_device_pixel_ratio)*v_gamma_scale;float alpha=clamp(min(dist-(v_width2.t-blur2),v_width2.s-dist)/blur2,0.0,1.0);float x_a=mod(v_linesofar/pattern_size_a.x*aspect_a,1.0);float x_b=mod(v_linesofar/pattern_size_b.x*aspect_b,1.0);float y=0.5*v_normal.y+0.5;vec2 texel_size=1.0/u_texsize;vec2 pos_a=mix(pattern_tl_a*texel_size-texel_size,pattern_br_a*texel_size+texel_size,vec2(x_a,y));vec2 pos_b=mix(pattern_tl_b*texel_size-texel_size,pattern_br_b*texel_size+texel_size,vec2(x_b,y));vec4 color=mix(texture2D(u_image,pos_a),texture2D(u_image,pos_b),u_fade);gl_FragColor=color*alpha*opacity;\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"\\n#define scale 0.015873016\\n#define LINE_DISTANCE_SCALE 2.0\\nattribute vec2 a_pos_normal;attribute vec4 a_data;uniform mat4 u_matrix;uniform vec2 u_units_to_pixels;uniform mediump float u_ratio;uniform lowp float u_device_pixel_ratio;varying vec2 v_normal;varying vec2 v_width2;varying float v_linesofar;varying float v_gamma_scale;varying float v_width;\\n#pragma mapbox: define lowp float blur\\n#pragma mapbox: define lowp float opacity\\n#pragma mapbox: define lowp float offset\\n#pragma mapbox: define mediump float gapwidth\\n#pragma mapbox: define mediump float width\\n#pragma mapbox: define lowp float floorwidth\\n#pragma mapbox: define lowp vec4 pattern_from\\n#pragma mapbox: define lowp vec4 pattern_to\\n#pragma mapbox: define lowp float pixel_ratio_from\\n#pragma mapbox: define lowp float pixel_ratio_to\\nvoid main() {\\n#pragma mapbox: initialize lowp float blur\\n#pragma mapbox: initialize lowp float opacity\\n#pragma mapbox: initialize lowp float offset\\n#pragma mapbox: initialize mediump float gapwidth\\n#pragma mapbox: initialize mediump float width\\n#pragma mapbox: initialize lowp float floorwidth\\n#pragma mapbox: initialize mediump vec4 pattern_from\\n#pragma mapbox: initialize mediump vec4 pattern_to\\n#pragma mapbox: initialize lowp float pixel_ratio_from\\n#pragma mapbox: initialize lowp float pixel_ratio_to\\nfloat ANTIALIASING=1.0/u_device_pixel_ratio/2.0;vec2 a_extrude=a_data.xy-128.0;float a_direction=mod(a_data.z,4.0)-1.0;float a_linesofar=(floor(a_data.z/4.0)+a_data.w*64.0)*LINE_DISTANCE_SCALE;vec2 pos=floor(a_pos_normal*0.5);mediump vec2 normal=a_pos_normal-2.0*pos;normal.y=normal.y*2.0-1.0;v_normal=normal;gapwidth=gapwidth/2.0;float halfwidth=width/2.0;offset=-1.0*offset;float inset=gapwidth+(gapwidth > 0.0 ? ANTIALIASING : 0.0);float outset=gapwidth+halfwidth*(gapwidth > 0.0 ? 2.0 : 1.0)+(halfwidth==0.0 ? 0.0 : ANTIALIASING);mediump vec2 dist=outset*a_extrude*scale;mediump float u=0.5*a_direction;mediump float t=1.0-abs(u);mediump vec2 offset2=offset*a_extrude*scale*normal.y*mat2(t,-u,u,t);vec4 projected_extrude=u_matrix*vec4(dist/u_ratio,0.0,0.0);gl_Position=u_matrix*vec4(pos+offset2/u_ratio,0.0,1.0)+projected_extrude;float extrude_length_without_perspective=length(dist);float extrude_length_with_perspective=length(projected_extrude.xy/gl_Position.w*u_units_to_pixels);v_gamma_scale=extrude_length_without_perspective/extrude_length_with_perspective;v_linesofar=a_linesofar;v_width2=vec2(outset,inset);v_width=floorwidth;}\"),pr=yr(\"uniform lowp float u_device_pixel_ratio;uniform sampler2D u_image;uniform float u_sdfgamma;uniform float u_mix;varying vec2 v_normal;varying vec2 v_width2;varying vec2 v_tex_a;varying vec2 v_tex_b;varying float v_gamma_scale;\\n#pragma mapbox: define highp vec4 color\\n#pragma mapbox: define lowp float blur\\n#pragma mapbox: define lowp float opacity\\n#pragma mapbox: define mediump float width\\n#pragma mapbox: define lowp float floorwidth\\nvoid main() {\\n#pragma mapbox: initialize highp vec4 color\\n#pragma mapbox: initialize lowp float blur\\n#pragma mapbox: initialize lowp float opacity\\n#pragma mapbox: initialize mediump float width\\n#pragma mapbox: initialize lowp float floorwidth\\nfloat dist=length(v_normal)*v_width2.s;float blur2=(blur+1.0/u_device_pixel_ratio)*v_gamma_scale;float alpha=clamp(min(dist-(v_width2.t-blur2),v_width2.s-dist)/blur2,0.0,1.0);float sdfdist_a=texture2D(u_image,v_tex_a).a;float sdfdist_b=texture2D(u_image,v_tex_b).a;float sdfdist=mix(sdfdist_a,sdfdist_b,u_mix);alpha*=smoothstep(0.5-u_sdfgamma/floorwidth,0.5+u_sdfgamma/floorwidth,sdfdist);gl_FragColor=color*(alpha*opacity);\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"\\n#define scale 0.015873016\\n#define LINE_DISTANCE_SCALE 2.0\\nattribute vec2 a_pos_normal;attribute vec4 a_data;uniform mat4 u_matrix;uniform mediump float u_ratio;uniform lowp float u_device_pixel_ratio;uniform vec2 u_patternscale_a;uniform float u_tex_y_a;uniform vec2 u_patternscale_b;uniform float u_tex_y_b;uniform vec2 u_units_to_pixels;varying vec2 v_normal;varying vec2 v_width2;varying vec2 v_tex_a;varying vec2 v_tex_b;varying float v_gamma_scale;\\n#pragma mapbox: define highp vec4 color\\n#pragma mapbox: define lowp float blur\\n#pragma mapbox: define lowp float opacity\\n#pragma mapbox: define mediump float gapwidth\\n#pragma mapbox: define lowp float offset\\n#pragma mapbox: define mediump float width\\n#pragma mapbox: define lowp float floorwidth\\nvoid main() {\\n#pragma mapbox: initialize highp vec4 color\\n#pragma mapbox: initialize lowp float blur\\n#pragma mapbox: initialize lowp float opacity\\n#pragma mapbox: initialize mediump float gapwidth\\n#pragma mapbox: initialize lowp float offset\\n#pragma mapbox: initialize mediump float width\\n#pragma mapbox: initialize lowp float floorwidth\\nfloat ANTIALIASING=1.0/u_device_pixel_ratio/2.0;vec2 a_extrude=a_data.xy-128.0;float a_direction=mod(a_data.z,4.0)-1.0;float a_linesofar=(floor(a_data.z/4.0)+a_data.w*64.0)*LINE_DISTANCE_SCALE;vec2 pos=floor(a_pos_normal*0.5);mediump vec2 normal=a_pos_normal-2.0*pos;normal.y=normal.y*2.0-1.0;v_normal=normal;gapwidth=gapwidth/2.0;float halfwidth=width/2.0;offset=-1.0*offset;float inset=gapwidth+(gapwidth > 0.0 ? ANTIALIASING : 0.0);float outset=gapwidth+halfwidth*(gapwidth > 0.0 ? 2.0 : 1.0)+(halfwidth==0.0 ? 0.0 : ANTIALIASING);mediump vec2 dist=outset*a_extrude*scale;mediump float u=0.5*a_direction;mediump float t=1.0-abs(u);mediump vec2 offset2=offset*a_extrude*scale*normal.y*mat2(t,-u,u,t);vec4 projected_extrude=u_matrix*vec4(dist/u_ratio,0.0,0.0);gl_Position=u_matrix*vec4(pos+offset2/u_ratio,0.0,1.0)+projected_extrude;float extrude_length_without_perspective=length(dist);float extrude_length_with_perspective=length(projected_extrude.xy/gl_Position.w*u_units_to_pixels);v_gamma_scale=extrude_length_without_perspective/extrude_length_with_perspective;v_tex_a=vec2(a_linesofar*u_patternscale_a.x/floorwidth,normal.y*u_patternscale_a.y+u_tex_y_a);v_tex_b=vec2(a_linesofar*u_patternscale_b.x/floorwidth,normal.y*u_patternscale_b.y+u_tex_y_b);v_width2=vec2(outset,inset);}\"),dr=yr(\"uniform float u_fade_t;uniform float u_opacity;uniform sampler2D u_image0;uniform sampler2D u_image1;varying vec2 v_pos0;varying vec2 v_pos1;uniform float u_brightness_low;uniform float u_brightness_high;uniform float u_saturation_factor;uniform float u_contrast_factor;uniform vec3 u_spin_weights;void main() {vec4 color0=texture2D(u_image0,v_pos0);vec4 color1=texture2D(u_image1,v_pos1);if (color0.a > 0.0) {color0.rgb=color0.rgb/color0.a;}if (color1.a > 0.0) {color1.rgb=color1.rgb/color1.a;}vec4 color=mix(color0,color1,u_fade_t);color.a*=u_opacity;vec3 rgb=color.rgb;rgb=vec3(dot(rgb,u_spin_weights.xyz),dot(rgb,u_spin_weights.zxy),dot(rgb,u_spin_weights.yzx));float average=(color.r+color.g+color.b)/3.0;rgb+=(average-rgb)*u_saturation_factor;rgb=(rgb-0.5)*u_contrast_factor+0.5;vec3 u_high_vec=vec3(u_brightness_low,u_brightness_low,u_brightness_low);vec3 u_low_vec=vec3(u_brightness_high,u_brightness_high,u_brightness_high);gl_FragColor=vec4(mix(u_high_vec,u_low_vec,rgb)*color.a,color.a);\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"uniform mat4 u_matrix;uniform vec2 u_tl_parent;uniform float u_scale_parent;uniform float u_buffer_scale;attribute vec2 a_pos;attribute vec2 a_texture_pos;varying vec2 v_pos0;varying vec2 v_pos1;void main() {gl_Position=u_matrix*vec4(a_pos,0,1);v_pos0=(((a_texture_pos/8192.0)-0.5)/u_buffer_scale )+0.5;v_pos1=(v_pos0*u_scale_parent)+u_tl_parent;}\"),mr=yr(\"uniform sampler2D u_texture;varying vec2 v_tex;varying float v_fade_opacity;\\n#pragma mapbox: define lowp float opacity\\nvoid main() {\\n#pragma mapbox: initialize lowp float opacity\\nlowp float alpha=opacity*v_fade_opacity;gl_FragColor=texture2D(u_texture,v_tex)*alpha;\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"const float PI=3.141592653589793;attribute vec4 a_pos_offset;attribute vec4 a_data;attribute vec4 a_pixeloffset;attribute vec3 a_projected_pos;attribute float a_fade_opacity;uniform bool u_is_size_zoom_constant;uniform bool u_is_size_feature_constant;uniform highp float u_size_t;uniform highp float u_size;uniform highp float u_camera_to_center_distance;uniform highp float u_pitch;uniform bool u_rotate_symbol;uniform highp float u_aspect_ratio;uniform float u_fade_change;uniform mat4 u_matrix;uniform mat4 u_label_plane_matrix;uniform mat4 u_coord_matrix;uniform bool u_is_text;uniform bool u_pitch_with_map;uniform vec2 u_texsize;varying vec2 v_tex;varying float v_fade_opacity;\\n#pragma mapbox: define lowp float opacity\\nvoid main() {\\n#pragma mapbox: initialize lowp float opacity\\nvec2 a_pos=a_pos_offset.xy;vec2 a_offset=a_pos_offset.zw;vec2 a_tex=a_data.xy;vec2 a_size=a_data.zw;float a_size_min=floor(a_size[0]*0.5);vec2 a_pxoffset=a_pixeloffset.xy;vec2 a_minFontScale=a_pixeloffset.zw/256.0;highp float segment_angle=-a_projected_pos[2];float size;if (!u_is_size_zoom_constant && !u_is_size_feature_constant) {size=mix(a_size_min,a_size[1],u_size_t)/128.0;} else if (u_is_size_zoom_constant && !u_is_size_feature_constant) {size=a_size_min/128.0;} else {size=u_size;}vec4 projectedPoint=u_matrix*vec4(a_pos,0,1);highp float camera_to_anchor_distance=projectedPoint.w;highp float distance_ratio=u_pitch_with_map ?\\ncamera_to_anchor_distance/u_camera_to_center_distance :\\nu_camera_to_center_distance/camera_to_anchor_distance;highp float perspective_ratio=clamp(0.5+0.5*distance_ratio,0.0,4.0);size*=perspective_ratio;float fontScale=u_is_text ? size/24.0 : size;highp float symbol_rotation=0.0;if (u_rotate_symbol) {vec4 offsetProjectedPoint=u_matrix*vec4(a_pos+vec2(1,0),0,1);vec2 a=projectedPoint.xy/projectedPoint.w;vec2 b=offsetProjectedPoint.xy/offsetProjectedPoint.w;symbol_rotation=atan((b.y-a.y)/u_aspect_ratio,b.x-a.x);}highp float angle_sin=sin(segment_angle+symbol_rotation);highp float angle_cos=cos(segment_angle+symbol_rotation);mat2 rotation_matrix=mat2(angle_cos,-1.0*angle_sin,angle_sin,angle_cos);vec4 projected_pos=u_label_plane_matrix*vec4(a_projected_pos.xy,0.0,1.0);gl_Position=u_coord_matrix*vec4(projected_pos.xy/projected_pos.w+rotation_matrix*(a_offset/32.0*max(a_minFontScale,fontScale)+a_pxoffset/16.0),0.0,1.0);v_tex=a_tex/u_texsize;vec2 fade_opacity=unpack_opacity(a_fade_opacity);float fade_change=fade_opacity[1] > 0.5 ? u_fade_change :-u_fade_change;v_fade_opacity=max(0.0,min(1.0,fade_opacity[0]+fade_change));}\"),gr=yr(\"#define SDF_PX 8.0\\nuniform bool u_is_halo;uniform sampler2D u_texture;uniform highp float u_gamma_scale;uniform lowp float u_device_pixel_ratio;uniform bool u_is_text;varying vec2 v_data0;varying vec3 v_data1;\\n#pragma mapbox: define highp vec4 fill_color\\n#pragma mapbox: define highp vec4 halo_color\\n#pragma mapbox: define lowp float opacity\\n#pragma mapbox: define lowp float halo_width\\n#pragma mapbox: define lowp float halo_blur\\nvoid main() {\\n#pragma mapbox: initialize highp vec4 fill_color\\n#pragma mapbox: initialize highp vec4 halo_color\\n#pragma mapbox: initialize lowp float opacity\\n#pragma mapbox: initialize lowp float halo_width\\n#pragma mapbox: initialize lowp float halo_blur\\nfloat EDGE_GAMMA=0.105/u_device_pixel_ratio;vec2 tex=v_data0.xy;float gamma_scale=v_data1.x;float size=v_data1.y;float fade_opacity=v_data1[2];float fontScale=u_is_text ? size/24.0 : size;lowp vec4 color=fill_color;highp float gamma=EDGE_GAMMA/(fontScale*u_gamma_scale);lowp float buff=(256.0-64.0)/256.0;if (u_is_halo) {color=halo_color;gamma=(halo_blur*1.19/SDF_PX+EDGE_GAMMA)/(fontScale*u_gamma_scale);buff=(6.0-halo_width/fontScale)/SDF_PX;}lowp float dist=texture2D(u_texture,tex).a;highp float gamma_scaled=gamma*gamma_scale;highp float alpha=smoothstep(buff-gamma_scaled,buff+gamma_scaled,dist);gl_FragColor=color*(alpha*opacity*fade_opacity);\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"const float PI=3.141592653589793;attribute vec4 a_pos_offset;attribute vec4 a_data;attribute vec4 a_pixeloffset;attribute vec3 a_projected_pos;attribute float a_fade_opacity;uniform bool u_is_size_zoom_constant;uniform bool u_is_size_feature_constant;uniform highp float u_size_t;uniform highp float u_size;uniform mat4 u_matrix;uniform mat4 u_label_plane_matrix;uniform mat4 u_coord_matrix;uniform bool u_is_text;uniform bool u_pitch_with_map;uniform highp float u_pitch;uniform bool u_rotate_symbol;uniform highp float u_aspect_ratio;uniform highp float u_camera_to_center_distance;uniform float u_fade_change;uniform vec2 u_texsize;varying vec2 v_data0;varying vec3 v_data1;\\n#pragma mapbox: define highp vec4 fill_color\\n#pragma mapbox: define highp vec4 halo_color\\n#pragma mapbox: define lowp float opacity\\n#pragma mapbox: define lowp float halo_width\\n#pragma mapbox: define lowp float halo_blur\\nvoid main() {\\n#pragma mapbox: initialize highp vec4 fill_color\\n#pragma mapbox: initialize highp vec4 halo_color\\n#pragma mapbox: initialize lowp float opacity\\n#pragma mapbox: initialize lowp float halo_width\\n#pragma mapbox: initialize lowp float halo_blur\\nvec2 a_pos=a_pos_offset.xy;vec2 a_offset=a_pos_offset.zw;vec2 a_tex=a_data.xy;vec2 a_size=a_data.zw;float a_size_min=floor(a_size[0]*0.5);vec2 a_pxoffset=a_pixeloffset.xy;highp float segment_angle=-a_projected_pos[2];float size;if (!u_is_size_zoom_constant && !u_is_size_feature_constant) {size=mix(a_size_min,a_size[1],u_size_t)/128.0;} else if (u_is_size_zoom_constant && !u_is_size_feature_constant) {size=a_size_min/128.0;} else {size=u_size;}vec4 projectedPoint=u_matrix*vec4(a_pos,0,1);highp float camera_to_anchor_distance=projectedPoint.w;highp float distance_ratio=u_pitch_with_map ?\\ncamera_to_anchor_distance/u_camera_to_center_distance :\\nu_camera_to_center_distance/camera_to_anchor_distance;highp float perspective_ratio=clamp(0.5+0.5*distance_ratio,0.0,4.0);size*=perspective_ratio;float fontScale=u_is_text ? size/24.0 : size;highp float symbol_rotation=0.0;if (u_rotate_symbol) {vec4 offsetProjectedPoint=u_matrix*vec4(a_pos+vec2(1,0),0,1);vec2 a=projectedPoint.xy/projectedPoint.w;vec2 b=offsetProjectedPoint.xy/offsetProjectedPoint.w;symbol_rotation=atan((b.y-a.y)/u_aspect_ratio,b.x-a.x);}highp float angle_sin=sin(segment_angle+symbol_rotation);highp float angle_cos=cos(segment_angle+symbol_rotation);mat2 rotation_matrix=mat2(angle_cos,-1.0*angle_sin,angle_sin,angle_cos);vec4 projected_pos=u_label_plane_matrix*vec4(a_projected_pos.xy,0.0,1.0);gl_Position=u_coord_matrix*vec4(projected_pos.xy/projected_pos.w+rotation_matrix*(a_offset/32.0*fontScale+a_pxoffset),0.0,1.0);float gamma_scale=gl_Position.w;vec2 fade_opacity=unpack_opacity(a_fade_opacity);float fade_change=fade_opacity[1] > 0.5 ? u_fade_change :-u_fade_change;float interpolated_fade_opacity=max(0.0,min(1.0,fade_opacity[0]+fade_change));v_data0=a_tex/u_texsize;v_data1=vec3(gamma_scale,size,interpolated_fade_opacity);}\"),vr=yr(\"#define SDF_PX 8.0\\n#define SDF 1.0\\n#define ICON 0.0\\nuniform bool u_is_halo;uniform sampler2D u_texture;uniform sampler2D u_texture_icon;uniform highp float u_gamma_scale;uniform lowp float u_device_pixel_ratio;varying vec4 v_data0;varying vec4 v_data1;\\n#pragma mapbox: define highp vec4 fill_color\\n#pragma mapbox: define highp vec4 halo_color\\n#pragma mapbox: define lowp float opacity\\n#pragma mapbox: define lowp float halo_width\\n#pragma mapbox: define lowp float halo_blur\\nvoid main() {\\n#pragma mapbox: initialize highp vec4 fill_color\\n#pragma mapbox: initialize highp vec4 halo_color\\n#pragma mapbox: initialize lowp float opacity\\n#pragma mapbox: initialize lowp float halo_width\\n#pragma mapbox: initialize lowp float halo_blur\\nfloat fade_opacity=v_data1[2];if (v_data1.w==ICON) {vec2 tex_icon=v_data0.zw;lowp float alpha=opacity*fade_opacity;gl_FragColor=texture2D(u_texture_icon,tex_icon)*alpha;\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\nreturn;}vec2 tex=v_data0.xy;float EDGE_GAMMA=0.105/u_device_pixel_ratio;float gamma_scale=v_data1.x;float size=v_data1.y;float fontScale=size/24.0;lowp vec4 color=fill_color;highp float gamma=EDGE_GAMMA/(fontScale*u_gamma_scale);lowp float buff=(256.0-64.0)/256.0;if (u_is_halo) {color=halo_color;gamma=(halo_blur*1.19/SDF_PX+EDGE_GAMMA)/(fontScale*u_gamma_scale);buff=(6.0-halo_width/fontScale)/SDF_PX;}lowp float dist=texture2D(u_texture,tex).a;highp float gamma_scaled=gamma*gamma_scale;highp float alpha=smoothstep(buff-gamma_scaled,buff+gamma_scaled,dist);gl_FragColor=color*(alpha*opacity*fade_opacity);\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"const float PI=3.141592653589793;attribute vec4 a_pos_offset;attribute vec4 a_data;attribute vec3 a_projected_pos;attribute float a_fade_opacity;uniform bool u_is_size_zoom_constant;uniform bool u_is_size_feature_constant;uniform highp float u_size_t;uniform highp float u_size;uniform mat4 u_matrix;uniform mat4 u_label_plane_matrix;uniform mat4 u_coord_matrix;uniform bool u_is_text;uniform bool u_pitch_with_map;uniform highp float u_pitch;uniform bool u_rotate_symbol;uniform highp float u_aspect_ratio;uniform highp float u_camera_to_center_distance;uniform float u_fade_change;uniform vec2 u_texsize;uniform vec2 u_texsize_icon;varying vec4 v_data0;varying vec4 v_data1;\\n#pragma mapbox: define highp vec4 fill_color\\n#pragma mapbox: define highp vec4 halo_color\\n#pragma mapbox: define lowp float opacity\\n#pragma mapbox: define lowp float halo_width\\n#pragma mapbox: define lowp float halo_blur\\nvoid main() {\\n#pragma mapbox: initialize highp vec4 fill_color\\n#pragma mapbox: initialize highp vec4 halo_color\\n#pragma mapbox: initialize lowp float opacity\\n#pragma mapbox: initialize lowp float halo_width\\n#pragma mapbox: initialize lowp float halo_blur\\nvec2 a_pos=a_pos_offset.xy;vec2 a_offset=a_pos_offset.zw;vec2 a_tex=a_data.xy;vec2 a_size=a_data.zw;float a_size_min=floor(a_size[0]*0.5);float is_sdf=a_size[0]-2.0*a_size_min;highp float segment_angle=-a_projected_pos[2];float size;if (!u_is_size_zoom_constant && !u_is_size_feature_constant) {size=mix(a_size_min,a_size[1],u_size_t)/128.0;} else if (u_is_size_zoom_constant && !u_is_size_feature_constant) {size=a_size_min/128.0;} else {size=u_size;}vec4 projectedPoint=u_matrix*vec4(a_pos,0,1);highp float camera_to_anchor_distance=projectedPoint.w;highp float distance_ratio=u_pitch_with_map ?\\ncamera_to_anchor_distance/u_camera_to_center_distance :\\nu_camera_to_center_distance/camera_to_anchor_distance;highp float perspective_ratio=clamp(0.5+0.5*distance_ratio,0.0,4.0);size*=perspective_ratio;float fontScale=size/24.0;highp float symbol_rotation=0.0;if (u_rotate_symbol) {vec4 offsetProjectedPoint=u_matrix*vec4(a_pos+vec2(1,0),0,1);vec2 a=projectedPoint.xy/projectedPoint.w;vec2 b=offsetProjectedPoint.xy/offsetProjectedPoint.w;symbol_rotation=atan((b.y-a.y)/u_aspect_ratio,b.x-a.x);}highp float angle_sin=sin(segment_angle+symbol_rotation);highp float angle_cos=cos(segment_angle+symbol_rotation);mat2 rotation_matrix=mat2(angle_cos,-1.0*angle_sin,angle_sin,angle_cos);vec4 projected_pos=u_label_plane_matrix*vec4(a_projected_pos.xy,0.0,1.0);gl_Position=u_coord_matrix*vec4(projected_pos.xy/projected_pos.w+rotation_matrix*(a_offset/32.0*fontScale),0.0,1.0);float gamma_scale=gl_Position.w;vec2 fade_opacity=unpack_opacity(a_fade_opacity);float fade_change=fade_opacity[1] > 0.5 ? u_fade_change :-u_fade_change;float interpolated_fade_opacity=max(0.0,min(1.0,fade_opacity[0]+fade_change));v_data0.xy=a_tex/u_texsize;v_data0.zw=a_tex/u_texsize_icon;v_data1=vec4(gamma_scale,size,interpolated_fade_opacity,is_sdf);}\");function yr(t,e){var r=/#pragma mapbox: ([\\w]+) ([\\w]+) ([\\w]+) ([\\w]+)/g,n={};return{fragmentSource:t=t.replace(r,(function(t,e,r,i,a){return n[a]=!0,\"define\"===e?\"\\n#ifndef HAS_UNIFORM_u_\"+a+\"\\nvarying \"+r+\" \"+i+\" \"+a+\";\\n#else\\nuniform \"+r+\" \"+i+\" u_\"+a+\";\\n#endif\\n\":\"\\n#ifdef HAS_UNIFORM_u_\"+a+\"\\n \"+r+\" \"+i+\" \"+a+\" = u_\"+a+\";\\n#endif\\n\"})),vertexSource:e=e.replace(r,(function(t,e,r,i,a){var o=\"float\"===i?\"vec2\":\"vec4\",s=a.match(/color/)?\"color\":o;return n[a]?\"define\"===e?\"\\n#ifndef HAS_UNIFORM_u_\"+a+\"\\nuniform lowp float u_\"+a+\"_t;\\nattribute \"+r+\" \"+o+\" a_\"+a+\";\\nvarying \"+r+\" \"+i+\" \"+a+\";\\n#else\\nuniform \"+r+\" \"+i+\" u_\"+a+\";\\n#endif\\n\":\"vec4\"===s?\"\\n#ifndef HAS_UNIFORM_u_\"+a+\"\\n \"+a+\" = a_\"+a+\";\\n#else\\n \"+r+\" \"+i+\" \"+a+\" = u_\"+a+\";\\n#endif\\n\":\"\\n#ifndef HAS_UNIFORM_u_\"+a+\"\\n \"+a+\" = unpack_mix_\"+s+\"(a_\"+a+\", u_\"+a+\"_t);\\n#else\\n \"+r+\" \"+i+\" \"+a+\" = u_\"+a+\";\\n#endif\\n\":\"define\"===e?\"\\n#ifndef HAS_UNIFORM_u_\"+a+\"\\nuniform lowp float u_\"+a+\"_t;\\nattribute \"+r+\" \"+o+\" a_\"+a+\";\\n#else\\nuniform \"+r+\" \"+i+\" u_\"+a+\";\\n#endif\\n\":\"vec4\"===s?\"\\n#ifndef HAS_UNIFORM_u_\"+a+\"\\n \"+r+\" \"+i+\" \"+a+\" = a_\"+a+\";\\n#else\\n \"+r+\" \"+i+\" \"+a+\" = u_\"+a+\";\\n#endif\\n\":\"\\n#ifndef HAS_UNIFORM_u_\"+a+\"\\n \"+r+\" \"+i+\" \"+a+\" = unpack_mix_\"+s+\"(a_\"+a+\", u_\"+a+\"_t);\\n#else\\n \"+r+\" \"+i+\" \"+a+\" = u_\"+a+\";\\n#endif\\n\"}))}}var xr=Object.freeze({__proto__:null,prelude:Ye,background:We,backgroundPattern:Xe,circle:Ze,clippingMask:Je,heatmap:Ke,heatmapTexture:Qe,collisionBox:$e,collisionCircle:tr,debug:er,fill:rr,fillOutline:nr,fillOutlinePattern:ir,fillPattern:ar,fillExtrusion:or,fillExtrusionPattern:sr,hillshadePrepare:lr,hillshade:cr,line:ur,lineGradient:fr,linePattern:hr,lineSDF:pr,raster:dr,symbolIcon:mr,symbolSDF:gr,symbolTextAndIcon:vr}),br=function(){this.boundProgram=null,this.boundLayoutVertexBuffer=null,this.boundPaintVertexBuffers=[],this.boundIndexBuffer=null,this.boundVertexOffset=null,this.boundDynamicVertexBuffer=null,this.vao=null};br.prototype.bind=function(t,e,r,n,i,a,o,s){this.context=t;for(var l=this.boundPaintVertexBuffers.length!==n.length,c=0;!l&&c<n.length;c++)this.boundPaintVertexBuffers[c]!==n[c]&&(l=!0);var u=!this.vao||this.boundProgram!==e||this.boundLayoutVertexBuffer!==r||l||this.boundIndexBuffer!==i||this.boundVertexOffset!==a||this.boundDynamicVertexBuffer!==o||this.boundDynamicVertexBuffer2!==s;!t.extVertexArrayObject||u?this.freshBind(e,r,n,i,a,o,s):(t.bindVertexArrayOES.set(this.vao),o&&o.bind(),i&&i.dynamicDraw&&i.bind(),s&&s.bind())},br.prototype.freshBind=function(t,e,r,n,i,a,o){var s,l=t.numAttributes,c=this.context,u=c.gl;if(c.extVertexArrayObject)this.vao&&this.destroy(),this.vao=c.extVertexArrayObject.createVertexArrayOES(),c.bindVertexArrayOES.set(this.vao),s=0,this.boundProgram=t,this.boundLayoutVertexBuffer=e,this.boundPaintVertexBuffers=r,this.boundIndexBuffer=n,this.boundVertexOffset=i,this.boundDynamicVertexBuffer=a,this.boundDynamicVertexBuffer2=o;else{s=c.currentNumAttributes||0;for(var f=l;f<s;f++)u.disableVertexAttribArray(f)}e.enableAttributes(u,t);for(var h=0,p=r;h<p.length;h+=1){p[h].enableAttributes(u,t)}a&&a.enableAttributes(u,t),o&&o.enableAttributes(u,t),e.bind(),e.setVertexAttribPointers(u,t,i);for(var d=0,m=r;d<m.length;d+=1){var g=m[d];g.bind(),g.setVertexAttribPointers(u,t,i)}a&&(a.bind(),a.setVertexAttribPointers(u,t,i)),n&&n.bind(),o&&(o.bind(),o.setVertexAttribPointers(u,t,i)),c.currentNumAttributes=l},br.prototype.destroy=function(){this.vao&&(this.context.extVertexArrayObject.deleteVertexArrayOES(this.vao),this.vao=null)};var _r=function(t,e,r,n,i){var a=t.gl;this.program=a.createProgram();var o=r?r.defines():[];i&&o.push(\"#define OVERDRAW_INSPECTOR;\");var s=o.concat(Ye.fragmentSource,e.fragmentSource).join(\"\\n\"),l=o.concat(Ye.vertexSource,e.vertexSource).join(\"\\n\"),c=a.createShader(a.FRAGMENT_SHADER);if(a.isContextLost())this.failedToCreate=!0;else{a.shaderSource(c,s),a.compileShader(c),a.attachShader(this.program,c);var u=a.createShader(a.VERTEX_SHADER);if(a.isContextLost())this.failedToCreate=!0;else{a.shaderSource(u,l),a.compileShader(u),a.attachShader(this.program,u);for(var f=r?r.layoutAttributes:[],h=0;h<f.length;h++)a.bindAttribLocation(this.program,h,f[h].name);a.linkProgram(this.program),a.deleteShader(u),a.deleteShader(c),this.numAttributes=a.getProgramParameter(this.program,a.ACTIVE_ATTRIBUTES),this.attributes={};for(var p={},d=0;d<this.numAttributes;d++){var m=a.getActiveAttrib(this.program,d);m&&(this.attributes[m.name]=a.getAttribLocation(this.program,m.name))}for(var g=a.getProgramParameter(this.program,a.ACTIVE_UNIFORMS),v=0;v<g;v++){var y=a.getActiveUniform(this.program,v);y&&(p[y.name]=a.getUniformLocation(this.program,y.name))}this.fixedUniforms=n(t,p),this.binderUniforms=r?r.getUniforms(t,p):[]}}};function wr(t,e,r){var n=1/pe(r,1,e.transform.tileZoom),i=Math.pow(2,r.tileID.overscaledZ),a=r.tileSize*Math.pow(2,e.transform.tileZoom)/i,o=a*(r.tileID.canonical.x+r.tileID.wrap*i),s=a*r.tileID.canonical.y;return{u_image:0,u_texsize:r.imageAtlasTexture.size,u_scale:[n,t.fromScale,t.toScale],u_fade:t.t,u_pixel_coord_upper:[o>>16,s>>16],u_pixel_coord_lower:[65535&o,65535&s]}}_r.prototype.draw=function(t,e,r,n,i,a,o,s,l,c,u,f,h,p,d,m){var g,v=t.gl;if(!this.failedToCreate){for(var y in t.program.set(this.program),t.setDepthMode(r),t.setStencilMode(n),t.setColorMode(i),t.setCullFace(a),this.fixedUniforms)this.fixedUniforms[y].set(o[y]);p&&p.setUniforms(t,this.binderUniforms,f,{zoom:h});for(var x=(g={},g[v.LINES]=2,g[v.TRIANGLES]=3,g[v.LINE_STRIP]=1,g)[e],b=0,_=u.get();b<_.length;b+=1){var w=_[b],T=w.vaos||(w.vaos={});(T[s]||(T[s]=new br)).bind(t,this,l,p?p.getPaintVertexBuffers():[],c,w.vertexOffset,d,m),v.drawElements(e,w.primitiveLength*x,v.UNSIGNED_SHORT,w.primitiveOffset*x*2)}}};var Tr=function(e,r,n,i){var a=r.style.light,o=a.properties.get(\"position\"),s=[o.x,o.y,o.z],l=t.create$1();\"viewport\"===a.properties.get(\"anchor\")&&t.fromRotation(l,-r.transform.angle),t.transformMat3(s,s,l);var c=a.properties.get(\"color\");return{u_matrix:e,u_lightpos:s,u_lightintensity:a.properties.get(\"intensity\"),u_lightcolor:[c.r,c.g,c.b],u_vertical_gradient:+n,u_opacity:i}},kr=function(e,r,n,i,a,o,s){return t.extend(Tr(e,r,n,i),wr(o,r,s),{u_height_factor:-Math.pow(2,a.overscaledZ)/s.tileSize/8})},Ar=function(t){return{u_matrix:t}},Mr=function(e,r,n,i){return t.extend(Ar(e),wr(n,r,i))},Sr=function(t,e){return{u_matrix:t,u_world:e}},Er=function(e,r,n,i,a){return t.extend(Mr(e,r,n,i),{u_world:a})},Lr=function(e,r,n,i){var a,o,s=e.transform;if(\"map\"===i.paint.get(\"circle-pitch-alignment\")){var l=pe(n,1,s.zoom);a=!0,o=[l,l]}else a=!1,o=s.pixelsToGLUnits;return{u_camera_to_center_distance:s.cameraToCenterDistance,u_scale_with_map:+(\"map\"===i.paint.get(\"circle-pitch-scale\")),u_matrix:e.translatePosMatrix(r.posMatrix,n,i.paint.get(\"circle-translate\"),i.paint.get(\"circle-translate-anchor\")),u_pitch_with_map:+a,u_device_pixel_ratio:t.browser.devicePixelRatio,u_extrude_scale:o}},Cr=function(t,e,r){var n=pe(r,1,e.zoom),i=Math.pow(2,e.zoom-r.tileID.overscaledZ),a=r.tileID.overscaleFactor();return{u_matrix:t,u_camera_to_center_distance:e.cameraToCenterDistance,u_pixels_to_tile_units:n,u_extrude_scale:[e.pixelsToGLUnits[0]/(n*i),e.pixelsToGLUnits[1]/(n*i)],u_overscale_factor:a}},Pr=function(t,e,r){return{u_matrix:t,u_inv_matrix:e,u_camera_to_center_distance:r.cameraToCenterDistance,u_viewport_size:[r.width,r.height]}},Ir=function(t,e,r){return void 0===r&&(r=1),{u_matrix:t,u_color:e,u_overlay:0,u_overlay_scale:r}},Or=function(t){return{u_matrix:t}},zr=function(t,e,r,n){return{u_matrix:t,u_extrude_scale:pe(e,1,r),u_intensity:n}};function Dr(e,r){var n=Math.pow(2,r.canonical.z),i=r.canonical.y;return[new t.MercatorCoordinate(0,i/n).toLngLat().lat,new t.MercatorCoordinate(0,(i+1)/n).toLngLat().lat]}var Rr=function(e,r,n){var i=e.transform;return{u_matrix:Ur(e,r,n),u_ratio:1/pe(r,1,i.zoom),u_device_pixel_ratio:t.browser.devicePixelRatio,u_units_to_pixels:[1/i.pixelsToGLUnits[0],1/i.pixelsToGLUnits[1]]}},Fr=function(e,r,n){return t.extend(Rr(e,r,n),{u_image:0})},Br=function(e,r,n,i){var a=e.transform,o=jr(r,a);return{u_matrix:Ur(e,r,n),u_texsize:r.imageAtlasTexture.size,u_ratio:1/pe(r,1,a.zoom),u_device_pixel_ratio:t.browser.devicePixelRatio,u_image:0,u_scale:[o,i.fromScale,i.toScale],u_fade:i.t,u_units_to_pixels:[1/a.pixelsToGLUnits[0],1/a.pixelsToGLUnits[1]]}},Nr=function(e,r,n,i,a){var o=e.transform,s=e.lineAtlas,l=jr(r,o),c=\"round\"===n.layout.get(\"line-cap\"),u=s.getDash(i.from,c),f=s.getDash(i.to,c),h=u.width*a.fromScale,p=f.width*a.toScale;return t.extend(Rr(e,r,n),{u_patternscale_a:[l/h,-u.height/2],u_patternscale_b:[l/p,-f.height/2],u_sdfgamma:s.width/(256*Math.min(h,p)*t.browser.devicePixelRatio)/2,u_image:0,u_tex_y_a:u.y,u_tex_y_b:f.y,u_mix:a.t})};function jr(t,e){return 1/pe(t,1,e.tileZoom)}function Ur(t,e,r){return t.translatePosMatrix(e.tileID.posMatrix,e,r.paint.get(\"line-translate\"),r.paint.get(\"line-translate-anchor\"))}var Vr=function(t,e,r,n,i){return{u_matrix:t,u_tl_parent:e,u_scale_parent:r,u_buffer_scale:1,u_fade_t:n.mix,u_opacity:n.opacity*i.paint.get(\"raster-opacity\"),u_image0:0,u_image1:1,u_brightness_low:i.paint.get(\"raster-brightness-min\"),u_brightness_high:i.paint.get(\"raster-brightness-max\"),u_saturation_factor:(o=i.paint.get(\"raster-saturation\"),o>0?1-1/(1.001-o):-o),u_contrast_factor:(a=i.paint.get(\"raster-contrast\"),a>0?1/(1-a):1+a),u_spin_weights:Hr(i.paint.get(\"raster-hue-rotate\"))};var a,o};function Hr(t){t*=Math.PI/180;var e=Math.sin(t),r=Math.cos(t);return[(2*r+1)/3,(-Math.sqrt(3)*e-r+1)/3,(Math.sqrt(3)*e-r+1)/3]}var qr,Gr=function(t,e,r,n,i,a,o,s,l,c){var u=i.transform;return{u_is_size_zoom_constant:+(\"constant\"===t||\"source\"===t),u_is_size_feature_constant:+(\"constant\"===t||\"camera\"===t),u_size_t:e?e.uSizeT:0,u_size:e?e.uSize:0,u_camera_to_center_distance:u.cameraToCenterDistance,u_pitch:u.pitch/360*2*Math.PI,u_rotate_symbol:+r,u_aspect_ratio:u.width/u.height,u_fade_change:i.options.fadeDuration?i.symbolFadeChange:1,u_matrix:a,u_label_plane_matrix:o,u_coord_matrix:s,u_is_text:+l,u_pitch_with_map:+n,u_texsize:c,u_texture:0}},Yr=function(e,r,n,i,a,o,s,l,c,u,f){var h=a.transform;return t.extend(Gr(e,r,n,i,a,o,s,l,c,u),{u_gamma_scale:i?Math.cos(h._pitch)*h.cameraToCenterDistance:1,u_device_pixel_ratio:t.browser.devicePixelRatio,u_is_halo:+f})},Wr=function(e,r,n,i,a,o,s,l,c,u){return t.extend(Yr(e,r,n,i,a,o,s,l,!0,c,!0),{u_texsize_icon:u,u_texture_icon:1})},Xr=function(t,e,r){return{u_matrix:t,u_opacity:e,u_color:r}},Zr=function(e,r,n,i,a,o){return t.extend(function(t,e,r,n){var i=r.imageManager.getPattern(t.from.toString()),a=r.imageManager.getPattern(t.to.toString()),o=r.imageManager.getPixelSize(),s=o.width,l=o.height,c=Math.pow(2,n.tileID.overscaledZ),u=n.tileSize*Math.pow(2,r.transform.tileZoom)/c,f=u*(n.tileID.canonical.x+n.tileID.wrap*c),h=u*n.tileID.canonical.y;return{u_image:0,u_pattern_tl_a:i.tl,u_pattern_br_a:i.br,u_pattern_tl_b:a.tl,u_pattern_br_b:a.br,u_texsize:[s,l],u_mix:e.t,u_pattern_size_a:i.displaySize,u_pattern_size_b:a.displaySize,u_scale_a:e.fromScale,u_scale_b:e.toScale,u_tile_units_to_pixels:1/pe(n,1,r.transform.tileZoom),u_pixel_coord_upper:[f>>16,h>>16],u_pixel_coord_lower:[65535&f,65535&h]}}(i,o,n,a),{u_matrix:e,u_opacity:r})},Jr={fillExtrusion:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_lightpos:new t.Uniform3f(e,r.u_lightpos),u_lightintensity:new t.Uniform1f(e,r.u_lightintensity),u_lightcolor:new t.Uniform3f(e,r.u_lightcolor),u_vertical_gradient:new t.Uniform1f(e,r.u_vertical_gradient),u_opacity:new t.Uniform1f(e,r.u_opacity)}},fillExtrusionPattern:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_lightpos:new t.Uniform3f(e,r.u_lightpos),u_lightintensity:new t.Uniform1f(e,r.u_lightintensity),u_lightcolor:new t.Uniform3f(e,r.u_lightcolor),u_vertical_gradient:new t.Uniform1f(e,r.u_vertical_gradient),u_height_factor:new t.Uniform1f(e,r.u_height_factor),u_image:new t.Uniform1i(e,r.u_image),u_texsize:new t.Uniform2f(e,r.u_texsize),u_pixel_coord_upper:new t.Uniform2f(e,r.u_pixel_coord_upper),u_pixel_coord_lower:new t.Uniform2f(e,r.u_pixel_coord_lower),u_scale:new t.Uniform3f(e,r.u_scale),u_fade:new t.Uniform1f(e,r.u_fade),u_opacity:new t.Uniform1f(e,r.u_opacity)}},fill:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix)}},fillPattern:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_image:new t.Uniform1i(e,r.u_image),u_texsize:new t.Uniform2f(e,r.u_texsize),u_pixel_coord_upper:new t.Uniform2f(e,r.u_pixel_coord_upper),u_pixel_coord_lower:new t.Uniform2f(e,r.u_pixel_coord_lower),u_scale:new t.Uniform3f(e,r.u_scale),u_fade:new t.Uniform1f(e,r.u_fade)}},fillOutline:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_world:new t.Uniform2f(e,r.u_world)}},fillOutlinePattern:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_world:new t.Uniform2f(e,r.u_world),u_image:new t.Uniform1i(e,r.u_image),u_texsize:new t.Uniform2f(e,r.u_texsize),u_pixel_coord_upper:new t.Uniform2f(e,r.u_pixel_coord_upper),u_pixel_coord_lower:new t.Uniform2f(e,r.u_pixel_coord_lower),u_scale:new t.Uniform3f(e,r.u_scale),u_fade:new t.Uniform1f(e,r.u_fade)}},circle:function(e,r){return{u_camera_to_center_distance:new t.Uniform1f(e,r.u_camera_to_center_distance),u_scale_with_map:new t.Uniform1i(e,r.u_scale_with_map),u_pitch_with_map:new t.Uniform1i(e,r.u_pitch_with_map),u_extrude_scale:new t.Uniform2f(e,r.u_extrude_scale),u_device_pixel_ratio:new t.Uniform1f(e,r.u_device_pixel_ratio),u_matrix:new t.UniformMatrix4f(e,r.u_matrix)}},collisionBox:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_camera_to_center_distance:new t.Uniform1f(e,r.u_camera_to_center_distance),u_pixels_to_tile_units:new t.Uniform1f(e,r.u_pixels_to_tile_units),u_extrude_scale:new t.Uniform2f(e,r.u_extrude_scale),u_overscale_factor:new t.Uniform1f(e,r.u_overscale_factor)}},collisionCircle:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_inv_matrix:new t.UniformMatrix4f(e,r.u_inv_matrix),u_camera_to_center_distance:new t.Uniform1f(e,r.u_camera_to_center_distance),u_viewport_size:new t.Uniform2f(e,r.u_viewport_size)}},debug:function(e,r){return{u_color:new t.UniformColor(e,r.u_color),u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_overlay:new t.Uniform1i(e,r.u_overlay),u_overlay_scale:new t.Uniform1f(e,r.u_overlay_scale)}},clippingMask:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix)}},heatmap:function(e,r){return{u_extrude_scale:new t.Uniform1f(e,r.u_extrude_scale),u_intensity:new t.Uniform1f(e,r.u_intensity),u_matrix:new t.UniformMatrix4f(e,r.u_matrix)}},heatmapTexture:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_world:new t.Uniform2f(e,r.u_world),u_image:new t.Uniform1i(e,r.u_image),u_color_ramp:new t.Uniform1i(e,r.u_color_ramp),u_opacity:new t.Uniform1f(e,r.u_opacity)}},hillshade:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_image:new t.Uniform1i(e,r.u_image),u_latrange:new t.Uniform2f(e,r.u_latrange),u_light:new t.Uniform2f(e,r.u_light),u_shadow:new t.UniformColor(e,r.u_shadow),u_highlight:new t.UniformColor(e,r.u_highlight),u_accent:new t.UniformColor(e,r.u_accent)}},hillshadePrepare:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_image:new t.Uniform1i(e,r.u_image),u_dimension:new t.Uniform2f(e,r.u_dimension),u_zoom:new t.Uniform1f(e,r.u_zoom),u_maxzoom:new t.Uniform1f(e,r.u_maxzoom),u_unpack:new t.Uniform4f(e,r.u_unpack)}},line:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_ratio:new t.Uniform1f(e,r.u_ratio),u_device_pixel_ratio:new t.Uniform1f(e,r.u_device_pixel_ratio),u_units_to_pixels:new t.Uniform2f(e,r.u_units_to_pixels)}},lineGradient:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_ratio:new t.Uniform1f(e,r.u_ratio),u_device_pixel_ratio:new t.Uniform1f(e,r.u_device_pixel_ratio),u_units_to_pixels:new t.Uniform2f(e,r.u_units_to_pixels),u_image:new t.Uniform1i(e,r.u_image)}},linePattern:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_texsize:new t.Uniform2f(e,r.u_texsize),u_ratio:new t.Uniform1f(e,r.u_ratio),u_device_pixel_ratio:new t.Uniform1f(e,r.u_device_pixel_ratio),u_image:new t.Uniform1i(e,r.u_image),u_units_to_pixels:new t.Uniform2f(e,r.u_units_to_pixels),u_scale:new t.Uniform3f(e,r.u_scale),u_fade:new t.Uniform1f(e,r.u_fade)}},lineSDF:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_ratio:new t.Uniform1f(e,r.u_ratio),u_device_pixel_ratio:new t.Uniform1f(e,r.u_device_pixel_ratio),u_units_to_pixels:new t.Uniform2f(e,r.u_units_to_pixels),u_patternscale_a:new t.Uniform2f(e,r.u_patternscale_a),u_patternscale_b:new t.Uniform2f(e,r.u_patternscale_b),u_sdfgamma:new t.Uniform1f(e,r.u_sdfgamma),u_image:new t.Uniform1i(e,r.u_image),u_tex_y_a:new t.Uniform1f(e,r.u_tex_y_a),u_tex_y_b:new t.Uniform1f(e,r.u_tex_y_b),u_mix:new t.Uniform1f(e,r.u_mix)}},raster:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_tl_parent:new t.Uniform2f(e,r.u_tl_parent),u_scale_parent:new t.Uniform1f(e,r.u_scale_parent),u_buffer_scale:new t.Uniform1f(e,r.u_buffer_scale),u_fade_t:new t.Uniform1f(e,r.u_fade_t),u_opacity:new t.Uniform1f(e,r.u_opacity),u_image0:new t.Uniform1i(e,r.u_image0),u_image1:new t.Uniform1i(e,r.u_image1),u_brightness_low:new t.Uniform1f(e,r.u_brightness_low),u_brightness_high:new t.Uniform1f(e,r.u_brightness_high),u_saturation_factor:new t.Uniform1f(e,r.u_saturation_factor),u_contrast_factor:new t.Uniform1f(e,r.u_contrast_factor),u_spin_weights:new t.Uniform3f(e,r.u_spin_weights)}},symbolIcon:function(e,r){return{u_is_size_zoom_constant:new t.Uniform1i(e,r.u_is_size_zoom_constant),u_is_size_feature_constant:new t.Uniform1i(e,r.u_is_size_feature_constant),u_size_t:new t.Uniform1f(e,r.u_size_t),u_size:new t.Uniform1f(e,r.u_size),u_camera_to_center_distance:new t.Uniform1f(e,r.u_camera_to_center_distance),u_pitch:new t.Uniform1f(e,r.u_pitch),u_rotate_symbol:new t.Uniform1i(e,r.u_rotate_symbol),u_aspect_ratio:new t.Uniform1f(e,r.u_aspect_ratio),u_fade_change:new t.Uniform1f(e,r.u_fade_change),u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_label_plane_matrix:new t.UniformMatrix4f(e,r.u_label_plane_matrix),u_coord_matrix:new t.UniformMatrix4f(e,r.u_coord_matrix),u_is_text:new t.Uniform1i(e,r.u_is_text),u_pitch_with_map:new t.Uniform1i(e,r.u_pitch_with_map),u_texsize:new t.Uniform2f(e,r.u_texsize),u_texture:new t.Uniform1i(e,r.u_texture)}},symbolSDF:function(e,r){return{u_is_size_zoom_constant:new t.Uniform1i(e,r.u_is_size_zoom_constant),u_is_size_feature_constant:new t.Uniform1i(e,r.u_is_size_feature_constant),u_size_t:new t.Uniform1f(e,r.u_size_t),u_size:new t.Uniform1f(e,r.u_size),u_camera_to_center_distance:new t.Uniform1f(e,r.u_camera_to_center_distance),u_pitch:new t.Uniform1f(e,r.u_pitch),u_rotate_symbol:new t.Uniform1i(e,r.u_rotate_symbol),u_aspect_ratio:new t.Uniform1f(e,r.u_aspect_ratio),u_fade_change:new t.Uniform1f(e,r.u_fade_change),u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_label_plane_matrix:new t.UniformMatrix4f(e,r.u_label_plane_matrix),u_coord_matrix:new t.UniformMatrix4f(e,r.u_coord_matrix),u_is_text:new t.Uniform1i(e,r.u_is_text),u_pitch_with_map:new t.Uniform1i(e,r.u_pitch_with_map),u_texsize:new t.Uniform2f(e,r.u_texsize),u_texture:new t.Uniform1i(e,r.u_texture),u_gamma_scale:new t.Uniform1f(e,r.u_gamma_scale),u_device_pixel_ratio:new t.Uniform1f(e,r.u_device_pixel_ratio),u_is_halo:new t.Uniform1i(e,r.u_is_halo)}},symbolTextAndIcon:function(e,r){return{u_is_size_zoom_constant:new t.Uniform1i(e,r.u_is_size_zoom_constant),u_is_size_feature_constant:new t.Uniform1i(e,r.u_is_size_feature_constant),u_size_t:new t.Uniform1f(e,r.u_size_t),u_size:new t.Uniform1f(e,r.u_size),u_camera_to_center_distance:new t.Uniform1f(e,r.u_camera_to_center_distance),u_pitch:new t.Uniform1f(e,r.u_pitch),u_rotate_symbol:new t.Uniform1i(e,r.u_rotate_symbol),u_aspect_ratio:new t.Uniform1f(e,r.u_aspect_ratio),u_fade_change:new t.Uniform1f(e,r.u_fade_change),u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_label_plane_matrix:new t.UniformMatrix4f(e,r.u_label_plane_matrix),u_coord_matrix:new t.UniformMatrix4f(e,r.u_coord_matrix),u_is_text:new t.Uniform1i(e,r.u_is_text),u_pitch_with_map:new t.Uniform1i(e,r.u_pitch_with_map),u_texsize:new t.Uniform2f(e,r.u_texsize),u_texsize_icon:new t.Uniform2f(e,r.u_texsize_icon),u_texture:new t.Uniform1i(e,r.u_texture),u_texture_icon:new t.Uniform1i(e,r.u_texture_icon),u_gamma_scale:new t.Uniform1f(e,r.u_gamma_scale),u_device_pixel_ratio:new t.Uniform1f(e,r.u_device_pixel_ratio),u_is_halo:new t.Uniform1i(e,r.u_is_halo)}},background:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_opacity:new t.Uniform1f(e,r.u_opacity),u_color:new t.UniformColor(e,r.u_color)}},backgroundPattern:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_opacity:new t.Uniform1f(e,r.u_opacity),u_image:new t.Uniform1i(e,r.u_image),u_pattern_tl_a:new t.Uniform2f(e,r.u_pattern_tl_a),u_pattern_br_a:new t.Uniform2f(e,r.u_pattern_br_a),u_pattern_tl_b:new t.Uniform2f(e,r.u_pattern_tl_b),u_pattern_br_b:new t.Uniform2f(e,r.u_pattern_br_b),u_texsize:new t.Uniform2f(e,r.u_texsize),u_mix:new t.Uniform1f(e,r.u_mix),u_pattern_size_a:new t.Uniform2f(e,r.u_pattern_size_a),u_pattern_size_b:new t.Uniform2f(e,r.u_pattern_size_b),u_scale_a:new t.Uniform1f(e,r.u_scale_a),u_scale_b:new t.Uniform1f(e,r.u_scale_b),u_pixel_coord_upper:new t.Uniform2f(e,r.u_pixel_coord_upper),u_pixel_coord_lower:new t.Uniform2f(e,r.u_pixel_coord_lower),u_tile_units_to_pixels:new t.Uniform1f(e,r.u_tile_units_to_pixels)}}};function Kr(e,r,n,i,a,o,s){for(var l=e.context,c=l.gl,u=e.useProgram(\"collisionBox\"),f=[],h=0,p=0,d=0;d<i.length;d++){var m=i[d],g=r.getTile(m),v=g.getBucket(n);if(v){var y=m.posMatrix;0===a[0]&&0===a[1]||(y=e.translatePosMatrix(m.posMatrix,g,a,o));var x=s?v.textCollisionBox:v.iconCollisionBox,b=v.collisionCircleArray;if(b.length>0){var _=t.create(),w=y;t.mul(_,v.placementInvProjMatrix,e.transform.glCoordMatrix),t.mul(_,_,v.placementViewportMatrix),f.push({circleArray:b,circleOffset:p,transform:w,invTransform:_}),p=h+=b.length/4}x&&u.draw(l,c.LINES,At.disabled,Mt.disabled,e.colorModeForRenderPass(),Et.disabled,Cr(y,e.transform,g),n.id,x.layoutVertexBuffer,x.indexBuffer,x.segments,null,e.transform.zoom,null,null,x.collisionVertexBuffer)}}if(s&&f.length){var T=e.useProgram(\"collisionCircle\"),k=new t.StructArrayLayout2f1f2i16;k.resize(4*h),k._trim();for(var A=0,M=0,S=f;M<S.length;M+=1)for(var E=S[M],L=0;L<E.circleArray.length/4;L++){var C=4*L,P=E.circleArray[C+0],I=E.circleArray[C+1],O=E.circleArray[C+2],z=E.circleArray[C+3];k.emplace(A++,P,I,O,z,0),k.emplace(A++,P,I,O,z,1),k.emplace(A++,P,I,O,z,2),k.emplace(A++,P,I,O,z,3)}(!qr||qr.length<2*h)&&(qr=function(e){var r=2*e,n=new t.StructArrayLayout3ui6;n.resize(r),n._trim();for(var i=0;i<r;i++){var a=6*i;n.uint16[a+0]=4*i+0,n.uint16[a+1]=4*i+1,n.uint16[a+2]=4*i+2,n.uint16[a+3]=4*i+2,n.uint16[a+4]=4*i+3,n.uint16[a+5]=4*i+0}return n}(h));for(var D=l.createIndexBuffer(qr,!0),R=l.createVertexBuffer(k,t.collisionCircleLayout.members,!0),F=0,B=f;F<B.length;F+=1){var N=B[F],j=Pr(N.transform,N.invTransform,e.transform);T.draw(l,c.TRIANGLES,At.disabled,Mt.disabled,e.colorModeForRenderPass(),Et.disabled,j,n.id,R,D,t.SegmentVector.simpleSegment(0,2*N.circleOffset,N.circleArray.length,N.circleArray.length/2),null,e.transform.zoom,null,null,null)}R.destroy(),D.destroy()}}var Qr=t.identity(new Float32Array(16));function $r(e,r,n,i,a,o){var s=t.getAnchorAlignment(e),l=-(s.horizontalAlign-.5)*r,c=-(s.verticalAlign-.5)*n,u=t.evaluateVariableOffset(e,i);return new t.Point((l/a+u[0])*o,(c/a+u[1])*o)}function tn(e,r,n,i,a,o,s,l,c,u,f){var h=e.text.placedSymbolArray,p=e.text.dynamicLayoutVertexArray,d=e.icon.dynamicLayoutVertexArray,m={};p.clear();for(var g=0;g<h.length;g++){var v=h.get(g),y=e.allowVerticalPlacement&&!v.placedOrientation,x=v.hidden||!v.crossTileID||y?null:i[v.crossTileID];if(x){var b=new t.Point(v.anchorX,v.anchorY),_=te(b,n?l:s),w=ee(o.cameraToCenterDistance,_.signedDistanceFromCamera),T=a.evaluateSizeForFeature(e.textSizeData,u,v)*w/t.ONE_EM;n&&(T*=e.tilePixelRatio/c);for(var k=x.width,A=x.height,M=$r(x.anchor,k,A,x.textOffset,x.textBoxScale,T),S=n?te(b.add(M),s).point:_.point.add(r?M.rotate(-o.angle):M),E=e.allowVerticalPlacement&&v.placedOrientation===t.WritingMode.vertical?Math.PI/2:0,L=0;L<v.numGlyphs;L++)t.addDynamicAttributes(p,S,E);f&&v.associatedIconIndex>=0&&(m[v.associatedIconIndex]={shiftedAnchor:S,angle:E})}else ue(v.numGlyphs,p)}if(f){d.clear();for(var C=e.icon.placedSymbolArray,P=0;P<C.length;P++){var I=C.get(P);if(I.hidden)ue(I.numGlyphs,d);else{var O=m[P];if(O)for(var z=0;z<I.numGlyphs;z++)t.addDynamicAttributes(d,O.shiftedAnchor,O.angle);else ue(I.numGlyphs,d)}}e.icon.dynamicLayoutVertexBuffer.updateData(d)}e.text.dynamicLayoutVertexBuffer.updateData(p)}function en(t,e,r){return r.iconsInText&&e?\"symbolTextAndIcon\":t?\"symbolSDF\":\"symbolIcon\"}function rn(e,r,n,i,a,o,s,l,c,u,f,h){for(var p=e.context,d=p.gl,m=e.transform,g=\"map\"===l,v=\"map\"===c,y=g&&\"point\"!==n.layout.get(\"symbol-placement\"),x=g&&!v&&!y,b=void 0!==n.layout.get(\"symbol-sort-key\").constantOr(1),_=e.depthModeForSublayer(0,At.ReadOnly),w=n.layout.get(\"text-variable-anchor\"),T=[],k=0,A=i;k<A.length;k+=1){var M=A[k],S=r.getTile(M),E=S.getBucket(n);if(E){var L=a?E.text:E.icon;if(L&&L.segments.get().length){var C=L.programConfigurations.get(n.id),P=a||E.sdfIcons,I=a?E.textSizeData:E.iconSizeData,O=v||0!==m.pitch,z=e.useProgram(en(P,a,E),C),D=t.evaluateSizeForZoom(I,m.zoom),R=void 0,F=[0,0],B=void 0,N=void 0,j=null,U=void 0;if(a){if(B=S.glyphAtlasTexture,N=d.LINEAR,R=S.glyphAtlasTexture.size,E.iconsInText){F=S.imageAtlasTexture.size,j=S.imageAtlasTexture;var V=\"composite\"===I.kind||\"camera\"===I.kind;U=O||e.options.rotating||e.options.zooming||V?d.LINEAR:d.NEAREST}}else{var H=1!==n.layout.get(\"icon-size\").constantOr(0)||E.iconsNeedLinear;B=S.imageAtlasTexture,N=P||e.options.rotating||e.options.zooming||H||O?d.LINEAR:d.NEAREST,R=S.imageAtlasTexture.size}var q=pe(S,1,e.transform.zoom),G=Qt(M.posMatrix,v,g,e.transform,q),Y=$t(M.posMatrix,v,g,e.transform,q),W=w&&E.hasTextData(),X=\"none\"!==n.layout.get(\"icon-text-fit\")&&W&&E.hasIconData();y&&ne(E,M.posMatrix,e,a,G,Y,v,u);var Z=e.translatePosMatrix(M.posMatrix,S,o,s),J=y||a&&w||X?Qr:G,K=e.translatePosMatrix(Y,S,o,s,!0),Q=P&&0!==n.paint.get(a?\"text-halo-width\":\"icon-halo-width\").constantOr(1),$={program:z,buffers:L,uniformValues:P?E.iconsInText?Wr(I.kind,D,x,v,e,Z,J,K,R,F):Yr(I.kind,D,x,v,e,Z,J,K,a,R,!0):Gr(I.kind,D,x,v,e,Z,J,K,a,R),atlasTexture:B,atlasTextureIcon:j,atlasInterpolation:N,atlasInterpolationIcon:U,isSDF:P,hasHalo:Q};if(b)for(var tt=0,et=L.segments.get();tt<et.length;tt+=1){var rt=et[tt];T.push({segments:new t.SegmentVector([rt]),sortKey:rt.sortKey,state:$})}else T.push({segments:L.segments,sortKey:0,state:$})}}}b&&T.sort((function(t,e){return t.sortKey-e.sortKey}));for(var nt=0,it=T;nt<it.length;nt+=1){var at=it[nt],ot=at.state;if(p.activeTexture.set(d.TEXTURE0),ot.atlasTexture.bind(ot.atlasInterpolation,d.CLAMP_TO_EDGE),ot.atlasTextureIcon&&(p.activeTexture.set(d.TEXTURE1),ot.atlasTextureIcon&&ot.atlasTextureIcon.bind(ot.atlasInterpolationIcon,d.CLAMP_TO_EDGE)),ot.isSDF){var st=ot.uniformValues;ot.hasHalo&&(st.u_is_halo=1,nn(ot.buffers,at.segments,n,e,ot.program,_,f,h,st)),st.u_is_halo=0}nn(ot.buffers,at.segments,n,e,ot.program,_,f,h,ot.uniformValues)}}function nn(t,e,r,n,i,a,o,s,l){var c=n.context,u=c.gl;i.draw(c,u.TRIANGLES,a,o,s,Et.disabled,l,r.id,t.layoutVertexBuffer,t.indexBuffer,e,r.paint,n.transform.zoom,t.programConfigurations.get(r.id),t.dynamicLayoutVertexBuffer,t.opacityVertexBuffer)}function an(t,e,r,n,i,a,o){var s,l,c,u,f,h=t.context.gl,p=r.paint.get(\"fill-pattern\"),d=p&&p.constantOr(1),m=r.getCrossfadeParameters();o?(l=d&&!r.getPaintProperty(\"fill-outline-color\")?\"fillOutlinePattern\":\"fillOutline\",s=h.LINES):(l=d?\"fillPattern\":\"fill\",s=h.TRIANGLES);for(var g=0,v=n;g<v.length;g+=1){var y=v[g],x=e.getTile(y);if(!d||x.patternsLoaded()){var b=x.getBucket(r);if(b){var _=b.programConfigurations.get(r.id),w=t.useProgram(l,_);d&&(t.context.activeTexture.set(h.TEXTURE0),x.imageAtlasTexture.bind(h.LINEAR,h.CLAMP_TO_EDGE),_.updatePaintBuffers(m));var T=p.constantOr(null);if(T&&x.imageAtlas){var k=x.imageAtlas,A=k.patternPositions[T.to.toString()],M=k.patternPositions[T.from.toString()];A&&M&&_.setConstantPatternPositions(A,M)}var S=t.translatePosMatrix(y.posMatrix,x,r.paint.get(\"fill-translate\"),r.paint.get(\"fill-translate-anchor\"));if(o){u=b.indexBuffer2,f=b.segments2;var E=[h.drawingBufferWidth,h.drawingBufferHeight];c=\"fillOutlinePattern\"===l&&d?Er(S,t,m,x,E):Sr(S,E)}else u=b.indexBuffer,f=b.segments,c=d?Mr(S,t,m,x):Ar(S);w.draw(t.context,s,i,t.stencilModeForClipping(y),a,Et.disabled,c,r.id,b.layoutVertexBuffer,u,f,r.paint,t.transform.zoom,_)}}}}function on(t,e,r,n,i,a,o){for(var s=t.context,l=s.gl,c=r.paint.get(\"fill-extrusion-pattern\"),u=c.constantOr(1),f=r.getCrossfadeParameters(),h=r.paint.get(\"fill-extrusion-opacity\"),p=0,d=n;p<d.length;p+=1){var m=d[p],g=e.getTile(m),v=g.getBucket(r);if(v){var y=v.programConfigurations.get(r.id),x=t.useProgram(u?\"fillExtrusionPattern\":\"fillExtrusion\",y);u&&(t.context.activeTexture.set(l.TEXTURE0),g.imageAtlasTexture.bind(l.LINEAR,l.CLAMP_TO_EDGE),y.updatePaintBuffers(f));var b=c.constantOr(null);if(b&&g.imageAtlas){var _=g.imageAtlas,w=_.patternPositions[b.to.toString()],T=_.patternPositions[b.from.toString()];w&&T&&y.setConstantPatternPositions(w,T)}var k=t.translatePosMatrix(m.posMatrix,g,r.paint.get(\"fill-extrusion-translate\"),r.paint.get(\"fill-extrusion-translate-anchor\")),A=r.paint.get(\"fill-extrusion-vertical-gradient\"),M=u?kr(k,t,A,h,m,f,g):Tr(k,t,A,h);x.draw(s,s.gl.TRIANGLES,i,a,o,Et.backCCW,M,r.id,v.layoutVertexBuffer,v.indexBuffer,v.segments,r.paint,t.transform.zoom,y)}}}function sn(t,e,r,n,i,a){var o=t.context,s=o.gl,l=e.fbo;if(l){var c=t.useProgram(\"hillshade\");o.activeTexture.set(s.TEXTURE0),s.bindTexture(s.TEXTURE_2D,l.colorAttachment.get());var u=function(t,e,r){var n=r.paint.get(\"hillshade-shadow-color\"),i=r.paint.get(\"hillshade-highlight-color\"),a=r.paint.get(\"hillshade-accent-color\"),o=r.paint.get(\"hillshade-illumination-direction\")*(Math.PI/180);\"viewport\"===r.paint.get(\"hillshade-illumination-anchor\")&&(o-=t.transform.angle);var s=!t.options.moving;return{u_matrix:t.transform.calculatePosMatrix(e.tileID.toUnwrapped(),s),u_image:0,u_latrange:Dr(t,e.tileID),u_light:[r.paint.get(\"hillshade-exaggeration\"),o],u_shadow:n,u_highlight:i,u_accent:a}}(t,e,r);c.draw(o,s.TRIANGLES,n,i,a,Et.disabled,u,r.id,t.rasterBoundsBuffer,t.quadTriangleIndexBuffer,t.rasterBoundsSegments)}}function ln(e,r,n,i,a,o,s){var l=e.context,c=l.gl,u=r.dem;if(u&&u.data){var f=u.dim,h=u.stride,p=u.getPixels();if(l.activeTexture.set(c.TEXTURE1),l.pixelStoreUnpackPremultiplyAlpha.set(!1),r.demTexture=r.demTexture||e.getTileTexture(h),r.demTexture){var d=r.demTexture;d.update(p,{premultiply:!1}),d.bind(c.NEAREST,c.CLAMP_TO_EDGE)}else r.demTexture=new t.Texture(l,p,c.RGBA,{premultiply:!1}),r.demTexture.bind(c.NEAREST,c.CLAMP_TO_EDGE);l.activeTexture.set(c.TEXTURE0);var m=r.fbo;if(!m){var g=new t.Texture(l,{width:f,height:f,data:null},c.RGBA);g.bind(c.LINEAR,c.CLAMP_TO_EDGE),(m=r.fbo=l.createFramebuffer(f,f,!0)).colorAttachment.set(g.texture)}l.bindFramebuffer.set(m.framebuffer),l.viewport.set([0,0,f,f]),e.useProgram(\"hillshadePrepare\").draw(l,c.TRIANGLES,a,o,s,Et.disabled,function(e,r,n){var i=r.stride,a=t.create();return t.ortho(a,0,t.EXTENT,-t.EXTENT,0,0,1),t.translate(a,a,[0,-t.EXTENT,0]),{u_matrix:a,u_image:1,u_dimension:[i,i],u_zoom:e.overscaledZ,u_maxzoom:n,u_unpack:r.getUnpackVector()}}(r.tileID,u,i),n.id,e.rasterBoundsBuffer,e.quadTriangleIndexBuffer,e.rasterBoundsSegments),r.needsHillshadePrepare=!1}}function cn(e,r,n,i,a){var o=i.paint.get(\"raster-fade-duration\");if(o>0){var s=t.browser.now(),l=(s-e.timeAdded)/o,c=r?(s-r.timeAdded)/o:-1,u=n.getSource(),f=a.coveringZoomLevel({tileSize:u.tileSize,roundZoom:u.roundZoom}),h=!r||Math.abs(r.tileID.overscaledZ-f)>Math.abs(e.tileID.overscaledZ-f),p=h&&e.refreshedUponExpiration?1:t.clamp(h?l:1-c,0,1);return e.refreshedUponExpiration&&l>=1&&(e.refreshedUponExpiration=!1),r?{opacity:1,mix:1-p}:{opacity:p,mix:0}}return{opacity:1,mix:0}}var un=new t.Color(1,0,0,1),fn=new t.Color(0,1,0,1),hn=new t.Color(0,0,1,1),pn=new t.Color(1,0,1,1),dn=new t.Color(0,1,1,1);function mn(t){var e=t.transform.padding;gn(t,t.transform.height-(e.top||0),3,un),gn(t,e.bottom||0,3,fn),vn(t,e.left||0,3,hn),vn(t,t.transform.width-(e.right||0),3,pn);var r=t.transform.centerPoint;!function(t,e,r,n){yn(t,e-1,r-10,2,20,n),yn(t,e-10,r-1,20,2,n)}(t,r.x,t.transform.height-r.y,dn)}function gn(t,e,r,n){yn(t,0,e+r/2,t.transform.width,r,n)}function vn(t,e,r,n){yn(t,e-r/2,0,r,t.transform.height,n)}function yn(e,r,n,i,a,o){var s=e.context,l=s.gl;l.enable(l.SCISSOR_TEST),l.scissor(r*t.browser.devicePixelRatio,n*t.browser.devicePixelRatio,i*t.browser.devicePixelRatio,a*t.browser.devicePixelRatio),s.clear({color:o}),l.disable(l.SCISSOR_TEST)}function xn(e,r,n){var i=e.context,a=i.gl,o=n.posMatrix,s=e.useProgram(\"debug\"),l=At.disabled,c=Mt.disabled,u=e.colorModeForRenderPass();i.activeTexture.set(a.TEXTURE0),e.emptyTexture.bind(a.LINEAR,a.CLAMP_TO_EDGE),s.draw(i,a.LINE_STRIP,l,c,u,Et.disabled,Ir(o,t.Color.red),\"$debug\",e.debugBuffer,e.tileBorderIndexBuffer,e.debugSegments);var f=r.getTileByID(n.key).latestRawTileData,h=f&&f.byteLength||0,p=Math.floor(h/1024),d=r.getTile(n).tileSize,m=512/Math.min(d,512)*(n.overscaledZ/e.transform.zoom)*.5,g=n.canonical.toString();n.overscaledZ!==n.canonical.z&&(g+=\" => \"+n.overscaledZ),function(t,e){t.initDebugOverlayCanvas();var r=t.debugOverlayCanvas,n=t.context.gl,i=t.debugOverlayCanvas.getContext(\"2d\");i.clearRect(0,0,r.width,r.height),i.shadowColor=\"white\",i.shadowBlur=2,i.lineWidth=1.5,i.strokeStyle=\"white\",i.textBaseline=\"top\",i.font=\"bold 36px Open Sans, sans-serif\",i.fillText(e,5,5),i.strokeText(e,5,5),t.debugOverlayTexture.update(r),t.debugOverlayTexture.bind(n.LINEAR,n.CLAMP_TO_EDGE)}(e,g+\" \"+p+\"kb\"),s.draw(i,a.TRIANGLES,l,c,St.alphaBlended,Et.disabled,Ir(o,t.Color.transparent,m),\"$debug\",e.debugBuffer,e.quadTriangleIndexBuffer,e.debugSegments)}var bn={symbol:function(e,r,n,i,a){if(\"translucent\"===e.renderPass){var o=Mt.disabled,s=e.colorModeForRenderPass();n.layout.get(\"text-variable-anchor\")&&function(e,r,n,i,a,o,s){for(var l=r.transform,c=\"map\"===a,u=\"map\"===o,f=0,h=e;f<h.length;f+=1){var p=h[f],d=i.getTile(p),m=d.getBucket(n);if(m&&m.text&&m.text.segments.get().length){var g=m.textSizeData,v=t.evaluateSizeForZoom(g,l.zoom),y=pe(d,1,r.transform.zoom),x=Qt(p.posMatrix,u,c,r.transform,y),b=\"none\"!==n.layout.get(\"icon-text-fit\")&&m.hasIconData();if(v){var _=Math.pow(2,l.zoom-d.tileID.overscaledZ);tn(m,c,u,s,t.symbolSize,l,x,p.posMatrix,_,v,b)}}}}(i,e,n,r,n.layout.get(\"text-rotation-alignment\"),n.layout.get(\"text-pitch-alignment\"),a),0!==n.paint.get(\"icon-opacity\").constantOr(1)&&rn(e,r,n,i,!1,n.paint.get(\"icon-translate\"),n.paint.get(\"icon-translate-anchor\"),n.layout.get(\"icon-rotation-alignment\"),n.layout.get(\"icon-pitch-alignment\"),n.layout.get(\"icon-keep-upright\"),o,s),0!==n.paint.get(\"text-opacity\").constantOr(1)&&rn(e,r,n,i,!0,n.paint.get(\"text-translate\"),n.paint.get(\"text-translate-anchor\"),n.layout.get(\"text-rotation-alignment\"),n.layout.get(\"text-pitch-alignment\"),n.layout.get(\"text-keep-upright\"),o,s),r.map.showCollisionBoxes&&(Kr(e,r,n,i,n.paint.get(\"text-translate\"),n.paint.get(\"text-translate-anchor\"),!0),Kr(e,r,n,i,n.paint.get(\"icon-translate\"),n.paint.get(\"icon-translate-anchor\"),!1))}},circle:function(e,r,n,i){if(\"translucent\"===e.renderPass){var a=n.paint.get(\"circle-opacity\"),o=n.paint.get(\"circle-stroke-width\"),s=n.paint.get(\"circle-stroke-opacity\"),l=void 0!==n.layout.get(\"circle-sort-key\").constantOr(1);if(0!==a.constantOr(1)||0!==o.constantOr(1)&&0!==s.constantOr(1)){for(var c=e.context,u=c.gl,f=e.depthModeForSublayer(0,At.ReadOnly),h=Mt.disabled,p=e.colorModeForRenderPass(),d=[],m=0;m<i.length;m++){var g=i[m],v=r.getTile(g),y=v.getBucket(n);if(y){var x=y.programConfigurations.get(n.id),b={programConfiguration:x,program:e.useProgram(\"circle\",x),layoutVertexBuffer:y.layoutVertexBuffer,indexBuffer:y.indexBuffer,uniformValues:Lr(e,g,v,n)};if(l)for(var _=0,w=y.segments.get();_<w.length;_+=1){var T=w[_];d.push({segments:new t.SegmentVector([T]),sortKey:T.sortKey,state:b})}else d.push({segments:y.segments,sortKey:0,state:b})}}l&&d.sort((function(t,e){return t.sortKey-e.sortKey}));for(var k=0,A=d;k<A.length;k+=1){var M=A[k],S=M.state,E=S.programConfiguration,L=S.program,C=S.layoutVertexBuffer,P=S.indexBuffer,I=S.uniformValues,O=M.segments;L.draw(c,u.TRIANGLES,f,h,p,Et.disabled,I,n.id,C,P,O,n.paint,e.transform.zoom,E)}}}},heatmap:function(e,r,n,i){if(0!==n.paint.get(\"heatmap-opacity\"))if(\"offscreen\"===e.renderPass){var a=e.context,o=a.gl,s=Mt.disabled,l=new St([o.ONE,o.ONE],t.Color.transparent,[!0,!0,!0,!0]);!function(t,e,r){var n=t.gl;t.activeTexture.set(n.TEXTURE1),t.viewport.set([0,0,e.width/4,e.height/4]);var i=r.heatmapFbo;if(i)n.bindTexture(n.TEXTURE_2D,i.colorAttachment.get()),t.bindFramebuffer.set(i.framebuffer);else{var a=n.createTexture();n.bindTexture(n.TEXTURE_2D,a),n.texParameteri(n.TEXTURE_2D,n.TEXTURE_WRAP_S,n.CLAMP_TO_EDGE),n.texParameteri(n.TEXTURE_2D,n.TEXTURE_WRAP_T,n.CLAMP_TO_EDGE),n.texParameteri(n.TEXTURE_2D,n.TEXTURE_MIN_FILTER,n.LINEAR),n.texParameteri(n.TEXTURE_2D,n.TEXTURE_MAG_FILTER,n.LINEAR),i=r.heatmapFbo=t.createFramebuffer(e.width/4,e.height/4,!1),function(t,e,r,n){var i=t.gl,a=t.extRenderToTextureHalfFloat?t.extTextureHalfFloat.HALF_FLOAT_OES:i.UNSIGNED_BYTE;i.texImage2D(i.TEXTURE_2D,0,i.RGBA,e.width/4,e.height/4,0,i.RGBA,a,null),n.colorAttachment.set(r)}(t,e,a,i)}}(a,e,n),a.clear({color:t.Color.transparent});for(var c=0;c<i.length;c++){var u=i[c];if(!r.hasRenderableParent(u)){var f=r.getTile(u),h=f.getBucket(n);if(h){var p=h.programConfigurations.get(n.id),d=e.useProgram(\"heatmap\",p),m=e.transform.zoom;d.draw(a,o.TRIANGLES,At.disabled,s,l,Et.disabled,zr(u.posMatrix,f,m,n.paint.get(\"heatmap-intensity\")),n.id,h.layoutVertexBuffer,h.indexBuffer,h.segments,n.paint,e.transform.zoom,p)}}}a.viewport.set([0,0,e.width,e.height])}else\"translucent\"===e.renderPass&&(e.context.setColorMode(e.colorModeForRenderPass()),function(e,r){var n=e.context,i=n.gl,a=r.heatmapFbo;if(!a)return;n.activeTexture.set(i.TEXTURE0),i.bindTexture(i.TEXTURE_2D,a.colorAttachment.get()),n.activeTexture.set(i.TEXTURE1);var o=r.colorRampTexture;o||(o=r.colorRampTexture=new t.Texture(n,r.colorRamp,i.RGBA));o.bind(i.LINEAR,i.CLAMP_TO_EDGE),e.useProgram(\"heatmapTexture\").draw(n,i.TRIANGLES,At.disabled,Mt.disabled,e.colorModeForRenderPass(),Et.disabled,function(e,r,n,i){var a=t.create();t.ortho(a,0,e.width,e.height,0,0,1);var o=e.context.gl;return{u_matrix:a,u_world:[o.drawingBufferWidth,o.drawingBufferHeight],u_image:n,u_color_ramp:i,u_opacity:r.paint.get(\"heatmap-opacity\")}}(e,r,0,1),r.id,e.viewportBuffer,e.quadTriangleIndexBuffer,e.viewportSegments,r.paint,e.transform.zoom)}(e,n))},line:function(e,r,n,i){if(\"translucent\"===e.renderPass){var a=n.paint.get(\"line-opacity\"),o=n.paint.get(\"line-width\");if(0!==a.constantOr(1)&&0!==o.constantOr(1)){var s=e.depthModeForSublayer(0,At.ReadOnly),l=e.colorModeForRenderPass(),c=n.paint.get(\"line-dasharray\"),u=n.paint.get(\"line-pattern\"),f=u.constantOr(1),h=n.paint.get(\"line-gradient\"),p=n.getCrossfadeParameters(),d=f?\"linePattern\":c?\"lineSDF\":h?\"lineGradient\":\"line\",m=e.context,g=m.gl,v=!0;if(h){m.activeTexture.set(g.TEXTURE0);var y=n.gradientTexture;if(!n.gradient)return;y||(y=n.gradientTexture=new t.Texture(m,n.gradient,g.RGBA)),y.bind(g.LINEAR,g.CLAMP_TO_EDGE)}for(var x=0,b=i;x<b.length;x+=1){var _=b[x],w=r.getTile(_);if(!f||w.patternsLoaded()){var T=w.getBucket(n);if(T){var k=T.programConfigurations.get(n.id),A=e.context.program.get(),M=e.useProgram(d,k),S=v||M.program!==A,E=u.constantOr(null);if(E&&w.imageAtlas){var L=w.imageAtlas,C=L.patternPositions[E.to.toString()],P=L.patternPositions[E.from.toString()];C&&P&&k.setConstantPatternPositions(C,P)}var I=f?Br(e,w,n,p):c?Nr(e,w,n,c,p):h?Fr(e,w,n):Rr(e,w,n);f?(m.activeTexture.set(g.TEXTURE0),w.imageAtlasTexture.bind(g.LINEAR,g.CLAMP_TO_EDGE),k.updatePaintBuffers(p)):c&&(S||e.lineAtlas.dirty)&&(m.activeTexture.set(g.TEXTURE0),e.lineAtlas.bind(m)),M.draw(m,g.TRIANGLES,s,e.stencilModeForClipping(_),l,Et.disabled,I,n.id,T.layoutVertexBuffer,T.indexBuffer,T.segments,n.paint,e.transform.zoom,k),v=!1}}}}}},fill:function(e,r,n,i){var a=n.paint.get(\"fill-color\"),o=n.paint.get(\"fill-opacity\");if(0!==o.constantOr(1)){var s=e.colorModeForRenderPass(),l=n.paint.get(\"fill-pattern\"),c=e.opaquePassEnabledForLayer()&&!l.constantOr(1)&&1===a.constantOr(t.Color.transparent).a&&1===o.constantOr(0)?\"opaque\":\"translucent\";if(e.renderPass===c){var u=e.depthModeForSublayer(1,\"opaque\"===e.renderPass?At.ReadWrite:At.ReadOnly);an(e,r,n,i,u,s,!1)}if(\"translucent\"===e.renderPass&&n.paint.get(\"fill-antialias\")){var f=e.depthModeForSublayer(n.getPaintProperty(\"fill-outline-color\")?2:0,At.ReadOnly);an(e,r,n,i,f,s,!0)}}},\"fill-extrusion\":function(t,e,r,n){var i=r.paint.get(\"fill-extrusion-opacity\");if(0!==i&&\"translucent\"===t.renderPass){var a=new At(t.context.gl.LEQUAL,At.ReadWrite,t.depthRangeFor3D);if(1!==i||r.paint.get(\"fill-extrusion-pattern\").constantOr(1))on(t,e,r,n,a,Mt.disabled,St.disabled),on(t,e,r,n,a,t.stencilModeFor3D(),t.colorModeForRenderPass());else{var o=t.colorModeForRenderPass();on(t,e,r,n,a,Mt.disabled,o)}}},hillshade:function(t,e,r,n){if(\"offscreen\"===t.renderPass||\"translucent\"===t.renderPass){for(var i=t.context,a=e.getSource().maxzoom,o=t.depthModeForSublayer(0,At.ReadOnly),s=t.colorModeForRenderPass(),l=\"translucent\"===t.renderPass?t.stencilConfigForOverlap(n):[{},n],c=l[0],u=0,f=l[1];u<f.length;u+=1){var h=f[u],p=e.getTile(h);p.needsHillshadePrepare&&\"offscreen\"===t.renderPass?ln(t,p,r,a,o,Mt.disabled,s):\"translucent\"===t.renderPass&&sn(t,p,r,o,c[h.overscaledZ],s)}i.viewport.set([0,0,t.width,t.height])}},raster:function(t,e,r,n){if(\"translucent\"===t.renderPass&&0!==r.paint.get(\"raster-opacity\")&&n.length)for(var i=t.context,a=i.gl,o=e.getSource(),s=t.useProgram(\"raster\"),l=t.colorModeForRenderPass(),c=o instanceof I?[{},n]:t.stencilConfigForOverlap(n),u=c[0],f=c[1],h=f[f.length-1].overscaledZ,p=!t.options.moving,d=0,m=f;d<m.length;d+=1){var g=m[d],v=t.depthModeForSublayer(g.overscaledZ-h,1===r.paint.get(\"raster-opacity\")?At.ReadWrite:At.ReadOnly,a.LESS),y=e.getTile(g),x=t.transform.calculatePosMatrix(g.toUnwrapped(),p);y.registerFadeDuration(r.paint.get(\"raster-fade-duration\"));var b=e.findLoadedParent(g,0),_=cn(y,b,e,r,t.transform),w=void 0,T=void 0,k=\"nearest\"===r.paint.get(\"raster-resampling\")?a.NEAREST:a.LINEAR;i.activeTexture.set(a.TEXTURE0),y.texture.bind(k,a.CLAMP_TO_EDGE,a.LINEAR_MIPMAP_NEAREST),i.activeTexture.set(a.TEXTURE1),b?(b.texture.bind(k,a.CLAMP_TO_EDGE,a.LINEAR_MIPMAP_NEAREST),w=Math.pow(2,b.tileID.overscaledZ-y.tileID.overscaledZ),T=[y.tileID.canonical.x*w%1,y.tileID.canonical.y*w%1]):y.texture.bind(k,a.CLAMP_TO_EDGE,a.LINEAR_MIPMAP_NEAREST);var A=Vr(x,T||[0,0],w||1,_,r);o instanceof I?s.draw(i,a.TRIANGLES,v,Mt.disabled,l,Et.disabled,A,r.id,o.boundsBuffer,t.quadTriangleIndexBuffer,o.boundsSegments):s.draw(i,a.TRIANGLES,v,u[g.overscaledZ],l,Et.disabled,A,r.id,t.rasterBoundsBuffer,t.quadTriangleIndexBuffer,t.rasterBoundsSegments)}},background:function(t,e,r){var n=r.paint.get(\"background-color\"),i=r.paint.get(\"background-opacity\");if(0!==i){var a=t.context,o=a.gl,s=t.transform,l=s.tileSize,c=r.paint.get(\"background-pattern\");if(!t.isPatternMissing(c)){var u=!c&&1===n.a&&1===i&&t.opaquePassEnabledForLayer()?\"opaque\":\"translucent\";if(t.renderPass===u){var f=Mt.disabled,h=t.depthModeForSublayer(0,\"opaque\"===u?At.ReadWrite:At.ReadOnly),p=t.colorModeForRenderPass(),d=t.useProgram(c?\"backgroundPattern\":\"background\"),m=s.coveringTiles({tileSize:l});c&&(a.activeTexture.set(o.TEXTURE0),t.imageManager.bind(t.context));for(var g=r.getCrossfadeParameters(),v=0,y=m;v<y.length;v+=1){var x=y[v],b=t.transform.calculatePosMatrix(x.toUnwrapped()),_=c?Zr(b,i,t,c,{tileID:x,tileSize:l},g):Xr(b,i,n);d.draw(a,o.TRIANGLES,h,f,p,Et.disabled,_,r.id,t.tileExtentBuffer,t.quadTriangleIndexBuffer,t.tileExtentSegments)}}}}},debug:function(t,e,r){for(var n=0;n<r.length;n++)xn(t,e,r[n])},custom:function(t,e,r){var n=t.context,i=r.implementation;if(\"offscreen\"===t.renderPass){var a=i.prerender;a&&(t.setCustomLayerDefaults(),n.setColorMode(t.colorModeForRenderPass()),a.call(i,n.gl,t.transform.customLayerMatrix()),n.setDirty(),t.setBaseState())}else if(\"translucent\"===t.renderPass){t.setCustomLayerDefaults(),n.setColorMode(t.colorModeForRenderPass()),n.setStencilMode(Mt.disabled);var o=\"3d\"===i.renderingMode?new At(t.context.gl.LEQUAL,At.ReadWrite,t.depthRangeFor3D):t.depthModeForSublayer(0,At.ReadOnly);n.setDepthMode(o),i.render(n.gl,t.transform.customLayerMatrix()),n.setDirty(),t.setBaseState(),n.bindFramebuffer.set(null)}}},_n=function(t,e){this.context=new Lt(t),this.transform=e,this._tileTextures={},this.setup(),this.numSublayers=Ct.maxUnderzooming+Ct.maxOverzooming+1,this.depthEpsilon=1/Math.pow(2,16),this.crossTileSymbolIndex=new Ne,this.gpuTimers={}};_n.prototype.resize=function(e,r){if(this.width=e*t.browser.devicePixelRatio,this.height=r*t.browser.devicePixelRatio,this.context.viewport.set([0,0,this.width,this.height]),this.style)for(var n=0,i=this.style._order;n<i.length;n+=1){var a=i[n];this.style._layers[a].resize()}},_n.prototype.setup=function(){var e=this.context,r=new t.StructArrayLayout2i4;r.emplaceBack(0,0),r.emplaceBack(t.EXTENT,0),r.emplaceBack(0,t.EXTENT),r.emplaceBack(t.EXTENT,t.EXTENT),this.tileExtentBuffer=e.createVertexBuffer(r,Ge.members),this.tileExtentSegments=t.SegmentVector.simpleSegment(0,0,4,2);var n=new t.StructArrayLayout2i4;n.emplaceBack(0,0),n.emplaceBack(t.EXTENT,0),n.emplaceBack(0,t.EXTENT),n.emplaceBack(t.EXTENT,t.EXTENT),this.debugBuffer=e.createVertexBuffer(n,Ge.members),this.debugSegments=t.SegmentVector.simpleSegment(0,0,4,5);var i=new t.StructArrayLayout4i8;i.emplaceBack(0,0,0,0),i.emplaceBack(t.EXTENT,0,t.EXTENT,0),i.emplaceBack(0,t.EXTENT,0,t.EXTENT),i.emplaceBack(t.EXTENT,t.EXTENT,t.EXTENT,t.EXTENT),this.rasterBoundsBuffer=e.createVertexBuffer(i,P.members),this.rasterBoundsSegments=t.SegmentVector.simpleSegment(0,0,4,2);var a=new t.StructArrayLayout2i4;a.emplaceBack(0,0),a.emplaceBack(1,0),a.emplaceBack(0,1),a.emplaceBack(1,1),this.viewportBuffer=e.createVertexBuffer(a,Ge.members),this.viewportSegments=t.SegmentVector.simpleSegment(0,0,4,2);var o=new t.StructArrayLayout1ui2;o.emplaceBack(0),o.emplaceBack(1),o.emplaceBack(3),o.emplaceBack(2),o.emplaceBack(0),this.tileBorderIndexBuffer=e.createIndexBuffer(o);var s=new t.StructArrayLayout3ui6;s.emplaceBack(0,1,2),s.emplaceBack(2,1,3),this.quadTriangleIndexBuffer=e.createIndexBuffer(s),this.emptyTexture=new t.Texture(e,{width:1,height:1,data:new Uint8Array([0,0,0,0])},e.gl.RGBA);var l=this.context.gl;this.stencilClearMode=new Mt({func:l.ALWAYS,mask:0},0,255,l.ZERO,l.ZERO,l.ZERO)},_n.prototype.clearStencil=function(){var e=this.context,r=e.gl;this.nextStencilID=1,this.currentStencilSource=void 0;var n=t.create();t.ortho(n,0,this.width,this.height,0,0,1),t.scale(n,n,[r.drawingBufferWidth,r.drawingBufferHeight,0]),this.useProgram(\"clippingMask\").draw(e,r.TRIANGLES,At.disabled,this.stencilClearMode,St.disabled,Et.disabled,Or(n),\"$clipping\",this.viewportBuffer,this.quadTriangleIndexBuffer,this.viewportSegments)},_n.prototype._renderTileClippingMasks=function(t,e){if(this.currentStencilSource!==t.source&&t.isTileClipped()&&e&&e.length){this.currentStencilSource=t.source;var r=this.context,n=r.gl;this.nextStencilID+e.length>256&&this.clearStencil(),r.setColorMode(St.disabled),r.setDepthMode(At.disabled);var i=this.useProgram(\"clippingMask\");this._tileClippingMaskIDs={};for(var a=0,o=e;a<o.length;a+=1){var s=o[a],l=this._tileClippingMaskIDs[s.key]=this.nextStencilID++;i.draw(r,n.TRIANGLES,At.disabled,new Mt({func:n.ALWAYS,mask:0},l,255,n.KEEP,n.KEEP,n.REPLACE),St.disabled,Et.disabled,Or(s.posMatrix),\"$clipping\",this.tileExtentBuffer,this.quadTriangleIndexBuffer,this.tileExtentSegments)}}},_n.prototype.stencilModeFor3D=function(){this.currentStencilSource=void 0,this.nextStencilID+1>256&&this.clearStencil();var t=this.nextStencilID++,e=this.context.gl;return new Mt({func:e.NOTEQUAL,mask:255},t,255,e.KEEP,e.KEEP,e.REPLACE)},_n.prototype.stencilModeForClipping=function(t){var e=this.context.gl;return new Mt({func:e.EQUAL,mask:255},this._tileClippingMaskIDs[t.key],0,e.KEEP,e.KEEP,e.REPLACE)},_n.prototype.stencilConfigForOverlap=function(t){var e,r=this.context.gl,n=t.sort((function(t,e){return e.overscaledZ-t.overscaledZ})),i=n[n.length-1].overscaledZ,a=n[0].overscaledZ-i+1;if(a>1){this.currentStencilSource=void 0,this.nextStencilID+a>256&&this.clearStencil();for(var o={},s=0;s<a;s++)o[s+i]=new Mt({func:r.GEQUAL,mask:255},s+this.nextStencilID,255,r.KEEP,r.KEEP,r.REPLACE);return this.nextStencilID+=a,[o,n]}return[(e={},e[i]=Mt.disabled,e),n]},_n.prototype.colorModeForRenderPass=function(){var e=this.context.gl;if(this._showOverdrawInspector){return new St([e.CONSTANT_COLOR,e.ONE],new t.Color(1/8,1/8,1/8,0),[!0,!0,!0,!0])}return\"opaque\"===this.renderPass?St.unblended:St.alphaBlended},_n.prototype.depthModeForSublayer=function(t,e,r){if(!this.opaquePassEnabledForLayer())return At.disabled;var n=1-((1+this.currentLayer)*this.numSublayers+t)*this.depthEpsilon;return new At(r||this.context.gl.LEQUAL,e,[n,n])},_n.prototype.opaquePassEnabledForLayer=function(){return this.currentLayer<this.opaquePassCutoff},_n.prototype.render=function(e,r){var n=this;this.style=e,this.options=r,this.lineAtlas=e.lineAtlas,this.imageManager=e.imageManager,this.glyphManager=e.glyphManager,this.symbolFadeChange=e.placement.symbolFadeChange(t.browser.now()),this.imageManager.beginFrame();var i=this.style._order,a=this.style.sourceCaches;for(var o in a){var s=a[o];s.used&&s.prepare(this.context)}var l,c,u={},f={},h={};for(var p in a){var d=a[p];u[p]=d.getVisibleCoordinates(),f[p]=u[p].slice().reverse(),h[p]=d.getVisibleCoordinates(!0).reverse()}this.opaquePassCutoff=1/0;for(var m=0;m<i.length;m++){var g=i[m];if(this.style._layers[g].is3D()){this.opaquePassCutoff=m;break}}this.renderPass=\"offscreen\";for(var v=0,y=i;v<y.length;v+=1){var x=y[v],b=this.style._layers[x];if(b.hasOffscreenPass()&&!b.isHidden(this.transform.zoom)){var _=f[b.source];(\"custom\"===b.type||_.length)&&this.renderLayer(this,a[b.source],b,_)}}for(this.context.bindFramebuffer.set(null),this.context.clear({color:r.showOverdrawInspector?t.Color.black:t.Color.transparent,depth:1}),this.clearStencil(),this._showOverdrawInspector=r.showOverdrawInspector,this.depthRangeFor3D=[0,1-(e._order.length+2)*this.numSublayers*this.depthEpsilon],this.renderPass=\"opaque\",this.currentLayer=i.length-1;this.currentLayer>=0;this.currentLayer--){var w=this.style._layers[i[this.currentLayer]],T=a[w.source],k=u[w.source];this._renderTileClippingMasks(w,k),this.renderLayer(this,T,w,k)}for(this.renderPass=\"translucent\",this.currentLayer=0;this.currentLayer<i.length;this.currentLayer++){var A=this.style._layers[i[this.currentLayer]],M=a[A.source],S=(\"symbol\"===A.type?h:f)[A.source];this._renderTileClippingMasks(A,u[A.source]),this.renderLayer(this,M,A,S)}this.options.showTileBoundaries&&(t.values(this.style._layers).forEach((function(t){t.source&&!t.isHidden(n.transform.zoom)&&(t.source!==(c&&c.id)&&(c=n.style.sourceCaches[t.source]),(!l||l.getSource().maxzoom<c.getSource().maxzoom)&&(l=c))})),l&&bn.debug(this,l,l.getVisibleCoordinates()));this.options.showPadding&&mn(this),this.context.setDefault()},_n.prototype.renderLayer=function(t,e,r,n){r.isHidden(this.transform.zoom)||(\"background\"===r.type||\"custom\"===r.type||n.length)&&(this.id=r.id,this.gpuTimingStart(r),bn[r.type](t,e,r,n,this.style.placement.variableOffsets),this.gpuTimingEnd())},_n.prototype.gpuTimingStart=function(t){if(this.options.gpuTiming){var e=this.context.extTimerQuery,r=this.gpuTimers[t.id];r||(r=this.gpuTimers[t.id]={calls:0,cpuTime:0,query:e.createQueryEXT()}),r.calls++,e.beginQueryEXT(e.TIME_ELAPSED_EXT,r.query)}},_n.prototype.gpuTimingEnd=function(){if(this.options.gpuTiming){var t=this.context.extTimerQuery;t.endQueryEXT(t.TIME_ELAPSED_EXT)}},_n.prototype.collectGpuTimers=function(){var t=this.gpuTimers;return this.gpuTimers={},t},_n.prototype.queryGpuTimers=function(t){var e={};for(var r in t){var n=t[r],i=this.context.extTimerQuery,a=i.getQueryObjectEXT(n.query,i.QUERY_RESULT_EXT)/1e6;i.deleteQueryEXT(n.query),e[r]=a}return e},_n.prototype.translatePosMatrix=function(e,r,n,i,a){if(!n[0]&&!n[1])return e;var o=a?\"map\"===i?this.transform.angle:0:\"viewport\"===i?-this.transform.angle:0;if(o){var s=Math.sin(o),l=Math.cos(o);n=[n[0]*l-n[1]*s,n[0]*s+n[1]*l]}var c=[a?n[0]:pe(r,n[0],this.transform.zoom),a?n[1]:pe(r,n[1],this.transform.zoom),0],u=new Float32Array(16);return t.translate(u,e,c),u},_n.prototype.saveTileTexture=function(t){var e=this._tileTextures[t.size[0]];e?e.push(t):this._tileTextures[t.size[0]]=[t]},_n.prototype.getTileTexture=function(t){var e=this._tileTextures[t];return e&&e.length>0?e.pop():null},_n.prototype.isPatternMissing=function(t){if(!t)return!1;if(!t.from||!t.to)return!0;var e=this.imageManager.getPattern(t.from.toString()),r=this.imageManager.getPattern(t.to.toString());return!e||!r},_n.prototype.useProgram=function(t,e){this.cache=this.cache||{};var r=\"\"+t+(e?e.cacheKey:\"\")+(this._showOverdrawInspector?\"/overdraw\":\"\");return this.cache[r]||(this.cache[r]=new _r(this.context,xr[t],e,Jr[t],this._showOverdrawInspector)),this.cache[r]},_n.prototype.setCustomLayerDefaults=function(){this.context.unbindVAO(),this.context.cullFace.setDefault(),this.context.activeTexture.setDefault(),this.context.pixelStoreUnpack.setDefault(),this.context.pixelStoreUnpackPremultiplyAlpha.setDefault(),this.context.pixelStoreUnpackFlipY.setDefault()},_n.prototype.setBaseState=function(){var t=this.context.gl;this.context.cullFace.set(!1),this.context.viewport.set([0,0,this.width,this.height]),this.context.blendEquation.set(t.FUNC_ADD)},_n.prototype.initDebugOverlayCanvas=function(){if(null==this.debugOverlayCanvas){this.debugOverlayCanvas=t.window.document.createElement(\"canvas\"),this.debugOverlayCanvas.width=512,this.debugOverlayCanvas.height=512;var e=this.context.gl;this.debugOverlayTexture=new t.Texture(this.context,this.debugOverlayCanvas,e.RGBA)}},_n.prototype.destroy=function(){this.emptyTexture.destroy(),this.debugOverlayTexture&&this.debugOverlayTexture.destroy()};var wn=function(t,e){this.points=t,this.planes=e};wn.fromInvProjectionMatrix=function(e,r,n){var i=Math.pow(2,n),a=[[-1,1,-1,1],[1,1,-1,1],[1,-1,-1,1],[-1,-1,-1,1],[-1,1,1,1],[1,1,1,1],[1,-1,1,1],[-1,-1,1,1]].map((function(r){return t.transformMat4([],r,e)})).map((function(e){return t.scale$1([],e,1/e[3]/r*i)})),o=[[0,1,2],[6,5,4],[0,3,7],[2,1,5],[3,2,6],[0,4,5]].map((function(e){var r=t.sub([],a[e[0]],a[e[1]]),n=t.sub([],a[e[2]],a[e[1]]),i=t.normalize([],t.cross([],r,n)),o=-t.dot(i,a[e[1]]);return i.concat(o)}));return new wn(a,o)};var Tn=function(e,r){this.min=e,this.max=r,this.center=t.scale$2([],t.add([],this.min,this.max),.5)};Tn.prototype.quadrant=function(e){for(var r=[e%2==0,e<2],n=t.clone$2(this.min),i=t.clone$2(this.max),a=0;a<r.length;a++)n[a]=r[a]?this.min[a]:this.center[a],i[a]=r[a]?this.center[a]:this.max[a];return i[2]=this.max[2],new Tn(n,i)},Tn.prototype.distanceX=function(t){return Math.max(Math.min(this.max[0],t[0]),this.min[0])-t[0]},Tn.prototype.distanceY=function(t){return Math.max(Math.min(this.max[1],t[1]),this.min[1])-t[1]},Tn.prototype.intersects=function(e){for(var r=[[this.min[0],this.min[1],0,1],[this.max[0],this.min[1],0,1],[this.max[0],this.max[1],0,1],[this.min[0],this.max[1],0,1]],n=!0,i=0;i<e.planes.length;i++){for(var a=e.planes[i],o=0,s=0;s<r.length;s++)o+=t.dot$1(a,r[s])>=0;if(0===o)return 0;o!==r.length&&(n=!1)}if(n)return 2;for(var l=0;l<3;l++){for(var c=Number.MAX_VALUE,u=-Number.MAX_VALUE,f=0;f<e.points.length;f++){var h=e.points[f][l]-this.min[l];c=Math.min(c,h),u=Math.max(u,h)}if(u<0||c>this.max[l]-this.min[l])return 0}return 1};var kn=function(t,e,r,n){if(void 0===t&&(t=0),void 0===e&&(e=0),void 0===r&&(r=0),void 0===n&&(n=0),isNaN(t)||t<0||isNaN(e)||e<0||isNaN(r)||r<0||isNaN(n)||n<0)throw new Error(\"Invalid value for edge-insets, top, bottom, left and right must all be numbers\");this.top=t,this.bottom=e,this.left=r,this.right=n};kn.prototype.interpolate=function(e,r,n){return null!=r.top&&null!=e.top&&(this.top=t.number(e.top,r.top,n)),null!=r.bottom&&null!=e.bottom&&(this.bottom=t.number(e.bottom,r.bottom,n)),null!=r.left&&null!=e.left&&(this.left=t.number(e.left,r.left,n)),null!=r.right&&null!=e.right&&(this.right=t.number(e.right,r.right,n)),this},kn.prototype.getCenter=function(e,r){var n=t.clamp((this.left+e-this.right)/2,0,e),i=t.clamp((this.top+r-this.bottom)/2,0,r);return new t.Point(n,i)},kn.prototype.equals=function(t){return this.top===t.top&&this.bottom===t.bottom&&this.left===t.left&&this.right===t.right},kn.prototype.clone=function(){return new kn(this.top,this.bottom,this.left,this.right)},kn.prototype.toJSON=function(){return{top:this.top,bottom:this.bottom,left:this.left,right:this.right}};var An=function(e,r,n,i,a){this.tileSize=512,this.maxValidLatitude=85.051129,this._renderWorldCopies=void 0===a||a,this._minZoom=e||0,this._maxZoom=r||22,this._minPitch=null==n?0:n,this._maxPitch=null==i?60:i,this.setMaxBounds(),this.width=0,this.height=0,this._center=new t.LngLat(0,0),this.zoom=0,this.angle=0,this._fov=.6435011087932844,this._pitch=0,this._unmodified=!0,this._edgeInsets=new kn,this._posMatrixCache={},this._alignedPosMatrixCache={}},Mn={minZoom:{configurable:!0},maxZoom:{configurable:!0},minPitch:{configurable:!0},maxPitch:{configurable:!0},renderWorldCopies:{configurable:!0},worldSize:{configurable:!0},centerOffset:{configurable:!0},size:{configurable:!0},bearing:{configurable:!0},pitch:{configurable:!0},fov:{configurable:!0},zoom:{configurable:!0},center:{configurable:!0},padding:{configurable:!0},centerPoint:{configurable:!0},unmodified:{configurable:!0},point:{configurable:!0}};An.prototype.clone=function(){var t=new An(this._minZoom,this._maxZoom,this._minPitch,this.maxPitch,this._renderWorldCopies);return t.tileSize=this.tileSize,t.latRange=this.latRange,t.width=this.width,t.height=this.height,t._center=this._center,t.zoom=this.zoom,t.angle=this.angle,t._fov=this._fov,t._pitch=this._pitch,t._unmodified=this._unmodified,t._edgeInsets=this._edgeInsets.clone(),t._calcMatrices(),t},Mn.minZoom.get=function(){return this._minZoom},Mn.minZoom.set=function(t){this._minZoom!==t&&(this._minZoom=t,this.zoom=Math.max(this.zoom,t))},Mn.maxZoom.get=function(){return this._maxZoom},Mn.maxZoom.set=function(t){this._maxZoom!==t&&(this._maxZoom=t,this.zoom=Math.min(this.zoom,t))},Mn.minPitch.get=function(){return this._minPitch},Mn.minPitch.set=function(t){this._minPitch!==t&&(this._minPitch=t,this.pitch=Math.max(this.pitch,t))},Mn.maxPitch.get=function(){return this._maxPitch},Mn.maxPitch.set=function(t){this._maxPitch!==t&&(this._maxPitch=t,this.pitch=Math.min(this.pitch,t))},Mn.renderWorldCopies.get=function(){return this._renderWorldCopies},Mn.renderWorldCopies.set=function(t){void 0===t?t=!0:null===t&&(t=!1),this._renderWorldCopies=t},Mn.worldSize.get=function(){return this.tileSize*this.scale},Mn.centerOffset.get=function(){return this.centerPoint._sub(this.size._div(2))},Mn.size.get=function(){return new t.Point(this.width,this.height)},Mn.bearing.get=function(){return-this.angle/Math.PI*180},Mn.bearing.set=function(e){var r=-t.wrap(e,-180,180)*Math.PI/180;this.angle!==r&&(this._unmodified=!1,this.angle=r,this._calcMatrices(),this.rotationMatrix=t.create$2(),t.rotate(this.rotationMatrix,this.rotationMatrix,this.angle))},Mn.pitch.get=function(){return this._pitch/Math.PI*180},Mn.pitch.set=function(e){var r=t.clamp(e,this.minPitch,this.maxPitch)/180*Math.PI;this._pitch!==r&&(this._unmodified=!1,this._pitch=r,this._calcMatrices())},Mn.fov.get=function(){return this._fov/Math.PI*180},Mn.fov.set=function(t){t=Math.max(.01,Math.min(60,t)),this._fov!==t&&(this._unmodified=!1,this._fov=t/180*Math.PI,this._calcMatrices())},Mn.zoom.get=function(){return this._zoom},Mn.zoom.set=function(t){var e=Math.min(Math.max(t,this.minZoom),this.maxZoom);this._zoom!==e&&(this._unmodified=!1,this._zoom=e,this.scale=this.zoomScale(e),this.tileZoom=Math.floor(e),this.zoomFraction=e-this.tileZoom,this._constrain(),this._calcMatrices())},Mn.center.get=function(){return this._center},Mn.center.set=function(t){t.lat===this._center.lat&&t.lng===this._center.lng||(this._unmodified=!1,this._center=t,this._constrain(),this._calcMatrices())},Mn.padding.get=function(){return this._edgeInsets.toJSON()},Mn.padding.set=function(t){this._edgeInsets.equals(t)||(this._unmodified=!1,this._edgeInsets.interpolate(this._edgeInsets,t,1),this._calcMatrices())},Mn.centerPoint.get=function(){return this._edgeInsets.getCenter(this.width,this.height)},An.prototype.isPaddingEqual=function(t){return this._edgeInsets.equals(t)},An.prototype.interpolatePadding=function(t,e,r){this._unmodified=!1,this._edgeInsets.interpolate(t,e,r),this._constrain(),this._calcMatrices()},An.prototype.coveringZoomLevel=function(t){var e=(t.roundZoom?Math.round:Math.floor)(this.zoom+this.scaleZoom(this.tileSize/t.tileSize));return Math.max(0,e)},An.prototype.getVisibleUnwrappedCoordinates=function(e){var r=[new t.UnwrappedTileID(0,e)];if(this._renderWorldCopies)for(var n=this.pointCoordinate(new t.Point(0,0)),i=this.pointCoordinate(new t.Point(this.width,0)),a=this.pointCoordinate(new t.Point(this.width,this.height)),o=this.pointCoordinate(new t.Point(0,this.height)),s=Math.floor(Math.min(n.x,i.x,a.x,o.x)),l=Math.floor(Math.max(n.x,i.x,a.x,o.x)),c=s-1;c<=l+1;c++)0!==c&&r.push(new t.UnwrappedTileID(c,e));return r},An.prototype.coveringTiles=function(e){var r=this.coveringZoomLevel(e),n=r;if(void 0!==e.minzoom&&r<e.minzoom)return[];void 0!==e.maxzoom&&r>e.maxzoom&&(r=e.maxzoom);var i=t.MercatorCoordinate.fromLngLat(this.center),a=Math.pow(2,r),o=[a*i.x,a*i.y,0],s=wn.fromInvProjectionMatrix(this.invProjMatrix,this.worldSize,r),l=e.minzoom||0;this.pitch<=60&&this._edgeInsets.top<.1&&(l=r);var c=function(t){return{aabb:new Tn([t*a,0,0],[(t+1)*a,a,0]),zoom:0,x:0,y:0,wrap:t,fullyVisible:!1}},u=[],f=[],h=r,p=e.reparseOverscaled?n:r;if(this._renderWorldCopies)for(var d=1;d<=3;d++)u.push(c(-d)),u.push(c(d));for(u.push(c(0));u.length>0;){var m=u.pop(),g=m.x,v=m.y,y=m.fullyVisible;if(!y){var x=m.aabb.intersects(s);if(0===x)continue;y=2===x}var b=m.aabb.distanceX(o),_=m.aabb.distanceY(o),w=Math.max(Math.abs(b),Math.abs(_)),T=3+(1<<h-m.zoom)-2;if(m.zoom===h||w>T&&m.zoom>=l)f.push({tileID:new t.OverscaledTileID(m.zoom===h?p:m.zoom,m.wrap,m.zoom,g,v),distanceSq:t.sqrLen([o[0]-.5-g,o[1]-.5-v])});else for(var k=0;k<4;k++){var A=(g<<1)+k%2,M=(v<<1)+(k>>1);u.push({aabb:m.aabb.quadrant(k),zoom:m.zoom+1,x:A,y:M,wrap:m.wrap,fullyVisible:y})}}return f.sort((function(t,e){return t.distanceSq-e.distanceSq})).map((function(t){return t.tileID}))},An.prototype.resize=function(t,e){this.width=t,this.height=e,this.pixelsToGLUnits=[2/t,-2/e],this._constrain(),this._calcMatrices()},Mn.unmodified.get=function(){return this._unmodified},An.prototype.zoomScale=function(t){return Math.pow(2,t)},An.prototype.scaleZoom=function(t){return Math.log(t)/Math.LN2},An.prototype.project=function(e){var r=t.clamp(e.lat,-this.maxValidLatitude,this.maxValidLatitude);return new t.Point(t.mercatorXfromLng(e.lng)*this.worldSize,t.mercatorYfromLat(r)*this.worldSize)},An.prototype.unproject=function(e){return new t.MercatorCoordinate(e.x/this.worldSize,e.y/this.worldSize).toLngLat()},Mn.point.get=function(){return this.project(this.center)},An.prototype.setLocationAtPoint=function(e,r){var n=this.pointCoordinate(r),i=this.pointCoordinate(this.centerPoint),a=this.locationCoordinate(e),o=new t.MercatorCoordinate(a.x-(n.x-i.x),a.y-(n.y-i.y));this.center=this.coordinateLocation(o),this._renderWorldCopies&&(this.center=this.center.wrap())},An.prototype.locationPoint=function(t){return this.coordinatePoint(this.locationCoordinate(t))},An.prototype.pointLocation=function(t){return this.coordinateLocation(this.pointCoordinate(t))},An.prototype.locationCoordinate=function(e){return t.MercatorCoordinate.fromLngLat(e)},An.prototype.coordinateLocation=function(t){return t.toLngLat()},An.prototype.pointCoordinate=function(e){var r=[e.x,e.y,0,1],n=[e.x,e.y,1,1];t.transformMat4(r,r,this.pixelMatrixInverse),t.transformMat4(n,n,this.pixelMatrixInverse);var i=r[3],a=n[3],o=r[0]/i,s=n[0]/a,l=r[1]/i,c=n[1]/a,u=r[2]/i,f=n[2]/a,h=u===f?0:(0-u)/(f-u);return new t.MercatorCoordinate(t.number(o,s,h)/this.worldSize,t.number(l,c,h)/this.worldSize)},An.prototype.coordinatePoint=function(e){var r=[e.x*this.worldSize,e.y*this.worldSize,0,1];return t.transformMat4(r,r,this.pixelMatrix),new t.Point(r[0]/r[3],r[1]/r[3])},An.prototype.getBounds=function(){return(new t.LngLatBounds).extend(this.pointLocation(new t.Point(0,0))).extend(this.pointLocation(new t.Point(this.width,0))).extend(this.pointLocation(new t.Point(this.width,this.height))).extend(this.pointLocation(new t.Point(0,this.height)))},An.prototype.getMaxBounds=function(){return this.latRange&&2===this.latRange.length&&this.lngRange&&2===this.lngRange.length?new t.LngLatBounds([this.lngRange[0],this.latRange[0]],[this.lngRange[1],this.latRange[1]]):null},An.prototype.setMaxBounds=function(t){t?(this.lngRange=[t.getWest(),t.getEast()],this.latRange=[t.getSouth(),t.getNorth()],this._constrain()):(this.lngRange=null,this.latRange=[-this.maxValidLatitude,this.maxValidLatitude])},An.prototype.calculatePosMatrix=function(e,r){void 0===r&&(r=!1);var n=e.key,i=r?this._alignedPosMatrixCache:this._posMatrixCache;if(i[n])return i[n];var a=e.canonical,o=this.worldSize/this.zoomScale(a.z),s=a.x+Math.pow(2,a.z)*e.wrap,l=t.identity(new Float64Array(16));return t.translate(l,l,[s*o,a.y*o,0]),t.scale(l,l,[o/t.EXTENT,o/t.EXTENT,1]),t.multiply(l,r?this.alignedProjMatrix:this.projMatrix,l),i[n]=new Float32Array(l),i[n]},An.prototype.customLayerMatrix=function(){return this.mercatorMatrix.slice()},An.prototype._constrain=function(){if(this.center&&this.width&&this.height&&!this._constraining){this._constraining=!0;var e,r,n,i,a=-90,o=90,s=-180,l=180,c=this.size,u=this._unmodified;if(this.latRange){var f=this.latRange;a=t.mercatorYfromLat(f[1])*this.worldSize,e=(o=t.mercatorYfromLat(f[0])*this.worldSize)-a<c.y?c.y/(o-a):0}if(this.lngRange){var h=this.lngRange;s=t.mercatorXfromLng(h[0])*this.worldSize,r=(l=t.mercatorXfromLng(h[1])*this.worldSize)-s<c.x?c.x/(l-s):0}var p=this.point,d=Math.max(r||0,e||0);if(d)return this.center=this.unproject(new t.Point(r?(l+s)/2:p.x,e?(o+a)/2:p.y)),this.zoom+=this.scaleZoom(d),this._unmodified=u,void(this._constraining=!1);if(this.latRange){var m=p.y,g=c.y/2;m-g<a&&(i=a+g),m+g>o&&(i=o-g)}if(this.lngRange){var v=p.x,y=c.x/2;v-y<s&&(n=s+y),v+y>l&&(n=l-y)}void 0===n&&void 0===i||(this.center=this.unproject(new t.Point(void 0!==n?n:p.x,void 0!==i?i:p.y))),this._unmodified=u,this._constraining=!1}},An.prototype._calcMatrices=function(){if(this.height){var e=this._fov/2,r=this.centerOffset;this.cameraToCenterDistance=.5/Math.tan(e)*this.height;var n=Math.PI/2+this._pitch,i=this._fov*(.5+r.y/this.height),a=Math.sin(i)*this.cameraToCenterDistance/Math.sin(t.clamp(Math.PI-n-i,.01,Math.PI-.01)),o=this.point,s=o.x,l=o.y,c=1.01*(Math.cos(Math.PI/2-this._pitch)*a+this.cameraToCenterDistance),u=this.height/50,f=new Float64Array(16);t.perspective(f,this._fov,this.width/this.height,u,c),f[8]=2*-r.x/this.width,f[9]=2*r.y/this.height,t.scale(f,f,[1,-1,1]),t.translate(f,f,[0,0,-this.cameraToCenterDistance]),t.rotateX(f,f,this._pitch),t.rotateZ(f,f,this.angle),t.translate(f,f,[-s,-l,0]),this.mercatorMatrix=t.scale([],f,[this.worldSize,this.worldSize,this.worldSize]),t.scale(f,f,[1,1,t.mercatorZfromAltitude(1,this.center.lat)*this.worldSize,1]),this.projMatrix=f,this.invProjMatrix=t.invert([],this.projMatrix);var h=this.width%2/2,p=this.height%2/2,d=Math.cos(this.angle),m=Math.sin(this.angle),g=s-Math.round(s)+d*h+m*p,v=l-Math.round(l)+d*p+m*h,y=new Float64Array(f);if(t.translate(y,y,[g>.5?g-1:g,v>.5?v-1:v,0]),this.alignedProjMatrix=y,f=t.create(),t.scale(f,f,[this.width/2,-this.height/2,1]),t.translate(f,f,[1,-1,0]),this.labelPlaneMatrix=f,f=t.create(),t.scale(f,f,[1,-1,1]),t.translate(f,f,[-1,-1,0]),t.scale(f,f,[2/this.width,2/this.height,1]),this.glCoordMatrix=f,this.pixelMatrix=t.multiply(new Float64Array(16),this.labelPlaneMatrix,this.projMatrix),!(f=t.invert(new Float64Array(16),this.pixelMatrix)))throw new Error(\"failed to invert matrix\");this.pixelMatrixInverse=f,this._posMatrixCache={},this._alignedPosMatrixCache={}}},An.prototype.maxPitchScaleFactor=function(){if(!this.pixelMatrixInverse)return 1;var e=this.pointCoordinate(new t.Point(0,0)),r=[e.x*this.worldSize,e.y*this.worldSize,0,1];return t.transformMat4(r,r,this.pixelMatrix)[3]/this.cameraToCenterDistance},An.prototype.getCameraPoint=function(){var e=this._pitch,r=Math.tan(e)*(this.cameraToCenterDistance||1);return this.centerPoint.add(new t.Point(0,r))},An.prototype.getCameraQueryGeometry=function(e){var r=this.getCameraPoint();if(1===e.length)return[e[0],r];for(var n=r.x,i=r.y,a=r.x,o=r.y,s=0,l=e;s<l.length;s+=1){var c=l[s];n=Math.min(n,c.x),i=Math.min(i,c.y),a=Math.max(a,c.x),o=Math.max(o,c.y)}return[new t.Point(n,i),new t.Point(a,i),new t.Point(a,o),new t.Point(n,o),new t.Point(n,i)]},Object.defineProperties(An.prototype,Mn);var Sn=function(e){var r,n,i,a,o;this._hashName=e&&encodeURIComponent(e),t.bindAll([\"_getCurrentHash\",\"_onHashChange\",\"_updateHash\"],this),this._updateHash=(r=this._updateHashUnthrottled.bind(this),n=300,i=!1,a=null,o=function(){a=null,i&&(r(),a=setTimeout(o,n),i=!1)},function(){return i=!0,a||o(),a})};Sn.prototype.addTo=function(e){return this._map=e,t.window.addEventListener(\"hashchange\",this._onHashChange,!1),this._map.on(\"moveend\",this._updateHash),this},Sn.prototype.remove=function(){return t.window.removeEventListener(\"hashchange\",this._onHashChange,!1),this._map.off(\"moveend\",this._updateHash),clearTimeout(this._updateHash()),delete this._map,this},Sn.prototype.getHashString=function(e){var r=this._map.getCenter(),n=Math.round(100*this._map.getZoom())/100,i=Math.ceil((n*Math.LN2+Math.log(512/360/.5))/Math.LN10),a=Math.pow(10,i),o=Math.round(r.lng*a)/a,s=Math.round(r.lat*a)/a,l=this._map.getBearing(),c=this._map.getPitch(),u=\"\";if(u+=e?\"/\"+o+\"/\"+s+\"/\"+n:n+\"/\"+s+\"/\"+o,(l||c)&&(u+=\"/\"+Math.round(10*l)/10),c&&(u+=\"/\"+Math.round(c)),this._hashName){var f=this._hashName,h=!1,p=t.window.location.hash.slice(1).split(\"&\").map((function(t){var e=t.split(\"=\")[0];return e===f?(h=!0,e+\"=\"+u):t})).filter((function(t){return t}));return h||p.push(f+\"=\"+u),\"#\"+p.join(\"&\")}return\"#\"+u},Sn.prototype._getCurrentHash=function(){var e,r=this,n=t.window.location.hash.replace(\"#\",\"\");return this._hashName?(n.split(\"&\").map((function(t){return t.split(\"=\")})).forEach((function(t){t[0]===r._hashName&&(e=t)})),(e&&e[1]||\"\").split(\"/\")):n.split(\"/\")},Sn.prototype._onHashChange=function(){var t=this._getCurrentHash();if(t.length>=3&&!t.some((function(t){return isNaN(t)}))){var e=this._map.dragRotate.isEnabled()&&this._map.touchZoomRotate.isEnabled()?+(t[3]||0):this._map.getBearing();return this._map.jumpTo({center:[+t[2],+t[1]],zoom:+t[0],bearing:e,pitch:+(t[4]||0)}),!0}return!1},Sn.prototype._updateHashUnthrottled=function(){var e=this.getHashString();try{t.window.history.replaceState(t.window.history.state,\"\",e)}catch(t){}};var En={linearity:.3,easing:t.bezier(0,0,.3,1)},Ln=t.extend({deceleration:2500,maxSpeed:1400},En),Cn=t.extend({deceleration:20,maxSpeed:1400},En),Pn=t.extend({deceleration:1e3,maxSpeed:360},En),In=t.extend({deceleration:1e3,maxSpeed:90},En),On=function(t){this._map=t,this.clear()};function zn(t,e){(!t.duration||t.duration<e.duration)&&(t.duration=e.duration,t.easing=e.easing)}function Dn(e,r,n){var i=n.maxSpeed,a=n.linearity,o=n.deceleration,s=t.clamp(e*a/(r/1e3),-i,i),l=Math.abs(s)/(o*a);return{easing:n.easing,duration:1e3*l,amount:s*(l/2)}}On.prototype.clear=function(){this._inertiaBuffer=[]},On.prototype.record=function(e){this._drainInertiaBuffer(),this._inertiaBuffer.push({time:t.browser.now(),settings:e})},On.prototype._drainInertiaBuffer=function(){for(var e=this._inertiaBuffer,r=t.browser.now();e.length>0&&r-e[0].time>160;)e.shift()},On.prototype._onMoveEnd=function(e){if(this._drainInertiaBuffer(),!(this._inertiaBuffer.length<2)){for(var r={zoom:0,bearing:0,pitch:0,pan:new t.Point(0,0),pinchAround:void 0,around:void 0},n=0,i=this._inertiaBuffer;n<i.length;n+=1){var a=i[n].settings;r.zoom+=a.zoomDelta||0,r.bearing+=a.bearingDelta||0,r.pitch+=a.pitchDelta||0,a.panDelta&&r.pan._add(a.panDelta),a.around&&(r.around=a.around),a.pinchAround&&(r.pinchAround=a.pinchAround)}var o=this._inertiaBuffer[this._inertiaBuffer.length-1].time-this._inertiaBuffer[0].time,s={};if(r.pan.mag()){var l=Dn(r.pan.mag(),o,t.extend({},Ln,e||{}));s.offset=r.pan.mult(l.amount/r.pan.mag()),s.center=this._map.transform.center,zn(s,l)}if(r.zoom){var c=Dn(r.zoom,o,Cn);s.zoom=this._map.transform.zoom+c.amount,zn(s,c)}if(r.bearing){var u=Dn(r.bearing,o,Pn);s.bearing=this._map.transform.bearing+t.clamp(u.amount,-179,179),zn(s,u)}if(r.pitch){var f=Dn(r.pitch,o,In);s.pitch=this._map.transform.pitch+f.amount,zn(s,f)}if(s.zoom||s.bearing){var h=void 0===r.pinchAround?r.around:r.pinchAround;s.around=h?this._map.unproject(h):this._map.getCenter()}return this.clear(),t.extend(s,{noMoveStart:!0})}};var Rn=function(e){function n(n,i,a,o){void 0===o&&(o={});var s=r.mousePos(i.getCanvasContainer(),a),l=i.unproject(s);e.call(this,n,t.extend({point:s,lngLat:l,originalEvent:a},o)),this._defaultPrevented=!1,this.target=i}e&&(n.__proto__=e),n.prototype=Object.create(e&&e.prototype),n.prototype.constructor=n;var i={defaultPrevented:{configurable:!0}};return n.prototype.preventDefault=function(){this._defaultPrevented=!0},i.defaultPrevented.get=function(){return this._defaultPrevented},Object.defineProperties(n.prototype,i),n}(t.Event),Fn=function(e){function n(n,i,a){var o=\"touchend\"===n?a.changedTouches:a.touches,s=r.touchPos(i.getCanvasContainer(),o),l=s.map((function(t){return i.unproject(t)})),c=s.reduce((function(t,e,r,n){return t.add(e.div(n.length))}),new t.Point(0,0)),u=i.unproject(c);e.call(this,n,{points:s,point:c,lngLats:l,lngLat:u,originalEvent:a}),this._defaultPrevented=!1}e&&(n.__proto__=e),n.prototype=Object.create(e&&e.prototype),n.prototype.constructor=n;var i={defaultPrevented:{configurable:!0}};return n.prototype.preventDefault=function(){this._defaultPrevented=!0},i.defaultPrevented.get=function(){return this._defaultPrevented},Object.defineProperties(n.prototype,i),n}(t.Event),Bn=function(t){function e(e,r,n){t.call(this,e,{originalEvent:n}),this._defaultPrevented=!1}t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e;var r={defaultPrevented:{configurable:!0}};return e.prototype.preventDefault=function(){this._defaultPrevented=!0},r.defaultPrevented.get=function(){return this._defaultPrevented},Object.defineProperties(e.prototype,r),e}(t.Event),Nn=function(t,e){this._map=t,this._clickTolerance=e.clickTolerance};Nn.prototype.reset=function(){delete this._mousedownPos},Nn.prototype.wheel=function(t){return this._firePreventable(new Bn(t.type,this._map,t))},Nn.prototype.mousedown=function(t,e){return this._mousedownPos=e,this._firePreventable(new Rn(t.type,this._map,t))},Nn.prototype.mouseup=function(t){this._map.fire(new Rn(t.type,this._map,t))},Nn.prototype.click=function(t,e){this._mousedownPos&&this._mousedownPos.dist(e)>=this._clickTolerance||this._map.fire(new Rn(t.type,this._map,t))},Nn.prototype.dblclick=function(t){return this._firePreventable(new Rn(t.type,this._map,t))},Nn.prototype.mouseover=function(t){this._map.fire(new Rn(t.type,this._map,t))},Nn.prototype.mouseout=function(t){this._map.fire(new Rn(t.type,this._map,t))},Nn.prototype.touchstart=function(t){return this._firePreventable(new Fn(t.type,this._map,t))},Nn.prototype.touchmove=function(t){this._map.fire(new Fn(t.type,this._map,t))},Nn.prototype.touchend=function(t){this._map.fire(new Fn(t.type,this._map,t))},Nn.prototype.touchcancel=function(t){this._map.fire(new Fn(t.type,this._map,t))},Nn.prototype._firePreventable=function(t){if(this._map.fire(t),t.defaultPrevented)return{}},Nn.prototype.isEnabled=function(){return!0},Nn.prototype.isActive=function(){return!1},Nn.prototype.enable=function(){},Nn.prototype.disable=function(){};var jn=function(t){this._map=t};jn.prototype.reset=function(){this._delayContextMenu=!1,delete this._contextMenuEvent},jn.prototype.mousemove=function(t){this._map.fire(new Rn(t.type,this._map,t))},jn.prototype.mousedown=function(){this._delayContextMenu=!0},jn.prototype.mouseup=function(){this._delayContextMenu=!1,this._contextMenuEvent&&(this._map.fire(new Rn(\"contextmenu\",this._map,this._contextMenuEvent)),delete this._contextMenuEvent)},jn.prototype.contextmenu=function(t){this._delayContextMenu?this._contextMenuEvent=t:this._map.fire(new Rn(t.type,this._map,t)),this._map.listens(\"contextmenu\")&&t.preventDefault()},jn.prototype.isEnabled=function(){return!0},jn.prototype.isActive=function(){return!1},jn.prototype.enable=function(){},jn.prototype.disable=function(){};var Un=function(t,e){this._map=t,this._el=t.getCanvasContainer(),this._container=t.getContainer(),this._clickTolerance=e.clickTolerance||1};function Vn(t,e){for(var r={},n=0;n<t.length;n++)r[t[n].identifier]=e[n];return r}Un.prototype.isEnabled=function(){return!!this._enabled},Un.prototype.isActive=function(){return!!this._active},Un.prototype.enable=function(){this.isEnabled()||(this._enabled=!0)},Un.prototype.disable=function(){this.isEnabled()&&(this._enabled=!1)},Un.prototype.mousedown=function(t,e){this.isEnabled()&&t.shiftKey&&0===t.button&&(r.disableDrag(),this._startPos=this._lastPos=e,this._active=!0)},Un.prototype.mousemoveWindow=function(t,e){if(this._active){var n=e;if(!(this._lastPos.equals(n)||!this._box&&n.dist(this._startPos)<this._clickTolerance)){var i=this._startPos;this._lastPos=n,this._box||(this._box=r.create(\"div\",\"mapboxgl-boxzoom\",this._container),this._container.classList.add(\"mapboxgl-crosshair\"),this._fireEvent(\"boxzoomstart\",t));var a=Math.min(i.x,n.x),o=Math.max(i.x,n.x),s=Math.min(i.y,n.y),l=Math.max(i.y,n.y);r.setTransform(this._box,\"translate(\"+a+\"px,\"+s+\"px)\"),this._box.style.width=o-a+\"px\",this._box.style.height=l-s+\"px\"}}},Un.prototype.mouseupWindow=function(e,n){var i=this;if(this._active&&0===e.button){var a=this._startPos,o=n;if(this.reset(),r.suppressClick(),a.x!==o.x||a.y!==o.y)return this._map.fire(new t.Event(\"boxzoomend\",{originalEvent:e})),{cameraAnimation:function(t){return t.fitScreenCoordinates(a,o,i._map.getBearing(),{linear:!0})}};this._fireEvent(\"boxzoomcancel\",e)}},Un.prototype.keydown=function(t){this._active&&27===t.keyCode&&(this.reset(),this._fireEvent(\"boxzoomcancel\",t))},Un.prototype.reset=function(){this._active=!1,this._container.classList.remove(\"mapboxgl-crosshair\"),this._box&&(r.remove(this._box),this._box=null),r.enableDrag(),delete this._startPos,delete this._lastPos},Un.prototype._fireEvent=function(e,r){return this._map.fire(new t.Event(e,{originalEvent:r}))};var Hn=function(t){this.reset(),this.numTouches=t.numTouches};Hn.prototype.reset=function(){delete this.centroid,delete this.startTime,delete this.touches,this.aborted=!1},Hn.prototype.touchstart=function(e,r,n){(this.centroid||n.length>this.numTouches)&&(this.aborted=!0),this.aborted||(void 0===this.startTime&&(this.startTime=e.timeStamp),n.length===this.numTouches&&(this.centroid=function(e){for(var r=new t.Point(0,0),n=0,i=e;n<i.length;n+=1){var a=i[n];r._add(a)}return r.div(e.length)}(r),this.touches=Vn(n,r)))},Hn.prototype.touchmove=function(t,e,r){if(!this.aborted&&this.centroid){var n=Vn(r,e);for(var i in this.touches){var a=this.touches[i],o=n[i];(!o||o.dist(a)>30)&&(this.aborted=!0)}}},Hn.prototype.touchend=function(t,e,r){if((!this.centroid||t.timeStamp-this.startTime>500)&&(this.aborted=!0),0===r.length){var n=!this.aborted&&this.centroid;if(this.reset(),n)return n}};var qn=function(t){this.singleTap=new Hn(t),this.numTaps=t.numTaps,this.reset()};qn.prototype.reset=function(){this.lastTime=1/0,delete this.lastTap,this.count=0,this.singleTap.reset()},qn.prototype.touchstart=function(t,e,r){this.singleTap.touchstart(t,e,r)},qn.prototype.touchmove=function(t,e,r){this.singleTap.touchmove(t,e,r)},qn.prototype.touchend=function(t,e,r){var n=this.singleTap.touchend(t,e,r);if(n){var i=t.timeStamp-this.lastTime<500,a=!this.lastTap||this.lastTap.dist(n)<30;if(i&&a||this.reset(),this.count++,this.lastTime=t.timeStamp,this.lastTap=n,this.count===this.numTaps)return this.reset(),n}};var Gn=function(){this._zoomIn=new qn({numTouches:1,numTaps:2}),this._zoomOut=new qn({numTouches:2,numTaps:1}),this.reset()};Gn.prototype.reset=function(){this._active=!1,this._zoomIn.reset(),this._zoomOut.reset()},Gn.prototype.touchstart=function(t,e,r){this._zoomIn.touchstart(t,e,r),this._zoomOut.touchstart(t,e,r)},Gn.prototype.touchmove=function(t,e,r){this._zoomIn.touchmove(t,e,r),this._zoomOut.touchmove(t,e,r)},Gn.prototype.touchend=function(t,e,r){var n=this,i=this._zoomIn.touchend(t,e,r),a=this._zoomOut.touchend(t,e,r);return i?(this._active=!0,t.preventDefault(),setTimeout((function(){return n.reset()}),0),{cameraAnimation:function(e){return e.easeTo({duration:300,zoom:e.getZoom()+1,around:e.unproject(i)},{originalEvent:t})}}):a?(this._active=!0,t.preventDefault(),setTimeout((function(){return n.reset()}),0),{cameraAnimation:function(e){return e.easeTo({duration:300,zoom:e.getZoom()-1,around:e.unproject(a)},{originalEvent:t})}}):void 0},Gn.prototype.touchcancel=function(){this.reset()},Gn.prototype.enable=function(){this._enabled=!0},Gn.prototype.disable=function(){this._enabled=!1,this.reset()},Gn.prototype.isEnabled=function(){return this._enabled},Gn.prototype.isActive=function(){return this._active};var Yn=function(t){this.reset(),this._clickTolerance=t.clickTolerance||1};Yn.prototype.reset=function(){this._active=!1,this._moved=!1,delete this._lastPoint,delete this._eventButton},Yn.prototype._correctButton=function(t,e){return!1},Yn.prototype._move=function(t,e){return{}},Yn.prototype.mousedown=function(t,e){if(!this._lastPoint){var n=r.mouseButton(t);this._correctButton(t,n)&&(this._lastPoint=e,this._eventButton=n)}},Yn.prototype.mousemoveWindow=function(t,e){var r=this._lastPoint;if(r&&(t.preventDefault(),this._moved||!(e.dist(r)<this._clickTolerance)))return this._moved=!0,this._lastPoint=e,this._move(r,e)},Yn.prototype.mouseupWindow=function(t){r.mouseButton(t)===this._eventButton&&(this._moved&&r.suppressClick(),this.reset())},Yn.prototype.enable=function(){this._enabled=!0},Yn.prototype.disable=function(){this._enabled=!1,this.reset()},Yn.prototype.isEnabled=function(){return this._enabled},Yn.prototype.isActive=function(){return this._active};var Wn=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.mousedown=function(e,r){t.prototype.mousedown.call(this,e,r),this._lastPoint&&(this._active=!0)},e.prototype._correctButton=function(t,e){return 0===e&&!t.ctrlKey},e.prototype._move=function(t,e){return{around:e,panDelta:e.sub(t)}},e}(Yn),Xn=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._correctButton=function(t,e){return 0===e&&t.ctrlKey||2===e},e.prototype._move=function(t,e){var r=.8*(e.x-t.x);if(r)return this._active=!0,{bearingDelta:r}},e.prototype.contextmenu=function(t){t.preventDefault()},e}(Yn),Zn=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._correctButton=function(t,e){return 0===e&&t.ctrlKey||2===e},e.prototype._move=function(t,e){var r=-.5*(e.y-t.y);if(r)return this._active=!0,{pitchDelta:r}},e.prototype.contextmenu=function(t){t.preventDefault()},e}(Yn),Jn=function(t){this._minTouches=1,this._clickTolerance=t.clickTolerance||1,this.reset()};Jn.prototype.reset=function(){this._active=!1,this._touches={},this._sum=new t.Point(0,0)},Jn.prototype.touchstart=function(t,e,r){return this._calculateTransform(t,e,r)},Jn.prototype.touchmove=function(t,e,r){if(this._active)return t.preventDefault(),this._calculateTransform(t,e,r)},Jn.prototype.touchend=function(t,e,r){this._calculateTransform(t,e,r),this._active&&r.length<this._minTouches&&this.reset()},Jn.prototype.touchcancel=function(){this.reset()},Jn.prototype._calculateTransform=function(e,r,n){n.length>0&&(this._active=!0);var i=Vn(n,r),a=new t.Point(0,0),o=new t.Point(0,0),s=0;for(var l in i){var c=i[l],u=this._touches[l];u&&(a._add(c),o._add(c.sub(u)),s++,i[l]=c)}if(this._touches=i,!(s<this._minTouches)&&o.mag()){var f=o.div(s);if(this._sum._add(f),!(this._sum.mag()<this._clickTolerance))return{around:a.div(s),panDelta:f}}},Jn.prototype.enable=function(){this._enabled=!0},Jn.prototype.disable=function(){this._enabled=!1,this.reset()},Jn.prototype.isEnabled=function(){return this._enabled},Jn.prototype.isActive=function(){return this._active};var Kn=function(){this.reset()};function Qn(t,e,r){for(var n=0;n<t.length;n++)if(t[n].identifier===r)return e[n]}Kn.prototype.reset=function(){this._active=!1,delete this._firstTwoTouches},Kn.prototype._start=function(t){},Kn.prototype._move=function(t,e,r){return{}},Kn.prototype.touchstart=function(t,e,r){this._firstTwoTouches||r.length<2||(this._firstTwoTouches=[r[0].identifier,r[1].identifier],this._start([e[0],e[1]]))},Kn.prototype.touchmove=function(t,e,r){if(this._firstTwoTouches){t.preventDefault();var n=this._firstTwoTouches,i=n[0],a=n[1],o=Qn(r,e,i),s=Qn(r,e,a);if(o&&s){var l=this._aroundCenter?null:o.add(s).div(2);return this._move([o,s],l,t)}}},Kn.prototype.touchend=function(t,e,n){if(this._firstTwoTouches){var i=this._firstTwoTouches,a=i[0],o=i[1],s=Qn(n,e,a),l=Qn(n,e,o);s&&l||(this._active&&r.suppressClick(),this.reset())}},Kn.prototype.touchcancel=function(){this.reset()},Kn.prototype.enable=function(t){this._enabled=!0,this._aroundCenter=!!t&&\"center\"===t.around},Kn.prototype.disable=function(){this._enabled=!1,this.reset()},Kn.prototype.isEnabled=function(){return this._enabled},Kn.prototype.isActive=function(){return this._active};function $n(t,e){return Math.log(t/e)/Math.LN2}var ti=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.reset=function(){t.prototype.reset.call(this),delete this._distance,delete this._startDistance},e.prototype._start=function(t){this._startDistance=this._distance=t[0].dist(t[1])},e.prototype._move=function(t,e){var r=this._distance;if(this._distance=t[0].dist(t[1]),this._active||!(Math.abs($n(this._distance,this._startDistance))<.1))return this._active=!0,{zoomDelta:$n(this._distance,r),pinchAround:e}},e}(Kn);function ei(t,e){return 180*t.angleWith(e)/Math.PI}var ri=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.reset=function(){t.prototype.reset.call(this),delete this._minDiameter,delete this._startVector,delete this._vector},e.prototype._start=function(t){this._startVector=this._vector=t[0].sub(t[1]),this._minDiameter=t[0].dist(t[1])},e.prototype._move=function(t,e){var r=this._vector;if(this._vector=t[0].sub(t[1]),this._active||!this._isBelowThreshold(this._vector))return this._active=!0,{bearingDelta:ei(this._vector,r),pinchAround:e}},e.prototype._isBelowThreshold=function(t){this._minDiameter=Math.min(this._minDiameter,t.mag());var e=25/(Math.PI*this._minDiameter)*360,r=ei(t,this._startVector);return Math.abs(r)<e},e}(Kn);function ni(t){return Math.abs(t.y)>Math.abs(t.x)}var ii=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.reset=function(){t.prototype.reset.call(this),this._valid=void 0,delete this._firstMove,delete this._lastPoints},e.prototype._start=function(t){this._lastPoints=t,ni(t[0].sub(t[1]))&&(this._valid=!1)},e.prototype._move=function(t,e,r){var n=t[0].sub(this._lastPoints[0]),i=t[1].sub(this._lastPoints[1]);if(this._valid=this.gestureBeginsVertically(n,i,r.timeStamp),this._valid){this._lastPoints=t,this._active=!0;return{pitchDelta:-.5*((n.y+i.y)/2)}}},e.prototype.gestureBeginsVertically=function(t,e,r){if(void 0!==this._valid)return this._valid;var n=t.mag()>=2,i=e.mag()>=2;if(n||i){if(!n||!i)return void 0===this._firstMove&&(this._firstMove=r),r-this._firstMove<100&&void 0;var a=t.y>0==e.y>0;return ni(t)&&ni(e)&&a}},e}(Kn),ai={panStep:100,bearingStep:15,pitchStep:10},oi=function(){var t=ai;this._panStep=t.panStep,this._bearingStep=t.bearingStep,this._pitchStep=t.pitchStep};function si(t){return t*(2-t)}oi.prototype.reset=function(){this._active=!1},oi.prototype.keydown=function(t){var e=this;if(!(t.altKey||t.ctrlKey||t.metaKey)){var r=0,n=0,i=0,a=0,o=0;switch(t.keyCode){case 61:case 107:case 171:case 187:r=1;break;case 189:case 109:case 173:r=-1;break;case 37:t.shiftKey?n=-1:(t.preventDefault(),a=-1);break;case 39:t.shiftKey?n=1:(t.preventDefault(),a=1);break;case 38:t.shiftKey?i=1:(t.preventDefault(),o=-1);break;case 40:t.shiftKey?i=-1:(t.preventDefault(),o=1);break;default:return}return{cameraAnimation:function(s){var l=s.getZoom();s.easeTo({duration:300,easeId:\"keyboardHandler\",easing:si,zoom:r?Math.round(l)+r*(t.shiftKey?2:1):l,bearing:s.getBearing()+n*e._bearingStep,pitch:s.getPitch()+i*e._pitchStep,offset:[-a*e._panStep,-o*e._panStep],center:s.getCenter()},{originalEvent:t})}}}},oi.prototype.enable=function(){this._enabled=!0},oi.prototype.disable=function(){this._enabled=!1,this.reset()},oi.prototype.isEnabled=function(){return this._enabled},oi.prototype.isActive=function(){return this._active};var li=function(e,r){this._map=e,this._el=e.getCanvasContainer(),this._handler=r,this._delta=0,this._defaultZoomRate=.01,this._wheelZoomRate=1/450,t.bindAll([\"_onWheel\",\"_onTimeout\",\"_onScrollFrame\",\"_onScrollFinished\"],this)};li.prototype.setZoomRate=function(t){this._defaultZoomRate=t},li.prototype.setWheelZoomRate=function(t){this._wheelZoomRate=t},li.prototype.isEnabled=function(){return!!this._enabled},li.prototype.isActive=function(){return!!this._active||void 0!==this._finishTimeout},li.prototype.isZooming=function(){return!!this._zooming},li.prototype.enable=function(t){this.isEnabled()||(this._enabled=!0,this._aroundCenter=t&&\"center\"===t.around)},li.prototype.disable=function(){this.isEnabled()&&(this._enabled=!1)},li.prototype.wheel=function(e){if(this.isEnabled()){var r=e.deltaMode===t.window.WheelEvent.DOM_DELTA_LINE?40*e.deltaY:e.deltaY,n=t.browser.now(),i=n-(this._lastWheelEventTime||0);this._lastWheelEventTime=n,0!==r&&r%4.000244140625==0?this._type=\"wheel\":0!==r&&Math.abs(r)<4?this._type=\"trackpad\":i>400?(this._type=null,this._lastValue=r,this._timeout=setTimeout(this._onTimeout,40,e)):this._type||(this._type=Math.abs(i*r)<200?\"trackpad\":\"wheel\",this._timeout&&(clearTimeout(this._timeout),this._timeout=null,r+=this._lastValue)),e.shiftKey&&r&&(r/=4),this._type&&(this._lastWheelEvent=e,this._delta-=r,this._active||this._start(e)),e.preventDefault()}},li.prototype._onTimeout=function(t){this._type=\"wheel\",this._delta-=this._lastValue,this._active||this._start(t)},li.prototype._start=function(e){if(this._delta){this._frameId&&(this._frameId=null),this._active=!0,this.isZooming()||(this._zooming=!0),this._finishTimeout&&(clearTimeout(this._finishTimeout),delete this._finishTimeout);var n=r.mousePos(this._el,e);this._around=t.LngLat.convert(this._aroundCenter?this._map.getCenter():this._map.unproject(n)),this._aroundPoint=this._map.transform.locationPoint(this._around),this._frameId||(this._frameId=!0,this._handler._triggerRenderFrame())}},li.prototype.renderFrame=function(){return this._onScrollFrame()},li.prototype._onScrollFrame=function(){var e=this;if(this._frameId&&(this._frameId=null,this.isActive())){var r=this._map.transform;if(0!==this._delta){var n=\"wheel\"===this._type&&Math.abs(this._delta)>4.000244140625?this._wheelZoomRate:this._defaultZoomRate,i=2/(1+Math.exp(-Math.abs(this._delta*n)));this._delta<0&&0!==i&&(i=1/i);var a=\"number\"==typeof this._targetZoom?r.zoomScale(this._targetZoom):r.scale;this._targetZoom=Math.min(r.maxZoom,Math.max(r.minZoom,r.scaleZoom(a*i))),\"wheel\"===this._type&&(this._startZoom=r.zoom,this._easing=this._smoothOutEasing(200)),this._delta=0}var o,s=\"number\"==typeof this._targetZoom?this._targetZoom:r.zoom,l=this._startZoom,c=this._easing,u=!1;if(\"wheel\"===this._type&&l&&c){var f=Math.min((t.browser.now()-this._lastWheelEventTime)/200,1),h=c(f);o=t.number(l,s,h),f<1?this._frameId||(this._frameId=!0):u=!0}else o=s,u=!0;return this._active=!0,u&&(this._active=!1,this._finishTimeout=setTimeout((function(){e._zooming=!1,e._handler._triggerRenderFrame(),delete e._targetZoom,delete e._finishTimeout}),200)),{noInertia:!0,needsRenderFrame:!u,zoomDelta:o-r.zoom,around:this._aroundPoint,originalEvent:this._lastWheelEvent}}},li.prototype._smoothOutEasing=function(e){var r=t.ease;if(this._prevEase){var n=this._prevEase,i=(t.browser.now()-n.start)/n.duration,a=n.easing(i+.01)-n.easing(i),o=.27/Math.sqrt(a*a+1e-4)*.01,s=Math.sqrt(.0729-o*o);r=t.bezier(o,s,.25,1)}return this._prevEase={start:t.browser.now(),duration:e,easing:r},r},li.prototype.reset=function(){this._active=!1};var ci=function(t,e){this._clickZoom=t,this._tapZoom=e};ci.prototype.enable=function(){this._clickZoom.enable(),this._tapZoom.enable()},ci.prototype.disable=function(){this._clickZoom.disable(),this._tapZoom.disable()},ci.prototype.isEnabled=function(){return this._clickZoom.isEnabled()&&this._tapZoom.isEnabled()},ci.prototype.isActive=function(){return this._clickZoom.isActive()||this._tapZoom.isActive()};var ui=function(){this.reset()};ui.prototype.reset=function(){this._active=!1},ui.prototype.dblclick=function(t,e){return t.preventDefault(),{cameraAnimation:function(r){r.easeTo({duration:300,zoom:r.getZoom()+(t.shiftKey?-1:1),around:r.unproject(e)},{originalEvent:t})}}},ui.prototype.enable=function(){this._enabled=!0},ui.prototype.disable=function(){this._enabled=!1,this.reset()},ui.prototype.isEnabled=function(){return this._enabled},ui.prototype.isActive=function(){return this._active};var fi=function(){this._tap=new qn({numTouches:1,numTaps:1}),this.reset()};fi.prototype.reset=function(){this._active=!1,delete this._swipePoint,delete this._swipeTouch,delete this._tapTime,this._tap.reset()},fi.prototype.touchstart=function(t,e,r){this._swipePoint||(this._tapTime&&t.timeStamp-this._tapTime>500&&this.reset(),this._tapTime?r.length>0&&(this._swipePoint=e[0],this._swipeTouch=r[0].identifier):this._tap.touchstart(t,e,r))},fi.prototype.touchmove=function(t,e,r){if(this._tapTime){if(this._swipePoint){if(r[0].identifier!==this._swipeTouch)return;var n=e[0],i=n.y-this._swipePoint.y;return this._swipePoint=n,t.preventDefault(),this._active=!0,{zoomDelta:i/128}}}else this._tap.touchmove(t,e,r)},fi.prototype.touchend=function(t,e,r){this._tapTime?this._swipePoint&&0===r.length&&this.reset():this._tap.touchend(t,e,r)&&(this._tapTime=t.timeStamp)},fi.prototype.touchcancel=function(){this.reset()},fi.prototype.enable=function(){this._enabled=!0},fi.prototype.disable=function(){this._enabled=!1,this.reset()},fi.prototype.isEnabled=function(){return this._enabled},fi.prototype.isActive=function(){return this._active};var hi=function(t,e,r){this._el=t,this._mousePan=e,this._touchPan=r};hi.prototype.enable=function(t){this._inertiaOptions=t||{},this._mousePan.enable(),this._touchPan.enable(),this._el.classList.add(\"mapboxgl-touch-drag-pan\")},hi.prototype.disable=function(){this._mousePan.disable(),this._touchPan.disable(),this._el.classList.remove(\"mapboxgl-touch-drag-pan\")},hi.prototype.isEnabled=function(){return this._mousePan.isEnabled()&&this._touchPan.isEnabled()},hi.prototype.isActive=function(){return this._mousePan.isActive()||this._touchPan.isActive()};var pi=function(t,e,r){this._pitchWithRotate=t.pitchWithRotate,this._mouseRotate=e,this._mousePitch=r};pi.prototype.enable=function(){this._mouseRotate.enable(),this._pitchWithRotate&&this._mousePitch.enable()},pi.prototype.disable=function(){this._mouseRotate.disable(),this._mousePitch.disable()},pi.prototype.isEnabled=function(){return this._mouseRotate.isEnabled()&&(!this._pitchWithRotate||this._mousePitch.isEnabled())},pi.prototype.isActive=function(){return this._mouseRotate.isActive()||this._mousePitch.isActive()};var di=function(t,e,r,n){this._el=t,this._touchZoom=e,this._touchRotate=r,this._tapDragZoom=n,this._rotationDisabled=!1,this._enabled=!0};di.prototype.enable=function(t){this._touchZoom.enable(t),this._rotationDisabled||this._touchRotate.enable(t),this._tapDragZoom.enable(),this._el.classList.add(\"mapboxgl-touch-zoom-rotate\")},di.prototype.disable=function(){this._touchZoom.disable(),this._touchRotate.disable(),this._tapDragZoom.disable(),this._el.classList.remove(\"mapboxgl-touch-zoom-rotate\")},di.prototype.isEnabled=function(){return this._touchZoom.isEnabled()&&(this._rotationDisabled||this._touchRotate.isEnabled())&&this._tapDragZoom.isEnabled()},di.prototype.isActive=function(){return this._touchZoom.isActive()||this._touchRotate.isActive()||this._tapDragZoom.isActive()},di.prototype.disableRotation=function(){this._rotationDisabled=!0,this._touchRotate.disable()},di.prototype.enableRotation=function(){this._rotationDisabled=!1,this._touchZoom.isEnabled()&&this._touchRotate.enable()};var mi=function(t){return t.zoom||t.drag||t.pitch||t.rotate},gi=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e}(t.Event);function vi(t){return t.panDelta&&t.panDelta.mag()||t.zoomDelta||t.bearingDelta||t.pitchDelta}var yi=function(e,n){this._map=e,this._el=this._map.getCanvasContainer(),this._handlers=[],this._handlersById={},this._changes=[],this._inertia=new On(e),this._bearingSnap=n.bearingSnap,this._previousActiveHandlers={},this._eventsInProgress={},this._addDefaultHandlers(n),t.bindAll([\"handleEvent\",\"handleWindowEvent\"],this);var i=this._el;this._listeners=[[i,\"touchstart\",{passive:!1}],[i,\"touchmove\",{passive:!1}],[i,\"touchend\",void 0],[i,\"touchcancel\",void 0],[i,\"mousedown\",void 0],[i,\"mousemove\",void 0],[i,\"mouseup\",void 0],[t.window.document,\"mousemove\",{capture:!0}],[t.window.document,\"mouseup\",void 0],[i,\"mouseover\",void 0],[i,\"mouseout\",void 0],[i,\"dblclick\",void 0],[i,\"click\",void 0],[i,\"keydown\",{capture:!1}],[i,\"keyup\",void 0],[i,\"wheel\",{passive:!1}],[i,\"contextmenu\",void 0],[t.window,\"blur\",void 0]];for(var a=0,o=this._listeners;a<o.length;a+=1){var s=o[a],l=s[0],c=s[1],u=s[2];r.addEventListener(l,c,l===t.window.document?this.handleWindowEvent:this.handleEvent,u)}};yi.prototype.destroy=function(){for(var e=0,n=this._listeners;e<n.length;e+=1){var i=n[e],a=i[0],o=i[1],s=i[2];r.removeEventListener(a,o,a===t.window.document?this.handleWindowEvent:this.handleEvent,s)}},yi.prototype._addDefaultHandlers=function(t){var e=this._map,r=e.getCanvasContainer();this._add(\"mapEvent\",new Nn(e,t));var n=e.boxZoom=new Un(e,t);this._add(\"boxZoom\",n);var i=new Gn,a=new ui;e.doubleClickZoom=new ci(a,i),this._add(\"tapZoom\",i),this._add(\"clickZoom\",a);var o=new fi;this._add(\"tapDragZoom\",o);var s=e.touchPitch=new ii;this._add(\"touchPitch\",s);var l=new Xn(t),c=new Zn(t);e.dragRotate=new pi(t,l,c),this._add(\"mouseRotate\",l,[\"mousePitch\"]),this._add(\"mousePitch\",c,[\"mouseRotate\"]);var u=new Wn(t),f=new Jn(t);e.dragPan=new hi(r,u,f),this._add(\"mousePan\",u),this._add(\"touchPan\",f,[\"touchZoom\",\"touchRotate\"]);var h=new ri,p=new ti;e.touchZoomRotate=new di(r,p,h,o),this._add(\"touchRotate\",h,[\"touchPan\",\"touchZoom\"]),this._add(\"touchZoom\",p,[\"touchPan\",\"touchRotate\"]);var d=e.scrollZoom=new li(e,this);this._add(\"scrollZoom\",d,[\"mousePan\"]);var m=e.keyboard=new oi;this._add(\"keyboard\",m),this._add(\"blockableMapEvent\",new jn(e));for(var g=0,v=[\"boxZoom\",\"doubleClickZoom\",\"tapDragZoom\",\"touchPitch\",\"dragRotate\",\"dragPan\",\"touchZoomRotate\",\"scrollZoom\",\"keyboard\"];g<v.length;g+=1){var y=v[g];t.interactive&&t[y]&&e[y].enable(t[y])}},yi.prototype._add=function(t,e,r){this._handlers.push({handlerName:t,handler:e,allowed:r}),this._handlersById[t]=e},yi.prototype.stop=function(){if(!this._updatingCamera){for(var t=0,e=this._handlers;t<e.length;t+=1){e[t].handler.reset()}this._inertia.clear(),this._fireEvents({},{}),this._changes=[]}},yi.prototype.isActive=function(){for(var t=0,e=this._handlers;t<e.length;t+=1){if(e[t].handler.isActive())return!0}return!1},yi.prototype.isZooming=function(){return!!this._eventsInProgress.zoom||this._map.scrollZoom.isZooming()},yi.prototype.isRotating=function(){return!!this._eventsInProgress.rotate},yi.prototype.isMoving=function(){return Boolean(mi(this._eventsInProgress))||this.isZooming()},yi.prototype._blockedByActive=function(t,e,r){for(var n in t)if(n!==r&&(!e||e.indexOf(n)<0))return!0;return!1},yi.prototype.handleWindowEvent=function(t){this.handleEvent(t,t.type+\"Window\")},yi.prototype._getMapTouches=function(t){for(var e=[],r=0,n=t;r<n.length;r+=1){var i=n[r],a=i.target;this._el.contains(a)&&e.push(i)}return e},yi.prototype.handleEvent=function(t,e){if(\"blur\"!==t.type){this._updatingCamera=!0;for(var n=\"renderFrame\"===t.type?void 0:t,i={needsRenderFrame:!1},a={},o={},s=t.touches?this._getMapTouches(t.touches):void 0,l=s?r.touchPos(this._el,s):r.mousePos(this._el,t),c=0,u=this._handlers;c<u.length;c+=1){var f=u[c],h=f.handlerName,p=f.handler,d=f.allowed;if(p.isEnabled()){var m=void 0;this._blockedByActive(o,d,h)?p.reset():p[e||t.type]&&(m=p[e||t.type](t,l,s),this.mergeHandlerResult(i,a,m,h,n),m&&m.needsRenderFrame&&this._triggerRenderFrame()),(m||p.isActive())&&(o[h]=p)}}var g={};for(var v in this._previousActiveHandlers)o[v]||(g[v]=n);this._previousActiveHandlers=o,(Object.keys(g).length||vi(i))&&(this._changes.push([i,a,g]),this._triggerRenderFrame()),(Object.keys(o).length||vi(i))&&this._map._stop(!0),this._updatingCamera=!1;var y=i.cameraAnimation;y&&(this._inertia.clear(),this._fireEvents({},{}),this._changes=[],y(this._map))}else this.stop()},yi.prototype.mergeHandlerResult=function(e,r,n,i,a){if(n){t.extend(e,n);var o={handlerName:i,originalEvent:n.originalEvent||a};void 0!==n.zoomDelta&&(r.zoom=o),void 0!==n.panDelta&&(r.drag=o),void 0!==n.pitchDelta&&(r.pitch=o),void 0!==n.bearingDelta&&(r.rotate=o)}},yi.prototype._applyChanges=function(){for(var e={},r={},n={},i=0,a=this._changes;i<a.length;i+=1){var o=a[i],s=o[0],l=o[1],c=o[2];s.panDelta&&(e.panDelta=(e.panDelta||new t.Point(0,0))._add(s.panDelta)),s.zoomDelta&&(e.zoomDelta=(e.zoomDelta||0)+s.zoomDelta),s.bearingDelta&&(e.bearingDelta=(e.bearingDelta||0)+s.bearingDelta),s.pitchDelta&&(e.pitchDelta=(e.pitchDelta||0)+s.pitchDelta),void 0!==s.around&&(e.around=s.around),void 0!==s.pinchAround&&(e.pinchAround=s.pinchAround),s.noInertia&&(e.noInertia=s.noInertia),t.extend(r,l),t.extend(n,c)}this._updateMapTransform(e,r,n),this._changes=[]},yi.prototype._updateMapTransform=function(t,e,r){var n=this._map,i=n.transform;if(!vi(t))return this._fireEvents(e,r);var a=t.panDelta,o=t.zoomDelta,s=t.bearingDelta,l=t.pitchDelta,c=t.around,u=t.pinchAround;void 0!==u&&(c=u),n._stop(!0),c=c||n.transform.centerPoint;var f=i.pointLocation(a?c.sub(a):c);s&&(i.bearing+=s),l&&(i.pitch+=l),o&&(i.zoom+=o),i.setLocationAtPoint(f,c),this._map._update(),t.noInertia||this._inertia.record(t),this._fireEvents(e,r)},yi.prototype._fireEvents=function(e,r){var n=this,i=mi(this._eventsInProgress),a=mi(e),o={};for(var s in e){var l=e[s].originalEvent;this._eventsInProgress[s]||(o[s+\"start\"]=l),this._eventsInProgress[s]=e[s]}for(var c in!i&&a&&this._fireEvent(\"movestart\",a.originalEvent),o)this._fireEvent(c,o[c]);for(var u in e.rotate&&(this._bearingChanged=!0),a&&this._fireEvent(\"move\",a.originalEvent),e){var f=e[u].originalEvent;this._fireEvent(u,f)}var h,p={};for(var d in this._eventsInProgress){var m=this._eventsInProgress[d],g=m.handlerName,v=m.originalEvent;this._handlersById[g].isActive()||(delete this._eventsInProgress[d],h=r[g]||v,p[d+\"end\"]=h)}for(var y in p)this._fireEvent(y,p[y]);var x=mi(this._eventsInProgress);if((i||a)&&!x){this._updatingCamera=!0;var b=this._inertia._onMoveEnd(this._map.dragPan._inertiaOptions),_=function(t){return 0!==t&&-n._bearingSnap<t&&t<n._bearingSnap};b?(_(b.bearing||this._map.getBearing())&&(b.bearing=0),this._map.easeTo(b,{originalEvent:h})):(this._map.fire(new t.Event(\"moveend\",{originalEvent:h})),_(this._map.getBearing())&&this._map.resetNorth()),this._bearingChanged=!1,this._updatingCamera=!1}},yi.prototype._fireEvent=function(e,r){this._map.fire(new t.Event(e,r?{originalEvent:r}:{}))},yi.prototype._triggerRenderFrame=function(){var t=this;void 0===this._frameId&&(this._frameId=this._map._requestRenderFrame((function(e){delete t._frameId,t.handleEvent(new gi(\"renderFrame\",{timeStamp:e})),t._applyChanges()})))};var xi=function(e){function r(r,n){e.call(this),this._moving=!1,this._zooming=!1,this.transform=r,this._bearingSnap=n.bearingSnap,t.bindAll([\"_renderFrameCallback\"],this)}return e&&(r.__proto__=e),r.prototype=Object.create(e&&e.prototype),r.prototype.constructor=r,r.prototype.getCenter=function(){return new t.LngLat(this.transform.center.lng,this.transform.center.lat)},r.prototype.setCenter=function(t,e){return this.jumpTo({center:t},e)},r.prototype.panBy=function(e,r,n){return e=t.Point.convert(e).mult(-1),this.panTo(this.transform.center,t.extend({offset:e},r),n)},r.prototype.panTo=function(e,r,n){return this.easeTo(t.extend({center:e},r),n)},r.prototype.getZoom=function(){return this.transform.zoom},r.prototype.setZoom=function(t,e){return this.jumpTo({zoom:t},e),this},r.prototype.zoomTo=function(e,r,n){return this.easeTo(t.extend({zoom:e},r),n)},r.prototype.zoomIn=function(t,e){return this.zoomTo(this.getZoom()+1,t,e),this},r.prototype.zoomOut=function(t,e){return this.zoomTo(this.getZoom()-1,t,e),this},r.prototype.getBearing=function(){return this.transform.bearing},r.prototype.setBearing=function(t,e){return this.jumpTo({bearing:t},e),this},r.prototype.getPadding=function(){return this.transform.padding},r.prototype.setPadding=function(t,e){return this.jumpTo({padding:t},e),this},r.prototype.rotateTo=function(e,r,n){return this.easeTo(t.extend({bearing:e},r),n)},r.prototype.resetNorth=function(e,r){return this.rotateTo(0,t.extend({duration:1e3},e),r),this},r.prototype.resetNorthPitch=function(e,r){return this.easeTo(t.extend({bearing:0,pitch:0,duration:1e3},e),r),this},r.prototype.snapToNorth=function(t,e){return Math.abs(this.getBearing())<this._bearingSnap?this.resetNorth(t,e):this},r.prototype.getPitch=function(){return this.transform.pitch},r.prototype.setPitch=function(t,e){return this.jumpTo({pitch:t},e),this},r.prototype.cameraForBounds=function(e,r){return e=t.LngLatBounds.convert(e),this._cameraForBoxAndBearing(e.getNorthWest(),e.getSouthEast(),0,r)},r.prototype._cameraForBoxAndBearing=function(e,r,n,i){var a={top:0,bottom:0,right:0,left:0};if(\"number\"==typeof(i=t.extend({padding:a,offset:[0,0],maxZoom:this.transform.maxZoom},i)).padding){var o=i.padding;i.padding={top:o,bottom:o,right:o,left:o}}i.padding=t.extend(a,i.padding);var s=this.transform,l=s.padding,c=s.project(t.LngLat.convert(e)),u=s.project(t.LngLat.convert(r)),f=c.rotate(-n*Math.PI/180),h=u.rotate(-n*Math.PI/180),p=new t.Point(Math.max(f.x,h.x),Math.max(f.y,h.y)),d=new t.Point(Math.min(f.x,h.x),Math.min(f.y,h.y)),m=p.sub(d),g=(s.width-(l.left+l.right+i.padding.left+i.padding.right))/m.x,v=(s.height-(l.top+l.bottom+i.padding.top+i.padding.bottom))/m.y;if(!(v<0||g<0)){var y=Math.min(s.scaleZoom(s.scale*Math.min(g,v)),i.maxZoom),x=t.Point.convert(i.offset),b=(i.padding.left-i.padding.right)/2,_=(i.padding.top-i.padding.bottom)/2,w=new t.Point(x.x+b,x.y+_).mult(s.scale/s.zoomScale(y));return{center:s.unproject(c.add(u).div(2).sub(w)),zoom:y,bearing:n}}t.warnOnce(\"Map cannot fit within canvas with the given bounds, padding, and/or offset.\")},r.prototype.fitBounds=function(t,e,r){return this._fitInternal(this.cameraForBounds(t,e),e,r)},r.prototype.fitScreenCoordinates=function(e,r,n,i,a){return this._fitInternal(this._cameraForBoxAndBearing(this.transform.pointLocation(t.Point.convert(e)),this.transform.pointLocation(t.Point.convert(r)),n,i),i,a)},r.prototype._fitInternal=function(e,r,n){return e?(delete(r=t.extend(e,r)).padding,r.linear?this.easeTo(r,n):this.flyTo(r,n)):this},r.prototype.jumpTo=function(e,r){this.stop();var n=this.transform,i=!1,a=!1,o=!1;return\"zoom\"in e&&n.zoom!==+e.zoom&&(i=!0,n.zoom=+e.zoom),void 0!==e.center&&(n.center=t.LngLat.convert(e.center)),\"bearing\"in e&&n.bearing!==+e.bearing&&(a=!0,n.bearing=+e.bearing),\"pitch\"in e&&n.pitch!==+e.pitch&&(o=!0,n.pitch=+e.pitch),null==e.padding||n.isPaddingEqual(e.padding)||(n.padding=e.padding),this.fire(new t.Event(\"movestart\",r)).fire(new t.Event(\"move\",r)),i&&this.fire(new t.Event(\"zoomstart\",r)).fire(new t.Event(\"zoom\",r)).fire(new t.Event(\"zoomend\",r)),a&&this.fire(new t.Event(\"rotatestart\",r)).fire(new t.Event(\"rotate\",r)).fire(new t.Event(\"rotateend\",r)),o&&this.fire(new t.Event(\"pitchstart\",r)).fire(new t.Event(\"pitch\",r)).fire(new t.Event(\"pitchend\",r)),this.fire(new t.Event(\"moveend\",r))},r.prototype.easeTo=function(e,r){var n=this;this._stop(!1,e.easeId),(!1===(e=t.extend({offset:[0,0],duration:500,easing:t.ease},e)).animate||!e.essential&&t.browser.prefersReducedMotion)&&(e.duration=0);var i=this.transform,a=this.getZoom(),o=this.getBearing(),s=this.getPitch(),l=this.getPadding(),c=\"zoom\"in e?+e.zoom:a,u=\"bearing\"in e?this._normalizeBearing(e.bearing,o):o,f=\"pitch\"in e?+e.pitch:s,h=\"padding\"in e?e.padding:i.padding,p=t.Point.convert(e.offset),d=i.centerPoint.add(p),m=i.pointLocation(d),g=t.LngLat.convert(e.center||m);this._normalizeCenter(g);var v,y,x=i.project(m),b=i.project(g).sub(x),_=i.zoomScale(c-a);e.around&&(v=t.LngLat.convert(e.around),y=i.locationPoint(v));var w={moving:this._moving,zooming:this._zooming,rotating:this._rotating,pitching:this._pitching};return this._zooming=this._zooming||c!==a,this._rotating=this._rotating||o!==u,this._pitching=this._pitching||f!==s,this._padding=!i.isPaddingEqual(h),this._easeId=e.easeId,this._prepareEase(r,e.noMoveStart,w),clearTimeout(this._easeEndTimeoutID),this._ease((function(e){if(n._zooming&&(i.zoom=t.number(a,c,e)),n._rotating&&(i.bearing=t.number(o,u,e)),n._pitching&&(i.pitch=t.number(s,f,e)),n._padding&&(i.interpolatePadding(l,h,e),d=i.centerPoint.add(p)),v)i.setLocationAtPoint(v,y);else{var m=i.zoomScale(i.zoom-a),g=c>a?Math.min(2,_):Math.max(.5,_),w=Math.pow(g,1-e),T=i.unproject(x.add(b.mult(e*w)).mult(m));i.setLocationAtPoint(i.renderWorldCopies?T.wrap():T,d)}n._fireMoveEvents(r)}),(function(t){n._afterEase(r,t)}),e),this},r.prototype._prepareEase=function(e,r,n){void 0===n&&(n={}),this._moving=!0,r||n.moving||this.fire(new t.Event(\"movestart\",e)),this._zooming&&!n.zooming&&this.fire(new t.Event(\"zoomstart\",e)),this._rotating&&!n.rotating&&this.fire(new t.Event(\"rotatestart\",e)),this._pitching&&!n.pitching&&this.fire(new t.Event(\"pitchstart\",e))},r.prototype._fireMoveEvents=function(e){this.fire(new t.Event(\"move\",e)),this._zooming&&this.fire(new t.Event(\"zoom\",e)),this._rotating&&this.fire(new t.Event(\"rotate\",e)),this._pitching&&this.fire(new t.Event(\"pitch\",e))},r.prototype._afterEase=function(e,r){if(!this._easeId||!r||this._easeId!==r){delete this._easeId;var n=this._zooming,i=this._rotating,a=this._pitching;this._moving=!1,this._zooming=!1,this._rotating=!1,this._pitching=!1,this._padding=!1,n&&this.fire(new t.Event(\"zoomend\",e)),i&&this.fire(new t.Event(\"rotateend\",e)),a&&this.fire(new t.Event(\"pitchend\",e)),this.fire(new t.Event(\"moveend\",e))}},r.prototype.flyTo=function(e,r){var n=this;if(!e.essential&&t.browser.prefersReducedMotion){var i=t.pick(e,[\"center\",\"zoom\",\"bearing\",\"pitch\",\"around\"]);return this.jumpTo(i,r)}this.stop(),e=t.extend({offset:[0,0],speed:1.2,curve:1.42,easing:t.ease},e);var a=this.transform,o=this.getZoom(),s=this.getBearing(),l=this.getPitch(),c=this.getPadding(),u=\"zoom\"in e?t.clamp(+e.zoom,a.minZoom,a.maxZoom):o,f=\"bearing\"in e?this._normalizeBearing(e.bearing,s):s,h=\"pitch\"in e?+e.pitch:l,p=\"padding\"in e?e.padding:a.padding,d=a.zoomScale(u-o),m=t.Point.convert(e.offset),g=a.centerPoint.add(m),v=a.pointLocation(g),y=t.LngLat.convert(e.center||v);this._normalizeCenter(y);var x=a.project(v),b=a.project(y).sub(x),_=e.curve,w=Math.max(a.width,a.height),T=w/d,k=b.mag();if(\"minZoom\"in e){var A=t.clamp(Math.min(e.minZoom,o,u),a.minZoom,a.maxZoom),M=w/a.zoomScale(A-o);_=Math.sqrt(M/k*2)}var S=_*_;function E(t){var e=(T*T-w*w+(t?-1:1)*S*S*k*k)/(2*(t?T:w)*S*k);return Math.log(Math.sqrt(e*e+1)-e)}function L(t){return(Math.exp(t)-Math.exp(-t))/2}function C(t){return(Math.exp(t)+Math.exp(-t))/2}var P=E(0),I=function(t){return C(P)/C(P+_*t)},O=function(t){return w*((C(P)*(L(e=P+_*t)/C(e))-L(P))/S)/k;var e},z=(E(1)-P)/_;if(Math.abs(k)<1e-6||!isFinite(z)){if(Math.abs(w-T)<1e-6)return this.easeTo(e,r);var D=T<w?-1:1;z=Math.abs(Math.log(T/w))/_,O=function(){return 0},I=function(t){return Math.exp(D*_*t)}}if(\"duration\"in e)e.duration=+e.duration;else{var R=\"screenSpeed\"in e?+e.screenSpeed/_:+e.speed;e.duration=1e3*z/R}return e.maxDuration&&e.duration>e.maxDuration&&(e.duration=0),this._zooming=!0,this._rotating=s!==f,this._pitching=h!==l,this._padding=!a.isPaddingEqual(p),this._prepareEase(r,!1),this._ease((function(e){var i=e*z,d=1/I(i);a.zoom=1===e?u:o+a.scaleZoom(d),n._rotating&&(a.bearing=t.number(s,f,e)),n._pitching&&(a.pitch=t.number(l,h,e)),n._padding&&(a.interpolatePadding(c,p,e),g=a.centerPoint.add(m));var v=1===e?y:a.unproject(x.add(b.mult(O(i))).mult(d));a.setLocationAtPoint(a.renderWorldCopies?v.wrap():v,g),n._fireMoveEvents(r)}),(function(){return n._afterEase(r)}),e),this},r.prototype.isEasing=function(){return!!this._easeFrameId},r.prototype.stop=function(){return this._stop()},r.prototype._stop=function(t,e){if(this._easeFrameId&&(this._cancelRenderFrame(this._easeFrameId),delete this._easeFrameId,delete this._onEaseFrame),this._onEaseEnd){var r=this._onEaseEnd;delete this._onEaseEnd,r.call(this,e)}if(!t){var n=this.handlers;n&&n.stop()}return this},r.prototype._ease=function(e,r,n){!1===n.animate||0===n.duration?(e(1),r()):(this._easeStart=t.browser.now(),this._easeOptions=n,this._onEaseFrame=e,this._onEaseEnd=r,this._easeFrameId=this._requestRenderFrame(this._renderFrameCallback))},r.prototype._renderFrameCallback=function(){var e=Math.min((t.browser.now()-this._easeStart)/this._easeOptions.duration,1);this._onEaseFrame(this._easeOptions.easing(e)),e<1?this._easeFrameId=this._requestRenderFrame(this._renderFrameCallback):this.stop()},r.prototype._normalizeBearing=function(e,r){e=t.wrap(e,-180,180);var n=Math.abs(e-r);return Math.abs(e-360-r)<n&&(e-=360),Math.abs(e+360-r)<n&&(e+=360),e},r.prototype._normalizeCenter=function(t){var e=this.transform;if(e.renderWorldCopies&&!e.lngRange){var r=t.lng-e.center.lng;t.lng+=r>180?-360:r<-180?360:0}},r}(t.Evented),bi=function(e){void 0===e&&(e={}),this.options=e,t.bindAll([\"_updateEditLink\",\"_updateData\",\"_updateCompact\"],this)};bi.prototype.getDefaultPosition=function(){return\"bottom-right\"},bi.prototype.onAdd=function(t){var e=this.options&&this.options.compact;return this._map=t,this._container=r.create(\"div\",\"mapboxgl-ctrl mapboxgl-ctrl-attrib\"),this._innerContainer=r.create(\"div\",\"mapboxgl-ctrl-attrib-inner\",this._container),e&&this._container.classList.add(\"mapboxgl-compact\"),this._updateAttributions(),this._updateEditLink(),this._map.on(\"styledata\",this._updateData),this._map.on(\"sourcedata\",this._updateData),this._map.on(\"moveend\",this._updateEditLink),void 0===e&&(this._map.on(\"resize\",this._updateCompact),this._updateCompact()),this._container},bi.prototype.onRemove=function(){r.remove(this._container),this._map.off(\"styledata\",this._updateData),this._map.off(\"sourcedata\",this._updateData),this._map.off(\"moveend\",this._updateEditLink),this._map.off(\"resize\",this._updateCompact),this._map=void 0,this._attribHTML=void 0},bi.prototype._updateEditLink=function(){var e=this._editLink;e||(e=this._editLink=this._container.querySelector(\".mapbox-improve-map\"));var r=[{key:\"owner\",value:this.styleOwner},{key:\"id\",value:this.styleId},{key:\"access_token\",value:this._map._requestManager._customAccessToken||t.config.ACCESS_TOKEN}];if(e){var n=r.reduce((function(t,e,n){return e.value&&(t+=e.key+\"=\"+e.value+(n<r.length-1?\"&\":\"\")),t}),\"?\");e.href=t.config.FEEDBACK_URL+\"/\"+n+(this._map._hash?this._map._hash.getHashString(!0):\"\"),e.rel=\"noopener nofollow\"}},bi.prototype._updateData=function(t){!t||\"metadata\"!==t.sourceDataType&&\"style\"!==t.dataType||(this._updateAttributions(),this._updateEditLink())},bi.prototype._updateAttributions=function(){if(this._map.style){var t=[];if(this.options.customAttribution&&(Array.isArray(this.options.customAttribution)?t=t.concat(this.options.customAttribution.map((function(t){return\"string\"!=typeof t?\"\":t}))):\"string\"==typeof this.options.customAttribution&&t.push(this.options.customAttribution)),this._map.style.stylesheet){var e=this._map.style.stylesheet;this.styleOwner=e.owner,this.styleId=e.id}var r=this._map.style.sourceCaches;for(var n in r){var i=r[n];if(i.used){var a=i.getSource();a.attribution&&t.indexOf(a.attribution)<0&&t.push(a.attribution)}}t.sort((function(t,e){return t.length-e.length}));var o=(t=t.filter((function(e,r){for(var n=r+1;n<t.length;n++)if(t[n].indexOf(e)>=0)return!1;return!0}))).join(\" | \");o!==this._attribHTML&&(this._attribHTML=o,t.length?(this._innerContainer.innerHTML=o,this._container.classList.remove(\"mapboxgl-attrib-empty\")):this._container.classList.add(\"mapboxgl-attrib-empty\"),this._editLink=null)}},bi.prototype._updateCompact=function(){this._map.getCanvasContainer().offsetWidth<=640?this._container.classList.add(\"mapboxgl-compact\"):this._container.classList.remove(\"mapboxgl-compact\")};var _i=function(){t.bindAll([\"_updateLogo\"],this),t.bindAll([\"_updateCompact\"],this)};_i.prototype.onAdd=function(t){this._map=t,this._container=r.create(\"div\",\"mapboxgl-ctrl\");var e=r.create(\"a\",\"mapboxgl-ctrl-logo\");return e.target=\"_blank\",e.rel=\"noopener nofollow\",e.href=\"https://www.mapbox.com/\",e.setAttribute(\"aria-label\",this._map._getUIString(\"LogoControl.Title\")),e.setAttribute(\"rel\",\"noopener nofollow\"),this._container.appendChild(e),this._container.style.display=\"none\",this._map.on(\"sourcedata\",this._updateLogo),this._updateLogo(),this._map.on(\"resize\",this._updateCompact),this._updateCompact(),this._container},_i.prototype.onRemove=function(){r.remove(this._container),this._map.off(\"sourcedata\",this._updateLogo),this._map.off(\"resize\",this._updateCompact)},_i.prototype.getDefaultPosition=function(){return\"bottom-left\"},_i.prototype._updateLogo=function(t){t&&\"metadata\"!==t.sourceDataType||(this._container.style.display=this._logoRequired()?\"block\":\"none\")},_i.prototype._logoRequired=function(){if(this._map.style){var t=this._map.style.sourceCaches;for(var e in t){if(t[e].getSource().mapbox_logo)return!0}return!1}},_i.prototype._updateCompact=function(){var t=this._container.children;if(t.length){var e=t[0];this._map.getCanvasContainer().offsetWidth<250?e.classList.add(\"mapboxgl-compact\"):e.classList.remove(\"mapboxgl-compact\")}};var wi=function(){this._queue=[],this._id=0,this._cleared=!1,this._currentlyRunning=!1};wi.prototype.add=function(t){var e=++this._id;return this._queue.push({callback:t,id:e,cancelled:!1}),e},wi.prototype.remove=function(t){for(var e=this._currentlyRunning,r=0,n=e?this._queue.concat(e):this._queue;r<n.length;r+=1){var i=n[r];if(i.id===t)return void(i.cancelled=!0)}},wi.prototype.run=function(t){void 0===t&&(t=0);var e=this._currentlyRunning=this._queue;this._queue=[];for(var r=0,n=e;r<n.length;r+=1){var i=n[r];if(!i.cancelled&&(i.callback(t),this._cleared))break}this._cleared=!1,this._currentlyRunning=!1},wi.prototype.clear=function(){this._currentlyRunning&&(this._cleared=!0),this._queue=[]};var Ti={\"FullscreenControl.Enter\":\"Enter fullscreen\",\"FullscreenControl.Exit\":\"Exit fullscreen\",\"GeolocateControl.FindMyLocation\":\"Find my location\",\"GeolocateControl.LocationNotAvailable\":\"Location not available\",\"LogoControl.Title\":\"Mapbox logo\",\"NavigationControl.ResetBearing\":\"Reset bearing to north\",\"NavigationControl.ZoomIn\":\"Zoom in\",\"NavigationControl.ZoomOut\":\"Zoom out\",\"ScaleControl.Feet\":\"ft\",\"ScaleControl.Meters\":\"m\",\"ScaleControl.Kilometers\":\"km\",\"ScaleControl.Miles\":\"mi\",\"ScaleControl.NauticalMiles\":\"nm\"},ki=t.window.HTMLImageElement,Ai=t.window.HTMLElement,Mi=t.window.ImageBitmap,Si={center:[0,0],zoom:0,bearing:0,pitch:0,minZoom:-2,maxZoom:22,minPitch:0,maxPitch:60,interactive:!0,scrollZoom:!0,boxZoom:!0,dragRotate:!0,dragPan:!0,keyboard:!0,doubleClickZoom:!0,touchZoomRotate:!0,touchPitch:!0,bearingSnap:7,clickTolerance:3,pitchWithRotate:!0,hash:!1,attributionControl:!0,failIfMajorPerformanceCaveat:!1,preserveDrawingBuffer:!1,trackResize:!0,renderWorldCopies:!0,refreshExpiredTiles:!0,maxTileCacheSize:null,localIdeographFontFamily:\"sans-serif\",transformRequest:null,accessToken:null,fadeDuration:300,crossSourceCollisions:!0},Ei=function(n){function i(e){var r=this;if(null!=(e=t.extend({},Si,e)).minZoom&&null!=e.maxZoom&&e.minZoom>e.maxZoom)throw new Error(\"maxZoom must be greater than or equal to minZoom\");if(null!=e.minPitch&&null!=e.maxPitch&&e.minPitch>e.maxPitch)throw new Error(\"maxPitch must be greater than or equal to minPitch\");if(null!=e.minPitch&&e.minPitch<0)throw new Error(\"minPitch must be greater than or equal to 0\");if(null!=e.maxPitch&&e.maxPitch>60)throw new Error(\"maxPitch must be less than or equal to 60\");var i=new An(e.minZoom,e.maxZoom,e.minPitch,e.maxPitch,e.renderWorldCopies);if(n.call(this,i,e),this._interactive=e.interactive,this._maxTileCacheSize=e.maxTileCacheSize,this._failIfMajorPerformanceCaveat=e.failIfMajorPerformanceCaveat,this._preserveDrawingBuffer=e.preserveDrawingBuffer,this._antialias=e.antialias,this._trackResize=e.trackResize,this._bearingSnap=e.bearingSnap,this._refreshExpiredTiles=e.refreshExpiredTiles,this._fadeDuration=e.fadeDuration,this._crossSourceCollisions=e.crossSourceCollisions,this._crossFadingFactor=1,this._collectResourceTiming=e.collectResourceTiming,this._renderTaskQueue=new wi,this._controls=[],this._mapId=t.uniqueId(),this._locale=t.extend({},Ti,e.locale),this._requestManager=new t.RequestManager(e.transformRequest,e.accessToken),\"string\"==typeof e.container){if(this._container=t.window.document.getElementById(e.container),!this._container)throw new Error(\"Container '\"+e.container+\"' not found.\")}else{if(!(e.container instanceof Ai))throw new Error(\"Invalid type: 'container' must be a String or HTMLElement.\");this._container=e.container}if(e.maxBounds&&this.setMaxBounds(e.maxBounds),t.bindAll([\"_onWindowOnline\",\"_onWindowResize\",\"_contextLost\",\"_contextRestored\"],this),this._setupContainer(),this._setupPainter(),void 0===this.painter)throw new Error(\"Failed to initialize WebGL.\");this.on(\"move\",(function(){return r._update(!1)})),this.on(\"moveend\",(function(){return r._update(!1)})),this.on(\"zoom\",(function(){return r._update(!0)})),void 0!==t.window&&(t.window.addEventListener(\"online\",this._onWindowOnline,!1),t.window.addEventListener(\"resize\",this._onWindowResize,!1)),this.handlers=new yi(this,e);var a=\"string\"==typeof e.hash&&e.hash||void 0;this._hash=e.hash&&new Sn(a).addTo(this),this._hash&&this._hash._onHashChange()||(this.jumpTo({center:e.center,zoom:e.zoom,bearing:e.bearing,pitch:e.pitch}),e.bounds&&(this.resize(),this.fitBounds(e.bounds,t.extend({},e.fitBoundsOptions,{duration:0})))),this.resize(),this._localIdeographFontFamily=e.localIdeographFontFamily,e.style&&this.setStyle(e.style,{localIdeographFontFamily:e.localIdeographFontFamily}),e.attributionControl&&this.addControl(new bi({customAttribution:e.customAttribution})),this.addControl(new _i,e.logoPosition),this.on(\"style.load\",(function(){r.transform.unmodified&&r.jumpTo(r.style.stylesheet)})),this.on(\"data\",(function(e){r._update(\"style\"===e.dataType),r.fire(new t.Event(e.dataType+\"data\",e))})),this.on(\"dataloading\",(function(e){r.fire(new t.Event(e.dataType+\"dataloading\",e))}))}n&&(i.__proto__=n),i.prototype=Object.create(n&&n.prototype),i.prototype.constructor=i;var a={showTileBoundaries:{configurable:!0},showPadding:{configurable:!0},showCollisionBoxes:{configurable:!0},showOverdrawInspector:{configurable:!0},repaint:{configurable:!0},vertices:{configurable:!0},version:{configurable:!0}};return i.prototype._getMapId=function(){return this._mapId},i.prototype.addControl=function(e,r){if(void 0===r&&e.getDefaultPosition&&(r=e.getDefaultPosition()),void 0===r&&(r=\"top-right\"),!e||!e.onAdd)return this.fire(new t.ErrorEvent(new Error(\"Invalid argument to map.addControl(). Argument must be a control with onAdd and onRemove methods.\")));var n=e.onAdd(this);this._controls.push(e);var i=this._controlPositions[r];return-1!==r.indexOf(\"bottom\")?i.insertBefore(n,i.firstChild):i.appendChild(n),this},i.prototype.removeControl=function(e){if(!e||!e.onRemove)return this.fire(new t.ErrorEvent(new Error(\"Invalid argument to map.removeControl(). Argument must be a control with onAdd and onRemove methods.\")));var r=this._controls.indexOf(e);return r>-1&&this._controls.splice(r,1),e.onRemove(this),this},i.prototype.resize=function(e){var r=this._containerDimensions(),n=r[0],i=r[1];this._resizeCanvas(n,i),this.transform.resize(n,i),this.painter.resize(n,i);var a=!this._moving;return a&&(this.stop(),this.fire(new t.Event(\"movestart\",e)).fire(new t.Event(\"move\",e))),this.fire(new t.Event(\"resize\",e)),a&&this.fire(new t.Event(\"moveend\",e)),this},i.prototype.getBounds=function(){return this.transform.getBounds()},i.prototype.getMaxBounds=function(){return this.transform.getMaxBounds()},i.prototype.setMaxBounds=function(e){return this.transform.setMaxBounds(t.LngLatBounds.convert(e)),this._update()},i.prototype.setMinZoom=function(t){if((t=null==t?-2:t)>=-2&&t<=this.transform.maxZoom)return this.transform.minZoom=t,this._update(),this.getZoom()<t&&this.setZoom(t),this;throw new Error(\"minZoom must be between -2 and the current maxZoom, inclusive\")},i.prototype.getMinZoom=function(){return this.transform.minZoom},i.prototype.setMaxZoom=function(t){if((t=null==t?22:t)>=this.transform.minZoom)return this.transform.maxZoom=t,this._update(),this.getZoom()>t&&this.setZoom(t),this;throw new Error(\"maxZoom must be greater than the current minZoom\")},i.prototype.getMaxZoom=function(){return this.transform.maxZoom},i.prototype.setMinPitch=function(t){if((t=null==t?0:t)<0)throw new Error(\"minPitch must be greater than or equal to 0\");if(t>=0&&t<=this.transform.maxPitch)return this.transform.minPitch=t,this._update(),this.getPitch()<t&&this.setPitch(t),this;throw new Error(\"minPitch must be between 0 and the current maxPitch, inclusive\")},i.prototype.getMinPitch=function(){return this.transform.minPitch},i.prototype.setMaxPitch=function(t){if((t=null==t?60:t)>60)throw new Error(\"maxPitch must be less than or equal to 60\");if(t>=this.transform.minPitch)return this.transform.maxPitch=t,this._update(),this.getPitch()>t&&this.setPitch(t),this;throw new Error(\"maxPitch must be greater than the current minPitch\")},i.prototype.getMaxPitch=function(){return this.transform.maxPitch},i.prototype.getRenderWorldCopies=function(){return this.transform.renderWorldCopies},i.prototype.setRenderWorldCopies=function(t){return this.transform.renderWorldCopies=t,this._update()},i.prototype.project=function(e){return this.transform.locationPoint(t.LngLat.convert(e))},i.prototype.unproject=function(e){return this.transform.pointLocation(t.Point.convert(e))},i.prototype.isMoving=function(){return this._moving||this.handlers.isMoving()},i.prototype.isZooming=function(){return this._zooming||this.handlers.isZooming()},i.prototype.isRotating=function(){return this._rotating||this.handlers.isRotating()},i.prototype._createDelegatedListener=function(t,e,r){var n,i=this;if(\"mouseenter\"===t||\"mouseover\"===t){var a=!1;return{layer:e,listener:r,delegates:{mousemove:function(n){var o=i.getLayer(e)?i.queryRenderedFeatures(n.point,{layers:[e]}):[];o.length?a||(a=!0,r.call(i,new Rn(t,i,n.originalEvent,{features:o}))):a=!1},mouseout:function(){a=!1}}}}if(\"mouseleave\"===t||\"mouseout\"===t){var o=!1;return{layer:e,listener:r,delegates:{mousemove:function(n){(i.getLayer(e)?i.queryRenderedFeatures(n.point,{layers:[e]}):[]).length?o=!0:o&&(o=!1,r.call(i,new Rn(t,i,n.originalEvent)))},mouseout:function(e){o&&(o=!1,r.call(i,new Rn(t,i,e.originalEvent)))}}}}return{layer:e,listener:r,delegates:(n={},n[t]=function(t){var n=i.getLayer(e)?i.queryRenderedFeatures(t.point,{layers:[e]}):[];n.length&&(t.features=n,r.call(i,t),delete t.features)},n)}},i.prototype.on=function(t,e,r){if(void 0===r)return n.prototype.on.call(this,t,e);var i=this._createDelegatedListener(t,e,r);for(var a in this._delegatedListeners=this._delegatedListeners||{},this._delegatedListeners[t]=this._delegatedListeners[t]||[],this._delegatedListeners[t].push(i),i.delegates)this.on(a,i.delegates[a]);return this},i.prototype.once=function(t,e,r){if(void 0===r)return n.prototype.once.call(this,t,e);var i=this._createDelegatedListener(t,e,r);for(var a in i.delegates)this.once(a,i.delegates[a]);return this},i.prototype.off=function(t,e,r){var i=this;if(void 0===r)return n.prototype.off.call(this,t,e);return this._delegatedListeners&&this._delegatedListeners[t]&&function(n){for(var a=n[t],o=0;o<a.length;o++){var s=a[o];if(s.layer===e&&s.listener===r){for(var l in s.delegates)i.off(l,s.delegates[l]);return a.splice(o,1),i}}}(this._delegatedListeners),this},i.prototype.queryRenderedFeatures=function(e,r){if(!this.style)return[];var n;if(void 0!==r||void 0===e||e instanceof t.Point||Array.isArray(e)||(r=e,e=void 0),r=r||{},(e=e||[[0,0],[this.transform.width,this.transform.height]])instanceof t.Point||\"number\"==typeof e[0])n=[t.Point.convert(e)];else{var i=t.Point.convert(e[0]),a=t.Point.convert(e[1]);n=[i,new t.Point(a.x,i.y),a,new t.Point(i.x,a.y),i]}return this.style.queryRenderedFeatures(n,r,this.transform)},i.prototype.querySourceFeatures=function(t,e){return this.style.querySourceFeatures(t,e)},i.prototype.setStyle=function(e,r){return!1!==(r=t.extend({},{localIdeographFontFamily:this._localIdeographFontFamily},r)).diff&&r.localIdeographFontFamily===this._localIdeographFontFamily&&this.style&&e?(this._diffStyle(e,r),this):(this._localIdeographFontFamily=r.localIdeographFontFamily,this._updateStyle(e,r))},i.prototype._getUIString=function(t){var e=this._locale[t];if(null==e)throw new Error(\"Missing UI string '\"+t+\"'\");return e},i.prototype._updateStyle=function(t,e){return this.style&&(this.style.setEventedParent(null),this.style._remove()),t?(this.style=new qe(this,e||{}),this.style.setEventedParent(this,{style:this.style}),\"string\"==typeof t?this.style.loadURL(t):this.style.loadJSON(t),this):(delete this.style,this)},i.prototype._lazyInitEmptyStyle=function(){this.style||(this.style=new qe(this,{}),this.style.setEventedParent(this,{style:this.style}),this.style.loadEmpty())},i.prototype._diffStyle=function(e,r){var n=this;if(\"string\"==typeof e){var i=this._requestManager.normalizeStyleURL(e),a=this._requestManager.transformRequest(i,t.ResourceType.Style);t.getJSON(a,(function(e,i){e?n.fire(new t.ErrorEvent(e)):i&&n._updateDiff(i,r)}))}else\"object\"==typeof e&&this._updateDiff(e,r)},i.prototype._updateDiff=function(e,r){try{this.style.setState(e)&&this._update(!0)}catch(n){t.warnOnce(\"Unable to perform style diff: \"+(n.message||n.error||n)+\". Rebuilding the style from scratch.\"),this._updateStyle(e,r)}},i.prototype.getStyle=function(){if(this.style)return this.style.serialize()},i.prototype.isStyleLoaded=function(){return this.style?this.style.loaded():t.warnOnce(\"There is no style added to the map.\")},i.prototype.addSource=function(t,e){return this._lazyInitEmptyStyle(),this.style.addSource(t,e),this._update(!0)},i.prototype.isSourceLoaded=function(e){var r=this.style&&this.style.sourceCaches[e];if(void 0!==r)return r.loaded();this.fire(new t.ErrorEvent(new Error(\"There is no source with ID '\"+e+\"'\")))},i.prototype.areTilesLoaded=function(){var t=this.style&&this.style.sourceCaches;for(var e in t){var r=t[e]._tiles;for(var n in r){var i=r[n];if(\"loaded\"!==i.state&&\"errored\"!==i.state)return!1}}return!0},i.prototype.addSourceType=function(t,e,r){return this._lazyInitEmptyStyle(),this.style.addSourceType(t,e,r)},i.prototype.removeSource=function(t){return this.style.removeSource(t),this._update(!0)},i.prototype.getSource=function(t){return this.style.getSource(t)},i.prototype.addImage=function(e,r,n){void 0===n&&(n={});var i=n.pixelRatio;void 0===i&&(i=1);var a=n.sdf;void 0===a&&(a=!1);var o=n.stretchX,s=n.stretchY,l=n.content;this._lazyInitEmptyStyle();if(r instanceof ki||Mi&&r instanceof Mi){var c=t.browser.getImageData(r),u=c.width,f=c.height,h=c.data;this.style.addImage(e,{data:new t.RGBAImage({width:u,height:f},h),pixelRatio:i,stretchX:o,stretchY:s,content:l,sdf:a,version:0})}else{if(void 0===r.width||void 0===r.height)return this.fire(new t.ErrorEvent(new Error(\"Invalid arguments to map.addImage(). The second argument must be an `HTMLImageElement`, `ImageData`, `ImageBitmap`, or object with `width`, `height`, and `data` properties with the same format as `ImageData`\")));var p=r.width,d=r.height,m=r.data,g=r;this.style.addImage(e,{data:new t.RGBAImage({width:p,height:d},new Uint8Array(m)),pixelRatio:i,stretchX:o,stretchY:s,content:l,sdf:a,version:0,userImage:g}),g.onAdd&&g.onAdd(this,e)}},i.prototype.updateImage=function(e,r){var n=this.style.getImage(e);if(!n)return this.fire(new t.ErrorEvent(new Error(\"The map has no image with that id. If you are adding a new image use `map.addImage(...)` instead.\")));var i=r instanceof ki||Mi&&r instanceof Mi?t.browser.getImageData(r):r,a=i.width,o=i.height,s=i.data;if(void 0===a||void 0===o)return this.fire(new t.ErrorEvent(new Error(\"Invalid arguments to map.updateImage(). The second argument must be an `HTMLImageElement`, `ImageData`, `ImageBitmap`, or object with `width`, `height`, and `data` properties with the same format as `ImageData`\")));if(a!==n.data.width||o!==n.data.height)return this.fire(new t.ErrorEvent(new Error(\"The width and height of the updated image must be that same as the previous version of the image\")));var l=!(r instanceof ki||Mi&&r instanceof Mi);n.data.replace(s,l),this.style.updateImage(e,n)},i.prototype.hasImage=function(e){return e?!!this.style.getImage(e):(this.fire(new t.ErrorEvent(new Error(\"Missing required image id\"))),!1)},i.prototype.removeImage=function(t){this.style.removeImage(t)},i.prototype.loadImage=function(e,r){t.getImage(this._requestManager.transformRequest(e,t.ResourceType.Image),r)},i.prototype.listImages=function(){return this.style.listImages()},i.prototype.addLayer=function(t,e){return this._lazyInitEmptyStyle(),this.style.addLayer(t,e),this._update(!0)},i.prototype.moveLayer=function(t,e){return this.style.moveLayer(t,e),this._update(!0)},i.prototype.removeLayer=function(t){return this.style.removeLayer(t),this._update(!0)},i.prototype.getLayer=function(t){return this.style.getLayer(t)},i.prototype.setLayerZoomRange=function(t,e,r){return this.style.setLayerZoomRange(t,e,r),this._update(!0)},i.prototype.setFilter=function(t,e,r){return void 0===r&&(r={}),this.style.setFilter(t,e,r),this._update(!0)},i.prototype.getFilter=function(t){return this.style.getFilter(t)},i.prototype.setPaintProperty=function(t,e,r,n){return void 0===n&&(n={}),this.style.setPaintProperty(t,e,r,n),this._update(!0)},i.prototype.getPaintProperty=function(t,e){return this.style.getPaintProperty(t,e)},i.prototype.setLayoutProperty=function(t,e,r,n){return void 0===n&&(n={}),this.style.setLayoutProperty(t,e,r,n),this._update(!0)},i.prototype.getLayoutProperty=function(t,e){return this.style.getLayoutProperty(t,e)},i.prototype.setLight=function(t,e){return void 0===e&&(e={}),this._lazyInitEmptyStyle(),this.style.setLight(t,e),this._update(!0)},i.prototype.getLight=function(){return this.style.getLight()},i.prototype.setFeatureState=function(t,e){return this.style.setFeatureState(t,e),this._update()},i.prototype.removeFeatureState=function(t,e){return this.style.removeFeatureState(t,e),this._update()},i.prototype.getFeatureState=function(t){return this.style.getFeatureState(t)},i.prototype.getContainer=function(){return this._container},i.prototype.getCanvasContainer=function(){return this._canvasContainer},i.prototype.getCanvas=function(){return this._canvas},i.prototype._containerDimensions=function(){var t=0,e=0;return this._container&&(t=this._container.clientWidth||400,e=this._container.clientHeight||300),[t,e]},i.prototype._detectMissingCSS=function(){\"rgb(250, 128, 114)\"!==t.window.getComputedStyle(this._missingCSSCanary).getPropertyValue(\"background-color\")&&t.warnOnce(\"This page appears to be missing CSS declarations for Mapbox GL JS, which may cause the map to display incorrectly. Please ensure your page includes mapbox-gl.css, as described in https://www.mapbox.com/mapbox-gl-js/api/.\")},i.prototype._setupContainer=function(){var t=this._container;t.classList.add(\"mapboxgl-map\"),(this._missingCSSCanary=r.create(\"div\",\"mapboxgl-canary\",t)).style.visibility=\"hidden\",this._detectMissingCSS();var e=this._canvasContainer=r.create(\"div\",\"mapboxgl-canvas-container\",t);this._interactive&&e.classList.add(\"mapboxgl-interactive\"),this._canvas=r.create(\"canvas\",\"mapboxgl-canvas\",e),this._canvas.addEventListener(\"webglcontextlost\",this._contextLost,!1),this._canvas.addEventListener(\"webglcontextrestored\",this._contextRestored,!1),this._canvas.setAttribute(\"tabindex\",\"0\"),this._canvas.setAttribute(\"aria-label\",\"Map\");var n=this._containerDimensions();this._resizeCanvas(n[0],n[1]);var i=this._controlContainer=r.create(\"div\",\"mapboxgl-control-container\",t),a=this._controlPositions={};[\"top-left\",\"top-right\",\"bottom-left\",\"bottom-right\"].forEach((function(t){a[t]=r.create(\"div\",\"mapboxgl-ctrl-\"+t,i)}))},i.prototype._resizeCanvas=function(e,r){var n=t.browser.devicePixelRatio||1;this._canvas.width=n*e,this._canvas.height=n*r,this._canvas.style.width=e+\"px\",this._canvas.style.height=r+\"px\"},i.prototype._setupPainter=function(){var r=t.extend({},e.webGLContextAttributes,{failIfMajorPerformanceCaveat:this._failIfMajorPerformanceCaveat,preserveDrawingBuffer:this._preserveDrawingBuffer,antialias:this._antialias||!1}),n=this._canvas.getContext(\"webgl\",r)||this._canvas.getContext(\"experimental-webgl\",r);n?(this.painter=new _n(n,this.transform),t.webpSupported.testSupport(n)):this.fire(new t.ErrorEvent(new Error(\"Failed to initialize WebGL\")))},i.prototype._contextLost=function(e){e.preventDefault(),this._frame&&(this._frame.cancel(),this._frame=null),this.fire(new t.Event(\"webglcontextlost\",{originalEvent:e}))},i.prototype._contextRestored=function(e){this._setupPainter(),this.resize(),this._update(),this.fire(new t.Event(\"webglcontextrestored\",{originalEvent:e}))},i.prototype.loaded=function(){return!this._styleDirty&&!this._sourcesDirty&&!!this.style&&this.style.loaded()},i.prototype._update=function(t){return this.style?(this._styleDirty=this._styleDirty||t,this._sourcesDirty=!0,this.triggerRepaint(),this):this},i.prototype._requestRenderFrame=function(t){return this._update(),this._renderTaskQueue.add(t)},i.prototype._cancelRenderFrame=function(t){this._renderTaskQueue.remove(t)},i.prototype._render=function(e){var r,n=this,i=0,a=this.painter.context.extTimerQuery;if(this.listens(\"gpu-timing-frame\")&&(r=a.createQueryEXT(),a.beginQueryEXT(a.TIME_ELAPSED_EXT,r),i=t.browser.now()),this.painter.context.setDirty(),this.painter.setBaseState(),this._renderTaskQueue.run(e),!this._removed){var o=!1;if(this.style&&this._styleDirty){this._styleDirty=!1;var s=this.transform.zoom,l=t.browser.now();this.style.zoomHistory.update(s,l);var c=new t.EvaluationParameters(s,{now:l,fadeDuration:this._fadeDuration,zoomHistory:this.style.zoomHistory,transition:this.style.getTransition()}),u=c.crossFadingFactor();1===u&&u===this._crossFadingFactor||(o=!0,this._crossFadingFactor=u),this.style.update(c)}if(this.style&&this._sourcesDirty&&(this._sourcesDirty=!1,this.style._updateSources(this.transform)),this._placementDirty=this.style&&this.style._updatePlacement(this.painter.transform,this.showCollisionBoxes,this._fadeDuration,this._crossSourceCollisions),this.painter.render(this.style,{showTileBoundaries:this.showTileBoundaries,showOverdrawInspector:this._showOverdrawInspector,rotating:this.isRotating(),zooming:this.isZooming(),moving:this.isMoving(),fadeDuration:this._fadeDuration,showPadding:this.showPadding,gpuTiming:!!this.listens(\"gpu-timing-layer\")}),this.fire(new t.Event(\"render\")),this.loaded()&&!this._loaded&&(this._loaded=!0,this.fire(new t.Event(\"load\"))),this.style&&(this.style.hasTransitions()||o)&&(this._styleDirty=!0),this.style&&!this._placementDirty&&this.style._releaseSymbolFadeTiles(),this.listens(\"gpu-timing-frame\")){var f=t.browser.now()-i;a.endQueryEXT(a.TIME_ELAPSED_EXT,r),setTimeout((function(){var e=a.getQueryObjectEXT(r,a.QUERY_RESULT_EXT)/1e6;a.deleteQueryEXT(r),n.fire(new t.Event(\"gpu-timing-frame\",{cpuTime:f,gpuTime:e}))}),50)}if(this.listens(\"gpu-timing-layer\")){var h=this.painter.collectGpuTimers();setTimeout((function(){var e=n.painter.queryGpuTimers(h);n.fire(new t.Event(\"gpu-timing-layer\",{layerTimes:e}))}),50)}return this._sourcesDirty||this._styleDirty||this._placementDirty||this._repaint?this.triggerRepaint():!this.isMoving()&&this.loaded()&&(this._fullyLoaded||(this._fullyLoaded=!0),this.fire(new t.Event(\"idle\"))),this}},i.prototype.remove=function(){this._hash&&this._hash.remove();for(var e=0,r=this._controls;e<r.length;e+=1){r[e].onRemove(this)}this._controls=[],this._frame&&(this._frame.cancel(),this._frame=null),this._renderTaskQueue.clear(),this.painter.destroy(),this.handlers.destroy(),delete this.handlers,this.setStyle(null),void 0!==t.window&&(t.window.removeEventListener(\"resize\",this._onWindowResize,!1),t.window.removeEventListener(\"online\",this._onWindowOnline,!1));var n=this.painter.context.gl.getExtension(\"WEBGL_lose_context\");n&&n.loseContext(),Li(this._canvasContainer),Li(this._controlContainer),Li(this._missingCSSCanary),this._container.classList.remove(\"mapboxgl-map\"),this._removed=!0,this.fire(new t.Event(\"remove\"))},i.prototype.triggerRepaint=function(){var e=this;this.style&&!this._frame&&(this._frame=t.browser.frame((function(t){e._frame=null,e._render(t)})))},i.prototype._onWindowOnline=function(){this._update()},i.prototype._onWindowResize=function(t){this._trackResize&&this.resize({originalEvent:t})._update()},a.showTileBoundaries.get=function(){return!!this._showTileBoundaries},a.showTileBoundaries.set=function(t){this._showTileBoundaries!==t&&(this._showTileBoundaries=t,this._update())},a.showPadding.get=function(){return!!this._showPadding},a.showPadding.set=function(t){this._showPadding!==t&&(this._showPadding=t,this._update())},a.showCollisionBoxes.get=function(){return!!this._showCollisionBoxes},a.showCollisionBoxes.set=function(t){this._showCollisionBoxes!==t&&(this._showCollisionBoxes=t,t?this.style._generateCollisionBoxes():this._update())},a.showOverdrawInspector.get=function(){return!!this._showOverdrawInspector},a.showOverdrawInspector.set=function(t){this._showOverdrawInspector!==t&&(this._showOverdrawInspector=t,this._update())},a.repaint.get=function(){return!!this._repaint},a.repaint.set=function(t){this._repaint!==t&&(this._repaint=t,this.triggerRepaint())},a.vertices.get=function(){return!!this._vertices},a.vertices.set=function(t){this._vertices=t,this._update()},i.prototype._setCacheLimits=function(e,r){t.setCacheLimits(e,r)},a.version.get=function(){return t.version},Object.defineProperties(i.prototype,a),i}(xi);function Li(t){t.parentNode&&t.parentNode.removeChild(t)}var Ci={showCompass:!0,showZoom:!0,visualizePitch:!1},Pi=function(e){var n=this;this.options=t.extend({},Ci,e),this._container=r.create(\"div\",\"mapboxgl-ctrl mapboxgl-ctrl-group\"),this._container.addEventListener(\"contextmenu\",(function(t){return t.preventDefault()})),this.options.showZoom&&(t.bindAll([\"_setButtonTitle\",\"_updateZoomButtons\"],this),this._zoomInButton=this._createButton(\"mapboxgl-ctrl-zoom-in\",(function(t){return n._map.zoomIn({},{originalEvent:t})})),r.create(\"span\",\"mapboxgl-ctrl-icon\",this._zoomInButton).setAttribute(\"aria-hidden\",!0),this._zoomOutButton=this._createButton(\"mapboxgl-ctrl-zoom-out\",(function(t){return n._map.zoomOut({},{originalEvent:t})})),r.create(\"span\",\"mapboxgl-ctrl-icon\",this._zoomOutButton).setAttribute(\"aria-hidden\",!0)),this.options.showCompass&&(t.bindAll([\"_rotateCompassArrow\"],this),this._compass=this._createButton(\"mapboxgl-ctrl-compass\",(function(t){n.options.visualizePitch?n._map.resetNorthPitch({},{originalEvent:t}):n._map.resetNorth({},{originalEvent:t})})),this._compassIcon=r.create(\"span\",\"mapboxgl-ctrl-icon\",this._compass),this._compassIcon.setAttribute(\"aria-hidden\",!0))};Pi.prototype._updateZoomButtons=function(){var t=this._map.getZoom();this._zoomInButton.disabled=t===this._map.getMaxZoom(),this._zoomOutButton.disabled=t===this._map.getMinZoom()},Pi.prototype._rotateCompassArrow=function(){var t=this.options.visualizePitch?\"scale(\"+1/Math.pow(Math.cos(this._map.transform.pitch*(Math.PI/180)),.5)+\") rotateX(\"+this._map.transform.pitch+\"deg) rotateZ(\"+this._map.transform.angle*(180/Math.PI)+\"deg)\":\"rotate(\"+this._map.transform.angle*(180/Math.PI)+\"deg)\";this._compassIcon.style.transform=t},Pi.prototype.onAdd=function(t){return this._map=t,this.options.showZoom&&(this._setButtonTitle(this._zoomInButton,\"ZoomIn\"),this._setButtonTitle(this._zoomOutButton,\"ZoomOut\"),this._map.on(\"zoom\",this._updateZoomButtons),this._updateZoomButtons()),this.options.showCompass&&(this._setButtonTitle(this._compass,\"ResetBearing\"),this.options.visualizePitch&&this._map.on(\"pitch\",this._rotateCompassArrow),this._map.on(\"rotate\",this._rotateCompassArrow),this._rotateCompassArrow(),this._handler=new Ii(this._map,this._compass,this.options.visualizePitch)),this._container},Pi.prototype.onRemove=function(){r.remove(this._container),this.options.showZoom&&this._map.off(\"zoom\",this._updateZoomButtons),this.options.showCompass&&(this.options.visualizePitch&&this._map.off(\"pitch\",this._rotateCompassArrow),this._map.off(\"rotate\",this._rotateCompassArrow),this._handler.off(),delete this._handler),delete this._map},Pi.prototype._createButton=function(t,e){var n=r.create(\"button\",t,this._container);return n.type=\"button\",n.addEventListener(\"click\",e),n},Pi.prototype._setButtonTitle=function(t,e){var r=this._map._getUIString(\"NavigationControl.\"+e);t.title=r,t.setAttribute(\"aria-label\",r)};var Ii=function(e,n,i){void 0===i&&(i=!1),this._clickTolerance=10,this.element=n,this.mouseRotate=new Xn({clickTolerance:e.dragRotate._mouseRotate._clickTolerance}),this.map=e,i&&(this.mousePitch=new Zn({clickTolerance:e.dragRotate._mousePitch._clickTolerance})),t.bindAll([\"mousedown\",\"mousemove\",\"mouseup\",\"touchstart\",\"touchmove\",\"touchend\",\"reset\"],this),r.addEventListener(n,\"mousedown\",this.mousedown),r.addEventListener(n,\"touchstart\",this.touchstart,{passive:!1}),r.addEventListener(n,\"touchmove\",this.touchmove),r.addEventListener(n,\"touchend\",this.touchend),r.addEventListener(n,\"touchcancel\",this.reset)};function Oi(e,r,n){if(e=new t.LngLat(e.lng,e.lat),r){var i=new t.LngLat(e.lng-360,e.lat),a=new t.LngLat(e.lng+360,e.lat),o=n.locationPoint(e).distSqr(r);n.locationPoint(i).distSqr(r)<o?e=i:n.locationPoint(a).distSqr(r)<o&&(e=a)}for(;Math.abs(e.lng-n.center.lng)>180;){var s=n.locationPoint(e);if(s.x>=0&&s.y>=0&&s.x<=n.width&&s.y<=n.height)break;e.lng>n.center.lng?e.lng-=360:e.lng+=360}return e}Ii.prototype.down=function(t,e){this.mouseRotate.mousedown(t,e),this.mousePitch&&this.mousePitch.mousedown(t,e),r.disableDrag()},Ii.prototype.move=function(t,e){var r=this.map,n=this.mouseRotate.mousemoveWindow(t,e);if(n&&n.bearingDelta&&r.setBearing(r.getBearing()+n.bearingDelta),this.mousePitch){var i=this.mousePitch.mousemoveWindow(t,e);i&&i.pitchDelta&&r.setPitch(r.getPitch()+i.pitchDelta)}},Ii.prototype.off=function(){var t=this.element;r.removeEventListener(t,\"mousedown\",this.mousedown),r.removeEventListener(t,\"touchstart\",this.touchstart,{passive:!1}),r.removeEventListener(t,\"touchmove\",this.touchmove),r.removeEventListener(t,\"touchend\",this.touchend),r.removeEventListener(t,\"touchcancel\",this.reset),this.offTemp()},Ii.prototype.offTemp=function(){r.enableDrag(),r.removeEventListener(t.window,\"mousemove\",this.mousemove),r.removeEventListener(t.window,\"mouseup\",this.mouseup)},Ii.prototype.mousedown=function(e){this.down(t.extend({},e,{ctrlKey:!0,preventDefault:function(){return e.preventDefault()}}),r.mousePos(this.element,e)),r.addEventListener(t.window,\"mousemove\",this.mousemove),r.addEventListener(t.window,\"mouseup\",this.mouseup)},Ii.prototype.mousemove=function(t){this.move(t,r.mousePos(this.element,t))},Ii.prototype.mouseup=function(t){this.mouseRotate.mouseupWindow(t),this.mousePitch&&this.mousePitch.mouseupWindow(t),this.offTemp()},Ii.prototype.touchstart=function(t){1!==t.targetTouches.length?this.reset():(this._startPos=this._lastPos=r.touchPos(this.element,t.targetTouches)[0],this.down({type:\"mousedown\",button:0,ctrlKey:!0,preventDefault:function(){return t.preventDefault()}},this._startPos))},Ii.prototype.touchmove=function(t){1!==t.targetTouches.length?this.reset():(this._lastPos=r.touchPos(this.element,t.targetTouches)[0],this.move({preventDefault:function(){return t.preventDefault()}},this._lastPos))},Ii.prototype.touchend=function(t){0===t.targetTouches.length&&this._startPos&&this._lastPos&&this._startPos.dist(this._lastPos)<this._clickTolerance&&this.element.click(),this.reset()},Ii.prototype.reset=function(){this.mouseRotate.reset(),this.mousePitch&&this.mousePitch.reset(),delete this._startPos,delete this._lastPos,this.offTemp()};var zi={center:\"translate(-50%,-50%)\",top:\"translate(-50%,0)\",\"top-left\":\"translate(0,0)\",\"top-right\":\"translate(-100%,0)\",bottom:\"translate(-50%,-100%)\",\"bottom-left\":\"translate(0,-100%)\",\"bottom-right\":\"translate(-100%,-100%)\",left:\"translate(0,-50%)\",right:\"translate(-100%,-50%)\"};function Di(t,e,r){var n=t.classList;for(var i in zi)n.remove(\"mapboxgl-\"+r+\"-anchor-\"+i);n.add(\"mapboxgl-\"+r+\"-anchor-\"+e)}var Ri,Fi=function(e){function n(n,i){var a=this;if(e.call(this),(n instanceof t.window.HTMLElement||i)&&(n=t.extend({element:n},i)),t.bindAll([\"_update\",\"_onMove\",\"_onUp\",\"_addDragHandler\",\"_onMapClick\",\"_onKeyPress\"],this),this._anchor=n&&n.anchor||\"center\",this._color=n&&n.color||\"#3FB1CE\",this._draggable=n&&n.draggable||!1,this._state=\"inactive\",this._rotation=n&&n.rotation||0,this._rotationAlignment=n&&n.rotationAlignment||\"auto\",this._pitchAlignment=n&&n.pitchAlignment&&\"auto\"!==n.pitchAlignment?n.pitchAlignment:this._rotationAlignment,n&&n.element)this._element=n.element,this._offset=t.Point.convert(n&&n.offset||[0,0]);else{this._defaultMarker=!0,this._element=r.create(\"div\"),this._element.setAttribute(\"aria-label\",\"Map marker\");var o=r.createNS(\"http://www.w3.org/2000/svg\",\"svg\");o.setAttributeNS(null,\"display\",\"block\"),o.setAttributeNS(null,\"height\",\"41px\"),o.setAttributeNS(null,\"width\",\"27px\"),o.setAttributeNS(null,\"viewBox\",\"0 0 27 41\");var s=r.createNS(\"http://www.w3.org/2000/svg\",\"g\");s.setAttributeNS(null,\"stroke\",\"none\"),s.setAttributeNS(null,\"stroke-width\",\"1\"),s.setAttributeNS(null,\"fill\",\"none\"),s.setAttributeNS(null,\"fill-rule\",\"evenodd\");var l=r.createNS(\"http://www.w3.org/2000/svg\",\"g\");l.setAttributeNS(null,\"fill-rule\",\"nonzero\");var c=r.createNS(\"http://www.w3.org/2000/svg\",\"g\");c.setAttributeNS(null,\"transform\",\"translate(3.0, 29.0)\"),c.setAttributeNS(null,\"fill\",\"#000000\");for(var u=0,f=[{rx:\"10.5\",ry:\"5.25002273\"},{rx:\"10.5\",ry:\"5.25002273\"},{rx:\"9.5\",ry:\"4.77275007\"},{rx:\"8.5\",ry:\"4.29549936\"},{rx:\"7.5\",ry:\"3.81822308\"},{rx:\"6.5\",ry:\"3.34094679\"},{rx:\"5.5\",ry:\"2.86367051\"},{rx:\"4.5\",ry:\"2.38636864\"}];u<f.length;u+=1){var h=f[u],p=r.createNS(\"http://www.w3.org/2000/svg\",\"ellipse\");p.setAttributeNS(null,\"opacity\",\"0.04\"),p.setAttributeNS(null,\"cx\",\"10.5\"),p.setAttributeNS(null,\"cy\",\"5.80029008\"),p.setAttributeNS(null,\"rx\",h.rx),p.setAttributeNS(null,\"ry\",h.ry),c.appendChild(p)}var d=r.createNS(\"http://www.w3.org/2000/svg\",\"g\");d.setAttributeNS(null,\"fill\",this._color);var m=r.createNS(\"http://www.w3.org/2000/svg\",\"path\");m.setAttributeNS(null,\"d\",\"M27,13.5 C27,19.074644 20.250001,27.000002 14.75,34.500002 C14.016665,35.500004 12.983335,35.500004 12.25,34.500002 C6.7499993,27.000002 0,19.222562 0,13.5 C0,6.0441559 6.0441559,0 13.5,0 C20.955844,0 27,6.0441559 27,13.5 Z\"),d.appendChild(m);var g=r.createNS(\"http://www.w3.org/2000/svg\",\"g\");g.setAttributeNS(null,\"opacity\",\"0.25\"),g.setAttributeNS(null,\"fill\",\"#000000\");var v=r.createNS(\"http://www.w3.org/2000/svg\",\"path\");v.setAttributeNS(null,\"d\",\"M13.5,0 C6.0441559,0 0,6.0441559 0,13.5 C0,19.222562 6.7499993,27 12.25,34.5 C13,35.522727 14.016664,35.500004 14.75,34.5 C20.250001,27 27,19.074644 27,13.5 C27,6.0441559 20.955844,0 13.5,0 Z M13.5,1 C20.415404,1 26,6.584596 26,13.5 C26,15.898657 24.495584,19.181431 22.220703,22.738281 C19.945823,26.295132 16.705119,30.142167 13.943359,33.908203 C13.743445,34.180814 13.612715,34.322738 13.5,34.441406 C13.387285,34.322738 13.256555,34.180814 13.056641,33.908203 C10.284481,30.127985 7.4148684,26.314159 5.015625,22.773438 C2.6163816,19.232715 1,15.953538 1,13.5 C1,6.584596 6.584596,1 13.5,1 Z\"),g.appendChild(v);var y=r.createNS(\"http://www.w3.org/2000/svg\",\"g\");y.setAttributeNS(null,\"transform\",\"translate(6.0, 7.0)\"),y.setAttributeNS(null,\"fill\",\"#FFFFFF\");var x=r.createNS(\"http://www.w3.org/2000/svg\",\"g\");x.setAttributeNS(null,\"transform\",\"translate(8.0, 8.0)\");var b=r.createNS(\"http://www.w3.org/2000/svg\",\"circle\");b.setAttributeNS(null,\"fill\",\"#000000\"),b.setAttributeNS(null,\"opacity\",\"0.25\"),b.setAttributeNS(null,\"cx\",\"5.5\"),b.setAttributeNS(null,\"cy\",\"5.5\"),b.setAttributeNS(null,\"r\",\"5.4999962\");var _=r.createNS(\"http://www.w3.org/2000/svg\",\"circle\");_.setAttributeNS(null,\"fill\",\"#FFFFFF\"),_.setAttributeNS(null,\"cx\",\"5.5\"),_.setAttributeNS(null,\"cy\",\"5.5\"),_.setAttributeNS(null,\"r\",\"5.4999962\"),x.appendChild(b),x.appendChild(_),l.appendChild(c),l.appendChild(d),l.appendChild(g),l.appendChild(y),l.appendChild(x),o.appendChild(l),this._element.appendChild(o),this._offset=t.Point.convert(n&&n.offset||[0,-14])}this._element.classList.add(\"mapboxgl-marker\"),this._element.addEventListener(\"dragstart\",(function(t){t.preventDefault()})),this._element.addEventListener(\"mousedown\",(function(t){t.preventDefault()})),this._element.addEventListener(\"focus\",(function(){var t=a._map.getContainer();t.scrollTop=0,t.scrollLeft=0})),Di(this._element,this._anchor,\"marker\"),this._popup=null}return e&&(n.__proto__=e),n.prototype=Object.create(e&&e.prototype),n.prototype.constructor=n,n.prototype.addTo=function(t){return this.remove(),this._map=t,t.getCanvasContainer().appendChild(this._element),t.on(\"move\",this._update),t.on(\"moveend\",this._update),this.setDraggable(this._draggable),this._update(),this._map.on(\"click\",this._onMapClick),this},n.prototype.remove=function(){return this._map&&(this._map.off(\"click\",this._onMapClick),this._map.off(\"move\",this._update),this._map.off(\"moveend\",this._update),this._map.off(\"mousedown\",this._addDragHandler),this._map.off(\"touchstart\",this._addDragHandler),this._map.off(\"mouseup\",this._onUp),this._map.off(\"touchend\",this._onUp),this._map.off(\"mousemove\",this._onMove),this._map.off(\"touchmove\",this._onMove),delete this._map),r.remove(this._element),this._popup&&this._popup.remove(),this},n.prototype.getLngLat=function(){return this._lngLat},n.prototype.setLngLat=function(e){return this._lngLat=t.LngLat.convert(e),this._pos=null,this._popup&&this._popup.setLngLat(this._lngLat),this._update(),this},n.prototype.getElement=function(){return this._element},n.prototype.setPopup=function(t){if(this._popup&&(this._popup.remove(),this._popup=null,this._element.removeEventListener(\"keypress\",this._onKeyPress),this._originalTabIndex||this._element.removeAttribute(\"tabindex\")),t){if(!(\"offset\"in t.options)){var e=Math.sqrt(Math.pow(13.5,2)/2);t.options.offset=this._defaultMarker?{top:[0,0],\"top-left\":[0,0],\"top-right\":[0,0],bottom:[0,-38.1],\"bottom-left\":[e,-1*(24.6+e)],\"bottom-right\":[-e,-1*(24.6+e)],left:[13.5,-24.6],right:[-13.5,-24.6]}:this._offset}this._popup=t,this._lngLat&&this._popup.setLngLat(this._lngLat),this._originalTabIndex=this._element.getAttribute(\"tabindex\"),this._originalTabIndex||this._element.setAttribute(\"tabindex\",\"0\"),this._element.addEventListener(\"keypress\",this._onKeyPress)}return this},n.prototype._onKeyPress=function(t){var e=t.code,r=t.charCode||t.keyCode;\"Space\"!==e&&\"Enter\"!==e&&32!==r&&13!==r||this.togglePopup()},n.prototype._onMapClick=function(t){var e=t.originalEvent.target,r=this._element;this._popup&&(e===r||r.contains(e))&&this.togglePopup()},n.prototype.getPopup=function(){return this._popup},n.prototype.togglePopup=function(){var t=this._popup;return t?(t.isOpen()?t.remove():t.addTo(this._map),this):this},n.prototype._update=function(t){if(this._map){this._map.transform.renderWorldCopies&&(this._lngLat=Oi(this._lngLat,this._pos,this._map.transform)),this._pos=this._map.project(this._lngLat)._add(this._offset);var e=\"\";\"viewport\"===this._rotationAlignment||\"auto\"===this._rotationAlignment?e=\"rotateZ(\"+this._rotation+\"deg)\":\"map\"===this._rotationAlignment&&(e=\"rotateZ(\"+(this._rotation-this._map.getBearing())+\"deg)\");var n=\"\";\"viewport\"===this._pitchAlignment||\"auto\"===this._pitchAlignment?n=\"rotateX(0deg)\":\"map\"===this._pitchAlignment&&(n=\"rotateX(\"+this._map.getPitch()+\"deg)\"),t&&\"moveend\"!==t.type||(this._pos=this._pos.round()),r.setTransform(this._element,zi[this._anchor]+\" translate(\"+this._pos.x+\"px, \"+this._pos.y+\"px) \"+n+\" \"+e)}},n.prototype.getOffset=function(){return this._offset},n.prototype.setOffset=function(e){return this._offset=t.Point.convert(e),this._update(),this},n.prototype._onMove=function(e){this._pos=e.point.sub(this._positionDelta),this._lngLat=this._map.unproject(this._pos),this.setLngLat(this._lngLat),this._element.style.pointerEvents=\"none\",\"pending\"===this._state&&(this._state=\"active\",this.fire(new t.Event(\"dragstart\"))),this.fire(new t.Event(\"drag\"))},n.prototype._onUp=function(){this._element.style.pointerEvents=\"auto\",this._positionDelta=null,this._map.off(\"mousemove\",this._onMove),this._map.off(\"touchmove\",this._onMove),\"active\"===this._state&&this.fire(new t.Event(\"dragend\")),this._state=\"inactive\"},n.prototype._addDragHandler=function(t){this._element.contains(t.originalEvent.target)&&(t.preventDefault(),this._positionDelta=t.point.sub(this._pos).add(this._offset),this._state=\"pending\",this._map.on(\"mousemove\",this._onMove),this._map.on(\"touchmove\",this._onMove),this._map.once(\"mouseup\",this._onUp),this._map.once(\"touchend\",this._onUp))},n.prototype.setDraggable=function(t){return this._draggable=!!t,this._map&&(t?(this._map.on(\"mousedown\",this._addDragHandler),this._map.on(\"touchstart\",this._addDragHandler)):(this._map.off(\"mousedown\",this._addDragHandler),this._map.off(\"touchstart\",this._addDragHandler))),this},n.prototype.isDraggable=function(){return this._draggable},n.prototype.setRotation=function(t){return this._rotation=t||0,this._update(),this},n.prototype.getRotation=function(){return this._rotation},n.prototype.setRotationAlignment=function(t){return this._rotationAlignment=t||\"auto\",this._update(),this},n.prototype.getRotationAlignment=function(){return this._rotationAlignment},n.prototype.setPitchAlignment=function(t){return this._pitchAlignment=t&&\"auto\"!==t?t:this._rotationAlignment,this._update(),this},n.prototype.getPitchAlignment=function(){return this._pitchAlignment},n}(t.Evented),Bi={positionOptions:{enableHighAccuracy:!1,maximumAge:0,timeout:6e3},fitBoundsOptions:{maxZoom:15},trackUserLocation:!1,showAccuracyCircle:!0,showUserLocation:!0};var Ni=0,ji=!1,Ui=function(e){function n(r){e.call(this),this.options=t.extend({},Bi,r),t.bindAll([\"_onSuccess\",\"_onError\",\"_onZoom\",\"_finish\",\"_setupUI\",\"_updateCamera\",\"_updateMarker\"],this)}return e&&(n.__proto__=e),n.prototype=Object.create(e&&e.prototype),n.prototype.constructor=n,n.prototype.onAdd=function(e){var n;return this._map=e,this._container=r.create(\"div\",\"mapboxgl-ctrl mapboxgl-ctrl-group\"),n=this._setupUI,void 0!==Ri?n(Ri):void 0!==t.window.navigator.permissions?t.window.navigator.permissions.query({name:\"geolocation\"}).then((function(t){Ri=\"denied\"!==t.state,n(Ri)})):(Ri=!!t.window.navigator.geolocation,n(Ri)),this._container},n.prototype.onRemove=function(){void 0!==this._geolocationWatchID&&(t.window.navigator.geolocation.clearWatch(this._geolocationWatchID),this._geolocationWatchID=void 0),this.options.showUserLocation&&this._userLocationDotMarker&&this._userLocationDotMarker.remove(),this.options.showAccuracyCircle&&this._accuracyCircleMarker&&this._accuracyCircleMarker.remove(),r.remove(this._container),this._map.off(\"zoom\",this._onZoom),this._map=void 0,Ni=0,ji=!1},n.prototype._isOutOfMapMaxBounds=function(t){var e=this._map.getMaxBounds(),r=t.coords;return e&&(r.longitude<e.getWest()||r.longitude>e.getEast()||r.latitude<e.getSouth()||r.latitude>e.getNorth())},n.prototype._setErrorState=function(){switch(this._watchState){case\"WAITING_ACTIVE\":this._watchState=\"ACTIVE_ERROR\",this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-active\"),this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-active-error\");break;case\"ACTIVE_LOCK\":this._watchState=\"ACTIVE_ERROR\",this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-active\"),this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-active-error\"),this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-waiting\");break;case\"BACKGROUND\":this._watchState=\"BACKGROUND_ERROR\",this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-background\"),this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-background-error\"),this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-waiting\")}},n.prototype._onSuccess=function(e){if(this._map){if(this._isOutOfMapMaxBounds(e))return this._setErrorState(),this.fire(new t.Event(\"outofmaxbounds\",e)),this._updateMarker(),void this._finish();if(this.options.trackUserLocation)switch(this._lastKnownPosition=e,this._watchState){case\"WAITING_ACTIVE\":case\"ACTIVE_LOCK\":case\"ACTIVE_ERROR\":this._watchState=\"ACTIVE_LOCK\",this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-waiting\"),this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-active-error\"),this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-active\");break;case\"BACKGROUND\":case\"BACKGROUND_ERROR\":this._watchState=\"BACKGROUND\",this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-waiting\"),this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-background-error\"),this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-background\")}this.options.showUserLocation&&\"OFF\"!==this._watchState&&this._updateMarker(e),this.options.trackUserLocation&&\"ACTIVE_LOCK\"!==this._watchState||this._updateCamera(e),this.options.showUserLocation&&this._dotElement.classList.remove(\"mapboxgl-user-location-dot-stale\"),this.fire(new t.Event(\"geolocate\",e)),this._finish()}},n.prototype._updateCamera=function(e){var r=new t.LngLat(e.coords.longitude,e.coords.latitude),n=e.coords.accuracy,i=this._map.getBearing(),a=t.extend({bearing:i},this.options.fitBoundsOptions);this._map.fitBounds(r.toBounds(n),a,{geolocateSource:!0})},n.prototype._updateMarker=function(e){if(e){var r=new t.LngLat(e.coords.longitude,e.coords.latitude);this._accuracyCircleMarker.setLngLat(r).addTo(this._map),this._userLocationDotMarker.setLngLat(r).addTo(this._map),this._accuracy=e.coords.accuracy,this.options.showUserLocation&&this.options.showAccuracyCircle&&this._updateCircleRadius()}else this._userLocationDotMarker.remove(),this._accuracyCircleMarker.remove()},n.prototype._updateCircleRadius=function(){var t=this._map._container.clientHeight/2,e=this._map.unproject([0,t]),r=this._map.unproject([1,t]),n=e.distanceTo(r),i=Math.ceil(2*this._accuracy/n);this._circleElement.style.width=i+\"px\",this._circleElement.style.height=i+\"px\"},n.prototype._onZoom=function(){this.options.showUserLocation&&this.options.showAccuracyCircle&&this._updateCircleRadius()},n.prototype._onError=function(e){if(this._map){if(this.options.trackUserLocation)if(1===e.code){this._watchState=\"OFF\",this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-waiting\"),this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-active\"),this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-active-error\"),this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-background\"),this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-background-error\"),this._geolocateButton.disabled=!0;var r=this._map._getUIString(\"GeolocateControl.LocationNotAvailable\");this._geolocateButton.title=r,this._geolocateButton.setAttribute(\"aria-label\",r),void 0!==this._geolocationWatchID&&this._clearWatch()}else{if(3===e.code&&ji)return;this._setErrorState()}\"OFF\"!==this._watchState&&this.options.showUserLocation&&this._dotElement.classList.add(\"mapboxgl-user-location-dot-stale\"),this.fire(new t.Event(\"error\",e)),this._finish()}},n.prototype._finish=function(){this._timeoutId&&clearTimeout(this._timeoutId),this._timeoutId=void 0},n.prototype._setupUI=function(e){var n=this;if(this._container.addEventListener(\"contextmenu\",(function(t){return t.preventDefault()})),this._geolocateButton=r.create(\"button\",\"mapboxgl-ctrl-geolocate\",this._container),r.create(\"span\",\"mapboxgl-ctrl-icon\",this._geolocateButton).setAttribute(\"aria-hidden\",!0),this._geolocateButton.type=\"button\",!1===e){t.warnOnce(\"Geolocation support is not available so the GeolocateControl will be disabled.\");var i=this._map._getUIString(\"GeolocateControl.LocationNotAvailable\");this._geolocateButton.disabled=!0,this._geolocateButton.title=i,this._geolocateButton.setAttribute(\"aria-label\",i)}else{var a=this._map._getUIString(\"GeolocateControl.FindMyLocation\");this._geolocateButton.title=a,this._geolocateButton.setAttribute(\"aria-label\",a)}this.options.trackUserLocation&&(this._geolocateButton.setAttribute(\"aria-pressed\",\"false\"),this._watchState=\"OFF\"),this.options.showUserLocation&&(this._dotElement=r.create(\"div\",\"mapboxgl-user-location-dot\"),this._userLocationDotMarker=new Fi(this._dotElement),this._circleElement=r.create(\"div\",\"mapboxgl-user-location-accuracy-circle\"),this._accuracyCircleMarker=new Fi({element:this._circleElement,pitchAlignment:\"map\"}),this.options.trackUserLocation&&(this._watchState=\"OFF\"),this._map.on(\"zoom\",this._onZoom)),this._geolocateButton.addEventListener(\"click\",this.trigger.bind(this)),this._setup=!0,this.options.trackUserLocation&&this._map.on(\"movestart\",(function(e){var r=e.originalEvent&&\"resize\"===e.originalEvent.type;e.geolocateSource||\"ACTIVE_LOCK\"!==n._watchState||r||(n._watchState=\"BACKGROUND\",n._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-background\"),n._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-active\"),n.fire(new t.Event(\"trackuserlocationend\")))}))},n.prototype.trigger=function(){if(!this._setup)return t.warnOnce(\"Geolocate control triggered before added to a map\"),!1;if(this.options.trackUserLocation){switch(this._watchState){case\"OFF\":this._watchState=\"WAITING_ACTIVE\",this.fire(new t.Event(\"trackuserlocationstart\"));break;case\"WAITING_ACTIVE\":case\"ACTIVE_LOCK\":case\"ACTIVE_ERROR\":case\"BACKGROUND_ERROR\":Ni--,ji=!1,this._watchState=\"OFF\",this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-waiting\"),this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-active\"),this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-active-error\"),this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-background\"),this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-background-error\"),this.fire(new t.Event(\"trackuserlocationend\"));break;case\"BACKGROUND\":this._watchState=\"ACTIVE_LOCK\",this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-background\"),this._lastKnownPosition&&this._updateCamera(this._lastKnownPosition),this.fire(new t.Event(\"trackuserlocationstart\"))}switch(this._watchState){case\"WAITING_ACTIVE\":this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-waiting\"),this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-active\");break;case\"ACTIVE_LOCK\":this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-active\");break;case\"ACTIVE_ERROR\":this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-waiting\"),this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-active-error\");break;case\"BACKGROUND\":this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-background\");break;case\"BACKGROUND_ERROR\":this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-waiting\"),this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-background-error\")}if(\"OFF\"===this._watchState&&void 0!==this._geolocationWatchID)this._clearWatch();else if(void 0===this._geolocationWatchID){var e;this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-waiting\"),this._geolocateButton.setAttribute(\"aria-pressed\",\"true\"),++Ni>1?(e={maximumAge:6e5,timeout:0},ji=!0):(e=this.options.positionOptions,ji=!1),this._geolocationWatchID=t.window.navigator.geolocation.watchPosition(this._onSuccess,this._onError,e)}}else t.window.navigator.geolocation.getCurrentPosition(this._onSuccess,this._onError,this.options.positionOptions),this._timeoutId=setTimeout(this._finish,1e4);return!0},n.prototype._clearWatch=function(){t.window.navigator.geolocation.clearWatch(this._geolocationWatchID),this._geolocationWatchID=void 0,this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-waiting\"),this._geolocateButton.setAttribute(\"aria-pressed\",\"false\"),this.options.showUserLocation&&this._updateMarker(null)},n}(t.Evented),Vi={maxWidth:100,unit:\"metric\"},Hi=function(e){this.options=t.extend({},Vi,e),t.bindAll([\"_onMove\",\"setUnit\"],this)};function qi(t,e,r){var n=r&&r.maxWidth||100,i=t._container.clientHeight/2,a=t.unproject([0,i]),o=t.unproject([n,i]),s=a.distanceTo(o);if(r&&\"imperial\"===r.unit){var l=3.2808*s;if(l>5280)Gi(e,n,l/5280,t._getUIString(\"ScaleControl.Miles\"));else Gi(e,n,l,t._getUIString(\"ScaleControl.Feet\"))}else if(r&&\"nautical\"===r.unit){Gi(e,n,s/1852,t._getUIString(\"ScaleControl.NauticalMiles\"))}else s>=1e3?Gi(e,n,s/1e3,t._getUIString(\"ScaleControl.Kilometers\")):Gi(e,n,s,t._getUIString(\"ScaleControl.Meters\"))}function Gi(t,e,r,n){var i,a,o,s=(i=r,a=Math.pow(10,(\"\"+Math.floor(i)).length-1),o=(o=i/a)>=10?10:o>=5?5:o>=3?3:o>=2?2:o>=1?1:function(t){var e=Math.pow(10,Math.ceil(-Math.log(t)/Math.LN10));return Math.round(t*e)/e}(o),a*o),l=s/r;t.style.width=e*l+\"px\",t.innerHTML=s+\"&nbsp;\"+n}Hi.prototype.getDefaultPosition=function(){return\"bottom-left\"},Hi.prototype._onMove=function(){qi(this._map,this._container,this.options)},Hi.prototype.onAdd=function(t){return this._map=t,this._container=r.create(\"div\",\"mapboxgl-ctrl mapboxgl-ctrl-scale\",t.getContainer()),this._map.on(\"move\",this._onMove),this._onMove(),this._container},Hi.prototype.onRemove=function(){r.remove(this._container),this._map.off(\"move\",this._onMove),this._map=void 0},Hi.prototype.setUnit=function(t){this.options.unit=t,qi(this._map,this._container,this.options)};var Yi=function(e){this._fullscreen=!1,e&&e.container&&(e.container instanceof t.window.HTMLElement?this._container=e.container:t.warnOnce(\"Full screen control 'container' must be a DOM element.\")),t.bindAll([\"_onClickFullscreen\",\"_changeIcon\"],this),\"onfullscreenchange\"in t.window.document?this._fullscreenchange=\"fullscreenchange\":\"onmozfullscreenchange\"in t.window.document?this._fullscreenchange=\"mozfullscreenchange\":\"onwebkitfullscreenchange\"in t.window.document?this._fullscreenchange=\"webkitfullscreenchange\":\"onmsfullscreenchange\"in t.window.document&&(this._fullscreenchange=\"MSFullscreenChange\")};Yi.prototype.onAdd=function(e){return this._map=e,this._container||(this._container=this._map.getContainer()),this._controlContainer=r.create(\"div\",\"mapboxgl-ctrl mapboxgl-ctrl-group\"),this._checkFullscreenSupport()?this._setupUI():(this._controlContainer.style.display=\"none\",t.warnOnce(\"This device does not support fullscreen mode.\")),this._controlContainer},Yi.prototype.onRemove=function(){r.remove(this._controlContainer),this._map=null,t.window.document.removeEventListener(this._fullscreenchange,this._changeIcon)},Yi.prototype._checkFullscreenSupport=function(){return!!(t.window.document.fullscreenEnabled||t.window.document.mozFullScreenEnabled||t.window.document.msFullscreenEnabled||t.window.document.webkitFullscreenEnabled)},Yi.prototype._setupUI=function(){var e=this._fullscreenButton=r.create(\"button\",\"mapboxgl-ctrl-fullscreen\",this._controlContainer);r.create(\"span\",\"mapboxgl-ctrl-icon\",e).setAttribute(\"aria-hidden\",!0),e.type=\"button\",this._updateTitle(),this._fullscreenButton.addEventListener(\"click\",this._onClickFullscreen),t.window.document.addEventListener(this._fullscreenchange,this._changeIcon)},Yi.prototype._updateTitle=function(){var t=this._getTitle();this._fullscreenButton.setAttribute(\"aria-label\",t),this._fullscreenButton.title=t},Yi.prototype._getTitle=function(){return this._map._getUIString(this._isFullscreen()?\"FullscreenControl.Exit\":\"FullscreenControl.Enter\")},Yi.prototype._isFullscreen=function(){return this._fullscreen},Yi.prototype._changeIcon=function(){(t.window.document.fullscreenElement||t.window.document.mozFullScreenElement||t.window.document.webkitFullscreenElement||t.window.document.msFullscreenElement)===this._container!==this._fullscreen&&(this._fullscreen=!this._fullscreen,this._fullscreenButton.classList.toggle(\"mapboxgl-ctrl-shrink\"),this._fullscreenButton.classList.toggle(\"mapboxgl-ctrl-fullscreen\"),this._updateTitle())},Yi.prototype._onClickFullscreen=function(){this._isFullscreen()?t.window.document.exitFullscreen?t.window.document.exitFullscreen():t.window.document.mozCancelFullScreen?t.window.document.mozCancelFullScreen():t.window.document.msExitFullscreen?t.window.document.msExitFullscreen():t.window.document.webkitCancelFullScreen&&t.window.document.webkitCancelFullScreen():this._container.requestFullscreen?this._container.requestFullscreen():this._container.mozRequestFullScreen?this._container.mozRequestFullScreen():this._container.msRequestFullscreen?this._container.msRequestFullscreen():this._container.webkitRequestFullscreen&&this._container.webkitRequestFullscreen()};var Wi={closeButton:!0,closeOnClick:!0,className:\"\",maxWidth:\"240px\"},Xi=function(e){function n(r){e.call(this),this.options=t.extend(Object.create(Wi),r),t.bindAll([\"_update\",\"_onClose\",\"remove\",\"_onMouseMove\",\"_onMouseUp\",\"_onDrag\"],this)}return e&&(n.__proto__=e),n.prototype=Object.create(e&&e.prototype),n.prototype.constructor=n,n.prototype.addTo=function(e){return this._map&&this.remove(),this._map=e,this.options.closeOnClick&&this._map.on(\"click\",this._onClose),this.options.closeOnMove&&this._map.on(\"move\",this._onClose),this._map.on(\"remove\",this.remove),this._update(),this._trackPointer?(this._map.on(\"mousemove\",this._onMouseMove),this._map.on(\"mouseup\",this._onMouseUp),this._container&&this._container.classList.add(\"mapboxgl-popup-track-pointer\"),this._map._canvasContainer.classList.add(\"mapboxgl-track-pointer\")):this._map.on(\"move\",this._update),this.fire(new t.Event(\"open\")),this},n.prototype.isOpen=function(){return!!this._map},n.prototype.remove=function(){return this._content&&r.remove(this._content),this._container&&(r.remove(this._container),delete this._container),this._map&&(this._map.off(\"move\",this._update),this._map.off(\"move\",this._onClose),this._map.off(\"click\",this._onClose),this._map.off(\"remove\",this.remove),this._map.off(\"mousemove\",this._onMouseMove),this._map.off(\"mouseup\",this._onMouseUp),this._map.off(\"drag\",this._onDrag),delete this._map),this.fire(new t.Event(\"close\")),this},n.prototype.getLngLat=function(){return this._lngLat},n.prototype.setLngLat=function(e){return this._lngLat=t.LngLat.convert(e),this._pos=null,this._trackPointer=!1,this._update(),this._map&&(this._map.on(\"move\",this._update),this._map.off(\"mousemove\",this._onMouseMove),this._container&&this._container.classList.remove(\"mapboxgl-popup-track-pointer\"),this._map._canvasContainer.classList.remove(\"mapboxgl-track-pointer\")),this},n.prototype.trackPointer=function(){return this._trackPointer=!0,this._pos=null,this._update(),this._map&&(this._map.off(\"move\",this._update),this._map.on(\"mousemove\",this._onMouseMove),this._map.on(\"drag\",this._onDrag),this._container&&this._container.classList.add(\"mapboxgl-popup-track-pointer\"),this._map._canvasContainer.classList.add(\"mapboxgl-track-pointer\")),this},n.prototype.getElement=function(){return this._container},n.prototype.setText=function(e){return this.setDOMContent(t.window.document.createTextNode(e))},n.prototype.setHTML=function(e){var r,n=t.window.document.createDocumentFragment(),i=t.window.document.createElement(\"body\");for(i.innerHTML=e;r=i.firstChild;)n.appendChild(r);return this.setDOMContent(n)},n.prototype.getMaxWidth=function(){return this._container&&this._container.style.maxWidth},n.prototype.setMaxWidth=function(t){return this.options.maxWidth=t,this._update(),this},n.prototype.setDOMContent=function(t){return this._createContent(),this._content.appendChild(t),this._update(),this},n.prototype.addClassName=function(t){this._container&&this._container.classList.add(t)},n.prototype.removeClassName=function(t){this._container&&this._container.classList.remove(t)},n.prototype.toggleClassName=function(t){if(this._container)return this._container.classList.toggle(t)},n.prototype._createContent=function(){this._content&&r.remove(this._content),this._content=r.create(\"div\",\"mapboxgl-popup-content\",this._container),this.options.closeButton&&(this._closeButton=r.create(\"button\",\"mapboxgl-popup-close-button\",this._content),this._closeButton.type=\"button\",this._closeButton.setAttribute(\"aria-label\",\"Close popup\"),this._closeButton.innerHTML=\"&#215;\",this._closeButton.addEventListener(\"click\",this._onClose))},n.prototype._onMouseUp=function(t){this._update(t.point)},n.prototype._onMouseMove=function(t){this._update(t.point)},n.prototype._onDrag=function(t){this._update(t.point)},n.prototype._update=function(e){var n=this,i=this._lngLat||this._trackPointer;if(this._map&&i&&this._content&&(this._container||(this._container=r.create(\"div\",\"mapboxgl-popup\",this._map.getContainer()),this._tip=r.create(\"div\",\"mapboxgl-popup-tip\",this._container),this._container.appendChild(this._content),this.options.className&&this.options.className.split(\" \").forEach((function(t){return n._container.classList.add(t)})),this._trackPointer&&this._container.classList.add(\"mapboxgl-popup-track-pointer\")),this.options.maxWidth&&this._container.style.maxWidth!==this.options.maxWidth&&(this._container.style.maxWidth=this.options.maxWidth),this._map.transform.renderWorldCopies&&!this._trackPointer&&(this._lngLat=Oi(this._lngLat,this._pos,this._map.transform)),!this._trackPointer||e)){var a=this._pos=this._trackPointer&&e?e:this._map.project(this._lngLat),o=this.options.anchor,s=function e(r){if(r){if(\"number\"==typeof r){var n=Math.round(Math.sqrt(.5*Math.pow(r,2)));return{center:new t.Point(0,0),top:new t.Point(0,r),\"top-left\":new t.Point(n,n),\"top-right\":new t.Point(-n,n),bottom:new t.Point(0,-r),\"bottom-left\":new t.Point(n,-n),\"bottom-right\":new t.Point(-n,-n),left:new t.Point(r,0),right:new t.Point(-r,0)}}if(r instanceof t.Point||Array.isArray(r)){var i=t.Point.convert(r);return{center:i,top:i,\"top-left\":i,\"top-right\":i,bottom:i,\"bottom-left\":i,\"bottom-right\":i,left:i,right:i}}return{center:t.Point.convert(r.center||[0,0]),top:t.Point.convert(r.top||[0,0]),\"top-left\":t.Point.convert(r[\"top-left\"]||[0,0]),\"top-right\":t.Point.convert(r[\"top-right\"]||[0,0]),bottom:t.Point.convert(r.bottom||[0,0]),\"bottom-left\":t.Point.convert(r[\"bottom-left\"]||[0,0]),\"bottom-right\":t.Point.convert(r[\"bottom-right\"]||[0,0]),left:t.Point.convert(r.left||[0,0]),right:t.Point.convert(r.right||[0,0])}}return e(new t.Point(0,0))}(this.options.offset);if(!o){var l,c=this._container.offsetWidth,u=this._container.offsetHeight;l=a.y+s.bottom.y<u?[\"top\"]:a.y>this._map.transform.height-u?[\"bottom\"]:[],a.x<c/2?l.push(\"left\"):a.x>this._map.transform.width-c/2&&l.push(\"right\"),o=0===l.length?\"bottom\":l.join(\"-\")}var f=a.add(s[o]).round();r.setTransform(this._container,zi[o]+\" translate(\"+f.x+\"px,\"+f.y+\"px)\"),Di(this._container,o,\"popup\")}},n.prototype._onClose=function(){this.remove()},n}(t.Evented);var Zi={version:t.version,supported:e,setRTLTextPlugin:t.setRTLTextPlugin,getRTLTextPluginStatus:t.getRTLTextPluginStatus,Map:Ei,NavigationControl:Pi,GeolocateControl:Ui,AttributionControl:bi,ScaleControl:Hi,FullscreenControl:Yi,Popup:Xi,Marker:Fi,Style:qe,LngLat:t.LngLat,LngLatBounds:t.LngLatBounds,Point:t.Point,MercatorCoordinate:t.MercatorCoordinate,Evented:t.Evented,config:t.config,prewarm:function(){Bt().acquire(zt)},clearPrewarmedResources:function(){var t=Rt;t&&(t.isPreloaded()&&1===t.numActive()?(t.release(zt),Rt=null):console.warn(\"Could not clear WebWorkers since there are active Map instances that still reference it. The pre-warmed WebWorker pool can only be cleared when all map instances have been removed with map.remove()\"))},get accessToken(){return t.config.ACCESS_TOKEN},set accessToken(e){t.config.ACCESS_TOKEN=e},get baseApiUrl(){return t.config.API_URL},set baseApiUrl(e){t.config.API_URL=e},get workerCount(){return Dt.workerCount},set workerCount(t){Dt.workerCount=t},get maxParallelImageRequests(){return t.config.MAX_PARALLEL_IMAGE_REQUESTS},set maxParallelImageRequests(e){t.config.MAX_PARALLEL_IMAGE_REQUESTS=e},clearStorage:function(e){t.clearTileCache(e)},workerUrl:\"\"};return Zi})),r}))},{}],240:[function(t,e,r){\"use strict\";e.exports=Math.log2||function(t){return Math.log(t)*Math.LOG2E}},{}],241:[function(t,e,r){\"use strict\";e.exports=function(t,e){e||(e=t,t=window);var r=0,i=0,a=0,o={shift:!1,alt:!1,control:!1,meta:!1},s=!1;function l(t){var e=!1;return\"altKey\"in t&&(e=e||t.altKey!==o.alt,o.alt=!!t.altKey),\"shiftKey\"in t&&(e=e||t.shiftKey!==o.shift,o.shift=!!t.shiftKey),\"ctrlKey\"in t&&(e=e||t.ctrlKey!==o.control,o.control=!!t.ctrlKey),\"metaKey\"in t&&(e=e||t.metaKey!==o.meta,o.meta=!!t.metaKey),e}function c(t,s){var c=n.x(s),u=n.y(s);\"buttons\"in s&&(t=0|s.buttons),(t!==r||c!==i||u!==a||l(s))&&(r=0|t,i=c||0,a=u||0,e&&e(r,i,a,o))}function u(t){c(0,t)}function f(){(r||i||a||o.shift||o.alt||o.meta||o.control)&&(i=a=0,r=0,o.shift=o.alt=o.control=o.meta=!1,e&&e(0,0,0,o))}function h(t){l(t)&&e&&e(r,i,a,o)}function p(t){0===n.buttons(t)?c(0,t):c(r,t)}function d(t){c(r|n.buttons(t),t)}function m(t){c(r&~n.buttons(t),t)}function g(){s||(s=!0,t.addEventListener(\"mousemove\",p),t.addEventListener(\"mousedown\",d),t.addEventListener(\"mouseup\",m),t.addEventListener(\"mouseleave\",u),t.addEventListener(\"mouseenter\",u),t.addEventListener(\"mouseout\",u),t.addEventListener(\"mouseover\",u),t.addEventListener(\"blur\",f),t.addEventListener(\"keyup\",h),t.addEventListener(\"keydown\",h),t.addEventListener(\"keypress\",h),t!==window&&(window.addEventListener(\"blur\",f),window.addEventListener(\"keyup\",h),window.addEventListener(\"keydown\",h),window.addEventListener(\"keypress\",h)))}g();var v={element:t};return Object.defineProperties(v,{enabled:{get:function(){return s},set:function(e){e?g():function(){if(!s)return;s=!1,t.removeEventListener(\"mousemove\",p),t.removeEventListener(\"mousedown\",d),t.removeEventListener(\"mouseup\",m),t.removeEventListener(\"mouseleave\",u),t.removeEventListener(\"mouseenter\",u),t.removeEventListener(\"mouseout\",u),t.removeEventListener(\"mouseover\",u),t.removeEventListener(\"blur\",f),t.removeEventListener(\"keyup\",h),t.removeEventListener(\"keydown\",h),t.removeEventListener(\"keypress\",h),t!==window&&(window.removeEventListener(\"blur\",f),window.removeEventListener(\"keyup\",h),window.removeEventListener(\"keydown\",h),window.removeEventListener(\"keypress\",h))}()},enumerable:!0},buttons:{get:function(){return r},enumerable:!0},x:{get:function(){return i},enumerable:!0},y:{get:function(){return a},enumerable:!0},mods:{get:function(){return o},enumerable:!0}}),v};var n=t(\"mouse-event\")},{\"mouse-event\":243}],242:[function(t,e,r){var n={left:0,top:0};e.exports=function(t,e,r){e=e||t.currentTarget||t.srcElement,Array.isArray(r)||(r=[0,0]);var i=t.clientX||0,a=t.clientY||0,o=(s=e,s===window||s===document||s===document.body?n:s.getBoundingClientRect());var s;return r[0]=i-o.left,r[1]=a-o.top,r}},{}],243:[function(t,e,r){\"use strict\";function n(t){return t.target||t.srcElement||window}r.buttons=function(t){if(\"object\"==typeof t){if(\"buttons\"in t)return t.buttons;if(\"which\"in t){if(2===(e=t.which))return 4;if(3===e)return 2;if(e>0)return 1<<e-1}else if(\"button\"in t){var e;if(1===(e=t.button))return 4;if(2===e)return 2;if(e>=0)return 1<<e}}return 0},r.element=n,r.x=function(t){if(\"object\"==typeof t){if(\"offsetX\"in t)return t.offsetX;var e=n(t).getBoundingClientRect();return t.clientX-e.left}return 0},r.y=function(t){if(\"object\"==typeof t){if(\"offsetY\"in t)return t.offsetY;var e=n(t).getBoundingClientRect();return t.clientY-e.top}return 0}},{}],244:[function(t,e,r){\"use strict\";var n=t(\"to-px\");e.exports=function(t,e,r){\"function\"==typeof t&&(r=!!e,e=t,t=window);var i=n(\"ex\",t),a=function(t){r&&t.preventDefault();var n=t.deltaX||0,a=t.deltaY||0,o=t.deltaZ||0,s=1;switch(t.deltaMode){case 1:s=i;break;case 2:s=window.innerHeight}if(a*=s,o*=s,(n*=s)||a||o)return e(n,a,o,t)};return t.addEventListener(\"wheel\",a),a}},{\"to-px\":314}],245:[function(t,e,r){(function(t,r){(function(){\n",
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r=0,n=t[t.length-1][0],i=t[t.length-1][1],a=[],o=0;o<t.length;o++){var s=t[o][0],l=t[o][1];a.push([s,l]),r+=l*n-s*i,n=s,i=l}return r<0!==e&&a.reverse(),a.push([a[0][0],a[0][1]]),a}var u=[];function f(t){var e=[c(t.region,!1)];u.push(e);for(var r=0;r<t.children.length;r++)e.push(h(t.children[r]))}function h(t){for(var e=0;e<t.children.length;e++)f(t.children[e]);return c(t.region,!0)}for(s=0;s<a.children.length;s++)f(a.children[s]);return u.length<=0?{type:\"Polygon\",coordinates:[]}:1==u.length?{type:\"Polygon\",coordinates:u[0]}:{type:\"MultiPolygon\",coordinates:u}}};e.exports=n},{}],258:[function(t,e,r){var n=t(\"./linked-list\");e.exports=function(t,e,r){function i(t,e,n){return{id:r?r.segmentId():-1,start:t,end:e,myFill:{above:n.myFill.above,below:n.myFill.below},otherFill:null}}var a=n.create();function o(t,r){a.insertBefore(t,(function(n){return function(t,r,n,i,a,o){var s=e.pointsCompare(r,a);return 0!==s?s:e.pointsSame(n,o)?0:t!==i?t?1:-1:e.pointAboveOrOnLine(n,i?a:o,i?o:a)?1:-1}(t.isStart,t.pt,r,n.isStart,n.pt,n.other.pt)<0}))}function s(t,e){var r=function(t,e){var r=n.node({isStart:!0,pt:t.start,seg:t,primary:e,other:null,status:null});return o(r,t.end),r}(t,e);return function(t,e,r){var i=n.node({isStart:!1,pt:e.end,seg:e,primary:r,other:t,status:null});t.other=i,o(i,t.pt)}(r,t,e),r}function l(t,e){var n=i(e,t.seg.end,t.seg);return function(t,e){r&&r.segmentChop(t.seg,e),t.other.remove(),t.seg.end=e,t.other.pt=e,o(t.other,t.pt)}(t,e),s(n,t.primary)}function c(i,o){var s=n.create();function c(t){return s.findTransition((function(r){var n,i,a,o,s,l;return(n=t,i=r.ev,a=n.seg.start,o=n.seg.end,s=i.seg.start,l=i.seg.end,e.pointsCollinear(a,s,l)?e.pointsCollinear(o,s,l)||e.pointAboveOrOnLine(o,s,l)?1:-1:e.pointAboveOrOnLine(a,s,l)?1:-1)>0}))}function u(t,n){var i=t.seg,a=n.seg,o=i.start,s=i.end,c=a.start,u=a.end;r&&r.checkIntersection(i,a);var f=e.linesIntersect(o,s,c,u);if(!1===f){if(!e.pointsCollinear(o,s,c))return!1;if(e.pointsSame(o,u)||e.pointsSame(s,c))return!1;var h=e.pointsSame(o,c),p=e.pointsSame(s,u);if(h&&p)return n;var d=!h&&e.pointBetween(o,c,u),m=!p&&e.pointBetween(s,c,u);if(h)return m?l(n,s):l(t,u),n;d&&(p||(m?l(n,s):l(t,u)),l(n,o))}else 0===f.alongA&&(-1===f.alongB?l(t,c):0===f.alongB?l(t,f.pt):1===f.alongB&&l(t,u)),0===f.alongB&&(-1===f.alongA?l(n,o):0===f.alongA?l(n,f.pt):1===f.alongA&&l(n,s));return!1}for(var f=[];!a.isEmpty();){var h=a.getHead();if(r&&r.vert(h.pt[0]),h.isStart){r&&r.segmentNew(h.seg,h.primary);var p=c(h),d=p.before?p.before.ev:null,m=p.after?p.after.ev:null;function g(){if(d){var t=u(h,d);if(t)return t}return!!m&&u(h,m)}r&&r.tempStatus(h.seg,!!d&&d.seg,!!m&&m.seg);var v,y=g();if(y){var x;if(t)(x=null===h.seg.myFill.below||h.seg.myFill.above!==h.seg.myFill.below)&&(y.seg.myFill.above=!y.seg.myFill.above);else y.seg.otherFill=h.seg.myFill;r&&r.segmentUpdate(y.seg),h.other.remove(),h.remove()}if(a.getHead()!==h){r&&r.rewind(h.seg);continue}if(t)x=null===h.seg.myFill.below||h.seg.myFill.above!==h.seg.myFill.below,h.seg.myFill.below=m?m.seg.myFill.above:i,h.seg.myFill.above=x?!h.seg.myFill.below:h.seg.myFill.below;else if(null===h.seg.otherFill)v=m?h.primary===m.primary?m.seg.otherFill.above:m.seg.myFill.above:h.primary?o:i,h.seg.otherFill={above:v,below:v};r&&r.status(h.seg,!!d&&d.seg,!!m&&m.seg),h.other.status=p.insert(n.node({ev:h}))}else{var b=h.status;if(null===b)throw new Error(\"PolyBool: Zero-length segment detected; your epsilon is probably too small or too large\");if(s.exists(b.prev)&&s.exists(b.next)&&u(b.prev.ev,b.next.ev),r&&r.statusRemove(b.ev.seg),b.remove(),!h.primary){var _=h.seg.myFill;h.seg.myFill=h.seg.otherFill,h.seg.otherFill=_}f.push(h.seg)}a.getHead().remove()}return r&&r.done(),f}return t?{addRegion:function(t){for(var n,i,a,o=t[t.length-1],l=0;l<t.length;l++){n=o,o=t[l];var c=e.pointsCompare(n,o);0!==c&&s((i=c<0?n:o,a=c<0?o:n,{id:r?r.segmentId():-1,start:i,end:a,myFill:{above:null,below:null},otherFill:null}),!0)}},calculate:function(t){return c(t,!1)}}:{calculate:function(t,e,r,n){return t.forEach((function(t){s(i(t.start,t.end,t),!0)})),r.forEach((function(t){s(i(t.start,t.end,t),!1)})),c(e,n)}}}},{\"./linked-list\":259}],259:[function(t,e,r){e.exports={create:function(){var t={root:{root:!0,next:null},exists:function(e){return null!==e&&e!==t.root},isEmpty:function(){return null===t.root.next},getHead:function(){return t.root.next},insertBefore:function(e,r){for(var n=t.root,i=t.root.next;null!==i;){if(r(i))return e.prev=i.prev,e.next=i,i.prev.next=e,void(i.prev=e);n=i,i=i.next}n.next=e,e.prev=n,e.next=null},findTransition:function(e){for(var r=t.root,n=t.root.next;null!==n&&!e(n);)r=n,n=n.next;return{before:r===t.root?null:r,after:n,insert:function(t){return t.prev=r,t.next=n,r.next=t,null!==n&&(n.prev=t),t}}}};return t},node:function(t){return t.prev=null,t.next=null,t.remove=function(){t.prev.next=t.next,t.next&&(t.next.prev=t.prev),t.prev=null,t.next=null},t}}},{}],260:[function(t,e,r){e.exports=function(t,e,r){var n=[],i=[];return t.forEach((function(t){var a=t.start,o=t.end;if(e.pointsSame(a,o))console.warn(\"PolyBool: Warning: Zero-length segment detected; your epsilon is probably too small or too large\");else{r&&r.chainStart(t);for(var s={index:0,matches_head:!1,matches_pt1:!1},l={index:0,matches_head:!1,matches_pt1:!1},c=s,u=0;u<n.length;u++){var f=(g=n[u])[0],h=(g[1],g[g.length-1]);g[g.length-2];if(e.pointsSame(f,a)){if(k(u,!0,!0))break}else if(e.pointsSame(f,o)){if(k(u,!0,!1))break}else if(e.pointsSame(h,a)){if(k(u,!1,!0))break}else if(e.pointsSame(h,o)&&k(u,!1,!1))break}if(c===s)return n.push([a,o]),void(r&&r.chainNew(a,o));if(c===l){r&&r.chainMatch(s.index);var p=s.index,d=s.matches_pt1?o:a,m=s.matches_head,g=n[p],v=m?g[0]:g[g.length-1],y=m?g[1]:g[g.length-2],x=m?g[g.length-1]:g[0],b=m?g[g.length-2]:g[1];return e.pointsCollinear(y,v,d)&&(m?(r&&r.chainRemoveHead(s.index,d),g.shift()):(r&&r.chainRemoveTail(s.index,d),g.pop()),v=y),e.pointsSame(x,d)?(n.splice(p,1),e.pointsCollinear(b,x,v)&&(m?(r&&r.chainRemoveTail(s.index,v),g.pop()):(r&&r.chainRemoveHead(s.index,v),g.shift())),r&&r.chainClose(s.index),void i.push(g)):void(m?(r&&r.chainAddHead(s.index,d),g.unshift(d)):(r&&r.chainAddTail(s.index,d),g.push(d)))}var _=s.index,w=l.index;r&&r.chainConnect(_,w);var T=n[_].length<n[w].length;s.matches_head?l.matches_head?T?(A(_),M(_,w)):(A(w),M(w,_)):M(w,_):l.matches_head?M(_,w):T?(A(_),M(w,_)):(A(w),M(_,w))}function k(t,e,r){return c.index=t,c.matches_head=e,c.matches_pt1=r,c===s?(c=l,!1):(c=null,!0)}function A(t){r&&r.chainReverse(t),n[t].reverse()}function M(t,i){var a=n[t],o=n[i],s=a[a.length-1],l=a[a.length-2],c=o[0],u=o[1];e.pointsCollinear(l,s,c)&&(r&&r.chainRemoveTail(t,s),a.pop(),s=l),e.pointsCollinear(s,c,u)&&(r&&r.chainRemoveHead(i,c),o.shift()),r&&r.chainJoin(t,i),n[t]=a.concat(o),n.splice(i,1)}})),i}},{}],261:[function(t,e,r){function n(t,e,r){var n=[];return t.forEach((function(t){var i=(t.myFill.above?8:0)+(t.myFill.below?4:0)+(t.otherFill&&t.otherFill.above?2:0)+(t.otherFill&&t.otherFill.below?1:0);0!==e[i]&&n.push({id:r?r.segmentId():-1,start:t.start,end:t.end,myFill:{above:1===e[i],below:2===e[i]},otherFill:null})})),r&&r.selected(n),n}var i={union:function(t,e){return n(t,[0,2,1,0,2,2,0,0,1,0,1,0,0,0,0,0],e)},intersect:function(t,e){return n(t,[0,0,0,0,0,2,0,2,0,0,1,1,0,2,1,0],e)},difference:function(t,e){return n(t,[0,0,0,0,2,0,2,0,1,1,0,0,0,1,2,0],e)},differenceRev:function(t,e){return n(t,[0,2,1,0,0,0,1,1,0,2,0,2,0,0,0,0],e)},xor:function(t,e){return n(t,[0,2,1,0,2,0,0,1,1,0,0,2,0,1,2,0],e)}};e.exports=i},{}],262:[function(t,e,r){\"use strict\";var n=t(\"stream\").Transform,i=t(\"stream-parser\");function a(){n.call(this,{readableObjectMode:!0})}function o(t,e,r){Error.call(this),Error.captureStackTrace?Error.captureStackTrace(this,this.constructor):this.stack=(new Error).stack||\"\",this.name=this.constructor.name,this.message=t,e&&(this.code=e),r&&(this.statusCode=r)}a.prototype=Object.create(n.prototype),a.prototype.constructor=a,i(a.prototype),r.ParserStream=a,r.sliceEq=function(t,e,r){for(var n=e,i=0;i<r.length;)if(t[n++]!==r[i++])return!1;return!0},r.str2arr=function(t,e){var r=[],n=0;if(e&&\"hex\"===e)for(;n<t.length;)r.push(parseInt(t.slice(n,n+2),16)),n+=2;else for(;n<t.length;n++)r.push(255&t.charCodeAt(n));return r},r.readUInt16LE=function(t,e){return t[e]|t[e+1]<<8},r.readUInt16BE=function(t,e){return t[e+1]|t[e]<<8},r.readUInt32LE=function(t,e){return t[e]|t[e+1]<<8|t[e+2]<<16|16777216*t[e+3]},r.readUInt32BE=function(t,e){return t[e+3]|t[e+2]<<8|t[e+1]<<16|16777216*t[e]},o.prototype=Object.create(Error.prototype),o.prototype.constructor=o,r.ProbeError=o},{stream:285,\"stream-parser\":301}],263:[function(t,e,r){\"use strict\";function n(t,e){var r=new Error(t);return r.code=e,r}function i(t){try{return decodeURIComponent(escape(t))}catch(e){return t}}function a(t,e,r){this.input=t.subarray(e,r),this.start=e;var i=String.fromCharCode.apply(null,this.input.subarray(0,4));if(\"II*\\0\"!==i&&\"MM\\0*\"!==i)throw n(\"invalid TIFF signature\",\"EBADDATA\");this.big_endian=\"M\"===i[0]}a.prototype.each=function(t){this.aborted=!1;var e=this.read_uint32(4);for(this.ifds_to_read=[{id:0,offset:e}];this.ifds_to_read.length>0&&!this.aborted;){var r=this.ifds_to_read.shift();r.offset&&this.scan_ifd(r.id,r.offset,t)}},a.prototype.read_uint16=function(t){var e=this.input;if(t+2>e.length)throw n(\"unexpected EOF\",\"EBADDATA\");return this.big_endian?256*e[t]+e[t+1]:e[t]+256*e[t+1]},a.prototype.read_uint32=function(t){var e=this.input;if(t+4>e.length)throw n(\"unexpected EOF\",\"EBADDATA\");return this.big_endian?16777216*e[t]+65536*e[t+1]+256*e[t+2]+e[t+3]:e[t]+256*e[t+1]+65536*e[t+2]+16777216*e[t+3]},a.prototype.is_subifd_link=function(t,e){return 0===t&&34665===e||0===t&&34853===e||34665===t&&40965===e},a.prototype.exif_format_length=function(t){switch(t){case 1:case 2:case 6:case 7:return 1;case 3:case 8:return 2;case 4:case 9:case 11:return 4;case 5:case 10:case 12:return 8;default:return 0}},a.prototype.exif_format_read=function(t,e){var r;switch(t){case 1:case 2:return r=this.input[e];case 6:return(r=this.input[e])|33554430*(128&r);case 3:return r=this.read_uint16(e);case 8:return(r=this.read_uint16(e))|131070*(32768&r);case 4:return r=this.read_uint32(e);case 9:return 0|(r=this.read_uint32(e));case 5:case 10:case 11:case 12:case 7:default:return null}},a.prototype.scan_ifd=function(t,e,r){var a=this.read_uint16(e);e+=2;for(var o=0;o<a;o++){var s=this.read_uint16(e),l=this.read_uint16(e+2),c=this.read_uint32(e+4),u=this.exif_format_length(l),f=c*u,h=f<=4?e+8:this.read_uint32(e+8),p=!1;if(h+f>this.input.length)throw n(\"unexpected EOF\",\"EBADDATA\");for(var d=[],m=h,g=0;g<c;g++,m+=u){var v=this.exif_format_read(l,m);if(null===v){d=null;break}d.push(v)}if(Array.isArray(d)&&2===l&&(d=i(String.fromCharCode.apply(null,d)))&&\"\\0\"===d[d.length-1]&&(d=d.slice(0,-1)),this.is_subifd_link(t,s)&&Array.isArray(d)&&Number.isInteger(d[0])&&d[0]>0&&(this.ifds_to_read.push({id:s,offset:d[0]}),p=!0),!1===r({is_big_endian:this.big_endian,ifd:t,tag:s,format:l,count:c,entry_offset:e+this.start,data_length:f,data_offset:h+this.start,value:d,is_subifd_link:p}))return void(this.aborted=!0);e+=12}0===t&&this.ifds_to_read.push({id:1,offset:this.read_uint32(e)})},e.exports.ExifParser=a,e.exports.get_orientation=function(t){var e=0;try{return new a(t,0,t.length).each((function(t){if(0===t.ifd&&274===t.tag&&Array.isArray(t.value))return e=t.value[0],!1})),e}catch(t){return-1}}},{}],264:[function(t,e,r){\"use strict\";var n=t(\"./common\").readUInt16BE,i=t(\"./common\").readUInt32BE;function a(t,e){if(t.length<4+e)return null;var r=i(t,e);return t.length<r+e||r<8?null:{boxtype:String.fromCharCode.apply(null,t.slice(e+4,e+8)),data:t.slice(e+8,e+r),end:e+r}}function o(t,e){for(var r=0;;){var n=a(t,r);if(!n)break;switch(n.boxtype){case\"ispe\":e.sizes.push({width:i(n.data,4),height:i(n.data,8)});break;case\"irot\":e.transforms.push({type:\"irot\",value:3&n.data[0]});break;case\"imir\":e.transforms.push({type:\"imir\",value:1&n.data[0]})}r=n.end}}function s(t,e,r){for(var n=0,i=0;i<r;i++)n=256*n+(t[e+i]||0);return n}function l(t,e){for(var r=t[4]>>4&15,i=15&t[4],a=t[5]>>4&15,o=n(t,6),l=8,c=0;c<o;c++){var u=n(t,l),f=n(t,l+=2),h=s(t,l+=2,a),p=n(t,l+=a);if(l+=2,0===f&&1===p){var d=s(t,l,r),m=s(t,l+r,i);e.item_loc[u]={length:m,offset:d+h}}l+=p*(r+i)}}function c(t,e){for(var r=n(t,4),i=6,o=0;o<r;o++){var s=a(t,i);if(!s)break;if(\"infe\"===s.boxtype){for(var l=n(s.data,4),c=\"\",u=8;u<s.data.length&&s.data[u];u++)c+=String.fromCharCode(s.data[u]);e.item_inf[c]=l}i=s.end}}function u(t,e){for(var r=0;;){var n=a(t,r);if(!n)break;\"ipco\"===n.boxtype&&o(n.data,e),r=n.end}}e.exports.unbox=a,e.exports.readSizeFromMeta=function(t){var e={sizes:[],transforms:[],item_inf:{},item_loc:{}};if(function(t,e){for(var r=4;;){var n=a(t,r);if(!n)break;\"iprp\"===n.boxtype&&u(n.data,e),\"iloc\"===n.boxtype&&l(n.data,e),\"iinf\"===n.boxtype&&c(n.data,e),r=n.end}}(t,e),e.sizes.length){var r,n,i,o=(r=e.sizes,n=r.reduce((function(t,e){return t.width>e.width||t.width===e.width&&t.height>e.height?t:e})),i=r.reduce((function(t,e){return t.height>e.height||t.height===e.height&&t.width>e.width?t:e})),n.width>i.height||n.width===i.height&&n.height>i.width?n:i),s=1;e.transforms.forEach((function(t){var e={1:6,2:5,3:8,4:7,5:4,6:3,7:2,8:1},r={1:4,2:3,3:2,4:1,5:6,6:5,7:8,8:7};if(\"imir\"===t.type&&(s=0===t.value?r[s]:e[s=e[s=r[s]]]),\"irot\"===t.type)for(var n=0;n<t.value;n++)s=e[s]}));var f=null;return e.item_inf.Exif&&(f=e.item_loc[e.item_inf.Exif]),{width:o.width,height:o.height,orientation:e.transforms.length?s:null,variants:e.sizes,exif_location:f}}},e.exports.getMimeType=function(t){var e=String.fromCharCode.apply(null,t.slice(0,4)),r={};r[e]=!0;for(var 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h=[[1,0,0,1,0,0],[1,0,0,-1,0,0],[-1,0,0,-1,0,0],[-1,0,0,-1,0,0],[-1,0,0,1,0,0],[1,0,0,1,0,0],[1,0,-1,0,0,1],[1,0,-1,0,0,-1],[1,0,1,0,0,-1],[1,0,1,0,0,-1],[1,0,1,0,0,1],[1,0,-1,0,0,1],[-1,0,-1,0,0,1],[-1,0,-1,0,0,-1],[-1,0,1,0,0,-1],[-1,0,1,0,0,-1],[-1,0,1,0,0,1],[-1,0,-1,0,0,1],[0,1,1,0,0,0],[0,1,-1,0,0,0],[0,-1,-1,0,0,0],[0,-1,-1,0,0,0],[0,1,1,0,0,0],[0,-1,1,0,0,0],[0,1,0,-1,1,0],[0,1,0,-1,-1,0],[0,1,0,1,-1,0],[0,1,0,1,1,0],[0,1,0,-1,1,0],[0,1,0,1,-1,0],[0,-1,0,-1,1,0],[0,-1,0,-1,-1,0],[0,-1,0,1,-1,0],[0,-1,0,1,1,0],[0,-1,0,-1,1,0],[0,-1,0,1,-1,0]]},{\"array-bounds\":71,\"color-normalize\":89,\"flatten-vertex-data\":191,\"object-assign\":247,\"pick-by-alias\":253,\"to-float32\":313,\"update-diff\":329}],280:[function(t,e,r){\"use strict\";var n=t(\"color-normalize\"),i=t(\"array-bounds\"),a=t(\"object-assign\"),o=t(\"glslify\"),s=t(\"pick-by-alias\"),l=t(\"flatten-vertex-data\"),c=t(\"earcut\"),u=t(\"array-normalize\"),f=t(\"to-float32\"),h=f.float32,p=f.fract32,d=t(\"es6-weak-map\"),m=t(\"parse-rect\"),g=t(\"array-find-index\");function v(t,e){if(!(this instanceof v))return new v(t,e);if(\"function\"==typeof t?(e||(e={}),e.regl=t):e=t,e.length&&(e.positions=e),!(t=e.regl).hasExtension(\"ANGLE_instanced_arrays\"))throw Error(\"regl-error2d: `ANGLE_instanced_arrays` extension should be enabled\");this.gl=t._gl,this.regl=t,this.passes=[],this.shaders=v.shaders.has(t)?v.shaders.get(t):v.shaders.set(t,v.createShaders(t)).get(t),this.update(e)}e.exports=v,v.dashMult=2,v.maxPatternLength=256,v.precisionThreshold=3e6,v.maxPoints=1e4,v.maxLines=2048,v.shaders=new d,v.createShaders=function(t){var e,r=t.buffer({usage:\"static\",type:\"float\",data:[0,1,0,0,1,1,1,0]}),n={primitive:\"triangle strip\",instances:t.prop(\"count\"),count:4,offset:0,uniforms:{miterMode:function(t,e){return\"round\"===e.join?2:1},miterLimit:t.prop(\"miterLimit\"),scale:t.prop(\"scale\"),scaleFract:t.prop(\"scaleFract\"),translateFract:t.prop(\"translateFract\"),translate:t.prop(\"translate\"),thickness:t.prop(\"thickness\"),dashTexture:t.prop(\"dashTexture\"),opacity:t.prop(\"opacity\"),pixelRatio:t.context(\"pixelRatio\"),id:t.prop(\"id\"),dashLength:t.prop(\"dashLength\"),viewport:function(t,e){return[e.viewport.x,e.viewport.y,t.viewportWidth,t.viewportHeight]},depth:t.prop(\"depth\")},blend:{enable:!0,color:[0,0,0,0],equation:{rgb:\"add\",alpha:\"add\"},func:{srcRGB:\"src alpha\",dstRGB:\"one minus src alpha\",srcAlpha:\"one minus dst alpha\",dstAlpha:\"one\"}},depth:{enable:function(t,e){return!e.overlay}},stencil:{enable:!1},scissor:{enable:!0,box:t.prop(\"viewport\")},viewport:t.prop(\"viewport\")},i=t(a({vert:o([\"precision highp float;\\n#define GLSLIFY 1\\n\\nattribute vec2 aCoord, bCoord, aCoordFract, bCoordFract;\\nattribute vec4 color;\\nattribute float lineEnd, lineTop;\\n\\nuniform vec2 scale, scaleFract, translate, translateFract;\\nuniform float thickness, pixelRatio, id, depth;\\nuniform vec4 viewport;\\n\\nvarying vec4 fragColor;\\nvarying vec2 tangent;\\n\\nvec2 project(vec2 position, vec2 positionFract, vec2 scale, vec2 scaleFract, vec2 translate, vec2 translateFract) {\\n\\t// the order is important\\n\\treturn position * scale + translate\\n + positionFract * scale + translateFract\\n + position * scaleFract\\n + positionFract * scaleFract;\\n}\\n\\nvoid main() {\\n\\tfloat lineStart = 1. - lineEnd;\\n\\tfloat lineOffset = lineTop * 2. - 1.;\\n\\n\\tvec2 diff = (bCoord + bCoordFract - aCoord - aCoordFract);\\n\\ttangent = normalize(diff * scale * viewport.zw);\\n\\tvec2 normal = vec2(-tangent.y, tangent.x);\\n\\n\\tvec2 position = project(aCoord, aCoordFract, scale, scaleFract, translate, translateFract) * lineStart\\n\\t\\t+ project(bCoord, bCoordFract, scale, scaleFract, translate, translateFract) * lineEnd\\n\\n\\t\\t+ thickness * normal * .5 * lineOffset / viewport.zw;\\n\\n\\tgl_Position = vec4(position * 2.0 - 1.0, depth, 1);\\n\\n\\tfragColor = color / 255.;\\n}\\n\"]),frag:o([\"precision highp float;\\n#define GLSLIFY 1\\n\\nuniform float dashLength, pixelRatio, thickness, opacity, id;\\nuniform sampler2D dashTexture;\\n\\nvarying vec4 fragColor;\\nvarying vec2 tangent;\\n\\nvoid main() {\\n\\tfloat alpha = 1.;\\n\\n\\tfloat t = fract(dot(tangent, gl_FragCoord.xy) / dashLength) * .5 + .25;\\n\\tfloat dash = texture2D(dashTexture, vec2(t, .5)).r;\\n\\n\\tgl_FragColor = fragColor;\\n\\tgl_FragColor.a *= alpha * opacity * dash;\\n}\\n\"]),attributes:{lineEnd:{buffer:r,divisor:0,stride:8,offset:0},lineTop:{buffer:r,divisor:0,stride:8,offset:4},aCoord:{buffer:t.prop(\"positionBuffer\"),stride:8,offset:8,divisor:1},bCoord:{buffer:t.prop(\"positionBuffer\"),stride:8,offset:16,divisor:1},aCoordFract:{buffer:t.prop(\"positionFractBuffer\"),stride:8,offset:8,divisor:1},bCoordFract:{buffer:t.prop(\"positionFractBuffer\"),stride:8,offset:16,divisor:1},color:{buffer:t.prop(\"colorBuffer\"),stride:4,offset:0,divisor:1}}},n));try{e=t(a({cull:{enable:!0,face:\"back\"},vert:o([\"precision highp float;\\n#define GLSLIFY 1\\n\\nattribute vec2 aCoord, bCoord, nextCoord, prevCoord;\\nattribute vec4 aColor, bColor;\\nattribute float lineEnd, lineTop;\\n\\nuniform vec2 scale, translate;\\nuniform float thickness, pixelRatio, id, depth;\\nuniform vec4 viewport;\\nuniform float miterLimit, miterMode;\\n\\nvarying vec4 fragColor;\\nvarying vec4 startCutoff, endCutoff;\\nvarying vec2 tangent;\\nvarying vec2 startCoord, endCoord;\\nvarying float enableStartMiter, enableEndMiter;\\n\\nconst float REVERSE_THRESHOLD = -.875;\\nconst float MIN_DIFF = 1e-6;\\n\\n// TODO: possible optimizations: avoid overcalculating all for vertices and calc just one instead\\n// TODO: precalculate dot products, normalize things beforehead etc.\\n// TODO: refactor to rectangular algorithm\\n\\nfloat distToLine(vec2 p, vec2 a, vec2 b) {\\n\\tvec2 diff = b - a;\\n\\tvec2 perp = normalize(vec2(-diff.y, diff.x));\\n\\treturn dot(p - a, perp);\\n}\\n\\nbool isNaN( float val ){\\n return ( val < 0.0 || 0.0 < val || val == 0.0 ) ? false : true;\\n}\\n\\nvoid main() {\\n\\tvec2 aCoord = aCoord, bCoord = bCoord, prevCoord = prevCoord, nextCoord = nextCoord;\\n\\n vec2 adjustedScale;\\n adjustedScale.x = (abs(scale.x) < MIN_DIFF) ? MIN_DIFF : scale.x;\\n adjustedScale.y = (abs(scale.y) < MIN_DIFF) ? MIN_DIFF : scale.y;\\n\\n vec2 scaleRatio = adjustedScale * viewport.zw;\\n\\tvec2 normalWidth = thickness / scaleRatio;\\n\\n\\tfloat lineStart = 1. - lineEnd;\\n\\tfloat lineBot = 1. - lineTop;\\n\\n\\tfragColor = (lineStart * aColor + lineEnd * bColor) / 255.;\\n\\n\\tif (isNaN(aCoord.x) || isNaN(aCoord.y) || isNaN(bCoord.x) || isNaN(bCoord.y)) return;\\n\\n\\tif (aCoord == prevCoord) prevCoord = aCoord + normalize(bCoord - aCoord);\\n\\tif (bCoord == nextCoord) nextCoord = bCoord - normalize(bCoord - aCoord);\\n\\n\\tvec2 prevDiff = aCoord - prevCoord;\\n\\tvec2 currDiff = bCoord - aCoord;\\n\\tvec2 nextDiff = nextCoord - bCoord;\\n\\n\\tvec2 prevTangent = normalize(prevDiff * scaleRatio);\\n\\tvec2 currTangent = normalize(currDiff * scaleRatio);\\n\\tvec2 nextTangent = normalize(nextDiff * scaleRatio);\\n\\n\\tvec2 prevNormal = vec2(-prevTangent.y, prevTangent.x);\\n\\tvec2 currNormal = vec2(-currTangent.y, currTangent.x);\\n\\tvec2 nextNormal = vec2(-nextTangent.y, nextTangent.x);\\n\\n\\tvec2 startJoinDirection = normalize(prevTangent - currTangent);\\n\\tvec2 endJoinDirection = normalize(currTangent - nextTangent);\\n\\n\\t// collapsed/unidirectional segment cases\\n\\t// FIXME: there should be more elegant solution\\n\\tvec2 prevTanDiff = abs(prevTangent - currTangent);\\n\\tvec2 nextTanDiff = abs(nextTangent - currTangent);\\n\\tif (max(prevTanDiff.x, prevTanDiff.y) < MIN_DIFF) {\\n\\t\\tstartJoinDirection = currNormal;\\n\\t}\\n\\tif (max(nextTanDiff.x, nextTanDiff.y) < MIN_DIFF) {\\n\\t\\tendJoinDirection = currNormal;\\n\\t}\\n\\tif (aCoord == bCoord) {\\n\\t\\tendJoinDirection = startJoinDirection;\\n\\t\\tcurrNormal = prevNormal;\\n\\t\\tcurrTangent = prevTangent;\\n\\t}\\n\\n\\ttangent = currTangent;\\n\\n\\t//calculate join shifts relative to normals\\n\\tfloat startJoinShift = dot(currNormal, startJoinDirection);\\n\\tfloat endJoinShift = dot(currNormal, endJoinDirection);\\n\\n\\tfloat startMiterRatio = abs(1. / startJoinShift);\\n\\tfloat endMiterRatio = abs(1. / endJoinShift);\\n\\n\\tvec2 startJoin = startJoinDirection * startMiterRatio;\\n\\tvec2 endJoin = endJoinDirection * endMiterRatio;\\n\\n\\tvec2 startTopJoin, startBotJoin, endTopJoin, endBotJoin;\\n\\tstartTopJoin = sign(startJoinShift) * startJoin * .5;\\n\\tstartBotJoin = -startTopJoin;\\n\\n\\tendTopJoin = sign(endJoinShift) * endJoin * .5;\\n\\tendBotJoin = -endTopJoin;\\n\\n\\tvec2 aTopCoord = aCoord + normalWidth * startTopJoin;\\n\\tvec2 bTopCoord = bCoord + normalWidth * endTopJoin;\\n\\tvec2 aBotCoord = aCoord + normalWidth * startBotJoin;\\n\\tvec2 bBotCoord = bCoord + normalWidth * endBotJoin;\\n\\n\\t//miter anti-clipping\\n\\tfloat baClipping = distToLine(bCoord, aCoord, aBotCoord) / dot(normalize(normalWidth * endBotJoin), normalize(normalWidth.yx * vec2(-startBotJoin.y, startBotJoin.x)));\\n\\tfloat abClipping = distToLine(aCoord, bCoord, bTopCoord) / dot(normalize(normalWidth * startBotJoin), normalize(normalWidth.yx * vec2(-endBotJoin.y, endBotJoin.x)));\\n\\n\\t//prevent close to reverse direction switch\\n\\tbool prevReverse = dot(currTangent, prevTangent) <= REVERSE_THRESHOLD && abs(dot(currTangent, prevNormal)) * min(length(prevDiff), length(currDiff)) < length(normalWidth * currNormal);\\n\\tbool nextReverse = dot(currTangent, nextTangent) <= REVERSE_THRESHOLD && abs(dot(currTangent, nextNormal)) * min(length(nextDiff), length(currDiff)) < length(normalWidth * currNormal);\\n\\n\\tif (prevReverse) {\\n\\t\\t//make join rectangular\\n\\t\\tvec2 miterShift = normalWidth * startJoinDirection * miterLimit * .5;\\n\\t\\tfloat normalAdjust = 1. - min(miterLimit / startMiterRatio, 1.);\\n\\t\\taBotCoord = aCoord + miterShift - normalAdjust * normalWidth * currNormal * .5;\\n\\t\\taTopCoord = aCoord + miterShift + normalAdjust * normalWidth * currNormal * .5;\\n\\t}\\n\\telse if (!nextReverse && baClipping > 0. && baClipping < length(normalWidth * endBotJoin)) {\\n\\t\\t//handle miter clipping\\n\\t\\tbTopCoord -= normalWidth * endTopJoin;\\n\\t\\tbTopCoord += normalize(endTopJoin * normalWidth) * baClipping;\\n\\t}\\n\\n\\tif (nextReverse) {\\n\\t\\t//make join rectangular\\n\\t\\tvec2 miterShift = normalWidth * endJoinDirection * miterLimit * .5;\\n\\t\\tfloat normalAdjust = 1. - min(miterLimit / endMiterRatio, 1.);\\n\\t\\tbBotCoord = bCoord + miterShift - normalAdjust * normalWidth * currNormal * .5;\\n\\t\\tbTopCoord = bCoord + miterShift + normalAdjust * normalWidth * currNormal * .5;\\n\\t}\\n\\telse if (!prevReverse && abClipping > 0. && abClipping < length(normalWidth * startBotJoin)) {\\n\\t\\t//handle miter clipping\\n\\t\\taBotCoord -= normalWidth * startBotJoin;\\n\\t\\taBotCoord += normalize(startBotJoin * normalWidth) * abClipping;\\n\\t}\\n\\n\\tvec2 aTopPosition = (aTopCoord) * adjustedScale + translate;\\n\\tvec2 aBotPosition = (aBotCoord) * adjustedScale + translate;\\n\\n\\tvec2 bTopPosition = (bTopCoord) * adjustedScale + translate;\\n\\tvec2 bBotPosition = (bBotCoord) * adjustedScale + translate;\\n\\n\\t//position is normalized 0..1 coord on the screen\\n\\tvec2 position = (aTopPosition * lineTop + aBotPosition * lineBot) * lineStart + (bTopPosition * lineTop + bBotPosition * lineBot) * lineEnd;\\n\\n\\tstartCoord = aCoord * scaleRatio + translate * viewport.zw + viewport.xy;\\n\\tendCoord = bCoord * scaleRatio + translate * viewport.zw + viewport.xy;\\n\\n\\tgl_Position = vec4(position * 2.0 - 1.0, depth, 1);\\n\\n\\tenableStartMiter = step(dot(currTangent, prevTangent), .5);\\n\\tenableEndMiter = step(dot(currTangent, nextTangent), .5);\\n\\n\\t//bevel miter cutoffs\\n\\tif (miterMode == 1.) {\\n\\t\\tif (enableStartMiter == 1.) {\\n\\t\\t\\tvec2 startMiterWidth = vec2(startJoinDirection) * thickness * miterLimit * .5;\\n\\t\\t\\tstartCutoff = vec4(aCoord, aCoord);\\n\\t\\t\\tstartCutoff.zw += vec2(-startJoinDirection.y, startJoinDirection.x) / scaleRatio;\\n\\t\\t\\tstartCutoff = startCutoff * scaleRatio.xyxy + translate.xyxy * viewport.zwzw;\\n\\t\\t\\tstartCutoff += viewport.xyxy;\\n\\t\\t\\tstartCutoff += startMiterWidth.xyxy;\\n\\t\\t}\\n\\n\\t\\tif (enableEndMiter == 1.) {\\n\\t\\t\\tvec2 endMiterWidth = vec2(endJoinDirection) * thickness * miterLimit * .5;\\n\\t\\t\\tendCutoff = vec4(bCoord, bCoord);\\n\\t\\t\\tendCutoff.zw += vec2(-endJoinDirection.y, endJoinDirection.x) / scaleRatio;\\n\\t\\t\\tendCutoff = endCutoff * scaleRatio.xyxy + translate.xyxy * viewport.zwzw;\\n\\t\\t\\tendCutoff += viewport.xyxy;\\n\\t\\t\\tendCutoff += endMiterWidth.xyxy;\\n\\t\\t}\\n\\t}\\n\\n\\t//round miter cutoffs\\n\\telse if (miterMode == 2.) {\\n\\t\\tif (enableStartMiter == 1.) {\\n\\t\\t\\tvec2 startMiterWidth = vec2(startJoinDirection) * thickness * abs(dot(startJoinDirection, currNormal)) * .5;\\n\\t\\t\\tstartCutoff = vec4(aCoord, aCoord);\\n\\t\\t\\tstartCutoff.zw += vec2(-startJoinDirection.y, startJoinDirection.x) / scaleRatio;\\n\\t\\t\\tstartCutoff = startCutoff * scaleRatio.xyxy + translate.xyxy * viewport.zwzw;\\n\\t\\t\\tstartCutoff += viewport.xyxy;\\n\\t\\t\\tstartCutoff += startMiterWidth.xyxy;\\n\\t\\t}\\n\\n\\t\\tif (enableEndMiter == 1.) {\\n\\t\\t\\tvec2 endMiterWidth = vec2(endJoinDirection) * thickness * abs(dot(endJoinDirection, currNormal)) * .5;\\n\\t\\t\\tendCutoff = vec4(bCoord, bCoord);\\n\\t\\t\\tendCutoff.zw += vec2(-endJoinDirection.y, endJoinDirection.x) / scaleRatio;\\n\\t\\t\\tendCutoff = endCutoff * scaleRatio.xyxy + translate.xyxy * viewport.zwzw;\\n\\t\\t\\tendCutoff += viewport.xyxy;\\n\\t\\t\\tendCutoff += endMiterWidth.xyxy;\\n\\t\\t}\\n\\t}\\n}\\n\"]),frag:o([\"precision highp float;\\n#define GLSLIFY 1\\n\\nuniform float dashLength, pixelRatio, thickness, opacity, id, miterMode;\\nuniform sampler2D dashTexture;\\n\\nvarying vec4 fragColor;\\nvarying vec2 tangent;\\nvarying vec4 startCutoff, endCutoff;\\nvarying vec2 startCoord, endCoord;\\nvarying float enableStartMiter, enableEndMiter;\\n\\nfloat distToLine(vec2 p, vec2 a, vec2 b) {\\n\\tvec2 diff = b - a;\\n\\tvec2 perp = normalize(vec2(-diff.y, diff.x));\\n\\treturn dot(p - a, perp);\\n}\\n\\nvoid main() {\\n\\tfloat alpha = 1., distToStart, distToEnd;\\n\\tfloat cutoff = thickness * .5;\\n\\n\\t//bevel miter\\n\\tif (miterMode == 1.) {\\n\\t\\tif (enableStartMiter == 1.) {\\n\\t\\t\\tdistToStart = distToLine(gl_FragCoord.xy, startCutoff.xy, startCutoff.zw);\\n\\t\\t\\tif (distToStart < -1.) {\\n\\t\\t\\t\\tdiscard;\\n\\t\\t\\t\\treturn;\\n\\t\\t\\t}\\n\\t\\t\\talpha *= min(max(distToStart + 1., 0.), 1.);\\n\\t\\t}\\n\\n\\t\\tif (enableEndMiter == 1.) {\\n\\t\\t\\tdistToEnd = distToLine(gl_FragCoord.xy, endCutoff.xy, endCutoff.zw);\\n\\t\\t\\tif (distToEnd < -1.) {\\n\\t\\t\\t\\tdiscard;\\n\\t\\t\\t\\treturn;\\n\\t\\t\\t}\\n\\t\\t\\talpha *= min(max(distToEnd + 1., 0.), 1.);\\n\\t\\t}\\n\\t}\\n\\n\\t// round miter\\n\\telse if (miterMode == 2.) {\\n\\t\\tif (enableStartMiter == 1.) {\\n\\t\\t\\tdistToStart = distToLine(gl_FragCoord.xy, startCutoff.xy, startCutoff.zw);\\n\\t\\t\\tif (distToStart < 0.) {\\n\\t\\t\\t\\tfloat radius = length(gl_FragCoord.xy - startCoord);\\n\\n\\t\\t\\t\\tif(radius > cutoff + .5) {\\n\\t\\t\\t\\t\\tdiscard;\\n\\t\\t\\t\\t\\treturn;\\n\\t\\t\\t\\t}\\n\\n\\t\\t\\t\\talpha -= smoothstep(cutoff - .5, cutoff + .5, radius);\\n\\t\\t\\t}\\n\\t\\t}\\n\\n\\t\\tif (enableEndMiter == 1.) {\\n\\t\\t\\tdistToEnd = distToLine(gl_FragCoord.xy, endCutoff.xy, endCutoff.zw);\\n\\t\\t\\tif (distToEnd < 0.) {\\n\\t\\t\\t\\tfloat radius = length(gl_FragCoord.xy - endCoord);\\n\\n\\t\\t\\t\\tif(radius > cutoff + .5) {\\n\\t\\t\\t\\t\\tdiscard;\\n\\t\\t\\t\\t\\treturn;\\n\\t\\t\\t\\t}\\n\\n\\t\\t\\t\\talpha -= smoothstep(cutoff - .5, cutoff + .5, radius);\\n\\t\\t\\t}\\n\\t\\t}\\n\\t}\\n\\n\\tfloat t = fract(dot(tangent, gl_FragCoord.xy) / dashLength) * .5 + .25;\\n\\tfloat dash = texture2D(dashTexture, vec2(t, .5)).r;\\n\\n\\tgl_FragColor = fragColor;\\n\\tgl_FragColor.a *= alpha * opacity * 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t=this,e=[],r=arguments.length;r--;)e[r]=arguments[r];return(e.length?e:this.passes).forEach((function(e,r){var n;if(e&&Array.isArray(e))return(n=t).draw.apply(n,e);\"number\"==typeof e&&(e=t.passes[e]),e&&e.count>1&&e.opacity&&(t.regl._refresh(),e.fill&&e.triangles&&e.triangles.length>2&&t.shaders.fill(e),e.thickness&&(e.scale[0]*e.viewport.width>v.precisionThreshold||e.scale[1]*e.viewport.height>v.precisionThreshold||\"rect\"===e.join||!e.join&&(e.thickness<=2||e.count>=v.maxPoints)?t.shaders.rect(e):t.shaders.miter(e)))})),this},v.prototype.update=function(t){var e=this;if(t){null!=t.length?\"number\"==typeof t[0]&&(t=[{positions:t}]):Array.isArray(t)||(t=[t]);var r=this.regl,o=this.gl;if(t.forEach((function(t,f){var d=e.passes[f];if(void 0!==t)if(null!==t){if(\"number\"==typeof t[0]&&(t={positions:t}),t=s(t,{positions:\"positions points data coords\",thickness:\"thickness lineWidth lineWidths line-width linewidth width stroke-width strokewidth strokeWidth\",join:\"lineJoin linejoin 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Uint8Array})},t=a({},v.defaults,t)),null!=t.thickness&&(d.thickness=parseFloat(t.thickness)),null!=t.opacity&&(d.opacity=parseFloat(t.opacity)),null!=t.miterLimit&&(d.miterLimit=parseFloat(t.miterLimit)),null!=t.overlay&&(d.overlay=!!t.overlay,f<v.maxLines&&(d.depth=2*(v.maxLines-1-f%v.maxLines)/v.maxLines-1)),null!=t.join&&(d.join=t.join),null!=t.hole&&(d.hole=t.hole),null!=t.fill&&(d.fill=t.fill?n(t.fill,\"uint8\"):null),null!=t.viewport&&(d.viewport=m(t.viewport)),d.viewport||(d.viewport=m([o.drawingBufferWidth,o.drawingBufferHeight])),null!=t.close&&(d.close=t.close),null===t.positions&&(t.positions=[]),t.positions){var y,x;if(t.positions.x&&t.positions.y){var b=t.positions.x,_=t.positions.y;x=d.count=Math.max(b.length,_.length),y=new Float64Array(2*x);for(var w=0;w<x;w++)y[2*w]=b[w],y[2*w+1]=_[w]}else y=l(t.positions,\"float64\"),x=d.count=Math.floor(y.length/2);var T=d.bounds=i(y,2);if(d.fill){for(var k=[],A={},M=0,S=0,E=0,L=d.count;S<L;S++){var C=y[2*S],P=y[2*S+1];isNaN(C)||isNaN(P)||null==C||null==P?(C=y[2*M],P=y[2*M+1],A[S]=M):M=S,k[E++]=C,k[E++]=P}if(t.splitNull){d.count-1 in A||(A[d.count]=d.count-1);var I=Object.keys(A).map(Number).sort((function(t,e){return t-e})),O=[],z=0,D=null!=d.hole?d.hole[0]:null;if(null!=D){var R=g(I,(function(t){return t>=D}));(I=I.slice(0,R)).push(D)}for(var F=function(t){var e=k.slice(2*z,2*I[t]).concat(D?k.slice(2*D):[]),r=(d.hole||[]).map((function(e){return e-D+(I[t]-z)})),n=c(e,r);n=n.map((function(e){return e+z+(e+z<I[t]?0:D-I[t])})),O.push.apply(O,n),z=I[t]+1},B=0;B<I.length;B++)F(B);for(var N=0,j=O.length;N<j;N++)null!=A[O[N]]&&(O[N]=A[O[N]]);d.triangles=O}else{for(var U=c(k,d.hole||[]),V=0,H=U.length;V<H;V++)null!=A[U[V]]&&(U[V]=A[U[V]]);d.triangles=U}}var q=new Float64Array(y);u(q,2,T);var G=new Float64Array(2*x+6);d.close?y[0]===y[2*x-2]&&y[1]===y[2*x-1]?(G[0]=q[2*x-4],G[1]=q[2*x-3]):(G[0]=q[2*x-2],G[1]=q[2*x-1]):(G[0]=q[0],G[1]=q[1]),G.set(q,2),d.close?y[0]===y[2*x-2]&&y[1]===y[2*x-1]?(G[2*x+2]=q[2],G[2*x+3]=q[3],d.count-=1):(G[2*x+2]=q[0],G[2*x+3]=q[1],G[2*x+4]=q[2],G[2*x+5]=q[3]):(G[2*x+2]=q[2*x-2],G[2*x+3]=q[2*x-1],G[2*x+4]=q[2*x-2],G[2*x+5]=q[2*x-1]);var Y=h(G);d.positionBuffer(Y);var W=p(G,Y);d.positionFractBuffer(W)}if(t.range?d.range=t.range:d.range||(d.range=d.bounds),(t.range||t.positions)&&d.count){var X=d.bounds,Z=X[2]-X[0],J=X[3]-X[1],K=d.range[2]-d.range[0],Q=d.range[3]-d.range[1];d.scale=[Z/K,J/Q],d.translate=[-d.range[0]/K+X[0]/K||0,-d.range[1]/Q+X[1]/Q||0],d.scaleFract=p(d.scale),d.translateFract=p(d.translate)}if(t.dashes){var $,tt=0;if(!t.dashes||t.dashes.length<2)tt=1,$=new Uint8Array([255,255,255,255,255,255,255,255]);else{tt=0;for(var et=0;et<t.dashes.length;++et)tt+=t.dashes[et];$=new Uint8Array(tt*v.dashMult);for(var rt=0,nt=255,it=0;it<2;it++)for(var at=0;at<t.dashes.length;++at){for(var ot=0,st=t.dashes[at]*v.dashMult*.5;ot<st;++ot)$[rt++]=nt;nt^=255}}d.dashLength=tt,d.dashTexture({channels:1,data:$,width:$.length,height:1,mag:\"linear\",min:\"linear\"},0,0)}if(t.color){var lt=d.count,ct=t.color;ct||(ct=\"transparent\");var ut=new Uint8Array(4*lt+4);if(Array.isArray(ct)&&\"number\"!=typeof ct[0]){for(var ft=0;ft<lt;ft++){var ht=n(ct[ft],\"uint8\");ut.set(ht,4*ft)}ut.set(n(ct[0],\"uint8\"),4*lt)}else for(var pt=n(ct,\"uint8\"),dt=0;dt<lt+1;dt++)ut.set(pt,4*dt);d.colorBuffer({usage:\"dynamic\",type:\"uint8\",data:ut})}}else e.passes[f]=null})),t.length<this.passes.length){for(var f=t.length;f<this.passes.length;f++){var d=this.passes[f];d&&(d.colorBuffer.destroy(),d.positionBuffer.destroy(),d.dashTexture.destroy())}this.passes.length=t.length}for(var y=[],x=0;x<this.passes.length;x++)null!==this.passes[x]&&y.push(this.passes[x]);return this.passes=y,this}},v.prototype.destroy=function(){return 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s=t(\"color-normalize\"),l=t(\"array-bounds\"),c=t(\"color-id\"),u=t(\"@plotly/point-cluster\"),f=t(\"object-assign\"),h=t(\"glslify\"),p=t(\"pick-by-alias\"),d=t(\"update-diff\"),m=t(\"flatten-vertex-data\"),g=t(\"is-iexplorer\"),v=t(\"to-float32\"),y=t(\"parse-rect\"),x=b;function b(t,e){var r=this;if(!(this instanceof b))return new b(t,e);\"function\"==typeof t?(e||(e={}),e.regl=t):(e=t,t=null),e&&e.length&&(e.positions=e);var n,i=(t=e.regl)._gl,a=[];this.tooManyColors=g,n=t.texture({data:new Uint8Array(1020),width:255,height:1,type:\"uint8\",format:\"rgba\",wrapS:\"clamp\",wrapT:\"clamp\",mag:\"nearest\",min:\"nearest\"}),f(this,{regl:t,gl:i,groups:[],markerCache:[null],markerTextures:[null],palette:a,paletteIds:{},paletteTexture:n,maxColors:255,maxSize:100,canvas:i.canvas}),this.update(e);var o={uniforms:{constPointSize:!!e.constPointSize,opacity:t.prop(\"opacity\"),paletteSize:function(t,e){return[r.tooManyColors?0:255,n.height]},pixelRatio:t.context(\"pixelRatio\"),scale:t.prop(\"scale\"),scaleFract:t.prop(\"scaleFract\"),translate:t.prop(\"translate\"),translateFract:t.prop(\"translateFract\"),markerTexture:t.prop(\"markerTexture\"),paletteTexture:n},attributes:{x:function(t,e){return e.xAttr||{buffer:e.positionBuffer,stride:8,offset:0}},y:function(t,e){return e.yAttr||{buffer:e.positionBuffer,stride:8,offset:4}},xFract:function(t,e){return e.xAttr?{constant:[0,0]}:{buffer:e.positionFractBuffer,stride:8,offset:0}},yFract:function(t,e){return e.yAttr?{constant:[0,0]}:{buffer:e.positionFractBuffer,stride:8,offset:4}},size:function(t,e){return e.size.length?{buffer:e.sizeBuffer,stride:2,offset:0}:{constant:[Math.round(255*e.size/r.maxSize)]}},borderSize:function(t,e){return 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highp float;\\n#define GLSLIFY 1\\n\\nuniform float opacity;\\nuniform sampler2D markerTexture;\\n\\nvarying vec4 fragColor, fragBorderColor;\\nvarying float fragWidth, fragBorderColorLevel, fragColorLevel;\\n\\nfloat smoothStep(float x, float y) {\\n return 1.0 / (1.0 + exp(50.0*(x - y)));\\n}\\n\\nvoid main() {\\n float dist = texture2D(markerTexture, gl_PointCoord).r, delta = fragWidth;\\n\\n // max-distance alpha\\n if (dist < 0.003) discard;\\n\\n // null-border case\\n if (fragBorderColorLevel == fragColorLevel || fragBorderColor.a == 0.) {\\n float colorAmt = smoothstep(.5 - delta, .5 + delta, dist);\\n gl_FragColor = vec4(fragColor.rgb, colorAmt * fragColor.a * opacity);\\n }\\n else {\\n float borderColorAmt = smoothstep(fragBorderColorLevel - delta, fragBorderColorLevel + delta, dist);\\n float colorAmt = smoothstep(fragColorLevel - delta, fragColorLevel + delta, dist);\\n\\n vec4 color = fragBorderColor;\\n color.a *= borderColorAmt;\\n color = mix(color, fragColor, colorAmt);\\n color.a *= opacity;\\n\\n gl_FragColor = color;\\n }\\n\\n}\\n\"]),s.vert=h([\"precision highp float;\\n#define GLSLIFY 1\\n\\nattribute float x, y, xFract, yFract;\\nattribute float size, borderSize;\\nattribute vec4 colorId, borderColorId;\\nattribute float isActive;\\n\\nuniform bool constPointSize;\\nuniform float pixelRatio;\\nuniform vec2 scale, scaleFract, translate, translateFract, paletteSize;\\nuniform sampler2D paletteTexture;\\n\\nconst float maxSize = 100.;\\nconst float borderLevel = .5;\\n\\nvarying vec4 fragColor, fragBorderColor;\\nvarying float fragPointSize, fragBorderRadius, fragWidth, fragBorderColorLevel, fragColorLevel;\\n\\nfloat pointSizeScale = (constPointSize) ? 2. : pixelRatio;\\n\\nbool isDirect = (paletteSize.x < 1.);\\n\\nvec4 getColor(vec4 id) {\\n return isDirect ? id / 255. : texture2D(paletteTexture,\\n vec2(\\n (id.x + .5) / paletteSize.x,\\n (id.y + .5) / paletteSize.y\\n )\\n );\\n}\\n\\nvoid main() {\\n // ignore inactive points\\n if (isActive == 0.) return;\\n\\n vec2 position = vec2(x, y);\\n vec2 positionFract = vec2(xFract, yFract);\\n\\n vec4 color = getColor(colorId);\\n vec4 borderColor = getColor(borderColorId);\\n\\n float size = size * maxSize / 255.;\\n float borderSize = borderSize * maxSize / 255.;\\n\\n gl_PointSize = 2. * size * pointSizeScale;\\n fragPointSize = size * pixelRatio;\\n\\n vec2 pos = (position + translate) * scale\\n + (positionFract + translateFract) * scale\\n + (position + translate) * scaleFract\\n + (positionFract + translateFract) * scaleFract;\\n\\n gl_Position = vec4(pos * 2. - 1., 0., 1.);\\n\\n fragColor = color;\\n fragBorderColor = borderColor;\\n fragWidth = 1. / gl_PointSize;\\n\\n fragBorderColorLevel = clamp(borderLevel - borderLevel * borderSize / size, 0., 1.);\\n fragColorLevel = clamp(borderLevel + (1. - borderLevel) * borderSize / size, 0., 1.);\\n}\"]),this.drawMarker=t(s);var l=f({},o);l.frag=h([\"precision highp float;\\n#define GLSLIFY 1\\n\\nvarying vec4 fragColor, fragBorderColor;\\nvarying float fragBorderRadius, fragWidth;\\n\\nuniform float opacity;\\n\\nfloat smoothStep(float edge0, float edge1, float x) {\\n\\tfloat t;\\n\\tt = clamp((x - edge0) / (edge1 - edge0), 0.0, 1.0);\\n\\treturn t * t * (3.0 - 2.0 * t);\\n}\\n\\nvoid main() {\\n\\tfloat radius, alpha = 1.0, delta = fragWidth;\\n\\n\\tradius = length(2.0 * gl_PointCoord.xy - 1.0);\\n\\n\\tif (radius > 1.0 + delta) {\\n\\t\\tdiscard;\\n\\t}\\n\\n\\talpha -= smoothstep(1.0 - delta, 1.0 + delta, radius);\\n\\n\\tfloat borderRadius = fragBorderRadius;\\n\\tfloat ratio = smoothstep(borderRadius - delta, borderRadius + delta, radius);\\n\\tvec4 color = mix(fragColor, fragBorderColor, ratio);\\n\\tcolor.a *= alpha * opacity;\\n\\tgl_FragColor = color;\\n}\\n\"]),l.vert=h([\"precision highp float;\\n#define GLSLIFY 1\\n\\nattribute float x, y, xFract, yFract;\\nattribute float size, borderSize;\\nattribute vec4 colorId, borderColorId;\\nattribute float isActive;\\n\\nuniform bool constPointSize;\\nuniform float pixelRatio;\\nuniform vec2 paletteSize, scale, scaleFract, translate, translateFract;\\nuniform sampler2D paletteTexture;\\n\\nconst float maxSize = 100.;\\n\\nvarying vec4 fragColor, fragBorderColor;\\nvarying float fragBorderRadius, fragWidth;\\n\\nfloat pointSizeScale = (constPointSize) ? 2. : pixelRatio;\\n\\nbool isDirect = (paletteSize.x < 1.);\\n\\nvec4 getColor(vec4 id) {\\n return isDirect ? id / 255. : texture2D(paletteTexture,\\n vec2(\\n (id.x + .5) / paletteSize.x,\\n (id.y + .5) / paletteSize.y\\n )\\n );\\n}\\n\\nvoid main() {\\n // ignore inactive points\\n if (isActive == 0.) return;\\n\\n vec2 position = vec2(x, y);\\n vec2 positionFract = vec2(xFract, yFract);\\n\\n vec4 color = getColor(colorId);\\n vec4 borderColor = getColor(borderColorId);\\n\\n float size = size * maxSize / 255.;\\n float borderSize = borderSize * maxSize / 255.;\\n\\n gl_PointSize = (size + borderSize) * pointSizeScale;\\n\\n vec2 pos = (position + translate) * scale\\n + (positionFract + translateFract) * scale\\n + (position + translate) * scaleFract\\n + (positionFract + translateFract) * scaleFract;\\n\\n gl_Position = vec4(pos * 2. - 1., 0., 1.);\\n\\n fragBorderRadius = 1. - 2. * borderSize / (size + borderSize);\\n fragColor = color;\\n fragBorderColor = borderColor.a == 0. || borderSize == 0. ? vec4(color.rgb, 0.) : borderColor;\\n fragWidth = 1. / gl_PointSize;\\n}\\n\"]),g&&(l.frag=l.frag.replace(\"smoothstep\",\"smoothStep\"),s.frag=s.frag.replace(\"smoothstep\",\"smoothStep\")),this.drawCircle=t(l)}b.defaults={color:\"black\",borderColor:\"transparent\",borderSize:0,size:12,opacity:1,marker:void 0,viewport:null,range:null,pixelSize:null,count:0,offset:0,bounds:null,positions:[],snap:1e4},b.prototype.render=function(){return arguments.length&&this.update.apply(this,arguments),this.draw(),this},b.prototype.draw=function(){for(var t=this,e=arguments.length,r=new Array(e),n=0;n<e;n++)r[n]=arguments[n];var i=this.groups;if(1===r.length&&Array.isArray(r[0])&&(null===r[0][0]||Array.isArray(r[0][0]))&&(r=r[0]),this.regl._refresh(),r.length)for(var a=0;a<r.length;a++)this.drawItem(a,r[a]);else i.forEach((function(e,r){t.drawItem(r)}));return this},b.prototype.drawItem=function(t,e){var r=this.groups,n=r[t];if(\"number\"==typeof e&&(t=e,n=r[e],e=null),n&&n.count&&n.opacity){n.activation[0]&&this.drawCircle(this.getMarkerDrawOptions(0,n,e));for(var a=[],o=1;o<n.activation.length;o++)n.activation[o]&&(!0===n.activation[o]||n.activation[o].data.length)&&a.push.apply(a,i(this.getMarkerDrawOptions(o,n,e)));a.length&&this.drawMarker(a)}},b.prototype.getMarkerDrawOptions=function(t,e,r){var i=e.range,a=e.tree,o=e.viewport,s=e.activation,l=e.selectionBuffer,c=e.count;this.regl;if(!a)return r?[f({},e,{markerTexture:this.markerTextures[t],activation:s[t],count:r.length,elements:r,offset:0})]:[f({},e,{markerTexture:this.markerTextures[t],activation:s[t],offset:0})];var u=[],h=a.range(i,{lod:!0,px:[(i[2]-i[0])/o.width,(i[3]-i[1])/o.height]});if(r){for(var p=s[t].data,d=new Uint8Array(c),m=0;m<r.length;m++){var g=r[m];d[g]=p?p[g]:1}l.subdata(d)}for(var v=h.length;v--;){var y=n(h[v],2),x=y[0],b=y[1];u.push(f({},e,{markerTexture:this.markerTextures[t],activation:r?l:s[t],offset:x,count:b-x}))}return u},b.prototype.update=function(){for(var t=this,e=arguments.length,r=new Array(e),n=0;n<e;n++)r[n]=arguments[n];if(r.length){1===r.length&&Array.isArray(r[0])&&(r=r[0]);var i=this.groups,a=this.gl,o=this.regl,s=this.maxSize,c=this.maxColors,h=this.palette;this.groups=i=r.map((function(e,r){var n=i[r];if(void 0===e)return n;null===e?e={positions:null}:\"function\"==typeof e?e={ondraw:e}:\"number\"==typeof e[0]&&(e={positions:e}),null===(e=p(e,{positions:\"positions data points\",snap:\"snap cluster lod tree\",size:\"sizes size radius\",borderSize:\"borderSizes borderSize border-size bordersize borderWidth borderWidths border-width borderwidth stroke-width strokeWidth strokewidth outline\",color:\"colors color fill fill-color fillColor\",borderColor:\"borderColors borderColor stroke stroke-color strokeColor\",marker:\"markers marker shape\",range:\"range dataBox databox\",viewport:\"viewport viewPort viewBox viewbox\",opacity:\"opacity alpha transparency\",bounds:\"bound bounds boundaries limits\",tooManyColors:\"tooManyColors palette paletteMode optimizePalette enablePalette\"})).positions&&(e.positions=[]),null!=e.tooManyColors&&(t.tooManyColors=e.tooManyColors),n||(i[r]=n={id:r,scale:null,translate:null,scaleFract:null,translateFract:null,activation:[],selectionBuffer:o.buffer({data:new Uint8Array(0),usage:\"stream\",type:\"uint8\"}),sizeBuffer:o.buffer({data:new Uint8Array(0),usage:\"dynamic\",type:\"uint8\"}),colorBuffer:o.buffer({data:new Uint8Array(0),usage:\"dynamic\",type:\"uint8\"}),positionBuffer:o.buffer({data:new Uint8Array(0),usage:\"dynamic\",type:\"float\"}),positionFractBuffer:o.buffer({data:new Uint8Array(0),usage:\"dynamic\",type:\"float\"})},e=f({},b.defaults,e)),e.positions&&!(\"marker\"in e)&&(e.marker=n.marker,delete n.marker),e.marker&&!(\"positions\"in e)&&(e.positions=n.positions,delete n.positions);var g=0,x=0;if(d(n,e,[{snap:!0,size:function(t,e){return null==t&&(t=b.defaults.size),g+=t&&t.length?1:0,t},borderSize:function(t,e){return null==t&&(t=b.defaults.borderSize),g+=t&&t.length?1:0,t},opacity:parseFloat,color:function(e,r){return null==e&&(e=b.defaults.color),e=t.updateColor(e),x++,e},borderColor:function(e,r){return null==e&&(e=b.defaults.borderColor),e=t.updateColor(e),x++,e},bounds:function(t,e,r){return\"range\"in r||(r.range=null),t},positions:function(t,e,r){var n=e.snap,i=e.positionBuffer,a=e.positionFractBuffer,s=e.selectionBuffer;if(t.x||t.y)return t.x.length?e.xAttr={buffer:o.buffer(t.x),offset:0,stride:4,count:t.x.length}:e.xAttr={buffer:t.x.buffer,offset:4*t.x.offset||0,stride:4*(t.x.stride||1),count:t.x.count},t.y.length?e.yAttr={buffer:o.buffer(t.y),offset:0,stride:4,count:t.y.length}:e.yAttr={buffer:t.y.buffer,offset:4*t.y.offset||0,stride:4*(t.y.stride||1),count:t.y.count},e.count=Math.max(e.xAttr.count,e.yAttr.count),t;t=m(t,\"float64\");var c=e.count=Math.floor(t.length/2),f=e.bounds=c?l(t,2):null;if(r.range||e.range||(delete e.range,r.range=f),r.marker||e.marker||(delete e.marker,r.marker=null),n&&(!0===n||c>n)?e.tree=u(t,{bounds:f}):n&&n.length&&(e.tree=n),e.tree){var h={primitive:\"points\",usage:\"static\",data:e.tree,type:\"uint32\"};e.elements?e.elements(h):e.elements=o.elements(h)}var p=v.float32(t);return i({data:p,usage:\"dynamic\"}),a({data:v.fract32(t,p),usage:\"dynamic\"}),s({data:new Uint8Array(c),type:\"uint8\",usage:\"stream\"}),t}},{marker:function(e,r,n){var i=r.activation;if(i.forEach((function(t){return t&&t.destroy&&t.destroy()})),i.length=0,e&&\"number\"!=typeof e[0]){for(var a=[],s=0,l=Math.min(e.length,r.count);s<l;s++){var c=t.addMarker(e[s]);a[c]||(a[c]=new Uint8Array(r.count)),a[c][s]=1}for(var u=0;u<a.length;u++)if(a[u]){var f={data:a[u],type:\"uint8\",usage:\"static\"};i[u]?i[u](f):i[u]=o.buffer(f),i[u].data=a[u]}}else{i[t.addMarker(e)]=!0}return e},range:function(t,e,r){var n=e.bounds;if(n)return t||(t=n),e.scale=[1/(t[2]-t[0]),1/(t[3]-t[1])],e.translate=[-t[0],-t[1]],e.scaleFract=v.fract(e.scale),e.translateFract=v.fract(e.translate),t},viewport:function(t){return y(t||[a.drawingBufferWidth,a.drawingBufferHeight])}}]),g){var _=n,w=_.count,T=_.size,k=_.borderSize,A=_.sizeBuffer,M=new Uint8Array(2*w);if(T.length||k.length)for(var S=0;S<w;S++)M[2*S]=Math.round(255*(null==T[S]?T:T[S])/s),M[2*S+1]=Math.round(255*(null==k[S]?k:k[S])/s);A({data:M,usage:\"dynamic\"})}if(x){var E,L=n,C=L.count,P=L.color,I=L.borderColor,O=L.colorBuffer;if(t.tooManyColors){if(P.length||I.length){E=new Uint8Array(8*C);for(var z=0;z<C;z++){var D=P[z];E[8*z]=h[4*D],E[8*z+1]=h[4*D+1],E[8*z+2]=h[4*D+2],E[8*z+3]=h[4*D+3];var R=I[z];E[8*z+4]=h[4*R],E[8*z+5]=h[4*R+1],E[8*z+6]=h[4*R+2],E[8*z+7]=h[4*R+3]}}}else if(P.length||I.length){E=new Uint8Array(4*C+2);for(var F=0;F<C;F++)null!=P[F]&&(E[4*F]=P[F]%c,E[4*F+1]=Math.floor(P[F]/c)),null!=I[F]&&(E[4*F+2]=I[F]%c,E[4*F+3]=Math.floor(I[F]/c))}O({data:E||new Uint8Array(0),type:\"uint8\",usage:\"dynamic\"})}return n}))}},b.prototype.addMarker=function(t){var e,r=this.markerTextures,n=this.regl,i=this.markerCache,a=null==t?0:i.indexOf(t);if(a>=0)return a;if(t instanceof Uint8Array||t instanceof Uint8ClampedArray)e=t;else{e=new Uint8Array(t.length);for(var o=0,s=t.length;o<s;o++)e[o]=255*t[o]}var l=Math.floor(Math.sqrt(e.length));return a=r.length,i.push(t),r.push(n.texture({channels:1,data:e,radius:l,mag:\"linear\",min:\"linear\"})),a},b.prototype.updateColor=function(t){var e=this.paletteIds,r=this.palette,n=this.maxColors;Array.isArray(t)||(t=[t]);var i=[];if(\"number\"==typeof t[0]){var a=[];if(Array.isArray(t))for(var o=0;o<t.length;o+=4)a.push(t.slice(o,o+4));else for(var l=0;l<t.length;l+=4)a.push(t.subarray(l,l+4));t=a}for(var u=0;u<t.length;u++){var f=t[u];f=s(f,\"uint8\");var h=c(f,!1);if(null==e[h]){var p=r.length;e[h]=Math.floor(p/4),r[p]=f[0],r[p+1]=f[1],r[p+2]=f[2],r[p+3]=f[3]}i[u]=e[h]}return!this.tooManyColors&&r.length>4*n&&(this.tooManyColors=!0),this.updatePalette(r),1===i.length?i[0]:i},b.prototype.updatePalette=function(t){if(!this.tooManyColors){var e=this.maxColors,r=this.paletteTexture,n=Math.ceil(.25*t.length/e);if(n>1)for(var i=.25*(t=t.slice()).length%e;i<n*e;i++)t.push(0,0,0,0);r.height<n&&r.resize(e,n),r.subimage({width:Math.min(.25*t.length,e),height:n,data:t},0,0)}},b.prototype.destroy=function(){return this.groups.forEach((function(t){t.sizeBuffer.destroy(),t.positionBuffer.destroy(),t.positionFractBuffer.destroy(),t.colorBuffer.destroy(),t.activation.forEach((function(t){return t&&t.destroy&&t.destroy()})),t.selectionBuffer.destroy(),t.elements&&t.elements.destroy()})),this.groups.length=0,this.paletteTexture.destroy(),this.markerTextures.forEach((function(t){return t&&t.destroy&&t.destroy()})),this};var _=t(\"object-assign\");e.exports=function(t,e){var r=new x(t,e),n=r.render.bind(r);return _(n,{render:n,update:r.update.bind(r),draw:r.draw.bind(r),destroy:r.destroy.bind(r),regl:r.regl,gl:r.gl,canvas:r.gl.canvas,groups:r.groups,markers:r.markerCache,palette:r.palette}),n}},{\"@plotly/point-cluster\":59,\"array-bounds\":71,\"color-id\":87,\"color-normalize\":89,\"flatten-vertex-data\":191,glslify:227,\"is-iexplorer\":233,\"object-assign\":247,\"parse-rect\":249,\"pick-by-alias\":253,\"to-float32\":313,\"update-diff\":329}],282:[function(t,e,r){\"use strict\";var n=t(\"regl-scatter2d\"),i=t(\"pick-by-alias\"),a=t(\"array-bounds\"),o=t(\"raf\"),s=t(\"array-range\"),l=t(\"parse-rect\"),c=t(\"flatten-vertex-data\");function u(t,e){if(!(this instanceof u))return new u(t,e);this.traces=[],this.passes={},this.regl=t,this.scatter=n(t),this.canvas=this.scatter.canvas}function f(t,e,r){return(null!=t.id?t.id:t)<<16|(255&e)<<8|255&r}function h(t,e,r){var n,i,a,o,s=t[e],l=t[r];return s.length>2?(s[0],s[2],n=s[1],i=s[3]):s.length?(n=s[0],i=s[1]):(s.x,n=s.y,s.x+s.width,i=s.y+s.height),l.length>2?(a=l[0],o=l[2],l[1],l[3]):l.length?(a=l[0],o=l[1]):(a=l.x,l.y,o=l.x+l.width,l.y+l.height),[a,n,o,i]}function p(t){if(\"number\"==typeof t)return[t,t,t,t];if(2===t.length)return[t[0],t[1],t[0],t[1]];var e=l(t);return[e.x,e.y,e.x+e.width,e.y+e.height]}e.exports=u,u.prototype.render=function(){for(var t,e=this,r=[],n=arguments.length;n--;)r[n]=arguments[n];return r.length&&(t=this).update.apply(t,r),this.regl.attributes.preserveDrawingBuffer?this.draw():(this.dirty?null==this.planned&&(this.planned=o((function(){e.draw(),e.dirty=!0,e.planned=null}))):(this.draw(),this.dirty=!0,o((function(){e.dirty=!1}))),this)},u.prototype.update=function(){for(var t,e=[],r=arguments.length;r--;)e[r]=arguments[r];if(e.length){for(var n=0;n<e.length;n++)this.updateItem(n,e[n]);this.traces=this.traces.filter(Boolean);for(var i=[],a=0,o=0;o<this.traces.length;o++){for(var s=this.traces[o],l=this.traces[o].passes,c=0;c<l.length;c++)i.push(this.passes[l[c]]);s.passOffset=a,a+=s.passes.length}return(t=this.scatter).update.apply(t,i),this}},u.prototype.updateItem=function(t,e){var r=this.regl;if(null===e)return this.traces[t]=null,this;if(!e)return this;var n,o=i(e,{data:\"data items columns rows values dimensions samples x\",snap:\"snap cluster\",size:\"sizes size radius\",color:\"colors color fill fill-color fillColor\",opacity:\"opacity alpha transparency opaque\",borderSize:\"borderSizes borderSize border-size bordersize borderWidth borderWidths border-width borderwidth stroke-width strokeWidth strokewidth outline\",borderColor:\"borderColors borderColor bordercolor stroke stroke-color strokeColor\",marker:\"markers marker shape\",range:\"range ranges databox dataBox\",viewport:\"viewport viewBox viewbox\",domain:\"domain domains area areas\",padding:\"pad padding paddings pads margin margins\",transpose:\"transpose transposed\",diagonal:\"diagonal diag showDiagonal\",upper:\"upper up top upperhalf upperHalf showupperhalf showUpper showUpperHalf\",lower:\"lower low bottom lowerhalf lowerHalf showlowerhalf showLowerHalf showLower\"}),s=this.traces[t]||(this.traces[t]={id:t,buffer:r.buffer({usage:\"dynamic\",type:\"float\",data:new Uint8Array}),color:\"black\",marker:null,size:12,borderColor:\"transparent\",borderSize:1,viewport:l([r._gl.drawingBufferWidth,r._gl.drawingBufferHeight]),padding:[0,0,0,0],opacity:1,diagonal:!0,upper:!0,lower:!0});if(null!=o.color&&(s.color=o.color),null!=o.size&&(s.size=o.size),null!=o.marker&&(s.marker=o.marker),null!=o.borderColor&&(s.borderColor=o.borderColor),null!=o.borderSize&&(s.borderSize=o.borderSize),null!=o.opacity&&(s.opacity=o.opacity),o.viewport&&(s.viewport=l(o.viewport)),null!=o.diagonal&&(s.diagonal=o.diagonal),null!=o.upper&&(s.upper=o.upper),null!=o.lower&&(s.lower=o.lower),o.data){s.buffer(c(o.data)),s.columns=o.data.length,s.count=o.data[0].length,s.bounds=[];for(var u=0;u<s.columns;u++)s.bounds[u]=a(o.data[u],1)}o.range&&(s.range=o.range,n=s.range&&\"number\"!=typeof s.range[0]),o.domain&&(s.domain=o.domain);var d=!1;null!=o.padding&&(Array.isArray(o.padding)&&o.padding.length===s.columns&&\"number\"==typeof o.padding[o.padding.length-1]?(s.padding=o.padding.map(p),d=!0):s.padding=p(o.padding));var m=s.columns,g=s.count,v=s.viewport.width,y=s.viewport.height,x=s.viewport.x,b=s.viewport.y,_=v/m,w=y/m;s.passes=[];for(var T=0;T<m;T++)for(var k=0;k<m;k++)if((s.diagonal||k!==T)&&(s.upper||!(T>k))&&(s.lower||!(T<k))){var A=f(s.id,T,k),M=this.passes[A]||(this.passes[A]={});if(o.data&&(o.transpose?M.positions={x:{buffer:s.buffer,offset:k,count:g,stride:m},y:{buffer:s.buffer,offset:T,count:g,stride:m}}:M.positions={x:{buffer:s.buffer,offset:k*g,count:g},y:{buffer:s.buffer,offset:T*g,count:g}},M.bounds=h(s.bounds,T,k)),o.domain||o.viewport||o.data){var S=d?h(s.padding,T,k):s.padding;if(s.domain){var E=h(s.domain,T,k),L=E[0],C=E[1],P=E[2],I=E[3];M.viewport=[x+L*v+S[0],b+C*y+S[1],x+P*v-S[2],b+I*y-S[3]]}else M.viewport=[x+k*_+_*S[0],b+T*w+w*S[1],x+(k+1)*_-_*S[2],b+(T+1)*w-w*S[3]]}o.color&&(M.color=s.color),o.size&&(M.size=s.size),o.marker&&(M.marker=s.marker),o.borderSize&&(M.borderSize=s.borderSize),o.borderColor&&(M.borderColor=s.borderColor),o.opacity&&(M.opacity=s.opacity),o.range&&(M.range=n?h(s.range,T,k):s.range||M.bounds),s.passes.push(A)}return this},u.prototype.draw=function(){for(var t,e=[],r=arguments.length;r--;)e[r]=arguments[r];if(e.length){for(var n=[],i=0;i<e.length;i++)if(\"number\"==typeof e[i]){var a=this.traces[e[i]],o=a.passes,l=a.passOffset;n.push.apply(n,s(l,l+o.length))}else if(e[i].length){var c=e[i],u=this.traces[i],f=u.passes,h=u.passOffset;f=f.map((function(t,e){n[h+e]=c}))}(t=this.scatter).draw.apply(t,n)}else this.scatter.draw();return this},u.prototype.destroy=function(){return 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e=this._validate(t,this.minMonth,this.minDay,n.local.invalidYear);return(t=e.year()+(e.year()<0?1:0))%4==3||t%4==-1},monthsInYear:function(t){return this._validate(t,this.minMonth,this.minDay,n.local.invalidYear||n.regionalOptions[\"\"].invalidYear),13},weekOfYear:function(t,e,r){var n=this.newDate(t,e,r);return n.add(-n.dayOfWeek(),\"d\"),Math.floor((n.dayOfYear()-1)/7)+1},daysInMonth:function(t,e){var r=this._validate(t,e,this.minDay,n.local.invalidMonth);return this.daysPerMonth[r.month()-1]+(13===r.month()&&this.leapYear(r.year())?1:0)},weekDay:function(t,e,r){return(this.dayOfWeek(t,e,r)||7)<6},toJD:function(t,e,r){var i=this._validate(t,e,r,n.local.invalidDate);return(t=i.year())<0&&t++,i.day()+30*(i.month()-1)+365*(t-1)+Math.floor(t/4)+this.jdEpoch-1},fromJD:function(t){var e=Math.floor(t)+.5-this.jdEpoch,r=Math.floor((e-Math.floor((e+366)/1461))/365)+1;r<=0&&r--,e=Math.floor(t)+.5-this.newDate(r,1,1).toJD();var n=Math.floor(e/30)+1,i=e-30*(n-1)+1;return 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e=Math.floor(t/400)+1;t-=400*(e-1),t+=t>15?16:0;var r=Math.floor(t/32)+1,n=t-32*(r-1)+1;return this.newDate(e<=0?e-1:e,r,n)}});var o={20:\"Fruitbat\",21:\"Anchovy\"};n.calendars.discworld=a},{\"../main\":346,\"object-assign\":247}],335:[function(t,e,r){var n=t(\"../main\"),i=t(\"object-assign\");function a(t){this.local=this.regionalOptions[t||\"\"]||this.regionalOptions[\"\"]}a.prototype=new 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i=this._validate(t,e,r,n.local.invalidDate);return{yearType:(this.leapYear(i)?\"embolismic\":\"common\")+\" \"+[\"deficient\",\"regular\",\"complete\"][this.daysInYear(i)%10-3]}},toJD:function(t,e,r){var i=this._validate(t,e,r,n.local.invalidDate);t=i.year(),e=i.month(),r=i.day();var a=t<=0?t+1:t,o=this.jdEpoch+this._delay1(a)+this._delay2(a)+r+1;if(e<7){for(var s=7;s<=this.monthsInYear(t);s++)o+=this.daysInMonth(t,s);for(s=1;s<e;s++)o+=this.daysInMonth(t,s)}else for(s=7;s<e;s++)o+=this.daysInMonth(t,s);return o},_delay1:function(t){var e=Math.floor((235*t-234)/19),r=12084+13753*e,n=29*e+Math.floor(r/25920);return o(3*(n+1),7)<3&&n++,n},_delay2:function(t){var e=this._delay1(t-1),r=this._delay1(t);return this._delay1(t+1)-r==356?2:r-e==382?1:0},fromJD:function(t){t=Math.floor(t)+.5;for(var e=Math.floor(98496*(t-this.jdEpoch)/35975351)-1;t>=this.toJD(-1===e?1:e+1,7,1);)e++;for(var r=t<this.toJD(e,1,1)?7:1;t>this.toJD(e,r,this.daysInMonth(e,r));)r++;var n=t-this.toJD(e,r,1)+1;return this.newDate(e,r,n)}}),n.calendars.hebrew=a},{\"../main\":346,\"object-assign\":247}],337:[function(t,e,r){var n=t(\"../main\"),i=t(\"object-assign\");function a(t){this.local=this.regionalOptions[t||\"\"]||this.regionalOptions[\"\"]}a.prototype=new n.baseCalendar,i(a.prototype,{name:\"Islamic\",jdEpoch:1948439.5,daysPerMonth:[30,29,30,29,30,29,30,29,30,29,30,29],hasYearZero:!1,minMonth:1,firstMonth:1,minDay:1,regionalOptions:{\"\":{name:\"Islamic\",epochs:[\"BH\",\"AH\"],monthNames:[\"Muharram\",\"Safar\",\"Rabi' al-awwal\",\"Rabi' al-thani\",\"Jumada al-awwal\",\"Jumada al-thani\",\"Rajab\",\"Sha'aban\",\"Ramadan\",\"Shawwal\",\"Dhu al-Qi'dah\",\"Dhu al-Hijjah\"],monthNamesShort:[\"Muh\",\"Saf\",\"Rab1\",\"Rab2\",\"Jum1\",\"Jum2\",\"Raj\",\"Sha'\",\"Ram\",\"Shaw\",\"DhuQ\",\"DhuH\"],dayNames:[\"Yawm al-ahad\",\"Yawm al-ithnayn\",\"Yawm ath-thulaathaa'\",\"Yawm al-arbi'aa'\",\"Yawm al-kham\\u012bs\",\"Yawm al-jum'a\",\"Yawm as-sabt\"],dayNamesShort:[\"Aha\",\"Ith\",\"Thu\",\"Arb\",\"Kha\",\"Jum\",\"Sab\"],dayNamesMin:[\"Ah\",\"It\",\"Th\",\"Ar\",\"Kh\",\"Ju\",\"Sa\"],digits:null,dateFormat:\"yyyy/mm/dd\",firstDay:6,isRTL:!1}},leapYear:function(t){return(11*this._validate(t,this.minMonth,this.minDay,n.local.invalidYear).year()+14)%30<11},weekOfYear:function(t,e,r){var n=this.newDate(t,e,r);return n.add(-n.dayOfWeek(),\"d\"),Math.floor((n.dayOfYear()-1)/7)+1},daysInYear:function(t){return this.leapYear(t)?355:354},daysInMonth:function(t,e){var r=this._validate(t,e,this.minDay,n.local.invalidMonth);return this.daysPerMonth[r.month()-1]+(12===r.month()&&this.leapYear(r.year())?1:0)},weekDay:function(t,e,r){return 5!==this.dayOfWeek(t,e,r)},toJD:function(t,e,r){var i=this._validate(t,e,r,n.local.invalidDate);return t=i.year(),e=i.month(),t=t<=0?t+1:t,(r=i.day())+Math.ceil(29.5*(e-1))+354*(t-1)+Math.floor((3+11*t)/30)+this.jdEpoch-1},fromJD:function(t){t=Math.floor(t)+.5;var e=Math.floor((30*(t-this.jdEpoch)+10646)/10631);e=e<=0?e-1:e;var r=Math.min(12,Math.ceil((t-29-this.toJD(e,1,1))/29.5)+1),n=t-this.toJD(e,r,1)+1;return this.newDate(e,r,n)}}),n.calendars.islamic=a},{\"../main\":346,\"object-assign\":247}],338:[function(t,e,r){var n=t(\"../main\"),i=t(\"object-assign\");function a(t){this.local=this.regionalOptions[t||\"\"]||this.regionalOptions[\"\"]}a.prototype=new n.baseCalendar,i(a.prototype,{name:\"Julian\",jdEpoch:1721423.5,daysPerMonth:[31,28,31,30,31,30,31,31,30,31,30,31],hasYearZero:!1,minMonth:1,firstMonth:1,minDay:1,regionalOptions:{\"\":{name:\"Julian\",epochs:[\"BC\",\"AD\"],monthNames:[\"January\",\"February\",\"March\",\"April\",\"May\",\"June\",\"July\",\"August\",\"September\",\"October\",\"November\",\"December\"],monthNamesShort:[\"Jan\",\"Feb\",\"Mar\",\"Apr\",\"May\",\"Jun\",\"Jul\",\"Aug\",\"Sep\",\"Oct\",\"Nov\",\"Dec\"],dayNames:[\"Sunday\",\"Monday\",\"Tuesday\",\"Wednesday\",\"Thursday\",\"Friday\",\"Saturday\"],dayNamesShort:[\"Sun\",\"Mon\",\"Tue\",\"Wed\",\"Thu\",\"Fri\",\"Sat\"],dayNamesMin:[\"Su\",\"Mo\",\"Tu\",\"We\",\"Th\",\"Fr\",\"Sa\"],digits:null,dateFormat:\"mm/dd/yyyy\",firstDay:0,isRTL:!1}},leapYear:function(t){var e=this._validate(t,this.minMonth,this.minDay,n.local.invalidYear);return(t=e.year()<0?e.year()+1:e.year())%4==0},weekOfYear:function(t,e,r){var n=this.newDate(t,e,r);return n.add(4-(n.dayOfWeek()||7),\"d\"),Math.floor((n.dayOfYear()-1)/7)+1},daysInMonth:function(t,e){var r=this._validate(t,e,this.minDay,n.local.invalidMonth);return this.daysPerMonth[r.month()-1]+(2===r.month()&&this.leapYear(r.year())?1:0)},weekDay:function(t,e,r){return(this.dayOfWeek(t,e,r)||7)<6},toJD:function(t,e,r){var i=this._validate(t,e,r,n.local.invalidDate);return t=i.year(),e=i.month(),r=i.day(),t<0&&t++,e<=2&&(t--,e+=12),Math.floor(365.25*(t+4716))+Math.floor(30.6001*(e+1))+r-1524.5},fromJD:function(t){var e=Math.floor(t+.5)+1524,r=Math.floor((e-122.1)/365.25),n=Math.floor(365.25*r),i=Math.floor((e-n)/30.6001),a=i-Math.floor(i<14?1:13),o=r-Math.floor(a>2?4716:4715),s=e-n-Math.floor(30.6001*i);return o<=0&&o--,this.newDate(o,a,s)}}),n.calendars.julian=a},{\"../main\":346,\"object-assign\":247}],339:[function(t,e,r){var n=t(\"../main\"),i=t(\"object-assign\");function a(t){this.local=this.regionalOptions[t||\"\"]||this.regionalOptions[\"\"]}function o(t,e){return t-e*Math.floor(t/e)}function s(t,e){return o(t-1,e)+1}a.prototype=new n.baseCalendar,i(a.prototype,{name:\"Mayan\",jdEpoch:584282.5,hasYearZero:!0,minMonth:0,firstMonth:0,minDay:0,regionalOptions:{\"\":{name:\"Mayan\",epochs:[\"\",\"\"],monthNames:[\"0\",\"1\",\"2\",\"3\",\"4\",\"5\",\"6\",\"7\",\"8\",\"9\",\"10\",\"11\",\"12\",\"13\",\"14\",\"15\",\"16\",\"17\"],monthNamesShort:[\"0\",\"1\",\"2\",\"3\",\"4\",\"5\",\"6\",\"7\",\"8\",\"9\",\"10\",\"11\",\"12\",\"13\",\"14\",\"15\",\"16\",\"17\"],dayNames:[\"0\",\"1\",\"2\",\"3\",\"4\",\"5\",\"6\",\"7\",\"8\",\"9\",\"10\",\"11\",\"12\",\"13\",\"14\",\"15\",\"16\",\"17\",\"18\",\"19\"],dayNamesShort:[\"0\",\"1\",\"2\",\"3\",\"4\",\"5\",\"6\",\"7\",\"8\",\"9\",\"10\",\"11\",\"12\",\"13\",\"14\",\"15\",\"16\",\"17\",\"18\",\"19\"],dayNamesMin:[\"0\",\"1\",\"2\",\"3\",\"4\",\"5\",\"6\",\"7\",\"8\",\"9\",\"10\",\"11\",\"12\",\"13\",\"14\",\"15\",\"16\",\"17\",\"18\",\"19\"],digits:null,dateFormat:\"YYYY.m.d\",firstDay:0,isRTL:!1,haabMonths:[\"Pop\",\"Uo\",\"Zip\",\"Zotz\",\"Tzec\",\"Xul\",\"Yaxkin\",\"Mol\",\"Chen\",\"Yax\",\"Zac\",\"Ceh\",\"Mac\",\"Kankin\",\"Muan\",\"Pax\",\"Kayab\",\"Cumku\",\"Uayeb\"],tzolkinMonths:[\"Imix\",\"Ik\",\"Akbal\",\"Kan\",\"Chicchan\",\"Cimi\",\"Manik\",\"Lamat\",\"Muluc\",\"Oc\",\"Chuen\",\"Eb\",\"Ben\",\"Ix\",\"Men\",\"Cib\",\"Caban\",\"Etznab\",\"Cauac\",\"Ahau\"]}},leapYear:function(t){return this._validate(t,this.minMonth,this.minDay,n.local.invalidYear),!1},formatYear:function(t){t=this._validate(t,this.minMonth,this.minDay,n.local.invalidYear).year();var e=Math.floor(t/400);return t%=400,t+=t<0?400:0,e+\".\"+Math.floor(t/20)+\".\"+t%20},forYear:function(t){if((t=t.split(\".\")).length<3)throw\"Invalid Mayan year\";for(var e=0,r=0;r<t.length;r++){var n=parseInt(t[r],10);if(Math.abs(n)>19||r>0&&n<0)throw\"Invalid Mayan year\";e=20*e+n}return e},monthsInYear:function(t){return this._validate(t,this.minMonth,this.minDay,n.local.invalidYear),18},weekOfYear:function(t,e,r){return this._validate(t,e,r,n.local.invalidDate),0},daysInYear:function(t){return this._validate(t,this.minMonth,this.minDay,n.local.invalidYear),360},daysInMonth:function(t,e){return this._validate(t,e,this.minDay,n.local.invalidMonth),20},daysInWeek:function(){return 5},dayOfWeek:function(t,e,r){return this._validate(t,e,r,n.local.invalidDate).day()},weekDay:function(t,e,r){return this._validate(t,e,r,n.local.invalidDate),!0},extraInfo:function(t,e,r){var i=this._validate(t,e,r,n.local.invalidDate).toJD(),a=this._toHaab(i),o=this._toTzolkin(i);return{haabMonthName:this.local.haabMonths[a[0]-1],haabMonth:a[0],haabDay:a[1],tzolkinDayName:this.local.tzolkinMonths[o[0]-1],tzolkinDay:o[0],tzolkinTrecena:o[1]}},_toHaab:function(t){var e=o((t-=this.jdEpoch)+8+340,365);return[Math.floor(e/20)+1,o(e,20)]},_toTzolkin:function(t){return[s((t-=this.jdEpoch)+20,20),s(t+4,13)]},toJD:function(t,e,r){var i=this._validate(t,e,r,n.local.invalidDate);return i.day()+20*i.month()+360*i.year()+this.jdEpoch},fromJD:function(t){t=Math.floor(t)+.5-this.jdEpoch;var e=Math.floor(t/360);t%=360,t+=t<0?360:0;var r=Math.floor(t/20),n=t%20;return this.newDate(e,r,n)}}),n.calendars.mayan=a},{\"../main\":346,\"object-assign\":247}],340:[function(t,e,r){var n=t(\"../main\"),i=t(\"object-assign\");function a(t){this.local=this.regionalOptions[t||\"\"]||this.regionalOptions[\"\"]}a.prototype=new n.baseCalendar;var o=n.instance(\"gregorian\");i(a.prototype,{name:\"Nanakshahi\",jdEpoch:2257673.5,daysPerMonth:[31,31,31,31,31,30,30,30,30,30,30,30],hasYearZero:!1,minMonth:1,firstMonth:1,minDay:1,regionalOptions:{\"\":{name:\"Nanakshahi\",epochs:[\"BN\",\"AN\"],monthNames:[\"Chet\",\"Vaisakh\",\"Jeth\",\"Harh\",\"Sawan\",\"Bhadon\",\"Assu\",\"Katak\",\"Maghar\",\"Poh\",\"Magh\",\"Phagun\"],monthNamesShort:[\"Che\",\"Vai\",\"Jet\",\"Har\",\"Saw\",\"Bha\",\"Ass\",\"Kat\",\"Mgr\",\"Poh\",\"Mgh\",\"Pha\"],dayNames:[\"Somvaar\",\"Mangalvar\",\"Budhvaar\",\"Veervaar\",\"Shukarvaar\",\"Sanicharvaar\",\"Etvaar\"],dayNamesShort:[\"Som\",\"Mangal\",\"Budh\",\"Veer\",\"Shukar\",\"Sanichar\",\"Et\"],dayNamesMin:[\"So\",\"Ma\",\"Bu\",\"Ve\",\"Sh\",\"Sa\",\"Et\"],digits:null,dateFormat:\"dd-mm-yyyy\",firstDay:0,isRTL:!1}},leapYear:function(t){var e=this._validate(t,this.minMonth,this.minDay,n.local.invalidYear||n.regionalOptions[\"\"].invalidYear);return o.leapYear(e.year()+(e.year()<1?1:0)+1469)},weekOfYear:function(t,e,r){var n=this.newDate(t,e,r);return n.add(1-(n.dayOfWeek()||7),\"d\"),Math.floor((n.dayOfYear()-1)/7)+1},daysInMonth:function(t,e){var r=this._validate(t,e,this.minDay,n.local.invalidMonth);return this.daysPerMonth[r.month()-1]+(12===r.month()&&this.leapYear(r.year())?1:0)},weekDay:function(t,e,r){return(this.dayOfWeek(t,e,r)||7)<6},toJD:function(t,e,r){var i=this._validate(t,e,r,n.local.invalidMonth);(t=i.year())<0&&t++;for(var a=i.day(),s=1;s<i.month();s++)a+=this.daysPerMonth[s-1];return a+o.toJD(t+1468,3,13)},fromJD:function(t){t=Math.floor(t+.5);for(var e=Math.floor((t-(this.jdEpoch-1))/366);t>=this.toJD(e+1,1,1);)e++;for(var r=t-Math.floor(this.toJD(e,1,1)+.5)+1,n=1;r>this.daysInMonth(e,n);)r-=this.daysInMonth(e,n),n++;return this.newDate(e,n,r)}}),n.calendars.nanakshahi=a},{\"../main\":346,\"object-assign\":247}],341:[function(t,e,r){var n=t(\"../main\"),i=t(\"object-assign\");function a(t){this.local=this.regionalOptions[t||\"\"]||this.regionalOptions[\"\"]}a.prototype=new n.baseCalendar,i(a.prototype,{name:\"Nepali\",jdEpoch:1700709.5,daysPerMonth:[31,31,32,32,31,30,30,29,30,29,30,30],hasYearZero:!1,minMonth:1,firstMonth:1,minDay:1,daysPerYear:365,regionalOptions:{\"\":{name:\"Nepali\",epochs:[\"BBS\",\"ABS\"],monthNames:[\"Baisakh\",\"Jestha\",\"Ashadh\",\"Shrawan\",\"Bhadra\",\"Ashwin\",\"Kartik\",\"Mangsir\",\"Paush\",\"Mangh\",\"Falgun\",\"Chaitra\"],monthNamesShort:[\"Bai\",\"Je\",\"As\",\"Shra\",\"Bha\",\"Ash\",\"Kar\",\"Mang\",\"Pau\",\"Ma\",\"Fal\",\"Chai\"],dayNames:[\"Aaitabaar\",\"Sombaar\",\"Manglbaar\",\"Budhabaar\",\"Bihibaar\",\"Shukrabaar\",\"Shanibaar\"],dayNamesShort:[\"Aaita\",\"Som\",\"Mangl\",\"Budha\",\"Bihi\",\"Shukra\",\"Shani\"],dayNamesMin:[\"Aai\",\"So\",\"Man\",\"Bu\",\"Bi\",\"Shu\",\"Sha\"],digits:null,dateFormat:\"dd/mm/yyyy\",firstDay:1,isRTL:!1}},leapYear:function(t){return this.daysInYear(t)!==this.daysPerYear},weekOfYear:function(t,e,r){var n=this.newDate(t,e,r);return n.add(-n.dayOfWeek(),\"d\"),Math.floor((n.dayOfYear()-1)/7)+1},daysInYear:function(t){if(t=this._validate(t,this.minMonth,this.minDay,n.local.invalidYear).year(),void 0===this.NEPALI_CALENDAR_DATA[t])return this.daysPerYear;for(var e=0,r=this.minMonth;r<=12;r++)e+=this.NEPALI_CALENDAR_DATA[t][r];return e},daysInMonth:function(t,e){return t.year&&(e=t.month(),t=t.year()),this._validate(t,e,this.minDay,n.local.invalidMonth),void 0===this.NEPALI_CALENDAR_DATA[t]?this.daysPerMonth[e-1]:this.NEPALI_CALENDAR_DATA[t][e]},weekDay:function(t,e,r){return 6!==this.dayOfWeek(t,e,r)},toJD:function(t,e,r){var i=this._validate(t,e,r,n.local.invalidDate);t=i.year(),e=i.month(),r=i.day();var a=n.instance(),o=0,s=e,l=t;this._createMissingCalendarData(t);var c=t-(s>9||9===s&&r>=this.NEPALI_CALENDAR_DATA[l][0]?56:57);for(9!==e&&(o=r,s--);9!==s;)s<=0&&(s=12,l--),o+=this.NEPALI_CALENDAR_DATA[l][s],s--;return 9===e?(o+=r-this.NEPALI_CALENDAR_DATA[l][0])<0&&(o+=a.daysInYear(c)):o+=this.NEPALI_CALENDAR_DATA[l][9]-this.NEPALI_CALENDAR_DATA[l][0],a.newDate(c,1,1).add(o,\"d\").toJD()},fromJD:function(t){var e=n.instance().fromJD(t),r=e.year(),i=e.dayOfYear(),a=r+56;this._createMissingCalendarData(a);for(var o=9,s=this.NEPALI_CALENDAR_DATA[a][0],l=this.NEPALI_CALENDAR_DATA[a][o]-s+1;i>l;)++o>12&&(o=1,a++),l+=this.NEPALI_CALENDAR_DATA[a][o];var c=this.NEPALI_CALENDAR_DATA[a][o]-(l-i);return this.newDate(a,o,c)},_createMissingCalendarData:function(t){var e=this.daysPerMonth.slice(0);e.unshift(17);for(var r=t-1;r<t+2;r++)void 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e=this._validate(t,this.minMonth,this.minDay,n.local.invalidYear);return 682*((e.year()-(e.year()>0?474:473))%2820+474+38)%2816<682},weekOfYear:function(t,e,r){var n=this.newDate(t,e,r);return n.add(-(n.dayOfWeek()+1)%7,\"d\"),Math.floor((n.dayOfYear()-1)/7)+1},daysInMonth:function(t,e){var r=this._validate(t,e,this.minDay,n.local.invalidMonth);return this.daysPerMonth[r.month()-1]+(12===r.month()&&this.leapYear(r.year())?1:0)},weekDay:function(t,e,r){return 5!==this.dayOfWeek(t,e,r)},toJD:function(t,e,r){var i=this._validate(t,e,r,n.local.invalidDate);t=i.year(),e=i.month(),r=i.day();var a=t-(t>=0?474:473),s=474+o(a,2820);return r+(e<=7?31*(e-1):30*(e-1)+6)+Math.floor((682*s-110)/2816)+365*(s-1)+1029983*Math.floor(a/2820)+this.jdEpoch-1},fromJD:function(t){var e=(t=Math.floor(t)+.5)-this.toJD(475,1,1),r=Math.floor(e/1029983),n=o(e,1029983),i=2820;if(1029982!==n){var a=Math.floor(n/366),s=o(n,366);i=Math.floor((2134*a+2816*s+2815)/1028522)+a+1}var l=i+2820*r+474;l=l<=0?l-1:l;var 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i=this._validate(t,this.minMonth,this.minDay,n.local.invalidYear);t=this._t2gYear(i.year());return a.weekOfYear(t,i.month(),i.day())},daysInMonth:function(t,e){var r=this._validate(t,e,this.minDay,n.local.invalidMonth);return this.daysPerMonth[r.month()-1]+(2===r.month()&&this.leapYear(r.year())?1:0)},weekDay:function(t,e,r){return(this.dayOfWeek(t,e,r)||7)<6},toJD:function(t,e,r){var i=this._validate(t,e,r,n.local.invalidDate);t=this._t2gYear(i.year());return a.toJD(t,i.month(),i.day())},fromJD:function(t){var e=a.fromJD(t),r=this._g2tYear(e.year());return this.newDate(r,e.month(),e.day())},_t2gYear:function(t){return t+this.yearsOffset+(t>=-this.yearsOffset&&t<=-1?1:0)},_g2tYear:function(t){return t-this.yearsOffset-(t>=1&&t<=this.yearsOffset?1:0)}}),n.calendars.taiwan=o},{\"../main\":346,\"object-assign\":247}],344:[function(t,e,r){var n=t(\"../main\"),i=t(\"object-assign\"),a=n.instance();function 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e=this._validate(t,this.minMonth,this.minDay,n.local.invalidYear);t=this._t2gYear(e.year());return a.leapYear(t)},weekOfYear:function(t,e,r){var i=this._validate(t,this.minMonth,this.minDay,n.local.invalidYear);t=this._t2gYear(i.year());return a.weekOfYear(t,i.month(),i.day())},daysInMonth:function(t,e){var r=this._validate(t,e,this.minDay,n.local.invalidMonth);return this.daysPerMonth[r.month()-1]+(2===r.month()&&this.leapYear(r.year())?1:0)},weekDay:function(t,e,r){return(this.dayOfWeek(t,e,r)||7)<6},toJD:function(t,e,r){var i=this._validate(t,e,r,n.local.invalidDate);t=this._t2gYear(i.year());return a.toJD(t,i.month(),i.day())},fromJD:function(t){var e=a.fromJD(t),r=this._g2tYear(e.year());return this.newDate(r,e.month(),e.day())},_t2gYear:function(t){return t-this.yearsOffset-(t>=1&&t<=this.yearsOffset?1:0)},_g2tYear:function(t){return t+this.yearsOffset+(t>=-this.yearsOffset&&t<=-1?1:0)}}),n.calendars.thai=o},{\"../main\":346,\"object-assign\":247}],345:[function(t,e,r){var n=t(\"../main\"),i=t(\"object-assign\");function a(t){this.local=this.regionalOptions[t||\"\"]||this.regionalOptions[\"\"]}a.prototype=new n.baseCalendar,i(a.prototype,{name:\"UmmAlQura\",hasYearZero:!1,minMonth:1,firstMonth:1,minDay:1,regionalOptions:{\"\":{name:\"Umm al-Qura\",epochs:[\"BH\",\"AH\"],monthNames:[\"Al-Muharram\",\"Safar\",\"Rabi' al-awwal\",\"Rabi' Al-Thani\",\"Jumada Al-Awwal\",\"Jumada Al-Thani\",\"Rajab\",\"Sha'aban\",\"Ramadan\",\"Shawwal\",\"Dhu al-Qi'dah\",\"Dhu al-Hijjah\"],monthNamesShort:[\"Muh\",\"Saf\",\"Rab1\",\"Rab2\",\"Jum1\",\"Jum2\",\"Raj\",\"Sha'\",\"Ram\",\"Shaw\",\"DhuQ\",\"DhuH\"],dayNames:[\"Yawm al-Ahad\",\"Yawm al-Ithnain\",\"Yawm al-Thal\\u0101th\\u0101\\u2019\",\"Yawm al-Arba\\u2018\\u0101\\u2019\",\"Yawm al-Kham\\u012bs\",\"Yawm al-Jum\\u2018a\",\"Yawm al-Sabt\"],dayNamesMin:[\"Ah\",\"Ith\",\"Th\",\"Ar\",\"Kh\",\"Ju\",\"Sa\"],digits:null,dateFormat:\"yyyy/mm/dd\",firstDay:6,isRTL:!0}},leapYear:function(t){var e=this._validate(t,this.minMonth,this.minDay,n.local.invalidYear);return 355===this.daysInYear(e.year())},weekOfYear:function(t,e,r){var n=this.newDate(t,e,r);return n.add(-n.dayOfWeek(),\"d\"),Math.floor((n.dayOfYear()-1)/7)+1},daysInYear:function(t){for(var e=0,r=1;r<=12;r++)e+=this.daysInMonth(t,r);return e},daysInMonth:function(t,e){for(var r=this._validate(t,e,this.minDay,n.local.invalidMonth).toJD()-24e5+.5,i=0,a=0;a<o.length;a++){if(o[a]>r)return o[i]-o[i-1];i++}return 30},weekDay:function(t,e,r){return 5!==this.dayOfWeek(t,e,r)},toJD:function(t,e,r){var i=this._validate(t,e,r,n.local.invalidDate),a=12*(i.year()-1)+i.month()-15292;return i.day()+o[a-1]-1+24e5-.5},fromJD:function(t){for(var e=t-24e5+.5,r=0,n=0;n<o.length&&!(o[n]>e);n++)r++;var i=r+15292,a=Math.floor((i-1)/12),s=a+1,l=i-12*a,c=e-o[r-1]+1;return this.newDate(s,l,c)},isValid:function(t,e,r){var i=n.baseCalendar.prototype.isValid.apply(this,arguments);return i&&(i=(t=null!=t.year?t.year:t)>=1276&&t<=1500),i},_validate:function(t,e,r,i){var a=n.baseCalendar.prototype._validate.apply(this,arguments);if(a.year<1276||a.year>1500)throw i.replace(/\\{0\\}/,this.local.name);return a}}),n.calendars.ummalqura=a;var 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n=t(\"object-assign\");function i(){this.regionalOptions=[],this.regionalOptions[\"\"]={invalidCalendar:\"Calendar {0} not found\",invalidDate:\"Invalid {0} date\",invalidMonth:\"Invalid {0} month\",invalidYear:\"Invalid {0} year\",differentCalendars:\"Cannot mix {0} and {1} dates\"},this.local=this.regionalOptions[\"\"],this.calendars={},this._localCals={}}function a(t,e,r,n){if(this._calendar=t,this._year=e,this._month=r,this._day=n,0===this._calendar._validateLevel&&!this._calendar.isValid(this._year,this._month,this._day))throw(c.local.invalidDate||c.regionalOptions[\"\"].invalidDate).replace(/\\{0\\}/,this._calendar.local.name)}function o(t,e){return\"000000\".substring(0,e-(t=\"\"+t).length)+t}function s(){this.shortYearCutoff=\"+10\"}function l(t){this.local=this.regionalOptions[t]||this.regionalOptions[\"\"]}n(i.prototype,{instance:function(t,e){t=(t||\"gregorian\").toLowerCase(),e=e||\"\";var r=this._localCals[t+\"-\"+e];if(!r&&this.calendars[t]&&(r=new this.calendars[t](e),this._localCals[t+\"-\"+e]=r),!r)throw(this.local.invalidCalendar||this.regionalOptions[\"\"].invalidCalendar).replace(/\\{0\\}/,t);return r},newDate:function(t,e,r,n,i){return(n=(null!=t&&t.year?t.calendar():\"string\"==typeof n?this.instance(n,i):n)||this.instance()).newDate(t,e,r)},substituteDigits:function(t){return function(e){return(e+\"\").replace(/[0-9]/g,(function(e){return t[e]}))}},substituteChineseDigits:function(t,e){return function(r){for(var n=\"\",i=0;r>0;){var a=r%10;n=(0===a?\"\":t[a]+e[i])+n,i++,r=Math.floor(r/10)}return 0===n.indexOf(t[1]+e[1])&&(n=n.substr(1)),n||t[0]}}}),n(a.prototype,{newDate:function(t,e,r){return this._calendar.newDate(null==t?this:t,e,r)},year:function(t){return 0===arguments.length?this._year:this.set(t,\"y\")},month:function(t){return 0===arguments.length?this._month:this.set(t,\"m\")},day:function(t){return 0===arguments.length?this._day:this.set(t,\"d\")},date:function(t,e,r){if(!this._calendar.isValid(t,e,r))throw(c.local.invalidDate||c.regionalOptions[\"\"].invalidDate).replace(/\\{0\\}/,this._calendar.local.name);return this._year=t,this._month=e,this._day=r,this},leapYear:function(){return this._calendar.leapYear(this)},epoch:function(){return this._calendar.epoch(this)},formatYear:function(){return this._calendar.formatYear(this)},monthOfYear:function(){return this._calendar.monthOfYear(this)},weekOfYear:function(){return this._calendar.weekOfYear(this)},daysInYear:function(){return this._calendar.daysInYear(this)},dayOfYear:function(){return this._calendar.dayOfYear(this)},daysInMonth:function(){return this._calendar.daysInMonth(this)},dayOfWeek:function(){return this._calendar.dayOfWeek(this)},weekDay:function(){return this._calendar.weekDay(this)},extraInfo:function(){return this._calendar.extraInfo(this)},add:function(t,e){return this._calendar.add(this,t,e)},set:function(t,e){return this._calendar.set(this,t,e)},compareTo:function(t){if(this._calendar.name!==t._calendar.name)throw(c.local.differentCalendars||c.regionalOptions[\"\"].differentCalendars).replace(/\\{0\\}/,this._calendar.local.name).replace(/\\{1\\}/,t._calendar.local.name);var e=this._year!==t._year?this._year-t._year:this._month!==t._month?this.monthOfYear()-t.monthOfYear():this._day-t._day;return 0===e?0:e<0?-1:1},calendar:function(){return this._calendar},toJD:function(){return this._calendar.toJD(this)},fromJD:function(t){return this._calendar.fromJD(t)},toJSDate:function(){return this._calendar.toJSDate(this)},fromJSDate:function(t){return this._calendar.fromJSDate(t)},toString:function(){return(this.year()<0?\"-\":\"\")+o(Math.abs(this.year()),4)+\"-\"+o(this.month(),2)+\"-\"+o(this.day(),2)}}),n(s.prototype,{_validateLevel:0,newDate:function(t,e,r){return null==t?this.today():(t.year&&(this._validate(t,e,r,c.local.invalidDate||c.regionalOptions[\"\"].invalidDate),r=t.day(),e=t.month(),t=t.year()),new a(this,t,e,r))},today:function(){return this.fromJSDate(new Date)},epoch:function(t){return this._validate(t,this.minMonth,this.minDay,c.local.invalidYear||c.regionalOptions[\"\"].invalidYear).year()<0?this.local.epochs[0]:this.local.epochs[1]},formatYear:function(t){var e=this._validate(t,this.minMonth,this.minDay,c.local.invalidYear||c.regionalOptions[\"\"].invalidYear);return(e.year()<0?\"-\":\"\")+o(Math.abs(e.year()),4)},monthsInYear:function(t){return this._validate(t,this.minMonth,this.minDay,c.local.invalidYear||c.regionalOptions[\"\"].invalidYear),12},monthOfYear:function(t,e){var r=this._validate(t,e,this.minDay,c.local.invalidMonth||c.regionalOptions[\"\"].invalidMonth);return(r.month()+this.monthsInYear(r)-this.firstMonth)%this.monthsInYear(r)+this.minMonth},fromMonthOfYear:function(t,e){var r=(e+this.firstMonth-2*this.minMonth)%this.monthsInYear(t)+this.minMonth;return this._validate(t,r,this.minDay,c.local.invalidMonth||c.regionalOptions[\"\"].invalidMonth),r},daysInYear:function(t){var e=this._validate(t,this.minMonth,this.minDay,c.local.invalidYear||c.regionalOptions[\"\"].invalidYear);return this.leapYear(e)?366:365},dayOfYear:function(t,e,r){var n=this._validate(t,e,r,c.local.invalidDate||c.regionalOptions[\"\"].invalidDate);return n.toJD()-this.newDate(n.year(),this.fromMonthOfYear(n.year(),this.minMonth),this.minDay).toJD()+1},daysInWeek:function(){return 7},dayOfWeek:function(t,e,r){var n=this._validate(t,e,r,c.local.invalidDate||c.regionalOptions[\"\"].invalidDate);return(Math.floor(this.toJD(n))+2)%this.daysInWeek()},extraInfo:function(t,e,r){return this._validate(t,e,r,c.local.invalidDate||c.regionalOptions[\"\"].invalidDate),{}},add:function(t,e,r){return this._validate(t,this.minMonth,this.minDay,c.local.invalidDate||c.regionalOptions[\"\"].invalidDate),this._correctAdd(t,this._add(t,e,r),e,r)},_add:function(t,e,r){if(this._validateLevel++,\"d\"===r||\"w\"===r){var n=t.toJD()+e*(\"w\"===r?this.daysInWeek():1),i=t.calendar().fromJD(n);return this._validateLevel--,[i.year(),i.month(),i.day()]}try{var a=t.year()+(\"y\"===r?e:0),o=t.monthOfYear()+(\"m\"===r?e:0);i=t.day();\"y\"===r?(t.month()!==this.fromMonthOfYear(a,o)&&(o=this.newDate(a,t.month(),this.minDay).monthOfYear()),o=Math.min(o,this.monthsInYear(a)),i=Math.min(i,this.daysInMonth(a,this.fromMonthOfYear(a,o)))):\"m\"===r&&(!function(t){for(;o<t.minMonth;)a--,o+=t.monthsInYear(a);for(var e=t.monthsInYear(a);o>e-1+t.minMonth;)a++,o-=e,e=t.monthsInYear(a)}(this),i=Math.min(i,this.daysInMonth(a,this.fromMonthOfYear(a,o))));var s=[a,this.fromMonthOfYear(a,o),i];return this._validateLevel--,s}catch(t){throw 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r,s,l=o(t,e),c=l.on,u=l.off.concat(l.explicitOff),f={},h=t._fullLayout.annotations;if(!c.length&&!u.length)return;for(r=0;r<c.length;r++)(s=a(t.layout,\"annotations\",h[c[r]])).modifyItem(\"visible\",!0),n.extendFlat(f,s.getUpdateObj());for(r=0;r<u.length;r++)(s=a(t.layout,\"annotations\",h[u[r]])).modifyItem(\"visible\",!1),n.extendFlat(f,s.getUpdateObj());return i.call(\"update\",t,{},f)}}},{\"../../lib\":503,\"../../plot_api/plot_template\":543,\"../../registry\":638}],352:[function(t,e,r){\"use strict\";var n=t(\"../../lib\"),i=t(\"../color\");e.exports=function(t,e,r,a){a(\"opacity\");var o=a(\"bgcolor\"),s=a(\"bordercolor\"),l=i.opacity(s);a(\"borderpad\");var c=a(\"borderwidth\"),u=a(\"showarrow\");if(a(\"text\",u?\" \":r._dfltTitle.annotation),a(\"textangle\"),n.coerceFont(a,\"font\",r.font),a(\"width\"),a(\"align\"),a(\"height\")&&a(\"valign\"),u){var f,h,p=a(\"arrowside\");-1!==p.indexOf(\"end\")&&(f=a(\"arrowhead\"),h=a(\"arrowsize\")),-1!==p.indexOf(\"start\")&&(a(\"startarrowhead\",f),a(\"startarrowsize\",h)),a(\"arrowcolor\",l?e.bordercolor:i.defaultLine),a(\"arrowwidth\",2*(l&&c||1)),a(\"standoff\"),a(\"startstandoff\")}var d=a(\"hovertext\"),m=r.hoverlabel||{};if(d){var g=a(\"hoverlabel.bgcolor\",m.bgcolor||(i.opacity(o)?i.rgb(o):i.defaultLine)),v=a(\"hoverlabel.bordercolor\",m.bordercolor||i.contrast(g));n.coerceFont(a,\"hoverlabel.font\",{family:m.font.family,size:m.font.size,color:m.font.color||v})}a(\"captureevents\",!!d)}},{\"../../lib\":503,\"../color\":366}],353:[function(t,e,r){\"use strict\";var n=t(\"fast-isnumeric\"),i=t(\"../../lib/to_log_range\");e.exports=function(t,e,r,a){e=e||{};var o=\"log\"===r&&\"linear\"===e.type,s=\"linear\"===r&&\"log\"===e.type;if(o||s)for(var l,c,u=t._fullLayout.annotations,f=e._id.charAt(0),h=0;h<u.length;h++)l=u[h],c=\"annotations[\"+h+\"].\",l[f+\"ref\"]===e._id&&p(f),l[\"a\"+f+\"ref\"]===e._id&&p(\"a\"+f);function p(t){var r=l[t],s=null;s=o?i(r,e.range):Math.pow(10,r),n(s)||(s=null),a(c+t,s)}}},{\"../../lib/to_log_range\":531,\"fast-isnumeric\":190}],354:[function(t,e,r){\"use strict\";var n=t(\"../../lib\"),i=t(\"../../plots/cartesian/axes\"),a=t(\"../../plots/array_container_defaults\"),o=t(\"./common_defaults\"),s=t(\"./attributes\");function l(t,e,r){function a(r,i){return n.coerce(t,e,s,r,i)}var l=a(\"visible\"),c=a(\"clicktoshow\");if(l||c){o(t,e,r,a);for(var u=e.showarrow,f=[\"x\",\"y\"],h=[-10,-30],p={_fullLayout:r},d=0;d<2;d++){var m=f[d],g=i.coerceRef(t,e,p,m,\"\",\"paper\");if(\"paper\"!==g)i.getFromId(p,g)._annIndices.push(e._index);if(i.coercePosition(e,p,a,g,m,.5),u){var v=\"a\"+m,y=i.coerceRef(t,e,p,v,\"pixel\",[\"pixel\",\"paper\"]);\"pixel\"!==y&&y!==g&&(y=e[v]=\"pixel\");var 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r=t._fullLayout.annotations[e]||{},n=l.getFromId(t,r.xref),i=l.getFromId(t,r.yref);n&&n.setScale(),i&&i.setScale(),x(t,r,e,!1,n,i)}function y(t,e,r,n,i){var a=i[r],o=i[r+\"ref\"],s=-1!==r.indexOf(\"y\"),c=\"domain\"===l.getRefType(o),u=s?n.h:n.w;return t?c?a+(s?-e:e)/t._length:t.p2r(t.r2p(a)+e):a+(s?-e:e)/u}function x(t,e,r,a,v,x){var b,_,w=t._fullLayout,T=t._fullLayout._size,k=t._context.edits;a?(b=\"annotation-\"+a,_=a+\".annotations\"):(b=\"annotation\",_=\"annotations\");var A=m(t.layout,_,e),M=A.modifyBase,S=A.modifyItem,E=A.getUpdateObj;w._infolayer.selectAll(\".\"+b+'[data-index=\"'+r+'\"]').remove();var L=\"clip\"+w._uid+\"_ann\"+r;if(e._input&&!1!==e.visible){var C={x:{},y:{}},P=+e.textangle||0,I=w._infolayer.append(\"g\").classed(b,!0).attr(\"data-index\",String(r)).style(\"opacity\",e.opacity),O=I.append(\"g\").classed(\"annotation-text-g\",!0),z=k[e.showarrow?\"annotationTail\":\"annotationPosition\"],D=e.captureevents||k.annotationText||z,R=O.append(\"g\").style(\"pointer-events\",D?\"all\":null).call(p,\"pointer\").on(\"click\",(function(){t._dragging=!1,t.emit(\"plotly_clickannotation\",Y(n.event))}));e.hovertext&&R.on(\"mouseover\",(function(){var r=e.hoverlabel,n=r.font,i=this.getBoundingClientRect(),a=t.getBoundingClientRect();f.loneHover({x0:i.left-a.left,x1:i.right-a.left,y:(i.top+i.bottom)/2-a.top,text:e.hovertext,color:r.bgcolor,borderColor:r.bordercolor,fontFamily:n.family,fontSize:n.size,fontColor:n.color},{container:w._hoverlayer.node(),outerContainer:w._paper.node(),gd:t})})).on(\"mouseout\",(function(){f.loneUnhover(w._hoverlayer.node())}));var F=e.borderwidth,B=e.borderpad,N=F+B,j=R.append(\"rect\").attr(\"class\",\"bg\").style(\"stroke-width\",F+\"px\").call(c.stroke,e.bordercolor).call(c.fill,e.bgcolor),U=e.width||e.height,V=w._topclips.selectAll(\"#\"+L).data(U?[0]:[]);V.enter().append(\"clipPath\").classed(\"annclip\",!0).attr(\"id\",L).append(\"rect\"),V.exit().remove();var H=e.font,q=w._meta?o.templateString(e.text,w._meta):e.text,G=R.append(\"text\").classed(\"annotation-text\",!0).text(q);k.annotationText?G.call(h.makeEditable,{delegate:R,gd:t}).call(W).on(\"edit\",(function(r){e.text=r,this.call(W),S(\"text\",r),v&&v.autorange&&M(v._name+\".autorange\",!0),x&&x.autorange&&M(x._name+\".autorange\",!0),i.call(\"_guiRelayout\",t,E())})):G.call(W)}else n.selectAll(\"#\"+L).remove();function Y(t){var n={index:r,annotation:e._input,fullAnnotation:e,event:t};return a&&(n.subplotId=a),n}function W(r){return r.call(u.font,H).attr({\"text-anchor\":{left:\"start\",right:\"end\"}[e.align]||\"middle\"}),h.convertToTspans(r,t,X),r}function X(){var r=G.selectAll(\"a\");1===r.size()&&r.text()===G.text()&&R.insert(\"a\",\":first-child\").attr({\"xlink:xlink:href\":r.attr(\"xlink:href\"),\"xlink:xlink:show\":r.attr(\"xlink:show\")}).style({cursor:\"pointer\"}).node().appendChild(j.node());var n=R.select(\".annotation-text-math-group\"),f=!n.empty(),m=u.bBox((f?n:G).node()),b=m.width,_=m.height,A=e.width||b,D=e.height||_,B=Math.round(A+2*N),H=Math.round(D+2*N);function q(t,e){return\"auto\"===e&&(e=t<1/3?\"left\":t>2/3?\"right\":\"center\"),{center:0,middle:0,left:.5,bottom:-.5,right:-.5,top:.5}[e]}for(var W=!1,X=[\"x\",\"y\"],Z=0;Z<X.length;Z++){var J,K,Q,$,tt,et=X[Z],rt=e[et+\"ref\"]||et,nt=e[\"a\"+et+\"ref\"],it={x:v,y:x}[et],at=(P+(\"x\"===et?0:-90))*Math.PI/180,ot=B*Math.cos(at),st=H*Math.sin(at),lt=Math.abs(ot)+Math.abs(st),ct=e[et+\"anchor\"],ut=e[et+\"shift\"]*(\"x\"===et?1:-1),ft=C[et],ht=l.getRefType(rt);if(it&&\"domain\"!==ht){var pt=it.r2fraction(e[et]);(pt<0||pt>1)&&(nt===rt?((pt=it.r2fraction(e[\"a\"+et]))<0||pt>1)&&(W=!0):W=!0),J=it._offset+it.r2p(e[et]),$=.5}else{var dt=\"domain\"===ht;\"x\"===et?(Q=e[et],J=dt?it._offset+it._length*Q:J=T.l+T.w*Q):(Q=1-e[et],J=dt?it._offset+it._length*Q:J=T.t+T.h*Q),$=e.showarrow?.5:Q}if(e.showarrow){ft.head=J;var mt=e[\"a\"+et];if(tt=ot*q(.5,e.xanchor)-st*q(.5,e.yanchor),nt===rt){var gt=l.getRefType(nt);\"domain\"===gt?(\"y\"===et&&(mt=1-mt),ft.tail=it._offset+it._length*mt):\"paper\"===gt?\"y\"===et?(mt=1-mt,ft.tail=T.t+T.h*mt):ft.tail=T.l+T.w*mt:ft.tail=it._offset+it.r2p(mt),K=tt}else ft.tail=J+mt,K=tt+mt;ft.text=ft.tail+tt;var vt=w[\"x\"===et?\"width\":\"height\"];if(\"paper\"===rt&&(ft.head=o.constrain(ft.head,1,vt-1)),\"pixel\"===nt){var yt=-Math.max(ft.tail-3,ft.text),xt=Math.min(ft.tail+3,ft.text)-vt;yt>0?(ft.tail+=yt,ft.text+=yt):xt>0&&(ft.tail-=xt,ft.text-=xt)}ft.tail+=ut,ft.head+=ut}else K=tt=lt*q($,ct),ft.text=J+tt;ft.text+=ut,tt+=ut,K+=ut,e[\"_\"+et+\"padplus\"]=lt/2+K,e[\"_\"+et+\"padminus\"]=lt/2-K,e[\"_\"+et+\"size\"]=lt,e[\"_\"+et+\"shift\"]=tt}if(W)R.remove();else{var bt=0,_t=0;if(\"left\"!==e.align&&(bt=(A-b)*(\"center\"===e.align?.5:1)),\"top\"!==e.valign&&(_t=(D-_)*(\"middle\"===e.valign?.5:1)),f)n.select(\"svg\").attr({x:N+bt-1,y:N+_t}).call(u.setClipUrl,U?L:null,t);else{var wt=N+_t-m.top,Tt=N+bt-m.left;G.call(h.positionText,Tt,wt).call(u.setClipUrl,U?L:null,t)}V.select(\"rect\").call(u.setRect,N,N,A,D),j.call(u.setRect,F/2,F/2,B-F,H-F),R.call(u.setTranslate,Math.round(C.x.text-B/2),Math.round(C.y.text-H/2)),O.attr({transform:\"rotate(\"+P+\",\"+C.x.text+\",\"+C.y.text+\")\"});var kt,At=function(r,n){I.selectAll(\".annotation-arrow-g\").remove();var l=C.x.head,f=C.y.head,h=C.x.tail+r,p=C.y.tail+n,m=C.x.text+r,b=C.y.text+n,_=o.rotationXYMatrix(P,m,b),w=o.apply2DTransform(_),A=o.apply2DTransform2(_),L=+j.attr(\"width\"),z=+j.attr(\"height\"),D=m-.5*L,F=D+L,B=b-.5*z,N=B+z,U=[[D,B,D,N],[D,N,F,N],[F,N,F,B],[F,B,D,B]].map(A);if(!U.reduce((function(t,e){return t^!!o.segmentsIntersect(l,f,l+1e6,f+1e6,e[0],e[1],e[2],e[3])}),!1)){U.forEach((function(t){var e=o.segmentsIntersect(h,p,l,f,t[0],t[1],t[2],t[3]);e&&(h=e.x,p=e.y)}));var V=e.arrowwidth,H=e.arrowcolor,q=e.arrowside,G=I.append(\"g\").style({opacity:c.opacity(H)}).classed(\"annotation-arrow-g\",!0),Y=G.append(\"path\").attr(\"d\",\"M\"+h+\",\"+p+\"L\"+l+\",\"+f).style(\"stroke-width\",V+\"px\").call(c.stroke,c.rgb(H));if(g(Y,q,e),k.annotationPosition&&Y.node().parentNode&&!a){var W=l,X=f;if(e.standoff){var Z=Math.sqrt(Math.pow(l-h,2)+Math.pow(f-p,2));W+=e.standoff*(h-l)/Z,X+=e.standoff*(p-f)/Z}var J,K,Q=G.append(\"path\").classed(\"annotation-arrow\",!0).classed(\"anndrag\",!0).classed(\"cursor-move\",!0).attr({d:\"M3,3H-3V-3H3ZM0,0L\"+(h-W)+\",\"+(p-X),transform:s(W,X)}).style(\"stroke-width\",V+6+\"px\").call(c.stroke,\"rgba(0,0,0,0)\").call(c.fill,\"rgba(0,0,0,0)\");d.init({element:Q.node(),gd:t,prepFn:function(){var t=u.getTranslate(R);J=t.x,K=t.y,v&&v.autorange&&M(v._name+\".autorange\",!0),x&&x.autorange&&M(x._name+\".autorange\",!0)},moveFn:function(t,r){var n=w(J,K),i=n[0]+t,a=n[1]+r;R.call(u.setTranslate,i,a),S(\"x\",y(v,t,\"x\",T,e)),S(\"y\",y(x,r,\"y\",T,e)),e.axref===e.xref&&S(\"ax\",y(v,t,\"ax\",T,e)),e.ayref===e.yref&&S(\"ay\",y(x,r,\"ay\",T,e)),G.attr(\"transform\",s(t,r)),O.attr({transform:\"rotate(\"+P+\",\"+i+\",\"+a+\")\"})},doneFn:function(){i.call(\"_guiRelayout\",t,E());var e=document.querySelector(\".js-notes-box-panel\");e&&e.redraw(e.selectedObj)}})}}};if(e.showarrow&&At(0,0),z)d.init({element:R.node(),gd:t,prepFn:function(){kt=O.attr(\"transform\")},moveFn:function(t,r){var n=\"pointer\";if(e.showarrow)e.axref===e.xref?S(\"ax\",y(v,t,\"ax\",T,e)):S(\"ax\",e.ax+t),e.ayref===e.yref?S(\"ay\",y(x,r,\"ay\",T.w,e)):S(\"ay\",e.ay+r),At(t,r);else{if(a)return;var i,o;if(v)i=y(v,t,\"x\",T,e);else{var l=e._xsize/T.w,c=e.x+(e._xshift-e.xshift)/T.w-l/2;i=d.align(c+t/T.w,l,0,1,e.xanchor)}if(x)o=y(x,r,\"y\",T,e);else{var u=e._ysize/T.h,f=e.y-(e._yshift+e.yshift)/T.h-u/2;o=d.align(f-r/T.h,u,0,1,e.yanchor)}S(\"x\",i),S(\"y\",o),v&&x||(n=d.getCursor(v?.5:i,x?.5:o,e.xanchor,e.yanchor))}O.attr({transform:s(t,r)+kt}),p(R,n)},clickFn:function(r,n){e.captureevents&&t.emit(\"plotly_clickannotation\",Y(n))},doneFn:function(){p(R),i.call(\"_guiRelayout\",t,E());var e=document.querySelector(\".js-notes-box-panel\");e&&e.redraw(e.selectedObj)}})}}}e.exports={draw:function(t){var e=t._fullLayout;e._infolayer.selectAll(\".annotation\").remove();for(var r=0;r<e.annotations.length;r++)e.annotations[r].visible&&v(t,r);return a.previousPromises(t)},drawOne:v,drawRaw:x}},{\"../../lib\":503,\"../../lib/setcursor\":524,\"../../lib/svg_text_utils\":529,\"../../plot_api/plot_template\":543,\"../../plots/cartesian/axes\":554,\"../../plots/plots\":619,\"../../registry\":638,\"../color\":366,\"../dragelement\":385,\"../drawing\":388,\"../fx\":406,\"./draw_arrow_head\":356,\"@plotly/d3\":58}],356:[function(t,e,r){\"use strict\";var n=t(\"@plotly/d3\"),i=t(\"../color\"),a=t(\"./arrow_paths\"),o=t(\"../../lib\"),s=o.strScale,l=o.strRotate,c=o.strTranslate;e.exports=function(t,e,r){var o,u,f,h,p=t.node(),d=a[r.arrowhead||0],m=a[r.startarrowhead||0],g=(r.arrowwidth||1)*(r.arrowsize||1),v=(r.arrowwidth||1)*(r.startarrowsize||1),y=e.indexOf(\"start\")>=0,x=e.indexOf(\"end\")>=0,b=d.backoff*g+r.standoff,_=m.backoff*v+r.startstandoff;if(\"line\"===p.nodeName){o={x:+t.attr(\"x1\"),y:+t.attr(\"y1\")},u={x:+t.attr(\"x2\"),y:+t.attr(\"y2\")};var w=o.x-u.x,T=o.y-u.y;if(h=(f=Math.atan2(T,w))+Math.PI,b&&_&&b+_>Math.sqrt(w*w+T*T))return void z();if(b){if(b*b>w*w+T*T)return void z();var k=b*Math.cos(f),A=b*Math.sin(f);u.x+=k,u.y+=A,t.attr({x2:u.x,y2:u.y})}if(_){if(_*_>w*w+T*T)return void z();var M=_*Math.cos(f),S=_*Math.sin(f);o.x-=M,o.y-=S,t.attr({x1:o.x,y1:o.y})}}else if(\"path\"===p.nodeName){var E=p.getTotalLength(),L=\"\";if(E<b+_)return void z();var C=p.getPointAtLength(0),P=p.getPointAtLength(.1);f=Math.atan2(C.y-P.y,C.x-P.x),o=p.getPointAtLength(Math.min(_,E)),L=\"0px,\"+_+\"px,\";var 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n=t(\"@plotly/d3\"),i=t(\"tinycolor2\"),a=t(\"../../plots/plots\"),o=t(\"../../registry\"),s=t(\"../../plots/cartesian/axes\"),l=t(\"../dragelement\"),c=t(\"../../lib\"),u=c.strTranslate,f=t(\"../../lib/extend\").extendFlat,h=t(\"../../lib/setcursor\"),p=t(\"../drawing\"),d=t(\"../color\"),m=t(\"../titles\"),g=t(\"../../lib/svg_text_utils\"),v=t(\"../colorscale/helpers\").flipScale,y=t(\"../../plots/cartesian/axis_defaults\"),x=t(\"../../plots/cartesian/position_defaults\"),b=t(\"../../plots/cartesian/layout_attributes\"),_=t(\"../../constants/alignment\"),w=_.LINE_SPACING,T=_.FROM_TL,k=_.FROM_BR,A=t(\"./constants\").cn;e.exports={draw:function(t){var e=t._fullLayout._infolayer.selectAll(\"g.\"+A.colorbar).data(function(t){var e,r,n,i,a=t._fullLayout,o=t.calcdata,s=[];function l(t){return f(t,{_fillcolor:null,_line:{color:null,width:null,dash:null},_levels:{start:null,end:null,size:null},_filllevels:null,_fillgradient:null,_zrange:null})}function c(){\"function\"==typeof 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r=n.select(this);c.ensureSingle(r,\"rect\",A.cbbg),c.ensureSingle(r,\"g\",A.cbfills),c.ensureSingle(r,\"g\",A.cblines),c.ensureSingle(r,\"g\",A.cbaxis,(function(t){t.classed(A.crisp,!0)})),c.ensureSingle(r,\"g\",A.cbtitleunshift,(function(t){t.append(\"g\").classed(A.cbtitle,!0)})),c.ensureSingle(r,\"rect\",A.cboutline);var v=function(t,e,r){var o=\"v\"===e.orientation,l=e.len,h=e.lenmode,v=e.thickness,_=e.thicknessmode,M=e.outlinewidth,S=e.borderwidth,E=e.bgcolor,L=e.xanchor,C=e.yanchor,P=e.xpad,I=e.ypad,O=e.x,z=o?e.y:1-e.y,D=r._fullLayout,R=D._size,F=e._fillcolor,B=e._line,N=e.title,j=N.side,U=e._zrange||n.extent((\"function\"==typeof F?F:B.color).domain()),V=\"function\"==typeof B.color?B.color:function(){return B.color},H=\"function\"==typeof F?F:function(){return F},q=e._levels,G=function(t,e,r){var n,i,a=e._levels,o=[],s=[],l=a.end+a.size/100,c=a.size,u=1.001*r[0]-.001*r[1],f=1.001*r[1]-.001*r[0];for(i=0;i<1e5&&(n=a.start+i*c,!(c>0?n>=l:n<=l));i++)n>u&&n<f&&o.push(n);if(e._fillgradient)s=[0];else if(\"function\"==typeof e._fillcolor){var h=e._filllevels;if(h)for(l=h.end+h.size/100,c=h.size,i=0;i<1e5&&(n=h.start+i*c,!(c>0?n>=l:n<=l));i++)n>r[0]&&n<r[1]&&s.push(n);else(s=o.map((function(t){return t-a.size/2}))).push(s[s.length-1]+a.size)}else e._fillcolor&&\"string\"==typeof e._fillcolor&&(s=[0]);a.size<0&&(o.reverse(),s.reverse());return{line:o,fill:s}}(0,e,U),Y=G.fill,W=G.line,X=Math.round(v*(\"fraction\"===_?o?R.w:R.h:1)),Z=X/(o?R.w:R.h),J=Math.round(l*(\"fraction\"===h?o?R.h:R.w:1)),K=J/(o?R.h:R.w),Q=Math.round(o?O*R.w+P:z*R.h+I),$={center:.5,right:1}[L]||0,tt={top:1,middle:.5}[C]||0,et=o?O-$*Z:z-tt*Z,rt=o?z-tt*K:O-$*K,nt=Math.round(o?R.h*(1-rt):R.w*rt);e._lenFrac=K,e._thickFrac=Z,e._uFrac=et,e._vFrac=rt;var it=e._axis=function(t,e,r){var n=t._fullLayout,i=\"v\"===e.orientation,a={type:\"linear\",range:r,tickmode:e.tickmode,nticks:e.nticks,tick0:e.tick0,dtick:e.dtick,tickvals:e.tickvals,ticktext:e.ticktext,ticks:e.ticks,ticklen:e.ticklen,tickwidth:e.tickwidth,tickcolor:e.tickcolor,showticklabels:e.showticklabels,ticklabelposition:e.ticklabelposition,ticklabeloverflow:e.ticklabeloverflow,ticklabelstep:e.ticklabelstep,tickfont:e.tickfont,tickangle:e.tickangle,tickformat:e.tickformat,exponentformat:e.exponentformat,minexponent:e.minexponent,separatethousands:e.separatethousands,showexponent:e.showexponent,showtickprefix:e.showtickprefix,tickprefix:e.tickprefix,showticksuffix:e.showticksuffix,ticksuffix:e.ticksuffix,title:e.title,showline:!0,anchor:\"free\",side:i?\"right\":\"bottom\",position:1},o=i?\"y\":\"x\",s={type:\"linear\",_id:o+e._id},l={letter:o,font:n.font,noHover:!0,noTickson:!0,noTicklabelmode:!0,calendar:n.calendar};function u(t,e){return c.coerce(a,s,b,t,e)}return y(a,s,u,l,n),x(a,s,u,l),s}(r,e,U);it.position=Z+(o?O+P/R.w:z+I/R.h);var at=-1!==[\"top\",\"bottom\"].indexOf(j);o&&at&&(it.title.side=j,it.titlex=O+P/R.w,it.titley=rt+(\"top\"===N.side?K-I/R.h:I/R.h));o||at||(it.title.side=j,it.titley=z+I/R.h,it.titlex=rt+P/R.w);if(B.color&&\"auto\"===e.tickmode){it.tickmode=\"linear\",it.tick0=q.start;var ot=q.size,st=c.constrain(J/50,4,15)+1,lt=(U[1]-U[0])/((e.nticks||st)*ot);if(lt>1){var ct=Math.pow(10,Math.floor(Math.log(lt)/Math.LN10));ot*=ct*c.roundUp(lt/ct,[2,5,10]),(Math.abs(q.start)/q.size+1e-6)%1<2e-6&&(it.tick0=0)}it.dtick=ot}it.domain=o?[rt+I/R.h,rt+K-I/R.h]:[rt+P/R.w,rt+K-P/R.w],it.setScale(),t.attr(\"transform\",u(Math.round(R.l),Math.round(R.t)));var ut,ft=t.select(\".\"+A.cbtitleunshift).attr(\"transform\",u(-Math.round(R.l),-Math.round(R.t))),ht=it.ticklabelposition,pt=it.title.font.size,dt=t.select(\".\"+A.cbaxis),mt=0,gt=0;function vt(n,i){var a={propContainer:it,propName:e._propPrefix+\"title\",traceIndex:e._traceIndex,_meta:e._meta,placeholder:D._dfltTitle.colorbar,containerGroup:t.select(\".\"+A.cbtitle)},o=\"h\"===n.charAt(0)?n.substr(1):\"h\"+n;t.selectAll(\".\"+o+\",.\"+o+\"-math-group\").remove(),m.draw(r,n,f(a,i||{}))}return c.syncOrAsync([a.previousPromises,function(){var t,e;(o&&at||!o&&!at)&&(\"top\"===j&&(t=P+R.l+R.w*O,e=I+R.t+R.h*(1-rt-K)+3+.75*pt),\"bottom\"===j&&(t=P+R.l+R.w*O,e=I+R.t+R.h*(1-rt)-3-.25*pt),\"right\"===j&&(e=I+R.t+R.h*z+3+.75*pt,t=P+R.l+R.w*rt),vt(it._id+\"title\",{attributes:{x:t,y:e,\"text-anchor\":o?\"start\":\"middle\"}}))},function(){if(!o&&!at||o&&at){var a,l=t.select(\".\"+A.cbtitle),f=l.select(\"text\"),h=[-M/2,M/2],d=l.select(\".h\"+it._id+\"title-math-group\").node(),m=15.6;if(f.node()&&(m=parseInt(f.node().style.fontSize,10)*w),d?(a=p.bBox(d),gt=a.width,(mt=a.height)>m&&(h[1]-=(mt-m)/2)):f.node()&&!f.classed(A.jsPlaceholder)&&(a=p.bBox(f.node()),gt=a.width,mt=a.height),o){if(mt){if(mt+=5,\"top\"===j)it.domain[1]-=mt/R.h,h[1]*=-1;else{it.domain[0]+=mt/R.h;var v=g.lineCount(f);h[1]+=(1-v)*m}l.attr(\"transform\",u(h[0],h[1])),it.setScale()}}else gt&&(\"right\"===j&&(it.domain[0]+=(gt+pt/2)/R.w),l.attr(\"transform\",u(h[0],h[1])),it.setScale())}t.selectAll(\".\"+A.cbfills+\",.\"+A.cblines).attr(\"transform\",o?u(0,Math.round(R.h*(1-it.domain[1]))):u(Math.round(R.w*it.domain[0]),0)),dt.attr(\"transform\",o?u(0,Math.round(-R.t)):u(Math.round(-R.l),0));var y=t.select(\".\"+A.cbfills).selectAll(\"rect.\"+A.cbfill).attr(\"style\",\"\").data(Y);y.enter().append(\"rect\").classed(A.cbfill,!0).style(\"stroke\",\"none\"),y.exit().remove();var x=U.map(it.c2p).map(Math.round).sort((function(t,e){return t-e}));y.each((function(t,a){var s=[0===a?U[0]:(Y[a]+Y[a-1])/2,a===Y.length-1?U[1]:(Y[a]+Y[a+1])/2].map(it.c2p).map(Math.round);o&&(s[1]=c.constrain(s[1]+(s[1]>s[0])?1:-1,x[0],x[1]));var l=n.select(this).attr(o?\"x\":\"y\",Q).attr(o?\"y\":\"x\",n.min(s)).attr(o?\"width\":\"height\",Math.max(X,2)).attr(o?\"height\":\"width\",Math.max(n.max(s)-n.min(s),2));if(e._fillgradient)p.gradient(l,r,e._id,o?\"vertical\":\"horizontalreversed\",e._fillgradient,\"fill\");else{var u=H(t).replace(\"e-\",\"\");l.attr(\"fill\",i(u).toHexString())}}));var b=t.select(\".\"+A.cblines).selectAll(\"path.\"+A.cbline).data(B.color&&B.width?W:[]);b.enter().append(\"path\").classed(A.cbline,!0),b.exit().remove(),b.each((function(t){var e=Q,r=Math.round(it.c2p(t))+B.width/2%1;n.select(this).attr(\"d\",\"M\"+(o?e+\",\"+r:r+\",\"+e)+(o?\"h\":\"v\")+X).call(p.lineGroupStyle,B.width,V(t),B.dash)})),dt.selectAll(\"g.\"+it._id+\"tick,path\").remove();var _=Q+X+(M||0)/2-(\"outside\"===e.ticks?1:0),T=s.calcTicks(it),k=s.getTickSigns(it)[2];return s.drawTicks(r,it,{vals:\"inside\"===it.ticks?s.clipEnds(it,T):T,layer:dt,path:s.makeTickPath(it,_,k),transFn:s.makeTransTickFn(it)}),s.drawLabels(r,it,{vals:T,layer:dt,transFn:s.makeTransTickLabelFn(it),labelFns:s.makeLabelFns(it,_)})},function(){if(o&&!at||!o&&at){var t,i,a=it.position||0,s=it._offset+it._length/2;if(\"right\"===j)i=s,t=R.l+R.w*a+10+pt*(it.showticklabels?1:.5);else if(t=s,\"bottom\"===j&&(i=R.t+R.h*a+10+(-1===ht.indexOf(\"inside\")?it.tickfont.size:0)+(\"intside\"!==it.ticks&&e.ticklen||0)),\"top\"===j){var l=N.text.split(\"<br>\").length;i=R.t+R.h*a+10-X-w*pt*l}vt((o?\"h\":\"v\")+it._id+\"title\",{avoid:{selection:n.select(r).selectAll(\"g.\"+it._id+\"tick\"),side:j,offsetTop:o?0:R.t,offsetLeft:o?R.l:0,maxShift:o?D.width:D.height},attributes:{x:t,y:i,\"text-anchor\":\"middle\"},transform:{rotate:o?-90:0,offset:0}})}},a.previousPromises,function(){var n,s=X+M/2;-1===ht.indexOf(\"inside\")&&(n=p.bBox(dt.node()),s+=o?n.width:n.height),ut=ft.select(\"text\");var c=0,f=o&&\"top\"===j,m=!o&&\"right\"===j,g=0;if(ut.node()&&!ut.classed(A.jsPlaceholder)){var y,x=ft.select(\".h\"+it._id+\"title-math-group\").node();x&&(o&&at||!o&&!at)?(c=(n=p.bBox(x)).width,y=n.height):(c=(n=p.bBox(ft.node())).right-R.l-(o?Q:nt),y=n.bottom-R.t-(o?nt:Q),o||\"top\"!==j||(s+=n.height,g=n.height)),m&&(ut.attr(\"transform\",u(c/2+pt/2,0)),c*=2),s=Math.max(s,o?c:y)}var b=2*(o?P:I)+s+S+M/2,w=0;!o&&N.text&&\"bottom\"===C&&z<=0&&(b+=w=b/2,g+=w),D._hColorbarMoveTitle=w,D._hColorbarMoveCBTitle=g;var F=S+M;t.select(\".\"+A.cbbg).attr(\"x\",(o?Q:nt)-F/2-(o?P:0)).attr(\"y\",(o?nt:Q)-(o?J:I+g-w)).attr(o?\"width\":\"height\",Math.max(b-w,2)).attr(o?\"height\":\"width\",Math.max(J+F,2)).call(d.fill,E).call(d.stroke,e.bordercolor).style(\"stroke-width\",S);var B=m?Math.max(c-10,0):0;if(t.selectAll(\".\"+A.cboutline).attr(\"x\",(o?Q:nt+P)+B).attr(\"y\",(o?nt+I-J:Q)+(f?mt:0)).attr(o?\"width\":\"height\",Math.max(X,2)).attr(o?\"height\":\"width\",Math.max(J-(o?2*I+mt:2*P+B),2)).call(d.stroke,e.outlinecolor).style({fill:\"none\",\"stroke-width\":M}),t.attr(\"transform\",u(R.l-(o?$*b:0),R.t-(o?0:(1-tt)*b-g))),!o&&(S||i(E).getAlpha()&&!i.equals(D.paper_bgcolor,E))){var U=dt.selectAll(\"text\"),V=U[0].length,H=t.select(\".\"+A.cbbg).node(),q=p.bBox(H),G=p.getTranslate(t);U.each((function(t,e){var r=V-1;if(0===e||e===r){var n,i=p.bBox(this),a=p.getTranslate(this);if(e===r){var o=i.right+a.x;(n=q.right+G.x+nt-S-2+O-o)>0&&(n=0)}else if(0===e){var s=i.left+a.x;(n=q.left+G.x+nt+S+2-s)<0&&(n=0)}n&&(V<3?this.setAttribute(\"transform\",\"translate(\"+n+\",0) \"+this.getAttribute(\"transform\")):this.setAttribute(\"visibility\",\"hidden\"))}}))}var Y={},W=T[L],Z=k[L],K=T[C],et=k[C],rt=b-X;o?(\"pixels\"===h?(Y.y=z,Y.t=J*K,Y.b=J*et):(Y.t=Y.b=0,Y.yt=z+l*K,Y.yb=z-l*et),\"pixels\"===_?(Y.x=O,Y.l=b*W,Y.r=b*Z):(Y.l=rt*W,Y.r=rt*Z,Y.xl=O-v*W,Y.xr=O+v*Z)):(\"pixels\"===h?(Y.x=O,Y.l=J*W,Y.r=J*Z):(Y.l=Y.r=0,Y.xl=O+l*W,Y.xr=O-l*Z),\"pixels\"===_?(Y.y=1-z,Y.t=b*K,Y.b=b*et):(Y.t=rt*K,Y.b=rt*et,Y.yt=z-v*K,Y.yb=z+v*et)),a.autoMargin(r,e._id,Y)}],r)}(r,e,t);v&&v.then&&(t._promises||[]).push(v),t._context.edits.colorbarPosition&&function(t,e,r){var n,i,a,s=\"v\"===e.orientation,c=r._fullLayout._size;l.init({element:t.node(),gd:r,prepFn:function(){n=t.attr(\"transform\"),h(t)},moveFn:function(r,o){t.attr(\"transform\",n+u(r,o)),i=l.align((s?e._uFrac:e._vFrac)+r/c.w,s?e._thickFrac:e._lenFrac,0,1,e.xanchor),a=l.align((s?e._vFrac:1-e._uFrac)-o/c.h,s?e._lenFrac:e._thickFrac,0,1,e.yanchor);var f=l.getCursor(i,a,e.xanchor,e.yanchor);h(t,f)},doneFn:function(){if(h(t),void 0!==i&&void 0!==a){var n={};n[e._propPrefix+\"x\"]=i,n[e._propPrefix+\"y\"]=a,void 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o.warn(\"Fx.hover failed\",e,t),d.unhoverRaw(t,e)}var ct=1/0;function ut(t,r){for(G=0;G<rt.length;G++)if((Y=rt[G])&&Y[0]&&Y[0].trace&&!0===(W=Y[0].trace).visible&&0!==W._length&&-1===[\"carpet\",\"contourcarpet\"].indexOf(W._module.name)){if(\"splom\"===W.type?X=l[Z=0]:(X=v.getSubplot(W),Z=l.indexOf(X)),J=P,v.isUnifiedHover(J)&&(J=J.charAt(0)),$={cd:Y,trace:W,xa:_[Z],ya:w[Z],maxHoverDistance:O,maxSpikeDistance:B,index:!1,distance:Math.min(ct,O),spikeDistance:1/0,xSpike:void 0,ySpike:void 0,color:p.defaultLine,name:W.name,x0:void 0,x1:void 0,y0:void 0,y1:void 0,xLabelVal:void 0,yLabelVal:void 0,zLabelVal:void 0,text:void 0},u[X]&&($.subplot=u[X]._subplot),u._splomScenes&&u._splomScenes[W.uid]&&($.scene=u._splomScenes[W.uid]),tt=et.length,\"array\"===J){var n=e[G];\"pointNumber\"in n?($.index=n.pointNumber,J=\"closest\"):(J=\"\",\"xval\"in n&&(K=n.xval,J=\"x\"),\"yval\"in n&&(Q=n.yval,J=J?\"closest\":\"y\"))}else void 0!==t&&void 0!==r?(K=t,Q=r):(K=V[Z],Q=H[Z]);if(0!==O)if(W._module&&W._module.hoverPoints){var a=W._module.hoverPoints($,K,Q,J,{finiteRange:!0,hoverLayer:u._hoverlayer});if(a)for(var s,c=0;c<a.length;c++)s=a[c],i(s.x0)&&i(s.y0)&&et.push(D(s,P))}else o.log(\"Unrecognized trace type in hover:\",W);if(\"closest\"===P&&et.length>tt&&(et.splice(0,tt),ct=et[0].distance),y&&0!==B&&0===et.length){$.distance=B,$.index=!1;var f=W._module.hoverPoints($,K,Q,\"closest\",{hoverLayer:u._hoverlayer});if(f&&(f=f.filter((function(t){return t.spikeDistance<=B}))),f&&f.length){var h,d=f.filter((function(t){return t.xa.showspikes&&\"hovered data\"!==t.xa.spikesnap}));if(d.length){var m=d[0];i(m.x0)&&i(m.y0)&&(h=ht(m),(!nt.vLinePoint||nt.vLinePoint.spikeDistance>h.spikeDistance)&&(nt.vLinePoint=h))}var g=f.filter((function(t){return t.ya.showspikes&&\"hovered data\"!==t.ya.spikesnap}));if(g.length){var x=g[0];i(x.x0)&&i(x.y0)&&(h=ht(x),(!nt.hLinePoint||nt.hLinePoint.spikeDistance>h.spikeDistance)&&(nt.hLinePoint=h))}}}}}function ft(t,e,r){for(var n,i=null,a=1/0,o=0;o<t.length;o++)n=t[o].spikeDistance,r&&0===o&&(n=-1/0),n<=a&&n<=e&&(i=t[o],a=n);return i}function ht(t){return t?{xa:t.xa,ya:t.ya,x:void 0!==t.xSpike?t.xSpike:(t.x0+t.x1)/2,y:void 0!==t.ySpike?t.ySpike:(t.y0+t.y1)/2,distance:t.distance,spikeDistance:t.spikeDistance,curveNumber:t.trace.index,color:t.color,pointNumber:t.index}:null}ut();var pt={fullLayout:u,container:u._hoverlayer,event:e},dt=t._spikepoints,mt={vLinePoint:nt.vLinePoint,hLinePoint:nt.hLinePoint};t._spikepoints=mt;var gt=function(){et.sort((function(t,e){return t.distance-e.distance})),et=function(t,e){for(var r=e.charAt(0),n=[],i=[],a=[],o=0;o<t.length;o++){var s=t[o];g.traceIs(s.trace,\"bar-like\")||g.traceIs(s.trace,\"box-violin\")?a.push(s):s.trace[r+\"period\"]?i.push(s):n.push(s)}return n.concat(i).concat(a)}(et,P)};gt();var vt=P.charAt(0),yt=(\"x\"===vt||\"y\"===vt)&&et[0]&&L[et[0].trace.type];if(y&&0!==B&&0!==et.length){var xt=ft(et.filter((function(t){return t.ya.showspikes})),B,yt);nt.hLinePoint=ht(xt);var bt=ft(et.filter((function(t){return t.xa.showspikes})),B,yt);nt.vLinePoint=ht(bt)}if(0===et.length){var _t=d.unhoverRaw(t,e);return!y||null===nt.hLinePoint&&null===nt.vLinePoint||F(dt)&&R(t,nt,pt),_t}y&&F(dt)&&R(t,nt,pt);if(v.isXYhover(J)&&0!==et[0].length&&\"splom\"!==et[0].trace.type){var wt=et[0],Tt=(et=E[wt.trace.type]?et.filter((function(t){return t.trace.index===wt.trace.index})):[wt]).length,kt=N(\"x\",wt,u),At=N(\"y\",wt,u);ut(kt,At);var Mt,St=[],Et={},Lt=0,Ct=function(t){var e=E[t.trace.type]?C(t):t.trace.index;if(Et[e]){var r=Et[e]-1,n=St[r];r>0&&Math.abs(t.distance)<Math.abs(n.distance)&&(St[r]=t)}else Lt++,Et[e]=Lt,St.push(t)};for(Mt=0;Mt<Tt;Mt++)Ct(et[Mt]);for(Mt=et.length-1;Mt>Tt-1;Mt--)Ct(et[Mt]);et=St,gt()}var Pt=t._hoverdata,It=[],Ot=j(t),zt=U(t);for(q=0;q<et.length;q++){var Dt=et[q],Rt=v.makeEventData(Dt,Dt.trace,Dt.cd);if(!1!==Dt.hovertemplate){var Ft=!1;Dt.cd[Dt.index]&&Dt.cd[Dt.index].ht&&(Ft=Dt.cd[Dt.index].ht),Dt.hovertemplate=Ft||Dt.trace.hovertemplate||!1}if(Dt.xa&&Dt.ya){var Bt=Dt.x0+Dt.xa._offset,Nt=Dt.x1+Dt.xa._offset,jt=Dt.y0+Dt.ya._offset,Ut=Dt.y1+Dt.ya._offset,Vt=Math.min(Bt,Nt),Ht=Math.max(Bt,Nt),qt=Math.min(jt,Ut),Gt=Math.max(jt,Ut);Rt.bbox={x0:Vt+zt,x1:Ht+zt,y0:qt+Ot,y1:Gt+Ot}}Dt.eventData=[Rt],It.push(Rt)}t._hoverdata=It;var Yt=\"y\"===P&&(rt.length>1||et.length>1)||\"closest\"===P&&it&&et.length>1,Wt=p.combine(u.plot_bgcolor||p.background,u.paper_bgcolor),Xt=I(et,{gd:t,hovermode:P,rotateLabels:Yt,bgColor:Wt,container:u._hoverlayer,outerContainer:u._paper.node(),commonLabelOpts:u.hoverlabel,hoverdistance:u.hoverdistance});v.isUnifiedHover(P)||(!function(t,e,r){var n,i,a,o,s,l,c,u=0,f=1,h=t.size(),p=new Array(h),d=0;function m(t){var e=t[0],r=t[t.length-1];if(i=e.pmin-e.pos-e.dp+e.size,a=r.pos+r.dp+r.size-e.pmax,i>.01){for(s=t.length-1;s>=0;s--)t[s].dp+=i;n=!1}if(!(a<.01)){if(i<-.01){for(s=t.length-1;s>=0;s--)t[s].dp-=a;n=!1}if(n){var c=0;for(o=0;o<t.length;o++)(l=t[o]).pos+l.dp+l.size>e.pmax&&c++;for(o=t.length-1;o>=0&&!(c<=0);o--)(l=t[o]).pos>e.pmax-1&&(l.del=!0,c--);for(o=0;o<t.length&&!(c<=0);o++)if((l=t[o]).pos<e.pmin+1)for(l.del=!0,c--,a=2*l.size,s=t.length-1;s>=0;s--)t[s].dp-=a;for(o=t.length-1;o>=0&&!(c<=0);o--)(l=t[o]).pos+l.dp+l.size>e.pmax&&(l.del=!0,c--)}}}t.each((function(t){var n=t[e],i=\"x\"===n._id.charAt(0),a=n.range;0===d&&a&&a[0]>a[1]!==i&&(f=-1),p[d++]=[{datum:t,traceIndex:t.trace.index,dp:0,pos:t.pos,posref:t.posref,size:t.by*(i?T:1)/2,pmin:0,pmax:i?r.width:r.height}]})),p.sort((function(t,e){return t[0].posref-e[0].posref||f*(e[0].traceIndex-t[0].traceIndex)}));for(;!n&&u<=h;){for(u++,n=!0,o=0;o<p.length-1;){var g=p[o],v=p[o+1],y=g[g.length-1],x=v[0];if((i=y.pos+y.dp+y.size-x.pos-x.dp+x.size)>.01&&y.pmin===x.pmin&&y.pmax===x.pmax){for(s=v.length-1;s>=0;s--)v[s].dp+=i;for(g.push.apply(g,v),p.splice(o+1,1),c=0,s=g.length-1;s>=0;s--)c+=g[s].dp;for(a=c/g.length,s=g.length-1;s>=0;s--)g[s].dp-=a;n=!1}else o++}p.forEach(m)}for(o=p.length-1;o>=0;o--){var b=p[o];for(s=b.length-1;s>=0;s--){var _=b[s],w=_.datum;w.offset=_.dp,w.del=_.del}}}(Xt,Yt?\"xa\":\"ya\",u),z(Xt,Yt,u._invScaleX,u._invScaleY));if(s&&s.tagName){var Zt=g.getComponentMethod(\"annotations\",\"hasClickToShow\")(t,It);f(n.select(s),Zt?\"pointer\":\"\")}if(!s||a||!function(t,e,r){if(!r||r.length!==t._hoverdata.length)return!0;for(var n=r.length-1;n>=0;n--){var i=r[n],a=t._hoverdata[n];if(i.curveNumber!==a.curveNumber||String(i.pointNumber)!==String(a.pointNumber)||String(i.pointNumbers)!==String(a.pointNumbers))return!0}return!1}(t,0,Pt))return;Pt&&t.emit(\"plotly_unhover\",{event:e,points:Pt});t.emit(\"plotly_hover\",{event:e,points:t._hoverdata,xaxes:_,yaxes:w,xvals:V,yvals:H})}(t,e,r,a,s)}))},r.loneHover=function(t,e){var r=!0;Array.isArray(t)||(r=!1,t=[t]);var i=e.gd,a=j(i),o=U(i),s=I(t.map((function(t){var r=t._x0||t.x0||t.x||0,n=t._x1||t.x1||t.x||0,s=t._y0||t.y0||t.y||0,l=t._y1||t.y1||t.y||0,c=t.eventData;if(c){var u=Math.min(r,n),f=Math.max(r,n),h=Math.min(s,l),d=Math.max(s,l),m=t.trace;if(g.traceIs(m,\"gl3d\")){var v=i._fullLayout[m.scene]._scene.container,y=v.offsetLeft,x=v.offsetTop;u+=y,f+=y,h+=x,d+=x}c.bbox={x0:u+o,x1:f+o,y0:h+a,y1:d+a},e.inOut_bbox&&e.inOut_bbox.push(c.bbox)}else c=!1;return{color:t.color||p.defaultLine,x0:t.x0||t.x||0,x1:t.x1||t.x||0,y0:t.y0||t.y||0,y1:t.y1||t.y||0,xLabel:t.xLabel,yLabel:t.yLabel,zLabel:t.zLabel,text:t.text,name:t.name,idealAlign:t.idealAlign,borderColor:t.borderColor,fontFamily:t.fontFamily,fontSize:t.fontSize,fontColor:t.fontColor,nameLength:t.nameLength,textAlign:t.textAlign,trace:t.trace||{index:0,hoverinfo:\"\"},xa:{_offset:0},ya:{_offset:0},index:0,hovertemplate:t.hovertemplate||!1,hovertemplateLabels:t.hovertemplateLabels||!1,eventData:c}})),{gd:i,hovermode:\"closest\",rotateLabels:!1,bgColor:e.bgColor||p.background,container:n.select(e.container),outerContainer:e.outerContainer||e.container}),l=0,c=0;return s.sort((function(t,e){return t.y0-e.y0})).each((function(t,r){var n=t.y0-t.by/2;t.offset=n-5<l?l-n+5:0,l=n+t.by+t.offset,r===e.anchorIndex&&(c=t.offset)})).each((function(t){t.offset-=c})),z(s,!1,i._fullLayout._invScaleX,i._fullLayout._invScaleY),r?s:s.node()};var P=/<extra>([\\s\\S]*)<\\/extra>/;function I(t,e){var r=e.gd,i=r._fullLayout,a=e.hovermode,c=e.rotateLabels,f=e.bgColor,d=e.container,m=e.outerContainer,w=e.commonLabelOpts||{};if(0===t.length)return[[]];var T=e.fontFamily||y.HOVERFONT,k=e.fontSize||y.HOVERFONTSIZE,A=t[0],E=A.xa,L=A.ya,P=a.charAt(0),I=A[P+\"Label\"],z=V(r,m),D=z.top,R=z.width,F=z.height,B=void 0!==I&&A.distance<=e.hoverdistance&&(\"x\"===a||\"y\"===a);if(B){var N,j,U=!0;for(N=0;N<t.length;N++)if(U&&void 0===t[N].zLabel&&(U=!1),j=t[N].hoverinfo||t[N].trace.hoverinfo){var H=Array.isArray(j)?j:j.split(\"+\");if(-1===H.indexOf(\"all\")&&-1===H.indexOf(a)){B=!1;break}}U&&(B=!1)}var q=d.selectAll(\"g.axistext\").data(B?[0]:[]);if(q.enter().append(\"g\").classed(\"axistext\",!0),q.exit().remove(),q.each((function(){var t=n.select(this),e=o.ensureSingle(t,\"path\",\"\",(function(t){t.style({\"stroke-width\":\"1px\"})})),l=o.ensureSingle(t,\"text\",\"\",(function(t){t.attr(\"data-notex\",1)})),c=w.bgcolor||p.defaultLine,f=w.bordercolor||p.contrast(c),d=p.contrast(c),m={family:w.font.family||T,size:w.font.size||k,color:w.font.color||d};e.style({fill:c,stroke:f}),l.text(I).call(h.font,m).call(u.positionText,0,0).call(u.convertToTspans,r),t.attr(\"transform\",\"\");var g,v,y=V(r,l.node());if(\"x\"===a){var x=\"top\"===E.side?\"-\":\"\";l.attr(\"text-anchor\",\"middle\").call(u.positionText,0,\"top\"===E.side?D-y.bottom-M-S:D-y.top+M+S),g=E._offset+(A.x0+A.x1)/2,v=L._offset+(\"top\"===E.side?0:L._length);var b=y.width/2+S;g<b?(g=b,e.attr(\"d\",\"M-\"+(b-M)+\",0L-\"+(b-2*M)+\",\"+x+M+\"H\"+(S+y.width/2)+\"v\"+x+(2*S+y.height)+\"H-\"+b+\"V\"+x+M+\"Z\")):g>i.width-b?(g=i.width-b,e.attr(\"d\",\"M\"+(b-M)+\",0L\"+b+\",\"+x+M+\"v\"+x+(2*S+y.height)+\"H-\"+b+\"V\"+x+M+\"H\"+(b-2*M)+\"Z\")):e.attr(\"d\",\"M0,0L\"+M+\",\"+x+M+\"H\"+(S+y.width/2)+\"v\"+x+(2*S+y.height)+\"H-\"+(S+y.width/2)+\"V\"+x+M+\"H-\"+M+\"Z\")}else{var _,C,P;\"right\"===L.side?(_=\"start\",C=1,P=\"\",g=E._offset+E._length):(_=\"end\",C=-1,P=\"-\",g=E._offset),v=L._offset+(A.y0+A.y1)/2,l.attr(\"text-anchor\",_),e.attr(\"d\",\"M0,0L\"+P+M+\",\"+M+\"V\"+(S+y.height/2)+\"h\"+P+(2*S+y.width)+\"V-\"+(S+y.height/2)+\"H\"+P+M+\"V-\"+M+\"Z\");var O,z=y.height/2,R=D-y.top-z,F=\"clip\"+i._uid+\"commonlabel\"+L._id;if(g<y.width+2*S+M){O=\"M-\"+(M+S)+\"-\"+z+\"h-\"+(y.width-S)+\"V\"+z+\"h\"+(y.width-S)+\"Z\";var B=y.width-g+S;u.positionText(l,B,R),\"end\"===_&&l.selectAll(\"tspan\").each((function(){var t=n.select(this),e=h.tester.append(\"text\").text(t.text()).call(h.font,m),i=V(r,e.node());Math.round(i.width)<Math.round(y.width)&&t.attr(\"x\",B-i.width),e.remove()}))}else u.positionText(l,C*(S+M),R),O=null;var N=i._topclips.selectAll(\"#\"+F).data(O?[0]:[]);N.enter().append(\"clipPath\").attr(\"id\",F).append(\"path\"),N.exit().remove(),N.select(\"path\").attr(\"d\",O),h.setClipUrl(l,O?F:null,r)}t.attr(\"transform\",s(g,v))})),v.isUnifiedHover(a)){d.selectAll(\"g.hovertext\").remove();var G=t.filter((function(t){return\"none\"!==t.hoverinfo}));if(0===G.length)return;var Y=i.hoverlabel,W=Y.font,X={showlegend:!0,legend:{title:{text:I,font:W},font:W,bgcolor:Y.bgcolor,bordercolor:Y.bordercolor,borderwidth:1,tracegroupgap:7,traceorder:i.legend?i.legend.traceorder:void 0,orientation:\"v\"}},Z={font:W};x(X,Z,r._fullData);var J=Z.legend;J.entries=[];for(var K=0;K<G.length;K++){var Q=G[K];if(\"none\"!==Q.hoverinfo){var $=O(Q,!0,a,i,I),tt=$[0],et=$[1];Q.name=et,Q.text=\"\"!==et?et+\" : 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n=t(\"@plotly/d3\"),i=t(\"../../lib\"),a=t(\"../../plots/plots\"),o=t(\"../../registry\"),s=t(\"../../lib/events\"),l=t(\"../dragelement\"),c=t(\"../drawing\"),u=t(\"../color\"),f=t(\"../../lib/svg_text_utils\"),h=t(\"./handle_click\"),p=t(\"./constants\"),d=t(\"../../constants/alignment\"),m=d.LINE_SPACING,g=d.FROM_TL,v=d.FROM_BR,y=t(\"./get_legend_data\"),x=t(\"./style\"),b=t(\"./helpers\");function _(t,e,r,n,i){var a=r.data()[0][0].trace,l={event:i,node:r.node(),curveNumber:a.index,expandedIndex:a._expandedIndex,data:t.data,layout:t.layout,frames:t._transitionData._frames,config:t._context,fullData:t._fullData,fullLayout:t._fullLayout};if(a._group&&(l.group=a._group),o.traceIs(a,\"pie-like\")&&(l.label=r.datum()[0].label),!1!==s.triggerHandler(t,\"plotly_legendclick\",l))if(1===n)e._clickTimeout=setTimeout((function(){t._fullLayout&&h(r,t,n)}),t._context.doubleClickDelay);else 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rectangle\")},attr:\"dragmode\",val:\"drawrect\",icon:o.drawrect,click:f},u.drawcircle={name:\"drawcircle\",title:function(t){return c(t,\"Draw circle\")},attr:\"dragmode\",val:\"drawcircle\",icon:o.drawcircle,click:f},u.eraseshape={name:\"eraseshape\",title:function(t){return c(t,\"Erase active shape\")},icon:o.eraseshape,click:s},u.zoomIn2d={name:\"zoomIn2d\",_cat:\"zoomin\",title:function(t){return c(t,\"Zoom in\")},attr:\"zoom\",val:\"in\",icon:o.zoom_plus,click:f},u.zoomOut2d={name:\"zoomOut2d\",_cat:\"zoomout\",title:function(t){return c(t,\"Zoom out\")},attr:\"zoom\",val:\"out\",icon:o.zoom_minus,click:f},u.autoScale2d={name:\"autoScale2d\",_cat:\"autoscale\",title:function(t){return c(t,\"Autoscale\")},attr:\"zoom\",val:\"auto\",icon:o.autoscale,click:f},u.resetScale2d={name:\"resetScale2d\",_cat:\"resetscale\",title:function(t){return c(t,\"Reset axes\")},attr:\"zoom\",val:\"reset\",icon:o.home,click:f},u.hoverClosestCartesian={name:\"hoverClosestCartesian\",_cat:\"hoverclosest\",title:function(t){return c(t,\"Show closest data on hover\")},attr:\"hovermode\",val:\"closest\",icon:o.tooltip_basic,gravity:\"ne\",click:f},u.hoverCompareCartesian={name:\"hoverCompareCartesian\",_cat:\"hoverCompare\",title:function(t){return c(t,\"Compare data on hover\")},attr:\"hovermode\",val:function(t){return t._fullLayout._isHoriz?\"y\":\"x\"},icon:o.tooltip_compare,gravity:\"ne\",click:f},u.zoom3d={name:\"zoom3d\",_cat:\"zoom\",title:function(t){return c(t,\"Zoom\")},attr:\"scene.dragmode\",val:\"zoom\",icon:o.zoombox,click:h},u.pan3d={name:\"pan3d\",_cat:\"pan\",title:function(t){return c(t,\"Pan\")},attr:\"scene.dragmode\",val:\"pan\",icon:o.pan,click:h},u.orbitRotation={name:\"orbitRotation\",title:function(t){return c(t,\"Orbital rotation\")},attr:\"scene.dragmode\",val:\"orbit\",icon:o[\"3d_rotate\"],click:h},u.tableRotation={name:\"tableRotation\",title:function(t){return c(t,\"Turntable rotation\")},attr:\"scene.dragmode\",val:\"turntable\",icon:o[\"z-axis\"],click:h},u.resetCameraDefault3d={name:\"resetCameraDefault3d\",_cat:\"resetCameraDefault\",title:function(t){return c(t,\"Reset camera to default\")},attr:\"resetDefault\",icon:o.home,click:p},u.resetCameraLastSave3d={name:\"resetCameraLastSave3d\",_cat:\"resetCameraLastSave\",title:function(t){return c(t,\"Reset camera to last save\")},attr:\"resetLastSave\",icon:o.movie,click:p},u.hoverClosest3d={name:\"hoverClosest3d\",_cat:\"hoverclosest\",title:function(t){return c(t,\"Toggle show closest data on hover\")},attr:\"hovermode\",val:null,toggle:!0,icon:o.tooltip_basic,gravity:\"ne\",click:function(t,e){var r=d(t,e);n.call(\"_guiRelayout\",t,r)}},u.zoomInGeo={name:\"zoomInGeo\",_cat:\"zoomin\",title:function(t){return c(t,\"Zoom in\")},attr:\"zoom\",val:\"in\",icon:o.zoom_plus,click:m},u.zoomOutGeo={name:\"zoomOutGeo\",_cat:\"zoomout\",title:function(t){return c(t,\"Zoom out\")},attr:\"zoom\",val:\"out\",icon:o.zoom_minus,click:m},u.resetGeo={name:\"resetGeo\",_cat:\"reset\",title:function(t){return c(t,\"Reset\")},attr:\"reset\",val:null,icon:o.autoscale,click:m},u.hoverClosestGeo={name:\"hoverClosestGeo\",_cat:\"hoverclosest\",title:function(t){return c(t,\"Toggle show closest data on hover\")},attr:\"hovermode\",val:null,toggle:!0,icon:o.tooltip_basic,gravity:\"ne\",click:v},u.hoverClosestGl2d={name:\"hoverClosestGl2d\",_cat:\"hoverclosest\",title:function(t){return c(t,\"Toggle show closest data on hover\")},attr:\"hovermode\",val:null,toggle:!0,icon:o.tooltip_basic,gravity:\"ne\",click:v},u.hoverClosestPie={name:\"hoverClosestPie\",_cat:\"hoverclosest\",title:function(t){return c(t,\"Toggle show closest data on hover\")},attr:\"hovermode\",val:\"closest\",icon:o.tooltip_basic,gravity:\"ne\",click:v},u.resetViewSankey={name:\"resetSankeyGroup\",title:function(t){return c(t,\"Reset view\")},icon:o.home,click:function(t){for(var e={\"node.groups\":[],\"node.x\":[],\"node.y\":[]},r=0;r<t._fullData.length;r++){var i=t._fullData[r]._viewInitial;e[\"node.groups\"].push(i.node.groups.slice()),e[\"node.x\"].push(i.node.x.slice()),e[\"node.y\"].push(i.node.y.slice())}n.call(\"restyle\",t,e)}},u.toggleHover={name:\"toggleHover\",title:function(t){return c(t,\"Toggle show closest data on hover\")},attr:\"hovermode\",val:null,toggle:!0,icon:o.tooltip_basic,gravity:\"ne\",click:function(t,e){var r=d(t,e);r.hovermode=g(t),n.call(\"_guiRelayout\",t,r)}},u.resetViews={name:\"resetViews\",title:function(t){return c(t,\"Reset views\")},icon:o.home,click:function(t,e){var r=e.currentTarget;r.setAttribute(\"data-attr\",\"zoom\"),r.setAttribute(\"data-val\",\"reset\"),f(t,e),r.setAttribute(\"data-attr\",\"resetLastSave\"),p(t,e),x(t,\"geo\"),x(t,\"mapbox\")}},u.toggleSpikelines={name:\"toggleSpikelines\",title:function(t){return c(t,\"Toggle Spike Lines\")},icon:o.spikeline,attr:\"_cartesianSpikesEnabled\",val:\"on\",click:function(t){var e=t._fullLayout,r=e._cartesianSpikesEnabled;e._cartesianSpikesEnabled=\"on\"===r?\"off\":\"on\",n.call(\"_guiRelayout\",t,function(t){for(var e=\"on\"===t._fullLayout._cartesianSpikesEnabled,r=a.list(t,null,!0),n={},i=0;i<r.length;i++){var o=r[i];n[o._name+\".showspikes\"]=!!e||o._showSpikeInitial}return n}(t))}},u.resetViewMapbox={name:\"resetViewMapbox\",_cat:\"resetView\",title:function(t){return c(t,\"Reset view\")},attr:\"reset\",icon:o.home,click:function(t){x(t,\"mapbox\")}},u.zoomInMapbox={name:\"zoomInMapbox\",_cat:\"zoomin\",title:function(t){return c(t,\"Zoom in\")},attr:\"zoom\",val:\"in\",icon:o.zoom_plus,click:y},u.zoomOutMapbox={name:\"zoomOutMapbox\",_cat:\"zoomout\",title:function(t){return c(t,\"Zoom out\")},attr:\"zoom\",val:\"out\",icon:o.zoom_minus,click:y}},{\"../../fonts/ploticon\":482,\"../../lib\":503,\"../../plots/cartesian/axis_ids\":558,\"../../plots/plots\":619,\"../../registry\":638,\"../shapes/draw\":450}],427:[function(t,e,r){\"use strict\";var n=t(\"./buttons\"),i=Object.keys(n),a=[\"drawline\",\"drawopenpath\",\"drawclosedpath\",\"drawcircle\",\"drawrect\",\"eraseshape\"],o=[\"v1hovermode\",\"hoverclosest\",\"hovercompare\",\"togglehover\",\"togglespikelines\"].concat(a),s=[];i.forEach((function(t){!function(t){if(-1===o.indexOf(t._cat||t.name)){var e=t.name,r=(t._cat||t.name).toLowerCase();-1===s.indexOf(e)&&s.push(e),-1===s.indexOf(r)&&s.push(r)}}(n[t])})),s.sort(),e.exports={DRAW_MODES:a,backButtons:o,foreButtons:s}},{\"./buttons\":426}],428:[function(t,e,r){\"use strict\";var n=t(\"../../lib\"),i=t(\"../color\"),a=t(\"../../plot_api/plot_template\"),o=t(\"./attributes\");e.exports=function(t,e){var r=t.modebar||{},s=a.newContainer(e,\"modebar\");function l(t,e){return n.coerce(r,s,o,t,e)}l(\"orientation\"),l(\"bgcolor\",i.addOpacity(e.paper_bgcolor,.5));var c=i.contrast(i.rgb(e.modebar.bgcolor));l(\"color\",i.addOpacity(c,.3)),l(\"activecolor\",i.addOpacity(c,.7)),l(\"uirevision\",e.uirevision),l(\"add\"),l(\"remove\")}},{\"../../lib\":503,\"../../plot_api/plot_template\":543,\"../color\":366,\"./attributes\":425}],429:[function(t,e,r){\"use strict\";e.exports={moduleType:\"component\",name:\"modebar\",layoutAttributes:t(\"./attributes\"),supplyLayoutDefaults:t(\"./defaults\"),manage:t(\"./manage\")}},{\"./attributes\":425,\"./defaults\":428,\"./manage\":430}],430:[function(t,e,r){\"use strict\";var n=t(\"../../plots/cartesian/axis_ids\"),i=t(\"../../traces/scatter/subtypes\"),a=t(\"../../registry\"),o=t(\"../fx/helpers\").isUnifiedHover,s=t(\"./modebar\"),l=t(\"./buttons\"),c=t(\"./constants\").DRAW_MODES,u=t(\"../../lib\").extendDeep;e.exports=function(t){var e=t._fullLayout,r=t._context,f=e._modeBar;if(r.displayModeBar||r.watermark){if(!Array.isArray(r.modeBarButtonsToRemove))throw new Error([\"*modeBarButtonsToRemove* configuration options\",\"must be an array.\"].join(\" \"));if(!Array.isArray(r.modeBarButtonsToAdd))throw new Error([\"*modeBarButtonsToAdd* configuration options\",\"must be an array.\"].join(\" \"));var h,p=r.modeBarButtons;h=Array.isArray(p)&&p.length?function(t){for(var e=u([],t),r=0;r<e.length;r++)for(var n=e[r],i=0;i<n.length;i++){var a=n[i];if(\"string\"==typeof a){if(void 0===l[a])throw new Error([\"*modeBarButtons* configuration options\",\"invalid button name\"].join(\" \"));e[r][i]=l[a]}}return e}(p):!r.displayModeBar&&r.watermark?[]:function(t){var e=t._fullLayout,r=t._fullData,s=t._context;function u(t,e){if(\"string\"==typeof e){if(e.toLowerCase()===t.toLowerCase())return!0}else{var r=e.name,n=e._cat||e.name;if(r===t||n===t.toLowerCase())return!0}return!1}var f=e.modebar.add;\"string\"==typeof f&&(f=[f]);var h=e.modebar.remove;\"string\"==typeof h&&(h=[h]);var p=s.modeBarButtonsToAdd.concat(f.filter((function(t){for(var e=0;e<s.modeBarButtonsToRemove.length;e++)if(u(t,s.modeBarButtonsToRemove[e]))return!1;return!0}))),d=s.modeBarButtonsToRemove.concat(h.filter((function(t){for(var e=0;e<s.modeBarButtonsToAdd.length;e++)if(u(t,s.modeBarButtonsToAdd[e]))return!1;return!0}))),m=e._has(\"cartesian\"),g=e._has(\"gl3d\"),v=e._has(\"geo\"),y=e._has(\"pie\"),x=e._has(\"funnelarea\"),b=e._has(\"gl2d\"),_=e._has(\"ternary\"),w=e._has(\"mapbox\"),T=e._has(\"polar\"),k=e._has(\"smith\"),A=e._has(\"sankey\"),M=function(t){for(var e=n.list({_fullLayout:t},null,!0),r=0;r<e.length;r++)if(!e[r].fixedrange)return!1;return!0}(e),S=o(e.hovermode),E=[];function L(t){if(t.length){for(var e=[],r=0;r<t.length;r++){for(var n=t[r],i=l[n],a=i.name.toLowerCase(),o=(i._cat||i.name).toLowerCase(),s=!1,c=0;c<d.length;c++){var u=d[c].toLowerCase();if(u===a||u===o){s=!0;break}}s||e.push(l[n])}E.push(e)}}var C=[\"toImage\"];s.showEditInChartStudio?C.push(\"editInChartStudio\"):s.showSendToCloud&&C.push(\"sendDataToCloud\");L(C);var P=[],I=[],O=[],z=[];(m||b||y||x||_)+v+g+w+T+k>1?(I=[\"toggleHover\"],O=[\"resetViews\"]):v?(P=[\"zoomInGeo\",\"zoomOutGeo\"],I=[\"hoverClosestGeo\"],O=[\"resetGeo\"]):g?(I=[\"hoverClosest3d\"],O=[\"resetCameraDefault3d\",\"resetCameraLastSave3d\"]):w?(P=[\"zoomInMapbox\",\"zoomOutMapbox\"],I=[\"toggleHover\"],O=[\"resetViewMapbox\"]):b?I=[\"hoverClosestGl2d\"]:y?I=[\"hoverClosestPie\"]:A?(I=[\"hoverClosestCartesian\",\"hoverCompareCartesian\"],O=[\"resetViewSankey\"]):I=[\"toggleHover\"];m&&(I=[\"toggleSpikelines\",\"hoverClosestCartesian\",\"hoverCompareCartesian\"]);(function(t){for(var e=0;e<t.length;e++)if(!a.traceIs(t[e],\"noHover\"))return!1;return!0}(r)||S)&&(I=[]);!m&&!b||M||(P=[\"zoomIn2d\",\"zoomOut2d\",\"autoScale2d\"],\"resetViews\"!==O[0]&&(O=[\"resetScale2d\"]));g?z=[\"zoom3d\",\"pan3d\",\"orbitRotation\",\"tableRotation\"]:(m||b)&&!M||_?z=[\"zoom2d\",\"pan2d\"]:w||v?z=[\"pan2d\"]:T&&(z=[\"zoom2d\"]);(function(t){for(var e=!1,r=0;r<t.length&&!e;r++){var n=t[r];n._module&&n._module.selectPoints&&(a.traceIs(n,\"scatter-like\")?(i.hasMarkers(n)||i.hasText(n))&&(e=!0):a.traceIs(n,\"box-violin\")&&\"all\"!==n.boxpoints&&\"all\"!==n.points||(e=!0))}return e})(r)&&z.push(\"select2d\",\"lasso2d\");var D=[],R=function(t){-1===D.indexOf(t)&&-1!==I.indexOf(t)&&D.push(t)};if(Array.isArray(p)){for(var F=[],B=0;B<p.length;B++){var N=p[B];\"string\"==typeof N?(N=N.toLowerCase(),-1!==c.indexOf(N)?(e._has(\"mapbox\")||e._has(\"cartesian\"))&&z.push(N):\"togglespikelines\"===N?R(\"toggleSpikelines\"):\"togglehover\"===N?R(\"toggleHover\"):\"hovercompare\"===N?R(\"hoverCompareCartesian\"):\"hoverclosest\"===N?(R(\"hoverClosestCartesian\"),R(\"hoverClosestGeo\"),R(\"hoverClosest3d\"),R(\"hoverClosestGl2d\"),R(\"hoverClosestPie\")):\"v1hovermode\"===N&&(R(\"toggleHover\"),R(\"hoverClosestCartesian\"),R(\"hoverCompareCartesian\"),R(\"hoverClosestGeo\"),R(\"hoverClosest3d\"),R(\"hoverClosestGl2d\"),R(\"hoverClosestPie\"))):F.push(N)}p=F}return L(z),L(P.concat(O)),L(D),function(t,e){if(e.length)if(Array.isArray(e[0]))for(var r=0;r<e.length;r++)t.push(e[r]);else t.push(e);return t}(E,p)}(t),f?f.update(t,h):e._modeBar=s(t,h)}else f&&(f.destroy(),delete e._modeBar)}},{\"../../lib\":503,\"../../plots/cartesian/axis_ids\":558,\"../../registry\":638,\"../../traces/scatter/subtypes\":952,\"../fx/helpers\":402,\"./buttons\":426,\"./constants\":427,\"./modebar\":431}],431:[function(t,e,r){\"use strict\";var n=t(\"@plotly/d3\"),i=t(\"fast-isnumeric\"),a=t(\"../../lib\"),o=t(\"../../fonts/ploticon\"),s=t(\"../../version\").version,l=new DOMParser;function c(t){this.container=t.container,this.element=document.createElement(\"div\"),this.update(t.graphInfo,t.buttons),this.container.appendChild(this.element)}var u=c.prototype;u.update=function(t,e){this.graphInfo=t;var r=this.graphInfo._context,n=this.graphInfo._fullLayout,i=\"modebar-\"+n._uid;this.element.setAttribute(\"id\",i),this._uid=i,this.element.className=\"modebar\",\"hover\"===r.displayModeBar&&(this.element.className+=\" modebar--hover ease-bg\"),\"v\"===n.modebar.orientation&&(this.element.className+=\" vertical\",e=e.reverse());var o=n.modebar,s=\"hover\"===r.displayModeBar?\".js-plotly-plot .plotly:hover \":\"\";a.deleteRelatedStyleRule(i),a.addRelatedStyleRule(i,s+\"#\"+i+\" .modebar-group\",\"background-color: \"+o.bgcolor),a.addRelatedStyleRule(i,\"#\"+i+\" .modebar-btn .icon path\",\"fill: \"+o.color),a.addRelatedStyleRule(i,\"#\"+i+\" .modebar-btn:hover .icon path\",\"fill: \"+o.activecolor),a.addRelatedStyleRule(i,\"#\"+i+\" .modebar-btn.active .icon path\",\"fill: \"+o.activecolor);var l=!this.hasButtons(e),c=this.hasLogo!==r.displaylogo,u=this.locale!==r.locale;if(this.locale=r.locale,(l||c||u)&&(this.removeAllButtons(),this.updateButtons(e),r.watermark||r.displaylogo)){var f=this.getLogo();r.watermark&&(f.className=f.className+\" watermark\"),\"v\"===n.modebar.orientation?this.element.insertBefore(f,this.element.childNodes[0]):this.element.appendChild(f),this.hasLogo=!0}this.updateActiveButton()},u.updateButtons=function(t){var e=this;this.buttons=t,this.buttonElements=[],this.buttonsNames=[],this.buttons.forEach((function(t){var r=e.createGroup();t.forEach((function(t){var n=t.name;if(!n)throw new Error(\"must provide button 'name' in button config\");if(-1!==e.buttonsNames.indexOf(n))throw new Error(\"button name '\"+n+\"' is taken\");e.buttonsNames.push(n);var i=e.createButton(t);e.buttonElements.push(i),r.appendChild(i)})),e.element.appendChild(r)}))},u.createGroup=function(){var t=document.createElement(\"div\");return t.className=\"modebar-group\",t},u.createButton=function(t){var e=this,r=document.createElement(\"a\");r.setAttribute(\"rel\",\"tooltip\"),r.className=\"modebar-btn\";var i=t.title;void 0===i?i=t.name:\"function\"==typeof i&&(i=i(this.graphInfo)),(i||0===i)&&r.setAttribute(\"data-title\",i),void 0!==t.attr&&r.setAttribute(\"data-attr\",t.attr);var a=t.val;if(void 0!==a&&(\"function\"==typeof a&&(a=a(this.graphInfo)),r.setAttribute(\"data-val\",a)),\"function\"!=typeof t.click)throw new Error(\"must provide button 'click' function in button config\");r.addEventListener(\"click\",(function(r){t.click(e.graphInfo,r),e.updateActiveButton(r.currentTarget)})),r.setAttribute(\"data-toggle\",t.toggle||!1),t.toggle&&n.select(r).classed(\"active\",!0);var s=t.icon;return\"function\"==typeof s?r.appendChild(s()):r.appendChild(this.createIcon(s||o.question)),r.setAttribute(\"data-gravity\",t.gravity||\"n\"),r},u.createIcon=function(t){var e,r=i(t.height)?Number(t.height):t.ascent-t.descent,n=\"http://www.w3.org/2000/svg\";if(t.path){(e=document.createElementNS(n,\"svg\")).setAttribute(\"viewBox\",[0,0,t.width,r].join(\" \")),e.setAttribute(\"class\",\"icon\");var a=document.createElementNS(n,\"path\");a.setAttribute(\"d\",t.path),t.transform?a.setAttribute(\"transform\",t.transform):void 0!==t.ascent&&a.setAttribute(\"transform\",\"matrix(1 0 0 -1 0 \"+t.ascent+\")\"),e.appendChild(a)}t.svg&&(e=l.parseFromString(t.svg,\"application/xml\").childNodes[0]);return e.setAttribute(\"height\",\"1em\"),e.setAttribute(\"width\",\"1em\"),e},u.updateActiveButton=function(t){var e=this.graphInfo._fullLayout,r=void 0!==t?t.getAttribute(\"data-attr\"):null;this.buttonElements.forEach((function(t){var i=t.getAttribute(\"data-val\")||!0,o=t.getAttribute(\"data-attr\"),s=\"true\"===t.getAttribute(\"data-toggle\"),l=n.select(t);if(s)o===r&&l.classed(\"active\",!l.classed(\"active\"));else{var c=null===o?o:a.nestedProperty(e,o).get();l.classed(\"active\",c===i)}}))},u.hasButtons=function(t){var e=this.buttons;if(!e)return!1;if(t.length!==e.length)return!1;for(var r=0;r<t.length;++r){if(t[r].length!==e[r].length)return!1;for(var 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t.match(n.segmentRE).forEach((function(t){var a=e[t.charAt(0)].drawn;if(void 0!==a){var o=t.substr(1).match(n.paramRE);!o||o.length<a||r.push(i.cleanNumber(o[a]))}})),r},r.getDataToPixel=function(t,e,n,i){var a,o=t._fullLayout._size;if(e)if(\"domain\"===i)a=function(t){return e._length*(n?1-t:t)+e._offset};else{var s=r.shapePositionToRange(e);a=function(t){return e._offset+e.r2p(s(t,!0))},\"date\"===e.type&&(a=r.decodeDate(a))}else a=n?function(t){return o.t+o.h*(1-t)}:function(t){return o.l+o.w*t};return a},r.getPixelToData=function(t,e,n,i){var a,o=t._fullLayout._size;if(e)if(\"domain\"===i)a=function(t){var r=(t-e._offset)/e._length;return n?1-r:r};else{var s=r.rangeToShapePosition(e);a=function(t){return s(e.p2r(t-e._offset))}}else a=n?function(t){return 1-(t-o.t)/o.h}:function(t){return(t-o.l)/o.w};return a},r.roundPositionForSharpStrokeRendering=function(t,e){var r=1===Math.round(e%2),n=Math.round(t);return r?n+.5:n},r.makeOptionsAndPlotinfo=function(t,e){var 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n=t(\"../../plots/font_attributes\"),i=t(\"../../plots/pad_attributes\"),a=t(\"../../lib/extend\").extendDeepAll,o=t(\"../../plot_api/edit_types\").overrideAll,s=t(\"../../plots/animation_attributes\"),l=t(\"../../plot_api/plot_template\").templatedArray,c=t(\"./constants\"),u=l(\"step\",{visible:{valType:\"boolean\",dflt:!0},method:{valType:\"enumerated\",values:[\"restyle\",\"relayout\",\"animate\",\"update\",\"skip\"],dflt:\"restyle\"},args:{valType:\"info_array\",freeLength:!0,items:[{valType:\"any\"},{valType:\"any\"},{valType:\"any\"}]},label:{valType:\"string\"},value:{valType:\"string\"},execute:{valType:\"boolean\",dflt:!0}});e.exports=o(l(\"slider\",{visible:{valType:\"boolean\",dflt:!0},active:{valType:\"number\",min:0,dflt:0},steps:u,lenmode:{valType:\"enumerated\",values:[\"fraction\",\"pixels\"],dflt:\"fraction\"},len:{valType:\"number\",min:0,dflt:1},x:{valType:\"number\",min:-2,max:3,dflt:0},pad:a(i({editType:\"arraydraw\"}),{},{t:{dflt:20}}),xanchor:{valType:\"enumerated\",values:[\"auto\",\"left\",\"center\",\"right\"],dflt:\"left\"},y:{valType:\"number\",min:-2,max:3,dflt:0},yanchor:{valType:\"enumerated\",values:[\"auto\",\"top\",\"middle\",\"bottom\"],dflt:\"top\"},transition:{duration:{valType:\"number\",min:0,dflt:150},easing:{valType:\"enumerated\",values:s.transition.easing.values,dflt:\"cubic-in-out\"}},currentvalue:{visible:{valType:\"boolean\",dflt:!0},xanchor:{valType:\"enumerated\",values:[\"left\",\"center\",\"right\"],dflt:\"left\"},offset:{valType:\"number\",dflt:10},prefix:{valType:\"string\"},suffix:{valType:\"string\"},font:n({})},font:n({}),activebgcolor:{valType:\"color\",dflt:c.gripBgActiveColor},bgcolor:{valType:\"color\",dflt:c.railBgColor},bordercolor:{valType:\"color\",dflt:c.railBorderColor},borderwidth:{valType:\"number\",min:0,dflt:c.railBorderWidth},ticklen:{valType:\"number\",min:0,dflt:c.tickLength},tickcolor:{valType:\"color\",dflt:c.tickColor},tickwidth:{valType:\"number\",min:0,dflt:1},minorticklen:{valType:\"number\",min:0,dflt:c.minorTickLength}}),\"arraydraw\",\"from-root\")},{\"../../lib/extend\":493,\"../../plot_api/edit_types\":536,\"../../plot_api/plot_template\":543,\"../../plots/animation_attributes\":548,\"../../plots/font_attributes\":585,\"../../plots/pad_attributes\":618,\"./constants\":460}],460:[function(t,e,r){\"use 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T={y:e.y,b:u.height*m[w],t:u.height*d[w]};\"fraction\"===e.lenmode?(T.l=0,T.xl=e.x-e.len*d[b],T.r=0,T.xr=e.x+e.len*m[b]):(T.x=e.x,T.l=u.outerLength*d[b],T.r=u.outerLength*m[b]),i.autoMargin(t,g(e),T)}function x(t,e,r){if(e.currentvalue.visible){var n,i,a=e._dims;switch(e.currentvalue.xanchor){case\"right\":n=a.inputAreaLength-f.currentValueInset-a.currentValueMaxWidth,i=\"left\";break;case\"center\":n=.5*a.inputAreaLength,i=\"middle\";break;default:n=f.currentValueInset,i=\"left\"}var l=s.ensureSingle(t,\"text\",f.labelClass,(function(t){t.attr({\"text-anchor\":i,\"data-notex\":1})})),u=e.currentvalue.prefix?e.currentvalue.prefix:\"\";if(\"string\"==typeof r)u+=r;else{var h=e.steps[e.active].label,d=e._gd._fullLayout._meta;d&&(h=s.templateString(h,d)),u+=h}e.currentvalue.suffix&&(u+=e.currentvalue.suffix),l.call(o.font,e.currentvalue.font).text(u).call(c.convertToTspans,e._gd);var m=c.lineCount(l),g=(a.currentValueMaxLines+1-m)*e.currentvalue.font.size*p;return 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t=s(),a=L(t,n.mouse(i)[0]);T(e,r,t,a,!1)}function h(){var t=s();t._dragging=!1,l.call(a.fill,t.bgcolor),o.on(\"mouseup\",null),o.on(\"mousemove\",null),o.on(\"touchend\",null),o.on(\"touchmove\",null),e.emit(\"plotly_sliderend\",{slider:t,step:t.steps[t.active]})}T(e,r,t,c,!0),t._dragging=!0,o.on(\"mousemove\",u),o.on(\"touchmove\",u),o.on(\"mouseup\",h),o.on(\"touchend\",h)}t.on(\"mousedown\",l),t.on(\"touchstart\",l)}function M(t,e){var r=t.selectAll(\"rect.\"+f.tickRectClass).data(e._visibleSteps),i=e._dims;r.enter().append(\"rect\").classed(f.tickRectClass,!0),r.exit().remove(),r.attr({width:e.tickwidth+\"px\",\"shape-rendering\":\"crispEdges\"}),r.each((function(t,r){var s=r%i.labelStride==0,l=n.select(this);l.attr({height:s?e.ticklen:e.minorticklen}).call(a.fill,e.tickcolor),o.setTranslate(l,E(e,r/(e._stepCount-1))-.5*e.tickwidth,(s?f.tickOffset:f.minorTickOffset)+i.currentValueTotalHeight)}))}function S(t,e,r){for(var 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n=t(\"@plotly/d3\"),i=t(\"d3-time-format\").utcFormat,a=t(\"d3-format\").format,o=t(\"fast-isnumeric\"),s=t(\"../constants/numerical\"),l=s.FP_SAFE,c=-l,u=s.BADNUM,f=e.exports={};f.adjustFormat=function(t){return!t||/^\\d[.]\\df/.test(t)||/[.]\\d%/.test(t)?t:\"0.f\"===t?\"~f\":/^\\d%/.test(t)?\"~%\":/^\\ds/.test(t)?\"~s\":!/^[~,.0$]/.test(t)&&/[&fps]/.test(t)?\"~\"+t:t};var h={};f.warnBadFormat=function(t){var e=String(t);h[e]||(h[e]=1,f.warn('encountered bad format: \"'+e+'\"'))},f.noFormat=function(t){return String(t)},f.numberFormat=function(t){var e;try{e=a(f.adjustFormat(t))}catch(e){return f.warnBadFormat(t),f.noFormat}return e},f.nestedProperty=t(\"./nested_property\"),f.keyedContainer=t(\"./keyed_container\"),f.relativeAttr=t(\"./relative_attr\"),f.isPlainObject=t(\"./is_plain_object\"),f.toLogRange=t(\"./to_log_range\"),f.relinkPrivateKeys=t(\"./relink_private\");var 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b=0;b<t.calcdata.length;b++)t.calcdata[b][0].trace=t._fullData[b];t._context.responsive?t._responsiveChartHandler||(t._responsiveChartHandler=function(){o.isHidden(t)||h.resize(t)},window.addEventListener(\"resize\",t._responsiveChartHandler)):o.clearResponsive(t);var T=o.extendFlat({},m._size),k=0;function A(){if(h.clearAutoMarginIds(t),w.drawMarginPushers(t),p.allowAutoMargin(t),m._has(\"pie\"))for(var e=t._fullData,r=0;r<e.length;r++){var n=e[r];\"pie\"===n.type&&n.automargin&&h.allowAutoMargin(t,\"pie.\"+n.uid+\".automargin\")}return h.doAutoMargin(t),h.previousPromises(t)}function S(){t._transitioning||(w.doAutoRangeAndConstraints(t),f&&p.saveRangeInitial(t),u.getComponentMethod(\"rangeslider\",\"calcAutorange\")(t))}var E=[h.previousPromises,function(){if(s)return r.addFrames(t,s)},function e(){for(var 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u=e._clips.selectAll(\".axesclip\").data(c,(function(t){return t.x._id+t.y._id}));u.enter().append(\"clipPath\").classed(\"axesclip\",!0).attr(\"id\",(function(t){return\"clip\"+e._uid+t.x._id+t.y._id})).append(\"rect\"),u.exit().remove(),u.each((function(t){n.select(this).select(\"rect\").attr({x:t.x._offset||0,y:t.y._offset||0,width:t.x._length||1,height:t.y._length||1})}))}},H.draw=function(t,e,r){var n=t._fullLayout;\"redraw\"===e&&n._paper.selectAll(\"g.subplot\").each((function(t){var e=t[0],r=n._plots[e];if(r){var i=r.xaxis,a=r.yaxis;r.xaxislayer.selectAll(\".\"+i._id+\"tick\").remove(),r.yaxislayer.selectAll(\".\"+a._id+\"tick\").remove(),r.xaxislayer.selectAll(\".\"+i._id+\"tick2\").remove(),r.yaxislayer.selectAll(\".\"+a._id+\"tick2\").remove(),r.xaxislayer.selectAll(\".\"+i._id+\"divider\").remove(),r.yaxislayer.selectAll(\".\"+a._id+\"divider\").remove(),r.minorGridlayer&&r.minorGridlayer.selectAll(\"path\").remove(),r.gridlayer&&r.gridlayer.selectAll(\"path\").remove(),r.zerolinelayer&&r.zerolinelayer.selectAll(\"path\").remove(),n._infolayer.select(\".g-\"+i._id+\"title\").remove(),n._infolayer.select(\".g-\"+a._id+\"title\").remove()}}));var i=e&&\"redraw\"!==e?e:H.listIds(t);return s.syncOrAsync(i.map((function(e){return function(){if(e){var n=H.getFromId(t,e),i=H.drawOne(t,n,r);return n._r=n.range.slice(),n._rl=s.simpleMap(n._r,n.r2l),i}}})))},H.drawOne=function(t,e,r){var n,i,l;r=r||{},e.setScale();var c=t._fullLayout,p=e._id,d=p.charAt(0),m=H.counterLetter(p),g=c._plots[e._mainSubplot];if(g){var v=g[d+\"axislayer\"],y=e._mainLinePosition,x=e._mainMirrorPosition,b=e._vals=H.calcTicks(e),_=[e.mirror,y,x].join(\"_\");for(n=0;n<b.length;n++)b[n].axInfo=_;e._selections={},e._tickAngles&&(e._prevTickAngles=e._tickAngles),e._tickAngles={},e._depth=null;var w={};if(e.visible){var T,k,A=H.makeTransTickFn(e),M=H.makeTransTickLabelFn(e),S=\"inside\"===e.ticks,E=\"outside\"===e.ticks;if(\"boundaries\"===e.tickson){var L=function(t,e){var r,n=[],i=function(t,e){var r=t.xbnd[e];null!==r&&n.push(s.extendFlat({},t,{x:r}))};if(e.length){for(r=0;r<e.length;r++)i(e[r],0);i(e[r-1],1)}return n}(0,b);k=H.clipEnds(e,L),T=S?k:L}else k=H.clipEnds(e,b),T=S&&\"period\"!==e.ticklabelmode?k:b;var C,P=e._gridVals=k,I=function(t,e){var r,n,i=[],a=e.length&&e[e.length-1].x<e[0].x,o=function(t,e){var r=t.xbnd[e];null!==r&&i.push(s.extendFlat({},t,{x:r}))};if(t.showdividers&&e.length){for(r=0;r<e.length;r++){var l=e[r];l.text2!==n&&o(l,a?1:0),n=l.text2}o(e[r-1],a?0:1)}return i}(e,b);if(!c._hasOnlyLargeSploms){var O=e._subplotsWith,z={};for(n=0;n<O.length;n++){i=O[n];var D=(l=c._plots[i])[m+\"axis\"],R=D._mainAxis._id;if(!z[R]){z[R]=1;var F=\"x\"===d?\"M0,\"+D._offset+\"v\"+D._length:\"M\"+D._offset+\",0h\"+D._length;H.drawGrid(t,e,{vals:P,counterAxis:D,layer:l.gridlayer.select(\".\"+p),minorLayer:l.minorGridlayer.select(\".\"+p),path:F,transFn:A}),H.drawZeroLine(t,e,{counterAxis:D,layer:l.zerolinelayer,path:F,transFn:A})}}}var B=H.getTickSigns(e),N=H.getTickSigns(e,\"minor\");if(e.ticks||e.minor&&e.minor.ticks){var j,q,G,Y,W=H.makeTickPath(e,y,B[2]),X=H.makeTickPath(e,y,N[2],{minor:!0});if(e._anchorAxis&&e.mirror&&!0!==e.mirror?(j=H.makeTickPath(e,x,B[3]),q=H.makeTickPath(e,x,N[3],{minor:!0}),G=W+j,Y=X+q):(j=\"\",q=\"\",G=W,Y=X),e.showdividers&&E&&\"boundaries\"===e.tickson){var Z={};for(n=0;n<I.length;n++)Z[I[n].x]=1;C=function(t){return Z[t.x]?j:G}}else C=function(t){return t.minor?Y:G}}if(H.drawTicks(t,e,{vals:T,layer:v,path:C,transFn:A}),\"allticks\"===e.mirror){var J=Object.keys(e._linepositions||{});for(n=0;n<J.length;n++){i=J[n],l=c._plots[i];var K=e._linepositions[i]||[],Q=K[0],$=K[1],tt=K[2],et=H.makeTickPath(e,Q,tt?B[0]:N[0],{minor:tt})+H.makeTickPath(e,$,tt?B[1]:N[1],{minor:tt});H.drawTicks(t,e,{vals:T,layer:l[d+\"axislayer\"],path:et,transFn:A})}}var rt=[];if(rt.push((function(){return H.drawLabels(t,e,{vals:b,layer:v,plotinfo:l,transFn:M,labelFns:H.makeLabelFns(e,y)})})),\"multicategory\"===e.type){var nt={x:2,y:10}[d];rt.push((function(){var r={x:\"height\",y:\"width\"}[d],n=at()[r]+nt+(e._tickAngles[p+\"tick\"]?e.tickfont.size*U:0);return H.drawLabels(t,e,{vals:vt(e,b),layer:v,cls:p+\"tick2\",repositionOnUpdate:!0,secondary:!0,transFn:A,labelFns:H.makeLabelFns(e,y+n*B[4])})})),rt.push((function(){return e._depth=B[4]*(at(\"tick2\")[e.side]-y),function(t,e,r){var n=e._id+\"divider\",i=r.vals,a=r.layer.selectAll(\"path.\"+n).data(i,xt);a.exit().remove(),a.enter().insert(\"path\",\":first-child\").classed(n,1).classed(\"crisp\",1).call(f.stroke,e.dividercolor).style(\"stroke-width\",h.crispRound(t,e.dividerwidth,1)+\"px\"),a.attr(\"transform\",r.transFn).attr(\"d\",r.path)}(t,e,{vals:I,layer:v,path:H.makeTickPath(e,y,B[4],{len:e._depth}),transFn:A})}))}else e.title.hasOwnProperty(\"standoff\")&&rt.push((function(){e._depth=B[4]*(at()[e.side]-y)}));var it=o.getComponentMethod(\"rangeslider\",\"isVisible\")(e);return rt.push((function(){var r,n,i,s,l=e.side.charAt(0),u=V[e.side].charAt(0),f=H.getPxPosition(t,e),h=E?e.ticklen:0;if((e.automargin||it)&&(\"multicategory\"===e.type?r=at(\"tick2\"):(r=at(),\"x\"===d&&\"b\"===l&&(e._depth=Math.max(r.width>0?r.bottom-f:0,h)))),e.automargin){n={x:0,y:0,r:0,l:0,t:0,b:0};var p=[0,1];if(\"x\"===d){if(\"b\"===l?n[l]=e._depth:(n[l]=e._depth=Math.max(r.width>0?f-r.top:0,h),p.reverse()),r.width>0){var g=r.right-(e._offset+e._length);g>0&&(n.xr=1,n.r=g);var v=e._offset-r.left;v>0&&(n.xl=0,n.l=v)}}else if(\"l\"===l?n[l]=e._depth=Math.max(r.height>0?f-r.left:0,h):(n[l]=e._depth=Math.max(r.height>0?r.right-f:0,h),p.reverse()),r.height>0){var y=r.bottom-(e._offset+e._length);y>0&&(n.yb=0,n.b=y);var x=e._offset-r.top;x>0&&(n.yt=1,n.t=x)}n[m]=\"free\"===e.anchor?e.position:e._anchorAxis.domain[p[0]],e.title.text!==c._dfltTitle[d]&&(n[l]+=bt(e)+(e.title.standoff||0)),e.mirror&&\"free\"!==e.anchor&&((i={x:0,y:0,r:0,l:0,t:0,b:0})[u]=e.linewidth,e.mirror&&!0!==e.mirror&&(i[u]+=h),!0===e.mirror||\"ticks\"===e.mirror?i[m]=e._anchorAxis.domain[p[1]]:\"all\"!==e.mirror&&\"allticks\"!==e.mirror||(i[m]=[e._counterDomainMin,e._counterDomainMax][p[1]]))}it&&(s=o.getComponentMethod(\"rangeslider\",\"autoMarginOpts\")(t,e)),a.autoMargin(t,Tt(e),n),a.autoMargin(t,kt(e),i),a.autoMargin(t,At(e),s)})),r.skipTitle||it&&\"bottom\"===e.side||rt.push((function(){return function(t,e){var r,n=t._fullLayout,i=e._id,a=i.charAt(0),o=e.title.font.size;if(e.title.hasOwnProperty(\"standoff\"))r=e._depth+e.title.standoff+bt(e);else{var s=Pt(e);if(\"multicategory\"===e.type)r=e._depth;else{var l=1.5*o;s&&(l=.5*o,\"outside\"===e.ticks&&(l+=e.ticklen)),r=10+l+(e.linewidth?e.linewidth-1:0)}s||(r+=\"x\"===a?\"top\"===e.side?o*(e.showticklabels?1:0):o*(e.showticklabels?1.5:.5):\"right\"===e.side?o*(e.showticklabels?1:.5):o*(e.showticklabels?.5:0))}var c,f,p,d,m=H.getPxPosition(t,e);\"x\"===a?(f=e._offset+e._length/2,p=\"top\"===e.side?m-r:m+r):(p=e._offset+e._length/2,f=\"right\"===e.side?m+r:m-r,c={rotate:\"-90\",offset:0});if(\"multicategory\"!==e.type){var g=e._selections[e._id+\"tick\"];if(d={selection:g,side:e.side},g&&g.node()&&g.node().parentNode){var v=h.getTranslate(g.node().parentNode);d.offsetLeft=v.x,d.offsetTop=v.y}e.title.hasOwnProperty(\"standoff\")&&(d.pad=0)}return u.draw(t,i+\"title\",{propContainer:e,propName:e._name+\".title.text\",placeholder:n._dfltTitle[a],avoid:d,transform:c,attributes:{x:f,y:p,\"text-anchor\":\"middle\"}})}(t,e)})),s.syncOrAsync(rt)}}function at(t){var r=p+(t||\"tick\");return w[r]||(w[r]=function(t,e){var r,n,i,a;t._selections[e].size()?(r=1/0,n=-1/0,i=1/0,a=-1/0,t._selections[e].each((function(){var t=wt(this),e=h.bBox(t.node().parentNode);r=Math.min(r,e.top),n=Math.max(n,e.bottom),i=Math.min(i,e.left),a=Math.max(a,e.right)}))):(r=0,n=0,i=0,a=0);return{top:r,bottom:n,left:i,right:a,height:n-r,width:a-i}}(e,r)),w[r]}},H.getTickSigns=function(t,e){var r=t._id.charAt(0),n={x:\"top\",y:\"right\"}[r],i=t.side===n?1:-1,a=[-1,1,i,-i];return\"inside\"!==(e?(t.minor||{}).ticks:t.ticks)==(\"x\"===r)&&(a=a.map((function(t){return-t}))),t.side&&a.push({l:-1,t:-1,r:1,b:1}[t.side.charAt(0)]),a},H.makeTransTickFn=function(t){return\"x\"===t._id.charAt(0)?function(e){return l(t._offset+t.l2p(e.x),0)}:function(e){return l(0,t._offset+t.l2p(e.x))}},H.makeTransTickLabelFn=function(t){var e=function(t){var e=t.ticklabelposition||\"\",r=function(t){return-1!==e.indexOf(t)},n=r(\"top\"),i=r(\"left\"),a=r(\"right\"),o=r(\"bottom\"),s=r(\"inside\"),l=o||i||n||a;if(!l&&!s)return[0,0];var c=t.side,u=l?(t.tickwidth||0)/2:0,f=3,h=t.tickfont?t.tickfont.size:12;(o||n)&&(u+=h*j,f+=(t.linewidth||0)/2);(i||a)&&(u+=(t.linewidth||0)/2,f+=3);s&&\"top\"===c&&(f-=h*(1-j));(i||n)&&(u=-u);\"bottom\"!==c&&\"right\"!==c||(f=-f);return[l?u:0,s?f:0]}(t),r=e[0],n=e[1];return\"x\"===t._id.charAt(0)?function(e){return l(r+t._offset+t.l2p(yt(e)),n)}:function(e){return l(n,r+t._offset+t.l2p(yt(e)))}},H.makeTickPath=function(t,e,r,n){n||(n={});var i=n.minor;if(i&&!t.minor)return\"\";var a=void 0!==n.len?n.len:i?t.minor.ticklen:t.ticklen,o=t._id.charAt(0),s=(t.linewidth||1)/2;return\"x\"===o?\"M0,\"+(e+s*r)+\"v\"+a*r:\"M\"+(e+s*r)+\",0h\"+a*r},H.makeLabelFns=function(t,e,r){var n=t.ticklabelposition||\"\",a=function(t){return-1!==n.indexOf(t)},o=a(\"top\"),l=a(\"left\"),c=a(\"right\"),u=a(\"bottom\")||l||o||c,f=a(\"inside\"),h=\"inside\"===n&&\"inside\"===t.ticks||!f&&\"outside\"===t.ticks&&\"boundaries\"!==t.tickson,p=0,d=0,m=h?t.ticklen:0;if(f?m*=-1:u&&(m=0),h&&(p+=m,r)){var g=s.deg2rad(r);p=m*Math.cos(g)+1,d=m*Math.sin(g)}t.showticklabels&&(h||t.showline)&&(p+=.2*t.tickfont.size);var v,y,x,b,_,w={labelStandoff:p+=(t.linewidth||1)/2*(f?-1:1),labelShift:d},T=0,k=t.side,A=t._id.charAt(0),M=t.tickangle;if(\"x\"===A)b=(_=!f&&\"bottom\"===k||f&&\"top\"===k)?1:-1,f&&(b*=-1),v=d*b,y=e+p*b,x=_?1:-.2,90===Math.abs(M)&&(f?x+=N:x=-90===M&&\"bottom\"===k?j:90===M&&\"top\"===k?N:.5,T=N/2*(M/90)),w.xFn=function(t){return t.dx+v+T*t.fontSize},w.yFn=function(t){return t.dy+y+t.fontSize*x},w.anchorFn=function(t,e){if(u){if(l)return\"end\";if(c)return\"start\"}return i(e)&&0!==e&&180!==e?e*b<0!==f?\"end\":\"start\":\"middle\"},w.heightFn=function(e,r,n){return r<-60||r>60?-.5*n:\"top\"===t.side!==f?-n:0};else if(\"y\"===A){if(b=(_=!f&&\"left\"===k||f&&\"right\"===k)?1:-1,f&&(b*=-1),v=p,y=d*b,x=0,f||90!==Math.abs(M)||(x=-90===M&&\"left\"===k||90===M&&\"right\"===k?j:.5),f){var S=i(M)?+M:0;if(0!==S){var E=s.deg2rad(S);T=Math.abs(Math.sin(E))*j*b,x=0}}w.xFn=function(t){return t.dx+e-(v+t.fontSize*x)*b+T*t.fontSize},w.yFn=function(t){return t.dy+y+t.fontSize*N},w.anchorFn=function(t,e){return i(e)&&90===Math.abs(e)?\"middle\":_?\"end\":\"start\"},w.heightFn=function(e,r,n){return\"right\"===t.side&&(r*=-1),r<-30?-n:r<30?-.5*n:0}}return w},H.drawTicks=function(t,e,r){r=r||{};var i=e._id+\"tick\",a=[].concat(e.minor&&e.minor.ticks?r.vals.filter((function(t){return t.minor&&!t.noTick})):[]).concat(e.ticks?r.vals.filter((function(t){return!t.minor&&!t.noTick})):[]),o=r.layer.selectAll(\"path.\"+i).data(a,xt);o.exit().remove(),o.enter().append(\"path\").classed(i,1).classed(\"ticks\",1).classed(\"crisp\",!1!==r.crisp).each((function(t){return f.stroke(n.select(this),t.minor?e.minor.tickcolor:e.tickcolor)})).style(\"stroke-width\",(function(r){return h.crispRound(t,r.minor?e.minor.tickwidth:e.tickwidth,1)+\"px\"})).attr(\"d\",r.path).style(\"display\",null),It(e,[R]),o.attr(\"transform\",r.transFn)},H.drawGrid=function(t,e,r){r=r||{};var i=e._id+\"grid\",a=e.minor&&e.minor.showgrid,o=a?r.vals.filter((function(t){return t.minor})):[],s=e.showgrid?r.vals.filter((function(t){return!t.minor})):[],l=r.counterAxis;if(l&&H.shouldShowZeroLine(t,e,l))for(var c=\"array\"===e.tickmode,u=0;u<s.length;u++){var p=s[u].x;if(c?!p:Math.abs(p)<e.dtick/100){if(s=s.slice(0,u).concat(s.slice(u+1)),!c)break;u--}}e._gw=h.crispRound(t,e.gridwidth,1);for(var d=a?h.crispRound(t,e.minor.gridwidth,1):0,m=r.layer,g=r.minorLayer,v=1;v>=0;v--){var y=v?m:g;if(y){var x=y.selectAll(\"path.\"+i).data(v?s:o,xt);x.exit().remove(),x.enter().append(\"path\").classed(i,1).classed(\"crisp\",!1!==r.crisp),x.attr(\"transform\",r.transFn).attr(\"d\",r.path).each((function(t){return f.stroke(n.select(this),t.minor?e.minor.gridcolor:e.gridcolor||\"#ddd\")})).style(\"stroke-dasharray\",(function(t){return h.dashStyle(t.minor?e.minor.griddash:e.griddash,t.minor?e.minor.gridwidth:e.gridwidth)})).style(\"stroke-width\",(function(t){return(t.minor?d:e._gw)+\"px\"})).style(\"display\",null),\"function\"==typeof r.path&&x.attr(\"d\",r.path)}}It(e,[z,D])},H.drawZeroLine=function(t,e,r){r=r||r;var n=e._id+\"zl\",i=H.shouldShowZeroLine(t,e,r.counterAxis),a=r.layer.selectAll(\"path.\"+n).data(i?[{x:0,id:e._id}]:[]);a.exit().remove(),a.enter().append(\"path\").classed(n,1).classed(\"zl\",1).classed(\"crisp\",!1!==r.crisp).each((function(){r.layer.selectAll(\"path\").sort((function(t,e){return Y(t.id,e.id)}))})),a.attr(\"transform\",r.transFn).attr(\"d\",r.path).call(f.stroke,e.zerolinecolor||f.defaultLine).style(\"stroke-width\",h.crispRound(t,e.zerolinewidth,e._gw||1)+\"px\").style(\"display\",null),It(e,[O])},H.drawLabels=function(t,e,r){r=r||{};var a=t._fullLayout,o=e._id,u=o.charAt(0),f=r.cls||o+\"tick\",p=r.vals.filter((function(t){return t.text})),d=r.labelFns,m=r.secondary?0:e.tickangle,g=(e._prevTickAngles||{})[f],v=r.layer.selectAll(\"g.\"+f).data(e.showticklabels?p:[],xt),y=[];function x(t,a){t.each((function(t){var o=n.select(this),s=o.select(\".text-math-group\"),u=d.anchorFn(t,a),f=r.transFn.call(o.node(),t)+(i(a)&&0!=+a?\" rotate(\"+a+\",\"+d.xFn(t)+\",\"+(d.yFn(t)-t.fontSize/2)+\")\":\"\"),p=c.lineCount(o),m=U*t.fontSize,g=d.heightFn(t,i(a)?+a:0,(p-1)*m);if(g&&(f+=l(0,g)),s.empty()){var v=o.select(\"text\");v.attr({transform:f,\"text-anchor\":u}),v.style(\"opacity\",1),e._adjustTickLabelsOverflow&&e._adjustTickLabelsOverflow()}else{var y=h.bBox(s.node()).width*{end:-.5,start:.5}[u];s.attr(\"transform\",f+l(y,0))}}))}v.enter().append(\"g\").classed(f,1).append(\"text\").attr(\"text-anchor\",\"middle\").each((function(e){var r=n.select(this),i=t._promises.length;r.call(c.positionText,d.xFn(e),d.yFn(e)).call(h.font,e.font,e.fontSize,e.fontColor).text(e.text).call(c.convertToTspans,t),t._promises[i]?y.push(t._promises.pop().then((function(){x(r,m)}))):x(r,m)})),It(e,[F]),v.exit().remove(),r.repositionOnUpdate&&v.each((function(t){n.select(this).select(\"text\").call(c.positionText,d.xFn(t),d.yFn(t))})),e._adjustTickLabelsOverflow=function(){var r=e.ticklabeloverflow;if(r&&\"allow\"!==r){var i=-1!==r.indexOf(\"hide\"),o=\"x\"===e._id.charAt(0),l=0,c=o?t._fullLayout.width:t._fullLayout.height;if(-1!==r.indexOf(\"domain\")){var u=s.simpleMap(e.range,e.r2l);l=e.l2p(u[0])+e._offset,c=e.l2p(u[1])+e._offset}var f=Math.min(l,c),p=Math.max(l,c),d=e.side,m=1/0,g=-1/0;for(var y in v.each((function(t){var 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o=\"tick\"===t.K&&\"text\"===t.L&&\"period\"===e.ticklabelmode,s=a._plots[e._mainSubplot];(t.K===O.K?s.zerolinelayer.selectAll(\".\"+e._id+\"zl\"):t.K===D.K?s.minorGridlayer.selectAll(\".\"+e._id):t.K===z.K?s.gridlayer.selectAll(\".\"+e._id):s[e._id.charAt(0)+\"axislayer\"]).each((function(){var a=n.select(this);t.L&&(a=a.selectAll(t.L)),a.each((function(a){var s=e.l2p(o?yt(a):a.x)+e._offset,l=n.select(this);s<e[\"_visibleLabelMax_\"+r._id]&&s>e[\"_visibleLabelMin_\"+r._id]?l.style(\"display\",\"none\"):\"tick\"!==t.K||i||l.style(\"display\",null)}))}))}))}))},x(v,g+1?g:m);var b=null;e._selections&&(e._selections[f]=v);var _=[function(){return y.length&&Promise.all(y)}];e.automargin&&a._redrawFromAutoMarginCount&&90===g?(b=90,_.push((function(){x(v,g)}))):_.push((function(){if(x(v,m),p.length&&\"x\"===u&&!i(m)&&(\"log\"!==e.type||\"D\"!==String(e.dtick).charAt(0))){b=0;var t,n=0,a=[];if(v.each((function(t){n=Math.max(n,t.fontSize);var 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n=t(\"fast-isnumeric\"),i=t(\"../../registry\"),a=t(\"../../lib\"),o=t(\"../../plot_api/plot_template\"),s=t(\"../array_container_defaults\"),l=t(\"./layout_attributes\"),c=t(\"./tick_value_defaults\"),u=t(\"./tick_mark_defaults\"),f=t(\"./tick_label_defaults\"),h=t(\"./prefix_suffix_defaults\"),p=t(\"./category_order_defaults\"),d=t(\"./line_grid_defaults\"),m=t(\"./set_convert\"),g=t(\"./constants\").WEEKDAY_PATTERN,v=t(\"./constants\").HOUR_PATTERN;function y(t,e,r){function i(r,n){return a.coerce(t,e,l.rangebreaks,r,n)}if(i(\"enabled\")){var o=i(\"bounds\");if(o&&o.length>=2){var s,c,u=\"\";if(2===o.length)for(s=0;s<2;s++)if(c=b(o[s])){u=g;break}var f=i(\"pattern\",u);if(f===g)for(s=0;s<2;s++)(c=b(o[s]))&&(e.bounds[s]=o[s]=c-1);if(f)for(s=0;s<2;s++)switch(c=o[s],f){case g:if(!n(c))return void(e.enabled=!1);if((c=+c)!==Math.floor(c)||c<0||c>=7)return void(e.enabled=!1);e.bounds[s]=o[s]=c;break;case v:if(!n(c))return void(e.enabled=!1);if((c=+c)<0||c>24)return 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a=Pt.dragmode,s=t._fullLayout.dragmode;s!==a&&(Pt.dragmode=s),yt(),pt=t._fullLayout._invScaleX,dt=t._fullLayout._invScaleY,ot||(gt?e.shiftKey?\"pan\"===s?s=\"zoom\":y(s)||(s=\"pan\"):e.ctrlKey&&(s=\"pan\"):s=\"pan\"),x(s)?Pt.minDrag=1:Pt.minDrag=void 0,y(s)?(Pt.xaxes=J,Pt.yaxes=K,A(e,r,n,Pt,s)):(Pt.clickFn=Ot,y(a)&&It(),ot||(\"zoom\"===s?(Pt.moveFn=zt,Pt.doneFn=Rt,Pt.minDrag=1,function(e,r,n){var a=bt.getBoundingClientRect();_t=r-a.left,wt=n-a.top,t._fullLayout._calcInverseTransform(t);var s=i.apply3DTransform(t._fullLayout._invTransform)(_t,wt);_t=s[0],wt=s[1],Tt={l:_t,r:_t,w:0,t:wt,b:wt,h:0},kt=t._hmpixcount?t._hmlumcount/t._hmpixcount:o(t._fullLayout.plot_bgcolor).getLuminance(),Mt=!1,St=\"xy\",Ct=!1,Et=N(mt,kt,Q,$,At=\"M0,0H\"+tt+\"V\"+et+\"H0V0\"),Lt=j(mt,Q,$)}(0,r,n)):\"pan\"===s&&(Pt.moveFn=Ut,Pt.doneFn=Gt))),t._fullLayout._redrag=function(){var e=t._dragdata;if(e&&e.element===bt){var r=t._fullLayout.dragmode;y(r)||(yt(),Yt([0,0,tt,et]),Pt.moveFn(e.dx,e.dy))}}},g.init(Pt);var 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r,n,a,o,s=t._fullLayout,c=s._plots,u=s._subplots.cartesian;if(ut&&l.subplotsRegistry.splom.drag(t),ct)for(r=0;r<u.length;r++)if(a=(n=c[u[r]]).xaxis,o=n.yaxis,n._scene){var f=i.simpleMap(a.range,a.r2l),p=i.simpleMap(o.range,o.r2l);n._scene.update({range:[f[0],p[0],f[1],p[1]]})}if((ut||ct)&&(_(t),w(t)),ft){var d=e[2]/I._length,g=e[3]/O._length;for(r=0;r<u.length;r++){a=(n=c[u[r]]).xaxis,o=n.yaxis;var y,x,b,T,k=(st||nt.isSubplotConstrained)&&!a.fixedrange&&V[a._id],A=(lt||nt.isSubplotConstrained)&&!o.fixedrange&&Z[o._id];if(k?(y=d,b=v||nt.isSubplotConstrained?e[0]:Zt(a,y)):nt.xaHash[a._id]?(y=d,b=e[0]*a._length/I._length):nt.yaHash[a._id]?(y=g,b=\"ns\"===at?-e[1]*a._length/O._length:Zt(a,y,{n:\"top\",s:\"bottom\"}[at])):b=Xt(a,y=Wt(a,d,g)),A?(x=g,T=m||nt.isSubplotConstrained?e[1]:Zt(o,x)):nt.yaHash[o._id]?(x=g,T=e[1]*o._length/O._length):nt.xaHash[o._id]?(x=d,T=\"ew\"===it?-e[0]*o._length/I._length:Zt(o,x,{e:\"right\",w:\"left\"}[it])):T=Xt(o,x=Wt(o,d,g)),y||x){y||(y=1),x||(x=1);var M=a._offset-b/y,S=o._offset-T/x;n.clipRect.call(h.setTranslate,b,T).call(h.setScale,y,x),n.plot.call(h.setTranslate,M,S).call(h.setScale,1/y,1/x),y===n.xScaleFactor&&x===n.yScaleFactor||(h.setPointGroupScale(n.zoomScalePts,y,x),h.setTextPointsScale(n.zoomScaleTxt,y,x)),h.hideOutsideRangePoints(n.clipOnAxisFalseTraces,n),n.xScaleFactor=y,n.yScaleFactor=x}}}}function Wt(t,e,r){return t.fixedrange?0:st&&rt.xaHash[t._id]?e:lt&&(rt.isSubplotConstrained?rt.xaHash:rt.yaHash)[t._id]?r:0}function Xt(t,e){return e?(t.range=t._r.slice(),E(t,e),Zt(t,e)):0}function Zt(t,e,r){return t._length*(1-e)*b[r||t.constraintoward||\"middle\"]}return m.length*v.length!=1&&W(bt,(function(e){if(t._context._scrollZoom.cartesian||t._fullLayout._enablescrollzoom){if(It(),t._transitioningWithDuration)return e.preventDefault(),void e.stopPropagation();yt(),clearTimeout(Bt);var r=-e.deltaY;if(isFinite(r)||(r=e.wheelDelta/10),isFinite(r)){var n,a=Math.exp(-Math.min(Math.max(r,-20),20)/200),o=jt.draglayer.select(\".nsewdrag\").node().getBoundingClientRect(),s=(e.clientX-o.left)/o.width,l=(o.bottom-e.clientY)/o.height;if(st){for(v||(s=.5),n=0;n<J.length;n++)c(J[n],s,a);Vt(\"x\"),Ft[2]*=a,Ft[0]+=Ft[2]*s*(1/a-1)}if(lt){for(m||(l=.5),n=0;n<K.length;n++)c(K[n],l,a);Vt(\"y\"),Ft[3]*=a,Ft[1]+=Ft[3]*(1-l)*(1/a-1)}Yt(Ft),Ht(),t.emit(\"plotly_relayouting\",ht),Bt=setTimeout((function(){t._fullLayout&&(Ft=[0,0,tt,et],Gt())}),Nt),e.preventDefault()}else i.log(\"Did not find wheel motion attributes: \",e)}function c(t,e,r){if(!t.fixedrange){var n=i.simpleMap(t.range,t.r2l),a=n[0]+(n[1]-n[0])*e;t.range=n.map((function(e){return t.l2r(a+(e-a)*r)}))}}})),bt},makeDragger:O,makeRectDragger:z,makeZoombox:N,makeCorners:j,updateZoombox:U,xyCorners:G,transitionZoombox:V,removeZoombox:H,showDoubleClickNotifier:q,attachWheelEventHandler:W}},{\"../../components/color\":366,\"../../components/dragelement\":385,\"../../components/dragelement/helpers\":384,\"../../components/drawing\":388,\"../../components/fx\":406,\"../../constants/alignment\":471,\"../../lib\":503,\"../../lib/clear_gl_canvases\":487,\"../../lib/setcursor\":524,\"../../lib/svg_text_utils\":529,\"../../plot_api/subroutines\":544,\"../../registry\":638,\"../plots\":619,\"./axes\":554,\"./axis_ids\":558,\"./constants\":561,\"./scale_zoom\":574,\"./select\":575,\"@plotly/d3\":58,\"has-passive-events\":229,tinycolor2:312}],564:[function(t,e,r){\"use strict\";var n=t(\"@plotly/d3\"),i=t(\"../../components/fx\"),a=t(\"../../components/dragelement\"),o=t(\"../../lib/setcursor\"),s=t(\"./dragbox\").makeDragBox,l=t(\"./constants\").DRAGGERSIZE;r.initInteractions=function(t){var e=t._fullLayout;if(t._context.staticPlot)n.select(t).selectAll(\".drag\").remove();else if(e._has(\"cartesian\")||e._has(\"splom\")){Object.keys(e._plots||{}).sort((function(t,r){if((e._plots[t].mainplot&&!0)===(e._plots[r].mainplot&&!0)){var n=t.split(\"y\"),i=r.split(\"y\");return n[0]===i[0]?Number(n[1]||1)-Number(i[1]||1):Number(n[0]||1)-Number(i[0]||1)}return e._plots[t].mainplot?1:-1})).forEach((function(r){var n=e._plots[r],o=n.xaxis,c=n.yaxis;if(!n.mainplot){var u=s(t,n,o._offset,c._offset,o._length,c._length,\"ns\",\"ew\");u.onmousemove=function(e){t._fullLayout._rehover=function(){t._fullLayout._hoversubplot===r&&t._fullLayout._plots[r]&&i.hover(t,e,r)},i.hover(t,e,r),t._fullLayout._lasthover=u,t._fullLayout._hoversubplot=r},u.onmouseout=function(e){t._dragging||(t._fullLayout._hoversubplot=null,a.unhover(t,e))},t._context.showAxisDragHandles&&(s(t,n,o._offset-l,c._offset-l,l,l,\"n\",\"w\"),s(t,n,o._offset+o._length,c._offset-l,l,l,\"n\",\"e\"),s(t,n,o._offset-l,c._offset+c._length,l,l,\"s\",\"w\"),s(t,n,o._offset+o._length,c._offset+c._length,l,l,\"s\",\"e\"))}if(t._context.showAxisDragHandles){if(r===o._mainSubplot){var f=o._mainLinePosition;\"top\"===o.side&&(f-=l),s(t,n,o._offset+.1*o._length,f,.8*o._length,l,\"\",\"ew\"),s(t,n,o._offset,f,.1*o._length,l,\"\",\"w\"),s(t,n,o._offset+.9*o._length,f,.1*o._length,l,\"\",\"e\")}if(r===c._mainSubplot){var h=c._mainLinePosition;\"right\"!==c.side&&(h-=l),s(t,n,h,c._offset+.1*c._length,l,.8*c._length,\"ns\",\"\"),s(t,n,h,c._offset+.9*c._length,l,.1*c._length,\"s\",\"\"),s(t,n,h,c._offset,l,.1*c._length,\"n\",\"\")}}}));var o=e._hoverlayer.node();o.onmousemove=function(r){r.target=t._fullLayout._lasthover,i.hover(t,r,e._hoversubplot)},o.onclick=function(e){e.target=t._fullLayout._lasthover,i.click(t,e)},o.onmousedown=function(e){t._fullLayout._lasthover.onmousedown(e)},r.updateFx(t)}},r.updateFx=function(t){var e=t._fullLayout,r=\"pan\"===e.dragmode?\"move\":\"crosshair\";o(e._draggers,r)}},{\"../../components/dragelement\":385,\"../../components/fx\":406,\"../../lib/setcursor\":524,\"./constants\":561,\"./dragbox\":563,\"@plotly/d3\":58}],565:[function(t,e,r){\"use strict\";e.exports={clearOutlineControllers:function(t){var e=t._fullLayout._zoomlayer;e&&e.selectAll(\".outline-controllers\").remove()},clearSelect:function(t){var e=t._fullLayout._zoomlayer;e&&e.selectAll(\".select-outline\").remove(),t._fullLayout._drawing=!1}}},{}],566:[function(t,e,r){\"use strict\";var n=t(\"../../lib\").strTranslate;function i(t,e){switch(t.type){case\"log\":return t.p2d(e);case\"date\":return t.p2r(e,0,t.calendar);default:return t.p2r(e)}}e.exports={p2r:i,r2p:function(t,e){switch(t.type){case\"log\":return t.d2p(e);case\"date\":return t.r2p(e,0,t.calendar);default:return t.r2p(e)}},axValue:function(t){var e=\"y\"===t._id.charAt(0)?1:0;return function(r){return i(t,r[e])}},getTransform:function(t){return n(t.xaxis._offset,t.yaxis._offset)}}},{\"../../lib\":503}],567:[function(t,e,r){\"use strict\";var n=t(\"../../registry\"),i=t(\"../../lib\"),a=t(\"./axis_ids\");e.exports=function(t){return function(e,r){var o=e[t];if(Array.isArray(o))for(var s=n.subplotsRegistry.cartesian,l=s.idRegex,c=r._subplots,u=c.xaxis,f=c.yaxis,h=c.cartesian,p=r._has(\"cartesian\")||r._has(\"gl2d\"),d=0;d<o.length;d++){var m=o[d];if(i.isPlainObject(m)){var g=a.cleanId(m.xref,\"x\",!1),v=a.cleanId(m.yref,\"y\",!1),y=l.x.test(g),x=l.y.test(v);if(y||x){p||i.pushUnique(r._basePlotModules,s);var b=!1;y&&-1===u.indexOf(g)&&(u.push(g),b=!0),x&&-1===f.indexOf(v)&&(f.push(v),b=!0),b&&y&&x&&h.push(g+v)}}}}}},{\"../../lib\":503,\"../../registry\":638,\"./axis_ids\":558}],568:[function(t,e,r){\"use strict\";var n=t(\"@plotly/d3\"),i=t(\"../../registry\"),a=t(\"../../lib\"),o=t(\"../plots\"),s=t(\"../../components/drawing\"),l=t(\"../get_data\").getModuleCalcData,c=t(\"./axis_ids\"),u=t(\"./constants\"),f=t(\"../../constants/xmlns_namespaces\"),h=a.ensureSingle;function p(t,e,r){return a.ensureSingle(t,e,r,(function(t){t.datum(r)}))}function d(t,e,r,a,o){for(var c,f,h,p=u.traceLayerClasses,d=t._fullLayout,m=d._modules,g=[],v=[],y=0;y<m.length;y++){var x=(c=m[y]).name,b=i.modules[x].categories;if(b.svg){var _=c.layerName||x+\"layer\",w=c.plot;h=(f=l(r,w))[0],r=f[1],h.length&&g.push({i:p.indexOf(_),className:_,plotMethod:w,cdModule:h}),b.zoomScale&&v.push(\".\"+_)}}g.sort((function(t,e){return t.i-e.i}));var T=e.plot.selectAll(\"g.mlayer\").data(g,(function(t){return t.className}));if(T.enter().append(\"g\").attr(\"class\",(function(t){return t.className})).classed(\"mlayer\",!0).classed(\"rangeplot\",e.isRangePlot),T.exit().remove(),T.order(),T.each((function(r){var i=n.select(this),l=r.className;r.plotMethod(t,e,r.cdModule,i,a,o),-1===u.clipOnAxisFalseQuery.indexOf(\".\"+l)&&s.setClipUrl(i,e.layerClipId,t)})),d._has(\"scattergl\")&&(c=i.getModule(\"scattergl\"),h=l(r,c)[0],c.plot(t,e,h)),!t._context.staticPlot&&(e._hasClipOnAxisFalse&&(e.clipOnAxisFalseTraces=e.plot.selectAll(u.clipOnAxisFalseQuery.join(\",\")).selectAll(\".trace\")),v.length)){var k=e.plot.selectAll(v.join(\",\")).selectAll(\".trace\");e.zoomScalePts=k.selectAll(\"path.point\"),e.zoomScaleTxt=k.selectAll(\".textpoint\")}}function m(t,e){var r=e.plotgroup,n=e.id,i=u.layerValue2layerClass[e.xaxis.layer],a=u.layerValue2layerClass[e.yaxis.layer],o=t._fullLayout._hasOnlyLargeSploms;if(e.mainplot){var s=e.mainplotinfo,l=s.plotgroup,f=n+\"-x\",d=n+\"-y\";e.minorGridlayer=s.minorGridlayer,e.gridlayer=s.gridlayer,e.zerolinelayer=s.zerolinelayer,h(s.overlinesBelow,\"path\",f),h(s.overlinesBelow,\"path\",d),h(s.overaxesBelow,\"g\",f),h(s.overaxesBelow,\"g\",d),e.plot=h(s.overplot,\"g\",n),h(s.overlinesAbove,\"path\",f),h(s.overlinesAbove,\"path\",d),h(s.overaxesAbove,\"g\",f),h(s.overaxesAbove,\"g\",d),e.xlines=l.select(\".overlines-\"+i).select(\".\"+f),e.ylines=l.select(\".overlines-\"+a).select(\".\"+d),e.xaxislayer=l.select(\".overaxes-\"+i).select(\".\"+f),e.yaxislayer=l.select(\".overaxes-\"+a).select(\".\"+d)}else 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yt=b(\"rangeslider\",\"handleDefaults\"),xt=b(\"rangeselector\",\"handleDefaults\");for(y=0;y<j.length;y++)q=j[y],W=t[q],X=e[q],yt(t,e,q),\"date\"===X.type&&xt(W,X,e,U,X.calendar),K(\"fixedrange\");for(y=0;y<U.length;y++){q=U[y],W=t[q],X=e[q];var bt=e[m(X.anchor)];K(\"fixedrange\",b(\"rangeslider\",\"isVisible\")(bt))}h.handleDefaults(t,e,{axIds:rt.concat(it).sort(d.idSort),axHasImage:P})}},{\"../../components/color\":366,\"../../components/fx/helpers\":402,\"../../components/fx/hovermode_defaults\":405,\"../../lib\":503,\"../../plot_api/plot_template\":543,\"../../registry\":638,\"../layout_attributes\":610,\"./axis_defaults\":556,\"./axis_ids\":558,\"./constants\":561,\"./constraints\":562,\"./layout_attributes\":569,\"./position_defaults\":572,\"./type_defaults\":582}],571:[function(t,e,r){\"use strict\";var n=t(\"tinycolor2\").mix,i=t(\"../../components/color/attributes\"),a=t(\"../../lib\");e.exports=function(t,e,r,o){var s=(o=o||{}).dfltColor;function l(r,n){return a.coerce2(t,e,o.attributes,r,n)}var c=l(\"linecolor\",s),u=l(\"linewidth\");r(\"showline\",o.showLine||!!c||!!u)||(delete e.linecolor,delete e.linewidth);var f=l(\"gridcolor\",n(s,o.bgColor,o.blend||i.lightFraction).toRgbString()),h=l(\"gridwidth\"),p=l(\"griddash\");if(r(\"showgrid\",o.showGrid||!!f||!!h||!!p)||(delete e.gridcolor,delete e.gridwidth,delete e.griddash),o.hasMinor){var d=l(\"minor.gridcolor\",n(e.gridcolor,o.bgColor,67).toRgbString()),m=l(\"minor.gridwidth\",e.gridwidth||1),g=l(\"minor.griddash\",e.griddash||\"solid\");r(\"minor.showgrid\",!!d||!!m||!!g)||(delete e.minor.gridcolor,delete e.minor.gridwidth,delete e.minor.griddash)}if(!o.noZeroLine){var v=l(\"zerolinecolor\",s),y=l(\"zerolinewidth\");r(\"zeroline\",o.showGrid||!!v||!!y)||(delete e.zerolinecolor,delete e.zerolinewidth)}}},{\"../../components/color/attributes\":365,\"../../lib\":503,tinycolor2:312}],572:[function(t,e,r){\"use strict\";var n=t(\"fast-isnumeric\"),i=t(\"../../lib\");e.exports=function(t,e,r,a){var o,s,l,c,u=a.counterAxes||[],f=a.overlayableAxes||[],h=a.letter,p=a.grid;p&&(s=p._domains[h][p._axisMap[e._id]],o=p._anchors[e._id],s&&(l=p[h+\"side\"].split(\" \")[0],c=p.domain[h][\"right\"===l||\"top\"===l?1:0])),s=s||[0,1],o=o||(n(t.position)?\"free\":u[0]||\"free\"),l=l||(\"x\"===h?\"bottom\":\"left\"),c=c||0,\"free\"===i.coerce(t,e,{anchor:{valType:\"enumerated\",values:[\"free\"].concat(u),dflt:o}},\"anchor\")&&r(\"position\",c),i.coerce(t,e,{side:{valType:\"enumerated\",values:\"x\"===h?[\"bottom\",\"top\"]:[\"left\",\"right\"],dflt:l}},\"side\");var d=!1;if(f.length&&(d=i.coerce(t,e,{overlaying:{valType:\"enumerated\",values:[!1].concat(f),dflt:!1}},\"overlaying\")),!d){var m=r(\"domain\",s);m[0]>m[1]-1/4096&&(e.domain=s),i.noneOrAll(t.domain,e.domain,s)}return r(\"layer\"),e}},{\"../../lib\":503,\"fast-isnumeric\":190}],573:[function(t,e,r){\"use strict\";var n=t(\"./show_dflt\");e.exports=function(t,e,r,i,a){a||(a={});var o=a.tickSuffixDflt,s=n(t);r(\"tickprefix\")&&r(\"showtickprefix\",s),r(\"ticksuffix\",o)&&r(\"showticksuffix\",s)}},{\"./show_dflt\":577}],574:[function(t,e,r){\"use strict\";var n=t(\"../../constants/alignment\").FROM_BL;e.exports=function(t,e,r){void 0===r&&(r=n[t.constraintoward||\"center\"]);var i=[t.r2l(t.range[0]),t.r2l(t.range[1])],a=i[0]+(i[1]-i[0])*r;t.range=t._input.range=[t.l2r(a+(i[0]-a)*e),t.l2r(a+(i[1]-a)*e)],t.setScale()}},{\"../../constants/alignment\":471}],575:[function(t,e,r){\"use strict\";var n=t(\"polybooljs\"),i=t(\"../../registry\"),a=t(\"../../components/drawing\").dashStyle,o=t(\"../../components/color\"),s=t(\"../../components/fx\"),l=t(\"../../components/fx/helpers\").makeEventData,c=t(\"../../components/dragelement/helpers\"),u=c.freeMode,f=c.rectMode,h=c.drawMode,p=c.openMode,d=c.selectMode,m=t(\"../../components/shapes/draw_newshape/display_outlines\"),g=t(\"../../components/shapes/draw_newshape/helpers\").handleEllipse,v=t(\"../../components/shapes/draw_newshape/newshapes\"),y=t(\"../../lib\"),x=t(\"../../lib/polygon\"),b=t(\"../../lib/throttle\"),_=t(\"./axis_ids\").getFromId,w=t(\"../../lib/clear_gl_canvases\"),T=t(\"../../plot_api/subroutines\").redrawReglTraces,k=t(\"./constants\"),A=k.MINSELECT,M=x.filter,S=x.tester,E=t(\"./handle_outline\").clearSelect,L=t(\"./helpers\"),C=L.p2r,P=L.axValue,I=L.getTransform;function O(t,e,r,n,i,a,o){var s,l,c,u,f,h,d,g,v,y=e._hoverdata,x=e._fullLayout.clickmode.indexOf(\"event\")>-1,b=[];if(function(t){return 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e=[],r=z(t[0])?0:t[0][0][0],n=r,i=z(t[0])?0:t[0][0][1],a=i,o=0;o<t.length;o++)if(z(t[o]))e.push(D(t[o]));else{var s=x.tester(t[o]);s.subtract=t[o].subtract,e.push(s),r=Math.min(r,s.xmin),n=Math.max(n,s.xmax),i=Math.min(i,s.ymin),a=Math.max(a,s.ymax)}return{xmin:r,xmax:n,ymin:i,ymax:a,pts:[],contains:function(t,r,n,i){for(var a=!1,o=0;o<e.length;o++)e[o].contains(t,r,n,i)&&(a=!1===e[o].subtract);return a},isRect:!1,degenerate:!1}}function F(t,e,r){e._fullLayout._drawing=!1;var n=e._fullLayout,i=r.plotinfo,a=r.dragmode,o=n._lastSelectedSubplot&&n._lastSelectedSubplot===i.id,s=(t.shiftKey||t.altKey)&&!(h(a)&&p(a));o&&s&&i.selection&&i.selection.selectionDefs&&!r.selectionDefs?(r.selectionDefs=i.selection.selectionDefs,r.mergedPolygons=i.selection.mergedPolygons):s&&i.selection||B(r),o||(E(e),n._lastSelectedSubplot=i.id)}function B(t){var e=t.dragmode,r=t.plotinfo,n=t.gd;if(n._fullLayout._activeShapeIndex>=0&&n._fullLayout._deactivateShape(n),h(e)){var 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r=this.bounds,n=(e.framewidth||0)/2,i=r[0][0]-n,a=r[0][1]-n,o=r[1][0]-i+n,s=r[1][1]-a+n;h.setRect(this.clipRect,i,a,o,s),this.bgRect.call(h.setRect,i,a,o,s).call(f.fill,e.bgcolor),this.xaxis._offset=i,this.xaxis._length=o,this.yaxis._offset=a,this.yaxis._length=s},S.updateFx=function(t,e){var r=this,i=r.graphDiv,a=r.bgRect,o=t.dragmode,s=t.clickmode;if(!r.isStatic){var u;\"select\"===o?u=function(t,e){(t.range={})[r.id]=[h([e.xmin,e.ymin]),h([e.xmax,e.ymax])]}:\"lasso\"===o&&(u=function(t,e,n){(t.lassoPoints={})[r.id]=n.filtered.map(h)});var f={element:r.bgRect.node(),gd:i,plotinfo:{id:r.id,xaxis:r.xaxis,yaxis:r.yaxis,fillRangeItems:u},xaxes:[r.xaxis],yaxes:[r.yaxis],subplot:r.id,clickFn:function(t){2===t&&x(i)}};\"pan\"===o?(a.node().onmousedown=null,a.call(_(r,e)),a.on(\"dblclick.zoom\",(function(){var t=r.viewInitial,e={};for(var n in 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t=this,e=t.graphDiv,r=e._fullLayout,i=\"clip\"+r._uid+t.id;t.clipDef=r._clips.append(\"clipPath\").attr(\"id\",i),t.clipRect=t.clipDef.append(\"rect\"),t.framework=n.select(t.container).append(\"g\").attr(\"class\",\"geo \"+t.id).call(h.setClipUrl,i,e),t.project=function(e){var r=t.projection(e);return r?[r[0]-t.xaxis._offset,r[1]-t.yaxis._offset]:[null,null]},t.xaxis={_id:\"x\",c2p:function(e){return t.project(e)[0]}},t.yaxis={_id:\"y\",c2p:function(e){return t.project(e)[1]}},t.mockAxis={type:\"linear\",showexponent:\"all\",exponentformat:\"B\"},m.setConvert(t.mockAxis,r)},S.saveViewInitial=function(t){var 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e=t._fullLayout,r=t.calcdata,i=e._subplots.geo,s=0;s<i.length;s++){var l=i[s],c=n(r,o,l),u=e[l]._subplot;u||(u=a({id:l,graphDiv:t,container:e._geolayer.node(),topojsonURL:t._context.topojsonURL,staticPlot:t._context.staticPlot}),e[l]._subplot=u),u.plot(c,e,t._promises)}},updateFx:function(t){for(var e=t._fullLayout,r=e._subplots.geo,n=0;n<r.length;n++){var i=e[r[n]];i._subplot.updateFx(e,i)}},clean:function(t,e,r,n){for(var i=n._subplots.geo||[],a=0;a<i.length;a++){var o=i[a],s=n[o]._subplot;!e[o]&&s&&(s.framework.remove(),s.clipDef.remove())}}}},{\"../../lib\":503,\"../../plots/get_data\":593,\"./geo\":588,\"./layout_attributes\":590,\"./layout_defaults\":591}],590:[function(t,e,r){\"use strict\";var n=t(\"../../components/color/attributes\"),i=t(\"../domain\").attributes,a=t(\"../../components/drawing/attributes\").dash,o=t(\"./constants\"),s=t(\"../../plot_api/edit_types\").overrideAll,l=t(\"../../lib/sort_object_keys\"),c={range:{valType:\"info_array\",items:[{valType:\"number\"},{valType:\"number\"}]},showgrid:{valType:\"boolean\",dflt:!1},tick0:{valType:\"number\",dflt:0},dtick:{valType:\"number\"},gridcolor:{valType:\"color\",dflt:n.lightLine},gridwidth:{valType:\"number\",min:0,dflt:1},griddash:a};(e.exports=s({domain:i({name:\"geo\"},{}),fitbounds:{valType:\"enumerated\",values:[!1,\"locations\",\"geojson\"],dflt:!1,editType:\"plot\"},resolution:{valType:\"enumerated\",values:[110,50],dflt:110,coerceNumber:!0},scope:{valType:\"enumerated\",values:l(o.scopeDefaults),dflt:\"world\"},projection:{type:{valType:\"enumerated\",values:l(o.projNames)},rotation:{lon:{valType:\"number\"},lat:{valType:\"number\"},roll:{valType:\"number\"}},tilt:{valType:\"number\",dflt:0},distance:{valType:\"number\",min:1.001,dflt:2},parallels:{valType:\"info_array\",items:[{valType:\"number\"},{valType:\"number\"}]},scale:{valType:\"number\",min:0,dflt:1}},center:{lon:{valType:\"number\"},lat:{valType:\"number\"}},visible:{valType:\"boolean\",dflt:!0},showcoastlines:{valType:\"boolean\"},coastlinecolor:{valType:\"color\",dflt:n.defaultLine},coastlinewidth:{valType:\"number\",min:0,dflt:1},showland:{valType:\"boolean\",dflt:!1},landcolor:{valType:\"color\",dflt:o.landColor},showocean:{valType:\"boolean\",dflt:!1},oceancolor:{valType:\"color\",dflt:o.waterColor},showlakes:{valType:\"boolean\",dflt:!1},lakecolor:{valType:\"color\",dflt:o.waterColor},showrivers:{valType:\"boolean\",dflt:!1},rivercolor:{valType:\"color\",dflt:o.waterColor},riverwidth:{valType:\"number\",min:0,dflt:1},showcountries:{valType:\"boolean\"},countrycolor:{valType:\"color\",dflt:n.defaultLine},countrywidth:{valType:\"number\",min:0,dflt:1},showsubunits:{valType:\"boolean\"},subunitcolor:{valType:\"color\",dflt:n.defaultLine},subunitwidth:{valType:\"number\",min:0,dflt:1},showframe:{valType:\"boolean\"},framecolor:{valType:\"color\",dflt:n.defaultLine},framewidth:{valType:\"number\",min:0,dflt:1},bgcolor:{valType:\"color\",dflt:n.background},lonaxis:c,lataxis:c},\"plot\",\"from-root\")).uirevision={valType:\"any\",editType:\"none\"}},{\"../../components/color/attributes\":365,\"../../components/drawing/attributes\":387,\"../../lib/sort_object_keys\":526,\"../../plot_api/edit_types\":536,\"../domain\":584,\"./constants\":587}],591:[function(t,e,r){\"use 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d=(e=s[h]).charAt(0);for(n=(r=t[this.scene[e]._name]).title.text===this.scene.fullLayout._dfltTitle[d]?\"\":r.title.text,p=0;p<=2;p+=2)this.labelEnable[h+p]=!1,this.labels[h+p]=n,this.labelColor[h+p]=i(r.title.font.color),this.labelFont[h+p]=r.title.font.family,this.labelSize[h+p]=r.title.font.size,this.labelPad[h+p]=this.getLabelPad(e,r),this.tickEnable[h+p]=!1,this.tickColor[h+p]=i((r.tickfont||{}).color),this.tickAngle[h+p]=\"auto\"===r.tickangle?0:Math.PI*-r.tickangle/180,this.tickPad[h+p]=this.getTickPad(r),this.tickMarkLength[h+p]=0,this.tickMarkWidth[h+p]=r.tickwidth||0,this.tickMarkColor[h+p]=i(r.tickcolor),this.borderLineEnable[h+p]=!1,this.borderLineColor[h+p]=i(r.linecolor),this.borderLineWidth[h+p]=r.linewidth||0;c=this.hasSharedAxis(r),o=this.hasAxisInDfltPos(e,r)&&!c,l=this.hasAxisInAltrPos(e,r)&&!c,a=r.mirror||!1,u=c?-1!==String(a).indexOf(\"all\"):!!a,f=c?\"allticks\"===a:-1!==String(a).indexOf(\"ticks\"),o?this.labelEnable[h]=!0:l&&(this.labelEnable[h+2]=!0),o?this.tickEnable[h]=r.showticklabels:l&&(this.tickEnable[h+2]=r.showticklabels),(o||u)&&(this.borderLineEnable[h]=r.showline),(l||u)&&(this.borderLineEnable[h+2]=r.showline),(o||f)&&(this.tickMarkLength[h]=this.getTickMarkLength(r)),(l||f)&&(this.tickMarkLength[h+2]=this.getTickMarkLength(r)),this.gridLineEnable[h]=r.showgrid,this.gridLineColor[h]=i(r.gridcolor),this.gridLineWidth[h]=r.gridwidth,this.zeroLineEnable[h]=r.zeroline,this.zeroLineColor[h]=i(r.zerolinecolor),this.zeroLineWidth[h]=r.zerolinewidth}},o.hasSharedAxis=function(t){var 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n=t(\"../../plot_api/edit_types\").overrideAll,i=t(\"./scene2d\"),a=t(\"../layout_attributes\"),o=t(\"../../constants/xmlns_namespaces\"),s=t(\"../cartesian/constants\"),l=t(\"../cartesian\"),c=t(\"../../components/fx/layout_attributes\"),u=t(\"../get_data\").getSubplotData;r.name=\"gl2d\",r.attr=[\"xaxis\",\"yaxis\"],r.idRoot=[\"x\",\"y\"],r.idRegex=s.idRegex,r.attrRegex=s.attrRegex,r.attributes=t(\"../cartesian/attributes\"),r.supplyLayoutDefaults=function(t,e,r){e._has(\"cartesian\")||l.supplyLayoutDefaults(t,e,r)},r.layoutAttrOverrides=n(l.layoutAttributes,\"plot\",\"from-root\"),r.baseLayoutAttrOverrides=n({plot_bgcolor:a.plot_bgcolor,hoverlabel:c.hoverlabel},\"plot\",\"nested\"),r.plot=function(t){for(var e=t._fullLayout,r=t._fullData,n=e._subplots.gl2d,a=0;a<n.length;a++){var o=n[a],s=e._plots[o],l=u(r,\"gl2d\",o),c=s._scene2d;void 0===c&&(c=new i({id:o,graphDiv:t,container:t.querySelector(\".gl-container\"),staticPlot:t._context.staticPlot,plotGlPixelRatio:t._context.plotGlPixelRatio},e),s._scene2d=c),c.plot(l,t.calcdata,e,t.layout)}},r.clean=function(t,e,r,n){for(var i=n._subplots.gl2d||[],a=0;a<i.length;a++){var o=i[a],s=n._plots[o];if(s._scene2d){var c=u(t,\"gl2d\",o);0===c.length&&(s._scene2d.destroy(),delete n._plots[o])}}l.clean.apply(this,arguments)},r.drawFramework=function(t){t._context.staticPlot||l.drawFramework(t)},r.toSVG=function(t){for(var e=t._fullLayout,r=e._subplots.gl2d,n=0;n<r.length;n++){var i=e._plots[r[n]]._scene2d,a=i.toImage(\"png\");e._glimages.append(\"svg:image\").attr({xmlns:o.svg,\"xlink:href\":a,x:0,y:0,width:\"100%\",height:\"100%\",preserveAspectRatio:\"none\"}),i.destroy()}},r.updateFx=function(t){for(var e=t._fullLayout,r=e._subplots.gl2d,n=0;n<r.length;n++){e._plots[r[n]]._scene2d.updateFx(e.dragmode)}}},{\"../../components/fx/layout_attributes\":407,\"../../constants/xmlns_namespaces\":480,\"../../plot_api/edit_types\":536,\"../cartesian\":568,\"../cartesian/attributes\":552,\"../cartesian/constants\":561,\"../get_data\":593,\"../layout_attributes\":610,\"./scene2d\":597}],597:[function(t,e,r){\"use strict\";var n,i,a=t(\"../../registry\"),o=t(\"../../plots/cartesian/axes\"),s=t(\"../../components/fx\"),l=t(\"../../../stackgl_modules\").gl_plot2d,c=t(\"../../../stackgl_modules\").gl_spikes2d,u=t(\"../../../stackgl_modules\").gl_select_box,f=t(\"webgl-context\"),h=t(\"./convert\"),p=t(\"./camera\"),d=t(\"../../lib/show_no_webgl_msg\"),m=t(\"../cartesian/constraints\"),g=m.enforce,v=m.clean,y=t(\"../cartesian/autorange\").doAutoRange,x=t(\"../../components/dragelement/helpers\"),b=x.drawMode,_=x.selectMode,w=[\"xaxis\",\"yaxis\"],T=t(\"../cartesian/constants\").SUBPLOT_PATTERN;function k(t,e){this.container=t.container,this.graphDiv=t.graphDiv,this.pixelRatio=t.plotGlPixelRatio||window.devicePixelRatio,this.id=t.id,this.staticPlot=!!t.staticPlot,this.scrollZoom=this.graphDiv._context._scrollZoom.cartesian,this.fullData=null,this.updateRefs(e),this.makeFramework(),this.stopped||(this.glplotOptions=h(this),this.glplotOptions.merge(e),this.glplot=l(this.glplotOptions),this.camera=p(this),this.traces={},this.spikes=c(this.glplot),this.selectBox=u(this.glplot,{innerFill:!1,outerFill:!0}),this.lastButtonState=0,this.pickResult=null,this.isMouseOver=!0,this.stopped=!1,this.redraw=this.draw.bind(this),this.redraw())}e.exports=k;var A=k.prototype;A.makeFramework=function(){if(this.staticPlot){if(!(i||(n=document.createElement(\"canvas\"),i=f({canvas:n,preserveDrawingBuffer:!1,premultipliedAlpha:!0,antialias:!0}))))throw new Error(\"Error creating static canvas/context for image server\");this.canvas=n,this.gl=i}else{var t=this.container.querySelector(\".gl-canvas-focus\"),e=f({canvas:t,preserveDrawingBuffer:!0,premultipliedAlpha:!0});if(!e)return d(this),void(this.stopped=!0);this.canvas=t,this.gl=e}var r=this.canvas;r.style.width=\"100%\",r.style.height=\"100%\",r.style.position=\"absolute\",r.style.top=\"0px\",r.style.left=\"0px\",r.style[\"pointer-events\"]=\"none\",this.updateSize(r);var a=this.svgContainer=document.createElementNS(\"http://www.w3.org/2000/svg\",\"svg\");a.style.position=\"absolute\",a.style.top=a.style.left=\"0px\",a.style.width=a.style.height=\"100%\",a.style[\"z-index\"]=20,a.style[\"pointer-events\"]=\"none\";var o=this.mouseContainer=document.createElement(\"div\");o.style.position=\"absolute\",o.style[\"pointer-events\"]=\"auto\",this.pickCanvas=this.container.querySelector(\".gl-canvas-pick\");var s=this.container;s.appendChild(a),s.appendChild(o);var l=this;o.addEventListener(\"mouseout\",(function(){l.isMouseOver=!1,l.unhover()})),o.addEventListener(\"mouseover\",(function(){l.isMouseOver=!0}))},A.toImage=function(t){t||(t=\"png\"),this.stopped=!0,this.staticPlot&&this.container.appendChild(n),this.updateSize(this.canvas);var e=this.glplot.gl,r=e.drawingBufferWidth,i=e.drawingBufferHeight;e.clearColor(1,1,1,0),e.clear(e.COLOR_BUFFER_BIT|e.DEPTH_BUFFER_BIT),this.glplot.setDirty(),this.glplot.draw(),e.bindFramebuffer(e.FRAMEBUFFER,null);var a=new Uint8Array(r*i*4);e.readPixels(0,0,r,i,e.RGBA,e.UNSIGNED_BYTE,a);for(var o=0,s=i-1;o<s;++o,--s)for(var l=0;l<r;++l)for(var c=0;c<4;++c){var u=a[4*(r*o+l)+c];a[4*(r*o+l)+c]=a[4*(r*s+l)+c],a[4*(r*s+l)+c]=u}var f=document.createElement(\"canvas\");f.width=r,f.height=i;var h,p=f.getContext(\"2d\",{willReadFrequently:!0}),d=p.createImageData(r,i);switch(d.data.set(a),p.putImageData(d,0,0),t){case\"jpeg\":h=f.toDataURL(\"image/jpeg\");break;case\"webp\":h=f.toDataURL(\"image/webp\");break;default:h=f.toDataURL(\"image/png\")}return this.staticPlot&&this.container.removeChild(n),h},A.updateSize=function(t){t||(t=this.canvas);var e=this.pixelRatio,r=this.fullLayout,n=r.width,i=r.height,a=0|Math.ceil(e*n),o=0|Math.ceil(e*i);return t.width===a&&t.height===o||(t.width=a,t.height=o),t},A.computeTickMarks=function(){this.xaxis.setScale(),this.yaxis.setScale();for(var t=[o.calcTicks(this.xaxis),o.calcTicks(this.yaxis)],e=0;e<2;++e)for(var r=0;r<t[e].length;++r)t[e][r].text=t[e][r].text+\"\";return t},A.updateRefs=function(t){this.fullLayout=t;var e=this.id.match(T),r=\"xaxis\"+e[1],n=\"yaxis\"+e[2];this.xaxis=this.fullLayout[r],this.yaxis=this.fullLayout[n]},A.relayoutCallback=function(){var t=this.graphDiv,e=this.xaxis,r=this.yaxis,n=t.layout,i={},o=i[e._name+\".range\"]=e.range.slice(),s=i[r._name+\".range\"]=r.range.slice();i[e._name+\".autorange\"]=e.autorange,i[r._name+\".autorange\"]=r.autorange,a.call(\"_storeDirectGUIEdit\",t.layout,t._fullLayout._preGUI,i);var l=n[e._name];l.range=o,l.autorange=e.autorange;var c=n[r._name];c.range=s,c.autorange=r.autorange,i.lastInputTime=this.camera.lastInputTime,t.emit(\"plotly_relayout\",i)},A.cameraChanged=function(){var t=this.camera;this.glplot.setDataBox(this.calcDataBox());var e=this.computeTickMarks();(function(t,e){for(var r=0;r<2;++r){var n=t[r],i=e[r];if(n.length!==i.length)return!0;for(var a=0;a<n.length;++a)if(n[a].x!==i[a].x)return!0}return!1})(e,this.glplotOptions.ticks)&&(this.glplotOptions.ticks=e,this.glplotOptions.dataBox=t.dataBox,this.glplot.update(this.glplotOptions),this.handleAnnotations())},A.handleAnnotations=function(){for(var t=this.graphDiv,e=this.fullLayout.annotations,r=0;r<e.length;r++){var n=e[r];n.xref===this.xaxis._id&&n.yref===this.yaxis._id&&a.getComponentMethod(\"annotations\",\"drawOne\")(t,r)}},A.destroy=function(){if(this.glplot){var t=this.traces;t&&Object.keys(t).map((function(e){t[e].dispose(),delete t[e]})),this.glplot.dispose(),this.container.removeChild(this.svgContainer),this.container.removeChild(this.mouseContainer),this.fullData=null,this.glplot=null,this.stopped=!0,this.camera.mouseListener.enabled=!1,this.mouseContainer.removeEventListener(\"wheel\",this.camera.wheelListener),this.camera=null}},A.plot=function(t,e,r){var n=this.glplot;this.updateRefs(r),this.xaxis.clearCalc(),this.yaxis.clearCalc(),this.updateTraces(t,e),this.updateFx(r.dragmode);var i=r.width,a=r.height;this.updateSize(this.canvas);var o=this.glplotOptions;o.merge(r),o.screenBox=[0,0,i,a];var s={_fullLayout:{_axisConstraintGroups:r._axisConstraintGroups,xaxis:this.xaxis,yaxis:this.yaxis,_size:r._size}};v(s,this.xaxis),v(s,this.yaxis);var l,c,u=r._size,f=this.xaxis.domain,h=this.yaxis.domain;for(o.viewBox=[u.l+f[0]*u.w,u.b+h[0]*u.h,i-u.r-(1-f[1])*u.w,a-u.t-(1-h[1])*u.h],this.mouseContainer.style.width=u.w*(f[1]-f[0])+\"px\",this.mouseContainer.style.height=u.h*(h[1]-h[0])+\"px\",this.mouseContainer.height=u.h*(h[1]-h[0]),this.mouseContainer.style.left=u.l+f[0]*u.w+\"px\",this.mouseContainer.style.top=u.t+(1-h[1])*u.h+\"px\",c=0;c<2;++c)(l=this[w[c]])._length=o.viewBox[c+2]-o.viewBox[c],y(this.graphDiv,l),l.setScale();g(s),o.ticks=this.computeTickMarks(),o.dataBox=this.calcDataBox(),o.merge(r),n.update(o),this.glplot.draw()},A.calcDataBox=function(){var t=this.xaxis,e=this.yaxis,r=t.range,n=e.range,i=t.r2l,a=e.r2l;return[i(r[0]),a(n[0]),i(r[1]),a(n[1])]},A.setRanges=function(t){var e=this.xaxis,r=this.yaxis,n=e.l2r,i=r.l2r;e.range=[n(t[0]),n(t[2])],r.range=[i(t[1]),i(t[3])]},A.updateTraces=function(t,e){var r,n,i,a=Object.keys(this.traces);this.fullData=t;t:for(r=0;r<a.length;r++){var o=a[r],s=this.traces[o];for(n=0;n<t.length;n++)if((i=t[n]).uid===o&&i.type===s.type)continue t;s.dispose(),delete this.traces[o]}for(r=0;r<t.length;r++){i=t[r];var l=e[r],c=this.traces[i.uid];c?c.update(i,l):(c=i._module.plot(this,i,l),this.traces[i.uid]=c)}this.glplot.objects.sort((function(t,e){return t._trace.index-e._trace.index}))},A.updateFx=function(t){_(t)||b(t)?(this.pickCanvas.style[\"pointer-events\"]=\"none\",this.mouseContainer.style[\"pointer-events\"]=\"none\"):(this.pickCanvas.style[\"pointer-events\"]=\"auto\",this.mouseContainer.style[\"pointer-events\"]=\"auto\"),this.mouseContainer.style.cursor=\"pan\"===t?\"move\":\"zoom\"===t?\"crosshair\":null},A.emitPointAction=function(t,e){for(var r,n=t.trace.uid,i=t.pointIndex,a=0;a<this.fullData.length;a++)this.fullData[a].uid===n&&(r=this.fullData[a]);var o={x:t.traceCoord[0],y:t.traceCoord[1],curveNumber:r.index,pointNumber:i,data:r._input,fullData:this.fullData,xaxis:this.xaxis,yaxis:this.yaxis};s.appendArrayPointValue(o,r,i),this.graphDiv.emit(e,{points:[o]})},A.draw=function(){if(!this.stopped){requestAnimationFrame(this.redraw);var t=this.glplot,e=this.camera,r=e.mouseListener,n=1===this.lastButtonState&&0===r.buttons,i=this.fullLayout;this.lastButtonState=r.buttons,this.cameraChanged();var a,o=r.x*t.pixelRatio,l=this.canvas.height-t.pixelRatio*r.y;if(e.boxEnabled&&\"zoom\"===i.dragmode){this.selectBox.enabled=!0;for(var c=this.selectBox.selectBox=[Math.min(e.boxStart[0],e.boxEnd[0]),Math.min(e.boxStart[1],e.boxEnd[1]),Math.max(e.boxStart[0],e.boxEnd[0]),Math.max(e.boxStart[1],e.boxEnd[1])],u=0;u<2;u++)e.boxStart[u]===e.boxEnd[u]&&(c[u]=t.dataBox[u],c[u+2]=t.dataBox[u+2]);t.setDirty()}else if(!e.panning&&this.isMouseOver){this.selectBox.enabled=!1;var f=i._size,h=this.xaxis.domain,p=this.yaxis.domain,d=(a=t.pick(o/t.pixelRatio+f.l+h[0]*f.w,l/t.pixelRatio-(f.t+(1-p[1])*f.h)))&&a.object._trace.handlePick(a);if(d&&n&&this.emitPointAction(d,\"plotly_click\"),a&&\"skip\"!==a.object._trace.hoverinfo&&i.hovermode&&d&&(!this.lastPickResult||this.lastPickResult.traceUid!==d.trace.uid||this.lastPickResult.dataCoord[0]!==d.dataCoord[0]||this.lastPickResult.dataCoord[1]!==d.dataCoord[1])){var m=d;this.lastPickResult={traceUid:d.trace?d.trace.uid:null,dataCoord:d.dataCoord.slice()},this.spikes.update({center:a.dataCoord}),m.screenCoord=[((t.viewBox[2]-t.viewBox[0])*(a.dataCoord[0]-t.dataBox[0])/(t.dataBox[2]-t.dataBox[0])+t.viewBox[0])/t.pixelRatio,(this.canvas.height-(t.viewBox[3]-t.viewBox[1])*(a.dataCoord[1]-t.dataBox[1])/(t.dataBox[3]-t.dataBox[1])-t.viewBox[1])/t.pixelRatio],this.emitPointAction(d,\"plotly_hover\");var g=this.fullData[m.trace.index]||{},v=m.pointIndex,y=s.castHoverinfo(g,i,v);if(y&&\"all\"!==y){var x=y.split(\"+\");-1===x.indexOf(\"x\")&&(m.traceCoord[0]=void 0),-1===x.indexOf(\"y\")&&(m.traceCoord[1]=void 0),-1===x.indexOf(\"z\")&&(m.traceCoord[2]=void 0),-1===x.indexOf(\"text\")&&(m.textLabel=void 0),-1===x.indexOf(\"name\")&&(m.name=void 0)}s.loneHover({x:m.screenCoord[0],y:m.screenCoord[1],xLabel:this.hoverFormatter(\"xaxis\",m.traceCoord[0]),yLabel:this.hoverFormatter(\"yaxis\",m.traceCoord[1]),zLabel:m.traceCoord[2],text:m.textLabel,name:m.name,color:s.castHoverOption(g,v,\"bgcolor\")||m.color,borderColor:s.castHoverOption(g,v,\"bordercolor\"),fontFamily:s.castHoverOption(g,v,\"font.family\"),fontSize:s.castHoverOption(g,v,\"font.size\"),fontColor:s.castHoverOption(g,v,\"font.color\"),nameLength:s.castHoverOption(g,v,\"namelength\"),textAlign:s.castHoverOption(g,v,\"align\")},{container:this.svgContainer,gd:this.graphDiv})}}a||this.unhover(),t.draw()}},A.unhover=function(){this.lastPickResult&&(this.spikes.update({}),this.lastPickResult=null,this.graphDiv.emit(\"plotly_unhover\"),s.loneUnhover(this.svgContainer))},A.hoverFormatter=function(t,e){if(void 0!==e){var r=this[t];return o.tickText(r,r.c2l(e),\"hover\").text}}},{\"../../../stackgl_modules\":1124,\"../../components/dragelement/helpers\":384,\"../../components/fx\":406,\"../../lib/show_no_webgl_msg\":525,\"../../plots/cartesian/axes\":554,\"../../registry\":638,\"../cartesian/autorange\":553,\"../cartesian/constants\":561,\"../cartesian/constraints\":562,\"./camera\":594,\"./convert\":595,\"webgl-context\":331}],598:[function(t,e,r){\"use strict\";var n=t(\"../../plot_api/edit_types\").overrideAll,i=t(\"../../components/fx/layout_attributes\"),a=t(\"./scene\"),o=t(\"../get_data\").getSubplotData,s=t(\"../../lib\"),l=t(\"../../constants/xmlns_namespaces\");r.name=\"gl3d\",r.attr=\"scene\",r.idRoot=\"scene\",r.idRegex=r.attrRegex=s.counterRegex(\"scene\"),r.attributes=t(\"./layout/attributes\"),r.layoutAttributes=t(\"./layout/layout_attributes\"),r.baseLayoutAttrOverrides=n({hoverlabel:i.hoverlabel},\"plot\",\"nested\"),r.supplyLayoutDefaults=t(\"./layout/defaults\"),r.plot=function(t){for(var e=t._fullLayout,r=t._fullData,n=e._subplots.gl3d,i=0;i<n.length;i++){var s=n[i],l=o(r,\"gl3d\",s),c=e[s],u=c.camera,f=c._scene;f||(f=new a({id:s,graphDiv:t,container:t.querySelector(\".gl-container\"),staticPlot:t._context.staticPlot,plotGlPixelRatio:t._context.plotGlPixelRatio,camera:u},e),c._scene=f),f.viewInitial||(f.viewInitial={up:{x:u.up.x,y:u.up.y,z:u.up.z},eye:{x:u.eye.x,y:u.eye.y,z:u.eye.z},center:{x:u.center.x,y:u.center.y,z:u.center.z}}),f.plot(l,e,t.layout)}},r.clean=function(t,e,r,n){for(var i=n._subplots.gl3d||[],a=0;a<i.length;a++){var o=i[a];!e[o]&&n[o]._scene&&(n[o]._scene.destroy(),n._infolayer&&n._infolayer.selectAll(\".annotation-\"+o).remove())}},r.toSVG=function(t){for(var e=t._fullLayout,r=e._subplots.gl3d,n=e._size,i=0;i<r.length;i++){var a=e[r[i]],o=a.domain,s=a._scene,c=s.toImage(\"png\");e._glimages.append(\"svg:image\").attr({xmlns:l.svg,\"xlink:href\":c,x:n.l+n.w*o.x[0],y:n.t+n.h*(1-o.y[1]),width:n.w*(o.x[1]-o.x[0]),height:n.h*(o.y[1]-o.y[0]),preserveAspectRatio:\"none\"}),s.destroy()}},r.cleanId=function(t){if(t.match(/^scene[0-9]*$/)){var e=t.substr(5);return\"1\"===e&&(e=\"\"),\"scene\"+e}},r.updateFx=function(t){for(var e=t._fullLayout,r=e._subplots.gl3d,n=0;n<r.length;n++){e[r[n]]._scene.updateFx(e.dragmode,e.hovermode)}}},{\"../../components/fx/layout_attributes\":407,\"../../constants/xmlns_namespaces\":480,\"../../lib\":503,\"../../plot_api/edit_types\":536,\"../get_data\":593,\"./layout/attributes\":599,\"./layout/defaults\":603,\"./layout/layout_attributes\":604,\"./scene\":608}],599:[function(t,e,r){\"use strict\";e.exports={scene:{valType:\"subplotid\",dflt:\"scene\",editType:\"calc+clearAxisTypes\"}}},{}],600:[function(t,e,r){\"use strict\";var n=t(\"../../../components/color\"),i=t(\"../../cartesian/layout_attributes\"),a=t(\"../../../lib/extend\").extendFlat,o=t(\"../../../plot_api/edit_types\").overrideAll;e.exports=o({visible:i.visible,showspikes:{valType:\"boolean\",dflt:!0},spikesides:{valType:\"boolean\",dflt:!0},spikethickness:{valType:\"number\",min:0,dflt:2},spikecolor:{valType:\"color\",dflt:n.defaultLine},showbackground:{valType:\"boolean\",dflt:!1},backgroundcolor:{valType:\"color\",dflt:\"rgba(204, 204, 204, 0.5)\"},showaxeslabels:{valType:\"boolean\",dflt:!0},color:i.color,categoryorder:i.categoryorder,categoryarray:i.categoryarray,title:{text:i.title.text,font:i.title.font},type:a({},i.type,{values:[\"-\",\"linear\",\"log\",\"date\",\"category\"]}),autotypenumbers:i.autotypenumbers,autorange:i.autorange,rangemode:i.rangemode,range:a({},i.range,{items:[{valType:\"any\",editType:\"plot\",impliedEdits:{\"^autorange\":!1}},{valType:\"any\",editType:\"plot\",impliedEdits:{\"^autorange\":!1}}],anim:!1}),tickmode:i.tickmode,nticks:i.nticks,tick0:i.tick0,dtick:i.dtick,tickvals:i.tickvals,ticktext:i.ticktext,ticks:i.ticks,mirror:i.mirror,ticklen:i.ticklen,tickwidth:i.tickwidth,tickcolor:i.tickcolor,showticklabels:i.showticklabels,tickfont:i.tickfont,tickangle:i.tickangle,tickprefix:i.tickprefix,showtickprefix:i.showtickprefix,ticksuffix:i.ticksuffix,showticksuffix:i.showticksuffix,showexponent:i.showexponent,exponentformat:i.exponentformat,minexponent:i.minexponent,separatethousands:i.separatethousands,tickformat:i.tickformat,tickformatstops:i.tickformatstops,hoverformat:i.hoverformat,showline:i.showline,linecolor:i.linecolor,linewidth:i.linewidth,showgrid:i.showgrid,gridcolor:a({},i.gridcolor,{dflt:\"rgb(204, 204, 204)\"}),gridwidth:i.gridwidth,zeroline:i.zeroline,zerolinecolor:i.zerolinecolor,zerolinewidth:i.zerolinewidth,_deprecated:{title:i._deprecated.title,titlefont:i._deprecated.titlefont}},\"plot\",\"from-root\")},{\"../../../components/color\":366,\"../../../lib/extend\":493,\"../../../plot_api/edit_types\":536,\"../../cartesian/layout_attributes\":569}],601:[function(t,e,r){\"use strict\";var n=t(\"tinycolor2\").mix,i=t(\"../../../lib\"),a=t(\"../../../plot_api/plot_template\"),o=t(\"./axis_attributes\"),s=t(\"../../cartesian/type_defaults\"),l=t(\"../../cartesian/axis_defaults\"),c=[\"xaxis\",\"yaxis\",\"zaxis\"];e.exports=function(t,e,r){var u,f;function h(t,e){return i.coerce(u,f,o,t,e)}for(var p=0;p<c.length;p++){var d=c[p];u=t[d]||{},(f=a.newContainer(e,d))._id=d[0]+r.scene,f._name=d,s(u,f,h,r),l(u,f,h,{font:r.font,letter:d[0],data:r.data,showGrid:!0,noTickson:!0,noTicklabelmode:!0,noTicklabelstep:!0,noTicklabelposition:!0,noTicklabeloverflow:!0,bgColor:r.bgColor,calendar:r.calendar},r.fullLayout),h(\"gridcolor\",n(f.color,r.bgColor,13600/187).toRgbString()),h(\"title.text\",d[0]),f.setScale=i.noop,h(\"showspikes\")&&(h(\"spikesides\"),h(\"spikethickness\"),h(\"spikecolor\",f.color)),h(\"showaxeslabels\"),h(\"showbackground\")&&h(\"backgroundcolor\")}}},{\"../../../lib\":503,\"../../../plot_api/plot_template\":543,\"../../cartesian/axis_defaults\":556,\"../../cartesian/type_defaults\":582,\"./axis_attributes\":600,tinycolor2:312}],602:[function(t,e,r){\"use strict\";var n=t(\"../../../lib/str2rgbarray\"),i=t(\"../../../lib\"),a=[\"xaxis\",\"yaxis\",\"zaxis\"];function o(){this.bounds=[[-10,-10,-10],[10,10,10]],this.ticks=[[],[],[]],this.tickEnable=[!0,!0,!0],this.tickFont=[\"sans-serif\",\"sans-serif\",\"sans-serif\"],this.tickSize=[12,12,12],this.tickAngle=[0,0,0],this.tickColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.tickPad=[18,18,18],this.labels=[\"x\",\"y\",\"z\"],this.labelEnable=[!0,!0,!0],this.labelFont=[\"Open Sans\",\"Open Sans\",\"Open Sans\"],this.labelSize=[20,20,20],this.labelColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.labelPad=[30,30,30],this.lineEnable=[!0,!0,!0],this.lineMirror=[!1,!1,!1],this.lineWidth=[1,1,1],this.lineColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.lineTickEnable=[!0,!0,!0],this.lineTickMirror=[!1,!1,!1],this.lineTickLength=[10,10,10],this.lineTickWidth=[1,1,1],this.lineTickColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.gridEnable=[!0,!0,!0],this.gridWidth=[1,1,1],this.gridColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.zeroEnable=[!0,!0,!0],this.zeroLineColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.zeroLineWidth=[2,2,2],this.backgroundEnable=[!0,!0,!0],this.backgroundColor=[[.8,.8,.8,.5],[.8,.8,.8,.5],[.8,.8,.8,.5]],this._defaultTickPad=this.tickPad.slice(),this._defaultLabelPad=this.labelPad.slice(),this._defaultLineTickLength=this.lineTickLength.slice()}o.prototype.merge=function(t,e){for(var r=0;r<3;++r){var o=e[a[r]];o.visible?(this.labels[r]=t._meta?i.templateString(o.title.text,t._meta):o.title.text,\"font\"in o.title&&(o.title.font.color&&(this.labelColor[r]=n(o.title.font.color)),o.title.font.family&&(this.labelFont[r]=o.title.font.family),o.title.font.size&&(this.labelSize[r]=o.title.font.size)),\"showline\"in o&&(this.lineEnable[r]=o.showline),\"linecolor\"in o&&(this.lineColor[r]=n(o.linecolor)),\"linewidth\"in o&&(this.lineWidth[r]=o.linewidth),\"showgrid\"in o&&(this.gridEnable[r]=o.showgrid),\"gridcolor\"in o&&(this.gridColor[r]=n(o.gridcolor)),\"gridwidth\"in o&&(this.gridWidth[r]=o.gridwidth),\"log\"===o.type?this.zeroEnable[r]=!1:\"zeroline\"in o&&(this.zeroEnable[r]=o.zeroline),\"zerolinecolor\"in o&&(this.zeroLineColor[r]=n(o.zerolinecolor)),\"zerolinewidth\"in o&&(this.zeroLineWidth[r]=o.zerolinewidth),\"ticks\"in o&&o.ticks?this.lineTickEnable[r]=!0:this.lineTickEnable[r]=!1,\"ticklen\"in o&&(this.lineTickLength[r]=this._defaultLineTickLength[r]=o.ticklen),\"tickcolor\"in o&&(this.lineTickColor[r]=n(o.tickcolor)),\"tickwidth\"in o&&(this.lineTickWidth[r]=o.tickwidth),\"tickangle\"in o&&(this.tickAngle[r]=\"auto\"===o.tickangle?-3600:Math.PI*-o.tickangle/180),\"showticklabels\"in o&&(this.tickEnable[r]=o.showticklabels),\"tickfont\"in o&&(o.tickfont.color&&(this.tickColor[r]=n(o.tickfont.color)),o.tickfont.family&&(this.tickFont[r]=o.tickfont.family),o.tickfont.size&&(this.tickSize[r]=o.tickfont.size)),\"mirror\"in o?-1!==[\"ticks\",\"all\",\"allticks\"].indexOf(o.mirror)?(this.lineTickMirror[r]=!0,this.lineMirror[r]=!0):!0===o.mirror?(this.lineTickMirror[r]=!1,this.lineMirror[r]=!0):(this.lineTickMirror[r]=!1,this.lineMirror[r]=!1):this.lineMirror[r]=!1,\"showbackground\"in o&&!1!==o.showbackground?(this.backgroundEnable[r]=!0,this.backgroundColor[r]=n(o.backgroundcolor)):this.backgroundEnable[r]=!1):(this.tickEnable[r]=!1,this.labelEnable[r]=!1,this.lineEnable[r]=!1,this.lineTickEnable[r]=!1,this.gridEnable[r]=!1,this.zeroEnable[r]=!1,this.backgroundEnable[r]=!1)}},e.exports=function(t,e){var r=new o;return r.merge(t,e),r}},{\"../../../lib\":503,\"../../../lib/str2rgbarray\":528}],603:[function(t,e,r){\"use strict\";var n=t(\"../../../lib\"),i=t(\"../../../components/color\"),a=t(\"../../../registry\"),o=t(\"../../subplot_defaults\"),s=t(\"./axis_defaults\"),l=t(\"./layout_attributes\"),c=t(\"../../get_data\").getSubplotData;function u(t,e,r,n){for(var o=r(\"bgcolor\"),l=i.combine(o,n.paper_bgcolor),u=[\"up\",\"center\",\"eye\"],f=0;f<u.length;f++)r(\"camera.\"+u[f]+\".x\"),r(\"camera.\"+u[f]+\".y\"),r(\"camera.\"+u[f]+\".z\");r(\"camera.projection.type\");var h=!!r(\"aspectratio.x\")&&!!r(\"aspectratio.y\")&&!!r(\"aspectratio.z\"),p=r(\"aspectmode\",h?\"manual\":\"auto\");h||(t.aspectratio=e.aspectratio={x:1,y:1,z:1},\"manual\"===p&&(e.aspectmode=\"auto\"),t.aspectmode=e.aspectmode);var d=c(n.fullData,\"gl3d\",n.id);s(t,e,{font:n.font,scene:n.id,data:d,bgColor:l,calendar:n.calendar,autotypenumbersDflt:n.autotypenumbersDflt,fullLayout:n.fullLayout}),a.getComponentMethod(\"annotations3d\",\"handleDefaults\")(t,e,n);var m=n.getDfltFromLayout(\"dragmode\");if(!1!==m&&!m)if(m=\"orbit\",t.camera&&t.camera.up){var g=t.camera.up.x,v=t.camera.up.y,y=t.camera.up.z;0!==y&&(g&&v&&y?y/Math.sqrt(g*g+v*v+y*y)>.999&&(m=\"turntable\"):m=\"turntable\")}else m=\"turntable\";r(\"dragmode\",m),r(\"hovermode\",n.getDfltFromLayout(\"hovermode\"))}e.exports=function(t,e,r){var i=e._basePlotModules.length>1;o(t,e,r,{type:\"gl3d\",attributes:l,handleDefaults:u,fullLayout:e,font:e.font,fullData:r,getDfltFromLayout:function(e){if(!i)return n.validate(t[e],l[e])?t[e]:void 0},autotypenumbersDflt:e.autotypenumbers,paper_bgcolor:e.paper_bgcolor,calendar:e.calendar})}},{\"../../../components/color\":366,\"../../../lib\":503,\"../../../registry\":638,\"../../get_data\":593,\"../../subplot_defaults\":632,\"./axis_defaults\":601,\"./layout_attributes\":604}],604:[function(t,e,r){\"use strict\";var n=t(\"./axis_attributes\"),i=t(\"../../domain\").attributes,a=t(\"../../../lib/extend\").extendFlat,o=t(\"../../../lib\").counterRegex;function s(t,e,r){return{x:{valType:\"number\",dflt:t,editType:\"camera\"},y:{valType:\"number\",dflt:e,editType:\"camera\"},z:{valType:\"number\",dflt:r,editType:\"camera\"},editType:\"camera\"}}e.exports={_arrayAttrRegexps:[o(\"scene\",\".annotations\",!0)],bgcolor:{valType:\"color\",dflt:\"rgba(0,0,0,0)\",editType:\"plot\"},camera:{up:a(s(0,0,1),{}),center:a(s(0,0,0),{}),eye:a(s(1.25,1.25,1.25),{}),projection:{type:{valType:\"enumerated\",values:[\"perspective\",\"orthographic\"],dflt:\"perspective\",editType:\"calc\"},editType:\"calc\"},editType:\"camera\"},domain:i({name:\"scene\",editType:\"plot\"}),aspectmode:{valType:\"enumerated\",values:[\"auto\",\"cube\",\"data\",\"manual\"],dflt:\"auto\",editType:\"plot\",impliedEdits:{\"aspectratio.x\":void 0,\"aspectratio.y\":void 0,\"aspectratio.z\":void 0}},aspectratio:{x:{valType:\"number\",min:0,editType:\"plot\",impliedEdits:{\"^aspectmode\":\"manual\"}},y:{valType:\"number\",min:0,editType:\"plot\",impliedEdits:{\"^aspectmode\":\"manual\"}},z:{valType:\"number\",min:0,editType:\"plot\",impliedEdits:{\"^aspectmode\":\"manual\"}},editType:\"plot\",impliedEdits:{aspectmode:\"manual\"}},xaxis:n,yaxis:n,zaxis:n,dragmode:{valType:\"enumerated\",values:[\"orbit\",\"turntable\",\"zoom\",\"pan\",!1],editType:\"plot\"},hovermode:{valType:\"enumerated\",values:[\"closest\",!1],dflt:\"closest\",editType:\"modebar\"},uirevision:{valType:\"any\",editType:\"none\"},editType:\"plot\",_deprecated:{cameraposition:{valType:\"info_array\",editType:\"camera\"}}}},{\"../../../lib\":503,\"../../../lib/extend\":493,\"../../domain\":584,\"./axis_attributes\":600}],605:[function(t,e,r){\"use strict\";var n=t(\"../../../lib/str2rgbarray\"),i=[\"xaxis\",\"yaxis\",\"zaxis\"];function a(){this.enabled=[!0,!0,!0],this.colors=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.drawSides=[!0,!0,!0],this.lineWidth=[1,1,1]}a.prototype.merge=function(t){for(var e=0;e<3;++e){var r=t[i[e]];r.visible?(this.enabled[e]=r.showspikes,this.colors[e]=n(r.spikecolor),this.drawSides[e]=r.spikesides,this.lineWidth[e]=r.spikethickness):(this.enabled[e]=!1,this.drawSides[e]=!1)}},e.exports=function(t){var e=new a;return e.merge(t),e}},{\"../../../lib/str2rgbarray\":528}],606:[function(t,e,r){\"use strict\";e.exports=function(t){for(var e=t.axesOptions,r=t.glplot.axesPixels,s=t.fullSceneLayout,l=[[],[],[]],c=0;c<3;++c){var u=s[a[c]];if(u._length=(r[c].hi-r[c].lo)*r[c].pixelsPerDataUnit/t.dataScale[c],Math.abs(u._length)===1/0||isNaN(u._length))l[c]=[];else{u._input_range=u.range.slice(),u.range[0]=r[c].lo/t.dataScale[c],u.range[1]=r[c].hi/t.dataScale[c],u._m=1/(t.dataScale[c]*r[c].pixelsPerDataUnit),u.range[0]===u.range[1]&&(u.range[0]-=1,u.range[1]+=1);var f=u.tickmode;if(\"auto\"===u.tickmode){u.tickmode=\"linear\";var h=u.nticks||i.constrain(u._length/40,4,9);n.autoTicks(u,Math.abs(u.range[1]-u.range[0])/h)}for(var p=n.calcTicks(u,{msUTC:!0}),d=0;d<p.length;++d)p[d].x=p[d].x*t.dataScale[c],\"date\"===u.type&&(p[d].text=p[d].text.replace(/\\<br\\>/g,\" \"));l[c]=p,u.tickmode=f}}e.ticks=l;for(c=0;c<3;++c){o[c]=.5*(t.glplot.bounds[0][c]+t.glplot.bounds[1][c]);for(d=0;d<2;++d)e.bounds[d][c]=t.glplot.bounds[d][c]}t.contourLevels=function(t){for(var e=new Array(3),r=0;r<3;++r){for(var n=t[r],i=new Array(n.length),a=0;a<n.length;++a)i[a]=n[a].x;e[r]=i}return e}(l)};var n=t(\"../../cartesian/axes\"),i=t(\"../../../lib\"),a=[\"xaxis\",\"yaxis\",\"zaxis\"],o=[0,0,0]},{\"../../../lib\":503,\"../../cartesian/axes\":554}],607:[function(t,e,r){\"use strict\";function n(t,e){var r,n,i=[0,0,0,0];for(r=0;r<4;++r)for(n=0;n<4;++n)i[n]+=t[4*r+n]*e[r];return i}e.exports=function(t,e){return n(t.projection,n(t.view,n(t.model,[e[0],e[1],e[2],1])))}},{}],608:[function(t,e,r){\"use strict\";var n,i,a=t(\"../../../stackgl_modules\").gl_plot3d,o=a.createCamera,s=a.createScene,l=t(\"webgl-context\"),c=t(\"has-passive-events\"),u=t(\"../../registry\"),f=t(\"../../lib\"),h=f.preserveDrawingBuffer(),p=t(\"../../plots/cartesian/axes\"),d=t(\"../../components/fx\"),m=t(\"../../lib/str2rgbarray\"),g=t(\"../../lib/show_no_webgl_msg\"),v=t(\"./project\"),y=t(\"./layout/convert\"),x=t(\"./layout/spikes\"),b=t(\"./layout/tick_marks\");function _(t,e){var r=document.createElement(\"div\"),n=t.container;this.graphDiv=t.graphDiv;var i=document.createElementNS(\"http://www.w3.org/2000/svg\",\"svg\");i.style.position=\"absolute\",i.style.top=i.style.left=\"0px\",i.style.width=i.style.height=\"100%\",i.style[\"z-index\"]=20,i.style[\"pointer-events\"]=\"none\",r.appendChild(i),this.svgContainer=i,r.id=t.id,r.style.position=\"absolute\",r.style.top=r.style.left=\"0px\",r.style.width=r.style.height=\"100%\",n.appendChild(r),this.fullLayout=e,this.id=t.id||\"scene\",this.fullSceneLayout=e[this.id],this.plotArgs=[[],{},{}],this.axesOptions=y(e,e[this.id]),this.spikeOptions=x(e[this.id]),this.container=r,this.staticMode=!!t.staticPlot,this.pixelRatio=this.pixelRatio||t.plotGlPixelRatio||2,this.dataScale=[1,1,1],this.contourLevels=[[],[],[]],this.convertAnnotations=u.getComponentMethod(\"annotations3d\",\"convert\"),this.drawAnnotations=u.getComponentMethod(\"annotations3d\",\"draw\"),this.initializeGLPlot()}var w=_.prototype;w.prepareOptions=function(){var t={canvas:this.canvas,gl:this.gl,glOptions:{preserveDrawingBuffer:h,premultipliedAlpha:!0,antialias:!0},container:this.container,axes:this.axesOptions,spikes:this.spikeOptions,pickRadius:10,snapToData:!0,autoScale:!0,autoBounds:!1,cameraObject:this.camera,pixelRatio:this.pixelRatio};if(this.staticMode){if(!(i||(n=document.createElement(\"canvas\"),i=l({canvas:n,preserveDrawingBuffer:!0,premultipliedAlpha:!0,antialias:!0}))))throw new Error(\"error creating static canvas/context for image server\");t.gl=i,t.canvas=n}return t};var T=!0;w.tryCreatePlot=function(){var t=this.prepareOptions(),e=!0;try{this.glplot=s(t)}catch(r){if(this.staticMode||!T||h)e=!1;else{f.warn([\"webgl setup failed possibly due to\",\"false preserveDrawingBuffer config.\",\"The mobile/tablet device may not be detected by is-mobile module.\",\"Enabling preserveDrawingBuffer in second attempt to create webgl scene...\"].join(\" \"));try{h=t.glOptions.preserveDrawingBuffer=!0,this.glplot=s(t)}catch(r){h=t.glOptions.preserveDrawingBuffer=!1,e=!1}}}return T=!1,e},w.initializeGLCamera=function(){var t=this.fullSceneLayout.camera,e=\"orthographic\"===t.projection.type;this.camera=o(this.container,{center:[t.center.x,t.center.y,t.center.z],eye:[t.eye.x,t.eye.y,t.eye.z],up:[t.up.x,t.up.y,t.up.z],_ortho:e,zoomMin:.01,zoomMax:100,mode:\"orbit\"})},w.initializeGLPlot=function(){var t=this;if(t.initializeGLCamera(),!t.tryCreatePlot())return g(t);t.traces={},t.make4thDimension();var e=t.graphDiv,r=e.layout,n=function(){var e={};return t.isCameraChanged(r)&&(e[t.id+\".camera\"]=t.getCamera()),t.isAspectChanged(r)&&(e[t.id+\".aspectratio\"]=t.glplot.getAspectratio(),\"manual\"!==r[t.id].aspectmode&&(t.fullSceneLayout.aspectmode=r[t.id].aspectmode=e[t.id+\".aspectmode\"]=\"manual\")),e},i=function(t){if(!1!==t.fullSceneLayout.dragmode){var e=n();t.saveLayout(r),t.graphDiv.emit(\"plotly_relayout\",e)}};return t.glplot.canvas&&(t.glplot.canvas.addEventListener(\"mouseup\",(function(){i(t)})),t.glplot.canvas.addEventListener(\"wheel\",(function(r){if(e._context._scrollZoom.gl3d){if(t.camera._ortho){var n=r.deltaX>r.deltaY?1.1:1/1.1,a=t.glplot.getAspectratio();t.glplot.setAspectratio({x:n*a.x,y:n*a.y,z:n*a.z})}i(t)}}),!!c&&{passive:!1}),t.glplot.canvas.addEventListener(\"mousemove\",(function(){if(!1!==t.fullSceneLayout.dragmode&&0!==t.camera.mouseListener.buttons){var e=n();t.graphDiv.emit(\"plotly_relayouting\",e)}})),t.staticMode||t.glplot.canvas.addEventListener(\"webglcontextlost\",(function(r){e&&e.emit&&e.emit(\"plotly_webglcontextlost\",{event:r,layer:t.id})}),!1)),t.glplot.oncontextloss=function(){t.recoverContext()},t.glplot.onrender=function(){t.render()},!0},w.render=function(){var t,e=this,r=e.graphDiv,n=e.svgContainer,i=e.container.getBoundingClientRect();r._fullLayout._calcInverseTransform(r);var a=r._fullLayout._invScaleX,o=r._fullLayout._invScaleY,s=i.width*a,l=i.height*o;n.setAttributeNS(null,\"viewBox\",\"0 0 \"+s+\" \"+l),n.setAttributeNS(null,\"width\",s),n.setAttributeNS(null,\"height\",l),b(e),e.glplot.axes.update(e.axesOptions);for(var c=Object.keys(e.traces),u=null,h=e.glplot.selection,m=0;m<c.length;++m)\"skip\"!==(t=e.traces[c[m]]).data.hoverinfo&&t.handlePick(h)&&(u=t),t.setContourLevels&&t.setContourLevels();function g(t,r,n){var i=e.fullSceneLayout[t+\"axis\"];return\"log\"!==i.type&&(r=i.d2l(r)),p.hoverLabelText(i,r,n)}if(null!==u){var y=v(e.glplot.cameraParams,h.dataCoordinate);t=u.data;var x,_=r._fullData[t.index],w=h.index,T={xLabel:g(\"x\",h.traceCoordinate[0],t.xhoverformat),yLabel:g(\"y\",h.traceCoordinate[1],t.yhoverformat),zLabel:g(\"z\",h.traceCoordinate[2],t.zhoverformat)},k=d.castHoverinfo(_,e.fullLayout,w),A=(k||\"\").split(\"+\"),M=k&&\"all\"===k;_.hovertemplate||M||(-1===A.indexOf(\"x\")&&(T.xLabel=void 0),-1===A.indexOf(\"y\")&&(T.yLabel=void 0),-1===A.indexOf(\"z\")&&(T.zLabel=void 0),-1===A.indexOf(\"text\")&&(h.textLabel=void 0),-1===A.indexOf(\"name\")&&(u.name=void 0));var S=[];\"cone\"===t.type||\"streamtube\"===t.type?(T.uLabel=g(\"x\",h.traceCoordinate[3],t.uhoverformat),(M||-1!==A.indexOf(\"u\"))&&S.push(\"u: \"+T.uLabel),T.vLabel=g(\"y\",h.traceCoordinate[4],t.vhoverformat),(M||-1!==A.indexOf(\"v\"))&&S.push(\"v: \"+T.vLabel),T.wLabel=g(\"z\",h.traceCoordinate[5],t.whoverformat),(M||-1!==A.indexOf(\"w\"))&&S.push(\"w: \"+T.wLabel),T.normLabel=h.traceCoordinate[6].toPrecision(3),(M||-1!==A.indexOf(\"norm\"))&&S.push(\"norm: \"+T.normLabel),\"streamtube\"===t.type&&(T.divergenceLabel=h.traceCoordinate[7].toPrecision(3),(M||-1!==A.indexOf(\"divergence\"))&&S.push(\"divergence: \"+T.divergenceLabel)),h.textLabel&&S.push(h.textLabel),x=S.join(\"<br>\")):\"isosurface\"===t.type||\"volume\"===t.type?(T.valueLabel=p.hoverLabelText(e._mockAxis,e._mockAxis.d2l(h.traceCoordinate[3]),t.valuehoverformat),S.push(\"value: \"+T.valueLabel),h.textLabel&&S.push(h.textLabel),x=S.join(\"<br>\")):x=h.textLabel;var E={x:h.traceCoordinate[0],y:h.traceCoordinate[1],z:h.traceCoordinate[2],data:_._input,fullData:_,curveNumber:_.index,pointNumber:w};d.appendArrayPointValue(E,_,w),t._module.eventData&&(E=_._module.eventData(E,h,_,{},w));var L={points:[E]};if(e.fullSceneLayout.hovermode){var C=[];d.loneHover({trace:_,x:(.5+.5*y[0]/y[3])*s,y:(.5-.5*y[1]/y[3])*l,xLabel:T.xLabel,yLabel:T.yLabel,zLabel:T.zLabel,text:x,name:u.name,color:d.castHoverOption(_,w,\"bgcolor\")||u.color,borderColor:d.castHoverOption(_,w,\"bordercolor\"),fontFamily:d.castHoverOption(_,w,\"font.family\"),fontSize:d.castHoverOption(_,w,\"font.size\"),fontColor:d.castHoverOption(_,w,\"font.color\"),nameLength:d.castHoverOption(_,w,\"namelength\"),textAlign:d.castHoverOption(_,w,\"align\"),hovertemplate:f.castOption(_,w,\"hovertemplate\"),hovertemplateLabels:f.extendFlat({},E,T),eventData:[E]},{container:n,gd:r,inOut_bbox:C}),E.bbox=C[0]}h.buttons&&h.distance<5?r.emit(\"plotly_click\",L):r.emit(\"plotly_hover\",L),this.oldEventData=L}else d.loneUnhover(n),this.oldEventData&&r.emit(\"plotly_unhover\",this.oldEventData),this.oldEventData=void 0;e.drawAnnotations(e)},w.recoverContext=function(){var t=this;t.glplot.dispose();var e=function(){t.glplot.gl.isContextLost()?requestAnimationFrame(e):t.initializeGLPlot()?t.plot.apply(t,t.plotArgs):f.error(\"Catastrophic and unrecoverable WebGL error. Context lost.\")};requestAnimationFrame(e)};var k=[\"xaxis\",\"yaxis\",\"zaxis\"];function A(t,e,r){for(var n=t.fullSceneLayout,i=0;i<3;i++){var a=k[i],o=a.charAt(0),s=n[a],l=e[o],c=e[o+\"calendar\"],u=e[\"_\"+o+\"length\"];if(f.isArrayOrTypedArray(l))for(var h,p=0;p<(u||l.length);p++)if(f.isArrayOrTypedArray(l[p]))for(var d=0;d<l[p].length;++d)h=s.d2l(l[p][d],0,c),!isNaN(h)&&isFinite(h)&&(r[0][i]=Math.min(r[0][i],h),r[1][i]=Math.max(r[1][i],h));else h=s.d2l(l[p],0,c),!isNaN(h)&&isFinite(h)&&(r[0][i]=Math.min(r[0][i],h),r[1][i]=Math.max(r[1][i],h));else r[0][i]=Math.min(r[0][i],0),r[1][i]=Math.max(r[1][i],u-1)}}w.plot=function(t,e,r){if(this.plotArgs=[t,e,r],!this.glplot.contextLost){var n,i,a,o,s,l,c=e[this.id],u=r[this.id];this.fullLayout=e,this.fullSceneLayout=c,this.axesOptions.merge(e,c),this.spikeOptions.merge(c),this.setViewport(c),this.updateFx(c.dragmode,c.hovermode),this.camera.enableWheel=this.graphDiv._context._scrollZoom.gl3d,this.glplot.setClearColor(m(c.bgcolor)),this.setConvert(s),t?Array.isArray(t)||(t=[t]):t=[];var f=[[1/0,1/0,1/0],[-1/0,-1/0,-1/0]];for(a=0;a<t.length;++a)!0===(n=t[a]).visible&&0!==n._length&&A(this,n,f);!function(t,e){for(var r=t.fullSceneLayout,n=r.annotations||[],i=0;i<3;i++)for(var a=k[i],o=a.charAt(0),s=r[a],l=0;l<n.length;l++){var c=n[l];if(c.visible){var u=s.r2l(c[o]);!isNaN(u)&&isFinite(u)&&(e[0][i]=Math.min(e[0][i],u),e[1][i]=Math.max(e[1][i],u))}}}(this,f);var h=[1,1,1];for(o=0;o<3;++o)f[1][o]===f[0][o]?h[o]=1:h[o]=1/(f[1][o]-f[0][o]);for(this.dataScale=h,this.convertAnnotations(this),a=0;a<t.length;++a)!0===(n=t[a]).visible&&0!==n._length&&((i=this.traces[n.uid])?i.data.type===n.type?i.update(n):(i.dispose(),i=n._module.plot(this,n),this.traces[n.uid]=i):(i=n._module.plot(this,n),this.traces[n.uid]=i),i.name=n.name);var p=Object.keys(this.traces);t:for(a=0;a<p.length;++a){for(o=0;o<t.length;++o)if(t[o].uid===p[a]&&!0===t[o].visible&&0!==t[o]._length)continue t;(i=this.traces[p[a]]).dispose(),delete this.traces[p[a]]}this.glplot.objects.sort((function(t,e){return t._trace.data.index-e._trace.data.index}));var d,g=[[0,0,0],[0,0,0]],v=[],y={};for(a=0;a<3;++a){if((l=(s=c[k[a]]).type)in y?(y[l].acc*=h[a],y[l].count+=1):y[l]={acc:h[a],count:1},s.autorange){g[0][a]=1/0,g[1][a]=-1/0;var x=this.glplot.objects,b=this.fullSceneLayout.annotations||[],_=s._name.charAt(0);for(o=0;o<x.length;o++){var w=x[o],T=w.bounds,M=w._trace.data._pad||0;\"ErrorBars\"===w.constructor.name&&s._lowerLogErrorBound?g[0][a]=Math.min(g[0][a],s._lowerLogErrorBound):g[0][a]=Math.min(g[0][a],T[0][a]/h[a]-M),g[1][a]=Math.max(g[1][a],T[1][a]/h[a]+M)}for(o=0;o<b.length;o++){var S=b[o];if(S.visible){var E=s.r2l(S[_]);g[0][a]=Math.min(g[0][a],E),g[1][a]=Math.max(g[1][a],E)}}if(\"rangemode\"in s&&\"tozero\"===s.rangemode&&(g[0][a]=Math.min(g[0][a],0),g[1][a]=Math.max(g[1][a],0)),g[0][a]>g[1][a])g[0][a]=-1,g[1][a]=1;else{var L=g[1][a]-g[0][a];g[0][a]-=L/32,g[1][a]+=L/32}if(\"reversed\"===s.autorange){var C=g[0][a];g[0][a]=g[1][a],g[1][a]=C}}else{var P=s.range;g[0][a]=s.r2l(P[0]),g[1][a]=s.r2l(P[1])}g[0][a]===g[1][a]&&(g[0][a]-=1,g[1][a]+=1),v[a]=g[1][a]-g[0][a],this.glplot.setBounds(a,{min:g[0][a]*h[a],max:g[1][a]*h[a]})}var I=c.aspectmode;if(\"cube\"===I)d=[1,1,1];else if(\"manual\"===I){var O=c.aspectratio;d=[O.x,O.y,O.z]}else{if(\"auto\"!==I&&\"data\"!==I)throw new Error(\"scene.js aspectRatio was not one of the enumerated types\");var z=[1,1,1];for(a=0;a<3;++a){var D=y[l=(s=c[k[a]]).type];z[a]=Math.pow(D.acc,1/D.count)/h[a]}d=\"data\"===I||Math.max.apply(null,z)/Math.min.apply(null,z)<=4?z:[1,1,1]}c.aspectratio.x=u.aspectratio.x=d[0],c.aspectratio.y=u.aspectratio.y=d[1],c.aspectratio.z=u.aspectratio.z=d[2],this.glplot.setAspectratio(c.aspectratio),this.viewInitial.aspectratio||(this.viewInitial.aspectratio={x:c.aspectratio.x,y:c.aspectratio.y,z:c.aspectratio.z}),this.viewInitial.aspectmode||(this.viewInitial.aspectmode=c.aspectmode);var R=c.domain||null,F=e._size||null;if(R&&F){var B=this.container.style;B.position=\"absolute\",B.left=F.l+R.x[0]*F.w+\"px\",B.top=F.t+(1-R.y[1])*F.h+\"px\",B.width=F.w*(R.x[1]-R.x[0])+\"px\",B.height=F.h*(R.y[1]-R.y[0])+\"px\"}this.glplot.redraw()}},w.destroy=function(){this.glplot&&(this.camera.mouseListener.enabled=!1,this.container.removeEventListener(\"wheel\",this.camera.wheelListener),this.camera=null,this.glplot.dispose(),this.container.parentNode.removeChild(this.container),this.glplot=null)},w.getCamera=function(){var t;return this.camera.view.recalcMatrix(this.camera.view.lastT()),{up:{x:(t=this.camera).up[0],y:t.up[1],z:t.up[2]},center:{x:t.center[0],y:t.center[1],z:t.center[2]},eye:{x:t.eye[0],y:t.eye[1],z:t.eye[2]},projection:{type:!0===t._ortho?\"orthographic\":\"perspective\"}}},w.setViewport=function(t){var e,r=t.camera;this.camera.lookAt.apply(this,[[(e=r).eye.x,e.eye.y,e.eye.z],[e.center.x,e.center.y,e.center.z],[e.up.x,e.up.y,e.up.z]]),this.glplot.setAspectratio(t.aspectratio),\"orthographic\"===r.projection.type!==this.camera._ortho&&(this.glplot.redraw(),this.glplot.clearRGBA(),this.glplot.dispose(),this.initializeGLPlot())},w.isCameraChanged=function(t){var e=this.getCamera(),r=f.nestedProperty(t,this.id+\".camera\").get();function n(t,e,r,n){var i=[\"up\",\"center\",\"eye\"],a=[\"x\",\"y\",\"z\"];return e[i[r]]&&t[i[r]][a[n]]===e[i[r]][a[n]]}var i=!1;if(void 0===r)i=!0;else{for(var a=0;a<3;a++)for(var o=0;o<3;o++)if(!n(e,r,a,o)){i=!0;break}(!r.projection||e.projection&&e.projection.type!==r.projection.type)&&(i=!0)}return i},w.isAspectChanged=function(t){var e=this.glplot.getAspectratio(),r=f.nestedProperty(t,this.id+\".aspectratio\").get();return void 0===r||r.x!==e.x||r.y!==e.y||r.z!==e.z},w.saveLayout=function(t){var e,r,n,i,a,o,s=this.fullLayout,l=this.isCameraChanged(t),c=this.isAspectChanged(t),h=l||c;if(h){var p={};if(l&&(e=this.getCamera(),n=(r=f.nestedProperty(t,this.id+\".camera\")).get(),p[this.id+\".camera\"]=n),c&&(i=this.glplot.getAspectratio(),o=(a=f.nestedProperty(t,this.id+\".aspectratio\")).get(),p[this.id+\".aspectratio\"]=o),u.call(\"_storeDirectGUIEdit\",t,s._preGUI,p),l)r.set(e),f.nestedProperty(s,this.id+\".camera\").set(e);if(c)a.set(i),f.nestedProperty(s,this.id+\".aspectratio\").set(i),this.glplot.redraw()}return h},w.updateFx=function(t,e){var r=this.camera;if(r)if(\"orbit\"===t)r.mode=\"orbit\",r.keyBindingMode=\"rotate\";else if(\"turntable\"===t){r.up=[0,0,1],r.mode=\"turntable\",r.keyBindingMode=\"rotate\";var n=this.graphDiv,i=n._fullLayout,a=this.fullSceneLayout.camera,o=a.up.x,s=a.up.y,l=a.up.z;if(l/Math.sqrt(o*o+s*s+l*l)<.999){var c=this.id+\".camera.up\",h={x:0,y:0,z:1},p={};p[c]=h;var d=n.layout;u.call(\"_storeDirectGUIEdit\",d,i._preGUI,p),a.up=h,f.nestedProperty(d,c).set(h)}}else r.keyBindingMode=t;this.fullSceneLayout.hovermode=e},w.toImage=function(t){t||(t=\"png\"),this.staticMode&&this.container.appendChild(n),this.glplot.redraw();var e=this.glplot.gl,r=e.drawingBufferWidth,i=e.drawingBufferHeight;e.bindFramebuffer(e.FRAMEBUFFER,null);var a=new Uint8Array(r*i*4);e.readPixels(0,0,r,i,e.RGBA,e.UNSIGNED_BYTE,a),function(t,e,r){for(var n=0,i=r-1;n<i;++n,--i)for(var a=0;a<e;++a)for(var o=0;o<4;++o){var s=4*(e*n+a)+o,l=4*(e*i+a)+o,c=t[s];t[s]=t[l],t[l]=c}}(a,r,i),function(t,e,r){for(var n=0;n<r;++n)for(var i=0;i<e;++i){var a=4*(e*n+i),o=t[a+3];if(o>0)for(var s=255/o,l=0;l<3;++l)t[a+l]=Math.min(s*t[a+l],255)}}(a,r,i);var o=document.createElement(\"canvas\");o.width=r,o.height=i;var s,l=o.getContext(\"2d\",{willReadFrequently:!0}),c=l.createImageData(r,i);switch(c.data.set(a),l.putImageData(c,0,0),t){case\"jpeg\":s=o.toDataURL(\"image/jpeg\");break;case\"webp\":s=o.toDataURL(\"image/webp\");break;default:s=o.toDataURL(\"image/png\")}return this.staticMode&&this.container.removeChild(n),s},w.setConvert=function(){for(var t=0;t<3;t++){var e=this.fullSceneLayout[k[t]];p.setConvert(e,this.fullLayout),e.setScale=f.noop}},w.make4thDimension=function(){var t=this.graphDiv._fullLayout;this._mockAxis={type:\"linear\",showexponent:\"all\",exponentformat:\"B\"},p.setConvert(this._mockAxis,t)},e.exports=_},{\"../../../stackgl_modules\":1124,\"../../components/fx\":406,\"../../lib\":503,\"../../lib/show_no_webgl_msg\":525,\"../../lib/str2rgbarray\":528,\"../../plots/cartesian/axes\":554,\"../../registry\":638,\"./layout/convert\":602,\"./layout/spikes\":605,\"./layout/tick_marks\":606,\"./project\":607,\"has-passive-events\":229,\"webgl-context\":331}],609:[function(t,e,r){\"use strict\";e.exports=function(t,e,r,n){n=n||t.length;for(var i=new Array(n),a=0;a<n;a++)i[a]=[t[a],e[a],r[a]];return i}},{}],610:[function(t,e,r){\"use strict\";var n=t(\"./font_attributes\"),i=t(\"./animation_attributes\"),a=t(\"../components/color/attributes\"),o=t(\"../components/shapes/draw_newshape/attributes\"),s=t(\"./pad_attributes\"),l=t(\"../lib/extend\").extendFlat,c=n({editType:\"calc\"});c.family.dflt='\"Open Sans\", verdana, arial, sans-serif',c.size.dflt=12,c.color.dflt=a.defaultLine,e.exports={font:c,title:{text:{valType:\"string\",editType:\"layoutstyle\"},font:n({editType:\"layoutstyle\"}),xref:{valType:\"enumerated\",dflt:\"container\",values:[\"container\",\"paper\"],editType:\"layoutstyle\"},yref:{valType:\"enumerated\",dflt:\"container\",values:[\"container\",\"paper\"],editType:\"layoutstyle\"},x:{valType:\"number\",min:0,max:1,dflt:.5,editType:\"layoutstyle\"},y:{valType:\"number\",min:0,max:1,dflt:\"auto\",editType:\"layoutstyle\"},xanchor:{valType:\"enumerated\",dflt:\"auto\",values:[\"auto\",\"left\",\"center\",\"right\"],editType:\"layoutstyle\"},yanchor:{valType:\"enumerated\",dflt:\"auto\",values:[\"auto\",\"top\",\"middle\",\"bottom\"],editType:\"layoutstyle\"},pad:l(s({editType:\"layoutstyle\"}),{}),editType:\"layoutstyle\"},uniformtext:{mode:{valType:\"enumerated\",values:[!1,\"hide\",\"show\"],dflt:!1,editType:\"plot\"},minsize:{valType:\"number\",min:0,dflt:0,editType:\"plot\"},editType:\"plot\"},autosize:{valType:\"boolean\",dflt:!1,editType:\"none\"},width:{valType:\"number\",min:10,dflt:700,editType:\"plot\"},height:{valType:\"number\",min:10,dflt:450,editType:\"plot\"},margin:{l:{valType:\"number\",min:0,dflt:80,editType:\"plot\"},r:{valType:\"number\",min:0,dflt:80,editType:\"plot\"},t:{valType:\"number\",min:0,dflt:100,editType:\"plot\"},b:{valType:\"number\",min:0,dflt:80,editType:\"plot\"},pad:{valType:\"number\",min:0,dflt:0,editType:\"plot\"},autoexpand:{valType:\"boolean\",dflt:!0,editType:\"plot\"},editType:\"plot\"},computed:{valType:\"any\",editType:\"none\"},paper_bgcolor:{valType:\"color\",dflt:a.background,editType:\"plot\"},plot_bgcolor:{valType:\"color\",dflt:a.background,editType:\"layoutstyle\"},autotypenumbers:{valType:\"enumerated\",values:[\"convert types\",\"strict\"],dflt:\"convert types\",editType:\"calc\"},separators:{valType:\"string\",editType:\"plot\"},hidesources:{valType:\"boolean\",dflt:!1,editType:\"plot\"},showlegend:{valType:\"boolean\",editType:\"legend\"},colorway:{valType:\"colorlist\",dflt:a.defaults,editType:\"calc\"},datarevision:{valType:\"any\",editType:\"calc\"},uirevision:{valType:\"any\",editType:\"none\"},editrevision:{valType:\"any\",editType:\"none\"},selectionrevision:{valType:\"any\",editType:\"none\"},template:{valType:\"any\",editType:\"calc\"},newshape:o.newshape,activeshape:o.activeshape,meta:{valType:\"any\",arrayOk:!0,editType:\"plot\"},transition:l({},i.transition,{editType:\"none\"}),_deprecated:{title:{valType:\"string\",editType:\"layoutstyle\"},titlefont:n({editType:\"layoutstyle\"})}}},{\"../components/color/attributes\":365,\"../components/shapes/draw_newshape/attributes\":451,\"../lib/extend\":493,\"./animation_attributes\":548,\"./font_attributes\":585,\"./pad_attributes\":618}],611:[function(t,e,r){\"use strict\";var n=t(\"../../lib/sort_object_keys\"),i='\\xa9 <a target=\"_blank\" href=\"https://www.openstreetmap.org/copyright\">OpenStreetMap</a> contributors',a=['\\xa9 <a target=\"_blank\" href=\"https://carto.com/\">Carto</a>',i].join(\" \"),o=['Map tiles by <a target=\"_blank\" href=\"https://stamen.com\">Stamen Design</a>','under <a target=\"_blank\" href=\"https://creativecommons.org/licenses/by/3.0\">CC BY 3.0</a>',\"|\",'Data by <a target=\"_blank\" href=\"https://openstreetmap.org\">OpenStreetMap</a> contributors','under <a target=\"_blank\" href=\"https://www.openstreetmap.org/copyright\">ODbL</a>'].join(\" \"),s={\"open-street-map\":{id:\"osm\",version:8,sources:{\"plotly-osm-tiles\":{type:\"raster\",attribution:i,tiles:[\"https://a.tile.openstreetmap.org/{z}/{x}/{y}.png\",\"https://b.tile.openstreetmap.org/{z}/{x}/{y}.png\"],tileSize:256}},layers:[{id:\"plotly-osm-tiles\",type:\"raster\",source:\"plotly-osm-tiles\",minzoom:0,maxzoom:22}]},\"white-bg\":{id:\"white-bg\",version:8,sources:{},layers:[{id:\"white-bg\",type:\"background\",paint:{\"background-color\":\"#FFFFFF\"},minzoom:0,maxzoom:22}]},\"carto-positron\":{id:\"carto-positron\",version:8,sources:{\"plotly-carto-positron\":{type:\"raster\",attribution:a,tiles:[\"https://cartodb-basemaps-c.global.ssl.fastly.net/light_all/{z}/{x}/{y}.png\"],tileSize:256}},layers:[{id:\"plotly-carto-positron\",type:\"raster\",source:\"plotly-carto-positron\",minzoom:0,maxzoom:22}]},\"carto-darkmatter\":{id:\"carto-darkmatter\",version:8,sources:{\"plotly-carto-darkmatter\":{type:\"raster\",attribution:a,tiles:[\"https://cartodb-basemaps-c.global.ssl.fastly.net/dark_all/{z}/{x}/{y}.png\"],tileSize:256}},layers:[{id:\"plotly-carto-darkmatter\",type:\"raster\",source:\"plotly-carto-darkmatter\",minzoom:0,maxzoom:22}]},\"stamen-terrain\":{id:\"stamen-terrain\",version:8,sources:{\"plotly-stamen-terrain\":{type:\"raster\",attribution:o,tiles:[\"https://stamen-tiles.a.ssl.fastly.net/terrain/{z}/{x}/{y}.png\"],tileSize:256}},layers:[{id:\"plotly-stamen-terrain\",type:\"raster\",source:\"plotly-stamen-terrain\",minzoom:0,maxzoom:22}]},\"stamen-toner\":{id:\"stamen-toner\",version:8,sources:{\"plotly-stamen-toner\":{type:\"raster\",attribution:o,tiles:[\"https://stamen-tiles.a.ssl.fastly.net/toner/{z}/{x}/{y}.png\"],tileSize:256}},layers:[{id:\"plotly-stamen-toner\",type:\"raster\",source:\"plotly-stamen-toner\",minzoom:0,maxzoom:22}]},\"stamen-watercolor\":{id:\"stamen-watercolor\",version:8,sources:{\"plotly-stamen-watercolor\":{type:\"raster\",attribution:['Map 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t&&(-1!==p.styleValuesMapbox.indexOf(t)||0===t.indexOf(\"mapbox://\"))}r.name=\"mapbox\",r.attr=\"subplot\",r.idRoot=\"mapbox\",r.idRegex=r.attrRegex=i.counterRegex(\"mapbox\"),r.attributes={subplot:{valType:\"subplotid\",dflt:\"mapbox\",editType:\"calc\"}},r.layoutAttributes=t(\"./layout_attributes\"),r.supplyLayoutDefaults=t(\"./layout_defaults\"),r.plot=function(t){var e=t._fullLayout,r=t.calcdata,a=e._subplots.mapbox;if(n.version!==p.requiredVersion)throw new Error(p.wrongVersionErrorMsg);var o=function(t,e){var r=t._fullLayout;if(\"\"===t._context.mapboxAccessToken)return\"\";for(var n=[],a=[],o=!1,s=!1,l=0;l<e.length;l++){var c=r[e[l]],u=c.accesstoken;d(c.style)&&(u?i.pushUnique(n,u):(d(c._input.style)&&(i.error(\"Uses Mapbox map style, but did not set an access token.\"),o=!0),s=!0)),u&&i.pushUnique(a,u)}if(s){var f=o?p.noAccessTokenErrorMsg:p.missingStyleErrorMsg;throw i.error(f),new Error(f)}return 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m=c.select(s._subplot.div);if(!(null===m.select(\".mapboxgl-ctrl-logo\").node().offsetParent)){var g=e._glimages.append(\"g\");g.attr(\"transform\",a(n.l+n.w*h.x[0]+10,n.t+n.h*(1-h.y[0])-31)),g.append(\"path\").attr(\"d\",p.mapboxLogo.path0).style({opacity:.9,fill:\"#ffffff\",\"enable-background\":\"new\"}),g.append(\"path\").attr(\"d\",p.mapboxLogo.path1).style(\"opacity\",.35).style(\"enable-background\",\"new\"),g.append(\"path\").attr(\"d\",p.mapboxLogo.path2).style(\"opacity\",.35).style(\"enable-background\",\"new\"),g.append(\"polygon\").attr(\"points\",p.mapboxLogo.polygon).style({opacity:.9,fill:\"#ffffff\",\"enable-background\":\"new\"})}var v=m.select(\".mapboxgl-ctrl-attrib\").text().replace(\"Improve this map\",\"\"),y=e._glimages.append(\"g\"),x=y.append(\"text\");x.text(v).classed(\"static-attribution\",!0).attr({\"font-size\":12,\"font-family\":\"Arial\",color:\"rgba(0, 0, 0, 0.75)\",\"text-anchor\":\"end\",\"data-unformatted\":v});var b=u.bBox(x.node()),_=n.w*(h.x[1]-h.x[0]);if(b.width>_/2){var w=v.split(\"|\").join(\"<br>\");x.text(w).attr(\"data-unformatted\",w).call(f.convertToTspans,t),b=u.bBox(x.node())}x.attr(\"transform\",a(-3,8-b.height)),y.insert(\"rect\",\".static-attribution\").attr({x:-b.width-6,y:-b.height-3,width:b.width+6,height:b.height+3,fill:\"rgba(255, 255, 255, 0.75)\"});var T=1;b.width+6>_&&(T=_/(b.width+6));var k=[n.l+n.w*h.x[1],n.t+n.h*(1-h.y[0])];y.attr(\"transform\",a(k[0],k[1])+o(T))}},r.updateFx=function(t){for(var e=t._fullLayout,r=e._subplots.mapbox,n=0;n<r.length;n++){e[r[n]]._subplot.updateFx(e)}}},{\"../../components/drawing\":388,\"../../constants/xmlns_namespaces\":480,\"../../lib\":503,\"../../lib/svg_text_utils\":529,\"../../plots/get_data\":593,\"./constants\":611,\"./layout_attributes\":615,\"./layout_defaults\":616,\"./mapbox\":617,\"@plotly/d3\":58,\"mapbox-gl/dist/mapbox-gl-unminified\":239}],614:[function(t,e,r){\"use strict\";var n=t(\"../../lib\"),i=t(\"../../lib/svg_text_utils\").sanitizeHTML,a=t(\"./convert_text_opts\"),o=t(\"./constants\");function s(t,e){this.subplot=t,this.uid=t.uid+\"-\"+e,this.index=e,this.idSource=\"source-\"+this.uid,this.idLayer=o.layoutLayerPrefix+this.uid,this.sourceType=null,this.source=null,this.layerType=null,this.below=null,this.visible=!1}var l=s.prototype;function c(t){if(!t.visible)return!1;var e=t.source;if(Array.isArray(e)&&e.length>0){for(var r=0;r<e.length;r++)if(\"string\"!=typeof e[r]||0===e[r].length)return!1;return!0}return n.isPlainObject(e)||\"string\"==typeof e&&e.length>0}function u(t){var e={},r={};switch(t.type){case\"circle\":n.extendFlat(r,{\"circle-radius\":t.circle.radius,\"circle-color\":t.color,\"circle-opacity\":t.opacity});break;case\"line\":n.extendFlat(r,{\"line-width\":t.line.width,\"line-color\":t.color,\"line-opacity\":t.opacity,\"line-dasharray\":t.line.dash});break;case\"fill\":n.extendFlat(r,{\"fill-color\":t.color,\"fill-outline-color\":t.fill.outlinecolor,\"fill-opacity\":t.opacity});break;case\"symbol\":var i=t.symbol,o=a(i.textposition,i.iconsize);n.extendFlat(e,{\"icon-image\":i.icon+\"-15\",\"icon-size\":i.iconsize/10,\"text-field\":i.text,\"text-size\":i.textfont.size,\"text-anchor\":o.anchor,\"text-offset\":o.offset,\"symbol-placement\":i.placement}),n.extendFlat(r,{\"icon-color\":t.color,\"text-color\":i.textfont.color,\"text-opacity\":t.opacity});break;case\"raster\":n.extendFlat(r,{\"raster-fade-duration\":0,\"raster-opacity\":t.opacity})}return{layout:e,paint:r}}l.update=function(t){this.visible?this.needsNewImage(t)?this.updateImage(t):this.needsNewSource(t)?(this.removeLayer(),this.updateSource(t),this.updateLayer(t)):this.needsNewLayer(t)?this.updateLayer(t):this.updateStyle(t):(this.updateSource(t),this.updateLayer(t)),this.visible=c(t)},l.needsNewImage=function(t){return this.subplot.map.getSource(this.idSource)&&\"image\"===this.sourceType&&\"image\"===t.sourcetype&&(this.source!==t.source||JSON.stringify(this.coordinates)!==JSON.stringify(t.coordinates))},l.needsNewSource=function(t){return this.sourceType!==t.sourcetype||JSON.stringify(this.source)!==JSON.stringify(t.source)||this.layerType!==t.type},l.needsNewLayer=function(t){return this.layerType!==t.type||this.below!==this.subplot.belowLookup[\"layout-\"+this.index]},l.lookupBelow=function(){return this.subplot.belowLookup[\"layout-\"+this.index]},l.updateImage=function(t){this.subplot.map.getSource(this.idSource).updateImage({url:t.source,coordinates:t.coordinates});var e=this.findFollowingMapboxLayerId(this.lookupBelow());null!==e&&this.subplot.map.moveLayer(this.idLayer,e)},l.updateSource=function(t){var e=this.subplot.map;if(e.getSource(this.idSource)&&e.removeSource(this.idSource),this.sourceType=t.sourcetype,this.source=t.source,c(t)){var r=function(t){var e,r=t.sourcetype,n=t.source,a={type:r};\"geojson\"===r?e=\"data\":\"vector\"===r?e=\"string\"==typeof n?\"url\":\"tiles\":\"raster\"===r?(e=\"tiles\",a.tileSize=256):\"image\"===r&&(e=\"url\",a.coordinates=t.coordinates);a[e]=n,t.sourceattribution&&(a.attribution=i(t.sourceattribution));return a}(t);e.addSource(this.idSource,r)}},l.findFollowingMapboxLayerId=function(t){if(\"traces\"===t)for(var e=this.subplot.getMapLayers(),r=0;r<e.length;r++){var n=e[r].id;if(\"string\"==typeof n&&0===n.indexOf(o.traceLayerPrefix)){t=n;break}}return t},l.updateLayer=function(t){var e=this.subplot,r=u(t),n=this.lookupBelow(),i=this.findFollowingMapboxLayerId(n);this.removeLayer(),c(t)&&e.addLayer({id:this.idLayer,source:this.idSource,\"source-layer\":t.sourcelayer||\"\",type:t.type,minzoom:t.minzoom,maxzoom:t.maxzoom,layout:r.layout,paint:r.paint},i),this.layerType=t.type,this.below=n},l.updateStyle=function(t){if(c(t)){var e=u(t);this.subplot.setOptions(this.idLayer,\"setLayoutProperty\",e.layout),this.subplot.setOptions(this.idLayer,\"setPaintProperty\",e.paint)}},l.removeLayer=function(){var t=this.subplot.map;t.getLayer(this.idLayer)&&t.removeLayer(this.idLayer)},l.dispose=function(){var t=this.subplot.map;t.getLayer(this.idLayer)&&t.removeLayer(this.idLayer),t.getSource(this.idSource)&&t.removeSource(this.idSource)},e.exports=function(t,e,r){var n=new s(t,e);return n.update(r),n}},{\"../../lib\":503,\"../../lib/svg_text_utils\":529,\"./constants\":611,\"./convert_text_opts\":612}],615:[function(t,e,r){\"use strict\";var n=t(\"../../lib\"),i=t(\"../../components/color\").defaultLine,a=t(\"../domain\").attributes,o=t(\"../font_attributes\"),s=t(\"../../traces/scatter/attributes\").textposition,l=t(\"../../plot_api/edit_types\").overrideAll,c=t(\"../../plot_api/plot_template\").templatedArray,u=t(\"./constants\"),f=o({});f.family.dflt=\"Open Sans Regular, Arial Unicode MS 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e,r,s=this,c=s.isSmith,u=s.gd,f=s.layers,h=t._zoomlayer,p=S.MINZOOM,d=S.OFFEDGE,m=s.radius,x=s.innerRadius,T=s.cx,k=s.cy,A=s.cxx,M=s.cyy,L=s.sectorInRad,C=s.vangles,P=s.radialAxis,I=E.clampTiny,O=E.findXYatLength,z=E.findEnclosingVertexAngles,D=S.cornerHalfWidth,R=S.cornerLen/2,F=g.makeDragger(f,\"path\",\"maindrag\",!1===t.dragmode?\"none\":\"crosshair\");n.select(F).attr(\"d\",s.pathSubplot()).attr(\"transform\",l(T,k)),F.onmousemove=function(t){y.hover(u,t,s.id),u._fullLayout._lasthover=F,u._fullLayout._hoversubplot=s.id},F.onmouseout=function(t){u._dragging||v.unhover(u,t)};var B,N,j,U,V,H,q,G,Y,W={element:F,gd:u,subplot:s.id,plotinfo:{id:s.id,xaxis:s.xaxis,yaxis:s.yaxis},xaxes:[s.xaxis],yaxes:[s.yaxis]};function X(t,e){return Math.sqrt(t*t+e*e)}function Z(t,e){return X(t-A,e-M)}function J(t,e){return Math.atan2(M-e,t-A)}function K(t,e){return[t*Math.cos(e),t*Math.sin(-e)]}function Q(t,e){if(0===t)return s.pathSector(2*D);var 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O,z,D,B=g.makeRectDragger(u,T,\"crosshair\",-x,-x,y,y),N={element:B,gd:c};!1===t.dragmode&&(N.dragmode=!1),V(n.select(B),m.visible&&h<f,{transform:l(b,_)}),N.prepFn=function(){O=null,z=null,D=null,N.moveFn=j,N.doneFn=H,w(c)},N.clampFn=function(t,e){return Math.sqrt(t*t+e*e)<S.MINDRAG&&(t=0,e=0),[t,e]},v.init(N)}function j(t,e){if(O)O(t,e);else{var n=[t,-e],a=[Math.cos(M),Math.sin(M)],s=Math.abs(o.dot(n,a)/Math.sqrt(o.dot(n,n)));isNaN(s)||(O=s<.5?q:G)}var l={};!function(t){null!==z?t[i.id+\".radialaxis.angle\"]=z:null!==D&&(t[i.id+\".radialaxis.range[\"+r+\"]\"]=D)}(l),c.emit(\"plotly_relayouting\",l)}function H(){null!==z?a.call(\"_guiRelayout\",c,i.id+\".radialaxis.angle\",z):null!==D&&a.call(\"_guiRelayout\",c,i.id+\".radialaxis.range[\"+r+\"]\",D)}function q(t,e){if(0!==r){var n=b+t,a=_+e;z=Math.atan2(d-a,n-p),i.vangles&&(z=U(z,i.vangles)),z=F(z);var o=l(p,d)+s(-z);u[\"radial-axis\"].attr(\"transform\",o),u[\"radial-line\"].select(\"line\").attr(\"transform\",o);var 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e=this.graphDiv,r=t[this.id],n=this.clipId=\"clip\"+this.layoutId+this.id,i=this.clipIdRelative=\"clip-relative\"+this.layoutId+this.id;this.clipDef=o.ensureSingleById(t._clips,\"clipPath\",n,(function(t){t.append(\"path\").attr(\"d\",\"M0,0Z\")})),this.clipDefRelative=o.ensureSingleById(t._clips,\"clipPath\",i,(function(t){t.append(\"path\").attr(\"d\",\"M0,0Z\")})),this.plotContainer=o.ensureSingle(this.container,\"g\",this.id),this.updateLayers(r),u.setClipUrl(this.layers.backplot,n,e),u.setClipUrl(this.layers.grids,n,e)},S.updateLayers=function(t){var e=this.layers,r=[\"draglayer\",\"plotbg\",\"backplot\",\"grids\"];\"below traces\"===t.aaxis.layer&&r.push(\"aaxis\",\"aline\"),\"below traces\"===t.baxis.layer&&r.push(\"baxis\",\"bline\"),\"below traces\"===t.caxis.layer&&r.push(\"caxis\",\"cline\"),r.push(\"frontplot\"),\"above traces\"===t.aaxis.layer&&r.push(\"aaxis\",\"aline\"),\"above traces\"===t.baxis.layer&&r.push(\"baxis\",\"bline\"),\"above 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r,n,i,a,o,l,p=this,d=t.domain,m=(d.x[0]+d.x[1])/2,g=(d.y[0]+d.y[1])/2,v=d.x[1]-d.x[0],y=d.y[1]-d.y[0],x=v*e.w,b=y*e.h,_=t.sum,w=t.aaxis.min,T=t.baxis.min,k=t.caxis.min;x>E*b?i=(a=b)*E:a=(i=x)/E,o=v*i/x,l=y*a/b,r=e.l+e.w*m-i/2,n=e.t+e.h*(1-g)-a/2,p.x0=r,p.y0=n,p.w=i,p.h=a,p.sum=_,p.xaxis={type:\"linear\",range:[w+2*k-_,_-w-2*T],domain:[m-o/2,m+o/2],_id:\"x\"},f(p.xaxis,p.graphDiv._fullLayout),p.xaxis.setScale(),p.xaxis.isPtWithinRange=function(t){return t.a>=p.aaxis.range[0]&&t.a<=p.aaxis.range[1]&&t.b>=p.baxis.range[1]&&t.b<=p.baxis.range[0]&&t.c>=p.caxis.range[1]&&t.c<=p.caxis.range[0]},p.yaxis={type:\"linear\",range:[w,_-T-k],domain:[g-l/2,g+l/2],_id:\"y\"},f(p.yaxis,p.graphDiv._fullLayout),p.yaxis.setScale(),p.yaxis.isPtWithinRange=function(){return!0};var A=p.yaxis.domain[0],M=p.aaxis=h({},t.aaxis,{range:[w,_-T-k],side:\"left\",tickangle:(+t.aaxis.tickangle||0)-30,domain:[A,A+l*E],anchor:\"free\",position:0,_id:\"y\",_length:i});f(M,p.graphDiv._fullLayout),M.setScale();var 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D=s(r+i/2,n)+\"rotate(-30)\"+s(0,-L._offset);p.layers.caxis.attr(\"transform\",D),p.layers.cgrid.attr(\"transform\",D),p.drawAxes(!0),p.layers.aline.select(\"path\").attr(\"d\",M.showline?\"M\"+r+\",\"+(n+a)+\"l\"+i/2+\",-\"+a:\"M0,0\").call(c.stroke,M.linecolor||\"#000\").style(\"stroke-width\",(M.linewidth||0)+\"px\"),p.layers.bline.select(\"path\").attr(\"d\",S.showline?\"M\"+r+\",\"+(n+a)+\"h\"+i:\"M0,0\").call(c.stroke,S.linecolor||\"#000\").style(\"stroke-width\",(S.linewidth||0)+\"px\"),p.layers.cline.select(\"path\").attr(\"d\",L.showline?\"M\"+(r+i/2)+\",\"+n+\"l\"+i/2+\",\"+a:\"M0,0\").call(c.stroke,L.linecolor||\"#000\").style(\"stroke-width\",(L.linewidth||0)+\"px\"),p.graphDiv._context.staticPlot||p.initInteractions(),u.setClipUrl(p.layers.frontplot,p._hasClipOnAxisFalse?null:p.clipId,p.graphDiv)},S.drawAxes=function(t){var 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L=A.MINZOOM/2+.87,C=\"m-0.87,.5h\"+L+\"v3h-\"+(L+5.2)+\"l\"+(L/2+2.6)+\",-\"+(.87*L+4.5)+\"l2.6,1.5l-\"+L/2+\",\"+.87*L+\"Z\",P=\"m0.87,.5h-\"+L+\"v3h\"+(L+5.2)+\"l-\"+(L/2+2.6)+\",-\"+(.87*L+4.5)+\"l-2.6,1.5l\"+L/2+\",\"+.87*L+\"Z\",I=\"m0,1l\"+L/2+\",\"+.87*L+\"l2.6,-1.5l-\"+(L/2+2.6)+\",-\"+(.87*L+4.5)+\"l-\"+(L/2+2.6)+\",\"+(.87*L+4.5)+\"l2.6,1.5l\"+L/2+\",-\"+.87*L+\"Z\",O=!0;function z(t){n.select(t).selectAll(\".zoombox,.js-zoombox-backdrop,.js-zoombox-menu,.zoombox-corners\").remove()}S.clearSelect=function(){k(this.dragOptions),T(this.dragOptions.gd)},S.initInteractions=function(){var t,e,r,n,f,h,p,d,v,b,T,k,M=this,S=M.layers.plotbg.select(\"path\").node(),L=M.graphDiv,D=L._fullLayout._zoomlayer;function R(t){var e={};return e[M.id+\".aaxis.min\"]=t.a,e[M.id+\".baxis.min\"]=t.b,e[M.id+\".caxis.min\"]=t.c,e}function F(t,e){var 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r=t/M.xaxis._m,n=e/M.yaxis._m,i=[(p={a:f.a-n,b:f.b+(r+n)/2,c:f.c-(r-n)/2}).a,p.b,p.c].sort(o.sorterAsc),a=i.indexOf(p.a),l=i.indexOf(p.b),c=i.indexOf(p.c);i[0]<0&&(i[1]+i[0]/2<0?(i[2]+=i[0]+i[1],i[0]=i[1]=0):(i[2]+=i[0]/2,i[1]+=i[0]/2,i[0]=0),p={a:i[a],b:i[l],c:i[c]},e=(f.a-p.a)*M.yaxis._m,t=(f.c-p.c-f.b+p.b)*M.xaxis._m);var h=s(M.x0+t,M.y0+e);M.plotContainer.selectAll(\".scatterlayer,.maplayer\").attr(\"transform\",h);var d=s(-t,-e);M.clipDefRelative.select(\"path\").attr(\"transform\",d),M.aaxis.range=[p.a,M.sum-p.b-p.c],M.baxis.range=[M.sum-p.a-p.c,p.b],M.caxis.range=[M.sum-p.a-p.b,p.c],M.drawAxes(!1),M._hasClipOnAxisFalse&&M.plotContainer.select(\".scatterlayer\").selectAll(\".trace\").call(u.hideOutsideRangePoints,M),L.emit(\"plotly_relayouting\",R(p))}function 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n=t(\"../../components/colorscale/defaults\"),i=t(\"./label_defaults\");e.exports=function(t,e,r,a,o){var s,l=r(\"contours.coloring\"),c=\"\";\"fill\"===l&&(s=r(\"contours.showlines\")),!1!==s&&(\"lines\"!==l&&(c=r(\"line.color\",\"#000\")),r(\"line.width\",.5),r(\"line.dash\")),\"none\"!==l&&(!0!==t.showlegend&&(e.showlegend=!1),e._dfltShowLegend=!1,n(t,e,a,r,{prefix:\"\",cLetter:\"z\"})),r(\"line.smoothing\"),i(r,a,c,o)}},{\"../../components/colorscale/defaults\":376,\"./label_defaults\":750}],757:[function(t,e,r){\"use strict\";var n=t(\"../heatmap/attributes\"),i=t(\"../contour/attributes\"),a=t(\"../../components/colorscale/attributes\"),o=t(\"../../lib/extend\").extendFlat,s=i.contours;e.exports=o({carpet:{valType:\"string\",editType:\"calc\"},z:n.z,a:n.x,a0:n.x0,da:n.dx,b:n.y,b0:n.y0,db:n.dy,text:n.text,hovertext:n.hovertext,transpose:n.transpose,atype:n.xtype,btype:n.ytype,fillcolor:i.fillcolor,autocontour:i.autocontour,ncontours:i.ncontours,contours:{type:s.type,start:s.start,end:s.end,size:s.size,coloring:{valType:\"enumerated\",values:[\"fill\",\"lines\",\"none\"],dflt:\"fill\",editType:\"calc\"},showlines:s.showlines,showlabels:s.showlabels,labelfont:s.labelfont,labelformat:s.labelformat,operation:s.operation,value:s.value,editType:\"calc\",impliedEdits:{autocontour:!1}},line:{color:i.line.color,width:i.line.width,dash:i.line.dash,smoothing:i.line.smoothing,editType:\"plot\"},transforms:void 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n=t(\"../pie/layout_attributes\").hiddenlabels;e.exports={hiddenlabels:n,funnelareacolorway:{valType:\"colorlist\",editType:\"calc\"},extendfunnelareacolors:{valType:\"boolean\",dflt:!0,editType:\"calc\"}}},{\"../pie/layout_attributes\":908}],789:[function(t,e,r){\"use strict\";var n=t(\"../../lib\"),i=t(\"./layout_attributes\");e.exports=function(t,e){function r(r,a){return n.coerce(t,e,i,r,a)}r(\"hiddenlabels\"),r(\"funnelareacolorway\",e.colorway),r(\"extendfunnelareacolors\")}},{\"../../lib\":503,\"./layout_attributes\":788}],790:[function(t,e,r){\"use strict\";var 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n=t(\"../scatter/attributes\"),i=t(\"../../plots/attributes\"),a=t(\"../../plots/font_attributes\"),o=t(\"../../plots/cartesian/axis_format_attributes\").axisHoverFormat,s=t(\"../../plots/template_attributes\").hovertemplateAttrs,l=t(\"../../plots/template_attributes\").texttemplateAttrs,c=t(\"../../components/colorscale/attributes\"),u=t(\"../../lib/extend\").extendFlat;e.exports=u({z:{valType:\"data_array\",editType:\"calc\"},x:u({},n.x,{impliedEdits:{xtype:\"array\"}}),x0:u({},n.x0,{impliedEdits:{xtype:\"scaled\"}}),dx:u({},n.dx,{impliedEdits:{xtype:\"scaled\"}}),y:u({},n.y,{impliedEdits:{ytype:\"array\"}}),y0:u({},n.y0,{impliedEdits:{ytype:\"scaled\"}}),dy:u({},n.dy,{impliedEdits:{ytype:\"scaled\"}}),xperiod:u({},n.xperiod,{impliedEdits:{xtype:\"scaled\"}}),yperiod:u({},n.yperiod,{impliedEdits:{ytype:\"scaled\"}}),xperiod0:u({},n.xperiod0,{impliedEdits:{xtype:\"scaled\"}}),yperiod0:u({},n.yperiod0,{impliedEdits:{ytype:\"scaled\"}}),xperiodalignment:u({},n.xperiodalignment,{impliedEdits:{xtype:\"scaled\"}}),yperiodalignment:u({},n.yperiodalignment,{impliedEdits:{ytype:\"scaled\"}}),text:{valType:\"data_array\",editType:\"calc\"},hovertext:{valType:\"data_array\",editType:\"calc\"},transpose:{valType:\"boolean\",dflt:!1,editType:\"calc\"},xtype:{valType:\"enumerated\",values:[\"array\",\"scaled\"],editType:\"calc+clearAxisTypes\"},ytype:{valType:\"enumerated\",values:[\"array\",\"scaled\"],editType:\"calc+clearAxisTypes\"},zsmooth:{valType:\"enumerated\",values:[\"fast\",\"best\",!1],dflt:!1,editType:\"calc\"},hoverongaps:{valType:\"boolean\",dflt:!0,editType:\"none\"},connectgaps:{valType:\"boolean\",editType:\"calc\"},xgap:{valType:\"number\",dflt:0,min:0,editType:\"plot\"},ygap:{valType:\"number\",dflt:0,min:0,editType:\"plot\"},xhoverformat:o(\"x\"),yhoverformat:o(\"y\"),zhoverformat:o(\"z\",1),hovertemplate:s(),texttemplate:l({arrayOk:!1,editType:\"plot\"},{keys:[\"x\",\"y\",\"z\",\"text\"]}),textfont:a({editType:\"plot\",autoSize:!0,autoColor:!0,colorEditType:\"style\"}),showlegend:u({},i.showlegend,{dflt:!1})},{transforms:void 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W=_.selectAll(\"g.gauge-outline\").data([x]);W.enter().append(\"g\").classed(\"gauge-outline\",!0).append(\"path\"),W.select(\"path\").call(P).call(T),W.exit().remove()}(t,0,e,{radius:U,innerRadius:V,gauge:Y,layer:W,size:B,gaugeBg:C,gaugeOutline:P,transitionOpts:r,onComplete:g});var X=O.selectAll(\"g.bullet\").data(R?e:[]);X.exit().remove();var Z=O.selectAll(\"g.bulletaxis\").data(R?e:[]);Z.exit().remove(),R&&function(t,e,r,n){var i,a,o,s,c,u=r[0].trace,f=n.gauge,p=n.layer,m=n.gaugeBg,g=n.gaugeOutline,v=n.size,x=u.domain,b=n.transitionOpts,_=n.onComplete;f.enter().append(\"g\").classed(\"bullet\",!0),f.attr(\"transform\",l(v.l,v.t)),p.enter().append(\"g\").classed(\"bulletaxis\",!0).classed(\"crisp\",!0),p.selectAll(\"g.xbulletaxistick,path,text\").remove();var A=v.h,M=u.gauge.bar.thickness*A,S=x.x[0],E=x.x[0]+(x.x[1]-x.x[0])*(u._hasNumber||u._hasDelta?1-h.bulletNumberDomainSize:1);(i=k(t,u.gauge.axis))._id=\"xbulletaxis\",i.domain=[S,E],i.setScale(),a=d.calcTicks(i),o=d.makeTransTickFn(i),s=d.getTickSigns(i)[2],c=v.t+v.h,i.visible&&(d.drawTicks(t,i,{vals:\"inside\"===i.ticks?d.clipEnds(i,a):a,layer:p,path:d.makeTickPath(i,c,s),transFn:o}),d.drawLabels(t,i,{vals:a,layer:p,transFn:o,labelFns:d.makeLabelFns(i,c)}));function L(t){t.attr(\"width\",(function(t){return Math.max(0,i.c2p(t.range[1])-i.c2p(t.range[0]))})).attr(\"x\",(function(t){return i.c2p(t.range[0])})).attr(\"y\",(function(t){return.5*(1-t.thickness)*A})).attr(\"height\",(function(t){return t.thickness*A}))}var C=[m].concat(u.gauge.steps),P=f.selectAll(\"g.bg-bullet\").data(C);P.enter().append(\"g\").classed(\"bg-bullet\",!0).append(\"rect\"),P.select(\"rect\").call(L).call(T),P.exit().remove();var 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n=t(\"../../components/colorscale/attributes\"),i=t(\"../../plots/cartesian/axis_format_attributes\").axisHoverFormat,a=t(\"../../plots/template_attributes\").hovertemplateAttrs,o=t(\"../surface/attributes\"),s=t(\"../../plots/attributes\"),l=t(\"../../lib/extend\").extendFlat;e.exports=l({x:{valType:\"data_array\",editType:\"calc+clearAxisTypes\"},y:{valType:\"data_array\",editType:\"calc+clearAxisTypes\"},z:{valType:\"data_array\",editType:\"calc+clearAxisTypes\"},i:{valType:\"data_array\",editType:\"calc\"},j:{valType:\"data_array\",editType:\"calc\"},k:{valType:\"data_array\",editType:\"calc\"},text:{valType:\"string\",dflt:\"\",arrayOk:!0,editType:\"calc\"},hovertext:{valType:\"string\",dflt:\"\",arrayOk:!0,editType:\"calc\"},hovertemplate:a({editType:\"calc\"}),xhoverformat:i(\"x\"),yhoverformat:i(\"y\"),zhoverformat:i(\"z\"),delaunayaxis:{valType:\"enumerated\",values:[\"x\",\"y\",\"z\"],dflt:\"z\",editType:\"calc\"},alphahull:{valType:\"number\",dflt:-1,editType:\"calc\"},intensity:{valType:\"data_array\",editType:\"calc\"},intensitymode:{valType:\"enumerated\",values:[\"vertex\",\"cell\"],dflt:\"vertex\",editType:\"calc\"},color:{valType:\"color\",editType:\"calc\"},vertexcolor:{valType:\"data_array\",editType:\"calc\"},facecolor:{valType:\"data_array\",editType:\"calc\"},transforms:void 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n=t(\"../../components/colorscale/calc\");e.exports=function(t,e){e.intensity&&n(t,e,{vals:e.intensity,containerStr:\"\",cLetter:\"c\"})}},{\"../../components/colorscale/calc\":374}],869:[function(t,e,r){\"use strict\";var n=t(\"../../../stackgl_modules\").gl_mesh3d,i=t(\"../../../stackgl_modules\").delaunay_triangulate,a=t(\"../../../stackgl_modules\").alpha_shape,o=t(\"../../../stackgl_modules\").convex_hull,s=t(\"../../lib/gl_format_color\").parseColorScale,l=t(\"../../lib/str2rgbarray\"),c=t(\"../../components/colorscale\").extractOpts,u=t(\"../../plots/gl3d/zip3\");function f(t,e,r){this.scene=t,this.uid=r,this.mesh=e,this.name=\"\",this.color=\"#fff\",this.data=null,this.showContour=!1}var h=f.prototype;function p(t){for(var e=[],r=t.length,n=0;n<r;n++)e[n]=l(t[n]);return e}function d(t,e,r,n){for(var i=[],a=e.length,o=0;o<a;o++)i[o]=t.d2l(e[o],0,n)*r;return i}function m(t){for(var e=[],r=t.length,n=0;n<r;n++)e[n]=Math.round(t[n]);return e}function g(t,e){for(var r=t.length,n=0;n<r;n++)if(t[n]<=-.5||t[n]>=e-.5)return!1;return!0}h.handlePick=function(t){if(t.object===this.mesh){var e=t.index=t.data.index;t.data._cellCenter?t.traceCoordinate=t.data.dataCoordinate:t.traceCoordinate=[this.data.x[e],this.data.y[e],this.data.z[e]];var r=this.data.hovertext||this.data.text;return Array.isArray(r)&&void 0!==r[e]?t.textLabel=r[e]:r&&(t.textLabel=r),!0}},h.update=function(t){var e=this.scene,r=e.fullSceneLayout;this.data=t;var n,f=t.x.length,h=u(d(r.xaxis,t.x,e.dataScale[0],t.xcalendar),d(r.yaxis,t.y,e.dataScale[1],t.ycalendar),d(r.zaxis,t.z,e.dataScale[2],t.zcalendar));if(t.i&&t.j&&t.k){if(t.i.length!==t.j.length||t.j.length!==t.k.length||!g(t.i,f)||!g(t.j,f)||!g(t.k,f))return;n=u(m(t.i),m(t.j),m(t.k))}else n=0===t.alphahull?o(h):t.alphahull>0?a(t.alphahull,h):function(t,e){for(var r=[\"x\",\"y\",\"z\"].indexOf(t),n=[],a=e.length,o=0;o<a;o++)n[o]=[e[o][(r+1)%3],e[o][(r+2)%3]];return i(n)}(t.delaunayaxis,h);var v={positions:h,cells:n,lightPosition:[t.lightposition.x,t.lightposition.y,t.lightposition.z],ambient:t.lighting.ambient,diffuse:t.lighting.diffuse,specular:t.lighting.specular,roughness:t.lighting.roughness,fresnel:t.lighting.fresnel,vertexNormalsEpsilon:t.lighting.vertexnormalsepsilon,faceNormalsEpsilon:t.lighting.facenormalsepsilon,opacity:t.opacity,contourEnable:t.contour.show,contourColor:l(t.contour.color).slice(0,3),contourWidth:t.contour.width,useFacetNormals:t.flatshading};if(t.intensity){var y=c(t);this.color=\"#fff\";var x=t.intensitymode;v[x+\"Intensity\"]=t.intensity,v[x+\"IntensityBounds\"]=[y.min,y.max],v.colormap=s(t)}else t.vertexcolor?(this.color=t.vertexcolor[0],v.vertexColors=p(t.vertexcolor)):t.facecolor?(this.color=t.facecolor[0],v.cellColors=p(t.facecolor)):(this.color=t.color,v.meshColor=l(t.color));this.mesh.update(v)},h.dispose=function(){this.scene.glplot.remove(this.mesh),this.mesh.dispose()},e.exports=function(t,e){var r=t.glplot.gl,i=n({gl:r}),a=new 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n=t(\"../../lib\").extendFlat,i=t(\"../scatter/attributes\"),a=t(\"../../plots/cartesian/axis_format_attributes\").axisHoverFormat,o=t(\"../../components/drawing/attributes\").dash,s=t(\"../../components/fx/attributes\"),l=t(\"../../constants/delta.js\"),c=l.INCREASING.COLOR,u=l.DECREASING.COLOR,f=i.line;function 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E=S.enter().append(\"rect\").attr(\"class\",\"bandrect\").attr(\"stroke-opacity\",0).attr(\"fill\",(function(t){return t.color})).attr(\"fill-opacity\",0);S.attr(\"fill\",(function(t){return t.color})).attr(\"width\",(function(t){return t.width})).attr(\"height\",(function(t){return t.height})).attr(\"y\",(function(t){return t.y})).attr(\"cursor\",(function(t){return\"fixed\"===t.parcatsViewModel.arrangement?\"default\":\"perpendicular\"===t.parcatsViewModel.arrangement?\"ns-resize\":\"move\"})),k(E),S.exit().remove(),M.append(\"text\").attr(\"class\",\"catlabel\").attr(\"pointer-events\",\"none\");var z=e._fullLayout.paper_bgcolor;A.select(\"text.catlabel\").attr(\"text-anchor\",(function(t){return d(t)?\"start\":\"end\"})).attr(\"alignment-baseline\",\"middle\").style(\"text-shadow\",f.makeTextShadow(z)).style(\"fill\",\"rgb(0, 0, 0)\").attr(\"x\",(function(t){return d(t)?t.width+5:-5})).attr(\"y\",(function(t){return t.height/2})).text((function(t){return t.model.categoryLabel})).each((function(t){c.font(n.select(this),t.parcatsViewModel.categorylabelfont),f.convertToTspans(n.select(this),e)})),M.append(\"text\").attr(\"class\",\"dimlabel\"),A.select(\"text.dimlabel\").attr(\"text-anchor\",\"middle\").attr(\"alignment-baseline\",\"baseline\").attr(\"cursor\",(function(t){return\"fixed\"===t.parcatsViewModel.arrangement?\"default\":\"ew-resize\"})).attr(\"x\",(function(t){return t.width/2})).attr(\"y\",-5).text((function(t,e){return 0===e?t.parcatsViewModel.model.dimensions[t.model.dimensionInd].dimensionLabel:null})).each((function(t){c.font(n.select(this),t.parcatsViewModel.labelfont)})),A.selectAll(\"rect.bandrect\").on(\"mouseover\",L).on(\"mouseout\",C),A.exit().remove(),w.call(n.behavior.drag().origin((function(t){return{x:t.x,y:0}})).on(\"dragstart\",P).on(\"drag\",I).on(\"dragend\",O)),u.each((function(t){t.traceSelection=n.select(this),t.pathSelection=n.select(this).selectAll(\"g.paths\").selectAll(\"path.path\"),t.dimensionSelection=n.select(this).selectAll(\"g.dimensions\").selectAll(\"g.dimension\")})),u.exit().remove()}function p(t){return t.key}function d(t){var e=t.parcatsViewModel.dimensions.length,r=t.parcatsViewModel.dimensions[e-1].model.dimensionInd;return t.model.dimensionInd===r}function m(t,e){return t.model.rawColor>e.model.rawColor?1:t.model.rawColor<e.model.rawColor?-1:0}function g(t){if(!t.parcatsViewModel.dragDimension&&-1===t.parcatsViewModel.hoverinfoItems.indexOf(\"skip\")){s.raiseToTop(this),w(n.select(this));var e=y(t),r=x(t);if(t.parcatsViewModel.graphDiv.emit(\"plotly_hover\",{points:e,event:n.event,constraints:r}),-1===t.parcatsViewModel.hoverinfoItems.indexOf(\"none\")){var i,a,l,c=n.mouse(this)[0],f=t.parcatsViewModel.graphDiv,h=t.parcatsViewModel.trace,p=f._fullLayout,d=p._paperdiv.node().getBoundingClientRect(),m=t.parcatsViewModel.graphDiv.getBoundingClientRect();for(l=0;l<t.leftXs.length-1;l++)if(t.leftXs[l]+t.dimWidths[l]-2<=c&&c<=t.leftXs[l+1]+2){var g=t.parcatsViewModel.dimensions[l],v=t.parcatsViewModel.dimensions[l+1];i=(g.x+g.width+v.x)/2,a=(t.topYs[l]+t.topYs[l+1]+t.height)/2;break}var b=t.parcatsViewModel.x+i,_=t.parcatsViewModel.y+a,T=u.mostReadable(t.model.color,[\"black\",\"white\"]),k=t.model.count,A=k/t.parcatsViewModel.model.count,M={countLabel:k,probabilityLabel:A.toFixed(3)},S=[];-1!==t.parcatsViewModel.hoverinfoItems.indexOf(\"count\")&&S.push([\"Count:\",M.countLabel].join(\" \")),-1!==t.parcatsViewModel.hoverinfoItems.indexOf(\"probability\")&&S.push([\"P:\",M.probabilityLabel].join(\" \"));var E=S.join(\"<br>\"),L=n.mouse(f)[0];o.loneHover({trace:h,x:b-d.left+m.left,y:_-d.top+m.top,text:E,color:t.model.color,borderColor:\"black\",fontFamily:'Monaco, \"Courier New\", monospace',fontSize:10,fontColor:T,idealAlign:L<b?\"right\":\"left\",hovertemplate:(h.line||{}).hovertemplate,hovertemplateLabels:M,eventData:[{data:h._input,fullData:h,count:k,probability:A}]},{container:p._hoverlayer.node(),outerContainer:p._paper.node(),gd:f})}}}function v(t){if(!t.parcatsViewModel.dragDimension&&(_(n.select(this)),o.loneUnhover(t.parcatsViewModel.graphDiv._fullLayout._hoverlayer.node()),t.parcatsViewModel.pathSelection.sort(m),-1===t.parcatsViewModel.hoverinfoItems.indexOf(\"skip\"))){var e=y(t),r=x(t);t.parcatsViewModel.graphDiv.emit(\"plotly_unhover\",{points:e,event:n.event,constraints:r})}}function y(t){for(var e=[],r=z(t.parcatsViewModel),n=0;n<t.model.valueInds.length;n++){var i=t.model.valueInds[n];e.push({curveNumber:r,pointNumber:i})}return e}function x(t){for(var e={},r=t.parcatsViewModel.model.dimensions,n=0;n<r.length;n++){var i=r[n],a=i.categories[t.model.categoryInds[n]];e[i.containerInd]=a.categoryValue}return void 0!==t.model.rawColor&&(e.color=t.model.rawColor),e}function b(t){if(-1===t.parcatsViewModel.hoverinfoItems.indexOf(\"skip\")){var e=y(t),r=x(t);t.parcatsViewModel.graphDiv.emit(\"plotly_click\",{points:e,event:n.event,constraints:r})}}function _(t){t.attr(\"fill\",(function(t){return t.model.color})).attr(\"fill-opacity\",.6).attr(\"stroke\",\"lightgray\").attr(\"stroke-width\",.2).attr(\"stroke-opacity\",1)}function w(t){t.attr(\"fill-opacity\",.8).attr(\"stroke\",(function(t){return u.mostReadable(t.model.color,[\"black\",\"white\"])})).attr(\"stroke-width\",.3)}function T(t){t.select(\"rect.catrect\").attr(\"stroke\",\"black\").attr(\"stroke-width\",1).attr(\"stroke-opacity\",1)}function k(t){t.attr(\"stroke\",\"black\").attr(\"stroke-width\",.2).attr(\"stroke-opacity\",1).attr(\"fill-opacity\",1)}function A(t){var e=t.parcatsViewModel.pathSelection,r=t.categoryViewModel.model.dimensionInd,n=t.categoryViewModel.model.categoryInd;return e.filter((function(e){return e.model.categoryInds[r]===n&&e.model.color===t.color}))}function M(t,e,r){var i=n.select(t).datum(),a=i.categoryViewModel.model,o=i.parcatsViewModel.graphDiv,s=n.select(t.parentNode).selectAll(\"rect.bandrect\"),l=[];s.each((function(t){A(t).each((function(t){Array.prototype.push.apply(l,y(t))}))}));var c={};c[a.dimensionInd]=a.categoryValue,o.emit(e,{points:l,event:r,constraints:c})}function S(t,e,r){var i=n.select(t).datum(),a=i.categoryViewModel.model,o=i.parcatsViewModel.graphDiv,s=A(i),l=[];s.each((function(t){Array.prototype.push.apply(l,y(t))}));var c={};c[a.dimensionInd]=a.categoryValue,void 0!==i.rawColor&&(c.color=i.rawColor),o.emit(e,{points:l,event:r,constraints:c})}function E(t,e,r){t._fullLayout._calcInverseTransform(t);var i,a,o=t._fullLayout._invScaleX,s=t._fullLayout._invScaleY,l=n.select(r.parentNode).select(\"rect.catrect\"),c=l.node().getBoundingClientRect(),u=l.datum(),f=u.parcatsViewModel,h=f.model.dimensions[u.model.dimensionInd],p=f.trace,d=c.top+c.height/2;f.dimensions.length>1&&h.displayInd===f.dimensions.length-1?(i=c.left,a=\"left\"):(i=c.left+c.width,a=\"right\");var m=u.model.count,g=u.model.categoryLabel,v=m/u.parcatsViewModel.model.count,y={countLabel:m,categoryLabel:g,probabilityLabel:v.toFixed(3)},x=[];-1!==u.parcatsViewModel.hoverinfoItems.indexOf(\"count\")&&x.push([\"Count:\",y.countLabel].join(\" \")),-1!==u.parcatsViewModel.hoverinfoItems.indexOf(\"probability\")&&x.push([\"P(\"+y.categoryLabel+\"):\",y.probabilityLabel].join(\" \"));var b=x.join(\"<br>\");return{trace:p,x:o*(i-e.left),y:s*(d-e.top),text:b,color:\"lightgray\",borderColor:\"black\",fontFamily:'Monaco, \"Courier New\", monospace',fontSize:12,fontColor:\"black\",idealAlign:a,hovertemplate:p.hovertemplate,hovertemplateLabels:y,eventData:[{data:p._input,fullData:p,count:m,category:g,probability:v}]}}function L(t){if(!t.parcatsViewModel.dragDimension&&-1===t.parcatsViewModel.hoverinfoItems.indexOf(\"skip\")){if(n.mouse(this)[1]<-1)return;var e,r=t.parcatsViewModel.graphDiv,i=r._fullLayout,a=i._paperdiv.node().getBoundingClientRect(),l=t.parcatsViewModel.hoveron;if(\"color\"===l?(!function(t){var e=n.select(t).datum(),r=A(e);w(r),r.each((function(){s.raiseToTop(this)})),n.select(t.parentNode).selectAll(\"rect.bandrect\").filter((function(t){return t.color===e.color})).each((function(){s.raiseToTop(this),n.select(this).attr(\"stroke\",\"black\").attr(\"stroke-width\",1.5)}))}(this),S(this,\"plotly_hover\",n.event)):(!function(t){n.select(t.parentNode).selectAll(\"rect.bandrect\").each((function(t){var e=A(t);w(e),e.each((function(){s.raiseToTop(this)}))})),n.select(t.parentNode).select(\"rect.catrect\").attr(\"stroke\",\"black\").attr(\"stroke-width\",2.5)}(this),M(this,\"plotly_hover\",n.event)),-1===t.parcatsViewModel.hoverinfoItems.indexOf(\"none\"))\"category\"===l?e=E(r,a,this):\"color\"===l?e=function(t,e,r){t._fullLayout._calcInverseTransform(t);var i,a,o=t._fullLayout._invScaleX,s=t._fullLayout._invScaleY,l=r.getBoundingClientRect(),c=n.select(r).datum(),f=c.categoryViewModel,h=f.parcatsViewModel,p=h.model.dimensions[f.model.dimensionInd],d=h.trace,m=l.y+l.height/2;h.dimensions.length>1&&p.displayInd===h.dimensions.length-1?(i=l.left,a=\"left\"):(i=l.left+l.width,a=\"right\");var g=f.model.categoryLabel,v=c.parcatsViewModel.model.count,y=0;c.categoryViewModel.bands.forEach((function(t){t.color===c.color&&(y+=t.count)}));var x=f.model.count,b=0;h.pathSelection.each((function(t){t.model.color===c.color&&(b+=t.model.count)}));var _=y/v,w=y/b,T=y/x,k={countLabel:v,categoryLabel:g,probabilityLabel:_.toFixed(3)},A=[];-1!==f.parcatsViewModel.hoverinfoItems.indexOf(\"count\")&&A.push([\"Count:\",k.countLabel].join(\" \")),-1!==f.parcatsViewModel.hoverinfoItems.indexOf(\"probability\")&&(A.push(\"P(color \\u2229 \"+g+\"): \"+k.probabilityLabel),A.push(\"P(\"+g+\" | color): \"+w.toFixed(3)),A.push(\"P(color | \"+g+\"): \"+T.toFixed(3)));var M=A.join(\"<br>\"),S=u.mostReadable(c.color,[\"black\",\"white\"]);return{trace:d,x:o*(i-e.left),y:s*(m-e.top),text:M,color:c.color,borderColor:\"black\",fontFamily:'Monaco, \"Courier New\", monospace',fontColor:S,fontSize:10,idealAlign:a,hovertemplate:d.hovertemplate,hovertemplateLabels:k,eventData:[{data:d._input,fullData:d,category:g,count:v,probability:_,categorycount:x,colorcount:b,bandcolorcount:y}]}}(r,a,this):\"dimension\"===l&&(e=function(t,e,r){var i=[];return n.select(r.parentNode.parentNode).selectAll(\"g.category\").select(\"rect.catrect\").each((function(){i.push(E(t,e,this))})),i}(r,a,this)),e&&o.loneHover(e,{container:i._hoverlayer.node(),outerContainer:i._paper.node(),gd:r})}}function C(t){var e=t.parcatsViewModel;if(!e.dragDimension&&(_(e.pathSelection),T(e.dimensionSelection.selectAll(\"g.category\")),k(e.dimensionSelection.selectAll(\"g.category\").selectAll(\"rect.bandrect\")),o.loneUnhover(e.graphDiv._fullLayout._hoverlayer.node()),e.pathSelection.sort(m),-1===e.hoverinfoItems.indexOf(\"skip\"))){\"color\"===t.parcatsViewModel.hoveron?S(this,\"plotly_unhover\",n.event):M(this,\"plotly_unhover\",n.event)}}function P(t){\"fixed\"!==t.parcatsViewModel.arrangement&&(t.dragDimensionDisplayInd=t.model.displayInd,t.initialDragDimensionDisplayInds=t.parcatsViewModel.model.dimensions.map((function(t){return t.displayInd})),t.dragHasMoved=!1,t.dragCategoryDisplayInd=null,n.select(this).selectAll(\"g.category\").select(\"rect.catrect\").each((function(e){var r=n.mouse(this)[0],i=n.mouse(this)[1];-2<=r&&r<=e.width+2&&-2<=i&&i<=e.height+2&&(t.dragCategoryDisplayInd=e.model.displayInd,t.initialDragCategoryDisplayInds=t.model.categories.map((function(t){return t.displayInd})),e.model.dragY=e.y,s.raiseToTop(this.parentNode),n.select(this.parentNode).selectAll(\"rect.bandrect\").each((function(e){e.y<i&&i<=e.y+e.height&&(t.potentialClickBand=this)})))})),t.parcatsViewModel.dragDimension=t,o.loneUnhover(t.parcatsViewModel.graphDiv._fullLayout._hoverlayer.node()))}function I(t){if(\"fixed\"!==t.parcatsViewModel.arrangement&&(t.dragHasMoved=!0,null!==t.dragDimensionDisplayInd)){var e=t.dragDimensionDisplayInd,r=e-1,i=e+1,a=t.parcatsViewModel.dimensions[e];if(null!==t.dragCategoryDisplayInd){var o=a.categories[t.dragCategoryDisplayInd];o.model.dragY+=n.event.dy;var s=o.model.dragY,l=o.model.displayInd,c=a.categories,u=c[l-1],f=c[l+1];void 0!==u&&s<u.y+u.height/2&&(o.model.displayInd=u.model.displayInd,u.model.displayInd=l),void 0!==f&&s+o.height>f.y+f.height/2&&(o.model.displayInd=f.model.displayInd,f.model.displayInd=l),t.dragCategoryDisplayInd=o.model.displayInd}if(null===t.dragCategoryDisplayInd||\"freeform\"===t.parcatsViewModel.arrangement){a.model.dragX=n.event.x;var h=t.parcatsViewModel.dimensions[r],p=t.parcatsViewModel.dimensions[i];void 0!==h&&a.model.dragX<h.x+h.width&&(a.model.displayInd=h.model.displayInd,h.model.displayInd=e),void 0!==p&&a.model.dragX+a.width>p.x&&(a.model.displayInd=p.model.displayInd,p.model.displayInd=t.dragDimensionDisplayInd),t.dragDimensionDisplayInd=a.model.displayInd}j(t.parcatsViewModel),N(t.parcatsViewModel),R(t.parcatsViewModel),D(t.parcatsViewModel)}}function O(t){if(\"fixed\"!==t.parcatsViewModel.arrangement&&null!==t.dragDimensionDisplayInd){n.select(this).selectAll(\"text\").attr(\"font-weight\",\"normal\");var e={},r=z(t.parcatsViewModel),i=t.parcatsViewModel.model.dimensions.map((function(t){return t.displayInd})),o=t.initialDragDimensionDisplayInds.some((function(t,e){return t!==i[e]}));o&&i.forEach((function(r,n){var i=t.parcatsViewModel.model.dimensions[n].containerInd;e[\"dimensions[\"+i+\"].displayindex\"]=r}));var s=!1;if(null!==t.dragCategoryDisplayInd){var l=t.model.categories.map((function(t){return t.displayInd}));if(s=t.initialDragCategoryDisplayInds.some((function(t,e){return t!==l[e]}))){var c=t.model.categories.slice().sort((function(t,e){return t.displayInd-e.displayInd})),u=c.map((function(t){return t.categoryValue})),f=c.map((function(t){return t.categoryLabel}));e[\"dimensions[\"+t.model.containerInd+\"].categoryarray\"]=[u],e[\"dimensions[\"+t.model.containerInd+\"].ticktext\"]=[f],e[\"dimensions[\"+t.model.containerInd+\"].categoryorder\"]=\"array\"}}if(-1===t.parcatsViewModel.hoverinfoItems.indexOf(\"skip\")&&!t.dragHasMoved&&t.potentialClickBand&&(\"color\"===t.parcatsViewModel.hoveron?S(t.potentialClickBand,\"plotly_click\",n.event.sourceEvent):M(t.potentialClickBand,\"plotly_click\",n.event.sourceEvent)),t.model.dragX=null,null!==t.dragCategoryDisplayInd)t.parcatsViewModel.dimensions[t.dragDimensionDisplayInd].categories[t.dragCategoryDisplayInd].model.dragY=null,t.dragCategoryDisplayInd=null;t.dragDimensionDisplayInd=null,t.parcatsViewModel.dragDimension=null,t.dragHasMoved=null,t.potentialClickBand=null,j(t.parcatsViewModel),N(t.parcatsViewModel),n.transition().duration(300).ease(\"cubic-in-out\").each((function(){R(t.parcatsViewModel,!0),D(t.parcatsViewModel,!0)})).each(\"end\",(function(){(o||s)&&a.restyle(t.parcatsViewModel.graphDiv,e,[r])}))}}function z(t){for(var e,r=t.graphDiv._fullData,n=0;n<r.length;n++)if(t.key===r[n].uid){e=n;break}return e}function D(t,e){var r;void 0===e&&(e=!1),t.pathSelection.data((function(t){return t.paths}),p),(r=t.pathSelection,e?r.transition():r).attr(\"d\",(function(t){return t.svgD}))}function R(t,e){function r(t){return e?t.transition():t}void 0===e&&(e=!1),t.dimensionSelection.data((function(t){return t.dimensions}),p);var i=t.dimensionSelection.selectAll(\"g.category\").data((function(t){return t.categories}),p);r(t.dimensionSelection).attr(\"transform\",(function(t){return l(t.x,0)})),r(i).attr(\"transform\",(function(t){return l(0,t.y)})),i.select(\".dimlabel\").text((function(t,e){return 0===e?t.parcatsViewModel.model.dimensions[t.model.dimensionInd].dimensionLabel:null})),i.select(\".catlabel\").attr(\"text-anchor\",(function(t){return d(t)?\"start\":\"end\"})).attr(\"x\",(function(t){return d(t)?t.width+5:-5})).each((function(t){var e,r;d(t)?(e=t.width+5,r=\"start\"):(e=-5,r=\"end\"),n.select(this).selectAll(\"tspan\").attr(\"x\",e).attr(\"text-anchor\",r)}));var a=i.selectAll(\"rect.bandrect\").data((function(t){return t.bands}),p),o=a.enter().append(\"rect\").attr(\"class\",\"bandrect\").attr(\"cursor\",\"move\").attr(\"stroke-opacity\",0).attr(\"fill\",(function(t){return t.color})).attr(\"fill-opacity\",0);a.attr(\"fill\",(function(t){return t.color})).attr(\"width\",(function(t){return t.width})).attr(\"height\",(function(t){return t.height})).attr(\"y\",(function(t){return t.y})),k(o),a.each((function(){s.raiseToTop(this)})),a.exit().remove()}function F(t,e,r){var n,i=r[0],a=e.margin||{l:80,r:80,t:100,b:80},o=i.trace,s=o.domain,l=e.width,c=e.height,u=Math.floor(l*(s.x[1]-s.x[0])),f=Math.floor(c*(s.y[1]-s.y[0])),h=s.x[0]*l+a.l,p=e.height-s.y[1]*e.height+a.t,d=o.line.shape;n=\"all\"===o.hoverinfo?[\"count\",\"probability\"]:(o.hoverinfo||\"\").split(\"+\");var m={trace:o,key:o.uid,model:i,x:h,y:p,width:u,height:f,hoveron:o.hoveron,hoverinfoItems:n,arrangement:o.arrangement,bundlecolors:o.bundlecolors,sortpaths:o.sortpaths,labelfont:o.labelfont,categorylabelfont:o.tickfont,pathShape:d,dragDimension:null,margin:a,paths:[],dimensions:[],graphDiv:t,traceSelection:null,pathSelection:null,dimensionSelection:null};return i.dimensions&&(j(m),N(m)),m}function B(t,e,r,n,a){var o,s,l=[],c=[];for(s=0;s<r.length-1;s++)o=i(r[s]+t[s],t[s+1]),l.push(o(a)),c.push(o(1-a));var u=\"M \"+t[0]+\",\"+e[0];for(u+=\"l\"+r[0]+\",0 \",s=1;s<r.length;s++)u+=\"C\"+l[s-1]+\",\"+e[s-1]+\" \"+c[s-1]+\",\"+e[s]+\" \"+t[s]+\",\"+e[s],u+=\"l\"+r[s]+\",0 \";for(u+=\"l0,\"+n+\" \",u+=\"l -\"+r[r.length-1]+\",0 \",s=r.length-2;s>=0;s--)u+=\"C\"+c[s]+\",\"+(e[s+1]+n)+\" \"+l[s]+\",\"+(e[s]+n)+\" \"+(t[s]+r[s])+\",\"+(e[s]+n),u+=\"l-\"+r[s]+\",0 \";return u+=\"Z\"}function N(t){var e=t.dimensions,r=t.model,n=e.map((function(t){return t.categories.map((function(t){return t.y}))})),i=t.model.dimensions.map((function(t){return t.categories.map((function(t){return t.displayInd}))})),a=t.model.dimensions.map((function(t){return t.displayInd})),o=t.dimensions.map((function(t){return t.model.dimensionInd})),s=e.map((function(t){return t.x})),l=e.map((function(t){return t.width})),c=[];for(var u in r.paths)r.paths.hasOwnProperty(u)&&c.push(r.paths[u]);function f(t){var e=t.categoryInds.map((function(t,e){return i[e][t]}));return o.map((function(t){return e[t]}))}c.sort((function(e,r){var n=f(e),i=f(r);return\"backward\"===t.sortpaths&&(n.reverse(),i.reverse()),n.push(e.valueInds[0]),i.push(r.valueInds[0]),t.bundlecolors&&(n.unshift(e.rawColor),i.unshift(r.rawColor)),n<i?-1:n>i?1:0}));for(var h=new Array(c.length),p=e[0].model.count,d=e[0].categories.map((function(t){return t.height})).reduce((function(t,e){return t+e})),m=0;m<c.length;m++){var g,v=c[m];g=p>0?d*(v.count/p):0;for(var y,x=new Array(n.length),b=0;b<v.categoryInds.length;b++){var 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n=t(\"../../lib\").isTypedArray;r.convertTypedArray=function(t){return n(t)?Array.prototype.slice.call(t):t},r.isOrdinal=function(t){return!!t.tickvals},r.isVisible=function(t){return t.visible||!(\"visible\"in t)}},{\"../../lib\":503}],896:[function(t,e,r){\"use strict\";var n=t(\"./base_index\");n.plot=t(\"./plot\"),e.exports=n},{\"./base_index\":890,\"./plot\":900}],897:[function(t,e,r){\"use strict\";var n=t(\"glslify\"),i=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nvarying vec4 fragColor;\\n\\nattribute vec4 p01_04, p05_08, p09_12, p13_16,\\n p17_20, p21_24, p25_28, p29_32,\\n p33_36, p37_40, p41_44, p45_48,\\n p49_52, p53_56, p57_60, colors;\\n\\nuniform mat4 dim0A, dim1A, dim0B, dim1B, dim0C, dim1C, dim0D, dim1D,\\n loA, hiA, loB, hiB, loC, hiC, loD, hiD;\\n\\nuniform vec2 resolution, viewBoxPos, viewBoxSize;\\nuniform float maskHeight;\\nuniform float drwLayer; // 0: context, 1: focus, 2: pick\\nuniform vec4 contextColor;\\nuniform sampler2D maskTexture, palette;\\n\\nbool isPick = (drwLayer > 1.5);\\nbool isContext = (drwLayer < 0.5);\\n\\nconst vec4 ZEROS = vec4(0.0, 0.0, 0.0, 0.0);\\nconst vec4 UNITS = vec4(1.0, 1.0, 1.0, 1.0);\\n\\nfloat val(mat4 p, mat4 v) {\\n return dot(matrixCompMult(p, v) * UNITS, UNITS);\\n}\\n\\nfloat axisY(float ratio, mat4 A, mat4 B, mat4 C, mat4 D) {\\n float y1 = val(A, dim0A) + val(B, dim0B) + val(C, dim0C) + val(D, dim0D);\\n float y2 = val(A, dim1A) + val(B, dim1B) + val(C, dim1C) + val(D, dim1D);\\n return y1 * (1.0 - ratio) + y2 * ratio;\\n}\\n\\nint iMod(int a, int b) {\\n return a - b * (a / b);\\n}\\n\\nbool fOutside(float p, float lo, float hi) {\\n return (lo < hi) && (lo > p || p > hi);\\n}\\n\\nbool vOutside(vec4 p, vec4 lo, vec4 hi) {\\n return (\\n fOutside(p[0], lo[0], hi[0]) ||\\n fOutside(p[1], lo[1], hi[1]) ||\\n fOutside(p[2], lo[2], hi[2]) ||\\n fOutside(p[3], lo[3], hi[3])\\n );\\n}\\n\\nbool mOutside(mat4 p, mat4 lo, mat4 hi) {\\n return (\\n vOutside(p[0], lo[0], hi[0]) ||\\n 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isContext ? 0.0 : 2.0 * float(\\n outsideBoundingBox(A, B, C, D) ||\\n outsideRasterMask(A, B, C, D)\\n );\\n\\n return vec4(\\n 2.0 * (vec2(x, y) * viewBoxSize + viewBoxPos) / resolution - 1.0,\\n z,\\n 1.0\\n );\\n}\\n\\nvoid main() {\\n mat4 A = mat4(p01_04, p05_08, p09_12, p13_16);\\n mat4 B = mat4(p17_20, p21_24, p25_28, p29_32);\\n mat4 C = mat4(p33_36, p37_40, p41_44, p45_48);\\n mat4 D = mat4(p49_52, p53_56, p57_60, ZEROS);\\n\\n float v = colors[3];\\n\\n gl_Position = position(isContext, v, A, B, C, D);\\n\\n fragColor =\\n isContext ? vec4(contextColor) :\\n isPick ? vec4(colors.rgb, 1.0) : texture2D(palette, vec2(abs(v), 0.5));\\n}\\n\"]),a=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nvarying vec4 fragColor;\\n\\nvoid main() {\\n gl_FragColor = fragColor;\\n}\\n\"]),o=t(\"./constants\").maxDimensionCount,s=t(\"../../lib\"),l=new Uint8Array(4),c=new Uint8Array(4),u={shape:[256,1],format:\"rgba\",type:\"uint8\",mag:\"nearest\",min:\"nearest\"};function f(t,e,r,n,i){var a=t._gl;a.enable(a.SCISSOR_TEST),a.scissor(e,r,n,i),t.clear({color:[0,0,0,0],depth:1})}function h(t,e,r,n,i,a){var o=a.key;r.drawCompleted||(!function(t){t.read({x:0,y:0,width:1,height:1,data:l})}(t),r.drawCompleted=!0),function s(l){var c=Math.min(n,i-l*n);0===l&&(window.cancelAnimationFrame(r.currentRafs[o]),delete r.currentRafs[o],f(t,a.scissorX,a.scissorY,a.scissorWidth,a.viewBoxSize[1])),r.clearOnly||(a.count=2*c,a.offset=2*l*n,e(a),l*n+c<i&&(r.currentRafs[o]=window.requestAnimationFrame((function(){s(l+1)}))),r.drawCompleted=!1)}(0)}function p(t,e){for(var r=new Array(256),n=0;n<256;n++)r[n]=t(n/255).concat(e);return r}function d(t,e){return(t>>>8*e)%256/255}function m(t,e,r){for(var n=new Array(8*e),i=0,a=0;a<e;a++)for(var o=0;o<2;o++)for(var s=0;s<4;s++){var l=4*t+s,c=r[64*a+l];63===l&&0===o&&(c*=-1),n[i++]=c}return n}function g(t){var e=\"0\"+t;return e.substr(e.length-2)}function v(t){return t<o?\"p\"+g(t+1)+\"_\"+g(t+4):\"colors\"}function 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e=Math.max(0,Math.floor(2047*t[0]),0),r=Math.min(2047,Math.ceil(2047*t[1]),2047);return[Math.min(e,r),Math.max(e,r)]}e.exports=function(t,e){var r,n,l,g,b,_=e.context,w=e.pick,T=e.regl,k=T._gl,A=k.getParameter(k.ALIASED_LINE_WIDTH_RANGE),M=Math.max(A[0],Math.min(A[1],e.viewModel.plotGlPixelRatio)),S={currentRafs:{},drawCompleted:!0,clearOnly:!1},E=function(t){for(var e={},r=0;r<=o;r+=4)e[v(r)]=t.buffer({usage:\"dynamic\",type:\"float\",data:new Uint8Array(0)});return e}(T),L=T.texture(u),C=[];I(e);var P=T({profile:!1,blend:{enable:_,func:{srcRGB:\"src alpha\",dstRGB:\"one minus src 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I(t){r=t.model,n=t.viewModel,l=n.dimensions.slice(),g=l[0]?l[0].values.length:0;var e=r.lines,i=w?e.color.map((function(t,r){return r/e.color.length})):e.color,a=function(t,e,r){for(var n,i=new Array(t*(o+4)),a=0,s=0;s<t;s++){for(var l=0;l<o;l++)i[a++]=l<e.length?e[l].paddedUnitValues[s]:.5;i[a++]=d(s,2),i[a++]=d(s,1),i[a++]=d(s,0),i[a++]=(n=r[s],Math.max(1e-6,Math.min(.999999,n)))}return i}(g,l,i);!function(t,e,r){for(var n=0;n<=o;n+=4)t[v(n)](m(n/4,e,r))}(E,g,a),_||w||(L=T.texture(s.extendFlat({data:p(r.unitToColor,255)},u)))}return{render:function(t,e,n){var i,a,o,s=t.length,c=1/0,u=-1/0;for(i=0;i<s;i++)t[i].dim0.canvasX<c&&(c=t[i].dim0.canvasX,a=i),t[i].dim1.canvasX>u&&(u=t[i].dim1.canvasX,o=i);0===s&&f(T,0,0,r.canvasWidth,r.canvasHeight);var p=function(t){var e,r,n,i=[[],[]];for(n=0;n<64;n++){var a=!t&&n<l.length?l[n].brush.filter.getBounds():[-1/0,1/0];i[0][n]=a[0],i[1][n]=a[1]}var o=new Array(16384);for(e=0;e<16384;e++)o[e]=255;if(!t)for(e=0;e<l.length;e++){var 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i=new Uint8Array(4*r*n);return T.read({x:t,y:e,width:r,height:n,data:i}),i},destroy:function(){for(var e in t.style[\"pointer-events\"]=\"none\",L.destroy(),b&&b.destroy(),E)E[e].destroy()},update:I}}},{\"../../lib\":503,\"./constants\":893,glslify:227}],898:[function(t,e,r){\"use strict\";e.exports=function(t,e,r,n){var i,a;for(n||(n=1/0),i=0;i<e.length;i++)(a=e[i]).visible&&(n=Math.min(n,a[r].length));for(n===1/0&&(n=0),t._length=n,i=0;i<e.length;i++)(a=e[i]).visible&&(a._length=n);return n}},{}],899:[function(t,e,r){\"use strict\";var n=t(\"@plotly/d3\"),i=t(\"../../lib\"),a=i.numberFormat,o=t(\"color-rgba\"),s=t(\"../../plots/cartesian/axes\"),l=i.strRotate,c=i.strTranslate,u=t(\"../../lib/svg_text_utils\"),f=t(\"../../components/drawing\"),h=t(\"../../components/colorscale\"),p=t(\"../../lib/gup\"),d=p.keyFun,m=p.repeat,g=p.unwrap,v=t(\"./helpers\"),y=t(\"./constants\"),x=t(\"./axisbrush\"),b=t(\"./lines\");function _(t,e,r){return i.aggNums(t,null,e,r)}function w(t,e){return k(_(Math.min,t,e),_(Math.max,t,e))}function T(t){var e=t.range;return e?k(e[0],e[1]):w(t.values,t._length)}function k(t,e){return!isNaN(t)&&isFinite(t)||(t=0),!isNaN(e)&&isFinite(e)||(e=0),t===e&&(0===t?(t-=1,e+=1):(t*=.9,e*=1.1)),[t,e]}function A(t,e,r,i,o){var s,l,c=T(r);return i?n.scale.ordinal().domain(i.map((s=a(r.tickformat),l=o,l?function(t,e){var r=l[e];return null==r?s(t):r}:s))).range(i.map((function(r){var n=(r-c[0])/(c[1]-c[0]);return t-e+n*(2*e-t)}))):n.scale.linear().domain(c).range([t-e,e])}function M(t){if(t.tickvals){var e=T(t);return n.scale.ordinal().domain(t.tickvals).range(t.tickvals.map((function(t){return(t-e[0])/(e[1]-e[0])})))}}function S(t){var e=t.map((function(t){return t[0]})),r=t.map((function(t){var e=o(t[1]);return n.rgb(\"rgb(\"+e[0]+\",\"+e[1]+\",\"+e[2]+\")\")})),i=\"rgb\".split(\"\").map((function(t){return n.scale.linear().clamp(!0).domain(e).range(r.map((i=t,function(t){return t[i]})));var i}));return function(t){return i.map((function(e){return 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n=t(\"../../plots/attributes\"),i=t(\"../../plots/domain\").attributes,a=t(\"../../plots/font_attributes\"),o=t(\"../../components/color/attributes\"),s=t(\"../../plots/template_attributes\").hovertemplateAttrs,l=t(\"../../plots/template_attributes\").texttemplateAttrs,c=t(\"../../lib/extend\").extendFlat,u=a({editType:\"plot\",arrayOk:!0,colorEditType:\"plot\"});e.exports={labels:{valType:\"data_array\",editType:\"calc\"},label0:{valType:\"number\",dflt:0,editType:\"calc\"},dlabel:{valType:\"number\",dflt:1,editType:\"calc\"},values:{valType:\"data_array\",editType:\"calc\"},marker:{colors:{valType:\"data_array\",editType:\"calc\"},line:{color:{valType:\"color\",dflt:o.defaultLine,arrayOk:!0,editType:\"style\"},width:{valType:\"number\",min:0,dflt:0,arrayOk:!0,editType:\"style\"},editType:\"calc\"},editType:\"calc\"},text:{valType:\"data_array\",editType:\"plot\"},hovertext:{valType:\"string\",dflt:\"\",arrayOk:!0,editType:\"style\"},scalegroup:{valType:\"string\",dflt:\"\",editType:\"calc\"},textinfo:{valType:\"flaglist\",flags:[\"label\",\"text\",\"value\",\"percent\"],extras:[\"none\"],editType:\"calc\"},hoverinfo:c({},n.hoverinfo,{flags:[\"label\",\"text\",\"value\",\"percent\",\"name\"]}),hovertemplate:s({},{keys:[\"label\",\"color\",\"value\",\"percent\",\"text\"]}),texttemplate:l({editType:\"plot\"},{keys:[\"label\",\"color\",\"value\",\"percent\",\"text\"]}),textposition:{valType:\"enumerated\",values:[\"inside\",\"outside\",\"auto\",\"none\"],dflt:\"auto\",arrayOk:!0,editType:\"plot\"},textfont:c({},u,{}),insidetextorientation:{valType:\"enumerated\",values:[\"horizontal\",\"radial\",\"tangential\",\"auto\"],dflt:\"auto\",editType:\"plot\"},insidetextfont:c({},u,{}),outsidetextfont:c({},u,{}),automargin:{valType:\"boolean\",dflt:!1,editType:\"plot\"},title:{text:{valType:\"string\",dflt:\"\",editType:\"plot\"},font:c({},u,{}),position:{valType:\"enumerated\",values:[\"top 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r,i,a=[],o=t._fullLayout,l=o.hiddenlabels||[],c=e.labels,u=e.marker.colors||[],f=e.values,h=e._length,p=e._hasValues&&h;if(e.dlabel)for(c=new Array(h),r=0;r<h;r++)c[r]=String(e.label0+r*e.dlabel);var d={},m=s(o[\"_\"+e.type+\"colormap\"]),g=0,v=!1;for(r=0;r<h;r++){var y,x,b;if(p){if(y=f[r],!n(y))continue;y=+y}else y=1;void 0!==(x=c[r])&&\"\"!==x||(x=r);var _=d[x=String(x)];void 0===_?(d[x]=a.length,(b=-1!==l.indexOf(x))||(g+=y),a.push({v:y,label:x,color:m(u[r],x),i:r,pts:[r],hidden:b})):(v=!0,(i=a[_]).v+=y,i.pts.push(r),i.hidden||(g+=y),!1===i.color&&u[r]&&(i.color=m(u[r],x)))}return a=a.filter((function(t){return t.v>=0})),(\"funnelarea\"===e.type?v:e.sort)&&a.sort((function(t,e){return e.v-t.v})),a[0]&&(a[0].vTotal=g),a},crossTraceCalc:function(t,e){var r=(e||{}).type;r||(r=\"pie\");var n=t._fullLayout,i=t.calcdata,a=n[r+\"colorway\"],s=n[\"_\"+r+\"colormap\"];n[\"extend\"+r+\"colors\"]&&(a=l(a,o));for(var c=0,u=0;u<i.length;u++){var f=i[u];if(f[0].trace.type===r)for(var h=0;h<f.length;h++){var p=f[h];!1===p.color&&(s[p.label]?p.color=s[p.label]:(s[p.label]=p.color=a[c%a.length],c++))}}},makePullColorFn:s,generateExtendedColors:l}},{\"../../components/color\":366,\"fast-isnumeric\":190,tinycolor2:312}],904:[function(t,e,r){\"use strict\";var n=t(\"fast-isnumeric\"),i=t(\"../../lib\"),a=t(\"./attributes\"),o=t(\"../../plots/domain\").defaults,s=t(\"../bar/defaults\").handleText;function l(t,e){var r=Array.isArray(t),a=i.isArrayOrTypedArray(e),o=Math.min(r?t.length:1/0,a?e.length:1/0);if(isFinite(o)||(o=0),o&&a){for(var s,l=0;l<o;l++){var c=e[l];if(n(c)&&c>0){s=!0;break}}s||(o=0)}return{hasLabels:r,hasValues:a,len:o}}e.exports={handleLabelsAndValues:l,supplyDefaults:function(t,e,r,n){function c(r,n){return i.coerce(t,e,a,r,n)}var u=l(c(\"labels\"),c(\"values\")),f=u.len;if(e._hasLabels=u.hasLabels,e._hasValues=u.hasValues,!e._hasLabels&&e._hasValues&&(c(\"label0\"),c(\"dlabel\")),f){e._length=f,c(\"marker.line.width\")&&c(\"marker.line.color\"),c(\"marker.colors\"),c(\"scalegroup\");var h,p=c(\"text\"),d=c(\"texttemplate\");if(d||(h=c(\"textinfo\",Array.isArray(p)?\"text+percent\":\"percent\")),c(\"hovertext\"),c(\"hovertemplate\"),d||h&&\"none\"!==h){var m=c(\"textposition\");s(t,e,n,c,m,{moduleHasSelected:!1,moduleHasUnselected:!1,moduleHasConstrain:!1,moduleHasCliponaxis:!1,moduleHasTextangle:!1,moduleHasInsideanchor:!1}),(Array.isArray(m)||\"auto\"===m||\"outside\"===m)&&c(\"automargin\"),(\"inside\"===m||\"auto\"===m||Array.isArray(m))&&c(\"insidetextorientation\")}o(e,n,c);var g=c(\"hole\");if(c(\"title.text\")){var v=c(\"title.position\",g?\"middle center\":\"top center\");g||\"middle center\"!==v||(e.title.position=\"top center\"),i.coerceFont(c,\"title.font\",n.font)}c(\"sort\"),c(\"direction\"),c(\"rotation\"),c(\"pull\")}else e.visible=!1}}},{\"../../lib\":503,\"../../plots/domain\":584,\"../bar/defaults\":652,\"./attributes\":901,\"fast-isnumeric\":190}],905:[function(t,e,r){\"use strict\";var n=t(\"../../components/fx/helpers\").appendArrayMultiPointValues;e.exports=function(t,e){var r={curveNumber:e.index,pointNumbers:t.pts,data:e._input,fullData:e,label:t.label,color:t.color,value:t.v,percent:t.percent,text:t.text,bbox:t.bbox,v:t.v};return 1===t.pts.length&&(r.pointNumber=r.i=t.pts[0]),n(r,e,t.pts),\"funnelarea\"===e.type&&(delete r.v,delete r.i),r}},{\"../../components/fx/helpers\":402}],906:[function(t,e,r){\"use strict\";var n=t(\"../../lib\");function i(t){return-1!==t.indexOf(\"e\")?t.replace(/[.]?0+e/,\"e\"):-1!==t.indexOf(\".\")?t.replace(/[.]?0+$/,\"\"):t}r.formatPiePercent=function(t,e){var r=i((100*t).toPrecision(3));return n.numSeparate(r,e)+\"%\"},r.formatPieValue=function(t,e){var r=i(t.toPrecision(10));return n.numSeparate(r,e)},r.getFirstFilled=function(t,e){if(Array.isArray(t))for(var r=0;r<e.length;r++){var n=t[e[r]];if(n||0===n||\"\"===n)return n}},r.castOption=function(t,e){return Array.isArray(t)?r.getFirstFilled(t,e):t||void 0},r.getRotationAngle=function(t){return(\"auto\"===t?0:t)*Math.PI/180}},{\"../../lib\":503}],907:[function(t,e,r){\"use strict\";e.exports={attributes:t(\"./attributes\"),supplyDefaults:t(\"./defaults\").supplyDefaults,supplyLayoutDefaults:t(\"./layout_defaults\"),layoutAttributes:t(\"./layout_attributes\"),calc:t(\"./calc\").calc,crossTraceCalc:t(\"./calc\").crossTraceCalc,plot:t(\"./plot\").plot,style:t(\"./style\"),styleOne:t(\"./style_one\"),moduleType:\"trace\",name:\"pie\",basePlotModule:t(\"./base_plot\"),categories:[\"pie-like\",\"pie\",\"showLegend\"],meta:{}}},{\"./attributes\":901,\"./base_plot\":902,\"./calc\":903,\"./defaults\":904,\"./layout_attributes\":908,\"./layout_defaults\":909,\"./plot\":910,\"./style\":911,\"./style_one\":912}],908:[function(t,e,r){\"use strict\";e.exports={hiddenlabels:{valType:\"data_array\",editType:\"calc\"},piecolorway:{valType:\"colorlist\",editType:\"calc\"},extendpiecolors:{valType:\"boolean\",dflt:!0,editType:\"calc\"}}},{}],909:[function(t,e,r){\"use strict\";var n=t(\"../../lib\"),i=t(\"./layout_attributes\");e.exports=function(t,e){function r(r,a){return n.coerce(t,e,i,r,a)}r(\"hiddenlabels\"),r(\"piecolorway\",e.colorway),r(\"extendpiecolors\")}},{\"../../lib\":503,\"./layout_attributes\":908}],910:[function(t,e,r){\"use strict\";var n=t(\"@plotly/d3\"),i=t(\"../../plots/plots\"),a=t(\"../../components/fx\"),o=t(\"../../components/color\"),s=t(\"../../components/drawing\"),l=t(\"../../lib\"),c=l.strScale,u=l.strTranslate,f=t(\"../../lib/svg_text_utils\"),h=t(\"../bar/uniform_text\"),p=h.recordMinTextSize,d=h.clearMinTextSize,m=t(\"../bar/constants\").TEXTPAD,g=t(\"./helpers\"),v=t(\"./event_data\"),y=t(\"../../lib\").isValidTextValue;function x(t,e,r){var i=r[0],o=i.cx,s=i.cy,c=i.trace,u=\"funnelarea\"===c.type;\"_hasHoverLabel\"in c||(c._hasHoverLabel=!1),\"_hasHoverEvent\"in c||(c._hasHoverEvent=!1),t.on(\"mouseover\",(function(t){var r=e._fullLayout,f=e._fullData[c.index];if(!e._dragging&&!1!==r.hovermode){var h=f.hoverinfo;if(Array.isArray(h)&&(h=a.castHoverinfo({hoverinfo:[g.castOption(h,t.pts)],_module:c._module},r,0)),\"all\"===h&&(h=\"label+text+value+percent+name\"),f.hovertemplate||\"none\"!==h&&\"skip\"!==h&&h){var p=t.rInscribed||0,d=o+t.pxmid[0]*(1-p),m=s+t.pxmid[1]*(1-p),y=r.separators,x=[];if(h&&-1!==h.indexOf(\"label\")&&x.push(t.label),t.text=g.castOption(f.hovertext||f.text,t.pts),h&&-1!==h.indexOf(\"text\")){var b=t.text;l.isValidTextValue(b)&&x.push(b)}t.value=t.v,t.valueLabel=g.formatPieValue(t.v,y),h&&-1!==h.indexOf(\"value\")&&x.push(t.valueLabel),t.percent=t.v/i.vTotal,t.percentLabel=g.formatPiePercent(t.percent,y),h&&-1!==h.indexOf(\"percent\")&&x.push(t.percentLabel);var _=f.hoverlabel,w=_.font,T=[];a.loneHover({trace:c,x0:d-p*i.r,x1:d+p*i.r,y:m,_x0:u?o+t.TL[0]:d-p*i.r,_x1:u?o+t.TR[0]:d+p*i.r,_y0:u?s+t.TL[1]:m-p*i.r,_y1:u?s+t.BL[1]:m+p*i.r,text:x.join(\"<br>\"),name:f.hovertemplate||-1!==h.indexOf(\"name\")?f.name:void 0,idealAlign:t.pxmid[0]<0?\"left\":\"right\",color:g.castOption(_.bgcolor,t.pts)||t.color,borderColor:g.castOption(_.bordercolor,t.pts),fontFamily:g.castOption(w.family,t.pts),fontSize:g.castOption(w.size,t.pts),fontColor:g.castOption(w.color,t.pts),nameLength:g.castOption(_.namelength,t.pts),textAlign:g.castOption(_.align,t.pts),hovertemplate:g.castOption(f.hovertemplate,t.pts),hovertemplateLabels:t,eventData:[v(t,f)]},{container:r._hoverlayer.node(),outerContainer:r._paper.node(),gd:e,inOut_bbox:T}),t.bbox=T[0],c._hasHoverLabel=!0}c._hasHoverEvent=!0,e.emit(\"plotly_hover\",{points:[v(t,f)],event:n.event})}})),t.on(\"mouseout\",(function(t){var r=e._fullLayout,i=e._fullData[c.index],o=n.select(this).datum();c._hasHoverEvent&&(t.originalEvent=n.event,e.emit(\"plotly_unhover\",{points:[v(o,i)],event:n.event}),c._hasHoverEvent=!1),c._hasHoverLabel&&(a.loneUnhover(r._hoverlayer.node()),c._hasHoverLabel=!1)})),t.on(\"click\",(function(t){var r=e._fullLayout,i=e._fullData[c.index];e._dragging||!1===r.hovermode||(e._hoverdata=[v(t,i)],a.click(e,n.event))}))}function b(t,e,r){var n=g.castOption(t.insidetextfont.color,e.pts);!n&&t._input.textfont&&(n=g.castOption(t._input.textfont.color,e.pts));var i=g.castOption(t.insidetextfont.family,e.pts)||g.castOption(t.textfont.family,e.pts)||r.family,a=g.castOption(t.insidetextfont.size,e.pts)||g.castOption(t.textfont.size,e.pts)||r.size;return{color:n||o.contrast(e.color),family:i,size:a}}function _(t,e){for(var r,n,i=0;i<t.length;i++)if((n=(r=t[i][0]).trace).title.text){var a=n.title.text;n._meta&&(a=l.templateString(a,n._meta));var o=s.tester.append(\"text\").attr(\"data-notex\",1).text(a).call(s.font,n.title.font).call(f.convertToTspans,e),c=s.bBox(o.node(),!0);r.titleBox={width:c.width,height:c.height},o.remove()}}function w(t,e,r){var n=r.r||e.rpx1,i=e.rInscribed;if(e.startangle===e.stopangle)return{rCenter:1-i,scale:0,rotate:0,textPosAngle:0};var a,o=e.ring,s=1===o&&Math.abs(e.startangle-e.stopangle)===2*Math.PI,l=e.halfangle,c=e.midangle,u=r.trace.insidetextorientation,f=\"horizontal\"===u,h=\"tangential\"===u,p=\"radial\"===u,d=\"auto\"===u,m=[];if(!d){var g,v=function(r,i){if(function(t,e){var r=t.startangle,n=t.stopangle;return r>e&&e>n||r<e&&e<n}(e,r)){var s=Math.abs(r-e.startangle),l=Math.abs(r-e.stopangle),c=s<l?s:l;(a=\"tan\"===i?k(t,n,o,c,0):T(t,n,o,c,Math.PI/2)).textPosAngle=r,m.push(a)}};if(f||h){for(g=4;g>=-4;g-=2)v(Math.PI*g,\"tan\");for(g=4;g>=-4;g-=2)v(Math.PI*(g+1),\"tan\")}if(f||p){for(g=4;g>=-4;g-=2)v(Math.PI*(g+1.5),\"rad\");for(g=4;g>=-4;g-=2)v(Math.PI*(g+.5),\"rad\")}}if(s||d||f){var y=Math.sqrt(t.width*t.width+t.height*t.height);if((a={scale:i*n*2/y,rCenter:1-i,rotate:0}).textPosAngle=(e.startangle+e.stopangle)/2,a.scale>=1)return a;m.push(a)}(d||p)&&((a=T(t,n,o,l,c)).textPosAngle=(e.startangle+e.stopangle)/2,m.push(a)),(d||h)&&((a=k(t,n,o,l,c)).textPosAngle=(e.startangle+e.stopangle)/2,m.push(a));for(var x=0,b=0,_=0;_<m.length;_++){var w=m[_].scale;if(b<w&&(b=w,x=_),!d&&b>=1)break}return m[x]}function T(t,e,r,n,i){e=Math.max(0,e-2*m);var a=t.width/t.height,o=S(a,n,e,r);return{scale:2*o/t.height,rCenter:A(a,o/e),rotate:M(i)}}function k(t,e,r,n,i){e=Math.max(0,e-2*m);var a=t.height/t.width,o=S(a,n,e,r);return{scale:2*o/t.width,rCenter:A(a,o/e),rotate:M(i+Math.PI/2)}}function A(t,e){return Math.cos(e)-t*e}function M(t){return(180/Math.PI*t+720)%180-90}function S(t,e,r,n){var i=t+1/(2*Math.tan(e));return r*Math.min(1/(Math.sqrt(i*i+.5)+i),n/(Math.sqrt(t*t+n/2)+t))}function E(t,e){return t.v!==e.vTotal||e.trace.hole?Math.min(1/(1+1/Math.sin(t.halfangle)),t.ring/2):1}function L(t,e){var r=e.pxmid[0],n=e.pxmid[1],i=t.width/2,a=t.height/2;return r<0&&(i*=-1),n<0&&(a*=-1),{scale:1,rCenter:1,rotate:0,x:i+Math.abs(a)*(i>0?1:-1)/2,y:a/(1+r*r/(n*n)),outside:!0}}function C(t,e){var r,n,i,a=t.trace,o={x:t.cx,y:t.cy},s={tx:0,ty:0};s.ty+=a.title.font.size,i=I(a),-1!==a.title.position.indexOf(\"top\")?(o.y-=(1+i)*t.r,s.ty-=t.titleBox.height):-1!==a.title.position.indexOf(\"bottom\")&&(o.y+=(1+i)*t.r);var l,c,u=(l=t.r,c=t.trace.aspectratio,l/(void 0===c?1:c)),f=e.w*(a.domain.x[1]-a.domain.x[0])/2;return-1!==a.title.position.indexOf(\"left\")?(f+=u,o.x-=(1+i)*u,s.tx+=t.titleBox.width/2):-1!==a.title.position.indexOf(\"center\")?f*=2:-1!==a.title.position.indexOf(\"right\")&&(f+=u,o.x+=(1+i)*u,s.tx-=t.titleBox.width/2),r=f/t.titleBox.width,n=P(t,e)/t.titleBox.height,{x:o.x,y:o.y,scale:Math.min(r,n),tx:s.tx,ty:s.ty}}function P(t,e){var r=t.trace,n=e.h*(r.domain.y[1]-r.domain.y[0]);return Math.min(t.titleBox.height,n/2)}function I(t){var e,r=t.pull;if(!r)return 0;if(Array.isArray(r))for(r=0,e=0;e<t.pull.length;e++)t.pull[e]>r&&(r=t.pull[e]);return r}function O(t,e){for(var r=[],n=0;n<t.length;n++){var i=t[n][0],a=i.trace,o=a.domain,s=e.w*(o.x[1]-o.x[0]),l=e.h*(o.y[1]-o.y[0]);a.title.text&&\"middle center\"!==a.title.position&&(l-=P(i,e));var c=s/2,u=l/2;\"funnelarea\"!==a.type||a.scalegroup||(u/=a.aspectratio),i.r=Math.min(c,u)/(1+I(a)),i.cx=e.l+e.w*(a.domain.x[1]+a.domain.x[0])/2,i.cy=e.t+e.h*(1-a.domain.y[0])-l/2,a.title.text&&-1!==a.title.position.indexOf(\"bottom\")&&(i.cy-=P(i,e)),a.scalegroup&&-1===r.indexOf(a.scalegroup)&&r.push(a.scalegroup)}!function(t,e){for(var r,n,i,a=0;a<e.length;a++){var o=1/0,s=e[a];for(n=0;n<t.length;n++)if(r=t[n][0],(i=r.trace).scalegroup===s){var l;if(\"pie\"===i.type)l=r.r*r.r;else if(\"funnelarea\"===i.type){var c,u;i.aspectratio>1?(c=r.r,u=c/i.aspectratio):(u=r.r,c=u*i.aspectratio),c*=(1+i.baseratio)/2,l=c*u}o=Math.min(o,l/r.vTotal)}for(n=0;n<t.length;n++)if(r=t[n][0],(i=r.trace).scalegroup===s){var f=o*r.vTotal;\"funnelarea\"===i.type&&(f/=(1+i.baseratio)/2,f/=i.aspectratio),r.r=Math.sqrt(f)}}}(t,r)}function z(t,e){return[t*Math.sin(e),-t*Math.cos(e)]}function D(t,e,r){var n=t._fullLayout,i=r.trace,a=i.texttemplate,o=i.textinfo;if(!a&&o&&\"none\"!==o){var s,c=o.split(\"+\"),u=function(t){return-1!==c.indexOf(t)},f=u(\"label\"),h=u(\"text\"),p=u(\"value\"),d=u(\"percent\"),m=n.separators;if(s=f?[e.label]:[],h){var v=g.getFirstFilled(i.text,e.pts);y(v)&&s.push(v)}p&&s.push(g.formatPieValue(e.v,m)),d&&s.push(g.formatPiePercent(e.v/r.vTotal,m)),e.text=s.join(\"<br>\")}if(a){var x=l.castOption(i,e.i,\"texttemplate\");if(x){var b=function(t){return{label:t.label,value:t.v,valueLabel:g.formatPieValue(t.v,n.separators),percent:t.v/r.vTotal,percentLabel:g.formatPiePercent(t.v/r.vTotal,n.separators),color:t.color,text:t.text,customdata:l.castOption(i,t.i,\"customdata\")}}(e),_=g.getFirstFilled(i.text,e.pts);(y(_)||\"\"===_)&&(b.text=_),e.text=l.texttemplateString(x,b,t._fullLayout._d3locale,b,i._meta||{})}else e.text=\"\"}}function R(t,e){var r=t.rotate*Math.PI/180,n=Math.cos(r),i=Math.sin(r),a=(e.left+e.right)/2,o=(e.top+e.bottom)/2;t.textX=a*n-o*i,t.textY=a*i+o*n,t.noCenter=!0}e.exports={plot:function(t,e){var r=t._fullLayout,a=r._size;d(\"pie\",r),_(e,t),O(e,a);var h=l.makeTraceGroups(r._pielayer,e,\"trace\").each((function(e){var h=n.select(this),d=e[0],m=d.trace;!function(t){var e,r,n,i=t[0],a=i.r,o=i.trace,s=g.getRotationAngle(o.rotation),l=2*Math.PI/i.vTotal,c=\"px0\",u=\"px1\";if(\"counterclockwise\"===o.direction){for(e=0;e<t.length&&t[e].hidden;e++);if(e===t.length)return;s+=l*t[e].v,l*=-1,c=\"px1\",u=\"px0\"}for(n=z(a,s),e=0;e<t.length;e++)(r=t[e]).hidden||(r[c]=n,r.startangle=s,s+=l*r.v/2,r.pxmid=z(a,s),r.midangle=s,s+=l*r.v/2,n=z(a,s),r.stopangle=s,r[u]=n,r.largeArc=r.v>i.vTotal/2?1:0,r.halfangle=Math.PI*Math.min(r.v/i.vTotal,.5),r.ring=1-o.hole,r.rInscribed=E(r,i))}(e),h.attr(\"stroke-linejoin\",\"round\"),h.each((function(){var v=n.select(this).selectAll(\"g.slice\").data(e);v.enter().append(\"g\").classed(\"slice\",!0),v.exit().remove();var y=[[[],[]],[[],[]]],_=!1;v.each((function(i,a){if(i.hidden)n.select(this).selectAll(\"path,g\").remove();else{i.pointNumber=i.i,i.curveNumber=m.index,y[i.pxmid[1]<0?0:1][i.pxmid[0]<0?0:1].push(i);var o=d.cx,c=d.cy,u=n.select(this),h=u.selectAll(\"path.surface\").data([i]);if(h.enter().append(\"path\").classed(\"surface\",!0).style({\"pointer-events\":\"all\"}),u.call(x,t,e),m.pull){var v=+g.castOption(m.pull,i.pts)||0;v>0&&(o+=v*i.pxmid[0],c+=v*i.pxmid[1])}i.cxFinal=o,i.cyFinal=c;var T=m.hole;if(i.v===d.vTotal){var k=\"M\"+(o+i.px0[0])+\",\"+(c+i.px0[1])+C(i.px0,i.pxmid,!0,1)+C(i.pxmid,i.px0,!0,1)+\"Z\";T?h.attr(\"d\",\"M\"+(o+T*i.px0[0])+\",\"+(c+T*i.px0[1])+C(i.px0,i.pxmid,!1,T)+C(i.pxmid,i.px0,!1,T)+\"Z\"+k):h.attr(\"d\",k)}else{var A=C(i.px0,i.px1,!0,1);if(T){var M=1-T;h.attr(\"d\",\"M\"+(o+T*i.px1[0])+\",\"+(c+T*i.px1[1])+C(i.px1,i.px0,!1,T)+\"l\"+M*i.px0[0]+\",\"+M*i.px0[1]+A+\"Z\")}else h.attr(\"d\",\"M\"+o+\",\"+c+\"l\"+i.px0[0]+\",\"+i.px0[1]+A+\"Z\")}D(t,i,d);var S=g.castOption(m.textposition,i.pts),E=u.selectAll(\"g.slicetext\").data(i.text&&\"none\"!==S?[0]:[]);E.enter().append(\"g\").classed(\"slicetext\",!0),E.exit().remove(),E.each((function(){var u=l.ensureSingle(n.select(this),\"text\",\"\",(function(t){t.attr(\"data-notex\",1)})),h=l.ensureUniformFontSize(t,\"outside\"===S?function(t,e,r){var n=g.castOption(t.outsidetextfont.color,e.pts)||g.castOption(t.textfont.color,e.pts)||r.color,i=g.castOption(t.outsidetextfont.family,e.pts)||g.castOption(t.textfont.family,e.pts)||r.family,a=g.castOption(t.outsidetextfont.size,e.pts)||g.castOption(t.textfont.size,e.pts)||r.size;return{color:n,family:i,size:a}}(m,i,r.font):b(m,i,r.font));u.text(i.text).attr({class:\"slicetext\",transform:\"\",\"text-anchor\":\"middle\"}).call(s.font,h).call(f.convertToTspans,t);var v,y=s.bBox(u.node());if(\"outside\"===S)v=L(y,i);else if(v=w(y,i,d),\"auto\"===S&&v.scale<1){var x=l.ensureUniformFontSize(t,m.outsidetextfont);u.call(s.font,x),v=L(y=s.bBox(u.node()),i)}var T=v.textPosAngle,k=void 0===T?i.pxmid:z(d.r,T);if(v.targetX=o+k[0]*v.rCenter+(v.x||0),v.targetY=c+k[1]*v.rCenter+(v.y||0),R(v,y),v.outside){var A=v.targetY;i.yLabelMin=A-y.height/2,i.yLabelMid=A,i.yLabelMax=A+y.height/2,i.labelExtraX=0,i.labelExtraY=0,_=!0}v.fontSize=h.size,p(m.type,v,r),e[a].transform=v,u.attr(\"transform\",l.getTextTransform(v))}))}function C(t,e,r,n){var a=n*(e[0]-t[0]),o=n*(e[1]-t[1]);return\"a\"+n*d.r+\",\"+n*d.r+\" 0 \"+i.largeArc+(r?\" 1 \":\" 0 \")+a+\",\"+o}}));var T=n.select(this).selectAll(\"g.titletext\").data(m.title.text?[0]:[]);if(T.enter().append(\"g\").classed(\"titletext\",!0),T.exit().remove(),T.each((function(){var e,r=l.ensureSingle(n.select(this),\"text\",\"\",(function(t){t.attr(\"data-notex\",1)})),i=m.title.text;m._meta&&(i=l.templateString(i,m._meta)),r.text(i).attr({class:\"titletext\",transform:\"\",\"text-anchor\":\"middle\"}).call(s.font,m.title.font).call(f.convertToTspans,t),e=\"middle center\"===m.title.position?function(t){var e=Math.sqrt(t.titleBox.width*t.titleBox.width+t.titleBox.height*t.titleBox.height);return{x:t.cx,y:t.cy,scale:t.trace.hole*t.r*2/e,tx:0,ty:-t.titleBox.height/2+t.trace.title.font.size}}(d):C(d,a),r.attr(\"transform\",u(e.x,e.y)+c(Math.min(1,e.scale))+u(e.tx,e.ty))})),_&&function(t,e){var r,n,i,a,o,s,l,c,u,f,h,p,d;function m(t,e){return t.pxmid[1]-e.pxmid[1]}function v(t,e){return e.pxmid[1]-t.pxmid[1]}function y(t,r){r||(r={});var 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n=t(\"@plotly/d3\"),i=t(\"../../lib\"),a=i.numberFormat,o=t(\"./render\"),s=t(\"../../components/fx\"),l=t(\"../../components/color\"),c=t(\"./constants\").cn,u=i._;function f(t){return\"\"!==t}function h(t,e){return t.filter((function(t){return t.key===e.traceId}))}function p(t,e){n.select(t).select(\"path\").style(\"fill-opacity\",e),n.select(t).select(\"rect\").style(\"fill-opacity\",e)}function d(t){n.select(t).select(\"text.name\").style(\"fill\",\"black\")}function m(t){return function(e){return-1!==t.node.sourceLinks.indexOf(e.link)||-1!==t.node.targetLinks.indexOf(e.link)}}function g(t){return function(e){return-1!==e.node.sourceLinks.indexOf(t.link)||-1!==e.node.targetLinks.indexOf(t.link)}}function v(t,e,r){e&&r&&h(r,e).selectAll(\".\"+c.sankeyLink).filter(m(e)).call(x.bind(0,e,r,!1))}function y(t,e,r){e&&r&&h(r,e).selectAll(\".\"+c.sankeyLink).filter(m(e)).call(b.bind(0,e,r,!1))}function x(t,e,r,n){var i=n.datum().link.label;n.style(\"fill-opacity\",(function(t){if(!t.link.concentrationscale)return.4})),i&&h(e,t).selectAll(\".\"+c.sankeyLink).filter((function(t){return t.link.label===i})).style(\"fill-opacity\",(function(t){if(!t.link.concentrationscale)return.4})),r&&h(e,t).selectAll(\".\"+c.sankeyNode).filter(g(t)).call(v)}function b(t,e,r,n){var i=n.datum().link.label;n.style(\"fill-opacity\",(function(t){return t.tinyColorAlpha})),i&&h(e,t).selectAll(\".\"+c.sankeyLink).filter((function(t){return t.link.label===i})).style(\"fill-opacity\",(function(t){return t.tinyColorAlpha})),r&&h(e,t).selectAll(c.sankeyNode).filter(g(t)).call(y)}function _(t,e){var r=t.hoverlabel||{},n=i.nestedProperty(r,e).get();return!Array.isArray(n)&&n}e.exports=function(t,e){for(var r=t._fullLayout,i=r._paper,h=r._size,m=0;m<t._fullData.length;m++)if(t._fullData[m].visible&&t._fullData[m].type===c.sankey&&!t._fullData[m]._viewInitial){var g=t._fullData[m].node;t._fullData[m]._viewInitial={node:{groups:g.groups.slice(),x:g.x.slice(),y:g.y.slice()}}}var w=u(t,\"source:\")+\" \",T=u(t,\"target:\")+\" \",k=u(t,\"concentration:\")+\" \",A=u(t,\"incoming flow count:\")+\" \",M=u(t,\"outgoing flow count:\")+\" \";o(t,i,e,{width:h.w,height:h.h,margin:{t:h.t,r:h.r,b:h.b,l:h.l}},{linkEvents:{hover:function(e,r,i){!1!==t._fullLayout.hovermode&&(n.select(e).call(x.bind(0,r,i,!0)),\"skip\"!==r.link.trace.link.hoverinfo&&(r.link.fullData=r.link.trace,t.emit(\"plotly_hover\",{event:n.event,points:[r.link]})))},follow:function(e,i){if(!1!==t._fullLayout.hovermode){var o=i.link.trace.link;if(\"none\"!==o.hoverinfo&&\"skip\"!==o.hoverinfo){for(var c=[],u=0,h=0;h<i.flow.links.length;h++){var m=i.flow.links[h];if(\"closest\"!==t._fullLayout.hovermode||i.link.pointNumber===m.pointNumber){i.link.pointNumber===m.pointNumber&&(u=h),m.fullData=m.trace,o=i.link.trace.link;var g=y(m),v={valueLabel:a(i.valueFormat)(m.value)+i.valueSuffix};c.push({x:g[0],y:g[1],name:v.valueLabel,text:[m.label||\"\",w+m.source.label,T+m.target.label,m.concentrationscale?k+a(\"%0.2f\")(m.flow.labelConcentration):\"\"].filter(f).join(\"<br>\"),color:_(o,\"bgcolor\")||l.addOpacity(m.color,1),borderColor:_(o,\"bordercolor\"),fontFamily:_(o,\"font.family\"),fontSize:_(o,\"font.size\"),fontColor:_(o,\"font.color\"),nameLength:_(o,\"namelength\"),textAlign:_(o,\"align\"),idealAlign:n.event.x<g[0]?\"right\":\"left\",hovertemplate:o.hovertemplate,hovertemplateLabels:v,eventData:[m]})}}s.loneHover(c,{container:r._hoverlayer.node(),outerContainer:r._paper.node(),gd:t,anchorIndex:u}).each((function(){i.link.concentrationscale||p(this,.65),d(this)}))}}function y(t){var e,r;t.circular?(e=(t.circularPathData.leftInnerExtent+t.circularPathData.rightInnerExtent)/2,r=t.circularPathData.verticalFullExtent):(e=(t.source.x1+t.target.x0)/2,r=(t.y0+t.y1)/2);var n=[e,r];return\"v\"===t.trace.orientation&&n.reverse(),n[0]+=i.parent.translateX,n[1]+=i.parent.translateY,n}},unhover:function(e,i,a){!1!==t._fullLayout.hovermode&&(n.select(e).call(b.bind(0,i,a,!0)),\"skip\"!==i.link.trace.link.hoverinfo&&(i.link.fullData=i.link.trace,t.emit(\"plotly_unhover\",{event:n.event,points:[i.link]})),s.loneUnhover(r._hoverlayer.node()))},select:function(e,r){var i=r.link;i.originalEvent=n.event,t._hoverdata=[i],s.click(t,{target:!0})}},nodeEvents:{hover:function(e,r,i){!1!==t._fullLayout.hovermode&&(n.select(e).call(v,r,i),\"skip\"!==r.node.trace.node.hoverinfo&&(r.node.fullData=r.node.trace,t.emit(\"plotly_hover\",{event:n.event,points:[r.node]})))},follow:function(e,i){if(!1!==t._fullLayout.hovermode){var o=i.node.trace.node;if(\"none\"!==o.hoverinfo&&\"skip\"!==o.hoverinfo){var l=n.select(e).select(\".\"+c.nodeRect),u=t._fullLayout._paperdiv.node().getBoundingClientRect(),h=l.node().getBoundingClientRect(),m=h.left-2-u.left,g=h.right+2-u.left,v=h.top+h.height/4-u.top,y={valueLabel:a(i.valueFormat)(i.node.value)+i.valueSuffix};i.node.fullData=i.node.trace,t._fullLayout._calcInverseTransform(t);var x=t._fullLayout._invScaleX,b=t._fullLayout._invScaleY,w=s.loneHover({x0:x*m,x1:x*g,y:b*v,name:a(i.valueFormat)(i.node.value)+i.valueSuffix,text:[i.node.label,A+i.node.targetLinks.length,M+i.node.sourceLinks.length].filter(f).join(\"<br>\"),color:_(o,\"bgcolor\")||i.tinyColorHue,borderColor:_(o,\"bordercolor\"),fontFamily:_(o,\"font.family\"),fontSize:_(o,\"font.size\"),fontColor:_(o,\"font.color\"),nameLength:_(o,\"namelength\"),textAlign:_(o,\"align\"),idealAlign:\"left\",hovertemplate:o.hovertemplate,hovertemplateLabels:y,eventData:[i.node]},{container:r._hoverlayer.node(),outerContainer:r._paper.node(),gd:t});p(w,.85),d(w)}}},unhover:function(e,i,a){!1!==t._fullLayout.hovermode&&(n.select(e).call(y,i,a),\"skip\"!==i.node.trace.node.hoverinfo&&(i.node.fullData=i.node.trace,t.emit(\"plotly_unhover\",{event:n.event,points:[i.node]})),s.loneUnhover(r._hoverlayer.node()))},select:function(e,r,i){var a=r.node;a.originalEvent=n.event,t._hoverdata=[a],n.select(e).call(y,r,i),s.click(t,{target:!0})}}})}},{\"../../components/color\":366,\"../../components/fx\":406,\"../../lib\":503,\"./constants\":920,\"./render\":924,\"@plotly/d3\":58}],924:[function(t,e,r){\"use strict\";var n=t(\"d3-force\"),i=t(\"d3-interpolate\").interpolateNumber,a=t(\"@plotly/d3\"),o=t(\"@plotly/d3-sankey\"),s=t(\"@plotly/d3-sankey-circular\"),l=t(\"./constants\"),c=t(\"tinycolor2\"),u=t(\"../../components/color\"),f=t(\"../../components/drawing\"),h=t(\"../../lib\"),p=h.strTranslate,d=h.strRotate,m=t(\"../../lib/gup\"),g=m.keyFun,v=m.repeat,y=m.unwrap,x=t(\"../../lib/svg_text_utils\"),b=t(\"../../registry\"),_=t(\"../../constants/alignment\"),w=_.CAP_SHIFT,T=_.LINE_SPACING;function k(t,e,r){var n,i=y(e),a=i.trace,u=a.domain,f=\"h\"===a.orientation,p=a.node.pad,d=a.node.thickness,m=t.width*(u.x[1]-u.x[0]),g=t.height*(u.y[1]-u.y[0]),v=i._nodes,x=i._links,b=i.circular;(n=b?s.sankeyCircular().circularLinkGap(0):o.sankey()).iterations(l.sankeyIterations).size(f?[m,g]:[g,m]).nodeWidth(d).nodePadding(p).nodeId((function(t){return t.pointNumber})).nodes(v).links(x);var _,w,T,k=n();for(var A in n.nodePadding()<p&&h.warn(\"node.pad was reduced to \",n.nodePadding(),\" to fit within the figure.\"),i._groupLookup){var M,S=parseInt(i._groupLookup[A]);for(_=0;_<k.nodes.length;_++)if(k.nodes[_].pointNumber===S){M=k.nodes[_];break}if(M){var E={pointNumber:parseInt(A),x0:M.x0,x1:M.x1,y0:M.y0,y1:M.y1,partOfGroup:!0,sourceLinks:[],targetLinks:[]};k.nodes.unshift(E),M.childrenNodes.unshift(E)}}if(function(){for(_=0;_<k.nodes.length;_++){var t,e,r=k.nodes[_],n={};for(w=0;w<r.targetLinks.length;w++)t=(e=r.targetLinks[w]).source.pointNumber+\":\"+e.target.pointNumber,n.hasOwnProperty(t)||(n[t]=[]),n[t].push(e);var i=Object.keys(n);for(w=0;w<i.length;w++){var a=n[t=i[w]],o=0,s={};for(T=0;T<a.length;T++)s[(e=a[T]).label]||(s[e.label]=0),s[e.label]+=e.value,o+=e.value;for(T=0;T<a.length;T++)(e=a[T]).flow={value:o,labelConcentration:s[e.label]/o,concentration:e.value/o,links:a},e.concentrationscale&&(e.color=c(e.concentrationscale(e.flow.labelConcentration)))}var l=0;for(w=0;w<r.sourceLinks.length;w++)l+=r.sourceLinks[w].value;for(w=0;w<r.sourceLinks.length;w++)(e=r.sourceLinks[w]).concentrationOut=e.value/l;var u=0;for(w=0;w<r.targetLinks.length;w++)u+=r.targetLinks[w].value;for(w=0;w<r.targetLinks.length;w++)(e=r.targetLinks[w]).concenrationIn=e.value/u}}(),a.node.x.length&&a.node.y.length){for(_=0;_<Math.min(a.node.x.length,a.node.y.length,k.nodes.length);_++)if(a.node.x[_]&&a.node.y[_]){var L=[a.node.x[_]*m,a.node.y[_]*g];k.nodes[_].x0=L[0]-d/2,k.nodes[_].x1=L[0]+d/2;var C=k.nodes[_].y1-k.nodes[_].y0;k.nodes[_].y0=L[1]-C/2,k.nodes[_].y1=L[1]+C/2}if(\"snap\"===a.arrangement)!function(t){t.forEach((function(t){var e,r,n,i=0,a=t.length;for(t.sort((function(t,e){return t.y0-e.y0})),n=0;n<a;++n)(e=t[n]).y0>=i||(r=i-e.y0)>1e-6&&(e.y0+=r,e.y1+=r),i=e.y1+p}))}(function(t){var e,r,n=t.map((function(t,e){return{x0:t.x0,index:e}})).sort((function(t,e){return t.x0-e.x0})),i=[],a=-1,o=-1/0;for(_=0;_<n.length;_++){var s=t[n[_].index];s.x0>o+d&&(a+=1,e=s.x0),o=s.x0,i[a]||(i[a]=[]),i[a].push(s),r=e-s.x0,s.x0+=r,s.x1+=r}return i}(v=k.nodes));n.update(k)}return{circular:b,key:r,trace:a,guid:h.randstr(),horizontal:f,width:m,height:g,nodePad:a.node.pad,nodeLineColor:a.node.line.color,nodeLineWidth:a.node.line.width,linkLineColor:a.link.line.color,linkLineWidth:a.link.line.width,valueFormat:a.valueformat,valueSuffix:a.valuesuffix,textFont:a.textfont,translateX:u.x[0]*t.width+t.margin.l,translateY:t.height-u.y[1]*t.height+t.margin.t,dragParallel:f?g:m,dragPerpendicular:f?m:g,arrangement:a.arrangement,sankey:n,graph:k,forceLayouts:{},interactionState:{dragInProgress:!1,hovered:!1}}}function A(t,e,r){var n=c(e.color),i=e.source.label+\"|\"+e.target.label+\"__\"+r;return e.trace=t.trace,e.curveNumber=t.trace.index,{circular:t.circular,key:i,traceId:t.key,pointNumber:e.pointNumber,link:e,tinyColorHue:u.tinyRGB(n),tinyColorAlpha:n.getAlpha(),linkPath:M,linkLineColor:t.linkLineColor,linkLineWidth:t.linkLineWidth,valueFormat:t.valueFormat,valueSuffix:t.valueSuffix,sankey:t.sankey,parent:t,interactionState:t.interactionState,flow:e.flow}}function M(){return function(t){if(t.link.circular)return e=t.link,r=e.width/2,n=e.circularPathData,\"top\"===e.circularLinkType?\"M \"+n.targetX+\" \"+(n.targetY+r)+\" L\"+n.rightInnerExtent+\" \"+(n.targetY+r)+\"A\"+(n.rightLargeArcRadius+r)+\" \"+(n.rightSmallArcRadius+r)+\" 0 0 1 \"+(n.rightFullExtent-r)+\" \"+(n.targetY-n.rightSmallArcRadius)+\"L\"+(n.rightFullExtent-r)+\" \"+n.verticalRightInnerExtent+\"A\"+(n.rightLargeArcRadius+r)+\" \"+(n.rightLargeArcRadius+r)+\" 0 0 1 \"+n.rightInnerExtent+\" \"+(n.verticalFullExtent-r)+\"L\"+n.leftInnerExtent+\" \"+(n.verticalFullExtent-r)+\"A\"+(n.leftLargeArcRadius+r)+\" \"+(n.leftLargeArcRadius+r)+\" 0 0 1 \"+(n.leftFullExtent+r)+\" \"+n.verticalLeftInnerExtent+\"L\"+(n.leftFullExtent+r)+\" \"+(n.sourceY-n.leftSmallArcRadius)+\"A\"+(n.leftLargeArcRadius+r)+\" \"+(n.leftSmallArcRadius+r)+\" 0 0 1 \"+n.leftInnerExtent+\" \"+(n.sourceY+r)+\"L\"+n.sourceX+\" \"+(n.sourceY+r)+\"L\"+n.sourceX+\" \"+(n.sourceY-r)+\"L\"+n.leftInnerExtent+\" \"+(n.sourceY-r)+\"A\"+(n.leftLargeArcRadius-r)+\" \"+(n.leftSmallArcRadius-r)+\" 0 0 0 \"+(n.leftFullExtent-r)+\" \"+(n.sourceY-n.leftSmallArcRadius)+\"L\"+(n.leftFullExtent-r)+\" \"+n.verticalLeftInnerExtent+\"A\"+(n.leftLargeArcRadius-r)+\" \"+(n.leftLargeArcRadius-r)+\" 0 0 0 \"+n.leftInnerExtent+\" \"+(n.verticalFullExtent+r)+\"L\"+n.rightInnerExtent+\" \"+(n.verticalFullExtent+r)+\"A\"+(n.rightLargeArcRadius-r)+\" \"+(n.rightLargeArcRadius-r)+\" 0 0 0 \"+(n.rightFullExtent+r)+\" \"+n.verticalRightInnerExtent+\"L\"+(n.rightFullExtent+r)+\" \"+(n.targetY-n.rightSmallArcRadius)+\"A\"+(n.rightLargeArcRadius-r)+\" \"+(n.rightSmallArcRadius-r)+\" 0 0 0 \"+n.rightInnerExtent+\" \"+(n.targetY-r)+\"L\"+n.targetX+\" \"+(n.targetY-r)+\"Z\":\"M \"+n.targetX+\" \"+(n.targetY-r)+\" L\"+n.rightInnerExtent+\" \"+(n.targetY-r)+\"A\"+(n.rightLargeArcRadius+r)+\" \"+(n.rightSmallArcRadius+r)+\" 0 0 0 \"+(n.rightFullExtent-r)+\" \"+(n.targetY+n.rightSmallArcRadius)+\"L\"+(n.rightFullExtent-r)+\" \"+n.verticalRightInnerExtent+\"A\"+(n.rightLargeArcRadius+r)+\" \"+(n.rightLargeArcRadius+r)+\" 0 0 0 \"+n.rightInnerExtent+\" \"+(n.verticalFullExtent+r)+\"L\"+n.leftInnerExtent+\" \"+(n.verticalFullExtent+r)+\"A\"+(n.leftLargeArcRadius+r)+\" \"+(n.leftLargeArcRadius+r)+\" 0 0 0 \"+(n.leftFullExtent+r)+\" \"+n.verticalLeftInnerExtent+\"L\"+(n.leftFullExtent+r)+\" \"+(n.sourceY+n.leftSmallArcRadius)+\"A\"+(n.leftLargeArcRadius+r)+\" \"+(n.leftSmallArcRadius+r)+\" 0 0 0 \"+n.leftInnerExtent+\" \"+(n.sourceY-r)+\"L\"+n.sourceX+\" \"+(n.sourceY-r)+\"L\"+n.sourceX+\" \"+(n.sourceY+r)+\"L\"+n.leftInnerExtent+\" \"+(n.sourceY+r)+\"A\"+(n.leftLargeArcRadius-r)+\" \"+(n.leftSmallArcRadius-r)+\" 0 0 1 \"+(n.leftFullExtent-r)+\" \"+(n.sourceY+n.leftSmallArcRadius)+\"L\"+(n.leftFullExtent-r)+\" \"+n.verticalLeftInnerExtent+\"A\"+(n.leftLargeArcRadius-r)+\" \"+(n.leftLargeArcRadius-r)+\" 0 0 1 \"+n.leftInnerExtent+\" \"+(n.verticalFullExtent-r)+\"L\"+n.rightInnerExtent+\" \"+(n.verticalFullExtent-r)+\"A\"+(n.rightLargeArcRadius-r)+\" \"+(n.rightLargeArcRadius-r)+\" 0 0 1 \"+(n.rightFullExtent+r)+\" \"+n.verticalRightInnerExtent+\"L\"+(n.rightFullExtent+r)+\" \"+(n.targetY+n.rightSmallArcRadius)+\"A\"+(n.rightLargeArcRadius-r)+\" \"+(n.rightSmallArcRadius-r)+\" 0 0 1 \"+n.rightInnerExtent+\" \"+(n.targetY+r)+\"L\"+n.targetX+\" \"+(n.targetY+r)+\"Z\";var e,r,n,a=t.link.source.x1,o=t.link.target.x0,s=i(a,o),l=s(.5),c=s(.5),u=t.link.y0-t.link.width/2,f=t.link.y0+t.link.width/2,h=t.link.y1-t.link.width/2,p=t.link.y1+t.link.width/2;return\"M\"+a+\",\"+u+\"C\"+l+\",\"+u+\" \"+c+\",\"+h+\" 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e.group&&(s=h.randstr()),e.trace=t.trace,e.curveNumber=t.trace.index,{index:e.pointNumber,key:s,partOfGroup:e.partOfGroup||!1,group:e.group,traceId:t.key,trace:t.trace,node:e,nodePad:t.nodePad,nodeLineColor:t.nodeLineColor,nodeLineWidth:t.nodeLineWidth,textFont:t.textFont,size:t.horizontal?t.height:t.width,visibleWidth:Math.ceil(a),visibleHeight:o,zoneX:-n,zoneY:-i,zoneWidth:a+2*n,zoneHeight:o+2*i,labelY:t.horizontal?e.dy/2+1:e.dx/2+1,left:1===e.originalLayer,sizeAcross:t.width,forceLayouts:t.forceLayouts,horizontal:t.horizontal,darkBackground:r.getBrightness()<=128,tinyColorHue:u.tinyRGB(r),tinyColorAlpha:r.getAlpha(),valueFormat:t.valueFormat,valueSuffix:t.valueSuffix,sankey:t.sankey,graph:t.graph,arrangement:t.arrangement,uniqueNodeLabelPathId:[t.guid,t.key,s].join(\"_\"),interactionState:t.interactionState,figure:t}}function E(t){t.attr(\"transform\",(function(t){return p(t.node.x0.toFixed(3),t.node.y0.toFixed(3))}))}function L(t){t.call(E)}function 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g=\"projection.\"+d[m];f(g+\".show\")&&(f(g+\".opacity\"),f(g+\".scale\"))}var v=n.getComponentMethod(\"errorbars\",\"supplyDefaults\");v(t,e,h||p||r,{axis:\"z\"}),v(t,e,h||p||r,{axis:\"y\",inherit:\"z\"}),v(t,e,h||p||r,{axis:\"x\",inherit:\"z\"})}else e.visible=!1}},{\"../../lib\":503,\"../../registry\":638,\"../scatter/line_defaults\":940,\"../scatter/marker_defaults\":946,\"../scatter/subtypes\":952,\"../scatter/text_defaults\":953,\"./attributes\":955}],960:[function(t,e,r){\"use 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n=t(\"../scatter/attributes\"),i=t(\"../../plots/attributes\"),a=t(\"../../plots/template_attributes\").hovertemplateAttrs,o=t(\"../../plots/template_attributes\").texttemplateAttrs,s=t(\"../../components/colorscale/attributes\"),l=t(\"../../lib/extend\").extendFlat,c=n.marker,u=n.line,f=c.line;e.exports={carpet:{valType:\"string\",editType:\"calc\"},a:{valType:\"data_array\",editType:\"calc\"},b:{valType:\"data_array\",editType:\"calc\"},mode:l({},n.mode,{dflt:\"markers\"}),text:l({},n.text,{}),texttemplate:o({editType:\"plot\"},{keys:[\"a\",\"b\",\"text\"]}),hovertext:l({},n.hovertext,{}),line:{color:u.color,width:u.width,dash:u.dash,shape:l({},u.shape,{values:[\"linear\",\"spline\"]}),smoothing:u.smoothing,editType:\"calc\"},connectgaps:n.connectgaps,fill:l({},n.fill,{values:[\"none\",\"toself\",\"tonext\"],dflt:\"none\"}),fillcolor:n.fillcolor,marker:l({symbol:c.symbol,opacity:c.opacity,maxdisplayed:c.maxdisplayed,size:c.size,sizeref:c.sizeref,sizemin:c.sizemin,sizemode:c.sizemode,line:l({width:f.width,editType:\"calc\"},s(\"marker.line\")),gradient:c.gradient,editType:\"calc\"},s(\"marker\")),textfont:n.textfont,textposition:n.textposition,selected:n.selected,unselected:n.unselected,hoverinfo:l({},i.hoverinfo,{flags:[\"a\",\"b\",\"text\",\"name\"]}),hoveron:n.hoveron,hovertemplate:a()}},{\"../../components/colorscale/attributes\":373,\"../../lib/extend\":493,\"../../plots/attributes\":550,\"../../plots/template_attributes\":633,\"../scatter/attributes\":927}],962:[function(t,e,r){\"use 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n=t(\"../../lib\"),i=t(\"../scatter/constants\"),a=t(\"../scatter/subtypes\"),o=t(\"../scatter/marker_defaults\"),s=t(\"../scatter/line_defaults\"),l=t(\"../scatter/line_shape_defaults\"),c=t(\"../scatter/text_defaults\"),u=t(\"../scatter/fillcolor_defaults\"),f=t(\"./attributes\");e.exports=function(t,e,r,h){function p(r,i){return n.coerce(t,e,f,r,i)}p(\"carpet\"),e.xaxis=\"x\",e.yaxis=\"y\";var d=p(\"a\"),m=p(\"b\"),g=Math.min(d.length,m.length);if(g){e._length=g,p(\"text\"),p(\"texttemplate\"),p(\"hovertext\"),p(\"mode\",g<i.PTS_LINESONLY?\"lines+markers\":\"lines\"),a.hasLines(e)&&(s(t,e,r,h,p),l(t,e,p),p(\"connectgaps\")),a.hasMarkers(e)&&o(t,e,r,h,p,{gradient:!0}),a.hasText(e)&&c(t,e,h,p);var v=[];(a.hasMarkers(e)||a.hasText(e))&&(p(\"marker.maxdisplayed\"),v.push(\"points\")),p(\"fill\"),\"none\"!==e.fill&&(u(t,e,r,p),a.hasLines(e)||l(t,e,p)),\"tonext\"!==e.fill&&\"toself\"!==e.fill||v.push(\"fills\"),\"fills\"!==p(\"hoveron\",v.join(\"+\")||\"points\")&&p(\"hovertemplate\"),n.coerceSelectionMarkerOpacity(e,p)}else e.visible=!1}},{\"../../lib\":503,\"../scatter/constants\":931,\"../scatter/fillcolor_defaults\":935,\"../scatter/line_defaults\":940,\"../scatter/line_shape_defaults\":942,\"../scatter/marker_defaults\":946,\"../scatter/subtypes\":952,\"../scatter/text_defaults\":953,\"./attributes\":961}],964:[function(t,e,r){\"use strict\";e.exports=function(t,e,r,n,i){var a=n[i];return t.a=a.a,t.b=a.b,t.y=a.y,t}},{}],965:[function(t,e,r){\"use strict\";e.exports=function(t,e){var r={},n=e._carpet,i=n.ab2ij([t.a,t.b]),a=Math.floor(i[0]),o=i[0]-a,s=Math.floor(i[1]),l=i[1]-s,c=n.evalxy([],a,s,o,l);return r.yLabel=c[1].toFixed(3),r}},{}],966:[function(t,e,r){\"use strict\";var n=t(\"../scatter/hover\"),i=t(\"../../lib\").fillText;e.exports=function(t,e,r,a){var o=n(t,e,r,a);if(o&&!1!==o[0].index){var s=o[0];if(void 0===s.index){var l=1-s.y0/t.ya._length,c=t.xa._length,u=c*l/2,f=c-u;return s.x0=Math.max(Math.min(s.x0,f),u),s.x1=Math.max(Math.min(s.x1,f),u),o}var h=s.cd[s.index];s.a=h.a,s.b=h.b,s.xLabelVal=void 0,s.yLabelVal=void 0;var p=s.trace,d=p._carpet,m=p._module.formatLabels(h,p);s.yLabel=m.yLabel,delete s.text;var g=[];if(!p.hovertemplate){var v=(h.hi||p.hoverinfo).split(\"+\");-1!==v.indexOf(\"all\")&&(v=[\"a\",\"b\",\"text\"]),-1!==v.indexOf(\"a\")&&y(d.aaxis,h.a),-1!==v.indexOf(\"b\")&&y(d.baxis,h.b),g.push(\"y: \"+s.yLabel),-1!==v.indexOf(\"text\")&&i(h,p,g),s.extraText=g.join(\"<br>\")}return o}function y(t,e){var r;r=t.labelprefix&&t.labelprefix.length>0?t.labelprefix.replace(/ = $/,\"\"):t._hovertitle,g.push(r+\": \"+e.toFixed(3)+t.labelsuffix)}}},{\"../../lib\":503,\"../scatter/hover\":938}],967:[function(t,e,r){\"use 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n=t(\"../../lib\"),i=t(\"../scatter/subtypes\"),a=t(\"../scatter/marker_defaults\"),o=t(\"../scatter/line_defaults\"),s=t(\"../scatter/text_defaults\"),l=t(\"../scatter/fillcolor_defaults\"),c=t(\"./attributes\");e.exports=function(t,e,r,u){function f(r,i){return n.coerce(t,e,c,r,i)}var h,p=f(\"locations\");if(p&&p.length){var d,m=f(\"geojson\");(\"string\"==typeof m&&\"\"!==m||n.isPlainObject(m))&&(d=\"geojson-id\"),\"geojson-id\"===f(\"locationmode\",d)&&f(\"featureidkey\"),h=p.length}else{var 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M=p.font[r]={};M.size=(s.isTypedArray(f)?f[r]:Array.isArray(f)?n(f[r])?f[r]:0:f)*d,M.family=Array.isArray(h)?h[r]:h}else p.font={size:f*d,family:h};return p}function x(t){var e,r,n=t._length,i=t.marker,o={},l=s.isArrayOrTypedArray(i.symbol),c=s.isArrayOrTypedArray(i.color),f=s.isArrayOrTypedArray(i.line.color),d=s.isArrayOrTypedArray(i.opacity),m=s.isArrayOrTypedArray(i.size),g=s.isArrayOrTypedArray(i.line.width);if(l||(r=p.isOpenSymbol(i.symbol)),l||c||f||d){o.colors=new Array(n),o.borderColors=new Array(n);var v=u(i,i.opacity,n),y=u(i.line,i.opacity,n);if(!Array.isArray(y[0])){var x=y;for(y=Array(n),e=0;e<n;e++)y[e]=x}if(!Array.isArray(v[0])){var b=v;for(v=Array(n),e=0;e<n;e++)v[e]=b}for(o.colors=v,o.borderColors=y,e=0;e<n;e++){if(l){var _=i.symbol[e];r=p.isOpenSymbol(_)}r&&(y[e]=v[e].slice(),v[e]=v[e].slice(),v[e][3]=0)}o.opacity=t.opacity}else 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i={opacity:1,text:e.text,texttemplate:e.texttemplate,textposition:e.textposition,textfont:s.extendFlat({},e.textfont)};r.textfont&&s.extendFlat(i.textfont,r.textfont),n=y(t,i)}return n}function w(t,e,r){var n={capSize:2*e.width*r,lineWidth:e.thickness*r,color:e.color};return e.copy_ystyle&&(n=t.error_y),n}var T=d.SYMBOL_SDF_SIZE,k=d.SYMBOL_SIZE,A=d.SYMBOL_STROKE,M={},S=l.symbolFuncs[0](.05*k);function E(t){if(\"circle\"===t)return null;var e,r,n=l.symbolNumber(t),a=l.symbolFuncs[n%100],o=!!l.symbolNoDot[n%100],s=!!l.symbolNoFill[n%100],c=p.isDotSymbol(t);return M[t]?M[t]:(e=c&&!o?a(1.1*k)+S:a(k),r=i(e,{w:T,h:T,viewBox:[-k,-k,k,k],stroke:s?A:-A}),M[t]=r,r||null)}e.exports={style:function(t,e){var r,n={marker:void 0,markerSel:void 0,markerUnsel:void 0,line:void 0,fill:void 0,errorX:void 0,errorY:void 0,text:void 0,textSel:void 0,textUnsel:void 0},i=t._context.plotGlPixelRatio;if(!0!==e.visible)return 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T=y-_,k=y+w;p[v+u[0]]=x-i.c2l(T),p[v+u[1]]=i.c2l(k)-x,p[v+u[2]]=0,p[v+u[3]]=0,d=Math.min(d,y-_),m=Math.max(m,y+w)}}}h[a]={positions:r,errors:p,_bnds:[d,m]}}}return p(i,l),p(a,u),h},textPosition:function(t,e,r,n){var i,a=e._length,o={};if(f.hasMarkers(e)){var s=r.font,l=r.align,c=r.baseline;for(o.offset=new Array(a),i=0;i<a;i++){var u=n.sizes?n.sizes[i]:n.size,h=Array.isArray(s)?s[i].size:s.size,p=Array.isArray(l)?l.length>1?l[i]:l[0]:l,d=Array.isArray(c)?c.length>1?c[i]:c[0]:c,m=g[p],v=g[d],y=u?u/.8+1:0,x=-v*y-.5*v;o.offset[i]=[m*y/h,x/h]}}return o}}},{\"../../components/drawing\":388,\"../../components/fx/helpers\":402,\"../../constants/interactions\":478,\"../../lib\":503,\"../../lib/gl_format_color\":499,\"../../plots/cartesian/axis_ids\":558,\"../../registry\":638,\"../scatter/make_bubble_size_func\":944,\"../scatter/subtypes\":952,\"./constants\":982,\"./helpers\":987,\"color-normalize\":89,\"fast-isnumeric\":190,\"svg-path-sdf\":310}],984:[function(t,e,r){\"use strict\";var n=t(\"../../lib\"),i=t(\"../../registry\"),a=t(\"./helpers\"),o=t(\"./attributes\"),s=t(\"../scatter/constants\"),l=t(\"../scatter/subtypes\"),c=t(\"../scatter/xy_defaults\"),u=t(\"../scatter/period_defaults\"),f=t(\"../scatter/marker_defaults\"),h=t(\"../scatter/line_defaults\"),p=t(\"../scatter/fillcolor_defaults\"),d=t(\"../scatter/text_defaults\");e.exports=function(t,e,r,m){function g(r,i){return n.coerce(t,e,o,r,i)}var v=!!t.marker&&a.isOpenSymbol(t.marker.symbol),y=l.isBubble(t),x=c(t,e,m,g);if(x){u(t,e,m,g),g(\"xhoverformat\"),g(\"yhoverformat\");var b=x<s.PTS_LINESONLY?\"lines+markers\":\"lines\";g(\"text\"),g(\"hovertext\"),g(\"hovertemplate\"),g(\"mode\",b),l.hasLines(e)&&(g(\"connectgaps\"),h(t,e,r,m,g),g(\"line.shape\")),l.hasMarkers(e)&&(f(t,e,r,m,g),g(\"marker.line.width\",v||y?1:0)),l.hasText(e)&&(g(\"texttemplate\"),d(t,e,m,g));var _=(e.line||{}).color,w=(e.marker||{}).color;g(\"fill\"),\"none\"!==e.fill&&p(t,e,r,g);var T=i.getComponentMethod(\"errorbars\",\"supplyDefaults\");T(t,e,_||w||r,{axis:\"y\"}),T(t,e,_||w||r,{axis:\"x\",inherit:\"y\"}),n.coerceSelectionMarkerOpacity(e,g)}else e.visible=!1}},{\"../../lib\":503,\"../../registry\":638,\"../scatter/constants\":931,\"../scatter/fillcolor_defaults\":935,\"../scatter/line_defaults\":940,\"../scatter/marker_defaults\":946,\"../scatter/period_defaults\":947,\"../scatter/subtypes\":952,\"../scatter/text_defaults\":953,\"../scatter/xy_defaults\":954,\"./attributes\":979,\"./helpers\":987}],985:[function(t,e,r){\"use strict\";var n=t(\"../../lib\"),i=t(\"../../components/color\"),a=t(\"../../constants/interactions\").DESELECTDIM;e.exports={styleTextSelection:function(t){var e,r,o=t[0],s=o.trace,l=o.t,c=l._scene,u=l.index,f=c.selectBatch[u],h=c.unselectBatch[u],p=c.textOptions[u],d=c.textSelectedOptions[u]||{},m=c.textUnselectedOptions[u]||{},g=n.extendFlat({},p);if(f.length||h.length){var v=d.color,y=m.color,x=p.color,b=Array.isArray(x);for(g.color=new Array(s._length),e=0;e<f.length;e++)r=f[e],g.color[r]=v||(b?x[r]:x);for(e=0;e<h.length;e++){r=h[e];var _=b?x[r]:x;g.color[r]=y||(v?_:i.addOpacity(_,a))}}c.glText[u].update(g)}}},{\"../../components/color\":366,\"../../constants/interactions\":478,\"../../lib\":503}],986:[function(t,e,r){\"use strict\";var n=t(\"../scatter/format_labels\");e.exports=function(t,e,r){var i=t.i;return\"x\"in t||(t.x=e._x[i]),\"y\"in t||(t.y=e._y[i]),n(t,e,r)}},{\"../scatter/format_labels\":936}],987:[function(t,e,r){\"use strict\";var n=t(\"./constants\");r.isOpenSymbol=function(t){return\"string\"==typeof t?n.OPEN_RE.test(t):t%200>100},r.isDotSymbol=function(t){return\"string\"==typeof t?n.DOT_RE.test(t):t>200}},{\"./constants\":982}],988:[function(t,e,r){\"use strict\";var n=t(\"../../registry\"),i=t(\"../../lib\"),a=t(\"../scatter/get_trace_color\");function o(t,e,r,o){var s=t.xa,l=t.ya,c=t.distance,u=t.dxy,f=t.index,h={pointNumber:f,x:e[f],y:r[f]};h.tx=Array.isArray(o.text)?o.text[f]:o.text,h.htx=Array.isArray(o.hovertext)?o.hovertext[f]:o.hovertext,h.data=Array.isArray(o.customdata)?o.customdata[f]:o.customdata,h.tp=Array.isArray(o.textposition)?o.textposition[f]:o.textposition;var p=o.textfont;p&&(h.ts=i.isArrayOrTypedArray(p.size)?p.size[f]:p.size,h.tc=Array.isArray(p.color)?p.color[f]:p.color,h.tf=Array.isArray(p.family)?p.family[f]:p.family);var d=o.marker;d&&(h.ms=i.isArrayOrTypedArray(d.size)?d.size[f]:d.size,h.mo=i.isArrayOrTypedArray(d.opacity)?d.opacity[f]:d.opacity,h.mx=i.isArrayOrTypedArray(d.symbol)?d.symbol[f]:d.symbol,h.mc=i.isArrayOrTypedArray(d.color)?d.color[f]:d.color);var m=d&&d.line;m&&(h.mlc=Array.isArray(m.color)?m.color[f]:m.color,h.mlw=i.isArrayOrTypedArray(m.width)?m.width[f]:m.width);var g=d&&d.gradient;g&&\"none\"!==g.type&&(h.mgt=Array.isArray(g.type)?g.type[f]:g.type,h.mgc=Array.isArray(g.color)?g.color[f]:g.color);var v=s.c2p(h.x,!0),y=l.c2p(h.y,!0),x=h.mrc||1,b=o.hoverlabel;b&&(h.hbg=Array.isArray(b.bgcolor)?b.bgcolor[f]:b.bgcolor,h.hbc=Array.isArray(b.bordercolor)?b.bordercolor[f]:b.bordercolor,h.hts=i.isArrayOrTypedArray(b.font.size)?b.font.size[f]:b.font.size,h.htc=Array.isArray(b.font.color)?b.font.color[f]:b.font.color,h.htf=Array.isArray(b.font.family)?b.font.family[f]:b.font.family,h.hnl=i.isArrayOrTypedArray(b.namelength)?b.namelength[f]:b.namelength);var _=o.hoverinfo;_&&(h.hi=Array.isArray(_)?_[f]:_);var w=o.hovertemplate;w&&(h.ht=Array.isArray(w)?w[f]:w);var T={};T[t.index]=h;var k=o._origX,A=o._origY,M=i.extendFlat({},t,{color:a(o,h),x0:v-x,x1:v+x,xLabelVal:k?k[f]:h.x,y0:y-x,y1:y+x,yLabelVal:A?A[f]:h.y,cd:T,distance:c,spikeDistance:u,hovertemplate:h.ht});return h.htx?M.text=h.htx:h.tx?M.text=h.tx:o.text&&(M.text=o.text),i.fillText(h,o,M),n.getComponentMethod(\"errorbars\",\"hoverInfo\")(h,o,M),M}e.exports={hoverPoints:function(t,e,r,n){var i,a,s,l,c,u,f,h,p,d,m=t.cd,g=m[0].t,v=m[0].trace,y=t.xa,x=t.ya,b=g.x,_=g.y,w=y.c2p(e),T=x.c2p(r),k=t.distance;if(g.tree){var A=y.p2c(w-k),M=y.p2c(w+k),S=x.p2c(T-k),E=x.p2c(T+k);i=\"x\"===n?g.tree.range(Math.min(A,M),Math.min(x._rl[0],x._rl[1]),Math.max(A,M),Math.max(x._rl[0],x._rl[1])):g.tree.range(Math.min(A,M),Math.min(S,E),Math.max(A,M),Math.max(S,E))}else i=g.ids;var L=k;if(\"x\"===n){var C=!!v.xperiodalignment,P=!!v.yperiodalignment;for(u=0;u<i.length;u++){if(l=b[a=i[u]],f=Math.abs(y.c2p(l)-w),C){var I=y.c2p(v._xStarts[a]),O=y.c2p(v._xEnds[a]);f=w>=Math.min(I,O)&&w<=Math.max(I,O)?0:1/0}if(f<L){if(L=f,c=_[a],h=x.c2p(c)-T,P){var z=x.c2p(v._yStarts[a]),D=x.c2p(v._yEnds[a]);h=T>=Math.min(z,D)&&T<=Math.max(z,D)?0:1/0}d=Math.sqrt(f*f+h*h),s=i[u]}}}else for(u=i.length-1;u>-1;u--)l=b[a=i[u]],c=_[a],f=y.c2p(l)-w,h=x.c2p(c)-T,(p=Math.sqrt(f*f+h*h))<L&&(L=d=p,s=a);return t.index=s,t.distance=L,t.dxy=d,void 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_=y.count,w=v._glcanvas.data()[0].regl;if(f(t,e,r),y.dirty){if(!0===y.error2d&&(y.error2d=a(w)),!0===y.line2d&&(y.line2d=i(w)),!0===y.scatter2d&&(y.scatter2d=n(w)),!0===y.fill2d&&(y.fill2d=i(w)),!0===y.glText)for(y.glText=new Array(_),m=0;m<_;m++)y.glText[m]=new o(w);if(y.glText){if(_>y.glText.length){var T=_-y.glText.length;for(m=0;m<T;m++)y.glText.push(new o(w))}else if(_<y.glText.length){var k=y.glText.length-_;y.glText.splice(_,k).forEach((function(t){t.destroy()}))}for(m=0;m<_;m++)y.glText[m].update(y.textOptions[m])}if(y.line2d&&(y.line2d.update(y.lineOptions),y.lineOptions=y.lineOptions.map((function(t){if(t&&t.positions){for(var e=t.positions,r=0;r<e.length&&(isNaN(e[r])||isNaN(e[r+1]));)r+=2;for(var n=e.length-2;n>r&&(isNaN(e[n])||isNaN(e[n+1]));)n-=2;t.positions=e.slice(r,n+2)}return t})),y.line2d.update(y.lineOptions)),y.error2d){var A=(y.errorXOptions||[]).concat(y.errorYOptions||[]);y.error2d.update(A)}y.scatter2d&&y.scatter2d.update(y.markerOptions),y.fillOrder=s.repeat(null,_),y.fill2d&&(y.fillOptions=y.fillOptions.map((function(t,e){var n=r[e];if(t&&n&&n[0]&&n[0].trace){var i,a,o=n[0],s=o.trace,l=o.t,c=y.lineOptions[e],u=[];s._ownfill&&u.push(e),s._nexttrace&&u.push(e+1),u.length&&(y.fillOrder[e]=u);var f,h,p=[],d=c&&c.positions||l.positions;if(\"tozeroy\"===s.fill){for(f=0;f<d.length&&isNaN(d[f+1]);)f+=2;for(h=d.length-2;h>f&&isNaN(d[h+1]);)h-=2;0!==d[f+1]&&(p=[d[f],0]),p=p.concat(d.slice(f,h+2)),0!==d[h+1]&&(p=p.concat([d[h],0]))}else if(\"tozerox\"===s.fill){for(f=0;f<d.length&&isNaN(d[f]);)f+=2;for(h=d.length-2;h>f&&isNaN(d[h]);)h-=2;0!==d[f]&&(p=[0,d[f+1]]),p=p.concat(d.slice(f,h+2)),0!==d[h]&&(p=p.concat([0,d[h+1]]))}else 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R=y.selectBatch[I]=s.selIndices2selPoints(C),F={};for(g=0;g<R.length;g++)F[R[g]]=1;var B=[];for(g=0;g<O;g++)F[g]||B.push(g);y.unselectBatch[I]=B}var N=P.xpx=new Array(O),j=P.ypx=new Array(O);for(g=0;g<O;g++)N[g]=x.c2p(z[g]),j[g]=b.c2p(D[g])}else P.xpx=P.ypx=null}if(S){if(y.select2d||(y.select2d=n(v._glcanvas.data()[1].regl)),y.scatter2d){var U=new Array(_);for(m=0;m<_;m++)U[m]=y.selectBatch[m].length||y.unselectBatch[m].length?y.markerUnselectedOptions[m]:{};y.scatter2d.update(U)}y.select2d&&(y.select2d.update(y.markerOptions),y.select2d.update(y.markerSelectedOptions)),y.glText&&r.forEach((function(t){var e=((t||[])[0]||{}).trace||{};u.hasText(e)&&h(t)}))}else y.scatter2d&&y.scatter2d.update(y.markerOptions);var V={viewport:d(v,x,b,t._context.plotGlPixelRatio),range:[(x._rl||x.range)[0],(b._rl||b.range)[0],(x._rl||x.range)[1],(b._rl||b.range)[1]]},H=s.repeat(V,y.count);y.fill2d&&y.fill2d.update(H),y.line2d&&y.line2d.update(H),y.error2d&&y.error2d.update(H.concat(H)),y.scatter2d&&y.scatter2d.update(H),y.select2d&&y.select2d.update(H),y.glText&&y.glText.forEach((function(t){t.update(V)}))}else y.init()}}).reglPrecompiled=p},{\"../../components/dragelement/helpers\":384,\"../../lib\":503,\"../../lib/prepare_regl\":516,\"../scatter/link_traces\":943,\"../scatter/subtypes\":952,\"./edit_style\":985,\"gl-text\":225,\"regl-error2d\":279,\"regl-line2d\":280,\"regl-scatter2d\":281}],991:[function(t,e,r){\"use strict\";var n=t(\"../../lib\");e.exports=function(t,e){var r=e._scene,i={count:0,dirty:!0,lineOptions:[],fillOptions:[],markerOptions:[],markerSelectedOptions:[],markerUnselectedOptions:[],errorXOptions:[],errorYOptions:[],textOptions:[],textSelectedOptions:[],textUnselectedOptions:[],selectBatch:[],unselectBatch:[]},a={fill2d:!1,scatter2d:!1,error2d:!1,line2d:!1,glText:!1,select2d:!1};return e._scene||((r=e._scene={}).init=function(){n.extendFlat(r,a,i)},r.init(),r.update=function(t){var e=n.repeat(t,r.count);if(r.fill2d&&r.fill2d.update(e),r.scatter2d&&r.scatter2d.update(e),r.line2d&&r.line2d.update(e),r.error2d&&r.error2d.update(e.concat(e)),r.select2d&&r.select2d.update(e),r.glText)for(var i=0;i<r.count;i++)r.glText[i].update(t)},r.draw=function(){for(var t=r.count,e=r.fill2d,i=r.error2d,a=r.line2d,o=r.scatter2d,s=r.glText,l=r.select2d,c=r.selectBatch,u=r.unselectBatch,f=0;f<t;f++){if(e&&r.fillOrder[f]&&e.draw(r.fillOrder[f]),a&&r.lineOptions[f]&&a.draw(f),i&&(r.errorXOptions[f]&&i.draw(f),r.errorYOptions[f]&&i.draw(f+t)),o&&r.markerOptions[f])if(u[f].length){var h=n.repeat([],r.count);h[f]=u[f],o.draw(h)}else c[f].length||o.draw(f);s[f]&&r.textOptions[f]&&s[f].render()}l&&l.draw(c),r.dirty=!1},r.destroy=function(){r.fill2d&&r.fill2d.destroy&&r.fill2d.destroy(),r.scatter2d&&r.scatter2d.destroy&&r.scatter2d.destroy(),r.error2d&&r.error2d.destroy&&r.error2d.destroy(),r.line2d&&r.line2d.destroy&&r.line2d.destroy(),r.select2d&&r.select2d.destroy&&r.select2d.destroy(),r.glText&&r.glText.forEach((function(t){t.destroy&&t.destroy()})),r.lineOptions=null,r.fillOptions=null,r.markerOptions=null,r.markerSelectedOptions=null,r.markerUnselectedOptions=null,r.errorXOptions=null,r.errorYOptions=null,r.textOptions=null,r.textSelectedOptions=null,r.textUnselectedOptions=null,r.selectBatch=null,r.unselectBatch=null,e._scene=null}),r.dirty||n.extendFlat(r,i),r}},{\"../../lib\":503}],992:[function(t,e,r){\"use strict\";var n=t(\"../scatter/subtypes\"),i=t(\"./edit_style\").styleTextSelection;e.exports=function(t,e){var r=t.cd,a=t.xaxis,o=t.yaxis,s=[],l=r[0].trace,c=r[0].t,u=l._length,f=c.x,h=c.y,p=c._scene,d=c.index;if(!p)return s;var m=n.hasText(l),g=n.hasMarkers(l),v=!g&&!m;if(!0!==l.visible||v)return s;var y=[],x=[];if(!1!==e&&!e.degenerate)for(var b=0;b<u;b++)e.contains([c.xpx[b],c.ypx[b]],!1,b,t)?(y.push(b),s.push({pointNumber:b,x:a.c2d(f[b]),y:o.c2d(h[b])})):x.push(b);if(g){var _=p.scatter2d;if(y.length||x.length){if(!p.selectBatch[d].length&&!p.unselectBatch[d].length){var w=new Array(p.count);w[d]=p.markerUnselectedOptions[d],_.update.apply(_,w)}}else{var T=new Array(p.count);T[d]=p.markerOptions[d],_.update.apply(_,T)}}return p.selectBatch[d]=y,p.unselectBatch[d]=x,m&&i(r),s}},{\"../scatter/subtypes\":952,\"./edit_style\":985}],993:[function(t,e,r){\"use strict\";var n=t(\"../../plots/template_attributes\").hovertemplateAttrs,i=t(\"../../plots/template_attributes\").texttemplateAttrs,a=t(\"../scattergeo/attributes\"),o=t(\"../scatter/attributes\"),s=t(\"../../plots/mapbox/layout_attributes\"),l=t(\"../../plots/attributes\"),c=t(\"../../components/colorscale/attributes\"),u=t(\"../../lib/extend\").extendFlat,f=t(\"../../plot_api/edit_types\").overrideAll,h=a.line,p=a.marker;e.exports=f({lon:a.lon,lat:a.lat,mode:u({},o.mode,{dflt:\"markers\"}),text:u({},o.text,{}),texttemplate:i({editType:\"plot\"},{keys:[\"lat\",\"lon\",\"text\"]}),hovertext:u({},o.hovertext,{}),line:{color:h.color,width:h.width},connectgaps:o.connectgaps,marker:u({symbol:{valType:\"string\",dflt:\"circle\",arrayOk:!0},angle:{valType:\"number\",dflt:\"auto\",arrayOk:!0},allowoverlap:{valType:\"boolean\",dflt:!1},opacity:p.opacity,size:p.size,sizeref:p.sizeref,sizemin:p.sizemin,sizemode:p.sizemode},c(\"marker\")),fill:a.fill,fillcolor:o.fillcolor,textfont:s.layers.symbol.textfont,textposition:s.layers.symbol.textposition,below:{valType:\"string\"},selected:{marker:o.selected.marker},unselected:{marker:o.unselected.marker},hoverinfo:u({},l.hoverinfo,{flags:[\"lon\",\"lat\",\"text\",\"name\"]}),hovertemplate:n()},\"calc\",\"nested\")},{\"../../components/colorscale/attributes\":373,\"../../lib/extend\":493,\"../../plot_api/edit_types\":536,\"../../plots/attributes\":550,\"../../plots/mapbox/layout_attributes\":615,\"../../plots/template_attributes\":633,\"../scatter/attributes\":927,\"../scattergeo/attributes\":969}],994:[function(t,e,r){\"use strict\";var n=t(\"fast-isnumeric\"),i=t(\"../../lib\"),a=t(\"../../constants/numerical\").BADNUM,o=t(\"../../lib/geojson_utils\"),s=t(\"../../components/colorscale\"),l=t(\"../../components/drawing\"),c=t(\"../scatter/make_bubble_size_func\"),u=t(\"../scatter/subtypes\"),f=t(\"../../plots/mapbox/convert_text_opts\"),h=t(\"../../components/fx/helpers\").appendArrayPointValue,p=t(\"../../lib/svg_text_utils\").NEWLINES,d=t(\"../../lib/svg_text_utils\").BR_TAG_ALL;function m(){return{geojson:o.makeBlank(),layout:{visibility:\"none\"},paint:{}}}function g(t,e){return i.isArrayOrTypedArray(t)?e?function(e){return n(t[e])?+t[e]:0}:function(e){return t[e]}:t?function(){return t}:v}function v(){return\"\"}function y(t){return t[0]===a}e.exports=function(t,e){var r,a=e[0].trace,x=!0===a.visible&&0!==a._length,b=\"none\"!==a.fill,_=u.hasLines(a),w=u.hasMarkers(a),T=u.hasText(a),k=w&&\"circle\"===a.marker.symbol,A=w&&\"circle\"!==a.marker.symbol,M=m(),S=m(),E=m(),L=m(),C={fill:M,line:S,circle:E,symbol:L};if(!x)return C;if((b||_)&&(r=o.calcTraceToLineCoords(e)),b&&(M.geojson=o.makePolygon(r),M.layout.visibility=\"visible\",i.extendFlat(M.paint,{\"fill-color\":a.fillcolor})),_&&(S.geojson=o.makeLine(r),S.layout.visibility=\"visible\",i.extendFlat(S.paint,{\"line-width\":a.line.width,\"line-color\":a.line.color,\"line-opacity\":a.opacity})),k){var P=function(t){var e,r,a,o,u=t[0].trace,f=u.marker,h=u.selectedpoints,p=i.isArrayOrTypedArray(f.color),d=i.isArrayOrTypedArray(f.size),m=i.isArrayOrTypedArray(f.opacity);function g(t){return u.opacity*t}p&&(r=s.hasColorscale(u,\"marker\")?s.makeColorScaleFuncFromTrace(f):i.identity);d&&(a=c(u));m&&(o=function(t){return g(n(t)?+i.constrain(t,0,1):0)});var v,x=[];for(e=0;e<t.length;e++){var 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n=t(\"../scatterpolar/attributes\"),i=t(\"../scattergl/attributes\"),a=t(\"../../plots/template_attributes\").texttemplateAttrs;e.exports={mode:n.mode,r:n.r,theta:n.theta,r0:n.r0,dr:n.dr,theta0:n.theta0,dtheta:n.dtheta,thetaunit:n.thetaunit,text:n.text,texttemplate:a({editType:\"plot\"},{keys:[\"r\",\"theta\",\"text\"]}),hovertext:n.hovertext,hovertemplate:n.hovertemplate,line:i.line,connectgaps:i.connectgaps,marker:i.marker,fill:i.fill,fillcolor:i.fillcolor,textposition:i.textposition,textfont:i.textfont,hoverinfo:n.hoverinfo,selected:n.selected,unselected:n.unselected}},{\"../../plots/template_attributes\":633,\"../scattergl/attributes\":979,\"../scatterpolar/attributes\":1002}],1010:[function(t,e,r){\"use 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A={};u.label&&(A.label=u.label),u.hasOwnProperty(\"v\")&&(A.value=u.v,A.valueLabel=b.formatValue(u.v,l)),A.currentPath=b.getPath(t.data),h||(A.percentParent=d/b.getValue(p),A.percentParentLabel=b.formatPercent(A.percentParent,l),A.parent=b.getPtLabel(p)),A.percentEntry=d/b.getValue(e),A.percentEntryLabel=b.formatPercent(A.percentEntry,l),A.entry=b.getPtLabel(e),A.percentRoot=d/b.getValue(f),A.percentRootLabel=b.formatPercent(A.percentRoot,l),A.root=b.getPtLabel(f),u.hasOwnProperty(\"color\")&&(A.color=u.color);var M=s.castOption(r,u.i,\"text\");return(s.isValidTextValue(M)||\"\"===M)&&(A.text=M),A.customdata=s.castOption(r,u.i,\"customdata\"),s.texttemplateString(k,A,i._d3locale,A,r._meta||{})}},{\"../../components/drawing\":388,\"../../lib\":503,\"../../lib/svg_text_utils\":529,\"../bar/style\":662,\"../bar/uniform_text\":664,\"../pie/helpers\":906,\"../pie/plot\":910,\"./constants\":1052,\"./fx\":1054,\"./helpers\":1055,\"./style\":1060,\"@plotly/d3\":58,\"d3-hierarchy\":115,\"d3-interpolate\":116}],1060:[function(t,e,r){\"use strict\";var n=t(\"@plotly/d3\"),i=t(\"../../components/color\"),a=t(\"../../lib\"),o=t(\"../bar/uniform_text\").resizeText;function s(t,e,r){var n=e.data.data,o=!e.children,s=n.i,l=a.castOption(r,s,\"marker.line.color\")||i.defaultLine,c=a.castOption(r,s,\"marker.line.width\")||0;t.style(\"stroke-width\",c).call(i.fill,n.color).call(i.stroke,l).style(\"opacity\",o?r.leaf.opacity:null)}e.exports={style:function(t){var e=t._fullLayout._sunburstlayer.selectAll(\".trace\");o(t,e,\"sunburst\"),e.each((function(t){var e=n.select(this),r=t[0].trace;e.style(\"opacity\",r.opacity),e.selectAll(\"path.surface\").each((function(t){n.select(this).call(s,t,r)}))}))},styleOne:s}},{\"../../components/color\":366,\"../../lib\":503,\"../bar/uniform_text\":664,\"@plotly/d3\":58}],1061:[function(t,e,r){\"use strict\";var n=t(\"../../components/color\"),i=t(\"../../components/colorscale/attributes\"),a=t(\"../../plots/cartesian/axis_format_attributes\").axisHoverFormat,o=t(\"../../plots/template_attributes\").hovertemplateAttrs,s=t(\"../../plots/attributes\"),l=t(\"../../lib/extend\").extendFlat,c=t(\"../../plot_api/edit_types\").overrideAll;function u(t){return{show:{valType:\"boolean\",dflt:!1},start:{valType:\"number\",dflt:null,editType:\"plot\"},end:{valType:\"number\",dflt:null,editType:\"plot\"},size:{valType:\"number\",dflt:null,min:0,editType:\"plot\"},project:{x:{valType:\"boolean\",dflt:!1},y:{valType:\"boolean\",dflt:!1},z:{valType:\"boolean\",dflt:!1}},color:{valType:\"color\",dflt:n.defaultLine},usecolormap:{valType:\"boolean\",dflt:!1},width:{valType:\"number\",min:1,max:16,dflt:2},highlight:{valType:\"boolean\",dflt:!0},highlightcolor:{valType:\"color\",dflt:n.defaultLine},highlightwidth:{valType:\"number\",min:1,max:16,dflt:2}}}var f=e.exports=c(l({z:{valType:\"data_array\"},x:{valType:\"data_array\"},y:{valType:\"data_array\"},text:{valType:\"string\",dflt:\"\",arrayOk:!0},hovertext:{valType:\"string\",dflt:\"\",arrayOk:!0},hovertemplate:o(),xhoverformat:a(\"x\"),yhoverformat:a(\"y\"),zhoverformat:a(\"z\"),connectgaps:{valType:\"boolean\",dflt:!1,editType:\"calc\"},surfacecolor:{valType:\"data_array\"}},i(\"\",{colorAttr:\"z or surfacecolor\",showScaleDflt:!0,autoColorDflt:!1,editTypeOverride:\"calc\"}),{contours:{x:u(),y:u(),z:u()},hidesurface:{valType:\"boolean\",dflt:!1},lightposition:{x:{valType:\"number\",min:-1e5,max:1e5,dflt:10},y:{valType:\"number\",min:-1e5,max:1e5,dflt:1e4},z:{valType:\"number\",min:-1e5,max:1e5,dflt:0}},lighting:{ambient:{valType:\"number\",min:0,max:1,dflt:.8},diffuse:{valType:\"number\",min:0,max:1,dflt:.8},specular:{valType:\"number\",min:0,max:2,dflt:.05},roughness:{valType:\"number\",min:0,max:1,dflt:.5},fresnel:{valType:\"number\",min:0,max:5,dflt:.2}},opacity:{valType:\"number\",min:0,max:1,dflt:1},opacityscale:{valType:\"any\",editType:\"calc\"},_deprecated:{zauto:l({},i.zauto,{}),zmin:l({},i.zmin,{}),zmax:l({},i.zmax,{})},hoverinfo:l({},s.hoverinfo),showlegend:l({},s.showlegend,{dflt:!1})}),\"calc\",\"nested\");f.x.editType=f.y.editType=f.z.editType=\"calc+clearAxisTypes\",f.transforms=void 0},{\"../../components/color\":366,\"../../components/colorscale/attributes\":373,\"../../lib/extend\":493,\"../../plot_api/edit_types\":536,\"../../plots/attributes\":550,\"../../plots/cartesian/axis_format_attributes\":557,\"../../plots/template_attributes\":633}],1062:[function(t,e,r){\"use strict\";var n=t(\"../../components/colorscale/calc\");e.exports=function(t,e){e.surfacecolor?n(t,e,{vals:e.surfacecolor,containerStr:\"\",cLetter:\"c\"}):n(t,e,{vals:e.z,containerStr:\"\",cLetter:\"c\"})}},{\"../../components/colorscale/calc\":374}],1063:[function(t,e,r){\"use strict\";var n=t(\"../../../stackgl_modules\").gl_surface3d,i=t(\"../../../stackgl_modules\").ndarray,a=t(\"../../../stackgl_modules\").ndarray_linear_interpolate.d2,o=t(\"../heatmap/interp2d\"),s=t(\"../heatmap/find_empties\"),l=t(\"../../lib\").isArrayOrTypedArray,c=t(\"../../lib/gl_format_color\").parseColorScale,u=t(\"../../lib/str2rgbarray\"),f=t(\"../../components/colorscale\").extractOpts;function h(t,e,r){this.scene=t,this.uid=r,this.surface=e,this.data=null,this.showContour=[!1,!1,!1],this.contourStart=[null,null,null],this.contourEnd=[null,null,null],this.contourSize=[0,0,0],this.minValues=[1/0,1/0,1/0],this.maxValues=[-1/0,-1/0,-1/0],this.dataScaleX=1,this.dataScaleY=1,this.refineData=!0,this.objectOffset=[0,0,0]}var p=h.prototype;p.getXat=function(t,e,r,n){var i=l(this.data.x)?l(this.data.x[0])?this.data.x[e][t]:this.data.x[t]:t;return void 0===r?i:n.d2l(i,0,r)},p.getYat=function(t,e,r,n){var i=l(this.data.y)?l(this.data.y[0])?this.data.y[e][t]:this.data.y[e]:e;return void 0===r?i:n.d2l(i,0,r)},p.getZat=function(t,e,r,n){var i=this.data.z[e][t];return null===i&&this.data.connectgaps&&this.data._interpolatedZ&&(i=this.data._interpolatedZ[e][t]),void 0===r?i:n.d2l(i,0,r)},p.handlePick=function(t){if(t.object===this.surface){var e=(t.data.index[0]-1)/this.dataScaleX-1,r=(t.data.index[1]-1)/this.dataScaleY-1,n=Math.max(Math.min(Math.round(e),this.data.z[0].length-1),0),i=Math.max(Math.min(Math.round(r),this.data._ylength-1),0);t.index=[n,i],t.traceCoordinate=[this.getXat(n,i),this.getYat(n,i),this.getZat(n,i)],t.dataCoordinate=[this.getXat(n,i,this.data.xcalendar,this.scene.fullSceneLayout.xaxis),this.getYat(n,i,this.data.ycalendar,this.scene.fullSceneLayout.yaxis),this.getZat(n,i,this.data.zcalendar,this.scene.fullSceneLayout.zaxis)];for(var a=0;a<3;a++){var o=t.dataCoordinate[a];null!=o&&(t.dataCoordinate[a]*=this.scene.dataScale[a])}var s=this.data.hovertext||this.data.text;return Array.isArray(s)&&s[i]&&void 0!==s[i][n]?t.textLabel=s[i][n]:t.textLabel=s||\"\",t.data.dataCoordinate=t.dataCoordinate.slice(),this.surface.highlight(t.data),this.scene.glplot.spikes.position=t.dataCoordinate,!0}};var d=[2,3,5,7,11,13,17,19,23,29,31,37,41,43,47,53,59,61,67,71,73,79,83,89,97,101,103,107,109,113,127,131,137,139,149,151,157,163,167,173,179,181,191,193,197,199,211,223,227,229,233,239,241,251,257,263,269,271,277,281,283,293,307,311,313,317,331,337,347,349,353,359,367,373,379,383,389,397,401,409,419,421,431,433,439,443,449,457,461,463,467,479,487,491,499,503,509,521,523,541,547,557,563,569,571,577,587,593,599,601,607,613,617,619,631,641,643,647,653,659,661,673,677,683,691,701,709,719,727,733,739,743,751,757,761,769,773,787,797,809,811,821,823,827,829,839,853,857,859,863,877,881,883,887,907,911,919,929,937,941,947,953,967,971,977,983,991,997,1009,1013,1019,1021,1031,1033,1039,1049,1051,1061,1063,1069,1087,1091,1093,1097,1103,1109,1117,1123,1129,1151,1153,1163,1171,1181,1187,1193,1201,1213,1217,1223,1229,1231,1237,1249,1259,1277,1279,1283,1289,1291,1297,1301,1303,1307,1319,1321,1327,1361,1367,1373,1381,1399,1409,1423,1427,1429,1433,1439,1447,1451,1453,1459,1471,1481,1483,1487,1489,1493,1499,1511,1523,1531,1543,1549,1553,1559,1567,1571,1579,1583,1597,1601,1607,1609,1613,1619,1621,1627,1637,1657,1663,1667,1669,1693,1697,1699,1709,1721,1723,1733,1741,1747,1753,1759,1777,1783,1787,1789,1801,1811,1823,1831,1847,1861,1867,1871,1873,1877,1879,1889,1901,1907,1913,1931,1933,1949,1951,1973,1979,1987,1993,1997,1999,2003,2011,2017,2027,2029,2039,2053,2063,2069,2081,2083,2087,2089,2099,2111,2113,2129,2131,2137,2141,2143,2153,2161,2179,2203,2207,2213,2221,2237,2239,2243,2251,2267,2269,2273,2281,2287,2293,2297,2309,2311,2333,2339,2341,2347,2351,2357,2371,2377,2381,2383,2389,2393,2399,2411,2417,2423,2437,2441,2447,2459,2467,2473,2477,2503,2521,2531,2539,2543,2549,2551,2557,2579,2591,2593,2609,2617,2621,2633,2647,2657,2659,2663,2671,2677,2683,2687,2689,2693,2699,2707,2711,2713,2719,2729,2731,2741,2749,2753,2767,2777,2789,2791,2797,2801,2803,2819,2833,2837,2843,2851,2857,2861,2879,2887,2897,2903,2909,2917,2927,2939,2953,2957,2963,2969,2971,2999];function m(t,e){if(t<e)return 0;for(var r=0;0===Math.floor(t%e);)t/=e,r++;return r}function g(t){for(var e=[],r=0;r<d.length;r++){var n=d[r];e.push(m(t,n))}return e}function v(t){for(var e=g(t),r=t,n=0;n<d.length;n++)if(e[n]>0){r=d[n];break}return r}function y(t,e){if(!(t<1||e<1)){for(var r=g(t),n=g(e),i=1,a=0;a<d.length;a++)i*=Math.pow(d[a],Math.max(r[a],n[a]));return i}}p.calcXnums=function(t){var e,r=[];for(e=1;e<t;e++){var n=this.getXat(e-1,0),i=this.getXat(e,0);r[e-1]=i!==n&&null!=n&&null!=i?Math.abs(i-n):0}var a=0;for(e=1;e<t;e++)a+=r[e-1];for(e=1;e<t;e++)0===r[e-1]?r[e-1]=1:r[e-1]=Math.round(a/r[e-1]);return r},p.calcYnums=function(t){var e,r=[];for(e=1;e<t;e++){var n=this.getYat(0,e-1),i=this.getYat(0,e);r[e-1]=i!==n&&null!=n&&null!=i?Math.abs(i-n):0}var a=0;for(e=1;e<t;e++)a+=r[e-1];for(e=1;e<t;e++)0===r[e-1]?r[e-1]=1:r[e-1]=Math.round(a/r[e-1]);return r};var x=[1,2,4,6,12,24,36,48,60,120,180,240,360,720,840,1260],b=x[9],_=x[13];function w(t,e,r){var n=r[8]+r[2]*e[0]+r[5]*e[1];return t[0]=(r[6]+r[0]*e[0]+r[3]*e[1])/n,t[1]=(r[7]+r[1]*e[0]+r[4]*e[1])/n,t}function T(t,e,r){return function(t,e,r,n){for(var i=[0,0],o=t.shape[0],s=t.shape[1],l=0;l<o;l++)for(var c=0;c<s;c++)r(i,[l,c],n),t.set(l,c,a(e,i[0],i[1]))}(t,e,w,r),t}function k(t,e){for(var r=!1,n=0;n<t.length;n++)if(e===t[n]){r=!0;break}!1===r&&t.push(e)}p.estimateScale=function(t,e){for(var r=1+function(t){if(0!==t.length){for(var e=1,r=0;r<t.length;r++)e=y(e,t[r]);return e}}(0===e?this.calcXnums(t):this.calcYnums(t));r<b;)r*=2;for(;r>_;)r--,r/=v(r),++r<b&&(r=_);var n=Math.round(r/t);return n>1?n:1},p.refineCoords=function(t){for(var e=this.dataScaleX,r=this.dataScaleY,n=t[0].shape[0],a=t[0].shape[1],o=0|Math.floor(t[0].shape[0]*e+1),s=0|Math.floor(t[0].shape[1]*r+1),l=1+n+1,c=1+a+1,u=i(new Float32Array(l*c),[l,c]),f=[1/e,0,0,0,1/r,0,0,0,1],h=0;h<t.length;++h){this.surface.padField(u,t[h]);var p=i(new Float32Array(o*s),[o,s]);T(p,u,f),t[h]=p}},p.setContourLevels=function(){var t,e,r,n=[[],[],[]],i=[!1,!1,!1],a=!1;for(t=0;t<3;++t)if(this.showContour[t]&&(a=!0,this.contourSize[t]>0&&null!==this.contourStart[t]&&null!==this.contourEnd[t]&&this.contourEnd[t]>this.contourStart[t]))for(i[t]=!0,e=this.contourStart[t];e<this.contourEnd[t];e+=this.contourSize[t])r=e*this.scene.dataScale[t],k(n[t],r);if(a){var o=[[],[],[]];for(t=0;t<3;++t)this.showContour[t]&&(o[t]=i[t]?n[t]:this.scene.contourLevels[t]);this.surface.update({levels:o})}},p.update=function(t){var e,r,n,a,l=this.scene,h=l.fullSceneLayout,p=this.surface,d=c(t),m=l.dataScale,g=t.z[0].length,v=t._ylength,y=l.contourLevels;this.data=t;var x=[];for(e=0;e<3;e++)for(x[e]=[],r=0;r<g;r++)x[e][r]=[];for(r=0;r<g;r++)for(n=0;n<v;n++)x[0][r][n]=this.getXat(r,n,t.xcalendar,h.xaxis),x[1][r][n]=this.getYat(r,n,t.ycalendar,h.yaxis),x[2][r][n]=this.getZat(r,n,t.zcalendar,h.zaxis);if(t.connectgaps)for(t._emptypoints=s(x[2]),o(x[2],t._emptypoints),t._interpolatedZ=[],r=0;r<g;r++)for(t._interpolatedZ[r]=[],n=0;n<v;n++)t._interpolatedZ[r][n]=x[2][r][n];for(e=0;e<3;e++)for(r=0;r<g;r++)for(n=0;n<v;n++)null==(a=x[e][r][n])?x[e][r][n]=NaN:a=x[e][r][n]*=m[e];for(e=0;e<3;e++)for(r=0;r<g;r++)for(n=0;n<v;n++)null!=(a=x[e][r][n])&&(this.minValues[e]>a&&(this.minValues[e]=a),this.maxValues[e]<a&&(this.maxValues[e]=a));for(e=0;e<3;e++)this.objectOffset[e]=.5*(this.minValues[e]+this.maxValues[e]);for(e=0;e<3;e++)for(r=0;r<g;r++)for(n=0;n<v;n++)null!=(a=x[e][r][n])&&(x[e][r][n]-=this.objectOffset[e]);var b=[i(new Float32Array(g*v),[g,v]),i(new Float32Array(g*v),[g,v]),i(new Float32Array(g*v),[g,v])];for(e=0;e<3;e++)for(r=0;r<g;r++)for(n=0;n<v;n++)b[e].set(r,n,x[e][r][n]);x=[];var w={colormap:d,levels:[[],[],[]],showContour:[!0,!0,!0],showSurface:!t.hidesurface,contourProject:[[!1,!1,!1],[!1,!1,!1],[!1,!1,!1]],contourWidth:[1,1,1],contourColor:[[1,1,1,1],[1,1,1,1],[1,1,1,1]],contourTint:[1,1,1],dynamicColor:[[1,1,1,1],[1,1,1,1],[1,1,1,1]],dynamicWidth:[1,1,1],dynamicTint:[1,1,1],opacityscale:t.opacityscale,opacity:t.opacity},T=f(t);if(w.intensityBounds=[T.min,T.max],t.surfacecolor){var k=i(new Float32Array(g*v),[g,v]);for(r=0;r<g;r++)for(n=0;n<v;n++)k.set(r,n,t.surfacecolor[n][r]);b.push(k)}else w.intensityBounds[0]*=m[2],w.intensityBounds[1]*=m[2];(_<b[0].shape[0]||_<b[0].shape[1])&&(this.refineData=!1),!0===this.refineData&&(this.dataScaleX=this.estimateScale(b[0].shape[0],0),this.dataScaleY=this.estimateScale(b[0].shape[1],1),1===this.dataScaleX&&1===this.dataScaleY||this.refineCoords(b)),t.surfacecolor&&(w.intensity=b.pop());var A=[!0,!0,!0],M=[\"x\",\"y\",\"z\"];for(e=0;e<3;++e){var S=t.contours[M[e]];A[e]=S.highlight,w.showContour[e]=S.show||S.highlight,w.showContour[e]&&(w.contourProject[e]=[S.project.x,S.project.y,S.project.z],S.show?(this.showContour[e]=!0,w.levels[e]=y[e],p.highlightColor[e]=w.contourColor[e]=u(S.color),S.usecolormap?p.highlightTint[e]=w.contourTint[e]=0:p.highlightTint[e]=w.contourTint[e]=1,w.contourWidth[e]=S.width,this.contourStart[e]=S.start,this.contourEnd[e]=S.end,this.contourSize[e]=S.size):(this.showContour[e]=!1,this.contourStart[e]=null,this.contourEnd[e]=null,this.contourSize[e]=0),S.highlight&&(w.dynamicColor[e]=u(S.highlightcolor),w.dynamicWidth[e]=S.highlightwidth))}(function(t){var e=t[0].rgb,r=t[t.length-1].rgb;return e[0]===r[0]&&e[1]===r[1]&&e[2]===r[2]&&e[3]===r[3]})(d)&&(w.vertexColor=!0),w.objectOffset=this.objectOffset,w.coords=b,p.update(w),p.visible=t.visible,p.enableDynamic=A,p.enableHighlight=A,p.snapToData=!0,\"lighting\"in t&&(p.ambientLight=t.lighting.ambient,p.diffuseLight=t.lighting.diffuse,p.specularLight=t.lighting.specular,p.roughness=t.lighting.roughness,p.fresnel=t.lighting.fresnel),\"lightposition\"in t&&(p.lightPosition=[t.lightposition.x,t.lightposition.y,t.lightposition.z])},p.dispose=function(){this.scene.glplot.remove(this.surface),this.surface.dispose()},e.exports=function(t,e){var r=t.glplot.gl,i=n({gl:r}),a=new h(t,i,e.uid);return i._trace=a,a.update(e),t.glplot.add(i),a}},{\"../../../stackgl_modules\":1124,\"../../components/colorscale\":378,\"../../lib\":503,\"../../lib/gl_format_color\":499,\"../../lib/str2rgbarray\":528,\"../heatmap/find_empties\":798,\"../heatmap/interp2d\":801}],1064:[function(t,e,r){\"use strict\";var n=t(\"../../registry\"),i=t(\"../../lib\"),a=t(\"../../components/colorscale/defaults\"),o=t(\"./attributes\");function s(t,e,r,n){var 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this._expand(r+1),this.words[r]=e?this.words[r]|1<<i:this.words[r]&~(1<<i),this.strip()},a.prototype.iadd=function(t){var e,r,n;if(0!==this.negative&&0===t.negative)return this.negative=0,e=this.isub(t),this.negative^=1,this._normSign();if(0===this.negative&&0!==t.negative)return t.negative=0,e=this.isub(t),t.negative=1,e._normSign();this.length>t.length?(r=this,n=t):(r=t,n=this);for(var i=0,a=0;a<n.length;a++)e=(0|r.words[a])+(0|n.words[a])+i,this.words[a]=67108863&e,i=e>>>26;for(;0!==i&&a<r.length;a++)e=(0|r.words[a])+i,this.words[a]=67108863&e,i=e>>>26;if(this.length=r.length,0!==i)this.words[this.length]=i,this.length++;else if(r!==this)for(;a<r.length;a++)this.words[a]=r.words[a];return this},a.prototype.add=function(t){var e;return 0!==t.negative&&0===this.negative?(t.negative=0,e=this.sub(t),t.negative^=1,e):0===t.negative&&0!==this.negative?(this.negative=0,e=t.sub(this),this.negative=1,e):this.length>t.length?this.clone().iadd(t):t.clone().iadd(this)},a.prototype.isub=function(t){if(0!==t.negative){t.negative=0;var e=this.iadd(t);return t.negative=1,e._normSign()}if(0!==this.negative)return this.negative=0,this.iadd(t),this.negative=1,this._normSign();var r,n,i=this.cmp(t);if(0===i)return this.negative=0,this.length=1,this.words[0]=0,this;i>0?(r=this,n=t):(r=t,n=this);for(var a=0,o=0;o<n.length;o++)a=(e=(0|r.words[o])-(0|n.words[o])+a)>>26,this.words[o]=67108863&e;for(;0!==a&&o<r.length;o++)a=(e=(0|r.words[o])+a)>>26,this.words[o]=67108863&e;if(0===a&&o<r.length&&r!==this)for(;o<r.length;o++)this.words[o]=r.words[o];return this.length=Math.max(this.length,o),r!==this&&(this.negative=1),this.strip()},a.prototype.sub=function(t){return this.clone().isub(t)};var d=function(t,e,r){var n,i,a,o=t.words,s=e.words,l=r.words,c=0,u=0|o[0],f=8191&u,h=u>>>13,p=0|o[1],d=8191&p,m=p>>>13,g=0|o[2],v=8191&g,y=g>>>13,x=0|o[3],b=8191&x,_=x>>>13,w=0|o[4],T=8191&w,k=w>>>13,A=0|o[5],M=8191&A,S=A>>>13,E=0|o[6],L=8191&E,C=E>>>13,P=0|o[7],I=8191&P,O=P>>>13,z=0|o[8],D=8191&z,R=z>>>13,F=0|o[9],B=8191&F,N=F>>>13,j=0|s[0],U=8191&j,V=j>>>13,H=0|s[1],q=8191&H,G=H>>>13,Y=0|s[2],W=8191&Y,X=Y>>>13,Z=0|s[3],J=8191&Z,K=Z>>>13,Q=0|s[4],$=8191&Q,tt=Q>>>13,et=0|s[5],rt=8191&et,nt=et>>>13,it=0|s[6],at=8191&it,ot=it>>>13,st=0|s[7],lt=8191&st,ct=st>>>13,ut=0|s[8],ft=8191&ut,ht=ut>>>13,pt=0|s[9],dt=8191&pt,mt=pt>>>13;r.negative=t.negative^e.negative,r.length=19;var gt=(c+(n=Math.imul(f,U))|0)+((8191&(i=(i=Math.imul(f,V))+Math.imul(h,U)|0))<<13)|0;c=((a=Math.imul(h,V))+(i>>>13)|0)+(gt>>>26)|0,gt&=67108863,n=Math.imul(d,U),i=(i=Math.imul(d,V))+Math.imul(m,U)|0,a=Math.imul(m,V);var vt=(c+(n=n+Math.imul(f,q)|0)|0)+((8191&(i=(i=i+Math.imul(f,G)|0)+Math.imul(h,q)|0))<<13)|0;c=((a=a+Math.imul(h,G)|0)+(i>>>13)|0)+(vt>>>26)|0,vt&=67108863,n=Math.imul(v,U),i=(i=Math.imul(v,V))+Math.imul(y,U)|0,a=Math.imul(y,V),n=n+Math.imul(d,q)|0,i=(i=i+Math.imul(d,G)|0)+Math.imul(m,q)|0,a=a+Math.imul(m,G)|0;var yt=(c+(n=n+Math.imul(f,W)|0)|0)+((8191&(i=(i=i+Math.imul(f,X)|0)+Math.imul(h,W)|0))<<13)|0;c=((a=a+Math.imul(h,X)|0)+(i>>>13)|0)+(yt>>>26)|0,yt&=67108863,n=Math.imul(b,U),i=(i=Math.imul(b,V))+Math.imul(_,U)|0,a=Math.imul(_,V),n=n+Math.imul(v,q)|0,i=(i=i+Math.imul(v,G)|0)+Math.imul(y,q)|0,a=a+Math.imul(y,G)|0,n=n+Math.imul(d,W)|0,i=(i=i+Math.imul(d,X)|0)+Math.imul(m,W)|0,a=a+Math.imul(m,X)|0;var xt=(c+(n=n+Math.imul(f,J)|0)|0)+((8191&(i=(i=i+Math.imul(f,K)|0)+Math.imul(h,J)|0))<<13)|0;c=((a=a+Math.imul(h,K)|0)+(i>>>13)|0)+(xt>>>26)|0,xt&=67108863,n=Math.imul(T,U),i=(i=Math.imul(T,V))+Math.imul(k,U)|0,a=Math.imul(k,V),n=n+Math.imul(b,q)|0,i=(i=i+Math.imul(b,G)|0)+Math.imul(_,q)|0,a=a+Math.imul(_,G)|0,n=n+Math.imul(v,W)|0,i=(i=i+Math.imul(v,X)|0)+Math.imul(y,W)|0,a=a+Math.imul(y,X)|0,n=n+Math.imul(d,J)|0,i=(i=i+Math.imul(d,K)|0)+Math.imul(m,J)|0,a=a+Math.imul(m,K)|0;var bt=(c+(n=n+Math.imul(f,$)|0)|0)+((8191&(i=(i=i+Math.imul(f,tt)|0)+Math.imul(h,$)|0))<<13)|0;c=((a=a+Math.imul(h,tt)|0)+(i>>>13)|0)+(bt>>>26)|0,bt&=67108863,n=Math.imul(M,U),i=(i=Math.imul(M,V))+Math.imul(S,U)|0,a=Math.imul(S,V),n=n+Math.imul(T,q)|0,i=(i=i+Math.imul(T,G)|0)+Math.imul(k,q)|0,a=a+Math.imul(k,G)|0,n=n+Math.imul(b,W)|0,i=(i=i+Math.imul(b,X)|0)+Math.imul(_,W)|0,a=a+Math.imul(_,X)|0,n=n+Math.imul(v,J)|0,i=(i=i+Math.imul(v,K)|0)+Math.imul(y,J)|0,a=a+Math.imul(y,K)|0,n=n+Math.imul(d,$)|0,i=(i=i+Math.imul(d,tt)|0)+Math.imul(m,$)|0,a=a+Math.imul(m,tt)|0;var _t=(c+(n=n+Math.imul(f,rt)|0)|0)+((8191&(i=(i=i+Math.imul(f,nt)|0)+Math.imul(h,rt)|0))<<13)|0;c=((a=a+Math.imul(h,nt)|0)+(i>>>13)|0)+(_t>>>26)|0,_t&=67108863,n=Math.imul(L,U),i=(i=Math.imul(L,V))+Math.imul(C,U)|0,a=Math.imul(C,V),n=n+Math.imul(M,q)|0,i=(i=i+Math.imul(M,G)|0)+Math.imul(S,q)|0,a=a+Math.imul(S,G)|0,n=n+Math.imul(T,W)|0,i=(i=i+Math.imul(T,X)|0)+Math.imul(k,W)|0,a=a+Math.imul(k,X)|0,n=n+Math.imul(b,J)|0,i=(i=i+Math.imul(b,K)|0)+Math.imul(_,J)|0,a=a+Math.imul(_,K)|0,n=n+Math.imul(v,$)|0,i=(i=i+Math.imul(v,tt)|0)+Math.imul(y,$)|0,a=a+Math.imul(y,tt)|0,n=n+Math.imul(d,rt)|0,i=(i=i+Math.imul(d,nt)|0)+Math.imul(m,rt)|0,a=a+Math.imul(m,nt)|0;var wt=(c+(n=n+Math.imul(f,at)|0)|0)+((8191&(i=(i=i+Math.imul(f,ot)|0)+Math.imul(h,at)|0))<<13)|0;c=((a=a+Math.imul(h,ot)|0)+(i>>>13)|0)+(wt>>>26)|0,wt&=67108863,n=Math.imul(I,U),i=(i=Math.imul(I,V))+Math.imul(O,U)|0,a=Math.imul(O,V),n=n+Math.imul(L,q)|0,i=(i=i+Math.imul(L,G)|0)+Math.imul(C,q)|0,a=a+Math.imul(C,G)|0,n=n+Math.imul(M,W)|0,i=(i=i+Math.imul(M,X)|0)+Math.imul(S,W)|0,a=a+Math.imul(S,X)|0,n=n+Math.imul(T,J)|0,i=(i=i+Math.imul(T,K)|0)+Math.imul(k,J)|0,a=a+Math.imul(k,K)|0,n=n+Math.imul(b,$)|0,i=(i=i+Math.imul(b,tt)|0)+Math.imul(_,$)|0,a=a+Math.imul(_,tt)|0,n=n+Math.imul(v,rt)|0,i=(i=i+Math.imul(v,nt)|0)+Math.imul(y,rt)|0,a=a+Math.imul(y,nt)|0,n=n+Math.imul(d,at)|0,i=(i=i+Math.imul(d,ot)|0)+Math.imul(m,at)|0,a=a+Math.imul(m,ot)|0;var Tt=(c+(n=n+Math.imul(f,lt)|0)|0)+((8191&(i=(i=i+Math.imul(f,ct)|0)+Math.imul(h,lt)|0))<<13)|0;c=((a=a+Math.imul(h,ct)|0)+(i>>>13)|0)+(Tt>>>26)|0,Tt&=67108863,n=Math.imul(D,U),i=(i=Math.imul(D,V))+Math.imul(R,U)|0,a=Math.imul(R,V),n=n+Math.imul(I,q)|0,i=(i=i+Math.imul(I,G)|0)+Math.imul(O,q)|0,a=a+Math.imul(O,G)|0,n=n+Math.imul(L,W)|0,i=(i=i+Math.imul(L,X)|0)+Math.imul(C,W)|0,a=a+Math.imul(C,X)|0,n=n+Math.imul(M,J)|0,i=(i=i+Math.imul(M,K)|0)+Math.imul(S,J)|0,a=a+Math.imul(S,K)|0,n=n+Math.imul(T,$)|0,i=(i=i+Math.imul(T,tt)|0)+Math.imul(k,$)|0,a=a+Math.imul(k,tt)|0,n=n+Math.imul(b,rt)|0,i=(i=i+Math.imul(b,nt)|0)+Math.imul(_,rt)|0,a=a+Math.imul(_,nt)|0,n=n+Math.imul(v,at)|0,i=(i=i+Math.imul(v,ot)|0)+Math.imul(y,at)|0,a=a+Math.imul(y,ot)|0,n=n+Math.imul(d,lt)|0,i=(i=i+Math.imul(d,ct)|0)+Math.imul(m,lt)|0,a=a+Math.imul(m,ct)|0;var kt=(c+(n=n+Math.imul(f,ft)|0)|0)+((8191&(i=(i=i+Math.imul(f,ht)|0)+Math.imul(h,ft)|0))<<13)|0;c=((a=a+Math.imul(h,ht)|0)+(i>>>13)|0)+(kt>>>26)|0,kt&=67108863,n=Math.imul(B,U),i=(i=Math.imul(B,V))+Math.imul(N,U)|0,a=Math.imul(N,V),n=n+Math.imul(D,q)|0,i=(i=i+Math.imul(D,G)|0)+Math.imul(R,q)|0,a=a+Math.imul(R,G)|0,n=n+Math.imul(I,W)|0,i=(i=i+Math.imul(I,X)|0)+Math.imul(O,W)|0,a=a+Math.imul(O,X)|0,n=n+Math.imul(L,J)|0,i=(i=i+Math.imul(L,K)|0)+Math.imul(C,J)|0,a=a+Math.imul(C,K)|0,n=n+Math.imul(M,$)|0,i=(i=i+Math.imul(M,tt)|0)+Math.imul(S,$)|0,a=a+Math.imul(S,tt)|0,n=n+Math.imul(T,rt)|0,i=(i=i+Math.imul(T,nt)|0)+Math.imul(k,rt)|0,a=a+Math.imul(k,nt)|0,n=n+Math.imul(b,at)|0,i=(i=i+Math.imul(b,ot)|0)+Math.imul(_,at)|0,a=a+Math.imul(_,ot)|0,n=n+Math.imul(v,lt)|0,i=(i=i+Math.imul(v,ct)|0)+Math.imul(y,lt)|0,a=a+Math.imul(y,ct)|0,n=n+Math.imul(d,ft)|0,i=(i=i+Math.imul(d,ht)|0)+Math.imul(m,ft)|0,a=a+Math.imul(m,ht)|0;var At=(c+(n=n+Math.imul(f,dt)|0)|0)+((8191&(i=(i=i+Math.imul(f,mt)|0)+Math.imul(h,dt)|0))<<13)|0;c=((a=a+Math.imul(h,mt)|0)+(i>>>13)|0)+(At>>>26)|0,At&=67108863,n=Math.imul(B,q),i=(i=Math.imul(B,G))+Math.imul(N,q)|0,a=Math.imul(N,G),n=n+Math.imul(D,W)|0,i=(i=i+Math.imul(D,X)|0)+Math.imul(R,W)|0,a=a+Math.imul(R,X)|0,n=n+Math.imul(I,J)|0,i=(i=i+Math.imul(I,K)|0)+Math.imul(O,J)|0,a=a+Math.imul(O,K)|0,n=n+Math.imul(L,$)|0,i=(i=i+Math.imul(L,tt)|0)+Math.imul(C,$)|0,a=a+Math.imul(C,tt)|0,n=n+Math.imul(M,rt)|0,i=(i=i+Math.imul(M,nt)|0)+Math.imul(S,rt)|0,a=a+Math.imul(S,nt)|0,n=n+Math.imul(T,at)|0,i=(i=i+Math.imul(T,ot)|0)+Math.imul(k,at)|0,a=a+Math.imul(k,ot)|0,n=n+Math.imul(b,lt)|0,i=(i=i+Math.imul(b,ct)|0)+Math.imul(_,lt)|0,a=a+Math.imul(_,ct)|0,n=n+Math.imul(v,ft)|0,i=(i=i+Math.imul(v,ht)|0)+Math.imul(y,ft)|0,a=a+Math.imul(y,ht)|0;var Mt=(c+(n=n+Math.imul(d,dt)|0)|0)+((8191&(i=(i=i+Math.imul(d,mt)|0)+Math.imul(m,dt)|0))<<13)|0;c=((a=a+Math.imul(m,mt)|0)+(i>>>13)|0)+(Mt>>>26)|0,Mt&=67108863,n=Math.imul(B,W),i=(i=Math.imul(B,X))+Math.imul(N,W)|0,a=Math.imul(N,X),n=n+Math.imul(D,J)|0,i=(i=i+Math.imul(D,K)|0)+Math.imul(R,J)|0,a=a+Math.imul(R,K)|0,n=n+Math.imul(I,$)|0,i=(i=i+Math.imul(I,tt)|0)+Math.imul(O,$)|0,a=a+Math.imul(O,tt)|0,n=n+Math.imul(L,rt)|0,i=(i=i+Math.imul(L,nt)|0)+Math.imul(C,rt)|0,a=a+Math.imul(C,nt)|0,n=n+Math.imul(M,at)|0,i=(i=i+Math.imul(M,ot)|0)+Math.imul(S,at)|0,a=a+Math.imul(S,ot)|0,n=n+Math.imul(T,lt)|0,i=(i=i+Math.imul(T,ct)|0)+Math.imul(k,lt)|0,a=a+Math.imul(k,ct)|0,n=n+Math.imul(b,ft)|0,i=(i=i+Math.imul(b,ht)|0)+Math.imul(_,ft)|0,a=a+Math.imul(_,ht)|0;var St=(c+(n=n+Math.imul(v,dt)|0)|0)+((8191&(i=(i=i+Math.imul(v,mt)|0)+Math.imul(y,dt)|0))<<13)|0;c=((a=a+Math.imul(y,mt)|0)+(i>>>13)|0)+(St>>>26)|0,St&=67108863,n=Math.imul(B,J),i=(i=Math.imul(B,K))+Math.imul(N,J)|0,a=Math.imul(N,K),n=n+Math.imul(D,$)|0,i=(i=i+Math.imul(D,tt)|0)+Math.imul(R,$)|0,a=a+Math.imul(R,tt)|0,n=n+Math.imul(I,rt)|0,i=(i=i+Math.imul(I,nt)|0)+Math.imul(O,rt)|0,a=a+Math.imul(O,nt)|0,n=n+Math.imul(L,at)|0,i=(i=i+Math.imul(L,ot)|0)+Math.imul(C,at)|0,a=a+Math.imul(C,ot)|0,n=n+Math.imul(M,lt)|0,i=(i=i+Math.imul(M,ct)|0)+Math.imul(S,lt)|0,a=a+Math.imul(S,ct)|0,n=n+Math.imul(T,ft)|0,i=(i=i+Math.imul(T,ht)|0)+Math.imul(k,ft)|0,a=a+Math.imul(k,ht)|0;var Et=(c+(n=n+Math.imul(b,dt)|0)|0)+((8191&(i=(i=i+Math.imul(b,mt)|0)+Math.imul(_,dt)|0))<<13)|0;c=((a=a+Math.imul(_,mt)|0)+(i>>>13)|0)+(Et>>>26)|0,Et&=67108863,n=Math.imul(B,$),i=(i=Math.imul(B,tt))+Math.imul(N,$)|0,a=Math.imul(N,tt),n=n+Math.imul(D,rt)|0,i=(i=i+Math.imul(D,nt)|0)+Math.imul(R,rt)|0,a=a+Math.imul(R,nt)|0,n=n+Math.imul(I,at)|0,i=(i=i+Math.imul(I,ot)|0)+Math.imul(O,at)|0,a=a+Math.imul(O,ot)|0,n=n+Math.imul(L,lt)|0,i=(i=i+Math.imul(L,ct)|0)+Math.imul(C,lt)|0,a=a+Math.imul(C,ct)|0,n=n+Math.imul(M,ft)|0,i=(i=i+Math.imul(M,ht)|0)+Math.imul(S,ft)|0,a=a+Math.imul(S,ht)|0;var Lt=(c+(n=n+Math.imul(T,dt)|0)|0)+((8191&(i=(i=i+Math.imul(T,mt)|0)+Math.imul(k,dt)|0))<<13)|0;c=((a=a+Math.imul(k,mt)|0)+(i>>>13)|0)+(Lt>>>26)|0,Lt&=67108863,n=Math.imul(B,rt),i=(i=Math.imul(B,nt))+Math.imul(N,rt)|0,a=Math.imul(N,nt),n=n+Math.imul(D,at)|0,i=(i=i+Math.imul(D,ot)|0)+Math.imul(R,at)|0,a=a+Math.imul(R,ot)|0,n=n+Math.imul(I,lt)|0,i=(i=i+Math.imul(I,ct)|0)+Math.imul(O,lt)|0,a=a+Math.imul(O,ct)|0,n=n+Math.imul(L,ft)|0,i=(i=i+Math.imul(L,ht)|0)+Math.imul(C,ft)|0,a=a+Math.imul(C,ht)|0;var Ct=(c+(n=n+Math.imul(M,dt)|0)|0)+((8191&(i=(i=i+Math.imul(M,mt)|0)+Math.imul(S,dt)|0))<<13)|0;c=((a=a+Math.imul(S,mt)|0)+(i>>>13)|0)+(Ct>>>26)|0,Ct&=67108863,n=Math.imul(B,at),i=(i=Math.imul(B,ot))+Math.imul(N,at)|0,a=Math.imul(N,ot),n=n+Math.imul(D,lt)|0,i=(i=i+Math.imul(D,ct)|0)+Math.imul(R,lt)|0,a=a+Math.imul(R,ct)|0,n=n+Math.imul(I,ft)|0,i=(i=i+Math.imul(I,ht)|0)+Math.imul(O,ft)|0,a=a+Math.imul(O,ht)|0;var Pt=(c+(n=n+Math.imul(L,dt)|0)|0)+((8191&(i=(i=i+Math.imul(L,mt)|0)+Math.imul(C,dt)|0))<<13)|0;c=((a=a+Math.imul(C,mt)|0)+(i>>>13)|0)+(Pt>>>26)|0,Pt&=67108863,n=Math.imul(B,lt),i=(i=Math.imul(B,ct))+Math.imul(N,lt)|0,a=Math.imul(N,ct),n=n+Math.imul(D,ft)|0,i=(i=i+Math.imul(D,ht)|0)+Math.imul(R,ft)|0,a=a+Math.imul(R,ht)|0;var It=(c+(n=n+Math.imul(I,dt)|0)|0)+((8191&(i=(i=i+Math.imul(I,mt)|0)+Math.imul(O,dt)|0))<<13)|0;c=((a=a+Math.imul(O,mt)|0)+(i>>>13)|0)+(It>>>26)|0,It&=67108863,n=Math.imul(B,ft),i=(i=Math.imul(B,ht))+Math.imul(N,ft)|0,a=Math.imul(N,ht);var Ot=(c+(n=n+Math.imul(D,dt)|0)|0)+((8191&(i=(i=i+Math.imul(D,mt)|0)+Math.imul(R,dt)|0))<<13)|0;c=((a=a+Math.imul(R,mt)|0)+(i>>>13)|0)+(Ot>>>26)|0,Ot&=67108863;var zt=(c+(n=Math.imul(B,dt))|0)+((8191&(i=(i=Math.imul(B,mt))+Math.imul(N,dt)|0))<<13)|0;return c=((a=Math.imul(N,mt))+(i>>>13)|0)+(zt>>>26)|0,zt&=67108863,l[0]=gt,l[1]=vt,l[2]=yt,l[3]=xt,l[4]=bt,l[5]=_t,l[6]=wt,l[7]=Tt,l[8]=kt,l[9]=At,l[10]=Mt,l[11]=St,l[12]=Et,l[13]=Lt,l[14]=Ct,l[15]=Pt,l[16]=It,l[17]=Ot,l[18]=zt,0!==c&&(l[19]=c,r.length++),r};function m(t,e,r){return(new g).mulp(t,e,r)}function g(t,e){this.x=t,this.y=e}Math.imul||(d=p),a.prototype.mulTo=function(t,e){var r=this.length+t.length;return 10===this.length&&10===t.length?d(this,t,e):r<63?p(this,t,e):r<1024?function(t,e,r){r.negative=e.negative^t.negative,r.length=t.length+e.length;for(var n=0,i=0,a=0;a<r.length-1;a++){var o=i;i=0;for(var s=67108863&n,l=Math.min(a,e.length-1),c=Math.max(0,a-t.length+1);c<=l;c++){var u=a-c,f=(0|t.words[u])*(0|e.words[c]),h=67108863&f;s=67108863&(h=h+s|0),i+=(o=(o=o+(f/67108864|0)|0)+(h>>>26)|0)>>>26,o&=67108863}r.words[a]=s,n=o,o=i}return 0!==n?r.words[a]=n:r.length--,r.strip()}(this,t,e):m(this,t,e)},g.prototype.makeRBT=function(t){for(var e=new Array(t),r=a.prototype._countBits(t)-1,n=0;n<t;n++)e[n]=this.revBin(n,r,t);return e},g.prototype.revBin=function(t,e,r){if(0===t||t===r-1)return t;for(var n=0,i=0;i<e;i++)n|=(1&t)<<e-i-1,t>>=1;return n},g.prototype.permute=function(t,e,r,n,i,a){for(var o=0;o<a;o++)n[o]=e[t[o]],i[o]=r[t[o]]},g.prototype.transform=function(t,e,r,n,i,a){this.permute(a,t,e,r,n,i);for(var o=1;o<i;o<<=1)for(var s=o<<1,l=Math.cos(2*Math.PI/s),c=Math.sin(2*Math.PI/s),u=0;u<i;u+=s)for(var f=l,h=c,p=0;p<o;p++){var d=r[u+p],m=n[u+p],g=r[u+p+o],v=n[u+p+o],y=f*g-h*v;v=f*v+h*g,g=y,r[u+p]=d+g,n[u+p]=m+v,r[u+p+o]=d-g,n[u+p+o]=m-v,p!==s&&(y=l*f-c*h,h=l*h+c*f,f=y)}},g.prototype.guessLen13b=function(t,e){var r=1|Math.max(e,t),n=1&r,i=0;for(r=r/2|0;r;r>>>=1)i++;return 1<<i+1+n},g.prototype.conjugate=function(t,e,r){if(!(r<=1))for(var n=0;n<r/2;n++){var i=t[n];t[n]=t[r-n-1],t[r-n-1]=i,i=e[n],e[n]=-e[r-n-1],e[r-n-1]=-i}},g.prototype.normalize13b=function(t,e){for(var r=0,n=0;n<e/2;n++){var i=8192*Math.round(t[2*n+1]/e)+Math.round(t[2*n]/e)+r;t[n]=67108863&i,r=i<67108864?0:i/67108864|0}return t},g.prototype.convert13b=function(t,e,r,i){for(var a=0,o=0;o<e;o++)a+=0|t[o],r[2*o]=8191&a,a>>>=13,r[2*o+1]=8191&a,a>>>=13;for(o=2*e;o<i;++o)r[o]=0;n(0===a),n(0==(-8192&a))},g.prototype.stub=function(t){for(var e=new Array(t),r=0;r<t;r++)e[r]=0;return e},g.prototype.mulp=function(t,e,r){var n=2*this.guessLen13b(t.length,e.length),i=this.makeRBT(n),a=this.stub(n),o=new Array(n),s=new Array(n),l=new Array(n),c=new Array(n),u=new Array(n),f=new Array(n),h=r.words;h.length=n,this.convert13b(t.words,t.length,o,n),this.convert13b(e.words,e.length,c,n),this.transform(o,a,s,l,n,i),this.transform(c,a,u,f,n,i);for(var p=0;p<n;p++){var d=s[p]*u[p]-l[p]*f[p];l[p]=s[p]*f[p]+l[p]*u[p],s[p]=d}return this.conjugate(s,l,n),this.transform(s,l,h,a,n,i),this.conjugate(h,a,n),this.normalize13b(h,n),r.negative=t.negative^e.negative,r.length=t.length+e.length,r.strip()},a.prototype.mul=function(t){var e=new a(null);return e.words=new Array(this.length+t.length),this.mulTo(t,e)},a.prototype.mulf=function(t){var e=new a(null);return e.words=new Array(this.length+t.length),m(this,t,e)},a.prototype.imul=function(t){return this.clone().mulTo(t,this)},a.prototype.imuln=function(t){n(\"number\"==typeof t),n(t<67108864);for(var e=0,r=0;r<this.length;r++){var i=(0|this.words[r])*t,a=(67108863&i)+(67108863&e);e>>=26,e+=i/67108864|0,e+=a>>>26,this.words[r]=67108863&a}return 0!==e&&(this.words[r]=e,this.length++),this},a.prototype.muln=function(t){return this.clone().imuln(t)},a.prototype.sqr=function(){return this.mul(this)},a.prototype.isqr=function(){return this.imul(this.clone())},a.prototype.pow=function(t){var e=function(t){for(var e=new Array(t.bitLength()),r=0;r<e.length;r++){var n=r/26|0,i=r%26;e[r]=(t.words[n]&1<<i)>>>i}return e}(t);if(0===e.length)return new a(1);for(var r=this,n=0;n<e.length&&0===e[n];n++,r=r.sqr());if(++n<e.length)for(var i=r.sqr();n<e.length;n++,i=i.sqr())0!==e[n]&&(r=r.mul(i));return r},a.prototype.iushln=function(t){n(\"number\"==typeof t&&t>=0);var e,r=t%26,i=(t-r)/26,a=67108863>>>26-r<<26-r;if(0!==r){var o=0;for(e=0;e<this.length;e++){var s=this.words[e]&a,l=(0|this.words[e])-s<<r;this.words[e]=l|o,o=s>>>26-r}o&&(this.words[e]=o,this.length++)}if(0!==i){for(e=this.length-1;e>=0;e--)this.words[e+i]=this.words[e];for(e=0;e<i;e++)this.words[e]=0;this.length+=i}return this.strip()},a.prototype.ishln=function(t){return n(0===this.negative),this.iushln(t)},a.prototype.iushrn=function(t,e,r){var i;n(\"number\"==typeof t&&t>=0),i=e?(e-e%26)/26:0;var a=t%26,o=Math.min((t-a)/26,this.length),s=67108863^67108863>>>a<<a,l=r;if(i-=o,i=Math.max(0,i),l){for(var c=0;c<o;c++)l.words[c]=this.words[c];l.length=o}if(0===o);else if(this.length>o)for(this.length-=o,c=0;c<this.length;c++)this.words[c]=this.words[c+o];else this.words[0]=0,this.length=1;var u=0;for(c=this.length-1;c>=0&&(0!==u||c>=i);c--){var f=0|this.words[c];this.words[c]=u<<26-a|f>>>a,u=f&s}return l&&0!==u&&(l.words[l.length++]=u),0===this.length&&(this.words[0]=0,this.length=1),this.strip()},a.prototype.ishrn=function(t,e,r){return n(0===this.negative),this.iushrn(t,e,r)},a.prototype.shln=function(t){return this.clone().ishln(t)},a.prototype.ushln=function(t){return this.clone().iushln(t)},a.prototype.shrn=function(t){return this.clone().ishrn(t)},a.prototype.ushrn=function(t){return this.clone().iushrn(t)},a.prototype.testn=function(t){n(\"number\"==typeof t&&t>=0);var e=t%26,r=(t-e)/26,i=1<<e;return!(this.length<=r)&&!!(this.words[r]&i)},a.prototype.imaskn=function(t){n(\"number\"==typeof t&&t>=0);var e=t%26,r=(t-e)/26;if(n(0===this.negative,\"imaskn works only with positive numbers\"),this.length<=r)return this;if(0!==e&&r++,this.length=Math.min(r,this.length),0!==e){var i=67108863^67108863>>>e<<e;this.words[this.length-1]&=i}return this.strip()},a.prototype.maskn=function(t){return this.clone().imaskn(t)},a.prototype.iaddn=function(t){return n(\"number\"==typeof t),n(t<67108864),t<0?this.isubn(-t):0!==this.negative?1===this.length&&(0|this.words[0])<t?(this.words[0]=t-(0|this.words[0]),this.negative=0,this):(this.negative=0,this.isubn(t),this.negative=1,this):this._iaddn(t)},a.prototype._iaddn=function(t){this.words[0]+=t;for(var e=0;e<this.length&&this.words[e]>=67108864;e++)this.words[e]-=67108864,e===this.length-1?this.words[e+1]=1:this.words[e+1]++;return this.length=Math.max(this.length,e+1),this},a.prototype.isubn=function(t){if(n(\"number\"==typeof t),n(t<67108864),t<0)return this.iaddn(-t);if(0!==this.negative)return this.negative=0,this.iaddn(t),this.negative=1,this;if(this.words[0]-=t,1===this.length&&this.words[0]<0)this.words[0]=-this.words[0],this.negative=1;else for(var e=0;e<this.length&&this.words[e]<0;e++)this.words[e]+=67108864,this.words[e+1]-=1;return this.strip()},a.prototype.addn=function(t){return this.clone().iaddn(t)},a.prototype.subn=function(t){return this.clone().isubn(t)},a.prototype.iabs=function(){return this.negative=0,this},a.prototype.abs=function(){return this.clone().iabs()},a.prototype._ishlnsubmul=function(t,e,r){var i,a,o=t.length+r;this._expand(o);var s=0;for(i=0;i<t.length;i++){a=(0|this.words[i+r])+s;var l=(0|t.words[i])*e;s=((a-=67108863&l)>>26)-(l/67108864|0),this.words[i+r]=67108863&a}for(;i<this.length-r;i++)s=(a=(0|this.words[i+r])+s)>>26,this.words[i+r]=67108863&a;if(0===s)return this.strip();for(n(-1===s),s=0,i=0;i<this.length;i++)s=(a=-(0|this.words[i])+s)>>26,this.words[i]=67108863&a;return this.negative=1,this.strip()},a.prototype._wordDiv=function(t,e){var r=(this.length,t.length),n=this.clone(),i=t,o=0|i.words[i.length-1];0!==(r=26-this._countBits(o))&&(i=i.ushln(r),n.iushln(r),o=0|i.words[i.length-1]);var s,l=n.length-i.length;if(\"mod\"!==e){(s=new a(null)).length=l+1,s.words=new Array(s.length);for(var c=0;c<s.length;c++)s.words[c]=0}var u=n.clone()._ishlnsubmul(i,1,l);0===u.negative&&(n=u,s&&(s.words[l]=1));for(var f=l-1;f>=0;f--){var h=67108864*(0|n.words[i.length+f])+(0|n.words[i.length+f-1]);for(h=Math.min(h/o|0,67108863),n._ishlnsubmul(i,h,f);0!==n.negative;)h--,n.negative=0,n._ishlnsubmul(i,1,f),n.isZero()||(n.negative^=1);s&&(s.words[f]=h)}return s&&s.strip(),n.strip(),\"div\"!==e&&0!==r&&n.iushrn(r),{div:s||null,mod:n}},a.prototype.divmod=function(t,e,r){return n(!t.isZero()),this.isZero()?{div:new a(0),mod:new a(0)}:0!==this.negative&&0===t.negative?(s=this.neg().divmod(t,e),\"mod\"!==e&&(i=s.div.neg()),\"div\"!==e&&(o=s.mod.neg(),r&&0!==o.negative&&o.iadd(t)),{div:i,mod:o}):0===this.negative&&0!==t.negative?(s=this.divmod(t.neg(),e),\"mod\"!==e&&(i=s.div.neg()),{div:i,mod:s.mod}):0!=(this.negative&t.negative)?(s=this.neg().divmod(t.neg(),e),\"div\"!==e&&(o=s.mod.neg(),r&&0!==o.negative&&o.isub(t)),{div:s.div,mod:o}):t.length>this.length||this.cmp(t)<0?{div:new a(0),mod:this}:1===t.length?\"div\"===e?{div:this.divn(t.words[0]),mod:null}:\"mod\"===e?{div:null,mod:new a(this.modn(t.words[0]))}:{div:this.divn(t.words[0]),mod:new a(this.modn(t.words[0]))}:this._wordDiv(t,e);var i,o,s},a.prototype.div=function(t){return this.divmod(t,\"div\",!1).div},a.prototype.mod=function(t){return this.divmod(t,\"mod\",!1).mod},a.prototype.umod=function(t){return this.divmod(t,\"mod\",!0).mod},a.prototype.divRound=function(t){var e=this.divmod(t);if(e.mod.isZero())return e.div;var r=0!==e.div.negative?e.mod.isub(t):e.mod,n=t.ushrn(1),i=t.andln(1),a=r.cmp(n);return a<0||1===i&&0===a?e.div:0!==e.div.negative?e.div.isubn(1):e.div.iaddn(1)},a.prototype.modn=function(t){n(t<=67108863);for(var e=(1<<26)%t,r=0,i=this.length-1;i>=0;i--)r=(e*r+(0|this.words[i]))%t;return r},a.prototype.idivn=function(t){n(t<=67108863);for(var e=0,r=this.length-1;r>=0;r--){var i=(0|this.words[r])+67108864*e;this.words[r]=i/t|0,e=i%t}return this.strip()},a.prototype.divn=function(t){return this.clone().idivn(t)},a.prototype.egcd=function(t){n(0===t.negative),n(!t.isZero());var e=this,r=t.clone();e=0!==e.negative?e.umod(t):e.clone();for(var i=new a(1),o=new a(0),s=new a(0),l=new a(1),c=0;e.isEven()&&r.isEven();)e.iushrn(1),r.iushrn(1),++c;for(var u=r.clone(),f=e.clone();!e.isZero();){for(var h=0,p=1;0==(e.words[0]&p)&&h<26;++h,p<<=1);if(h>0)for(e.iushrn(h);h-- >0;)(i.isOdd()||o.isOdd())&&(i.iadd(u),o.isub(f)),i.iushrn(1),o.iushrn(1);for(var d=0,m=1;0==(r.words[0]&m)&&d<26;++d,m<<=1);if(d>0)for(r.iushrn(d);d-- >0;)(s.isOdd()||l.isOdd())&&(s.iadd(u),l.isub(f)),s.iushrn(1),l.iushrn(1);e.cmp(r)>=0?(e.isub(r),i.isub(s),o.isub(l)):(r.isub(e),s.isub(i),l.isub(o))}return{a:s,b:l,gcd:r.iushln(c)}},a.prototype._invmp=function(t){n(0===t.negative),n(!t.isZero());var e=this,r=t.clone();e=0!==e.negative?e.umod(t):e.clone();for(var i,o=new a(1),s=new a(0),l=r.clone();e.cmpn(1)>0&&r.cmpn(1)>0;){for(var c=0,u=1;0==(e.words[0]&u)&&c<26;++c,u<<=1);if(c>0)for(e.iushrn(c);c-- >0;)o.isOdd()&&o.iadd(l),o.iushrn(1);for(var f=0,h=1;0==(r.words[0]&h)&&f<26;++f,h<<=1);if(f>0)for(r.iushrn(f);f-- >0;)s.isOdd()&&s.iadd(l),s.iushrn(1);e.cmp(r)>=0?(e.isub(r),o.isub(s)):(r.isub(e),s.isub(o))}return(i=0===e.cmpn(1)?o:s).cmpn(0)<0&&i.iadd(t),i},a.prototype.gcd=function(t){if(this.isZero())return t.abs();if(t.isZero())return this.abs();var e=this.clone(),r=t.clone();e.negative=0,r.negative=0;for(var n=0;e.isEven()&&r.isEven();n++)e.iushrn(1),r.iushrn(1);for(;;){for(;e.isEven();)e.iushrn(1);for(;r.isEven();)r.iushrn(1);var i=e.cmp(r);if(i<0){var a=e;e=r,r=a}else if(0===i||0===r.cmpn(1))break;e.isub(r)}return r.iushln(n)},a.prototype.invm=function(t){return this.egcd(t).a.umod(t)},a.prototype.isEven=function(){return 0==(1&this.words[0])},a.prototype.isOdd=function(){return 1==(1&this.words[0])},a.prototype.andln=function(t){return this.words[0]&t},a.prototype.bincn=function(t){n(\"number\"==typeof t);var e=t%26,r=(t-e)/26,i=1<<e;if(this.length<=r)return this._expand(r+1),this.words[r]|=i,this;for(var a=i,o=r;0!==a&&o<this.length;o++){var s=0|this.words[o];a=(s+=a)>>>26,s&=67108863,this.words[o]=s}return 0!==a&&(this.words[o]=a,this.length++),this},a.prototype.isZero=function(){return 1===this.length&&0===this.words[0]},a.prototype.cmpn=function(t){var e,r=t<0;if(0!==this.negative&&!r)return-1;if(0===this.negative&&r)return 1;if(this.strip(),this.length>1)e=1;else{r&&(t=-t),n(t<=67108863,\"Number is too big\");var i=0|this.words[0];e=i===t?0:i<t?-1:1}return 0!==this.negative?0|-e:e},a.prototype.cmp=function(t){if(0!==this.negative&&0===t.negative)return-1;if(0===this.negative&&0!==t.negative)return 1;var e=this.ucmp(t);return 0!==this.negative?0|-e:e},a.prototype.ucmp=function(t){if(this.length>t.length)return 1;if(this.length<t.length)return-1;for(var e=0,r=this.length-1;r>=0;r--){var n=0|this.words[r],i=0|t.words[r];if(n!==i){n<i?e=-1:n>i&&(e=1);break}}return 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numbers\"),this.red._verify1(this),this.red.sqr(this)},a.prototype.redISqr=function(){return n(this.red,\"redISqr works only with red numbers\"),this.red._verify1(this),this.red.isqr(this)},a.prototype.redSqrt=function(){return n(this.red,\"redSqrt works only with red numbers\"),this.red._verify1(this),this.red.sqrt(this)},a.prototype.redInvm=function(){return n(this.red,\"redInvm works only with red numbers\"),this.red._verify1(this),this.red.invm(this)},a.prototype.redNeg=function(){return n(this.red,\"redNeg works only with red numbers\"),this.red._verify1(this),this.red.neg(this)},a.prototype.redPow=function(t){return n(this.red&&!t.red,\"redPow(normalNum)\"),this.red._verify1(this),this.red.pow(this,t)};var v={k256:null,p224:null,p192:null,p25519:null};function y(t,e){this.name=t,this.p=new a(e,16),this.n=this.p.bitLength(),this.k=new a(1).iushln(this.n).isub(this.p),this.tmp=this._tmp()}function x(){y.call(this,\"k256\",\"ffffffff ffffffff ffffffff ffffffff ffffffff ffffffff fffffffe fffffc2f\")}function b(){y.call(this,\"p224\",\"ffffffff ffffffff ffffffff ffffffff 00000000 00000000 00000001\")}function _(){y.call(this,\"p192\",\"ffffffff ffffffff ffffffff fffffffe ffffffff ffffffff\")}function w(){y.call(this,\"25519\",\"7fffffffffffffff ffffffffffffffff ffffffffffffffff ffffffffffffffed\")}function T(t){if(\"string\"==typeof t){var e=a._prime(t);this.m=e.p,this.prime=e}else n(t.gtn(1),\"modulus must be greater than 1\"),this.m=t,this.prime=null}function k(t){T.call(this,t),this.shift=this.m.bitLength(),this.shift%26!=0&&(this.shift+=26-this.shift%26),this.r=new a(1).iushln(this.shift),this.r2=this.imod(this.r.sqr()),this.rinv=this.r._invmp(this.m),this.minv=this.rinv.mul(this.r).isubn(1).div(this.m),this.minv=this.minv.umod(this.r),this.minv=this.r.sub(this.minv)}y.prototype._tmp=function(){var t=new a(null);return t.words=new Array(Math.ceil(this.n/13)),t},y.prototype.ireduce=function(t){var e,r=t;do{this.split(r,this.tmp),e=(r=(r=this.imulK(r)).iadd(this.tmp)).bitLength()}while(e>this.n);var n=e<this.n?-1:r.ucmp(this.p);return 0===n?(r.words[0]=0,r.length=1):n>0?r.isub(this.p):void 0!==r.strip?r.strip():r._strip(),r},y.prototype.split=function(t,e){t.iushrn(this.n,0,e)},y.prototype.imulK=function(t){return t.imul(this.k)},i(x,y),x.prototype.split=function(t,e){for(var r=Math.min(t.length,9),n=0;n<r;n++)e.words[n]=t.words[n];if(e.length=r,t.length<=9)return t.words[0]=0,void(t.length=1);var i=t.words[9];for(e.words[e.length++]=4194303&i,n=10;n<t.length;n++){var a=0|t.words[n];t.words[n-10]=(4194303&a)<<4|i>>>22,i=a}i>>>=22,t.words[n-10]=i,0===i&&t.length>10?t.length-=10:t.length-=9},x.prototype.imulK=function(t){t.words[t.length]=0,t.words[t.length+1]=0,t.length+=2;for(var e=0,r=0;r<t.length;r++){var n=0|t.words[r];e+=977*n,t.words[r]=67108863&e,e=64*n+(e/67108864|0)}return 0===t.words[t.length-1]&&(t.length--,0===t.words[t.length-1]&&t.length--),t},i(b,y),i(_,y),i(w,y),w.prototype.imulK=function(t){for(var e=0,r=0;r<t.length;r++){var n=19*(0|t.words[r])+e,i=67108863&n;n>>>=26,t.words[r]=i,e=n}return 0!==e&&(t.words[t.length++]=e),t},a._prime=function(t){if(v[t])return v[t];var e;if(\"k256\"===t)e=new x;else if(\"p224\"===t)e=new b;else if(\"p192\"===t)e=new _;else{if(\"p25519\"!==t)throw new Error(\"Unknown prime \"+t);e=new w}return v[t]=e,e},T.prototype._verify1=function(t){n(0===t.negative,\"red works only with positives\"),n(t.red,\"red works only with red numbers\")},T.prototype._verify2=function(t,e){n(0==(t.negative|e.negative),\"red works only with positives\"),n(t.red&&t.red===e.red,\"red works only with red numbers\")},T.prototype.imod=function(t){return this.prime?this.prime.ireduce(t)._forceRed(this):t.umod(this.m)._forceRed(this)},T.prototype.neg=function(t){return t.isZero()?t.clone():this.m.sub(t)._forceRed(this)},T.prototype.add=function(t,e){this._verify2(t,e);var r=t.add(e);return r.cmp(this.m)>=0&&r.isub(this.m),r._forceRed(this)},T.prototype.iadd=function(t,e){this._verify2(t,e);var r=t.iadd(e);return r.cmp(this.m)>=0&&r.isub(this.m),r},T.prototype.sub=function(t,e){this._verify2(t,e);var r=t.sub(e);return r.cmpn(0)<0&&r.iadd(this.m),r._forceRed(this)},T.prototype.isub=function(t,e){this._verify2(t,e);var r=t.isub(e);return r.cmpn(0)<0&&r.iadd(this.m),r},T.prototype.shl=function(t,e){return this._verify1(t),this.imod(t.ushln(e))},T.prototype.imul=function(t,e){return this._verify2(t,e),this.imod(t.imul(e))},T.prototype.mul=function(t,e){return this._verify2(t,e),this.imod(t.mul(e))},T.prototype.isqr=function(t){return this.imul(t,t.clone())},T.prototype.sqr=function(t){return this.mul(t,t)},T.prototype.sqrt=function(t){if(t.isZero())return t.clone();var e=this.m.andln(3);if(n(e%2==1),3===e){var r=this.m.add(new a(1)).iushrn(2);return this.pow(t,r)}for(var i=this.m.subn(1),o=0;!i.isZero()&&0===i.andln(1);)o++,i.iushrn(1);n(!i.isZero());var s=new a(1).toRed(this),l=s.redNeg(),c=this.m.subn(1).iushrn(1),u=this.m.bitLength();for(u=new a(2*u*u).toRed(this);0!==this.pow(u,c).cmp(l);)u.redIAdd(l);for(var f=this.pow(u,i),h=this.pow(t,i.addn(1).iushrn(1)),p=this.pow(t,i),d=o;0!==p.cmp(s);){for(var m=p,g=0;0!==m.cmp(s);g++)m=m.redSqr();n(g<d);var v=this.pow(f,new a(1).iushln(d-g-1));h=h.redMul(v),f=v.redSqr(),p=p.redMul(f),d=g}return h},T.prototype.invm=function(t){var e=t._invmp(this.m);return 0!==e.negative?(e.negative=0,this.imod(e).redNeg()):this.imod(e)},T.prototype.pow=function(t,e){if(e.isZero())return new a(1).toRed(this);if(0===e.cmpn(1))return t.clone();var r=new Array(16);r[0]=new a(1).toRed(this),r[1]=t;for(var n=2;n<r.length;n++)r[n]=this.mul(r[n-1],t);var i=r[0],o=0,s=0,l=e.bitLength()%26;for(0===l&&(l=26),n=e.length-1;n>=0;n--){for(var c=e.words[n],u=l-1;u>=0;u--){var f=c>>u&1;i!==r[0]&&(i=this.sqr(i)),0!==f||0!==o?(o<<=1,o|=f,(4===++s||0===n&&0===u)&&(i=this.mul(i,r[o]),s=0,o=0)):s=0}l=26}return i},T.prototype.convertTo=function(t){var e=t.umod(this.m);return e===t?e.clone():e},T.prototype.convertFrom=function(t){var e=t.clone();return e.red=null,e},a.mont=function(t){return new k(t)},i(k,T),k.prototype.convertTo=function(t){return this.imod(t.ushln(this.shift))},k.prototype.convertFrom=function(t){var e=this.imod(t.mul(this.rinv));return e.red=null,e},k.prototype.imul=function(t,e){if(t.isZero()||e.isZero())return t.words[0]=0,t.length=1,t;var r=t.imul(e),n=r.maskn(this.shift).mul(this.minv).imaskn(this.shift).mul(this.m),i=r.isub(n).iushrn(this.shift),a=i;return i.cmp(this.m)>=0?a=i.isub(this.m):i.cmpn(0)<0&&(a=i.iadd(this.m)),a._forceRed(this)},k.prototype.mul=function(t,e){if(t.isZero()||e.isZero())return new a(0)._forceRed(this);var r=t.mul(e),n=r.maskn(this.shift).mul(this.minv).imaskn(this.shift).mul(this.m),i=r.isub(n).iushrn(this.shift),o=i;return i.cmp(this.m)>=0?o=i.isub(this.m):i.cmpn(0)<0&&(o=i.iadd(this.m)),o._forceRed(this)},k.prototype.invm=function(t){return this.imod(t._invmp(this.m).mul(this.r2))._forceRed(this)}}(void 0===e||e,this)},{buffer:2}],34:[function(t,e,r){\"use strict\";e.exports=function(t){var e,r,n,i=t.length,a=0;for(e=0;e<i;++e)a+=t[e].length;var o=new Array(a),s=0;for(e=0;e<i;++e){var l=t[e],c=l.length;for(r=0;r<c;++r){var u=o[s++]=new Array(c-1),f=0;for(n=0;n<c;++n)n!==r&&(u[f++]=l[n]);if(1&r){var h=u[1];u[1]=u[0],u[0]=h}}}return o}},{}],35:[function(t,e,r){\"use strict\";e.exports=function(t,e,r){switch(arguments.length){case 1:return f(t);case 2:return\"function\"==typeof e?c(t,t,e,!0):h(t,e);case 3:return c(t,e,r,!1);default:throw new Error(\"box-intersect: Invalid arguments\")}};var n,i=t(\"typedarray-pool\"),a=t(\"./lib/sweep\"),o=t(\"./lib/intersect\");function s(t,e){for(var r=0;r<t;++r)if(!(e[r]<=e[r+t]))return!0;return!1}function l(t,e,r,n){for(var i=0,a=0,o=0,l=t.length;o<l;++o){var c=t[o];if(!s(e,c)){for(var u=0;u<2*e;++u)r[i++]=c[u];n[a++]=o}}return a}function c(t,e,r,n){var s=t.length,c=e.length;if(!(s<=0||c<=0)){var u=t[0].length>>>1;if(!(u<=0)){var f,h=i.mallocDouble(2*u*s),p=i.mallocInt32(s);if((s=l(t,u,h,p))>0){if(1===u&&n)a.init(s),f=a.sweepComplete(u,r,0,s,h,p,0,s,h,p);else{var d=i.mallocDouble(2*u*c),m=i.mallocInt32(c);(c=l(e,u,d,m))>0&&(a.init(s+c),f=1===u?a.sweepBipartite(u,r,0,s,h,p,0,c,d,m):o(u,r,n,s,h,p,c,d,m),i.free(d),i.free(m))}i.free(h),i.free(p)}return f}}}function u(t,e){n.push([t,e])}function f(t){return n=[],c(t,t,u,!0),n}function h(t,e){return n=[],c(t,e,u,!1),n}},{\"./lib/intersect\":37,\"./lib/sweep\":41,\"typedarray-pool\":308}],36:[function(t,e,r){\"use strict\";function n(t){return t?function(t,e,r,n,i,a,o,s,l,c,u){return i-n>l-s?function(t,e,r,n,i,a,o,s,l,c,u){for(var f=2*t,h=n,p=f*n;h<i;++h,p+=f){var d=a[e+p],m=a[e+p+t],g=o[h];t:for(var v=s,y=f*s;v<l;++v,y+=f){var x=c[e+y],b=c[e+y+t],_=u[v];if(!(b<d||m<x)){for(var w=e+1;w<t;++w){var T=a[w+p],k=a[w+t+p],A=c[w+y],M=c[w+t+y];if(k<A||M<T)continue t}var S=r(g,_);if(void 0!==S)return S}}}}(t,e,r,n,i,a,o,s,l,c,u):function(t,e,r,n,i,a,o,s,l,c,u){for(var f=2*t,h=s,p=f*s;h<l;++h,p+=f){var d=c[e+p],m=c[e+p+t],g=u[h];t:for(var v=n,y=f*n;v<i;++v,y+=f){var x=a[e+y],b=a[e+y+t],_=o[v];if(!(m<x||b<d)){for(var w=e+1;w<t;++w){var T=a[w+y],k=a[w+t+y],A=c[w+p],M=c[w+t+p];if(k<A||M<T)continue t}var S=r(_,g);if(void 0!==S)return S}}}}(t,e,r,n,i,a,o,s,l,c,u)}:function(t,e,r,n,i,a,o,s,l,c,u,f){return a-i>c-l?n?function(t,e,r,n,i,a,o,s,l,c,u){for(var f=2*t,h=n,p=f*n;h<i;++h,p+=f){var d=a[e+p],m=a[e+p+t],g=o[h];t:for(var v=s,y=f*s;v<l;++v,y+=f){var x=c[e+y],b=u[v];if(!(x<=d||m<x)){for(var _=e+1;_<t;++_){var w=a[_+p],T=a[_+t+p],k=c[_+y],A=c[_+t+y];if(T<k||A<w)continue t}var M=r(b,g);if(void 0!==M)return 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e=i.nextPow2(t);o.length<e&&(n.free(o),o=n.mallocInt32(e));s.length<e&&(n.free(s),s=n.mallocInt32(e));l.length<e&&(n.free(l),l=n.mallocInt32(e));c.length<e&&(n.free(c),c=n.mallocInt32(e));u.length<e&&(n.free(u),u=n.mallocInt32(e));f.length<e&&(n.free(f),f=n.mallocInt32(e));var r=8*e;h.length<r&&(n.free(h),h=n.mallocDouble(r))},sweepBipartite:function(t,e,r,n,i,u,f,m,g,v){for(var y=0,x=2*t,b=t-1,_=x-1,w=r;w<n;++w){var T=u[w],k=x*w;h[y++]=i[k+b],h[y++]=-(T+1),h[y++]=i[k+_],h[y++]=T}for(w=f;w<m;++w){T=v[w]+(1<<28);var A=x*w;h[y++]=g[A+b],h[y++]=-T,h[y++]=g[A+_],h[y++]=T}var M=y>>>1;a(h,M);var S=0,E=0;for(w=0;w<M;++w){var L=0|h[2*w+1];if(L>=1<<28)p(l,c,E--,L=L-(1<<28)|0);else if(L>=0)p(o,s,S--,L);else if(L<=-(1<<28)){L=-L-(1<<28)|0;for(var C=0;C<S;++C){if(void 0!==(P=e(o[C],L)))return P}d(l,c,E++,L)}else{L=-L-1|0;for(C=0;C<E;++C){var P;if(void 0!==(P=e(L,l[C])))return P}d(o,s,S++,L)}}},sweepComplete:function(t,e,r,n,i,m,g,v,y,x){for(var b=0,_=2*t,w=t-1,T=_-1,k=r;k<n;++k){var 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e=this._compare,r=this.root,n=[],i=0;r;){var a=e(t,r.key);n.push(r),a<=0&&(i=n.length),r=a<=0?r.left:r.right}return n.length=i,new h(this,n)},l.gt=function(t){for(var e=this._compare,r=this.root,n=[],i=0;r;){var a=e(t,r.key);n.push(r),a<0&&(i=n.length),r=a<0?r.left:r.right}return n.length=i,new h(this,n)},l.lt=function(t){for(var e=this._compare,r=this.root,n=[],i=0;r;){var a=e(t,r.key);n.push(r),a>0&&(i=n.length),r=a<=0?r.left:r.right}return n.length=i,new h(this,n)},l.le=function(t){for(var e=this._compare,r=this.root,n=[],i=0;r;){var a=e(t,r.key);n.push(r),a>=0&&(i=n.length),r=a<0?r.left:r.right}return n.length=i,new h(this,n)},l.find=function(t){for(var e=this._compare,r=this.root,n=[];r;){var i=e(t,r.key);if(n.push(r),0===i)return new h(this,n);r=i<=0?r.left:r.right}return new h(this,[])},l.remove=function(t){var e=this.find(t);return e?e.remove():this},l.get=function(t){for(var e=this._compare,r=this.root;r;){var n=e(t,r.key);if(0===n)return r.value;r=n<=0?r.left:r.right}};var p=h.prototype;function d(t,e){t.key=e.key,t.value=e.value,t.left=e.left,t.right=e.right,t._color=e._color,t._count=e._count}function m(t,e){return t<e?-1:t>e?1:0}Object.defineProperty(p,\"valid\",{get:function(){return this._stack.length>0}}),Object.defineProperty(p,\"node\",{get:function(){return this._stack.length>0?this._stack[this._stack.length-1]:null},enumerable:!0}),p.clone=function(){return new h(this.tree,this._stack.slice())},p.remove=function(){var t=this._stack;if(0===t.length)return this.tree;var e=new Array(t.length),r=t[t.length-1];e[e.length-1]=new n(r._color,r.key,r.value,r.left,r.right,r._count);for(var l=t.length-2;l>=0;--l){(r=t[l]).left===t[l+1]?e[l]=new n(r._color,r.key,r.value,e[l+1],r.right,r._count):e[l]=new n(r._color,r.key,r.value,r.left,e[l+1],r._count)}if((r=e[e.length-1]).left&&r.right){var c=e.length;for(r=r.left;r.right;)e.push(r),r=r.right;var u=e[c-1];e.push(new n(r._color,u.key,u.value,r.left,r.right,r._count)),e[c-1].key=r.key,e[c-1].value=r.value;for(l=e.length-2;l>=c;--l)r=e[l],e[l]=new n(r._color,r.key,r.value,r.left,e[l+1],r._count);e[c-1].left=e[c]}if(0===(r=e[e.length-1])._color){var f=e[e.length-2];f.left===r?f.left=null:f.right===r&&(f.right=null),e.pop();for(l=0;l<e.length;++l)e[l]._count--;return new s(this.tree._compare,e[0])}if(r.left||r.right){r.left?d(r,r.left):r.right&&d(r,r.right),r._color=1;for(l=0;l<e.length-1;++l)e[l]._count--;return new s(this.tree._compare,e[0])}if(1===e.length)return new s(this.tree._compare,null);for(l=0;l<e.length;++l)e[l]._count--;var h=e[e.length-2];return function(t){for(var e,r,n,s,l=t.length-1;l>=0;--l){if(e=t[l],0===l)return void(e._color=1);if((r=t[l-1]).left===e){if((n=r.right).right&&0===n.right._color){if(s=(n=r.right=i(n)).right=i(n.right),r.right=n.left,n.left=r,n.right=s,n._color=r._color,e._color=1,r._color=1,s._color=1,o(r),o(n),l>1)(c=t[l-2]).left===r?c.left=n:c.right=n;return void(t[l-1]=n)}if(n.left&&0===n.left._color){if(s=(n=r.right=i(n)).left=i(n.left),r.right=s.left,n.left=s.right,s.left=r,s.right=n,s._color=r._color,r._color=1,n._color=1,e._color=1,o(r),o(n),o(s),l>1)(c=t[l-2]).left===r?c.left=s:c.right=s;return void(t[l-1]=s)}if(1===n._color){if(0===r._color)return r._color=1,void(r.right=a(0,n));r.right=a(0,n);continue}n=i(n),r.right=n.left,n.left=r,n._color=r._color,r._color=0,o(r),o(n),l>1&&((c=t[l-2]).left===r?c.left=n:c.right=n),t[l-1]=n,t[l]=r,l+1<t.length?t[l+1]=e:t.push(e),l+=2}else{if((n=r.left).left&&0===n.left._color){if(s=(n=r.left=i(n)).left=i(n.left),r.left=n.right,n.right=r,n.left=s,n._color=r._color,e._color=1,r._color=1,s._color=1,o(r),o(n),l>1)(c=t[l-2]).right===r?c.right=n:c.left=n;return void(t[l-1]=n)}if(n.right&&0===n.right._color){if(s=(n=r.left=i(n)).right=i(n.right),r.left=s.right,n.right=s.left,s.right=r,s.left=n,s._color=r._color,r._color=1,n._color=1,e._color=1,o(r),o(n),o(s),l>1)(c=t[l-2]).right===r?c.right=s:c.left=s;return void(t[l-1]=s)}if(1===n._color){if(0===r._color)return r._color=1,void(r.left=a(0,n));r.left=a(0,n);continue}var c;n=i(n),r.left=n.right,n.right=r,n._color=r._color,r._color=0,o(r),o(n),l>1&&((c=t[l-2]).right===r?c.right=n:c.left=n),t[l-1]=n,t[l]=r,l+1<t.length?t[l+1]=e:t.push(e),l+=2}}}(e),h.left===r?h.left=null:h.right=null,new s(this.tree._compare,e[0])},Object.defineProperty(p,\"key\",{get:function(){if(this._stack.length>0)return this._stack[this._stack.length-1].key},enumerable:!0}),Object.defineProperty(p,\"value\",{get:function(){if(this._stack.length>0)return this._stack[this._stack.length-1].value},enumerable:!0}),Object.defineProperty(p,\"index\",{get:function(){var t=0,e=this._stack;if(0===e.length){var r=this.tree.root;return r?r._count:0}e[e.length-1].left&&(t=e[e.length-1].left._count);for(var n=e.length-2;n>=0;--n)e[n+1]===e[n].right&&(++t,e[n].left&&(t+=e[n].left._count));return t},enumerable:!0}),p.next=function(){var t=this._stack;if(0!==t.length){var e=t[t.length-1];if(e.right)for(e=e.right;e;)t.push(e),e=e.left;else for(t.pop();t.length>0&&t[t.length-1].right===e;)e=t[t.length-1],t.pop()}},Object.defineProperty(p,\"hasNext\",{get:function(){var t=this._stack;if(0===t.length)return!1;if(t[t.length-1].right)return!0;for(var e=t.length-1;e>0;--e)if(t[e-1].left===t[e])return!0;return!1}}),p.update=function(t){var e=this._stack;if(0===e.length)throw new Error(\"Can't update empty node!\");var r=new Array(e.length),i=e[e.length-1];r[r.length-1]=new n(i._color,i.key,t,i.left,i.right,i._count);for(var a=e.length-2;a>=0;--a)(i=e[a]).left===e[a+1]?r[a]=new n(i._color,i.key,i.value,r[a+1],i.right,i._count):r[a]=new n(i._color,i.key,i.value,i.left,r[a+1],i._count);return new s(this.tree._compare,r[0])},p.prev=function(){var t=this._stack;if(0!==t.length){var e=t[t.length-1];if(e.left)for(e=e.left;e;)t.push(e),e=e.right;else for(t.pop();t.length>0&&t[t.length-1].left===e;)e=t[t.length-1],t.pop()}},Object.defineProperty(p,\"hasPrev\",{get:function(){var t=this._stack;if(0===t.length)return!1;if(t[t.length-1].left)return!0;for(var e=t.length-1;e>0;--e)if(t[e-1].right===t[e])return!0;return!1}})},{}],70:[function(t,e,r){\"use strict\";e.exports=function(t,e){var r=new u(t);return r.update(e),r};var n=t(\"./lib/text.js\"),i=t(\"./lib/lines.js\"),a=t(\"./lib/background.js\"),o=t(\"./lib/cube.js\"),s=t(\"./lib/ticks.js\"),l=new Float32Array([1,0,0,0,0,1,0,0,0,0,1,0,0,0,0,1]);function c(t,e){return t[0]=e[0],t[1]=e[1],t[2]=e[2],t}function u(t){this.gl=t,this.pixelRatio=1,this.bounds=[[-10,-10,-10],[10,10,10]],this.ticks=[[],[],[]],this.autoTicks=!0,this.tickSpacing=[1,1,1],this.tickEnable=[!0,!0,!0],this.tickFont=[\"sans-serif\",\"sans-serif\",\"sans-serif\"],this.tickSize=[12,12,12],this.tickAngle=[0,0,0],this.tickAlign=[\"auto\",\"auto\",\"auto\"],this.tickColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.tickPad=[10,10,10],this.lastCubeProps={cubeEdges:[0,0,0],axis:[0,0,0]},this.labels=[\"x\",\"y\",\"z\"],this.labelEnable=[!0,!0,!0],this.labelFont=\"sans-serif\",this.labelSize=[20,20,20],this.labelAngle=[0,0,0],this.labelAlign=[\"auto\",\"auto\",\"auto\"],this.labelColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.labelPad=[10,10,10],this.lineEnable=[!0,!0,!0],this.lineMirror=[!1,!1,!1],this.lineWidth=[1,1,1],this.lineColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.lineTickEnable=[!0,!0,!0],this.lineTickMirror=[!1,!1,!1],this.lineTickLength=[0,0,0],this.lineTickWidth=[1,1,1],this.lineTickColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.gridEnable=[!0,!0,!0],this.gridWidth=[1,1,1],this.gridColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.zeroEnable=[!0,!0,!0],this.zeroLineColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.zeroLineWidth=[2,2,2],this.backgroundEnable=[!1,!1,!1],this.backgroundColor=[[.8,.8,.8,.5],[.8,.8,.8,.5],[.8,.8,.8,.5]],this._firstInit=!0,this._text=null,this._lines=null,this._background=a(t)}var f=u.prototype;function h(){this.primalOffset=[0,0,0],this.primalMinor=[0,0,0],this.mirrorOffset=[0,0,0],this.mirrorMinor=[0,0,0]}f.update=function(t){function e(e,r,n){if(n in t){var i,a=t[n],o=this[n];(e?Array.isArray(a)&&Array.isArray(a[0]):Array.isArray(a))?this[n]=i=[r(a[0]),r(a[1]),r(a[2])]:this[n]=i=[r(a),r(a),r(a)];for(var s=0;s<3;++s)if(i[s]!==o[s])return!0}return!1}t=t||{};var r,a=e.bind(this,!1,Number),o=e.bind(this,!1,Boolean),l=e.bind(this,!1,String),c=e.bind(this,!0,(function(t){if(Array.isArray(t)){if(3===t.length)return[+t[0],+t[1],+t[2],1];if(4===t.length)return[+t[0],+t[1],+t[2],+t[3]]}return[0,0,0,1]})),u=!1,f=!1;if(\"bounds\"in t)for(var h=t.bounds,p=0;p<2;++p)for(var d=0;d<3;++d)h[p][d]!==this.bounds[p][d]&&(f=!0),this.bounds[p][d]=h[p][d];if(\"ticks\"in t){r=t.ticks,u=!0,this.autoTicks=!1;for(p=0;p<3;++p)this.tickSpacing[p]=0}else a(\"tickSpacing\")&&(this.autoTicks=!0,f=!0);if(this._firstInit&&(\"ticks\"in t||\"tickSpacing\"in t||(this.autoTicks=!0),f=!0,u=!0,this._firstInit=!1),f&&this.autoTicks&&(r=s.create(this.bounds,this.tickSpacing),u=!0),u){for(p=0;p<3;++p)r[p].sort((function(t,e){return t.x-e.x}));s.equal(r,this.ticks)?u=!1:this.ticks=r}o(\"tickEnable\"),l(\"tickFont\")&&(u=!0),a(\"tickSize\"),a(\"tickAngle\"),a(\"tickPad\"),c(\"tickColor\");var m=l(\"labels\");l(\"labelFont\")&&(m=!0),o(\"labelEnable\"),a(\"labelSize\"),a(\"labelPad\"),c(\"labelColor\"),o(\"lineEnable\"),o(\"lineMirror\"),a(\"lineWidth\"),c(\"lineColor\"),o(\"lineTickEnable\"),o(\"lineTickMirror\"),a(\"lineTickLength\"),a(\"lineTickWidth\"),c(\"lineTickColor\"),o(\"gridEnable\"),a(\"gridWidth\"),c(\"gridColor\"),o(\"zeroEnable\"),c(\"zeroLineColor\"),a(\"zeroLineWidth\"),o(\"backgroundEnable\"),c(\"backgroundColor\"),this._text?this._text&&(m||u)&&this._text.update(this.bounds,this.labels,this.labelFont,this.ticks,this.tickFont):this._text=n(this.gl,this.bounds,this.labels,this.labelFont,this.ticks,this.tickFont),this._lines&&u&&(this._lines.dispose(),this._lines=null),this._lines||(this._lines=i(this.gl,this.bounds,this.ticks))};var p=[new h,new h,new h];function d(t,e,r,n,i){for(var a=t.primalOffset,o=t.primalMinor,s=t.mirrorOffset,l=t.mirrorMinor,c=n[e],u=0;u<3;++u)if(e!==u){var f=a,h=s,p=o,d=l;c&1<<u&&(f=s,h=a,p=l,d=o),f[u]=r[0][u],h[u]=r[1][u],i[u]>0?(p[u]=-1,d[u]=0):(p[u]=0,d[u]=1)}}var m=[0,0,0],g={model:l,view:l,projection:l,_ortho:!1};f.isOpaque=function(){return!0},f.isTransparent=function(){return!1},f.drawTransparent=function(t){};var v=[0,0,0],y=[0,0,0],x=[0,0,0];f.draw=function(t){t=t||g;for(var e=this.gl,r=t.model||l,n=t.view||l,i=t.projection||l,a=this.bounds,s=t._ortho||!1,u=o(r,n,i,a,s),f=u.cubeEdges,h=u.axis,b=n[12],_=n[13],w=n[14],T=n[15],k=(s?2:1)*this.pixelRatio*(i[3]*b+i[7]*_+i[11]*w+i[15]*T)/e.drawingBufferHeight,A=0;A<3;++A)this.lastCubeProps.cubeEdges[A]=f[A],this.lastCubeProps.axis[A]=h[A];var M=p;for(A=0;A<3;++A)d(p[A],A,this.bounds,f,h);e=this.gl;var S,E=m;for(A=0;A<3;++A)this.backgroundEnable[A]?E[A]=h[A]:E[A]=0;this._background.draw(r,n,i,a,E,this.backgroundColor),this._lines.bind(r,n,i,this);for(A=0;A<3;++A){var L=[0,0,0];h[A]>0?L[A]=a[1][A]:L[A]=a[0][A];for(var C=0;C<2;++C){var P=(A+1+C)%3,I=(A+1+(1^C))%3;this.gridEnable[P]&&this._lines.drawGrid(P,I,this.bounds,L,this.gridColor[P],this.gridWidth[P]*this.pixelRatio)}for(C=0;C<2;++C){P=(A+1+C)%3,I=(A+1+(1^C))%3;this.zeroEnable[I]&&Math.min(a[0][I],a[1][I])<=0&&Math.max(a[0][I],a[1][I])>=0&&this._lines.drawZero(P,I,this.bounds,L,this.zeroLineColor[I],this.zeroLineWidth[I]*this.pixelRatio)}}for(A=0;A<3;++A){this.lineEnable[A]&&this._lines.drawAxisLine(A,this.bounds,M[A].primalOffset,this.lineColor[A],this.lineWidth[A]*this.pixelRatio),this.lineMirror[A]&&this._lines.drawAxisLine(A,this.bounds,M[A].mirrorOffset,this.lineColor[A],this.lineWidth[A]*this.pixelRatio);var O=c(v,M[A].primalMinor),z=c(y,M[A].mirrorMinor),D=this.lineTickLength;for(C=0;C<3;++C){var R=k/r[5*C];O[C]*=D[C]*R,z[C]*=D[C]*R}this.lineTickEnable[A]&&this._lines.drawAxisTicks(A,M[A].primalOffset,O,this.lineTickColor[A],this.lineTickWidth[A]*this.pixelRatio),this.lineTickMirror[A]&&this._lines.drawAxisTicks(A,M[A].mirrorOffset,z,this.lineTickColor[A],this.lineTickWidth[A]*this.pixelRatio)}this._lines.unbind(),this._text.bind(r,n,i,this.pixelRatio);var F,B;function N(t){(B=[0,0,0])[t]=1}function j(t,e,r){var n=(t+1)%3,i=(t+2)%3,a=e[n],o=e[i],s=r[n],l=r[i];a>0&&l>0||a>0&&l<0||a<0&&l>0||a<0&&l<0?N(n):(o>0&&s>0||o>0&&s<0||o<0&&s>0||o<0&&s<0)&&N(i)}for(A=0;A<3;++A){var U=M[A].primalMinor,V=M[A].mirrorMinor,H=c(x,M[A].primalOffset);for(C=0;C<3;++C)this.lineTickEnable[A]&&(H[C]+=k*U[C]*Math.max(this.lineTickLength[C],0)/r[5*C]);var q=[0,0,0];if(q[A]=1,this.tickEnable[A]){-3600===this.tickAngle[A]?(this.tickAngle[A]=0,this.tickAlign[A]=\"auto\"):this.tickAlign[A]=-1,F=1,\"auto\"===(S=[this.tickAlign[A],.5,F])[0]?S[0]=0:S[0]=parseInt(\"\"+S[0]),B=[0,0,0],j(A,U,V);for(C=0;C<3;++C)H[C]+=k*U[C]*this.tickPad[C]/r[5*C];this._text.drawTicks(A,this.tickSize[A],this.tickAngle[A],H,this.tickColor[A],q,B,S)}if(this.labelEnable[A]){F=0,B=[0,0,0],this.labels[A].length>4&&(N(A),F=1),\"auto\"===(S=[this.labelAlign[A],.5,F])[0]?S[0]=0:S[0]=parseInt(\"\"+S[0]);for(C=0;C<3;++C)H[C]+=k*U[C]*this.labelPad[C]/r[5*C];H[A]+=.5*(a[0][A]+a[1][A]),this._text.drawLabel(A,this.labelSize[A],this.labelAngle[A],H,this.labelColor[A],[0,0,0],B,S)}}this._text.unbind()},f.dispose=function(){this._text.dispose(),this._lines.dispose(),this._background.dispose(),this._lines=null,this._text=null,this._background=null,this.gl=null}},{\"./lib/background.js\":71,\"./lib/cube.js\":72,\"./lib/lines.js\":73,\"./lib/text.js\":75,\"./lib/ticks.js\":76}],71:[function(t,e,r){\"use strict\";e.exports=function(t){for(var e=[],r=[],s=0,l=0;l<3;++l)for(var c=(l+1)%3,u=(l+2)%3,f=[0,0,0],h=[0,0,0],p=-1;p<=1;p+=2){r.push(s,s+2,s+1,s+1,s+2,s+3),f[l]=p,h[l]=p;for(var d=-1;d<=1;d+=2){f[c]=d;for(var m=-1;m<=1;m+=2)f[u]=m,e.push(f[0],f[1],f[2],h[0],h[1],h[2]),s+=1}var g=c;c=u,u=g}var v=n(t,new Float32Array(e)),y=n(t,new Uint16Array(r),t.ELEMENT_ARRAY_BUFFER),x=i(t,[{buffer:v,type:t.FLOAT,size:3,offset:0,stride:24},{buffer:v,type:t.FLOAT,size:3,offset:12,stride:24}],y),b=a(t);return b.attributes.position.location=0,b.attributes.normal.location=1,new o(t,v,x,b)};var n=t(\"gl-buffer\"),i=t(\"gl-vao\"),a=t(\"./shaders\").bg;function o(t,e,r,n){this.gl=t,this.buffer=e,this.vao=r,this.shader=n}var s=o.prototype;s.draw=function(t,e,r,n,i,a){for(var o=!1,s=0;s<3;++s)o=o||i[s];if(o){var l=this.gl;l.enable(l.POLYGON_OFFSET_FILL),l.polygonOffset(1,2),this.shader.bind(),this.shader.uniforms={model:t,view:e,projection:r,bounds:n,enable:i,colors:a},this.vao.bind(),this.vao.draw(this.gl.TRIANGLES,36),this.vao.unbind(),l.disable(l.POLYGON_OFFSET_FILL)}},s.dispose=function(){this.vao.dispose(),this.buffer.dispose(),this.shader.dispose()}},{\"./shaders\":74,\"gl-buffer\":78,\"gl-vao\":150}],72:[function(t,e,r){\"use strict\";e.exports=function(t,e,r,a,p){i(s,e,t),i(s,r,s);for(var y=0,x=0;x<2;++x){u[2]=a[x][2];for(var b=0;b<2;++b){u[1]=a[b][1];for(var _=0;_<2;++_)u[0]=a[_][0],h(l[y],u,s),y+=1}}var w=-1;for(x=0;x<8;++x){for(var T=l[x][3],k=0;k<3;++k)c[x][k]=l[x][k]/T;p&&(c[x][2]*=-1),T<0&&(w<0||c[x][2]<c[w][2])&&(w=x)}if(w<0){w=0;for(var A=0;A<3;++A){for(var M=(A+2)%3,S=(A+1)%3,E=-1,L=-1,C=0;C<2;++C){var P=(O=C<<A)+(C<<M)+(1-C<<S),I=O+(1-C<<M)+(C<<S);o(c[O],c[P],c[I],f)<0||(C?E=1:L=1)}if(E<0||L<0)L>E&&(w|=1<<A);else{for(C=0;C<2;++C){P=(O=C<<A)+(C<<M)+(1-C<<S),I=O+(1-C<<M)+(C<<S);var O,z=d([l[O],l[P],l[I],l[O+(1<<M)+(1<<S)]]);C?E=z:L=z}L>E&&(w|=1<<A)}}}var D=7^w,R=-1;for(x=0;x<8;++x)x!==w&&x!==D&&(R<0||c[R][1]>c[x][1])&&(R=x);var F=-1;for(x=0;x<3;++x){if((N=R^1<<x)!==w&&N!==D)F<0&&(F=N),(S=c[N])[0]<c[F][0]&&(F=N)}var B=-1;for(x=0;x<3;++x){var N;if((N=R^1<<x)!==w&&N!==D&&N!==F)B<0&&(B=N),(S=c[N])[0]>c[B][0]&&(B=N)}var j=m;j[0]=j[1]=j[2]=0,j[n.log2(F^R)]=R&F,j[n.log2(R^B)]=R&B;var U=7^B;U===w||U===D?(U=7^F,j[n.log2(B^U)]=U&B):j[n.log2(F^U)]=U&F;var V=g,H=w;for(A=0;A<3;++A)V[A]=H&1<<A?-1:1;return v};var n=t(\"bit-twiddle\"),i=t(\"gl-mat4/multiply\"),a=t(\"split-polygon\"),o=t(\"robust-orientation\"),s=new Array(16),l=new Array(8),c=new Array(8),u=new Array(3),f=[0,0,0];function h(t,e,r){for(var n=0;n<4;++n){t[n]=r[12+n];for(var i=0;i<3;++i)t[n]+=e[i]*r[4*i+n]}}!function(){for(var t=0;t<8;++t)l[t]=[1,1,1,1],c[t]=[1,1,1]}();var p=[[0,0,1,0,0],[0,0,-1,1,0],[0,-1,0,1,0],[0,1,0,1,0],[-1,0,0,1,0],[1,0,0,1,0]];function d(t){for(var e=0;e<p.length;++e)if((t=a.positive(t,p[e])).length<3)return 0;var r=t[0],n=r[0]/r[3],i=r[1]/r[3],o=0;for(e=1;e+1<t.length;++e){var s=t[e],l=t[e+1],c=s[0]/s[3]-n,u=s[1]/s[3]-i,f=l[0]/l[3]-n,h=l[1]/l[3]-i;o+=Math.abs(c*h-u*f)}return o}var m=[1,1,1],g=[0,0,0],v={cubeEdges:m,axis:g}},{\"bit-twiddle\":32,\"gl-mat4/multiply\":100,\"robust-orientation\":284,\"split-polygon\":300}],73:[function(t,e,r){\"use strict\";e.exports=function(t,e,r){var o=[],s=[0,0,0],l=[0,0,0],c=[0,0,0],u=[0,0,0];o.push(0,0,1,0,1,1,0,0,-1,0,0,-1,0,1,1,0,1,-1);for(var f=0;f<3;++f){for(var h=o.length/3|0,d=0;d<r[f].length;++d){var m=+r[f][d].x;o.push(m,0,1,m,1,1,m,0,-1,m,0,-1,m,1,1,m,1,-1)}var g=o.length/3|0;s[f]=h,l[f]=g-h;h=o.length/3|0;for(var v=0;v<r[f].length;++v){m=+r[f][v].x;o.push(m,0,1,m,1,1,m,0,-1,m,0,-1,m,1,1,m,1,-1)}g=o.length/3|0;c[f]=h,u[f]=g-h}var y=n(t,new Float32Array(o)),x=i(t,[{buffer:y,type:t.FLOAT,size:3,stride:0,offset:0}]),b=a(t);return b.attributes.position.location=0,new p(t,y,x,b,l,s,u,c)};var n=t(\"gl-buffer\"),i=t(\"gl-vao\"),a=t(\"./shaders\").line,o=[0,0,0],s=[0,0,0],l=[0,0,0],c=[0,0,0],u=[1,1];function f(t){return t[0]=t[1]=t[2]=0,t}function h(t,e){return t[0]=e[0],t[1]=e[1],t[2]=e[2],t}function p(t,e,r,n,i,a,o,s){this.gl=t,this.vertBuffer=e,this.vao=r,this.shader=n,this.tickCount=i,this.tickOffset=a,this.gridCount=o,this.gridOffset=s}var d=p.prototype;d.bind=function(t,e,r){this.shader.bind(),this.shader.uniforms.model=t,this.shader.uniforms.view=e,this.shader.uniforms.projection=r,u[0]=this.gl.drawingBufferWidth,u[1]=this.gl.drawingBufferHeight,this.shader.uniforms.screenShape=u,this.vao.bind()},d.unbind=function(){this.vao.unbind()},d.drawAxisLine=function(t,e,r,n,i){var a=f(s);this.shader.uniforms.majorAxis=s,a[t]=e[1][t]-e[0][t],this.shader.uniforms.minorAxis=a;var o,u=h(c,r);u[t]+=e[0][t],this.shader.uniforms.offset=u,this.shader.uniforms.lineWidth=i,this.shader.uniforms.color=n,(o=f(l))[(t+2)%3]=1,this.shader.uniforms.screenAxis=o,this.vao.draw(this.gl.TRIANGLES,6),(o=f(l))[(t+1)%3]=1,this.shader.uniforms.screenAxis=o,this.vao.draw(this.gl.TRIANGLES,6)},d.drawAxisTicks=function(t,e,r,n,i){if(this.tickCount[t]){var a=f(o);a[t]=1,this.shader.uniforms.majorAxis=a,this.shader.uniforms.offset=e,this.shader.uniforms.minorAxis=r,this.shader.uniforms.color=n,this.shader.uniforms.lineWidth=i;var s=f(l);s[t]=1,this.shader.uniforms.screenAxis=s,this.vao.draw(this.gl.TRIANGLES,this.tickCount[t],this.tickOffset[t])}},d.drawGrid=function(t,e,r,n,i,a){if(this.gridCount[t]){var u=f(s);u[e]=r[1][e]-r[0][e],this.shader.uniforms.minorAxis=u;var p=h(c,n);p[e]+=r[0][e],this.shader.uniforms.offset=p;var d=f(o);d[t]=1,this.shader.uniforms.majorAxis=d;var m=f(l);m[t]=1,this.shader.uniforms.screenAxis=m,this.shader.uniforms.lineWidth=a,this.shader.uniforms.color=i,this.vao.draw(this.gl.TRIANGLES,this.gridCount[t],this.gridOffset[t])}},d.drawZero=function(t,e,r,n,i,a){var o=f(s);this.shader.uniforms.majorAxis=o,o[t]=r[1][t]-r[0][t],this.shader.uniforms.minorAxis=o;var u=h(c,n);u[t]+=r[0][t],this.shader.uniforms.offset=u;var p=f(l);p[e]=1,this.shader.uniforms.screenAxis=p,this.shader.uniforms.lineWidth=a,this.shader.uniforms.color=i,this.vao.draw(this.gl.TRIANGLES,6)},d.dispose=function(){this.vao.dispose(),this.vertBuffer.dispose(),this.shader.dispose()}},{\"./shaders\":74,\"gl-buffer\":78,\"gl-vao\":150}],74:[function(t,e,r){\"use strict\";var n=t(\"glslify\"),i=t(\"gl-shader\"),a=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nattribute vec3 position;\\n\\nuniform mat4 model, view, projection;\\nuniform vec3 offset, majorAxis, minorAxis, screenAxis;\\nuniform float lineWidth;\\nuniform vec2 screenShape;\\n\\nvec3 project(vec3 p) {\\n vec4 pp = projection * view * model * vec4(p, 1.0);\\n return pp.xyz / max(pp.w, 0.0001);\\n}\\n\\nvoid main() {\\n vec3 major = position.x * majorAxis;\\n vec3 minor = position.y * minorAxis;\\n\\n vec3 vPosition = major + minor + offset;\\n vec3 pPosition = project(vPosition);\\n vec3 offset = project(vPosition + screenAxis * position.z);\\n\\n vec2 screen = normalize((offset - pPosition).xy * screenShape) / screenShape;\\n\\n gl_Position = vec4(pPosition + vec3(0.5 * screen * lineWidth, 0), 1.0);\\n}\\n\"]),o=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nuniform vec4 color;\\nvoid main() {\\n gl_FragColor = color;\\n}\"]);r.line=function(t){return i(t,a,o,null,[{name:\"position\",type:\"vec3\"}])};var s=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nattribute vec3 position;\\n\\nuniform mat4 model, view, projection;\\nuniform vec3 offset, axis, alignDir, alignOpt;\\nuniform float scale, angle, pixelScale;\\nuniform vec2 resolution;\\n\\nvec3 project(vec3 p) {\\n vec4 pp = projection * view * model * vec4(p, 1.0);\\n return pp.xyz / max(pp.w, 0.0001);\\n}\\n\\nfloat computeViewAngle(vec3 a, vec3 b) {\\n vec3 A = project(a);\\n vec3 B = project(b);\\n\\n return atan(\\n (B.y - A.y) * resolution.y,\\n (B.x - A.x) * resolution.x\\n );\\n}\\n\\nconst float PI = 3.141592;\\nconst float TWO_PI = 2.0 * PI;\\nconst float HALF_PI = 0.5 * PI;\\nconst float ONE_AND_HALF_PI = 1.5 * PI;\\n\\nint option = int(floor(alignOpt.x + 0.001));\\nfloat hv_ratio = alignOpt.y;\\nbool enableAlign = (alignOpt.z != 0.0);\\n\\nfloat mod_angle(float a) {\\n return mod(a, PI);\\n}\\n\\nfloat positive_angle(float a) {\\n return mod_angle((a < 0.0) ?\\n a + TWO_PI :\\n a\\n );\\n}\\n\\nfloat look_upwards(float a) {\\n float b = positive_angle(a);\\n return ((b > HALF_PI) && (b <= ONE_AND_HALF_PI)) ?\\n b - PI :\\n b;\\n}\\n\\nfloat look_horizontal_or_vertical(float a, float ratio) {\\n // ratio controls the ratio between being horizontal to (vertical + horizontal)\\n // if ratio is set to 0.5 then it is 50%, 50%.\\n // when using a higher ratio e.g. 0.75 the result would\\n // likely be more horizontal than vertical.\\n\\n float b = positive_angle(a);\\n\\n return\\n (b < ( ratio) * HALF_PI) ? 0.0 :\\n (b < (2.0 - ratio) * HALF_PI) ? -HALF_PI :\\n (b < (2.0 + ratio) * HALF_PI) ? 0.0 :\\n (b < (4.0 - ratio) * HALF_PI) ? HALF_PI :\\n 0.0;\\n}\\n\\nfloat roundTo(float a, float b) {\\n return float(b * floor((a + 0.5 * b) / b));\\n}\\n\\nfloat look_round_n_directions(float a, int n) {\\n float b = positive_angle(a);\\n float div = TWO_PI / float(n);\\n float c = roundTo(b, div);\\n return look_upwards(c);\\n}\\n\\nfloat applyAlignOption(float rawAngle, float delta) {\\n return\\n (option > 2) ? look_round_n_directions(rawAngle + delta, option) : // option 3-n: round to n directions\\n (option == 2) ? look_horizontal_or_vertical(rawAngle + delta, hv_ratio) : // horizontal or vertical\\n (option == 1) ? rawAngle + delta : // use free angle, and flip to align with one direction of the axis\\n (option == 0) ? look_upwards(rawAngle) : // use free angle, and stay upwards\\n (option ==-1) ? 0.0 : // useful for backward compatibility, all texts remains horizontal\\n rawAngle; // otherwise return back raw input angle\\n}\\n\\nbool isAxisTitle = (axis.x == 0.0) &&\\n (axis.y == 0.0) &&\\n (axis.z == 0.0);\\n\\nvoid main() {\\n //Compute world offset\\n float axisDistance = position.z;\\n vec3 dataPosition = axisDistance * axis + offset;\\n\\n float beta = angle; // i.e. user defined attributes for each tick\\n\\n float axisAngle;\\n float clipAngle;\\n float flip;\\n\\n if (enableAlign) {\\n axisAngle = (isAxisTitle) ? HALF_PI :\\n computeViewAngle(dataPosition, dataPosition + axis);\\n clipAngle = computeViewAngle(dataPosition, dataPosition + alignDir);\\n\\n axisAngle += (sin(axisAngle) < 0.0) ? PI : 0.0;\\n clipAngle += (sin(clipAngle) < 0.0) ? PI : 0.0;\\n\\n flip = (dot(vec2(cos(axisAngle), sin(axisAngle)),\\n vec2(sin(clipAngle),-cos(clipAngle))) > 0.0) ? 1.0 : 0.0;\\n\\n beta += applyAlignOption(clipAngle, flip * PI);\\n }\\n\\n //Compute plane offset\\n vec2 planeCoord = position.xy * pixelScale;\\n\\n mat2 planeXform = scale * mat2(\\n cos(beta), sin(beta),\\n -sin(beta), cos(beta)\\n );\\n\\n vec2 viewOffset = 2.0 * planeXform * planeCoord / resolution;\\n\\n //Compute clip position\\n vec3 clipPosition = project(dataPosition);\\n\\n //Apply text offset in clip coordinates\\n clipPosition += vec3(viewOffset, 0.0);\\n\\n //Done\\n gl_Position = vec4(clipPosition, 1.0);\\n}\"]),l=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nuniform vec4 color;\\nvoid main() {\\n gl_FragColor = color;\\n}\"]);r.text=function(t){return i(t,s,l,null,[{name:\"position\",type:\"vec3\"}])};var c=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nattribute vec3 position;\\nattribute vec3 normal;\\n\\nuniform mat4 model, view, projection;\\nuniform vec3 enable;\\nuniform vec3 bounds[2];\\n\\nvarying vec3 colorChannel;\\n\\nvoid main() {\\n\\n vec3 signAxis = sign(bounds[1] - bounds[0]);\\n\\n vec3 realNormal = signAxis * normal;\\n\\n if(dot(realNormal, enable) > 0.0) {\\n vec3 minRange = min(bounds[0], bounds[1]);\\n vec3 maxRange = max(bounds[0], bounds[1]);\\n vec3 nPosition = mix(minRange, maxRange, 0.5 * (position + 1.0));\\n gl_Position = projection * view * model * vec4(nPosition, 1.0);\\n } else {\\n gl_Position = vec4(0,0,0,0);\\n }\\n\\n colorChannel = abs(realNormal);\\n}\"]),u=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nuniform vec4 colors[3];\\n\\nvarying vec3 colorChannel;\\n\\nvoid main() {\\n gl_FragColor = colorChannel.x * colors[0] +\\n colorChannel.y * colors[1] +\\n colorChannel.z * colors[2];\\n}\"]);r.bg=function(t){return i(t,c,u,null,[{name:\"position\",type:\"vec3\"},{name:\"normal\",type:\"vec3\"}])}},{\"gl-shader\":132,glslify:231}],75:[function(t,e,r){(function(r){(function(){\"use strict\";e.exports=function(t,e,r,a,s,l){var u=n(t),f=i(t,[{buffer:u,size:3}]),h=o(t);h.attributes.position.location=0;var p=new c(t,h,u,f);return p.update(e,r,a,s,l),p};var n=t(\"gl-buffer\"),i=t(\"gl-vao\"),a=t(\"vectorize-text\"),o=t(\"./shaders\").text,s=window||r.global||{},l=s.__TEXT_CACHE||{};s.__TEXT_CACHE={};function c(t,e,r,n){this.gl=t,this.shader=e,this.buffer=r,this.vao=n,this.tickOffset=this.tickCount=this.labelOffset=this.labelCount=null}var u=c.prototype,f=[0,0];u.bind=function(t,e,r,n){this.vao.bind(),this.shader.bind();var i=this.shader.uniforms;i.model=t,i.view=e,i.projection=r,i.pixelScale=n,f[0]=this.gl.drawingBufferWidth,f[1]=this.gl.drawingBufferHeight,this.shader.uniforms.resolution=f},u.unbind=function(){this.vao.unbind()},u.update=function(t,e,r,n,i){var o=[];function s(t,e,r,n,i,s){var c=l[r];c||(c=l[r]={});var u=c[e];u||(u=c[e]=function(t,e){try{return a(t,e)}catch(e){return console.warn('error vectorizing text:\"'+t+'\" error:',e),{cells:[],positions:[]}}}(e,{triangles:!0,font:r,textAlign:\"center\",textBaseline:\"middle\",lineSpacing:i,styletags:s}));for(var f=(n||12)/12,h=u.positions,p=u.cells,d=0,m=p.length;d<m;++d)for(var g=p[d],v=2;v>=0;--v){var y=h[g[v]];o.push(f*y[0],-f*y[1],t)}}for(var c=[0,0,0],u=[0,0,0],f=[0,0,0],h=[0,0,0],p={breaklines:!0,bolds:!0,italics:!0,subscripts:!0,superscripts:!0},d=0;d<3;++d){f[d]=o.length/3|0,s(.5*(t[0][d]+t[1][d]),e[d],r[d],12,1.25,p),h[d]=(o.length/3|0)-f[d],c[d]=o.length/3|0;for(var m=0;m<n[d].length;++m)n[d][m].text&&s(n[d][m].x,n[d][m].text,n[d][m].font||i,n[d][m].fontSize||12,1.25,p);u[d]=(o.length/3|0)-c[d]}this.buffer.update(o),this.tickOffset=c,this.tickCount=u,this.labelOffset=f,this.labelCount=h},u.drawTicks=function(t,e,r,n,i,a,o,s){this.tickCount[t]&&(this.shader.uniforms.axis=a,this.shader.uniforms.color=i,this.shader.uniforms.angle=r,this.shader.uniforms.scale=e,this.shader.uniforms.offset=n,this.shader.uniforms.alignDir=o,this.shader.uniforms.alignOpt=s,this.vao.draw(this.gl.TRIANGLES,this.tickCount[t],this.tickOffset[t]))},u.drawLabel=function(t,e,r,n,i,a,o,s){this.labelCount[t]&&(this.shader.uniforms.axis=a,this.shader.uniforms.color=i,this.shader.uniforms.angle=r,this.shader.uniforms.scale=e,this.shader.uniforms.offset=n,this.shader.uniforms.alignDir=o,this.shader.uniforms.alignOpt=s,this.vao.draw(this.gl.TRIANGLES,this.labelCount[t],this.labelOffset[t]))},u.dispose=function(){this.shader.dispose(),this.vao.dispose(),this.buffer.dispose()}}).call(this)}).call(this,t(\"_process\"))},{\"./shaders\":74,_process:5,\"gl-buffer\":78,\"gl-vao\":150,\"vectorize-text\":311}],76:[function(t,e,r){\"use strict\";function n(t,e){var r=t+\"\",n=r.indexOf(\".\"),i=0;n>=0&&(i=r.length-n-1);var a=Math.pow(10,i),o=Math.round(t*e*a),s=o+\"\";if(s.indexOf(\"e\")>=0)return s;var l=o/a,c=o%a;o<0?(l=0|-Math.ceil(l),c=0|-c):(l=0|Math.floor(l),c|=0);var u=\"\"+l;if(o<0&&(u=\"-\"+u),i){for(var f=\"\"+c;f.length<i;)f=\"0\"+f;return u+\".\"+f}return u}r.create=function(t,e){for(var r=[],i=0;i<3;++i){for(var a=[],o=(t[0][i],t[1][i],0);o*e[i]<=t[1][i];++o)a.push({x:o*e[i],text:n(e[i],o)});for(o=-1;o*e[i]>=t[0][i];--o)a.push({x:o*e[i],text:n(e[i],o)});r.push(a)}return r},r.equal=function(t,e){for(var r=0;r<3;++r){if(t[r].length!==e[r].length)return!1;for(var n=0;n<t[r].length;++n){var i=t[r][n],a=e[r][n];if(i.x!==a.x||i.text!==a.text||i.font!==a.font||i.fontColor!==a.fontColor||i.fontSize!==a.fontSize||i.dx!==a.dx||i.dy!==a.dy)return!1}}return!0}},{}],77:[function(t,e,r){\"use strict\";e.exports=function(t,e,r,l,f){var h=e.model||c,p=e.view||c,v=e.projection||c,y=e._ortho||!1,x=t.bounds,b=(f=f||a(h,p,v,x,y)).axis;o(u,p,h),o(u,v,u);for(var _=m,w=0;w<3;++w)_[w].lo=1/0,_[w].hi=-1/0,_[w].pixelsPerDataUnit=1/0;var T=n(s(u,u));s(u,u);for(var k=0;k<3;++k){var A=(k+1)%3,M=(k+2)%3,S=g;t:for(w=0;w<2;++w){var E=[];if(b[k]<0!=!!w){S[k]=x[w][k];for(var L=0;L<2;++L){S[A]=x[L^w][A];for(var C=0;C<2;++C)S[M]=x[C^L^w][M],E.push(S.slice())}var P=y?5:4;for(L=P;L===P;++L){if(0===E.length)continue t;E=i.positive(E,T[L])}for(L=0;L<E.length;++L){M=E[L];var I=d(g,u,M,r,l);for(C=0;C<3;++C)_[C].lo=Math.min(_[C].lo,M[C]),_[C].hi=Math.max(_[C].hi,M[C]),C!==k&&(_[C].pixelsPerDataUnit=Math.min(_[C].pixelsPerDataUnit,Math.abs(I[C])))}}}}return _};var n=t(\"extract-frustum-planes\"),i=t(\"split-polygon\"),a=t(\"./lib/cube.js\"),o=t(\"gl-mat4/multiply\"),s=t(\"gl-mat4/transpose\"),l=t(\"gl-vec4/transformMat4\"),c=new Float32Array([1,0,0,0,0,1,0,0,0,0,1,0,0,0,0,1]),u=new Float32Array(16);function f(t,e,r){this.lo=t,this.hi=e,this.pixelsPerDataUnit=r}var h=[0,0,0,1],p=[0,0,0,1];function d(t,e,r,n,i){for(var a=0;a<3;++a){for(var o=h,s=p,c=0;c<3;++c)s[c]=o[c]=r[c];s[3]=o[3]=1,s[a]+=1,l(s,s,e),s[3]<0&&(t[a]=1/0),o[a]-=1,l(o,o,e),o[3]<0&&(t[a]=1/0);var u=(o[0]/o[3]-s[0]/s[3])*n,f=(o[1]/o[3]-s[1]/s[3])*i;t[a]=.25*Math.sqrt(u*u+f*f)}return t}var m=[new f(1/0,-1/0,1/0),new f(1/0,-1/0,1/0),new f(1/0,-1/0,1/0)],g=[0,0,0]},{\"./lib/cube.js\":72,\"extract-frustum-planes\":67,\"gl-mat4/multiply\":100,\"gl-mat4/transpose\":109,\"gl-vec4/transformMat4\":221,\"split-polygon\":300}],78:[function(t,e,r){\"use strict\";var n=t(\"typedarray-pool\"),i=t(\"ndarray-ops\"),a=t(\"ndarray\"),o=[\"uint8\",\"uint8_clamped\",\"uint16\",\"uint32\",\"int8\",\"int16\",\"int32\",\"float32\"];function s(t,e,r,n,i){this.gl=t,this.type=e,this.handle=r,this.length=n,this.usage=i}var l=s.prototype;function c(t,e,r,n,i,a){var o=i.length*i.BYTES_PER_ELEMENT;if(a<0)return t.bufferData(e,i,n),o;if(o+a>r)throw new Error(\"gl-buffer: If resizing buffer, must not specify offset\");return t.bufferSubData(e,a,i),r}function u(t,e){for(var r=n.malloc(t.length,e),i=t.length,a=0;a<i;++a)r[a]=t[a];return r}l.bind=function(){this.gl.bindBuffer(this.type,this.handle)},l.unbind=function(){this.gl.bindBuffer(this.type,null)},l.dispose=function(){this.gl.deleteBuffer(this.handle)},l.update=function(t,e){if(\"number\"!=typeof e&&(e=-1),this.bind(),\"object\"==typeof t&&void 0!==t.shape){var r=t.dtype;if(o.indexOf(r)<0&&(r=\"float32\"),this.type===this.gl.ELEMENT_ARRAY_BUFFER)r=gl.getExtension(\"OES_element_index_uint\")&&\"uint16\"!==r?\"uint32\":\"uint16\";if(r===t.dtype&&function(t,e){for(var r=1,n=e.length-1;n>=0;--n){if(e[n]!==r)return!1;r*=t[n]}return!0}(t.shape,t.stride))0===t.offset&&t.data.length===t.shape[0]?this.length=c(this.gl,this.type,this.length,this.usage,t.data,e):this.length=c(this.gl,this.type,this.length,this.usage,t.data.subarray(t.offset,t.shape[0]),e);else{var s=n.malloc(t.size,r),l=a(s,t.shape);i.assign(l,t),this.length=c(this.gl,this.type,this.length,this.usage,e<0?s:s.subarray(0,t.size),e),n.free(s)}}else if(Array.isArray(t)){var f;f=this.type===this.gl.ELEMENT_ARRAY_BUFFER?u(t,\"uint16\"):u(t,\"float32\"),this.length=c(this.gl,this.type,this.length,this.usage,e<0?f:f.subarray(0,t.length),e),n.free(f)}else if(\"object\"==typeof t&&\"number\"==typeof t.length)this.length=c(this.gl,this.type,this.length,this.usage,t,e);else{if(\"number\"!=typeof t&&void 0!==t)throw new Error(\"gl-buffer: Invalid data type\");if(e>=0)throw new Error(\"gl-buffer: Cannot specify offset when resizing buffer\");(t|=0)<=0&&(t=1),this.gl.bufferData(this.type,0|t,this.usage),this.length=t}},e.exports=function(t,e,r,n){if(r=r||t.ARRAY_BUFFER,n=n||t.DYNAMIC_DRAW,r!==t.ARRAY_BUFFER&&r!==t.ELEMENT_ARRAY_BUFFER)throw new Error(\"gl-buffer: Invalid type for webgl buffer, must be either gl.ARRAY_BUFFER or gl.ELEMENT_ARRAY_BUFFER\");if(n!==t.DYNAMIC_DRAW&&n!==t.STATIC_DRAW&&n!==t.STREAM_DRAW)throw new Error(\"gl-buffer: Invalid usage for buffer, must be either gl.DYNAMIC_DRAW, gl.STATIC_DRAW or gl.STREAM_DRAW\");var i=t.createBuffer(),a=new s(t,r,i,0,n);return a.update(e),a}},{ndarray:259,\"ndarray-ops\":254,\"typedarray-pool\":308}],79:[function(t,e,r){\"use strict\";var n=t(\"gl-vec3\");e.exports=function(t,e){var r=t.positions,i=t.vectors,a={positions:[],vertexIntensity:[],vertexIntensityBounds:t.vertexIntensityBounds,vectors:[],cells:[],coneOffset:t.coneOffset,colormap:t.colormap};if(0===t.positions.length)return e&&(e[0]=[0,0,0],e[1]=[0,0,0]),a;for(var o=0,s=1/0,l=-1/0,c=1/0,u=-1/0,f=1/0,h=-1/0,p=null,d=null,m=[],g=1/0,v=!1,y=0;y<r.length;y++){var x=r[y];s=Math.min(x[0],s),l=Math.max(x[0],l),c=Math.min(x[1],c),u=Math.max(x[1],u),f=Math.min(x[2],f),h=Math.max(x[2],h);var b=i[y];if(n.length(b)>o&&(o=n.length(b)),y){var _=2*n.distance(p,x)/(n.length(d)+n.length(b));_?(g=Math.min(g,_),v=!1):v=!0}v||(p=x,d=b),m.push(b)}var w=[s,c,f],T=[l,u,h];e&&(e[0]=w,e[1]=T),0===o&&(o=1);var k=1/o;isFinite(g)||(g=1),a.vectorScale=g;var A=t.coneSize||.5;t.absoluteConeSize&&(A=t.absoluteConeSize*k),a.coneScale=A;y=0;for(var M=0;y<r.length;y++)for(var S=(x=r[y])[0],E=x[1],L=x[2],C=m[y],P=n.length(C)*k,I=0;I<8;I++){a.positions.push([S,E,L,M++]),a.positions.push([S,E,L,M++]),a.positions.push([S,E,L,M++]),a.positions.push([S,E,L,M++]),a.positions.push([S,E,L,M++]),a.positions.push([S,E,L,M++]),a.vectors.push(C),a.vectors.push(C),a.vectors.push(C),a.vectors.push(C),a.vectors.push(C),a.vectors.push(C),a.vertexIntensity.push(P,P,P),a.vertexIntensity.push(P,P,P);var O=a.positions.length;a.cells.push([O-6,O-5,O-4],[O-3,O-2,O-1])}return a};var i=t(\"./lib/shaders\");e.exports.createMesh=t(\"./create_mesh\"),e.exports.createConeMesh=function(t,r){return e.exports.createMesh(t,r,{shaders:i,traceType:\"cone\"})}},{\"./create_mesh\":80,\"./lib/shaders\":81,\"gl-vec3\":169}],80:[function(t,e,r){\"use strict\";var n=t(\"gl-shader\"),i=t(\"gl-buffer\"),a=t(\"gl-vao\"),o=t(\"gl-texture2d\"),s=t(\"gl-mat4/multiply\"),l=t(\"gl-mat4/invert\"),c=t(\"ndarray\"),u=t(\"colormap\"),f=[1,0,0,0,0,1,0,0,0,0,1,0,0,0,0,1];function h(t,e,r,n,i,a,o,s,l,c,u){this.gl=t,this.pixelRatio=1,this.cells=[],this.positions=[],this.intensity=[],this.texture=e,this.dirty=!0,this.triShader=r,this.pickShader=n,this.trianglePositions=i,this.triangleVectors=a,this.triangleColors=s,this.triangleUVs=l,this.triangleIds=o,this.triangleVAO=c,this.triangleCount=0,this.pickId=1,this.bounds=[[1/0,1/0,1/0],[-1/0,-1/0,-1/0]],this.clipBounds=[[-1/0,-1/0,-1/0],[1/0,1/0,1/0]],this.lightPosition=[1e5,1e5,0],this.ambientLight=.8,this.diffuseLight=.8,this.specularLight=2,this.roughness=.5,this.fresnel=1.5,this.opacity=1,this.traceType=u,this.tubeScale=1,this.coneScale=2,this.vectorScale=1,this.coneOffset=.25,this._model=f,this._view=f,this._projection=f,this._resolution=[1,1]}var p=h.prototype;function d(t,e){var r=n(t,e.meshShader.vertex,e.meshShader.fragment,null,e.meshShader.attributes);return r.attributes.position.location=0,r.attributes.color.location=2,r.attributes.uv.location=3,r.attributes.vector.location=4,r}function m(t,e){var r=n(t,e.pickShader.vertex,e.pickShader.fragment,null,e.pickShader.attributes);return r.attributes.position.location=0,r.attributes.id.location=1,r.attributes.vector.location=4,r}p.isOpaque=function(){return this.opacity>=1},p.isTransparent=function(){return this.opacity<1},p.pickSlots=1,p.setPickBase=function(t){this.pickId=t},p.update=function(t){t=t||{};var e=this.gl;this.dirty=!0,\"lightPosition\"in t&&(this.lightPosition=t.lightPosition),\"opacity\"in t&&(this.opacity=t.opacity),\"ambient\"in t&&(this.ambientLight=t.ambient),\"diffuse\"in t&&(this.diffuseLight=t.diffuse),\"specular\"in t&&(this.specularLight=t.specular),\"roughness\"in t&&(this.roughness=t.roughness),\"fresnel\"in t&&(this.fresnel=t.fresnel),void 0!==t.tubeScale&&(this.tubeScale=t.tubeScale),void 0!==t.vectorScale&&(this.vectorScale=t.vectorScale),void 0!==t.coneScale&&(this.coneScale=t.coneScale),void 0!==t.coneOffset&&(this.coneOffset=t.coneOffset),t.colormap&&(this.texture.shape=[256,256],this.texture.minFilter=e.LINEAR_MIPMAP_LINEAR,this.texture.magFilter=e.LINEAR,this.texture.setPixels(function(t){for(var e=u({colormap:t,nshades:256,format:\"rgba\"}),r=new Uint8Array(1024),n=0;n<256;++n){for(var i=e[n],a=0;a<3;++a)r[4*n+a]=i[a];r[4*n+3]=255*i[3]}return c(r,[256,256,4],[4,0,1])}(t.colormap)),this.texture.generateMipmap());var r=t.cells,n=t.positions,i=t.vectors;if(n&&r&&i){var a=[],o=[],s=[],l=[],f=[];this.cells=r,this.positions=n,this.vectors=i;var h=t.meshColor||[1,1,1,1],p=t.vertexIntensity,d=1/0,m=-1/0;if(p)if(t.vertexIntensityBounds)d=+t.vertexIntensityBounds[0],m=+t.vertexIntensityBounds[1];else for(var g=0;g<p.length;++g){var v=p[g];d=Math.min(d,v),m=Math.max(m,v)}else for(g=0;g<n.length;++g){v=n[g][2];d=Math.min(d,v),m=Math.max(m,v)}this.intensity=p||function(t){for(var e=t.length,r=new Array(e),n=0;n<e;++n)r[n]=t[n][2];return r}(n),this.bounds=[[1/0,1/0,1/0],[-1/0,-1/0,-1/0]];for(g=0;g<n.length;++g)for(var y=n[g],x=0;x<3;++x)!isNaN(y[x])&&isFinite(y[x])&&(this.bounds[0][x]=Math.min(this.bounds[0][x],y[x]),this.bounds[1][x]=Math.max(this.bounds[1][x],y[x]));var b=0;t:for(g=0;g<r.length;++g){var _=r[g];switch(_.length){case 3:for(x=0;x<3;++x){y=n[T=_[x]];for(var w=0;w<3;++w)if(isNaN(y[w])||!isFinite(y[w]))continue t}for(x=0;x<3;++x){var T;y=n[T=_[2-x]];a.push(y[0],y[1],y[2],y[3]);var k=i[T];o.push(k[0],k[1],k[2],k[3]||0);var A,M=h;3===M.length?s.push(M[0],M[1],M[2],1):s.push(M[0],M[1],M[2],M[3]),A=p?[(p[T]-d)/(m-d),0]:[(y[2]-d)/(m-d),0],l.push(A[0],A[1]),f.push(g)}b+=1}}this.triangleCount=b,this.trianglePositions.update(a),this.triangleVectors.update(o),this.triangleColors.update(s),this.triangleUVs.update(l),this.triangleIds.update(new Uint32Array(f))}},p.drawTransparent=p.draw=function(t){t=t||{};for(var e=this.gl,r=t.model||f,n=t.view||f,i=t.projection||f,a=[[-1e6,-1e6,-1e6],[1e6,1e6,1e6]],o=0;o<3;++o)a[0][o]=Math.max(a[0][o],this.clipBounds[0][o]),a[1][o]=Math.min(a[1][o],this.clipBounds[1][o]);var c={model:r,view:n,projection:i,inverseModel:f.slice(),clipBounds:a,kambient:this.ambientLight,kdiffuse:this.diffuseLight,kspecular:this.specularLight,roughness:this.roughness,fresnel:this.fresnel,eyePosition:[0,0,0],lightPosition:[0,0,0],opacity:this.opacity,tubeScale:this.tubeScale,vectorScale:this.vectorScale,coneScale:this.coneScale,coneOffset:this.coneOffset,texture:0};c.inverseModel=l(c.inverseModel,c.model),e.disable(e.CULL_FACE),this.texture.bind(0);var u=new Array(16);s(u,c.view,c.model),s(u,c.projection,u),l(u,u);for(o=0;o<3;++o)c.eyePosition[o]=u[12+o]/u[15];var h=u[15];for(o=0;o<3;++o)h+=this.lightPosition[o]*u[4*o+3];for(o=0;o<3;++o){for(var p=u[12+o],d=0;d<3;++d)p+=u[4*d+o]*this.lightPosition[d];c.lightPosition[o]=p/h}if(this.triangleCount>0){var m=this.triShader;m.bind(),m.uniforms=c,this.triangleVAO.bind(),e.drawArrays(e.TRIANGLES,0,3*this.triangleCount),this.triangleVAO.unbind()}},p.drawPick=function(t){t=t||{};for(var e=this.gl,r=t.model||f,n=t.view||f,i=t.projection||f,a=[[-1e6,-1e6,-1e6],[1e6,1e6,1e6]],o=0;o<3;++o)a[0][o]=Math.max(a[0][o],this.clipBounds[0][o]),a[1][o]=Math.min(a[1][o],this.clipBounds[1][o]);this._model=[].slice.call(r),this._view=[].slice.call(n),this._projection=[].slice.call(i),this._resolution=[e.drawingBufferWidth,e.drawingBufferHeight];var s={model:r,view:n,projection:i,clipBounds:a,tubeScale:this.tubeScale,vectorScale:this.vectorScale,coneScale:this.coneScale,coneOffset:this.coneOffset,pickId:this.pickId/255},l=this.pickShader;l.bind(),l.uniforms=s,this.triangleCount>0&&(this.triangleVAO.bind(),e.drawArrays(e.TRIANGLES,0,3*this.triangleCount),this.triangleVAO.unbind())},p.pick=function(t){if(!t)return null;if(t.id!==this.pickId)return null;var e=t.value[0]+256*t.value[1]+65536*t.value[2],r=this.cells[e],n=this.positions[r[1]].slice(0,3),i={position:n,dataCoordinate:n,index:Math.floor(r[1]/48)};return\"cone\"===this.traceType?i.index=Math.floor(r[1]/48):\"streamtube\"===this.traceType&&(i.intensity=this.intensity[r[1]],i.velocity=this.vectors[r[1]].slice(0,3),i.divergence=this.vectors[r[1]][3],i.index=e),i},p.dispose=function(){this.texture.dispose(),this.triShader.dispose(),this.pickShader.dispose(),this.triangleVAO.dispose(),this.trianglePositions.dispose(),this.triangleVectors.dispose(),this.triangleColors.dispose(),this.triangleUVs.dispose(),this.triangleIds.dispose()},e.exports=function(t,e,r){var n=r.shaders;1===arguments.length&&(t=(e=t).gl);var s=d(t,n),l=m(t,n),u=o(t,c(new Uint8Array([255,255,255,255]),[1,1,4]));u.generateMipmap(),u.minFilter=t.LINEAR_MIPMAP_LINEAR,u.magFilter=t.LINEAR;var f=i(t),p=i(t),g=i(t),v=i(t),y=i(t),x=a(t,[{buffer:f,type:t.FLOAT,size:4},{buffer:y,type:t.UNSIGNED_BYTE,size:4,normalized:!0},{buffer:g,type:t.FLOAT,size:4},{buffer:v,type:t.FLOAT,size:2},{buffer:p,type:t.FLOAT,size:4}]),b=new h(t,u,s,l,f,p,y,g,v,x,r.traceType||\"cone\");return b.update(e),b}},{colormap:53,\"gl-buffer\":78,\"gl-mat4/invert\":98,\"gl-mat4/multiply\":100,\"gl-shader\":132,\"gl-texture2d\":146,\"gl-vao\":150,ndarray:259}],81:[function(t,e,r){var n=t(\"glslify\"),i=n([\"precision highp float;\\n\\nprecision highp float;\\n#define GLSLIFY 1\\n\\nvec3 getOrthogonalVector(vec3 v) {\\n // Return up-vector for only-z vector.\\n // Return ax + by + cz = 0, a point that lies on the plane that has v as a normal and that isn't (0,0,0).\\n // From the above if-statement we have ||a|| > 0 U ||b|| > 0.\\n // Assign z = 0, x = -b, y = a:\\n // a*-b + b*a + c*0 = -ba + ba + 0 = 0\\n if (v.x*v.x > v.z*v.z || v.y*v.y > v.z*v.z) {\\n return normalize(vec3(-v.y, v.x, 0.0));\\n } else {\\n return normalize(vec3(0.0, v.z, -v.y));\\n }\\n}\\n\\n// Calculate the cone vertex and normal at the given index.\\n//\\n// The returned vertex is for a cone with its top at origin and height of 1.0,\\n// pointing in the direction of the vector attribute.\\n//\\n// Each cone is made up of a top vertex, a center base vertex and base perimeter vertices.\\n// These vertices are used to make up the triangles of the cone by the following:\\n// segment + 0 top vertex\\n// segment + 1 perimeter vertex a+1\\n// segment + 2 perimeter vertex a\\n// segment + 3 center base vertex\\n// segment + 4 perimeter vertex a\\n// segment + 5 perimeter vertex a+1\\n// Where segment is the number of the radial segment * 6 and a is the angle at that radial segment.\\n// To go from index to segment, floor(index / 6)\\n// To go from segment to angle, 2*pi * (segment/segmentCount)\\n// To go from index to segment index, index - (segment*6)\\n//\\nvec3 getConePosition(vec3 d, float rawIndex, float coneOffset, out vec3 normal) {\\n\\n const float segmentCount = 8.0;\\n\\n float index = rawIndex - floor(rawIndex /\\n (segmentCount * 6.0)) *\\n (segmentCount * 6.0);\\n\\n float segment = floor(0.001 + index/6.0);\\n float segmentIndex = index - (segment*6.0);\\n\\n normal = -normalize(d);\\n\\n if (segmentIndex > 2.99 && segmentIndex < 3.01) {\\n return mix(vec3(0.0), -d, coneOffset);\\n }\\n\\n float nextAngle = (\\n (segmentIndex > 0.99 && segmentIndex < 1.01) ||\\n (segmentIndex > 4.99 && segmentIndex < 5.01)\\n ) ? 1.0 : 0.0;\\n float angle = 2.0 * 3.14159 * ((segment + nextAngle) / segmentCount);\\n\\n vec3 v1 = mix(d, vec3(0.0), coneOffset);\\n vec3 v2 = v1 - d;\\n\\n vec3 u = getOrthogonalVector(d);\\n vec3 v = normalize(cross(u, d));\\n\\n vec3 x = u * cos(angle) * length(d)*0.25;\\n vec3 y = v * sin(angle) * length(d)*0.25;\\n vec3 v3 = v2 + x + y;\\n if (segmentIndex < 3.0) {\\n vec3 tx = u * sin(angle);\\n vec3 ty = v * -cos(angle);\\n vec3 tangent = tx + ty;\\n normal = normalize(cross(v3 - v1, tangent));\\n }\\n\\n if (segmentIndex == 0.0) {\\n return mix(d, vec3(0.0), coneOffset);\\n }\\n return v3;\\n}\\n\\nattribute vec3 vector;\\nattribute vec4 color, position;\\nattribute vec2 uv;\\n\\nuniform float vectorScale, coneScale, coneOffset;\\nuniform mat4 model, view, projection, inverseModel;\\nuniform vec3 eyePosition, lightPosition;\\n\\nvarying vec3 f_normal, f_lightDirection, f_eyeDirection, f_data, f_position;\\nvarying vec4 f_color;\\nvarying vec2 f_uv;\\n\\nvoid main() {\\n // Scale the vector magnitude to stay constant with\\n // model & view changes.\\n vec3 normal;\\n vec3 XYZ = getConePosition(mat3(model) * ((vectorScale * coneScale) * vector), position.w, coneOffset, normal);\\n vec4 conePosition = model * vec4(position.xyz, 1.0) + vec4(XYZ, 0.0);\\n\\n //Lighting geometry parameters\\n vec4 cameraCoordinate = view * conePosition;\\n cameraCoordinate.xyz /= cameraCoordinate.w;\\n f_lightDirection = lightPosition - cameraCoordinate.xyz;\\n f_eyeDirection = eyePosition - cameraCoordinate.xyz;\\n f_normal = normalize((vec4(normal, 0.0) * inverseModel).xyz);\\n\\n // vec4 m_position = model * vec4(conePosition, 1.0);\\n vec4 t_position = view * conePosition;\\n gl_Position = projection * t_position;\\n\\n f_color = color;\\n f_data = conePosition.xyz;\\n f_position = position.xyz;\\n f_uv = uv;\\n}\\n\"]),a=n([\"#extension GL_OES_standard_derivatives : enable\\n\\nprecision highp float;\\n#define GLSLIFY 1\\n\\nfloat beckmannDistribution(float x, float roughness) {\\n float NdotH = max(x, 0.0001);\\n float cos2Alpha = NdotH * NdotH;\\n float tan2Alpha = (cos2Alpha - 1.0) / cos2Alpha;\\n float roughness2 = roughness * roughness;\\n float denom = 3.141592653589793 * roughness2 * cos2Alpha * cos2Alpha;\\n return exp(tan2Alpha / roughness2) / denom;\\n}\\n\\nfloat cookTorranceSpecular(\\n vec3 lightDirection,\\n vec3 viewDirection,\\n vec3 surfaceNormal,\\n float roughness,\\n float fresnel) {\\n\\n float VdotN = max(dot(viewDirection, surfaceNormal), 0.0);\\n float LdotN = max(dot(lightDirection, surfaceNormal), 0.0);\\n\\n //Half angle vector\\n vec3 H = normalize(lightDirection + viewDirection);\\n\\n //Geometric term\\n float NdotH = max(dot(surfaceNormal, H), 0.0);\\n float VdotH = max(dot(viewDirection, H), 0.000001);\\n float LdotH = max(dot(lightDirection, H), 0.000001);\\n float G1 = (2.0 * NdotH * VdotN) / VdotH;\\n float G2 = (2.0 * NdotH * LdotN) / LdotH;\\n float G = min(1.0, min(G1, G2));\\n \\n //Distribution term\\n float D = beckmannDistribution(NdotH, roughness);\\n\\n //Fresnel term\\n float F = pow(1.0 - VdotN, fresnel);\\n\\n //Multiply terms and done\\n return G * F * D / max(3.14159265 * VdotN, 0.000001);\\n}\\n\\nbool outOfRange(float a, float b, float p) {\\n return ((p > max(a, b)) || \\n (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n return (outOfRange(a.x, b.x, p.x) ||\\n outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n return (outOfRange(a.x, b.x, p.x) ||\\n outOfRange(a.y, b.y, p.y) ||\\n outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nuniform vec3 clipBounds[2];\\nuniform float roughness, fresnel, kambient, kdiffuse, kspecular, opacity;\\nuniform sampler2D texture;\\n\\nvarying vec3 f_normal, f_lightDirection, f_eyeDirection, f_data, f_position;\\nvarying vec4 f_color;\\nvarying vec2 f_uv;\\n\\nvoid main() {\\n if (outOfRange(clipBounds[0], clipBounds[1], f_position)) discard;\\n vec3 N = normalize(f_normal);\\n vec3 L = normalize(f_lightDirection);\\n vec3 V = normalize(f_eyeDirection);\\n\\n if(gl_FrontFacing) {\\n N = -N;\\n }\\n\\n float specular = min(1.0, max(0.0, cookTorranceSpecular(L, V, N, roughness, fresnel)));\\n float diffuse = min(kambient + kdiffuse * max(dot(N, L), 0.0), 1.0);\\n\\n vec4 surfaceColor = f_color * texture2D(texture, f_uv);\\n vec4 litColor = surfaceColor.a * vec4(diffuse * surfaceColor.rgb + kspecular * vec3(1,1,1) * specular, 1.0);\\n\\n gl_FragColor = litColor * opacity;\\n}\\n\"]),o=n([\"precision highp float;\\n\\nprecision highp float;\\n#define GLSLIFY 1\\n\\nvec3 getOrthogonalVector(vec3 v) {\\n // Return up-vector for only-z vector.\\n // Return ax + by + cz = 0, a point that lies on the plane that has v as a normal and that isn't (0,0,0).\\n // From the above if-statement we have ||a|| > 0 U ||b|| > 0.\\n // Assign z = 0, x = -b, y = a:\\n // a*-b + b*a + c*0 = -ba + ba + 0 = 0\\n if (v.x*v.x > v.z*v.z || v.y*v.y > v.z*v.z) {\\n return normalize(vec3(-v.y, v.x, 0.0));\\n } else {\\n return normalize(vec3(0.0, v.z, -v.y));\\n }\\n}\\n\\n// Calculate the cone vertex and normal at the given index.\\n//\\n// The returned vertex is for a cone with its top at origin and height of 1.0,\\n// pointing in the direction of the vector attribute.\\n//\\n// Each cone is made up of a top vertex, a center base vertex and base perimeter vertices.\\n// These vertices are used to make up the triangles of the cone by the following:\\n// segment + 0 top vertex\\n// segment + 1 perimeter vertex a+1\\n// segment + 2 perimeter vertex a\\n// segment + 3 center base vertex\\n// segment + 4 perimeter vertex a\\n// segment + 5 perimeter vertex a+1\\n// Where segment is the number of the radial segment * 6 and a is the angle at that radial segment.\\n// To go from index to segment, floor(index / 6)\\n// To go from segment to angle, 2*pi * (segment/segmentCount)\\n// To go from index to segment index, index - (segment*6)\\n//\\nvec3 getConePosition(vec3 d, float rawIndex, float coneOffset, out vec3 normal) {\\n\\n const float segmentCount = 8.0;\\n\\n float index = rawIndex - floor(rawIndex /\\n (segmentCount * 6.0)) *\\n (segmentCount * 6.0);\\n\\n float segment = floor(0.001 + index/6.0);\\n float segmentIndex = index - (segment*6.0);\\n\\n normal = -normalize(d);\\n\\n if (segmentIndex > 2.99 && segmentIndex < 3.01) {\\n return mix(vec3(0.0), -d, coneOffset);\\n }\\n\\n float nextAngle = (\\n (segmentIndex > 0.99 && segmentIndex < 1.01) ||\\n (segmentIndex > 4.99 && segmentIndex < 5.01)\\n ) ? 1.0 : 0.0;\\n float angle = 2.0 * 3.14159 * ((segment + nextAngle) / segmentCount);\\n\\n vec3 v1 = mix(d, vec3(0.0), coneOffset);\\n vec3 v2 = v1 - d;\\n\\n vec3 u = getOrthogonalVector(d);\\n vec3 v = normalize(cross(u, d));\\n\\n vec3 x = u * cos(angle) * length(d)*0.25;\\n vec3 y = v * sin(angle) * length(d)*0.25;\\n vec3 v3 = v2 + x + y;\\n if (segmentIndex < 3.0) {\\n vec3 tx = u * sin(angle);\\n vec3 ty = v * -cos(angle);\\n vec3 tangent = tx + ty;\\n normal = normalize(cross(v3 - v1, tangent));\\n }\\n\\n if (segmentIndex == 0.0) {\\n return mix(d, vec3(0.0), coneOffset);\\n }\\n return v3;\\n}\\n\\nattribute vec4 vector;\\nattribute vec4 position;\\nattribute vec4 id;\\n\\nuniform mat4 model, view, projection;\\nuniform float vectorScale, coneScale, coneOffset;\\n\\nvarying vec3 f_position;\\nvarying vec4 f_id;\\n\\nvoid main() {\\n vec3 normal;\\n vec3 XYZ = getConePosition(mat3(model) * ((vectorScale * coneScale) * vector.xyz), position.w, coneOffset, normal);\\n vec4 conePosition = model * vec4(position.xyz, 1.0) + vec4(XYZ, 0.0);\\n gl_Position = projection * view * conePosition;\\n f_id = id;\\n f_position = position.xyz;\\n}\\n\"]),s=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nbool outOfRange(float a, float b, float p) {\\n return ((p > max(a, b)) || \\n (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n return (outOfRange(a.x, b.x, p.x) ||\\n outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n return (outOfRange(a.x, b.x, p.x) ||\\n outOfRange(a.y, b.y, p.y) ||\\n outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nuniform vec3 clipBounds[2];\\nuniform float pickId;\\n\\nvarying vec3 f_position;\\nvarying vec4 f_id;\\n\\nvoid main() {\\n if (outOfRange(clipBounds[0], clipBounds[1], f_position)) discard;\\n\\n gl_FragColor = vec4(pickId, 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y=r.getExtension(\"WEBGL_depth_texture\");y?d?t.depth=h(r,i,a,y.UNSIGNED_INT_24_8_WEBGL,r.DEPTH_STENCIL,r.DEPTH_STENCIL_ATTACHMENT):m&&(t.depth=h(r,i,a,r.UNSIGNED_SHORT,r.DEPTH_COMPONENT,r.DEPTH_ATTACHMENT)):m&&d?t._depth_rb=p(r,i,a,r.DEPTH_STENCIL,r.DEPTH_STENCIL_ATTACHMENT):m?t._depth_rb=p(r,i,a,r.DEPTH_COMPONENT16,r.DEPTH_ATTACHMENT):d&&(t._depth_rb=p(r,i,a,r.STENCIL_INDEX,r.STENCIL_ATTACHMENT));var x=r.checkFramebufferStatus(r.FRAMEBUFFER);if(x!==r.FRAMEBUFFER_COMPLETE){t._destroyed=!0,r.bindFramebuffer(r.FRAMEBUFFER,null),r.deleteFramebuffer(t.handle),t.handle=null,t.depth&&(t.depth.dispose(),t.depth=null),t._depth_rb&&(r.deleteRenderbuffer(t._depth_rb),t._depth_rb=null);for(v=0;v<t.color.length;++v)t.color[v].dispose(),t.color[v]=null;t._color_rb&&(r.deleteRenderbuffer(t._color_rb),t._color_rb=null),u(r,e),f(x)}u(r,e)}(this)}var m=d.prototype;function g(t,e,r){if(t._destroyed)throw new Error(\"gl-fbo: Can't resize destroyed FBO\");if(t._shape[0]!==e||t._shape[1]!==r){var n=t.gl,i=n.getParameter(n.MAX_RENDERBUFFER_SIZE);if(e<0||e>i||r<0||r>i)throw new Error(\"gl-fbo: Can't resize FBO, invalid dimensions\");t._shape[0]=e,t._shape[1]=r;for(var a=c(n),o=0;o<t.color.length;++o)t.color[o].shape=t._shape;t._color_rb&&(n.bindRenderbuffer(n.RENDERBUFFER,t._color_rb),n.renderbufferStorage(n.RENDERBUFFER,n.RGBA4,t._shape[0],t._shape[1])),t.depth&&(t.depth.shape=t._shape),t._depth_rb&&(n.bindRenderbuffer(n.RENDERBUFFER,t._depth_rb),t._useDepth&&t._useStencil?n.renderbufferStorage(n.RENDERBUFFER,n.DEPTH_STENCIL,t._shape[0],t._shape[1]):t._useDepth?n.renderbufferStorage(n.RENDERBUFFER,n.DEPTH_COMPONENT16,t._shape[0],t._shape[1]):t._useStencil&&n.renderbufferStorage(n.RENDERBUFFER,n.STENCIL_INDEX,t._shape[0],t._shape[1])),n.bindFramebuffer(n.FRAMEBUFFER,t.handle);var s=n.checkFramebufferStatus(n.FRAMEBUFFER);s!==n.FRAMEBUFFER_COMPLETE&&(t.dispose(),u(n,a),f(s)),u(n,a)}}Object.defineProperties(m,{shape:{get:function(){return this._destroyed?[0,0]:this._shapeVector},set:function(t){if(Array.isArray(t)||(t=[0|t,0|t]),2!==t.length)throw new Error(\"gl-fbo: Shape vector must be length 2\");var e=0|t[0],r=0|t[1];return g(this,e,r),[e,r]},enumerable:!1},width:{get:function(){return this._destroyed?0:this._shape[0]},set:function(t){return g(this,t|=0,this._shape[1]),t},enumerable:!1},height:{get:function(){return this._destroyed?0:this._shape[1]},set:function(t){return t|=0,g(this,this._shape[0],t),t},enumerable:!1}}),m.bind=function(){if(!this._destroyed){var t=this.gl;t.bindFramebuffer(t.FRAMEBUFFER,this.handle),t.viewport(0,0,this._shape[0],this._shape[1])}},m.dispose=function(){if(!this._destroyed){this._destroyed=!0;var t=this.gl;t.deleteFramebuffer(this.handle),this.handle=null,this.depth&&(this.depth.dispose(),this.depth=null),this._depth_rb&&(t.deleteRenderbuffer(this._depth_rb),this._depth_rb=null);for(var e=0;e<this.color.length;++e)this.color[e].dispose(),this.color[e]=null;this._color_rb&&(t.deleteRenderbuffer(this._color_rb),this._color_rb=null)}}},{\"gl-texture2d\":146}],87:[function(t,e,r){var n=t(\"sprintf-js\").sprintf,i=t(\"gl-constants/lookup\"),a=t(\"glsl-shader-name\"),o=t(\"add-line-numbers\");e.exports=function(t,e,r){\"use strict\";var s=a(e)||\"of unknown name (see npm glsl-shader-name)\",l=\"unknown type\";void 0!==r&&(l=r===i.FRAGMENT_SHADER?\"fragment\":\"vertex\");for(var c=n(\"Error compiling %s shader %s:\\n\",l,s),u=n(\"%s%s\",c,t),f=t.split(\"\\n\"),h={},p=0;p<f.length;p++){var d=f[p];if(\"\"!==d&&\"\\0\"!==d){var m=parseInt(d.split(\":\")[2]);if(isNaN(m))throw new Error(n(\"Could not parse error: %s\",d));h[m]=d}}var g=o(e).split(\"\\n\");for(p=0;p<g.length;p++)if(h[p+3]||h[p+2]||h[p+1]){var v=g[p];if(c+=v+\"\\n\",h[p+1]){var y=h[p+1];y=y.substr(y.split(\":\",3).join(\":\").length+1).trim(),c+=n(\"^^^ %s\\n\\n\",y)}}return{long:c.trim(),short:u.trim()}}},{\"add-line-numbers\":9,\"gl-constants/lookup\":83,\"glsl-shader-name\":223,\"sprintf-js\":301}],88:[function(t,e,r){\"use strict\";e.exports=function(t,e){var r=t.gl,n=o(r,l.vertex,l.fragment),i=o(r,l.pickVertex,l.pickFragment),a=s(r),u=s(r),f=s(r),h=s(r),p=new c(t,n,i,a,u,f,h);return p.update(e),t.addObject(p),p};var n=t(\"binary-search-bounds\"),i=t(\"iota-array\"),a=t(\"typedarray-pool\"),o=t(\"gl-shader\"),s=t(\"gl-buffer\"),l=t(\"./lib/shaders\");function c(t,e,r,n,i,a,o){this.plot=t,this.shader=e,this.pickShader=r,this.positionBuffer=n,this.weightBuffer=i,this.colorBuffer=a,this.idBuffer=o,this.xData=[],this.yData=[],this.shape=[0,0],this.bounds=[1/0,1/0,-1/0,-1/0],this.pickOffset=0}var u,f=c.prototype,h=[0,0,1,0,0,1,1,0,1,1,0,1];f.draw=(u=[1,0,0,0,1,0,0,0,1],function(){var t=this.plot,e=this.shader,r=this.bounds,n=this.numVertices;if(!(n<=0)){var i=t.gl,a=t.dataBox,o=r[2]-r[0],s=r[3]-r[1],l=a[2]-a[0],c=a[3]-a[1];u[0]=2*o/l,u[4]=2*s/c,u[6]=2*(r[0]-a[0])/l-1,u[7]=2*(r[1]-a[1])/c-1,e.bind();var f=e.uniforms;f.viewTransform=u,f.shape=this.shape;var h=e.attributes;this.positionBuffer.bind(),h.position.pointer(),this.weightBuffer.bind(),h.weight.pointer(i.UNSIGNED_BYTE,!1),this.colorBuffer.bind(),h.color.pointer(i.UNSIGNED_BYTE,!0),i.drawArrays(i.TRIANGLES,0,n)}}),f.drawPick=function(){var t=[1,0,0,0,1,0,0,0,1],e=[0,0,0,0];return function(r){var n=this.plot,i=this.pickShader,a=this.bounds,o=this.numVertices;if(!(o<=0)){var s=n.gl,l=n.dataBox,c=a[2]-a[0],u=a[3]-a[1],f=l[2]-l[0],h=l[3]-l[1];t[0]=2*c/f,t[4]=2*u/h,t[6]=2*(a[0]-l[0])/f-1,t[7]=2*(a[1]-l[1])/h-1;for(var p=0;p<4;++p)e[p]=r>>8*p&255;this.pickOffset=r,i.bind();var d=i.uniforms;d.viewTransform=t,d.pickOffset=e,d.shape=this.shape;var m=i.attributes;return this.positionBuffer.bind(),m.position.pointer(),this.weightBuffer.bind(),m.weight.pointer(s.UNSIGNED_BYTE,!1),this.idBuffer.bind(),m.pickId.pointer(s.UNSIGNED_BYTE,!1),s.drawArrays(s.TRIANGLES,0,o),r+this.shape[0]*this.shape[1]}}}(),f.pick=function(t,e,r){var n=this.pickOffset,i=this.shape[0]*this.shape[1];if(r<n||r>=n+i)return null;var a=r-n,o=this.xData,s=this.yData;return{object:this,pointId:a,dataCoord:[o[a%this.shape[0]],s[a/this.shape[0]|0]]}},f.update=function(t){var e=(t=t||{}).shape||[0,0],r=t.x||i(e[0]),o=t.y||i(e[1]),s=t.z||new Float32Array(e[0]*e[1]),l=!1!==t.zsmooth;this.xData=r,this.yData=o;var c,u,f,p,d=t.colorLevels||[0],m=t.colorValues||[0,0,0,1],g=d.length,v=this.bounds;l?(c=v[0]=r[0],u=v[1]=o[0],f=v[2]=r[r.length-1],p=v[3]=o[o.length-1]):(c=v[0]=r[0]+(r[1]-r[0])/2,u=v[1]=o[0]+(o[1]-o[0])/2,f=v[2]=r[r.length-1]+(r[r.length-1]-r[r.length-2])/2,p=v[3]=o[o.length-1]+(o[o.length-1]-o[o.length-2])/2);var y=1/(f-c),x=1/(p-u),b=e[0],_=e[1];this.shape=[b,_];var w=(l?(b-1)*(_-1):b*_)*(h.length>>>1);this.numVertices=w;for(var T=a.mallocUint8(4*w),k=a.mallocFloat32(2*w),A=a.mallocUint8(2*w),M=a.mallocUint32(w),S=0,E=l?b-1:b,L=l?_-1:_,C=0;C<L;++C){var P,I;l?(P=x*(o[C]-u),I=x*(o[C+1]-u)):(P=C<_-1?x*(o[C]-(o[C+1]-o[C])/2-u):x*(o[C]-(o[C]-o[C-1])/2-u),I=C<_-1?x*(o[C]+(o[C+1]-o[C])/2-u):x*(o[C]+(o[C]-o[C-1])/2-u));for(var O=0;O<E;++O){var z,D;l?(z=y*(r[O]-c),D=y*(r[O+1]-c)):(z=O<b-1?y*(r[O]-(r[O+1]-r[O])/2-c):y*(r[O]-(r[O]-r[O-1])/2-c),D=O<b-1?y*(r[O]+(r[O+1]-r[O])/2-c):y*(r[O]+(r[O]-r[O-1])/2-c));for(var R=0;R<h.length;R+=2){var F,B,N,j,U=h[R],V=h[R+1],H=s[l?(C+V)*b+(O+U):C*b+O],q=n.le(d,H);if(q<0)F=m[0],B=m[1],N=m[2],j=m[3];else if(q===g-1)F=m[4*g-4],B=m[4*g-3],N=m[4*g-2],j=m[4*g-1];else{var G=(H-d[q])/(d[q+1]-d[q]),Y=1-G,W=4*q,X=4*(q+1);F=Y*m[W]+G*m[X],B=Y*m[W+1]+G*m[X+1],N=Y*m[W+2]+G*m[X+2],j=Y*m[W+3]+G*m[X+3]}T[4*S]=255*F,T[4*S+1]=255*B,T[4*S+2]=255*N,T[4*S+3]=255*j,k[2*S]=.5*z+.5*D,k[2*S+1]=.5*P+.5*I,A[2*S]=U,A[2*S+1]=V,M[S]=C*b+O,S+=1}}}this.positionBuffer.update(k),this.weightBuffer.update(A),this.colorBuffer.update(T),this.idBuffer.update(M),a.free(k),a.free(T),a.free(A),a.free(M)},f.dispose=function(){this.shader.dispose(),this.pickShader.dispose(),this.positionBuffer.dispose(),this.weightBuffer.dispose(),this.colorBuffer.dispose(),this.idBuffer.dispose(),this.plot.removeObject(this)}},{\"./lib/shaders\":89,\"binary-search-bounds\":31,\"gl-buffer\":78,\"gl-shader\":132,\"iota-array\":235,\"typedarray-pool\":308}],89:[function(t,e,r){\"use strict\";var n=t(\"glslify\");e.exports={fragment:n([\"precision lowp float;\\n#define GLSLIFY 1\\nvarying vec4 fragColor;\\nvoid main() {\\n gl_FragColor = vec4(fragColor.rgb * fragColor.a, fragColor.a);\\n}\\n\"]),vertex:n([\"precision mediump float;\\n#define GLSLIFY 1\\n\\nattribute vec2 position;\\nattribute vec4 color;\\nattribute vec2 weight;\\n\\nuniform vec2 shape;\\nuniform mat3 viewTransform;\\n\\nvarying vec4 fragColor;\\n\\nvoid main() {\\n vec3 vPosition = viewTransform * vec3( position + (weight-.5)/(shape-1.) , 1.0);\\n fragColor = color;\\n gl_Position = vec4(vPosition.xy, 0, vPosition.z);\\n}\\n\"]),pickFragment:n([\"precision mediump float;\\n#define GLSLIFY 1\\n\\nvarying vec4 fragId;\\nvarying vec2 vWeight;\\n\\nuniform vec2 shape;\\nuniform vec4 pickOffset;\\n\\nvoid main() {\\n vec2 d = step(.5, vWeight);\\n vec4 id = fragId + pickOffset;\\n id.x += d.x + d.y*shape.x;\\n\\n id.y += floor(id.x / 256.0);\\n id.x -= floor(id.x / 256.0) * 256.0;\\n\\n id.z += floor(id.y / 256.0);\\n id.y -= floor(id.y / 256.0) * 256.0;\\n\\n id.w += floor(id.z / 256.0);\\n id.z -= floor(id.z / 256.0) * 256.0;\\n\\n gl_FragColor = id/255.;\\n}\\n\"]),pickVertex:n([\"precision mediump float;\\n#define GLSLIFY 1\\n\\nattribute vec2 position;\\nattribute vec4 pickId;\\nattribute vec2 weight;\\n\\nuniform vec2 shape;\\nuniform mat3 viewTransform;\\n\\nvarying vec4 fragId;\\nvarying vec2 vWeight;\\n\\nvoid main() {\\n vWeight = weight;\\n\\n fragId = pickId;\\n\\n vec3 vPosition = viewTransform * vec3( position + (weight-.5)/(shape-1.) , 1.0);\\n gl_Position = vec4(vPosition.xy, 0, vPosition.z);\\n}\\n\"])}},{glslify:231}],90:[function(t,e,r){var n=t(\"glslify\"),i=t(\"gl-shader\"),a=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nattribute vec3 position, nextPosition;\\nattribute float arcLength, lineWidth;\\nattribute vec4 color;\\n\\nuniform vec2 screenShape;\\nuniform float pixelRatio;\\nuniform mat4 model, view, projection;\\n\\nvarying vec4 fragColor;\\nvarying vec3 worldPosition;\\nvarying float pixelArcLength;\\n\\nvec4 project(vec3 p) {\\n return projection * view * model * vec4(p, 1.0);\\n}\\n\\nvoid main() {\\n vec4 startPoint = project(position);\\n vec4 endPoint = project(nextPosition);\\n\\n vec2 A = startPoint.xy / startPoint.w;\\n vec2 B = endPoint.xy / endPoint.w;\\n\\n float clipAngle = atan(\\n (B.y - A.y) * screenShape.y,\\n (B.x - A.x) * screenShape.x\\n );\\n\\n vec2 offset = 0.5 * pixelRatio * lineWidth * vec2(\\n sin(clipAngle),\\n -cos(clipAngle)\\n ) / screenShape;\\n\\n gl_Position = vec4(startPoint.xy + startPoint.w * offset, startPoint.zw);\\n\\n worldPosition = position;\\n pixelArcLength = arcLength;\\n fragColor = color;\\n}\\n\"]),o=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nbool outOfRange(float a, float b, float p) {\\n return ((p > max(a, b)) || \\n (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n return (outOfRange(a.x, b.x, p.x) ||\\n outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n return (outOfRange(a.x, b.x, p.x) ||\\n outOfRange(a.y, b.y, p.y) ||\\n outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nuniform vec3 clipBounds[2];\\nuniform sampler2D dashTexture;\\nuniform float dashScale;\\nuniform float opacity;\\n\\nvarying vec3 worldPosition;\\nvarying float pixelArcLength;\\nvarying vec4 fragColor;\\n\\nvoid main() {\\n if (\\n outOfRange(clipBounds[0], clipBounds[1], worldPosition) ||\\n fragColor.a * opacity == 0.\\n ) discard;\\n\\n float dashWeight = texture2D(dashTexture, vec2(dashScale * pixelArcLength, 0)).r;\\n if(dashWeight < 0.5) {\\n discard;\\n }\\n gl_FragColor = fragColor * opacity;\\n}\\n\"]),s=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\n#define FLOAT_MAX 1.70141184e38\\n#define FLOAT_MIN 1.17549435e-38\\n\\n// https://github.com/mikolalysenko/glsl-read-float/blob/master/index.glsl\\nvec4 packFloat(float v) {\\n float av = abs(v);\\n\\n //Handle special cases\\n if(av < FLOAT_MIN) {\\n return vec4(0.0, 0.0, 0.0, 0.0);\\n } else if(v > FLOAT_MAX) {\\n return vec4(127.0, 128.0, 0.0, 0.0) / 255.0;\\n } else if(v < -FLOAT_MAX) {\\n return vec4(255.0, 128.0, 0.0, 0.0) / 255.0;\\n }\\n\\n vec4 c = vec4(0,0,0,0);\\n\\n //Compute exponent and mantissa\\n float e = floor(log2(av));\\n float m = av * pow(2.0, -e) - 1.0;\\n\\n //Unpack mantissa\\n c[1] = floor(128.0 * m);\\n m -= c[1] / 128.0;\\n c[2] = floor(32768.0 * m);\\n m -= c[2] / 32768.0;\\n c[3] = floor(8388608.0 * m);\\n\\n //Unpack exponent\\n float ebias = e + 127.0;\\n c[0] = floor(ebias / 2.0);\\n ebias -= c[0] * 2.0;\\n c[1] += floor(ebias) * 128.0;\\n\\n //Unpack sign bit\\n c[0] += 128.0 * step(0.0, -v);\\n\\n //Scale back to range\\n return c / 255.0;\\n}\\n\\nbool outOfRange(float a, float b, float p) {\\n return ((p > max(a, b)) || \\n (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n return (outOfRange(a.x, b.x, p.x) ||\\n outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n return (outOfRange(a.x, b.x, p.x) ||\\n outOfRange(a.y, b.y, p.y) ||\\n outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nuniform float pickId;\\nuniform vec3 clipBounds[2];\\n\\nvarying vec3 worldPosition;\\nvarying float pixelArcLength;\\nvarying vec4 fragColor;\\n\\nvoid main() {\\n if (outOfRange(clipBounds[0], clipBounds[1], worldPosition)) discard;\\n\\n gl_FragColor = vec4(pickId/255.0, packFloat(pixelArcLength).xyz);\\n}\"]),l=[{name:\"position\",type:\"vec3\"},{name:\"nextPosition\",type:\"vec3\"},{name:\"arcLength\",type:\"float\"},{name:\"lineWidth\",type:\"float\"},{name:\"color\",type:\"vec4\"}];r.createShader=function(t){return i(t,a,o,null,l)},r.createPickShader=function(t){return i(t,a,s,null,l)}},{\"gl-shader\":132,glslify:231}],91:[function(t,e,r){\"use strict\";e.exports=function(t){var e=t.gl||t.scene&&t.scene.gl,r=f(e);r.attributes.position.location=0,r.attributes.nextPosition.location=1,r.attributes.arcLength.location=2,r.attributes.lineWidth.location=3,r.attributes.color.location=4;var o=h(e);o.attributes.position.location=0,o.attributes.nextPosition.location=1,o.attributes.arcLength.location=2,o.attributes.lineWidth.location=3,o.attributes.color.location=4;for(var s=n(e),l=i(e,[{buffer:s,size:3,offset:0,stride:48},{buffer:s,size:3,offset:12,stride:48},{buffer:s,size:1,offset:24,stride:48},{buffer:s,size:1,offset:28,stride:48},{buffer:s,size:4,offset:32,stride:48}]),u=c(new Array(1024),[256,1,4]),p=0;p<1024;++p)u.data[p]=255;var d=a(e,u);d.wrap=e.REPEAT;var m=new v(e,r,o,s,l,d);return m.update(t),m};var n=t(\"gl-buffer\"),i=t(\"gl-vao\"),a=t(\"gl-texture2d\"),o=new Uint8Array(4),s=new Float32Array(o.buffer);var l=t(\"binary-search-bounds\"),c=t(\"ndarray\"),u=t(\"./lib/shaders\"),f=u.createShader,h=u.createPickShader,p=[1,0,0,0,0,1,0,0,0,0,1,0,0,0,0,1];function d(t,e){for(var r=0,n=0;n<3;++n){var i=t[n]-e[n];r+=i*i}return Math.sqrt(r)}function m(t){for(var e=[[-1e6,-1e6,-1e6],[1e6,1e6,1e6]],r=0;r<3;++r)e[0][r]=Math.max(t[0][r],e[0][r]),e[1][r]=Math.min(t[1][r],e[1][r]);return e}function g(t,e,r,n){this.arcLength=t,this.position=e,this.index=r,this.dataCoordinate=n}function v(t,e,r,n,i,a){this.gl=t,this.shader=e,this.pickShader=r,this.buffer=n,this.vao=i,this.clipBounds=[[-1/0,-1/0,-1/0],[1/0,1/0,1/0]],this.points=[],this.arcLength=[],this.vertexCount=0,this.bounds=[[0,0,0],[0,0,0]],this.pickId=0,this.lineWidth=1,this.texture=a,this.dashScale=1,this.opacity=1,this.hasAlpha=!1,this.dirty=!0,this.pixelRatio=1}var y=v.prototype;y.isTransparent=function(){return this.hasAlpha},y.isOpaque=function(){return!this.hasAlpha},y.pickSlots=1,y.setPickBase=function(t){this.pickId=t},y.drawTransparent=y.draw=function(t){if(this.vertexCount){var e=this.gl,r=this.shader,n=this.vao;r.bind(),r.uniforms={model:t.model||p,view:t.view||p,projection:t.projection||p,clipBounds:m(this.clipBounds),dashTexture:this.texture.bind(),dashScale:this.dashScale/this.arcLength[this.arcLength.length-1],opacity:this.opacity,screenShape:[e.drawingBufferWidth,e.drawingBufferHeight],pixelRatio:this.pixelRatio},n.bind(),n.draw(e.TRIANGLE_STRIP,this.vertexCount),n.unbind()}},y.drawPick=function(t){if(this.vertexCount){var e=this.gl,r=this.pickShader,n=this.vao;r.bind(),r.uniforms={model:t.model||p,view:t.view||p,projection:t.projection||p,pickId:this.pickId,clipBounds:m(this.clipBounds),screenShape:[e.drawingBufferWidth,e.drawingBufferHeight],pixelRatio:this.pixelRatio},n.bind(),n.draw(e.TRIANGLE_STRIP,this.vertexCount),n.unbind()}},y.update=function(t){var e,r;this.dirty=!0;var n=!!t.connectGaps;\"dashScale\"in t&&(this.dashScale=t.dashScale),this.hasAlpha=!1,\"opacity\"in t&&(this.opacity=+t.opacity,this.opacity<1&&(this.hasAlpha=!0));var 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t[0]=a,t[1]=l,t[2]=f,t[3]=0,t[4]=o,t[5]=c,t[6]=h,t[7]=0,t[8]=s,t[9]=u,t[10]=p,t[11]=0,t[12]=-(a*m+o*g+s*v),t[13]=-(l*m+c*g+u*v),t[14]=-(f*m+h*g+p*v),t[15]=1,t}},{\"./identity\":97}],100:[function(t,e,r){e.exports=function(t,e,r){var n=e[0],i=e[1],a=e[2],o=e[3],s=e[4],l=e[5],c=e[6],u=e[7],f=e[8],h=e[9],p=e[10],d=e[11],m=e[12],g=e[13],v=e[14],y=e[15],x=r[0],b=r[1],_=r[2],w=r[3];return t[0]=x*n+b*s+_*f+w*m,t[1]=x*i+b*l+_*h+w*g,t[2]=x*a+b*c+_*p+w*v,t[3]=x*o+b*u+_*d+w*y,x=r[4],b=r[5],_=r[6],w=r[7],t[4]=x*n+b*s+_*f+w*m,t[5]=x*i+b*l+_*h+w*g,t[6]=x*a+b*c+_*p+w*v,t[7]=x*o+b*u+_*d+w*y,x=r[8],b=r[9],_=r[10],w=r[11],t[8]=x*n+b*s+_*f+w*m,t[9]=x*i+b*l+_*h+w*g,t[10]=x*a+b*c+_*p+w*v,t[11]=x*o+b*u+_*d+w*y,x=r[12],b=r[13],_=r[14],w=r[15],t[12]=x*n+b*s+_*f+w*m,t[13]=x*i+b*l+_*h+w*g,t[14]=x*a+b*c+_*p+w*v,t[15]=x*o+b*u+_*d+w*y,t}},{}],101:[function(t,e,r){e.exports=function(t,e,r,n,i,a,o){var s=1/(e-r),l=1/(n-i),c=1/(a-o);return t[0]=-2*s,t[1]=0,t[2]=0,t[3]=0,t[4]=0,t[5]=-2*l,t[6]=0,t[7]=0,t[8]=0,t[9]=0,t[10]=2*c,t[11]=0,t[12]=(e+r)*s,t[13]=(i+n)*l,t[14]=(o+a)*c,t[15]=1,t}},{}],102:[function(t,e,r){e.exports=function(t,e,r,n,i){var a=1/Math.tan(e/2),o=1/(n-i);return t[0]=a/r,t[1]=0,t[2]=0,t[3]=0,t[4]=0,t[5]=a,t[6]=0,t[7]=0,t[8]=0,t[9]=0,t[10]=(i+n)*o,t[11]=-1,t[12]=0,t[13]=0,t[14]=2*i*n*o,t[15]=0,t}},{}],103:[function(t,e,r){e.exports=function(t,e,r,n){var i,a,o,s,l,c,u,f,h,p,d,m,g,v,y,x,b,_,w,T,k,A,M,S,E=n[0],L=n[1],C=n[2],P=Math.sqrt(E*E+L*L+C*C);if(Math.abs(P)<1e-6)return null;E*=P=1/P,L*=P,C*=P,i=Math.sin(r),a=Math.cos(r),o=1-a,s=e[0],l=e[1],c=e[2],u=e[3],f=e[4],h=e[5],p=e[6],d=e[7],m=e[8],g=e[9],v=e[10],y=e[11],x=E*E*o+a,b=L*E*o+C*i,_=C*E*o-L*i,w=E*L*o-C*i,T=L*L*o+a,k=C*L*o+E*i,A=E*C*o+L*i,M=L*C*o-E*i,S=C*C*o+a,t[0]=s*x+f*b+m*_,t[1]=l*x+h*b+g*_,t[2]=c*x+p*b+v*_,t[3]=u*x+d*b+y*_,t[4]=s*w+f*T+m*k,t[5]=l*w+h*T+g*k,t[6]=c*w+p*T+v*k,t[7]=u*w+d*T+y*k,t[8]=s*A+f*M+m*S,t[9]=l*A+h*M+g*S,t[10]=c*A+p*M+v*S,t[11]=u*A+d*M+y*S,e!==t&&(t[12]=e[12],t[13]=e[13],t[14]=e[14],t[15]=e[15]);return t}},{}],104:[function(t,e,r){e.exports=function(t,e,r){var n=Math.sin(r),i=Math.cos(r),a=e[4],o=e[5],s=e[6],l=e[7],c=e[8],u=e[9],f=e[10],h=e[11];e!==t&&(t[0]=e[0],t[1]=e[1],t[2]=e[2],t[3]=e[3],t[12]=e[12],t[13]=e[13],t[14]=e[14],t[15]=e[15]);return t[4]=a*i+c*n,t[5]=o*i+u*n,t[6]=s*i+f*n,t[7]=l*i+h*n,t[8]=c*i-a*n,t[9]=u*i-o*n,t[10]=f*i-s*n,t[11]=h*i-l*n,t}},{}],105:[function(t,e,r){e.exports=function(t,e,r){var 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null;return[h,s(t,g),g]}},{barycentric:14,\"polytope-closest-point/lib/closest_point_2d.js\":270}],111:[function(t,e,r){var n=t(\"glslify\"),i=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nattribute vec3 position, normal;\\nattribute vec4 color;\\nattribute vec2 uv;\\n\\nuniform mat4 model\\n , view\\n , projection\\n , inverseModel;\\nuniform vec3 eyePosition\\n , lightPosition;\\n\\nvarying vec3 f_normal\\n , f_lightDirection\\n , f_eyeDirection\\n , f_data;\\nvarying vec4 f_color;\\nvarying vec2 f_uv;\\n\\nvec4 project(vec3 p) {\\n return projection * view * model * vec4(p, 1.0);\\n}\\n\\nvoid main() {\\n gl_Position = project(position);\\n\\n //Lighting geometry parameters\\n vec4 cameraCoordinate = view * vec4(position , 1.0);\\n cameraCoordinate.xyz /= cameraCoordinate.w;\\n f_lightDirection = lightPosition - cameraCoordinate.xyz;\\n f_eyeDirection = eyePosition - cameraCoordinate.xyz;\\n f_normal = normalize((vec4(normal, 0.0) * inverseModel).xyz);\\n\\n f_color = color;\\n f_data = position;\\n f_uv = uv;\\n}\\n\"]),a=n([\"#extension GL_OES_standard_derivatives : enable\\n\\nprecision highp float;\\n#define GLSLIFY 1\\n\\nfloat beckmannDistribution(float x, float roughness) {\\n float NdotH = max(x, 0.0001);\\n float cos2Alpha = NdotH * NdotH;\\n float tan2Alpha = (cos2Alpha - 1.0) / cos2Alpha;\\n float roughness2 = roughness * roughness;\\n float denom = 3.141592653589793 * roughness2 * cos2Alpha * cos2Alpha;\\n return exp(tan2Alpha / roughness2) / denom;\\n}\\n\\nfloat cookTorranceSpecular(\\n vec3 lightDirection,\\n vec3 viewDirection,\\n vec3 surfaceNormal,\\n float roughness,\\n float fresnel) {\\n\\n float VdotN = max(dot(viewDirection, surfaceNormal), 0.0);\\n float LdotN = max(dot(lightDirection, surfaceNormal), 0.0);\\n\\n //Half angle vector\\n vec3 H = normalize(lightDirection + viewDirection);\\n\\n //Geometric term\\n float NdotH = max(dot(surfaceNormal, H), 0.0);\\n float VdotH = max(dot(viewDirection, H), 0.000001);\\n float LdotH = max(dot(lightDirection, H), 0.000001);\\n float G1 = (2.0 * NdotH * VdotN) / VdotH;\\n float G2 = (2.0 * NdotH * LdotN) / LdotH;\\n float G = min(1.0, min(G1, G2));\\n \\n //Distribution term\\n float D = beckmannDistribution(NdotH, roughness);\\n\\n //Fresnel term\\n float F = pow(1.0 - VdotN, fresnel);\\n\\n //Multiply terms and done\\n return G * F * D / max(3.14159265 * VdotN, 0.000001);\\n}\\n\\n//#pragma glslify: beckmann = require(glsl-specular-beckmann) // used in gl-surface3d\\n\\nbool outOfRange(float a, float b, float p) {\\n return ((p > max(a, b)) || \\n (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n return (outOfRange(a.x, b.x, p.x) ||\\n outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n return (outOfRange(a.x, b.x, p.x) ||\\n outOfRange(a.y, b.y, p.y) ||\\n outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nuniform vec3 clipBounds[2];\\nuniform float roughness\\n , fresnel\\n , kambient\\n , kdiffuse\\n , kspecular;\\nuniform sampler2D texture;\\n\\nvarying vec3 f_normal\\n , f_lightDirection\\n , f_eyeDirection\\n , f_data;\\nvarying vec4 f_color;\\nvarying vec2 f_uv;\\n\\nvoid main() {\\n if (f_color.a == 0.0 ||\\n outOfRange(clipBounds[0], clipBounds[1], f_data)\\n ) discard;\\n\\n vec3 N = normalize(f_normal);\\n vec3 L = normalize(f_lightDirection);\\n vec3 V = normalize(f_eyeDirection);\\n\\n if(gl_FrontFacing) {\\n N = -N;\\n }\\n\\n float specular = min(1.0, max(0.0, cookTorranceSpecular(L, V, N, roughness, fresnel)));\\n //float specular = max(0.0, beckmann(L, V, N, roughness)); // used in gl-surface3d\\n\\n float diffuse = min(kambient + kdiffuse * max(dot(N, L), 0.0), 1.0);\\n\\n vec4 surfaceColor = vec4(f_color.rgb, 1.0) * texture2D(texture, f_uv);\\n vec4 litColor = surfaceColor.a * vec4(diffuse * surfaceColor.rgb + kspecular * vec3(1,1,1) * specular, 1.0);\\n\\n gl_FragColor = litColor * f_color.a;\\n}\\n\"]),o=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nattribute vec3 position;\\nattribute vec4 color;\\nattribute vec2 uv;\\n\\nuniform mat4 model, view, projection;\\n\\nvarying vec4 f_color;\\nvarying vec3 f_data;\\nvarying vec2 f_uv;\\n\\nvoid main() {\\n gl_Position = projection * view * model * vec4(position, 1.0);\\n f_color = color;\\n f_data = position;\\n f_uv = uv;\\n}\"]),s=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nbool outOfRange(float a, float b, float p) {\\n return ((p > max(a, b)) || \\n (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n return (outOfRange(a.x, b.x, p.x) ||\\n outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n return (outOfRange(a.x, b.x, p.x) ||\\n outOfRange(a.y, b.y, p.y) ||\\n outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nuniform vec3 clipBounds[2];\\nuniform sampler2D texture;\\nuniform float opacity;\\n\\nvarying vec4 f_color;\\nvarying vec3 f_data;\\nvarying vec2 f_uv;\\n\\nvoid main() {\\n if (outOfRange(clipBounds[0], clipBounds[1], f_data)) discard;\\n\\n gl_FragColor = f_color * texture2D(texture, f_uv) * opacity;\\n}\"]),l=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nbool outOfRange(float a, float b, float p) {\\n return ((p > max(a, b)) || \\n (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n return (outOfRange(a.x, b.x, p.x) ||\\n outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n return (outOfRange(a.x, b.x, p.x) ||\\n outOfRange(a.y, b.y, p.y) ||\\n outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nattribute vec3 position;\\nattribute vec4 color;\\nattribute vec2 uv;\\nattribute float pointSize;\\n\\nuniform mat4 model, view, projection;\\nuniform vec3 clipBounds[2];\\n\\nvarying vec4 f_color;\\nvarying vec2 f_uv;\\n\\nvoid main() {\\n if (outOfRange(clipBounds[0], clipBounds[1], position)) {\\n\\n gl_Position = vec4(0.0, 0.0 ,0.0 ,0.0);\\n } else {\\n gl_Position = projection * view * model * vec4(position, 1.0);\\n }\\n gl_PointSize = pointSize;\\n f_color = color;\\n f_uv = uv;\\n}\"]),c=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nuniform sampler2D texture;\\nuniform float opacity;\\n\\nvarying vec4 f_color;\\nvarying vec2 f_uv;\\n\\nvoid main() {\\n vec2 pointR = gl_PointCoord.xy - vec2(0.5, 0.5);\\n if(dot(pointR, pointR) > 0.25) {\\n discard;\\n }\\n gl_FragColor = f_color * texture2D(texture, f_uv) * opacity;\\n}\"]),u=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nattribute vec3 position;\\nattribute vec4 id;\\n\\nuniform mat4 model, view, projection;\\n\\nvarying vec3 f_position;\\nvarying vec4 f_id;\\n\\nvoid main() {\\n gl_Position = projection * view * model * vec4(position, 1.0);\\n f_id = id;\\n f_position = position;\\n}\"]),f=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nbool outOfRange(float a, float b, float p) {\\n return ((p > max(a, b)) || \\n (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n return (outOfRange(a.x, b.x, p.x) ||\\n outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n return (outOfRange(a.x, b.x, p.x) ||\\n outOfRange(a.y, b.y, p.y) ||\\n outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nuniform vec3 clipBounds[2];\\nuniform float pickId;\\n\\nvarying vec3 f_position;\\nvarying vec4 f_id;\\n\\nvoid main() {\\n if (outOfRange(clipBounds[0], clipBounds[1], f_position)) discard;\\n\\n gl_FragColor = vec4(pickId, f_id.xyz);\\n}\"]),h=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nbool outOfRange(float a, float b, float p) {\\n return ((p > max(a, b)) || \\n (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n return (outOfRange(a.x, b.x, p.x) ||\\n outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n return (outOfRange(a.x, b.x, p.x) ||\\n outOfRange(a.y, b.y, p.y) ||\\n outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nattribute vec3 position;\\nattribute float pointSize;\\nattribute vec4 id;\\n\\nuniform mat4 model, view, projection;\\nuniform vec3 clipBounds[2];\\n\\nvarying vec3 f_position;\\nvarying vec4 f_id;\\n\\nvoid main() {\\n if (outOfRange(clipBounds[0], clipBounds[1], position)) {\\n\\n gl_Position = vec4(0.0, 0.0, 0.0, 0.0);\\n } else {\\n gl_Position = projection * view * model * vec4(position, 1.0);\\n gl_PointSize = pointSize;\\n }\\n f_id = id;\\n f_position = position;\\n}\"]),p=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nattribute vec3 position;\\n\\nuniform mat4 model, view, projection;\\n\\nvoid main() {\\n gl_Position = projection * view * model * vec4(position, 1.0);\\n}\"]),d=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nuniform vec3 contourColor;\\n\\nvoid main() {\\n gl_FragColor = vec4(contourColor, 1.0);\\n}\\n\"]);r.meshShader={vertex:i,fragment:a,attributes:[{name:\"position\",type:\"vec3\"},{name:\"normal\",type:\"vec3\"},{name:\"color\",type:\"vec4\"},{name:\"uv\",type:\"vec2\"}]},r.wireShader={vertex:o,fragment:s,attributes:[{name:\"position\",type:\"vec3\"},{name:\"color\",type:\"vec4\"},{name:\"uv\",type:\"vec2\"}]},r.pointShader={vertex:l,fragment:c,attributes:[{name:\"position\",type:\"vec3\"},{name:\"color\",type:\"vec4\"},{name:\"uv\",type:\"vec2\"},{name:\"pointSize\",type:\"float\"}]},r.pickShader={vertex:u,fragment:f,attributes:[{name:\"position\",type:\"vec3\"},{name:\"id\",type:\"vec4\"}]},r.pointPickShader={vertex:h,fragment:f,attributes:[{name:\"position\",type:\"vec3\"},{name:\"pointSize\",type:\"float\"},{name:\"id\",type:\"vec4\"}]},r.contourShader={vertex:p,fragment:d,attributes:[{name:\"position\",type:\"vec3\"}]}},{glslify:231}],112:[function(t,e,r){\"use strict\";var n=t(\"gl-shader\"),i=t(\"gl-buffer\"),a=t(\"gl-vao\"),o=t(\"gl-texture2d\"),s=t(\"normals\"),l=t(\"gl-mat4/multiply\"),c=t(\"gl-mat4/invert\"),u=t(\"ndarray\"),f=t(\"colormap\"),h=t(\"simplicial-complex-contour\"),p=t(\"typedarray-pool\"),d=t(\"./lib/shaders\"),m=t(\"./lib/closest-point\"),g=d.meshShader,v=d.wireShader,y=d.pointShader,x=d.pickShader,b=d.pointPickShader,_=d.contourShader,w=[1,0,0,0,0,1,0,0,0,0,1,0,0,0,0,1];function T(t,e,r,n,i,a,o,s,l,c,u,f,h,p,d,m,g,v,y,x,b,_,T,k,A,M,S){this.gl=t,this.pixelRatio=1,this.cells=[],this.positions=[],this.intensity=[],this.texture=e,this.dirty=!0,this.triShader=r,this.lineShader=n,this.pointShader=i,this.pickShader=a,this.pointPickShader=o,this.contourShader=s,this.trianglePositions=l,this.triangleColors=u,this.triangleNormals=h,this.triangleUVs=f,this.triangleIds=c,this.triangleVAO=p,this.triangleCount=0,this.lineWidth=1,this.edgePositions=d,this.edgeColors=g,this.edgeUVs=v,this.edgeIds=m,this.edgeVAO=y,this.edgeCount=0,this.pointPositions=x,this.pointColors=_,this.pointUVs=T,this.pointSizes=k,this.pointIds=b,this.pointVAO=A,this.pointCount=0,this.contourLineWidth=1,this.contourPositions=M,this.contourVAO=S,this.contourCount=0,this.contourColor=[0,0,0],this.contourEnable=!0,this.pickVertex=!0,this.pickId=1,this.bounds=[[1/0,1/0,1/0],[-1/0,-1/0,-1/0]],this.clipBounds=[[-1/0,-1/0,-1/0],[1/0,1/0,1/0]],this.lightPosition=[1e5,1e5,0],this.ambientLight=.8,this.diffuseLight=.8,this.specularLight=2,this.roughness=.5,this.fresnel=1.5,this.opacity=1,this.hasAlpha=!1,this.opacityscale=!1,this._model=w,this._view=w,this._projection=w,this._resolution=[1,1]}var k=T.prototype;function A(t,e){if(!e)return 1;if(!e.length)return 1;for(var r=0;r<e.length;++r){if(e.length<2)return 1;if(e[r][0]===t)return e[r][1];if(e[r][0]>t&&r>0){var n=(e[r][0]-t)/(e[r][0]-e[r-1][0]);return e[r][1]*(1-n)+n*e[r-1][1]}}return 1}function M(t){var e=n(t,g.vertex,g.fragment);return e.attributes.position.location=0,e.attributes.color.location=2,e.attributes.uv.location=3,e.attributes.normal.location=4,e}function S(t){var e=n(t,v.vertex,v.fragment);return e.attributes.position.location=0,e.attributes.color.location=2,e.attributes.uv.location=3,e}function E(t){var e=n(t,y.vertex,y.fragment);return e.attributes.position.location=0,e.attributes.color.location=2,e.attributes.uv.location=3,e.attributes.pointSize.location=4,e}function L(t){var e=n(t,x.vertex,x.fragment);return e.attributes.position.location=0,e.attributes.id.location=1,e}function C(t){var e=n(t,b.vertex,b.fragment);return e.attributes.position.location=0,e.attributes.id.location=1,e.attributes.pointSize.location=4,e}function P(t){var e=n(t,_.vertex,_.fragment);return e.attributes.position.location=0,e}k.isOpaque=function(){return!this.hasAlpha},k.isTransparent=function(){return this.hasAlpha},k.pickSlots=1,k.setPickBase=function(t){this.pickId=t},k.highlight=function(t){if(t&&this.contourEnable){for(var e=h(this.cells,this.intensity,t.intensity),r=e.cells,n=e.vertexIds,i=e.vertexWeights,a=r.length,o=p.mallocFloat32(6*a),s=0,l=0;l<a;++l)for(var c=r[l],u=0;u<2;++u){var f=c[0];2===c.length&&(f=c[u]);for(var d=n[f][0],m=n[f][1],g=i[f],v=1-g,y=this.positions[d],x=this.positions[m],b=0;b<3;++b)o[s++]=g*y[b]+v*x[b]}this.contourCount=s/3|0,this.contourPositions.update(o.subarray(0,s)),p.free(o)}else this.contourCount=0},k.update=function(t){t=t||{};var e=this.gl;this.dirty=!0,\"contourEnable\"in t&&(this.contourEnable=t.contourEnable),\"contourColor\"in t&&(this.contourColor=t.contourColor),\"lineWidth\"in t&&(this.lineWidth=t.lineWidth),\"lightPosition\"in t&&(this.lightPosition=t.lightPosition),this.hasAlpha=!1,\"opacity\"in t&&(this.opacity=t.opacity,this.opacity<1&&(this.hasAlpha=!0)),\"opacityscale\"in t&&(this.opacityscale=t.opacityscale,this.hasAlpha=!0),\"ambient\"in t&&(this.ambientLight=t.ambient),\"diffuse\"in t&&(this.diffuseLight=t.diffuse),\"specular\"in t&&(this.specularLight=t.specular),\"roughness\"in t&&(this.roughness=t.roughness),\"fresnel\"in t&&(this.fresnel=t.fresnel),t.texture?(this.texture.dispose(),this.texture=o(e,t.texture)):t.colormap&&(this.texture.shape=[256,256],this.texture.minFilter=e.LINEAR_MIPMAP_LINEAR,this.texture.magFilter=e.LINEAR,this.texture.setPixels(function(t,e){for(var r=f({colormap:t,nshades:256,format:\"rgba\"}),n=new Uint8Array(1024),i=0;i<256;++i){for(var a=r[i],o=0;o<3;++o)n[4*i+o]=a[o];n[4*i+3]=e?255*A(i/255,e):255*a[3]}return u(n,[256,256,4],[4,0,1])}(t.colormap,this.opacityscale)),this.texture.generateMipmap());var r=t.cells,n=t.positions;if(n&&r){var i=[],a=[],l=[],c=[],h=[],p=[],d=[],m=[],g=[],v=[],y=[],x=[],b=[],_=[];this.cells=r,this.positions=n;var w=t.vertexNormals,T=t.cellNormals,k=void 0===t.vertexNormalsEpsilon?1e-6:t.vertexNormalsEpsilon,M=void 0===t.faceNormalsEpsilon?1e-6:t.faceNormalsEpsilon;t.useFacetNormals&&!T&&(T=s.faceNormals(r,n,M)),T||w||(w=s.vertexNormals(r,n,k));var S=t.vertexColors,E=t.cellColors,L=t.meshColor||[1,1,1,1],C=t.vertexUVs,P=t.vertexIntensity,I=t.cellUVs,O=t.cellIntensity,z=1/0,D=-1/0;if(!C&&!I)if(P)if(t.vertexIntensityBounds)z=+t.vertexIntensityBounds[0],D=+t.vertexIntensityBounds[1];else for(var R=0;R<P.length;++R){var F=P[R];z=Math.min(z,F),D=Math.max(D,F)}else if(O)if(t.cellIntensityBounds)z=+t.cellIntensityBounds[0],D=+t.cellIntensityBounds[1];else for(R=0;R<O.length;++R){F=O[R];z=Math.min(z,F),D=Math.max(D,F)}else for(R=0;R<n.length;++R){F=n[R][2];z=Math.min(z,F),D=Math.max(D,F)}this.intensity=P||(O||function(t){for(var e=t.length,r=new Array(e),n=0;n<e;++n)r[n]=t[n][2];return r}(n)),this.pickVertex=!(O||E);var B=t.pointSizes,N=t.pointSize||1;this.bounds=[[1/0,1/0,1/0],[-1/0,-1/0,-1/0]];for(R=0;R<n.length;++R)for(var j=n[R],U=0;U<3;++U)!isNaN(j[U])&&isFinite(j[U])&&(this.bounds[0][U]=Math.min(this.bounds[0][U],j[U]),this.bounds[1][U]=Math.max(this.bounds[1][U],j[U]));var V=0,H=0,q=0;t:for(R=0;R<r.length;++R){var G=r[R];switch(G.length){case 1:for(j=n[W=G[0]],U=0;U<3;++U)if(isNaN(j[U])||!isFinite(j[U]))continue t;v.push(j[0],j[1],j[2]),X=S?S[W]:E?E[R]:L,this.opacityscale&&P?a.push(X[0],X[1],X[2],this.opacity*A((P[W]-z)/(D-z),this.opacityscale)):3===X.length?y.push(X[0],X[1],X[2],this.opacity):(y.push(X[0],X[1],X[2],X[3]*this.opacity),X[3]<1&&(this.hasAlpha=!0)),Z=C?C[W]:P?[(P[W]-z)/(D-z),0]:I?I[R]:O?[(O[R]-z)/(D-z),0]:[(j[2]-z)/(D-z),0],x.push(Z[0],Z[1]),B?b.push(B[W]):b.push(N),_.push(R),q+=1;break;case 2:for(U=0;U<2;++U){j=n[W=G[U]];for(var Y=0;Y<3;++Y)if(isNaN(j[Y])||!isFinite(j[Y]))continue t}for(U=0;U<2;++U){j=n[W=G[U]];p.push(j[0],j[1],j[2]),X=S?S[W]:E?E[R]:L,this.opacityscale&&P?a.push(X[0],X[1],X[2],this.opacity*A((P[W]-z)/(D-z),this.opacityscale)):3===X.length?d.push(X[0],X[1],X[2],this.opacity):(d.push(X[0],X[1],X[2],X[3]*this.opacity),X[3]<1&&(this.hasAlpha=!0)),Z=C?C[W]:P?[(P[W]-z)/(D-z),0]:I?I[R]:O?[(O[R]-z)/(D-z),0]:[(j[2]-z)/(D-z),0],m.push(Z[0],Z[1]),g.push(R)}H+=1;break;case 3:for(U=0;U<3;++U)for(j=n[W=G[U]],Y=0;Y<3;++Y)if(isNaN(j[Y])||!isFinite(j[Y]))continue t;for(U=0;U<3;++U){var W,X,Z,J;j=n[W=G[2-U]];i.push(j[0],j[1],j[2]),(X=S?S[W]:E?E[R]:L)?this.opacityscale&&P?a.push(X[0],X[1],X[2],this.opacity*A((P[W]-z)/(D-z),this.opacityscale)):3===X.length?a.push(X[0],X[1],X[2],this.opacity):(a.push(X[0],X[1],X[2],X[3]*this.opacity),X[3]<1&&(this.hasAlpha=!0)):a.push(.5,.5,.5,1),Z=C?C[W]:P?[(P[W]-z)/(D-z),0]:I?I[R]:O?[(O[R]-z)/(D-z),0]:[(j[2]-z)/(D-z),0],c.push(Z[0],Z[1]),J=w?w[W]:T[R],l.push(J[0],J[1],J[2]),h.push(R)}V+=1}}this.pointCount=q,this.edgeCount=H,this.triangleCount=V,this.pointPositions.update(v),this.pointColors.update(y),this.pointUVs.update(x),this.pointSizes.update(b),this.pointIds.update(new Uint32Array(_)),this.edgePositions.update(p),this.edgeColors.update(d),this.edgeUVs.update(m),this.edgeIds.update(new Uint32Array(g)),this.trianglePositions.update(i),this.triangleColors.update(a),this.triangleUVs.update(c),this.triangleNormals.update(l),this.triangleIds.update(new Uint32Array(h))}},k.drawTransparent=k.draw=function(t){t=t||{};for(var e=this.gl,r=t.model||w,n=t.view||w,i=t.projection||w,a=[[-1e6,-1e6,-1e6],[1e6,1e6,1e6]],o=0;o<3;++o)a[0][o]=Math.max(a[0][o],this.clipBounds[0][o]),a[1][o]=Math.min(a[1][o],this.clipBounds[1][o]);var s={model:r,view:n,projection:i,inverseModel:w.slice(),clipBounds:a,kambient:this.ambientLight,kdiffuse:this.diffuseLight,kspecular:this.specularLight,roughness:this.roughness,fresnel:this.fresnel,eyePosition:[0,0,0],lightPosition:[0,0,0],contourColor:this.contourColor,texture:0};s.inverseModel=c(s.inverseModel,s.model),e.disable(e.CULL_FACE),this.texture.bind(0);var u=new Array(16);l(u,s.view,s.model),l(u,s.projection,u),c(u,u);for(o=0;o<3;++o)s.eyePosition[o]=u[12+o]/u[15];var f,h=u[15];for(o=0;o<3;++o)h+=this.lightPosition[o]*u[4*o+3];for(o=0;o<3;++o){for(var p=u[12+o],d=0;d<3;++d)p+=u[4*d+o]*this.lightPosition[d];s.lightPosition[o]=p/h}this.triangleCount>0&&((f=this.triShader).bind(),f.uniforms=s,this.triangleVAO.bind(),e.drawArrays(e.TRIANGLES,0,3*this.triangleCount),this.triangleVAO.unbind());this.edgeCount>0&&this.lineWidth>0&&((f=this.lineShader).bind(),f.uniforms=s,this.edgeVAO.bind(),e.lineWidth(this.lineWidth*this.pixelRatio),e.drawArrays(e.LINES,0,2*this.edgeCount),this.edgeVAO.unbind());this.pointCount>0&&((f=this.pointShader).bind(),f.uniforms=s,this.pointVAO.bind(),e.drawArrays(e.POINTS,0,this.pointCount),this.pointVAO.unbind());this.contourEnable&&this.contourCount>0&&this.contourLineWidth>0&&((f=this.contourShader).bind(),f.uniforms=s,this.contourVAO.bind(),e.drawArrays(e.LINES,0,this.contourCount),this.contourVAO.unbind())},k.drawPick=function(t){t=t||{};for(var e=this.gl,r=t.model||w,n=t.view||w,i=t.projection||w,a=[[-1e6,-1e6,-1e6],[1e6,1e6,1e6]],o=0;o<3;++o)a[0][o]=Math.max(a[0][o],this.clipBounds[0][o]),a[1][o]=Math.min(a[1][o],this.clipBounds[1][o]);this._model=[].slice.call(r),this._view=[].slice.call(n),this._projection=[].slice.call(i),this._resolution=[e.drawingBufferWidth,e.drawingBufferHeight];var s,l={model:r,view:n,projection:i,clipBounds:a,pickId:this.pickId/255};((s=this.pickShader).bind(),s.uniforms=l,this.triangleCount>0&&(this.triangleVAO.bind(),e.drawArrays(e.TRIANGLES,0,3*this.triangleCount),this.triangleVAO.unbind()),this.edgeCount>0&&(this.edgeVAO.bind(),e.lineWidth(this.lineWidth*this.pixelRatio),e.drawArrays(e.LINES,0,2*this.edgeCount),this.edgeVAO.unbind()),this.pointCount>0)&&((s=this.pointPickShader).bind(),s.uniforms=l,this.pointVAO.bind(),e.drawArrays(e.POINTS,0,this.pointCount),this.pointVAO.unbind())},k.pick=function(t){if(!t)return null;if(t.id!==this.pickId)return null;for(var e=t.value[0]+256*t.value[1]+65536*t.value[2],r=this.cells[e],n=this.positions,i=new Array(r.length),a=0;a<r.length;++a)i[a]=n[r[a]];var o=t.coord[0],s=t.coord[1];if(!this.pickVertex){var l=this.positions[r[0]],c=this.positions[r[1]],u=this.positions[r[2]],f=[(l[0]+c[0]+u[0])/3,(l[1]+c[1]+u[1])/3,(l[2]+c[2]+u[2])/3];return{_cellCenter:!0,position:[o,s],index:e,cell:r,cellId:e,intensity:this.intensity[e],dataCoordinate:f}}var h=m(i,[o*this.pixelRatio,this._resolution[1]-s*this.pixelRatio],this._model,this._view,this._projection,this._resolution);if(!h)return null;var p=h[2],d=0;for(a=0;a<r.length;++a)d+=p[a]*this.intensity[r[a]];return{position:h[1],index:r[h[0]],cell:r,cellId:e,intensity:d,dataCoordinate:this.positions[r[h[0]]]}},k.dispose=function(){this.texture.dispose(),this.triShader.dispose(),this.lineShader.dispose(),this.pointShader.dispose(),this.pickShader.dispose(),this.pointPickShader.dispose(),this.triangleVAO.dispose(),this.trianglePositions.dispose(),this.triangleColors.dispose(),this.triangleUVs.dispose(),this.triangleNormals.dispose(),this.triangleIds.dispose(),this.edgeVAO.dispose(),this.edgePositions.dispose(),this.edgeColors.dispose(),this.edgeUVs.dispose(),this.edgeIds.dispose(),this.pointVAO.dispose(),this.pointPositions.dispose(),this.pointColors.dispose(),this.pointUVs.dispose(),this.pointSizes.dispose(),this.pointIds.dispose(),this.contourVAO.dispose(),this.contourPositions.dispose(),this.contourShader.dispose()},e.exports=function(t,e){1===arguments.length&&(t=(e=t).gl);var r=t.getExtension(\"OES_standard_derivatives\")||t.getExtension(\"MOZ_OES_standard_derivatives\")||t.getExtension(\"WEBKIT_OES_standard_derivatives\");if(!r)throw new Error(\"derivatives not supported\");var n=M(t),s=S(t),l=E(t),c=L(t),f=C(t),h=P(t),p=o(t,u(new Uint8Array([255,255,255,255]),[1,1,4]));p.generateMipmap(),p.minFilter=t.LINEAR_MIPMAP_LINEAR,p.magFilter=t.LINEAR;var d=i(t),m=i(t),g=i(t),v=i(t),y=i(t),x=a(t,[{buffer:d,type:t.FLOAT,size:3},{buffer:y,type:t.UNSIGNED_BYTE,size:4,normalized:!0},{buffer:m,type:t.FLOAT,size:4},{buffer:g,type:t.FLOAT,size:2},{buffer:v,type:t.FLOAT,size:3}]),b=i(t),_=i(t),w=i(t),k=i(t),A=a(t,[{buffer:b,type:t.FLOAT,size:3},{buffer:k,type:t.UNSIGNED_BYTE,size:4,normalized:!0},{buffer:_,type:t.FLOAT,size:4},{buffer:w,type:t.FLOAT,size:2}]),I=i(t),O=i(t),z=i(t),D=i(t),R=i(t),F=a(t,[{buffer:I,type:t.FLOAT,size:3},{buffer:R,type:t.UNSIGNED_BYTE,size:4,normalized:!0},{buffer:O,type:t.FLOAT,size:4},{buffer:z,type:t.FLOAT,size:2},{buffer:D,type:t.FLOAT,size:1}]),B=i(t),N=a(t,[{buffer:B,type:t.FLOAT,size:3}]),j=new T(t,p,n,s,l,c,f,h,d,y,m,g,v,x,b,k,_,w,A,I,R,O,z,D,F,B,N);return j.update(e),j}},{\"./lib/closest-point\":110,\"./lib/shaders\":111,colormap:53,\"gl-buffer\":78,\"gl-mat4/invert\":98,\"gl-mat4/multiply\":100,\"gl-shader\":132,\"gl-texture2d\":146,\"gl-vao\":150,ndarray:259,normals:261,\"simplicial-complex-contour\":291,\"typedarray-pool\":308}],113:[function(t,e,r){\"use strict\";e.exports=function(t){var e=t.gl,r=n(e,[0,0,0,1,1,0,1,1]),s=i(e,a.boxVert,a.lineFrag);return new o(t,r,s)};var n=t(\"gl-buffer\"),i=t(\"gl-shader\"),a=t(\"./shaders\");function o(t,e,r){this.plot=t,this.vbo=e,this.shader=r}var s,l,c=o.prototype;c.bind=function(){var t=this.shader;this.vbo.bind(),this.shader.bind(),t.attributes.coord.pointer(),t.uniforms.screenBox=this.plot.screenBox},c.drawBox=(s=[0,0],l=[0,0],function(t,e,r,n,i){var a=this.plot,o=this.shader,c=a.gl;s[0]=t,s[1]=e,l[0]=r,l[1]=n,o.uniforms.lo=s,o.uniforms.hi=l,o.uniforms.color=i,c.drawArrays(c.TRIANGLE_STRIP,0,4)}),c.dispose=function(){this.vbo.dispose(),this.shader.dispose()}},{\"./shaders\":116,\"gl-buffer\":78,\"gl-shader\":132}],114:[function(t,e,r){\"use strict\";e.exports=function(t){var e=t.gl,r=n(e),a=i(e,o.gridVert,o.gridFrag),l=i(e,o.tickVert,o.gridFrag);return new s(t,r,a,l)};var n=t(\"gl-buffer\"),i=t(\"gl-shader\"),a=t(\"binary-search-bounds\"),o=t(\"./shaders\");function s(t,e,r,n){this.plot=t,this.vbo=e,this.shader=r,this.tickShader=n,this.ticks=[[],[]]}function l(t,e){return t-e}var c,u,f,h,p,d=s.prototype;d.draw=(c=[0,0],u=[0,0],f=[0,0],function(){for(var t=this.plot,e=this.vbo,r=this.shader,n=this.ticks,i=t.gl,a=t._tickBounds,o=t.dataBox,s=t.viewBox,l=t.gridLineWidth,h=t.gridLineColor,p=t.gridLineEnable,d=t.pixelRatio,m=0;m<2;++m){var g=a[m],v=a[m+2]-g,y=.5*(o[m+2]+o[m]),x=o[m+2]-o[m];u[m]=2*v/x,c[m]=2*(g-y)/x}r.bind(),e.bind(),r.attributes.dataCoord.pointer(),r.uniforms.dataShift=c,r.uniforms.dataScale=u;var b=0;for(m=0;m<2;++m){f[0]=f[1]=0,f[m]=1,r.uniforms.dataAxis=f,r.uniforms.lineWidth=l[m]/(s[m+2]-s[m])*d,r.uniforms.color=h[m];var _=6*n[m].length;p[m]&&_&&i.drawArrays(i.TRIANGLES,b,_),b+=_}}),d.drawTickMarks=function(){var t=[0,0],e=[0,0],r=[1,0],n=[0,1],i=[0,0],o=[0,0];return function(){for(var s=this.plot,c=this.vbo,u=this.tickShader,f=this.ticks,h=s.gl,p=s._tickBounds,d=s.dataBox,m=s.viewBox,g=s.pixelRatio,v=s.screenBox,y=v[2]-v[0],x=v[3]-v[1],b=m[2]-m[0],_=m[3]-m[1],w=0;w<2;++w){var T=p[w],k=p[w+2]-T,A=.5*(d[w+2]+d[w]),M=d[w+2]-d[w];e[w]=2*k/M,t[w]=2*(T-A)/M}e[0]*=b/y,t[0]*=b/y,e[1]*=_/x,t[1]*=_/x,u.bind(),c.bind(),u.attributes.dataCoord.pointer();var S=u.uniforms;S.dataShift=t,S.dataScale=e;var E=s.tickMarkLength,L=s.tickMarkWidth,C=s.tickMarkColor,P=6*f[0].length,I=Math.min(a.ge(f[0],(d[0]-p[0])/(p[2]-p[0]),l),f[0].length),O=Math.min(a.gt(f[0],(d[2]-p[0])/(p[2]-p[0]),l),f[0].length),z=0+6*I,D=6*Math.max(0,O-I),R=Math.min(a.ge(f[1],(d[1]-p[1])/(p[3]-p[1]),l),f[1].length),F=Math.min(a.gt(f[1],(d[3]-p[1])/(p[3]-p[1]),l),f[1].length),B=P+6*R,N=6*Math.max(0,F-R);i[0]=2*(m[0]-E[1])/y-1,i[1]=(m[3]+m[1])/x-1,o[0]=E[1]*g/y,o[1]=L[1]*g/x,N&&(S.color=C[1],S.tickScale=o,S.dataAxis=n,S.screenOffset=i,h.drawArrays(h.TRIANGLES,B,N)),i[0]=(m[2]+m[0])/y-1,i[1]=2*(m[1]-E[0])/x-1,o[0]=L[0]*g/y,o[1]=E[0]*g/x,D&&(S.color=C[0],S.tickScale=o,S.dataAxis=r,S.screenOffset=i,h.drawArrays(h.TRIANGLES,z,D)),i[0]=2*(m[2]+E[3])/y-1,i[1]=(m[3]+m[1])/x-1,o[0]=E[3]*g/y,o[1]=L[3]*g/x,N&&(S.color=C[3],S.tickScale=o,S.dataAxis=n,S.screenOffset=i,h.drawArrays(h.TRIANGLES,B,N)),i[0]=(m[2]+m[0])/y-1,i[1]=2*(m[3]+E[2])/x-1,o[0]=L[2]*g/y,o[1]=E[2]*g/x,D&&(S.color=C[2],S.tickScale=o,S.dataAxis=r,S.screenOffset=i,h.drawArrays(h.TRIANGLES,z,D))}}(),d.update=(h=[1,1,-1,-1,1,-1],p=[1,-1,1,1,-1,-1],function(t){for(var e=t.ticks,r=t.bounds,n=new Float32Array(18*(e[0].length+e[1].length)),i=(this.plot.zeroLineEnable,0),a=[[],[]],o=0;o<2;++o)for(var s=a[o],l=e[o],c=r[o],u=r[o+2],f=0;f<l.length;++f){var d=(l[f].x-c)/(u-c);s.push(d);for(var m=0;m<6;++m)n[i++]=d,n[i++]=h[m],n[i++]=p[m]}this.ticks=a,this.vbo.update(n)}),d.dispose=function(){this.vbo.dispose(),this.shader.dispose(),this.tickShader.dispose()}},{\"./shaders\":116,\"binary-search-bounds\":31,\"gl-buffer\":78,\"gl-shader\":132}],115:[function(t,e,r){\"use strict\";e.exports=function(t){var e=t.gl,r=n(e,[-1,-1,-1,1,1,-1,1,1]),s=i(e,a.lineVert,a.lineFrag);return new o(t,r,s)};var n=t(\"gl-buffer\"),i=t(\"gl-shader\"),a=t(\"./shaders\");function o(t,e,r){this.plot=t,this.vbo=e,this.shader=r}var s,l,c=o.prototype;c.bind=function(){var t=this.shader;this.vbo.bind(),this.shader.bind(),t.attributes.coord.pointer(),t.uniforms.screenBox=this.plot.screenBox},c.drawLine=(s=[0,0],l=[0,0],function(t,e,r,n,i,a){var o=this.plot,c=this.shader,u=o.gl;s[0]=t,s[1]=e,l[0]=r,l[1]=n,c.uniforms.start=s,c.uniforms.end=l,c.uniforms.width=i*o.pixelRatio,c.uniforms.color=a,u.drawArrays(u.TRIANGLE_STRIP,0,4)}),c.dispose=function(){this.vbo.dispose(),this.shader.dispose()}},{\"./shaders\":116,\"gl-buffer\":78,\"gl-shader\":132}],116:[function(t,e,r){\"use strict\";var n=t(\"glslify\"),i=n([\"precision lowp float;\\n#define GLSLIFY 1\\nuniform vec4 color;\\nvoid main() {\\n gl_FragColor = vec4(color.xyz * color.w, color.w);\\n}\\n\"]);e.exports={lineVert:n([\"precision mediump float;\\n#define GLSLIFY 1\\n\\nattribute vec2 coord;\\n\\nuniform vec4 screenBox;\\nuniform vec2 start, end;\\nuniform float width;\\n\\nvec2 perp(vec2 v) {\\n return vec2(v.y, -v.x);\\n}\\n\\nvec2 screen(vec2 v) {\\n return 2.0 * (v - screenBox.xy) / (screenBox.zw - screenBox.xy) - 1.0;\\n}\\n\\nvoid main() {\\n vec2 delta = normalize(perp(start - end));\\n vec2 offset = mix(start, end, 0.5 * (coord.y+1.0));\\n gl_Position = vec4(screen(offset + 0.5 * width * delta * coord.x), 0, 1);\\n}\\n\"]),lineFrag:i,textVert:n([\"#define GLSLIFY 1\\nattribute vec3 textCoordinate;\\n\\nuniform vec2 dataScale, dataShift, dataAxis, screenOffset, textScale;\\nuniform float angle;\\n\\nvoid main() {\\n float dataOffset = textCoordinate.z;\\n vec2 glyphOffset = textCoordinate.xy;\\n mat2 glyphMatrix = mat2(cos(angle), sin(angle), -sin(angle), cos(angle));\\n vec2 screenCoordinate = dataAxis * (dataScale * dataOffset + dataShift) +\\n glyphMatrix * glyphOffset * textScale + screenOffset;\\n gl_Position = vec4(screenCoordinate, 0, 1);\\n}\\n\"]),textFrag:i,gridVert:n([\"precision mediump float;\\n#define GLSLIFY 1\\n\\nattribute vec3 dataCoord;\\n\\nuniform vec2 dataAxis, dataShift, dataScale;\\nuniform float lineWidth;\\n\\nvoid main() {\\n vec2 pos = dataAxis * (dataScale * dataCoord.x + dataShift);\\n pos += 10.0 * dataCoord.y * vec2(dataAxis.y, -dataAxis.x) + dataCoord.z * lineWidth;\\n gl_Position = vec4(pos, 0, 1);\\n}\\n\"]),gridFrag:i,boxVert:n([\"precision mediump float;\\n#define GLSLIFY 1\\n\\nattribute vec2 coord;\\n\\nuniform vec4 screenBox;\\nuniform vec2 lo, hi;\\n\\nvec2 screen(vec2 v) {\\n return 2.0 * (v - screenBox.xy) / (screenBox.zw - screenBox.xy) - 1.0;\\n}\\n\\nvoid main() {\\n gl_Position = vec4(screen(mix(lo, hi, coord)), 0, 1);\\n}\\n\"]),tickVert:n([\"precision mediump float;\\n#define GLSLIFY 1\\n\\nattribute vec3 dataCoord;\\n\\nuniform vec2 dataAxis, dataShift, dataScale, screenOffset, tickScale;\\n\\nvoid main() {\\n vec2 pos = dataAxis * (dataScale * dataCoord.x + dataShift);\\n gl_Position = vec4(pos + tickScale*dataCoord.yz + screenOffset, 0, 1);\\n}\\n\"])}},{glslify:231}],117:[function(t,e,r){\"use strict\";e.exports=function(t){var e=t.gl,r=n(e),a=i(e,s.textVert,s.textFrag);return new l(t,r,a)};var n=t(\"gl-buffer\"),i=t(\"gl-shader\"),a=t(\"text-cache\"),o=t(\"binary-search-bounds\"),s=t(\"./shaders\");function l(t,e,r){this.plot=t,this.vbo=e,this.shader=r,this.tickOffset=[[],[]],this.tickX=[[],[]],this.labelOffset=[0,0],this.labelCount=[0,0]}var c,u,f,h,p,d,m=l.prototype;m.drawTicks=(c=[0,0],u=[0,0],f=[0,0],function(t){var e=this.plot,r=this.shader,n=this.tickX[t],i=this.tickOffset[t],a=e.gl,s=e.viewBox,l=e.dataBox,h=e.screenBox,p=e.pixelRatio,d=e.tickEnable,m=e.tickPad,g=e.tickColor,v=e.tickAngle,y=e.labelEnable,x=e.labelPad,b=e.labelColor,_=e.labelAngle,w=this.labelOffset[t],T=this.labelCount[t],k=o.lt(n,l[t]),A=o.le(n,l[t+2]);c[0]=c[1]=0,c[t]=1,u[t]=(s[2+t]+s[t])/(h[2+t]-h[t])-1;var M=2/h[2+(1^t)]-h[1^t];u[1^t]=M*s[1^t]-1,d[t]&&(u[1^t]-=M*p*m[t],k<A&&i[A]>i[k]&&(r.uniforms.dataAxis=c,r.uniforms.screenOffset=u,r.uniforms.color=g[t],r.uniforms.angle=v[t],a.drawArrays(a.TRIANGLES,i[k],i[A]-i[k]))),y[t]&&T&&(u[1^t]-=M*p*x[t],r.uniforms.dataAxis=f,r.uniforms.screenOffset=u,r.uniforms.color=b[t],r.uniforms.angle=_[t],a.drawArrays(a.TRIANGLES,w,T)),u[1^t]=M*s[2+(1^t)]-1,d[t+2]&&(u[1^t]+=M*p*m[t+2],k<A&&i[A]>i[k]&&(r.uniforms.dataAxis=c,r.uniforms.screenOffset=u,r.uniforms.color=g[t+2],r.uniforms.angle=v[t+2],a.drawArrays(a.TRIANGLES,i[k],i[A]-i[k]))),y[t+2]&&T&&(u[1^t]+=M*p*x[t+2],r.uniforms.dataAxis=f,r.uniforms.screenOffset=u,r.uniforms.color=b[t+2],r.uniforms.angle=_[t+2],a.drawArrays(a.TRIANGLES,w,T))}),m.drawTitle=function(){var t=[0,0],e=[0,0];return function(){var r=this.plot,n=this.shader,i=r.gl,a=r.screenBox,o=r.titleCenter,s=r.titleAngle,l=r.titleColor,c=r.pixelRatio;if(this.titleCount){for(var u=0;u<2;++u)e[u]=2*(o[u]*c-a[u])/(a[2+u]-a[u])-1;n.bind(),n.uniforms.dataAxis=t,n.uniforms.screenOffset=e,n.uniforms.angle=s,n.uniforms.color=l,i.drawArrays(i.TRIANGLES,this.titleOffset,this.titleCount)}}}(),m.bind=(h=[0,0],p=[0,0],d=[0,0],function(){var t=this.plot,e=this.shader,r=t._tickBounds,n=t.dataBox,i=t.screenBox,a=t.viewBox;e.bind();for(var o=0;o<2;++o){var s=r[o],l=r[o+2]-s,c=.5*(n[o+2]+n[o]),u=n[o+2]-n[o],f=a[o],m=a[o+2]-f,g=i[o],v=i[o+2]-g;p[o]=2*l/u*m/v,h[o]=2*(s-c)/u*m/v}d[1]=2*t.pixelRatio/(i[3]-i[1]),d[0]=d[1]*(i[3]-i[1])/(i[2]-i[0]),e.uniforms.dataScale=p,e.uniforms.dataShift=h,e.uniforms.textScale=d,this.vbo.bind(),e.attributes.textCoordinate.pointer()}),m.update=function(t){var e,r,n,i,o,s=[],l=t.ticks,c=t.bounds;for(o=0;o<2;++o){var u=[Math.floor(s.length/3)],f=[-1/0],h=l[o];for(e=0;e<h.length;++e){var p=h[e],d=p.x,m=p.text,g=p.font||\"sans-serif\";i=p.fontSize||12;for(var v=1/(c[o+2]-c[o]),y=c[o],x=m.split(\"\\n\"),b=0;b<x.length;b++)for(n=a(g,x[b]).data,r=0;r<n.length;r+=2)s.push(n[r]*i,-n[r+1]*i-b*i*1.2,(d-y)*v);u.push(Math.floor(s.length/3)),f.push(d)}this.tickOffset[o]=u,this.tickX[o]=f}for(o=0;o<2;++o){for(this.labelOffset[o]=Math.floor(s.length/3),n=a(t.labelFont[o],t.labels[o],{textAlign:\"center\"}).data,i=t.labelSize[o],e=0;e<n.length;e+=2)s.push(n[e]*i,-n[e+1]*i,0);this.labelCount[o]=Math.floor(s.length/3)-this.labelOffset[o]}for(this.titleOffset=Math.floor(s.length/3),n=a(t.titleFont,t.title).data,i=t.titleSize,e=0;e<n.length;e+=2)s.push(n[e]*i,-n[e+1]*i,0);this.titleCount=Math.floor(s.length/3)-this.titleOffset,this.vbo.update(s)},m.dispose=function(){this.vbo.dispose(),this.shader.dispose()}},{\"./shaders\":116,\"binary-search-bounds\":31,\"gl-buffer\":78,\"gl-shader\":132,\"text-cache\":303}],118:[function(t,e,r){\"use strict\";e.exports=function(t){var e=t.gl,r=n(e,[e.drawingBufferWidth,e.drawingBufferHeight]),c=new l(e,r);return c.grid=i(c),c.text=a(c),c.line=o(c),c.box=s(c),c.update(t),c};var n=t(\"gl-select-static\"),i=t(\"./lib/grid\"),a=t(\"./lib/text\"),o=t(\"./lib/line\"),s=t(\"./lib/box\");function l(t,e){this.gl=t,this.pickBuffer=e,this.screenBox=[0,0,t.drawingBufferWidth,t.drawingBufferHeight],this.viewBox=[0,0,0,0],this.dataBox=[-10,-10,10,10],this.gridLineEnable=[!0,!0],this.gridLineWidth=[1,1],this.gridLineColor=[[0,0,0,1],[0,0,0,1]],this.pixelRatio=1,this.tickMarkLength=[0,0,0,0],this.tickMarkWidth=[0,0,0,0],this.tickMarkColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.tickPad=[15,15,15,15],this.tickAngle=[0,0,0,0],this.tickEnable=[!0,!0,!0,!0],this.tickColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.labelPad=[15,15,15,15],this.labelAngle=[0,Math.PI/2,0,3*Math.PI/2],this.labelEnable=[!0,!0,!0,!0],this.labelColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.titleCenter=[0,0],this.titleEnable=!0,this.titleAngle=0,this.titleColor=[0,0,0,1],this.borderColor=[0,0,0,0],this.backgroundColor=[0,0,0,0],this.zeroLineEnable=[!0,!0],this.zeroLineWidth=[4,4],this.zeroLineColor=[[0,0,0,1],[0,0,0,1]],this.borderLineEnable=[!0,!0,!0,!0],this.borderLineWidth=[2,2,2,2],this.borderLineColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.grid=null,this.text=null,this.line=null,this.box=null,this.objects=[],this.overlays=[],this._tickBounds=[1/0,1/0,-1/0,-1/0],this.static=!1,this.dirty=!1,this.pickDirty=!1,this.pickDelay=120,this.pickRadius=10,this._pickTimeout=null,this._drawPick=this.drawPick.bind(this),this._depthCounter=0}var c=l.prototype;function u(t){for(var e=t.slice(),r=0;r<e.length;++r)e[r]=e[r].slice();return e}function f(t,e){return t.x-e.x}c.setDirty=function(){this.dirty=this.pickDirty=!0},c.setOverlayDirty=function(){this.dirty=!0},c.nextDepthValue=function(){return this._depthCounter++/65536},c.draw=function(){var t=this.gl,e=this.screenBox,r=this.viewBox,n=this.dataBox,i=this.pixelRatio,a=this.grid,o=this.line,s=this.text,l=this.objects;if(this._depthCounter=0,this.pickDirty&&(this._pickTimeout&&clearTimeout(this._pickTimeout),this.pickDirty=!1,this._pickTimeout=setTimeout(this._drawPick,this.pickDelay)),this.dirty){if(this.dirty=!1,t.bindFramebuffer(t.FRAMEBUFFER,null),t.enable(t.SCISSOR_TEST),t.disable(t.DEPTH_TEST),t.depthFunc(t.LESS),t.depthMask(!1),t.enable(t.BLEND),t.blendEquation(t.FUNC_ADD,t.FUNC_ADD),t.blendFunc(t.ONE,t.ONE_MINUS_SRC_ALPHA),this.borderColor){t.scissor(e[0],e[1],e[2]-e[0],e[3]-e[1]);var c=this.borderColor;t.clearColor(c[0]*c[3],c[1]*c[3],c[2]*c[3],c[3]),t.clear(t.COLOR_BUFFER_BIT|t.DEPTH_BUFFER_BIT)}t.scissor(r[0],r[1],r[2]-r[0],r[3]-r[1]),t.viewport(r[0],r[1],r[2]-r[0],r[3]-r[1]);var u=this.backgroundColor;t.clearColor(u[0]*u[3],u[1]*u[3],u[2]*u[3],u[3]),t.clear(t.COLOR_BUFFER_BIT),a.draw();var f=this.zeroLineEnable,h=this.zeroLineColor,p=this.zeroLineWidth;if(f[0]||f[1]){o.bind();for(var d=0;d<2;++d)if(f[d]&&n[d]<=0&&n[d+2]>=0){var m=e[d]-n[d]*(e[d+2]-e[d])/(n[d+2]-n[d]);0===d?o.drawLine(m,e[1],m,e[3],p[d],h[d]):o.drawLine(e[0],m,e[2],m,p[d],h[d])}}for(d=0;d<l.length;++d)l[d].draw();t.viewport(e[0],e[1],e[2]-e[0],e[3]-e[1]),t.scissor(e[0],e[1],e[2]-e[0],e[3]-e[1]),this.grid.drawTickMarks(),o.bind();var g=this.borderLineEnable,v=this.borderLineWidth,y=this.borderLineColor;for(g[1]&&o.drawLine(r[0],r[1]-.5*v[1]*i,r[0],r[3]+.5*v[3]*i,v[1],y[1]),g[0]&&o.drawLine(r[0]-.5*v[0]*i,r[1],r[2]+.5*v[2]*i,r[1],v[0],y[0]),g[3]&&o.drawLine(r[2],r[1]-.5*v[1]*i,r[2],r[3]+.5*v[3]*i,v[3],y[3]),g[2]&&o.drawLine(r[0]-.5*v[0]*i,r[3],r[2]+.5*v[2]*i,r[3],v[2],y[2]),s.bind(),d=0;d<2;++d)s.drawTicks(d);this.titleEnable&&s.drawTitle();var x=this.overlays;for(d=0;d<x.length;++d)x[d].draw();t.disable(t.SCISSOR_TEST),t.disable(t.BLEND),t.depthMask(!0)}},c.drawPick=function(){if(!this.static){var t=this.pickBuffer;this.gl,this._pickTimeout=null,t.begin();for(var e=1,r=this.objects,n=0;n<r.length;++n)e=r[n].drawPick(e);t.end()}},c.pick=function(t,e){if(!this.static){var r=this.pixelRatio,n=this.pickPixelRatio,i=this.viewBox,a=0|Math.round((t-i[0]/r)*n),o=0|Math.round((e-i[1]/r)*n),s=this.pickBuffer.query(a,o,this.pickRadius);if(!s)return null;for(var l=s.id+(s.value[0]<<8)+(s.value[1]<<16)+(s.value[2]<<24),c=this.objects,u=0;u<c.length;++u){var f=c[u].pick(a,o,l);if(f)return f}return null}},c.setScreenBox=function(t){var e=this.screenBox,r=this.pixelRatio;e[0]=0|Math.round(t[0]*r),e[1]=0|Math.round(t[1]*r),e[2]=0|Math.round(t[2]*r),e[3]=0|Math.round(t[3]*r),this.setDirty()},c.setDataBox=function(t){var e=this.dataBox;(e[0]!==t[0]||e[1]!==t[1]||e[2]!==t[2]||e[3]!==t[3])&&(e[0]=t[0],e[1]=t[1],e[2]=t[2],e[3]=t[3],this.setDirty())},c.setViewBox=function(t){var e=this.pixelRatio,r=this.viewBox;r[0]=0|Math.round(t[0]*e),r[1]=0|Math.round(t[1]*e),r[2]=0|Math.round(t[2]*e),r[3]=0|Math.round(t[3]*e);var n=this.pickPixelRatio;this.pickBuffer.shape=[0|Math.round((t[2]-t[0])*n),0|Math.round((t[3]-t[1])*n)],this.setDirty()},c.update=function(t){t=t||{};var e=this.gl;this.pixelRatio=t.pixelRatio||1;var r=this.pixelRatio;this.pickPixelRatio=Math.max(r,1),this.setScreenBox(t.screenBox||[0,0,e.drawingBufferWidth/r,e.drawingBufferHeight/r]);this.screenBox;this.setViewBox(t.viewBox||[.125*(this.screenBox[2]-this.screenBox[0])/r,.125*(this.screenBox[3]-this.screenBox[1])/r,.875*(this.screenBox[2]-this.screenBox[0])/r,.875*(this.screenBox[3]-this.screenBox[1])/r]);var n=this.viewBox,i=(n[2]-n[0])/(n[3]-n[1]);this.setDataBox(t.dataBox||[-10,-10/i,10,10/i]),this.borderColor=!1!==t.borderColor&&(t.borderColor||[0,0,0,0]).slice(),this.backgroundColor=(t.backgroundColor||[0,0,0,0]).slice(),this.gridLineEnable=(t.gridLineEnable||[!0,!0]).slice(),this.gridLineWidth=(t.gridLineWidth||[1,1]).slice(),this.gridLineColor=u(t.gridLineColor||[[.5,.5,.5,1],[.5,.5,.5,1]]),this.zeroLineEnable=(t.zeroLineEnable||[!0,!0]).slice(),this.zeroLineWidth=(t.zeroLineWidth||[4,4]).slice(),this.zeroLineColor=u(t.zeroLineColor||[[0,0,0,1],[0,0,0,1]]),this.tickMarkLength=(t.tickMarkLength||[0,0,0,0]).slice(),this.tickMarkWidth=(t.tickMarkWidth||[0,0,0,0]).slice(),this.tickMarkColor=u(t.tickMarkColor||[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]]),this.titleCenter=(t.titleCenter||[.5*(n[0]+n[2])/r,(n[3]+120)/r]).slice(),this.titleEnable=!(\"titleEnable\"in t)||!!t.titleEnable,this.titleAngle=t.titleAngle||0,this.titleColor=(t.titleColor||[0,0,0,1]).slice(),this.labelPad=(t.labelPad||[15,15,15,15]).slice(),this.labelAngle=(t.labelAngle||[0,Math.PI/2,0,3*Math.PI/2]).slice(),this.labelEnable=(t.labelEnable||[!0,!0,!0,!0]).slice(),this.labelColor=u(t.labelColor||[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]]),this.tickPad=(t.tickPad||[15,15,15,15]).slice(),this.tickAngle=(t.tickAngle||[0,0,0,0]).slice(),this.tickEnable=(t.tickEnable||[!0,!0,!0,!0]).slice(),this.tickColor=u(t.tickColor||[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]]),this.borderLineEnable=(t.borderLineEnable||[!0,!0,!0,!0]).slice(),this.borderLineWidth=(t.borderLineWidth||[2,2,2,2]).slice(),this.borderLineColor=u(t.borderLineColor||[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]]);var a=t.ticks||[[],[]],o=this._tickBounds;o[0]=o[1]=1/0,o[2]=o[3]=-1/0;for(var s=0;s<2;++s){var l=a[s].slice(0);0!==l.length&&(l.sort(f),o[s]=Math.min(o[s],l[0].x),o[s+2]=Math.max(o[s+2],l[l.length-1].x))}this.grid.update({bounds:o,ticks:a}),this.text.update({bounds:o,ticks:a,labels:t.labels||[\"x\",\"y\"],labelSize:t.labelSize||[12,12],labelFont:t.labelFont||[\"sans-serif\",\"sans-serif\"],title:t.title||\"\",titleSize:t.titleSize||18,titleFont:t.titleFont||\"sans-serif\"}),this.static=!!t.static,this.setDirty()},c.dispose=function(){this.box.dispose(),this.grid.dispose(),this.text.dispose(),this.line.dispose();for(var t=this.objects.length-1;t>=0;--t)this.objects[t].dispose();this.objects.length=0;for(t=this.overlays.length-1;t>=0;--t)this.overlays[t].dispose();this.overlays.length=0,this.gl=null},c.addObject=function(t){this.objects.indexOf(t)<0&&(this.objects.push(t),this.setDirty())},c.removeObject=function(t){for(var e=this.objects,r=0;r<e.length;++r)if(e[r]===t){e.splice(r,1),this.setDirty();break}},c.addOverlay=function(t){this.overlays.indexOf(t)<0&&(this.overlays.push(t),this.setOverlayDirty())},c.removeOverlay=function(t){for(var e=this.overlays,r=0;r<e.length;++r)if(e[r]===t){e.splice(r,1),this.setOverlayDirty();break}}},{\"./lib/box\":113,\"./lib/grid\":114,\"./lib/line\":115,\"./lib/text\":117,\"gl-select-static\":131}],119:[function(t,e,r){\"use strict\";e.exports=function(t,e){t=t||document.body,e=e||{};var r=[.01,1/0];\"distanceLimits\"in e&&(r[0]=e.distanceLimits[0],r[1]=e.distanceLimits[1]);\"zoomMin\"in e&&(r[0]=e.zoomMin);\"zoomMax\"in e&&(r[1]=e.zoomMax);var c=i({center:e.center||[0,0,0],up:e.up||[0,1,0],eye:e.eye||[0,0,10],mode:e.mode||\"orbit\",distanceLimits:r}),u=[0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0],f=0,h=t.clientWidth,p=t.clientHeight,d={keyBindingMode:\"rotate\",enableWheel:!0,view:c,element:t,delay:e.delay||16,rotateSpeed:e.rotateSpeed||1,zoomSpeed:e.zoomSpeed||1,translateSpeed:e.translateSpeed||1,flipX:!!e.flipX,flipY:!!e.flipY,modes:c.modes,_ortho:e._ortho||e.projection&&\"orthographic\"===e.projection.type||!1,tick:function(){var e=n(),r=this.delay,i=e-2*r;c.idle(e-r),c.recalcMatrix(i),c.flush(e-(100+2*r));for(var a=!0,o=c.computedMatrix,s=0;s<16;++s)a=a&&u[s]===o[s],u[s]=o[s];var l=t.clientWidth===h&&t.clientHeight===p;return h=t.clientWidth,p=t.clientHeight,a?!l:(f=Math.exp(c.computedRadius[0]),!0)},lookAt:function(t,e,r){c.lookAt(c.lastT(),t,e,r)},rotate:function(t,e,r){c.rotate(c.lastT(),t,e,r)},pan:function(t,e,r){c.pan(c.lastT(),t,e,r)},translate:function(t,e,r){c.translate(c.lastT(),t,e,r)}};return Object.defineProperties(d,{matrix:{get:function(){return c.computedMatrix},set:function(t){return c.setMatrix(c.lastT(),t),c.computedMatrix},enumerable:!0},mode:{get:function(){return c.getMode()},set:function(t){var e=c.computedUp.slice(),r=c.computedEye.slice(),i=c.computedCenter.slice();if(c.setMode(t),\"turntable\"===t){var a=n();c._active.lookAt(a,r,i,e),c._active.lookAt(a+500,r,i,[0,0,1]),c._active.flush(a)}return c.getMode()},enumerable:!0},center:{get:function(){return c.computedCenter},set:function(t){return c.lookAt(c.lastT(),null,t),c.computedCenter},enumerable:!0},eye:{get:function(){return c.computedEye},set:function(t){return c.lookAt(c.lastT(),t),c.computedEye},enumerable:!0},up:{get:function(){return c.computedUp},set:function(t){return c.lookAt(c.lastT(),null,null,t),c.computedUp},enumerable:!0},distance:{get:function(){return f},set:function(t){return c.setDistance(c.lastT(),t),t},enumerable:!0},distanceLimits:{get:function(){return c.getDistanceLimits(r)},set:function(t){return c.setDistanceLimits(t),t},enumerable:!0}}),t.addEventListener(\"contextmenu\",(function(t){return t.preventDefault(),!1})),d._lastX=-1,d._lastY=-1,d._lastMods={shift:!1,control:!1,alt:!1,meta:!1},d.enableMouseListeners=function(){function e(e,r,i,a){var o=d.keyBindingMode;if(!1!==o){var s=\"rotate\"===o,l=\"pan\"===o,u=\"zoom\"===o,h=!!a.control,p=!!a.alt,m=!!a.shift,g=!!(1&e),v=!!(2&e),y=!!(4&e),x=1/t.clientHeight,b=x*(r-d._lastX),_=x*(i-d._lastY),w=d.flipX?1:-1,T=d.flipY?1:-1,k=Math.PI*d.rotateSpeed,A=n();if(-1!==d._lastX&&-1!==d._lastY&&((s&&g&&!h&&!p&&!m||g&&!h&&!p&&m)&&c.rotate(A,w*k*b,-T*k*_,0),(l&&g&&!h&&!p&&!m||v||g&&h&&!p&&!m)&&c.pan(A,-d.translateSpeed*b*f,d.translateSpeed*_*f,0),u&&g&&!h&&!p&&!m||y||g&&!h&&p&&!m)){var M=-d.zoomSpeed*_/window.innerHeight*(A-c.lastT())*100;c.pan(A,0,0,f*(Math.exp(M)-1))}return d._lastX=r,d._lastY=i,d._lastMods=a,!0}}d.mouseListener=a(t,e),t.addEventListener(\"touchstart\",(function(r){var n=s(r.changedTouches[0],t);e(0,n[0],n[1],d._lastMods),e(1,n[0],n[1],d._lastMods)}),!!l&&{passive:!0}),t.addEventListener(\"touchmove\",(function(r){var n=s(r.changedTouches[0],t);e(1,n[0],n[1],d._lastMods),r.preventDefault()}),!!l&&{passive:!1}),t.addEventListener(\"touchend\",(function(t){e(0,d._lastX,d._lastY,d._lastMods)}),!!l&&{passive:!0}),d.wheelListener=o(t,(function(t,e){if(!1!==d.keyBindingMode&&d.enableWheel){var r=d.flipX?1:-1,i=d.flipY?1:-1,a=n();if(Math.abs(t)>Math.abs(e))c.rotate(a,0,0,-t*r*Math.PI*d.rotateSpeed/window.innerWidth);else if(!d._ortho){var o=-d.zoomSpeed*i*e/window.innerHeight*(a-c.lastT())/20;c.pan(a,0,0,f*(Math.exp(o)-1))}}}),!0)},d.enableMouseListeners(),d};var n=t(\"right-now\"),i=t(\"3d-view\"),a=t(\"mouse-change\"),o=t(\"mouse-wheel\"),s=t(\"mouse-event-offset\"),l=t(\"has-passive-events\")},{\"3d-view\":7,\"has-passive-events\":232,\"mouse-change\":247,\"mouse-event-offset\":248,\"mouse-wheel\":250,\"right-now\":278}],120:[function(t,e,r){var n=t(\"glslify\"),i=t(\"gl-shader\"),a=n([\"precision mediump float;\\n#define GLSLIFY 1\\nattribute vec2 position;\\nvarying vec2 uv;\\nvoid main() {\\n uv = position;\\n gl_Position = vec4(position, 0, 1);\\n}\"]),o=n([\"precision mediump float;\\n#define GLSLIFY 1\\n\\nuniform sampler2D accumBuffer;\\nvarying vec2 uv;\\n\\nvoid main() {\\n vec4 accum = texture2D(accumBuffer, 0.5 * (uv + 1.0));\\n gl_FragColor = min(vec4(1,1,1,1), accum);\\n}\"]);e.exports=function(t){return i(t,a,o,null,[{name:\"position\",type:\"vec2\"}])}},{\"gl-shader\":132,glslify:231}],121:[function(t,e,r){\"use strict\";var n=t(\"./camera.js\"),i=t(\"gl-axes3d\"),a=t(\"gl-axes3d/properties\"),o=t(\"gl-spikes3d\"),s=t(\"gl-select-static\"),l=t(\"gl-fbo\"),c=t(\"a-big-triangle\"),u=t(\"mouse-change\"),f=t(\"gl-mat4/perspective\"),h=t(\"gl-mat4/ortho\"),p=t(\"./lib/shader\"),d=t(\"is-mobile\")({tablet:!0,featureDetect:!0});function m(){this.mouse=[-1,-1],this.screen=null,this.distance=1/0,this.index=null,this.dataCoordinate=null,this.dataPosition=null,this.object=null,this.data=null}function g(t){var e=Math.round(Math.log(Math.abs(t))/Math.log(10));if(e<0){var r=Math.round(Math.pow(10,-e));return Math.ceil(t*r)/r}if(e>0){r=Math.round(Math.pow(10,e));return Math.ceil(t/r)*r}return Math.ceil(t)}function v(t){return\"boolean\"!=typeof t||t}e.exports={createScene:function(t){(t=t||{}).camera=t.camera||{};var e=t.canvas;if(!e){if(e=document.createElement(\"canvas\"),t.container)t.container.appendChild(e);else document.body.appendChild(e)}var r=t.gl;r||(t.glOptions&&(d=!!t.glOptions.preserveDrawingBuffer),r=function(t,e){var r=null;try{(r=t.getContext(\"webgl\",e))||(r=t.getContext(\"experimental-webgl\",e))}catch(t){return null}return r}(e,t.glOptions||{premultipliedAlpha:!0,antialias:!0,preserveDrawingBuffer:d}));if(!r)throw new Error(\"webgl not supported\");var y=t.bounds||[[-10,-10,-10],[10,10,10]],x=new m,b=l(r,r.drawingBufferWidth,r.drawingBufferHeight,{preferFloat:!d}),_=p(r),w=t.cameraObject&&!0===t.cameraObject._ortho||t.camera.projection&&\"orthographic\"===t.camera.projection.type||!1,T={eye:t.camera.eye||[2,0,0],center:t.camera.center||[0,0,0],up:t.camera.up||[0,1,0],zoomMin:t.camera.zoomMax||.1,zoomMax:t.camera.zoomMin||100,mode:t.camera.mode||\"turntable\",_ortho:w},k=t.axes||{},A=i(r,k);A.enable=!k.disable;var M=t.spikes||{},S=o(r,M),E=[],L=[],C=[],P=[],I=!0,O=!0,z=new Array(16),D=new Array(16),R={view:null,projection:z,model:D,_ortho:!1},F=(O=!0,[r.drawingBufferWidth,r.drawingBufferHeight]),B=t.cameraObject||n(e,T),N={gl:r,contextLost:!1,pixelRatio:t.pixelRatio||1,canvas:e,selection:x,camera:B,axes:A,axesPixels:null,spikes:S,bounds:y,objects:E,shape:F,aspect:t.aspectRatio||[1,1,1],pickRadius:t.pickRadius||10,zNear:t.zNear||.01,zFar:t.zFar||1e3,fovy:t.fovy||Math.PI/4,clearColor:t.clearColor||[0,0,0,0],autoResize:v(t.autoResize),autoBounds:v(t.autoBounds),autoScale:!!t.autoScale,autoCenter:v(t.autoCenter),clipToBounds:v(t.clipToBounds),snapToData:!!t.snapToData,onselect:t.onselect||null,onrender:t.onrender||null,onclick:t.onclick||null,cameraParams:R,oncontextloss:null,mouseListener:null,_stopped:!1,getAspectratio:function(){return{x:this.aspect[0],y:this.aspect[1],z:this.aspect[2]}},setAspectratio:function(t){this.aspect[0]=t.x,this.aspect[1]=t.y,this.aspect[2]=t.z,O=!0},setBounds:function(t,e){this.bounds[0][t]=e.min,this.bounds[1][t]=e.max},setClearColor:function(t){this.clearColor=t},clearRGBA:function(){this.gl.clearColor(this.clearColor[0],this.clearColor[1],this.clearColor[2],this.clearColor[3]),this.gl.clear(this.gl.COLOR_BUFFER_BIT|this.gl.DEPTH_BUFFER_BIT)}},j=[r.drawingBufferWidth/N.pixelRatio|0,r.drawingBufferHeight/N.pixelRatio|0];function U(){if(!N._stopped&&N.autoResize){var t=e.parentNode,r=1,n=1;t&&t!==document.body?(r=t.clientWidth,n=t.clientHeight):(r=window.innerWidth,n=window.innerHeight);var i=0|Math.ceil(r*N.pixelRatio),a=0|Math.ceil(n*N.pixelRatio);if(i!==e.width||a!==e.height){e.width=i,e.height=a;var o=e.style;o.position=o.position||\"absolute\",o.left=\"0px\",o.top=\"0px\",o.width=r+\"px\",o.height=n+\"px\",I=!0}}}N.autoResize&&U();function V(){for(var t=E.length,e=P.length,n=0;n<e;++n)C[n]=0;t:for(n=0;n<t;++n){var i=E[n],a=i.pickSlots;if(a){for(var o=0;o<e;++o)if(C[o]+a<255){L[n]=o,i.setPickBase(C[o]+1),C[o]+=a;continue t}var l=s(r,F);L[n]=e,P.push(l),C.push(a),i.setPickBase(1),e+=1}else L[n]=-1}for(;e>0&&0===C[e-1];)C.pop(),P.pop().dispose()}function H(){if(N.contextLost)return!0;r.isContextLost()&&(N.contextLost=!0,N.mouseListener.enabled=!1,N.selection.object=null,N.oncontextloss&&N.oncontextloss())}window.addEventListener(\"resize\",U),N.update=function(t){N._stopped||(t=t||{},I=!0,O=!0)},N.add=function(t){N._stopped||(t.axes=A,E.push(t),L.push(-1),I=!0,O=!0,V())},N.remove=function(t){if(!N._stopped){var e=E.indexOf(t);e<0||(E.splice(e,1),L.pop(),I=!0,O=!0,V())}},N.dispose=function(){if(!N._stopped&&(N._stopped=!0,window.removeEventListener(\"resize\",U),e.removeEventListener(\"webglcontextlost\",H),N.mouseListener.enabled=!1,!N.contextLost)){A.dispose(),S.dispose();for(var t=0;t<E.length;++t)E[t].dispose();b.dispose();for(t=0;t<P.length;++t)P[t].dispose();_.dispose(),r=null,A=null,S=null,E=[]}},N._mouseRotating=!1,N._prevButtons=0,N.enableMouseListeners=function(){N.mouseListener=u(e,(function(t,e,r){if(!N._stopped){var n=P.length,i=E.length,a=x.object;x.distance=1/0,x.mouse[0]=e,x.mouse[1]=r,x.object=null,x.screen=null,x.dataCoordinate=x.dataPosition=null;var o=!1;if(t&&N._prevButtons)N._mouseRotating=!0;else{N._mouseRotating&&(O=!0),N._mouseRotating=!1;for(var s=0;s<n;++s){var l=P[s].query(e,j[1]-r-1,N.pickRadius);if(l){if(l.distance>x.distance)continue;for(var c=0;c<i;++c){var u=E[c];if(L[c]===s){var f=u.pick(l);f&&(x.buttons=t,x.screen=l.coord,x.distance=l.distance,x.object=u,x.index=f.distance,x.dataPosition=f.position,x.dataCoordinate=f.dataCoordinate,x.data=f,o=!0)}}}}}a&&a!==x.object&&(a.highlight&&a.highlight(null),I=!0),x.object&&(x.object.highlight&&x.object.highlight(x.data),I=!0),(o=o||x.object!==a)&&N.onselect&&N.onselect(x),1&t&&!(1&N._prevButtons)&&N.onclick&&N.onclick(x),N._prevButtons=t}}))},e.addEventListener(\"webglcontextlost\",H);var q=[[1/0,1/0,1/0],[-1/0,-1/0,-1/0]],G=[q[0].slice(),q[1].slice()];function Y(){if(!H()){U();var t=N.camera.tick();R.view=N.camera.matrix,I=I||t,O=O||t,A.pixelRatio=N.pixelRatio,S.pixelRatio=N.pixelRatio;var e=E.length,n=q[0],i=q[1];n[0]=n[1]=n[2]=1/0,i[0]=i[1]=i[2]=-1/0;for(var o=0;o<e;++o){(C=E[o]).pixelRatio=N.pixelRatio,C.axes=N.axes,I=I||!!C.dirty,O=O||!!C.dirty;var s=C.bounds;if(s)for(var l=s[0],u=s[1],p=0;p<3;++p)n[p]=Math.min(n[p],l[p]),i[p]=Math.max(i[p],u[p])}var d=N.bounds;if(N.autoBounds)for(p=0;p<3;++p){if(i[p]<n[p])n[p]=-1,i[p]=1;else{n[p]===i[p]&&(n[p]-=1,i[p]+=1);var m=.05*(i[p]-n[p]);n[p]=n[p]-m,i[p]=i[p]+m}d[0][p]=n[p],d[1][p]=i[p]}var v=!1;for(p=0;p<3;++p)v=v||G[0][p]!==d[0][p]||G[1][p]!==d[1][p],G[0][p]=d[0][p],G[1][p]=d[1][p];if(O=O||v,I=I||v){if(v){var y=[0,0,0];for(o=0;o<3;++o)y[o]=g((d[1][o]-d[0][o])/10);A.autoTicks?A.update({bounds:d,tickSpacing:y}):A.update({bounds:d})}var T=r.drawingBufferWidth,k=r.drawingBufferHeight;F[0]=T,F[1]=k,j[0]=0|Math.max(T/N.pixelRatio,1),j[1]=0|Math.max(k/N.pixelRatio,1),function(t,e){var r=t.bounds,n=t.cameraParams,i=n.projection,a=n.model,o=t.gl.drawingBufferWidth,s=t.gl.drawingBufferHeight,l=t.zNear,c=t.zFar,u=t.fovy,p=o/s;e?(h(i,-p,p,-1,1,l,c),n._ortho=!0):(f(i,u,p,l,c),n._ortho=!1);for(var d=0;d<16;++d)a[d]=0;a[15]=1;var m=0;for(d=0;d<3;++d)m=Math.max(m,r[1][d]-r[0][d]);for(d=0;d<3;++d)t.autoScale?a[5*d]=t.aspect[d]/(r[1][d]-r[0][d]):a[5*d]=1/m,t.autoCenter&&(a[12+d]=.5*-a[5*d]*(r[0][d]+r[1][d]))}(N,w);for(o=0;o<e;++o){(C=E[o]).axesBounds=d,N.clipToBounds&&(C.clipBounds=d)}x.object&&(N.snapToData?S.position=x.dataCoordinate:S.position=x.dataPosition,S.bounds=d),O&&(O=!1,function(){if(!H()){r.colorMask(!0,!0,!0,!0),r.depthMask(!0),r.disable(r.BLEND),r.enable(r.DEPTH_TEST),r.depthFunc(r.LEQUAL);for(var t=E.length,e=P.length,n=0;n<e;++n){var i=P[n];i.shape=j,i.begin();for(var a=0;a<t;++a)if(L[a]===n){var o=E[a];o.drawPick&&(o.pixelRatio=1,o.drawPick(R))}i.end()}}}()),N.axesPixels=a(N.axes,R,T,k),N.onrender&&N.onrender(),r.bindFramebuffer(r.FRAMEBUFFER,null),r.viewport(0,0,T,k),N.clearRGBA(),r.depthMask(!0),r.colorMask(!0,!0,!0,!0),r.enable(r.DEPTH_TEST),r.depthFunc(r.LEQUAL),r.disable(r.BLEND),r.disable(r.CULL_FACE);var M=!1;A.enable&&(M=M||A.isTransparent(),A.draw(R)),S.axes=A,x.object&&S.draw(R),r.disable(r.CULL_FACE);for(o=0;o<e;++o){(C=E[o]).axes=A,C.pixelRatio=N.pixelRatio,C.isOpaque&&C.isOpaque()&&C.draw(R),C.isTransparent&&C.isTransparent()&&(M=!0)}if(M){b.shape=F,b.bind(),r.clear(r.DEPTH_BUFFER_BIT),r.colorMask(!1,!1,!1,!1),r.depthMask(!0),r.depthFunc(r.LESS),A.enable&&A.isTransparent()&&A.drawTransparent(R);for(o=0;o<e;++o){(C=E[o]).isOpaque&&C.isOpaque()&&C.draw(R)}r.enable(r.BLEND),r.blendEquation(r.FUNC_ADD),r.blendFunc(r.ONE,r.ONE_MINUS_SRC_ALPHA),r.colorMask(!0,!0,!0,!0),r.depthMask(!1),r.clearColor(0,0,0,0),r.clear(r.COLOR_BUFFER_BIT),A.isTransparent()&&A.drawTransparent(R);for(o=0;o<e;++o){var C;(C=E[o]).isTransparent&&C.isTransparent()&&C.drawTransparent(R)}r.bindFramebuffer(r.FRAMEBUFFER,null),r.blendFunc(r.ONE,r.ONE_MINUS_SRC_ALPHA),r.disable(r.DEPTH_TEST),_.bind(),b.color[0].bind(0),_.uniforms.accumBuffer=0,c(r),r.disable(r.BLEND)}I=!1;for(o=0;o<e;++o)E[o].dirty=!1}}}return N.enableMouseListeners(),function t(){if(N._stopped||N.contextLost)return;Y(),requestAnimationFrame(t)}(),N.redraw=function(){N._stopped||(I=!0,Y())},N},createCamera:n}},{\"./camera.js\":119,\"./lib/shader\":120,\"a-big-triangle\":8,\"gl-axes3d\":70,\"gl-axes3d/properties\":77,\"gl-fbo\":86,\"gl-mat4/ortho\":101,\"gl-mat4/perspective\":102,\"gl-select-static\":131,\"gl-spikes3d\":141,\"is-mobile\":238,\"mouse-change\":247}],122:[function(t,e,r){var n=t(\"glslify\");r.pointVertex=n([\"precision mediump float;\\n#define GLSLIFY 1\\n\\nattribute vec2 position;\\n\\nuniform mat3 matrix;\\nuniform float pointSize;\\nuniform float pointCloud;\\n\\nhighp float rand(vec2 co) {\\n highp float a = 12.9898;\\n highp float b = 78.233;\\n highp float c = 43758.5453;\\n highp float d = dot(co.xy, vec2(a, b));\\n highp float e = mod(d, 3.14);\\n return fract(sin(e) * c);\\n}\\n\\nvoid main() {\\n vec3 hgPosition = matrix * vec3(position, 1);\\n gl_Position = vec4(hgPosition.xy, 0, hgPosition.z);\\n // if we don't jitter the point size a bit, overall point cloud\\n // saturation 'jumps' on zooming, which is disturbing and confusing\\n gl_PointSize = pointSize * ((19.5 + rand(position)) / 20.0);\\n if(pointCloud != 0.0) { // pointCloud is truthy\\n // get the same square surface as circle would be\\n gl_PointSize *= 0.886;\\n }\\n}\"]),r.pointFragment=n([\"precision mediump float;\\n#define GLSLIFY 1\\n\\nuniform vec4 color, borderColor;\\nuniform float centerFraction;\\nuniform float pointCloud;\\n\\nvoid main() {\\n float radius;\\n vec4 baseColor;\\n if(pointCloud != 0.0) { // pointCloud is truthy\\n if(centerFraction == 1.0) {\\n gl_FragColor = color;\\n } else {\\n gl_FragColor = mix(borderColor, color, centerFraction);\\n }\\n } else {\\n radius = length(2.0 * gl_PointCoord.xy - 1.0);\\n if(radius > 1.0) {\\n discard;\\n }\\n baseColor = mix(borderColor, color, step(radius, centerFraction));\\n gl_FragColor = vec4(baseColor.rgb * baseColor.a, baseColor.a);\\n }\\n}\\n\"]),r.pickVertex=n([\"precision mediump float;\\n#define GLSLIFY 1\\n\\nattribute vec2 position;\\nattribute vec4 pickId;\\n\\nuniform mat3 matrix;\\nuniform float pointSize;\\nuniform vec4 pickOffset;\\n\\nvarying vec4 fragId;\\n\\nvoid main() {\\n vec3 hgPosition = matrix * vec3(position, 1);\\n gl_Position = vec4(hgPosition.xy, 0, hgPosition.z);\\n gl_PointSize = pointSize;\\n\\n vec4 id = pickId + pickOffset;\\n id.y += floor(id.x / 256.0);\\n id.x -= floor(id.x / 256.0) * 256.0;\\n\\n id.z += floor(id.y / 256.0);\\n id.y -= floor(id.y / 256.0) * 256.0;\\n\\n id.w += floor(id.z / 256.0);\\n id.z -= floor(id.z / 256.0) * 256.0;\\n\\n fragId = id;\\n}\\n\"]),r.pickFragment=n([\"precision mediump float;\\n#define GLSLIFY 1\\n\\nvarying vec4 fragId;\\n\\nvoid main() {\\n float radius = length(2.0 * gl_PointCoord.xy - 1.0);\\n if(radius > 1.0) {\\n discard;\\n }\\n gl_FragColor = fragId / 255.0;\\n}\\n\"])},{glslify:231}],123:[function(t,e,r){\"use strict\";var n=t(\"gl-shader\"),i=t(\"gl-buffer\"),a=t(\"typedarray-pool\"),o=t(\"./lib/shader\");function s(t,e,r,n,i){this.plot=t,this.offsetBuffer=e,this.pickBuffer=r,this.shader=n,this.pickShader=i,this.sizeMin=.5,this.sizeMinCap=2,this.sizeMax=20,this.areaRatio=1,this.pointCount=0,this.color=[1,0,0,1],this.borderColor=[0,0,0,1],this.blend=!1,this.pickOffset=0,this.points=null}e.exports=function(t,e){var r=t.gl,a=i(r),l=i(r),c=n(r,o.pointVertex,o.pointFragment),u=n(r,o.pickVertex,o.pickFragment),f=new s(t,a,l,c,u);return f.update(e),t.addObject(f),f};var l,c,u=s.prototype;u.dispose=function(){this.shader.dispose(),this.pickShader.dispose(),this.offsetBuffer.dispose(),this.pickBuffer.dispose(),this.plot.removeObject(this)},u.update=function(t){var e;function r(e,r){return e in t?t[e]:r}t=t||{},this.sizeMin=r(\"sizeMin\",.5),this.sizeMax=r(\"sizeMax\",20),this.color=r(\"color\",[1,0,0,1]).slice(),this.areaRatio=r(\"areaRatio\",1),this.borderColor=r(\"borderColor\",[0,0,0,1]).slice(),this.blend=r(\"blend\",!1);var n=t.positions.length>>>1,i=t.positions instanceof Float32Array,o=t.idToIndex instanceof Int32Array&&t.idToIndex.length>=n,s=t.positions,l=i?s:a.mallocFloat32(s.length),c=o?t.idToIndex:a.mallocInt32(n);if(i||l.set(s),!o)for(l.set(s),e=0;e<n;e++)c[e]=e;this.points=s,this.offsetBuffer.update(l),this.pickBuffer.update(c),i||a.free(l),o||a.free(c),this.pointCount=n,this.pickOffset=0},u.unifiedDraw=(l=[1,0,0,0,1,0,0,0,1],c=[0,0,0,0],function(t){var e=void 0!==t,r=e?this.pickShader:this.shader,n=this.plot.gl,i=this.plot.dataBox;if(0===this.pointCount)return t;var a=i[2]-i[0],o=i[3]-i[1],s=function(t,e){var r,n=0,i=t.length>>>1;for(r=0;r<i;r++){var a=t[2*r],o=t[2*r+1];a>=e[0]&&a<=e[2]&&o>=e[1]&&o<=e[3]&&n++}return n}(this.points,i),u=this.plot.pickPixelRatio*Math.max(Math.min(this.sizeMinCap,this.sizeMin),Math.min(this.sizeMax,this.sizeMax/Math.pow(s,.33333)));l[0]=2/a,l[4]=2/o,l[6]=-2*i[0]/a-1,l[7]=-2*i[1]/o-1,this.offsetBuffer.bind(),r.bind(),r.attributes.position.pointer(),r.uniforms.matrix=l,r.uniforms.color=this.color,r.uniforms.borderColor=this.borderColor,r.uniforms.pointCloud=u<5,r.uniforms.pointSize=u,r.uniforms.centerFraction=Math.min(1,Math.max(0,Math.sqrt(1-this.areaRatio))),e&&(c[0]=255&t,c[1]=t>>8&255,c[2]=t>>16&255,c[3]=t>>24&255,this.pickBuffer.bind(),r.attributes.pickId.pointer(n.UNSIGNED_BYTE),r.uniforms.pickOffset=c,this.pickOffset=t);var f=n.getParameter(n.BLEND),h=n.getParameter(n.DITHER);return f&&!this.blend&&n.disable(n.BLEND),h&&n.disable(n.DITHER),n.drawArrays(n.POINTS,0,this.pointCount),f&&!this.blend&&n.enable(n.BLEND),h&&n.enable(n.DITHER),t+this.pointCount}),u.draw=u.unifiedDraw,u.drawPick=u.unifiedDraw,u.pick=function(t,e,r){var n=this.pickOffset,i=this.pointCount;if(r<n||r>=n+i)return null;var a=r-n,o=this.points;return{object:this,pointId:a,dataCoord:[o[2*a],o[2*a+1]]}}},{\"./lib/shader\":122,\"gl-buffer\":78,\"gl-shader\":132,\"typedarray-pool\":308}],124:[function(t,e,r){e.exports=function(t,e,r,n){var i,a,o,s,l,c=e[0],u=e[1],f=e[2],h=e[3],p=r[0],d=r[1],m=r[2],g=r[3];(a=c*p+u*d+f*m+h*g)<0&&(a=-a,p=-p,d=-d,m=-m,g=-g);1-a>1e-6?(i=Math.acos(a),o=Math.sin(i),s=Math.sin((1-n)*i)/o,l=Math.sin(n*i)/o):(s=1-n,l=n);return t[0]=s*c+l*p,t[1]=s*u+l*d,t[2]=s*f+l*m,t[3]=s*h+l*g,t}},{}],125:[function(t,e,r){\"use strict\";e.exports=function(t){return t||0===t?t.toString():\"\"}},{}],126:[function(t,e,r){\"use strict\";var n=t(\"vectorize-text\");e.exports=function(t,e,r){var a=i[e];a||(a=i[e]={});if(t in a)return a[t];var o={textAlign:\"center\",textBaseline:\"middle\",lineHeight:1,font:e,lineSpacing:1.25,styletags:{breaklines:!0,bolds:!0,italics:!0,subscripts:!0,superscripts:!0},triangles:!0},s=n(t,o);o.triangles=!1;var l,c,u=n(t,o);if(r&&1!==r){for(l=0;l<s.positions.length;++l)for(c=0;c<s.positions[l].length;++c)s.positions[l][c]/=r;for(l=0;l<u.positions.length;++l)for(c=0;c<u.positions[l].length;++c)u.positions[l][c]/=r}var f=[[1/0,1/0],[-1/0,-1/0]],h=u.positions.length;for(l=0;l<h;++l){var p=u.positions[l];for(c=0;c<2;++c)f[0][c]=Math.min(f[0][c],p[c]),f[1][c]=Math.max(f[1][c],p[c])}return a[t]=[s,u,f]};var i={}},{\"vectorize-text\":311}],127:[function(t,e,r){var n=t(\"gl-shader\"),i=t(\"glslify\"),a=i([\"precision highp float;\\n#define GLSLIFY 1\\n\\nbool outOfRange(float a, float b, float p) {\\n return ((p > max(a, b)) || \\n (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n return (outOfRange(a.x, b.x, p.x) ||\\n outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n return (outOfRange(a.x, b.x, p.x) ||\\n outOfRange(a.y, b.y, p.y) ||\\n outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nattribute vec3 position;\\nattribute vec4 color;\\nattribute vec2 glyph;\\nattribute vec4 id;\\n\\nuniform vec4 highlightId;\\nuniform float highlightScale;\\nuniform mat4 model, view, projection;\\nuniform vec3 clipBounds[2];\\n\\nvarying vec4 interpColor;\\nvarying vec4 pickId;\\nvarying vec3 dataCoordinate;\\n\\nvoid main() {\\n if (outOfRange(clipBounds[0], clipBounds[1], position)) {\\n\\n gl_Position = vec4(0,0,0,0);\\n } else {\\n float scale = 1.0;\\n if(distance(highlightId, id) < 0.0001) {\\n scale = highlightScale;\\n }\\n\\n vec4 worldPosition = model * vec4(position, 1);\\n vec4 viewPosition = view * worldPosition;\\n viewPosition = viewPosition / viewPosition.w;\\n vec4 clipPosition = projection * (viewPosition + scale * vec4(glyph.x, -glyph.y, 0, 0));\\n\\n gl_Position = clipPosition;\\n interpColor = color;\\n pickId = id;\\n dataCoordinate = position;\\n }\\n}\"]),o=i([\"precision highp float;\\n#define GLSLIFY 1\\n\\nbool outOfRange(float a, float b, float p) {\\n return ((p > max(a, b)) || \\n (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n return (outOfRange(a.x, b.x, p.x) ||\\n outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n return (outOfRange(a.x, b.x, p.x) ||\\n outOfRange(a.y, b.y, p.y) ||\\n outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nattribute vec3 position;\\nattribute vec4 color;\\nattribute vec2 glyph;\\nattribute vec4 id;\\n\\nuniform mat4 model, view, projection;\\nuniform vec2 screenSize;\\nuniform vec3 clipBounds[2];\\nuniform float highlightScale, pixelRatio;\\nuniform vec4 highlightId;\\n\\nvarying vec4 interpColor;\\nvarying vec4 pickId;\\nvarying vec3 dataCoordinate;\\n\\nvoid main() {\\n if (outOfRange(clipBounds[0], clipBounds[1], position)) {\\n\\n gl_Position = vec4(0,0,0,0);\\n } else {\\n float scale = pixelRatio;\\n if(distance(highlightId.bgr, id.bgr) < 0.001) {\\n scale *= highlightScale;\\n }\\n\\n vec4 worldPosition = model * vec4(position, 1.0);\\n vec4 viewPosition = view * worldPosition;\\n vec4 clipPosition = projection * viewPosition;\\n clipPosition /= clipPosition.w;\\n\\n gl_Position = clipPosition + vec4(screenSize * scale * vec2(glyph.x, -glyph.y), 0.0, 0.0);\\n interpColor = color;\\n pickId = id;\\n dataCoordinate = position;\\n }\\n}\"]),s=i([\"precision highp float;\\n#define GLSLIFY 1\\n\\nbool outOfRange(float a, float b, float p) {\\n return ((p > max(a, b)) || \\n (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n return (outOfRange(a.x, b.x, p.x) ||\\n outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n return (outOfRange(a.x, b.x, p.x) ||\\n outOfRange(a.y, b.y, p.y) ||\\n outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nattribute vec3 position;\\nattribute vec4 color;\\nattribute vec2 glyph;\\nattribute vec4 id;\\n\\nuniform float highlightScale;\\nuniform vec4 highlightId;\\nuniform vec3 axes[2];\\nuniform mat4 model, view, projection;\\nuniform vec2 screenSize;\\nuniform vec3 clipBounds[2];\\nuniform float scale, pixelRatio;\\n\\nvarying vec4 interpColor;\\nvarying vec4 pickId;\\nvarying vec3 dataCoordinate;\\n\\nvoid main() {\\n if (outOfRange(clipBounds[0], clipBounds[1], position)) {\\n\\n gl_Position = vec4(0,0,0,0);\\n } else {\\n float lscale = pixelRatio * scale;\\n if(distance(highlightId, id) < 0.0001) {\\n lscale *= highlightScale;\\n }\\n\\n vec4 clipCenter = projection * view * model * vec4(position, 1);\\n vec3 dataPosition = position + 0.5*lscale*(axes[0] * glyph.x + axes[1] * glyph.y) * clipCenter.w * screenSize.y;\\n vec4 clipPosition = projection * view * model * vec4(dataPosition, 1);\\n\\n gl_Position = clipPosition;\\n interpColor = color;\\n pickId = id;\\n dataCoordinate = dataPosition;\\n }\\n}\\n\"]),l=i([\"precision highp float;\\n#define GLSLIFY 1\\n\\nbool outOfRange(float a, float b, float p) {\\n return ((p > max(a, b)) || \\n (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n return (outOfRange(a.x, b.x, p.x) ||\\n outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n return (outOfRange(a.x, b.x, p.x) ||\\n outOfRange(a.y, b.y, p.y) ||\\n outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nuniform vec3 fragClipBounds[2];\\nuniform float opacity;\\n\\nvarying vec4 interpColor;\\nvarying vec3 dataCoordinate;\\n\\nvoid main() {\\n if (\\n outOfRange(fragClipBounds[0], fragClipBounds[1], dataCoordinate) ||\\n interpColor.a * opacity == 0.\\n ) discard;\\n gl_FragColor = interpColor * opacity;\\n}\\n\"]),c=i([\"precision highp float;\\n#define GLSLIFY 1\\n\\nbool outOfRange(float a, float b, float p) {\\n return ((p > max(a, b)) || \\n (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n return (outOfRange(a.x, b.x, p.x) ||\\n outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n return (outOfRange(a.x, b.x, p.x) ||\\n outOfRange(a.y, b.y, p.y) ||\\n outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nuniform vec3 fragClipBounds[2];\\nuniform float pickGroup;\\n\\nvarying vec4 pickId;\\nvarying vec3 dataCoordinate;\\n\\nvoid main() {\\n if (outOfRange(fragClipBounds[0], fragClipBounds[1], dataCoordinate)) discard;\\n\\n gl_FragColor = vec4(pickGroup, pickId.bgr);\\n}\"]),u=[{name:\"position\",type:\"vec3\"},{name:\"color\",type:\"vec4\"},{name:\"glyph\",type:\"vec2\"},{name:\"id\",type:\"vec4\"}],f={vertex:a,fragment:l,attributes:u},h={vertex:o,fragment:l,attributes:u},p={vertex:s,fragment:l,attributes:u},d={vertex:a,fragment:c,attributes:u},m={vertex:o,fragment:c,attributes:u},g={vertex:s,fragment:c,attributes:u};function v(t,e){var r=n(t,e),i=r.attributes;return i.position.location=0,i.color.location=1,i.glyph.location=2,i.id.location=3,r}r.createPerspective=function(t){return v(t,f)},r.createOrtho=function(t){return v(t,h)},r.createProject=function(t){return v(t,p)},r.createPickPerspective=function(t){return v(t,d)},r.createPickOrtho=function(t){return v(t,m)},r.createPickProject=function(t){return v(t,g)}},{\"gl-shader\":132,glslify:231}],128:[function(t,e,r){\"use strict\";var n=t(\"is-string-blank\"),i=t(\"gl-buffer\"),a=t(\"gl-vao\"),o=t(\"typedarray-pool\"),s=t(\"gl-mat4/multiply\"),l=t(\"./lib/shaders\"),c=t(\"./lib/glyphs\"),u=t(\"./lib/get-simple-string\"),f=[1,0,0,0,0,1,0,0,0,0,1,0,0,0,0,1];function h(t,e){var r=t[0],n=t[1],i=t[2],a=t[3];return t[0]=e[0]*r+e[4]*n+e[8]*i+e[12]*a,t[1]=e[1]*r+e[5]*n+e[9]*i+e[13]*a,t[2]=e[2]*r+e[6]*n+e[10]*i+e[14]*a,t[3]=e[3]*r+e[7]*n+e[11]*i+e[15]*a,t}function p(t,e,r,n){return h(n,n),h(n,n),h(n,n)}function d(t,e){this.index=t,this.dataCoordinate=this.position=e}function m(t){return!0===t||t>1?1:t}function g(t,e,r,n,i,a,o,s,l,c,u,f){this.gl=t,this.pixelRatio=1,this.shader=e,this.orthoShader=r,this.projectShader=n,this.pointBuffer=i,this.colorBuffer=a,this.glyphBuffer=o,this.idBuffer=s,this.vao=l,this.vertexCount=0,this.lineVertexCount=0,this.opacity=1,this.hasAlpha=!1,this.lineWidth=0,this.projectScale=[2/3,2/3,2/3],this.projectOpacity=[1,1,1],this.projectHasAlpha=!1,this.pickId=0,this.pickPerspectiveShader=c,this.pickOrthoShader=u,this.pickProjectShader=f,this.points=[],this._selectResult=new d(0,[0,0,0]),this.useOrtho=!0,this.bounds=[[1/0,1/0,1/0],[-1/0,-1/0,-1/0]],this.axesProject=[!0,!0,!0],this.axesBounds=[[-1/0,-1/0,-1/0],[1/0,1/0,1/0]],this.highlightId=[1,1,1,1],this.highlightScale=2,this.clipBounds=[[-1/0,-1/0,-1/0],[1/0,1/0,1/0]],this.dirty=!0}e.exports=function(t){var e=t.gl,r=l.createPerspective(e),n=l.createOrtho(e),o=l.createProject(e),s=l.createPickPerspective(e),c=l.createPickOrtho(e),u=l.createPickProject(e),f=i(e),h=i(e),p=i(e),d=i(e),m=a(e,[{buffer:f,size:3,type:e.FLOAT},{buffer:h,size:4,type:e.FLOAT},{buffer:p,size:2,type:e.FLOAT},{buffer:d,size:4,type:e.UNSIGNED_BYTE,normalized:!0}]),v=new g(e,r,n,o,f,h,p,d,m,s,c,u);return v.update(t),v};var v=g.prototype;v.pickSlots=1,v.setPickBase=function(t){this.pickId=t},v.isTransparent=function(){if(this.hasAlpha)return!0;for(var t=0;t<3;++t)if(this.axesProject[t]&&this.projectHasAlpha)return!0;return!1},v.isOpaque=function(){if(!this.hasAlpha)return!0;for(var t=0;t<3;++t)if(this.axesProject[t]&&!this.projectHasAlpha)return!0;return!1};var y=[0,0],x=[0,0,0],b=[0,0,0],_=[0,0,0,1],w=[0,0,0,1],T=f.slice(),k=[0,0,0],A=[[0,0,0],[0,0,0]];function M(t){return t[0]=t[1]=t[2]=0,t}function S(t,e){return t[0]=e[0],t[1]=e[1],t[2]=e[2],t[3]=1,t}function E(t,e,r,n){return t[0]=e[0],t[1]=e[1],t[2]=e[2],t[r]=n,t}function L(t,e,r,n){var i,a=e.axesProject,o=e.gl,l=t.uniforms,c=r.model||f,u=r.view||f,h=r.projection||f,d=e.axesBounds,m=function(t){for(var e=A,r=0;r<2;++r)for(var n=0;n<3;++n)e[r][n]=Math.max(Math.min(t[r][n],1e8),-1e8);return e}(e.clipBounds);i=e.axes&&e.axes.lastCubeProps?e.axes.lastCubeProps.axis:[1,1,1],y[0]=2/o.drawingBufferWidth,y[1]=2/o.drawingBufferHeight,t.bind(),l.view=u,l.projection=h,l.screenSize=y,l.highlightId=e.highlightId,l.highlightScale=e.highlightScale,l.clipBounds=m,l.pickGroup=e.pickId/255,l.pixelRatio=n;for(var g=0;g<3;++g)if(a[g]){l.scale=e.projectScale[g],l.opacity=e.projectOpacity[g];for(var v=T,L=0;L<16;++L)v[L]=0;for(L=0;L<4;++L)v[5*L]=1;v[5*g]=0,i[g]<0?v[12+g]=d[0][g]:v[12+g]=d[1][g],s(v,c,v),l.model=v;var C=(g+1)%3,P=(g+2)%3,I=M(x),O=M(b);I[C]=1,O[P]=1;var z=p(0,0,0,S(_,I)),D=p(0,0,0,S(w,O));if(Math.abs(z[1])>Math.abs(D[1])){var R=z;z=D,D=R,R=I,I=O,O=R;var F=C;C=P,P=F}z[0]<0&&(I[C]=-1),D[1]>0&&(O[P]=-1);var B=0,N=0;for(L=0;L<4;++L)B+=Math.pow(c[4*C+L],2),N+=Math.pow(c[4*P+L],2);I[C]/=Math.sqrt(B),O[P]/=Math.sqrt(N),l.axes[0]=I,l.axes[1]=O,l.fragClipBounds[0]=E(k,m[0],g,-1e8),l.fragClipBounds[1]=E(k,m[1],g,1e8),e.vao.bind(),e.vao.draw(o.TRIANGLES,e.vertexCount),e.lineWidth>0&&(o.lineWidth(e.lineWidth*n),e.vao.draw(o.LINES,e.lineVertexCount,e.vertexCount)),e.vao.unbind()}}var C=[[-1e8,-1e8,-1e8],[1e8,1e8,1e8]];function P(t,e,r,n,i,a,o){var s=r.gl;if((a===r.projectHasAlpha||o)&&L(e,r,n,i),a===r.hasAlpha||o){t.bind();var l=t.uniforms;l.model=n.model||f,l.view=n.view||f,l.projection=n.projection||f,y[0]=2/s.drawingBufferWidth,y[1]=2/s.drawingBufferHeight,l.screenSize=y,l.highlightId=r.highlightId,l.highlightScale=r.highlightScale,l.fragClipBounds=C,l.clipBounds=r.axes.bounds,l.opacity=r.opacity,l.pickGroup=r.pickId/255,l.pixelRatio=i,r.vao.bind(),r.vao.draw(s.TRIANGLES,r.vertexCount),r.lineWidth>0&&(s.lineWidth(r.lineWidth*i),r.vao.draw(s.LINES,r.lineVertexCount,r.vertexCount)),r.vao.unbind()}}function I(t,e,r,i){var a;a=Array.isArray(t)?e<t.length?t[e]:void 0:t,a=u(a);var o=!0;n(a)&&(a=\"\\u25bc\",o=!1);var s=c(a,r,i);return{mesh:s[0],lines:s[1],bounds:s[2],visible:o}}v.draw=function(t){P(this.useOrtho?this.orthoShader:this.shader,this.projectShader,this,t,this.pixelRatio,!1,!1)},v.drawTransparent=function(t){P(this.useOrtho?this.orthoShader:this.shader,this.projectShader,this,t,this.pixelRatio,!0,!1)},v.drawPick=function(t){P(this.useOrtho?this.pickOrthoShader:this.pickPerspectiveShader,this.pickProjectShader,this,t,1,!0,!0)},v.pick=function(t){if(!t)return null;if(t.id!==this.pickId)return null;var e=t.value[2]+(t.value[1]<<8)+(t.value[0]<<16);if(e>=this.pointCount||e<0)return null;var r=this.points[e],n=this._selectResult;n.index=e;for(var i=0;i<3;++i)n.position[i]=n.dataCoordinate[i]=r[i];return n},v.highlight=function(t){if(t){var e=t.index,r=255&e,n=e>>8&255,i=e>>16&255;this.highlightId=[r/255,n/255,i/255,0]}else this.highlightId=[1,1,1,1]},v.update=function(t){if(\"perspective\"in(t=t||{})&&(this.useOrtho=!t.perspective),\"orthographic\"in 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i=0|Math.min(Math.max(t-r,0),n[0]),o=0|Math.min(Math.max(t+r,0),n[0]),l=0|Math.min(Math.max(e-r,0),n[1]),c=0|Math.min(Math.max(e+r,0),n[1]);if(o<=i||c<=l)return null;var u=[o-i,c-l],f=a(this.buffer,[u[0],u[1],4],[4,4*n[0],1],4*(i+n[0]*l)),h=function(t,e,r){for(var n=1e8,i=-1,a=-1,o=t.shape[0],s=t.shape[1],l=0;l<o;l++)for(var c=0;c<s;c++){var u=t.get(l,c,0),f=t.get(l,c,1),h=t.get(l,c,2),p=t.get(l,c,3);if(u<255||f<255||h<255||p<255){var d=e-l,m=r-c,g=d*d+m*m;g<n&&(n=g,i=l,a=c)}}return[i,a,n]}(f.hi(u[0],u[1],1),r,r),p=h[0],d=h[1];return p<0||Math.pow(this.radius,2)<h[2]?null:new s(p+i|0,d+l|0,f.get(p,d,0),[f.get(p,d,1),f.get(p,d,2),f.get(p,d,3)],Math.sqrt(h[2]))},c.dispose=function(){this.gl&&(this.fbo.dispose(),i.free(this.buffer),this.gl=null,this._readTimeout&&clearTimeout(this._readTimeout))}},{\"bit-twiddle\":32,\"gl-fbo\":86,ndarray:259,\"typedarray-pool\":308}],132:[function(t,e,r){\"use strict\";var 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w=c[y];if(w.type.indexOf(\"mat\")>=0){for(var T=0|w.type.charAt(w.type.length-1),k=new Array(T),A=0;A<T;++A)k[A]=_.length,b.push(w.name+\"[\"+A+\"]\"),\"number\"==typeof w.location?_.push(w.location+A):Array.isArray(w.location)&&w.location.length===T&&\"number\"==typeof w.location[A]?_.push(0|w.location[A]):_.push(-1);x.push({name:w.name,type:w.type,locations:k})}else x.push({name:w.name,type:w.type,locations:[_.length]}),b.push(w.name),\"number\"==typeof w.location?_.push(0|w.location):_.push(-1)}var M=0;for(y=0;y<_.length;++y)if(_[y]<0){for(;_.indexOf(M)>=0;)M+=1;_[y]=M}var S=new Array(r.length);function E(){h.program=o.program(p,h._vref,h._fref,b,_);for(var t=0;t<r.length;++t)S[t]=p.getUniformLocation(h.program,r[t].name)}E(),h._relink=E,h.types={uniforms:a(r),attributes:a(c)},h.attributes=i(p,h,x,_),Object.defineProperty(h,\"uniforms\",n(p,h,r,S))},e.exports=function(t,e,r,n,i){var a=new c(t);return 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to 8.\\n//\\nvec3 getTubePosition(vec3 d, float index, out vec3 normal) {\\n float segmentCount = 8.0;\\n\\n float angle = 2.0 * 3.14159 * (index / segmentCount);\\n\\n vec3 u = getOrthogonalVector(d);\\n vec3 v = normalize(cross(u, d));\\n\\n vec3 x = u * cos(angle) * length(d);\\n vec3 y = v * sin(angle) * length(d);\\n vec3 v3 = x + y;\\n\\n normal = normalize(v3);\\n\\n return v3;\\n}\\n\\nattribute vec4 vector;\\nattribute vec4 color, position;\\nattribute vec2 uv;\\n\\nuniform float vectorScale, tubeScale;\\nuniform mat4 model, view, projection, inverseModel;\\nuniform vec3 eyePosition, lightPosition;\\n\\nvarying vec3 f_normal, f_lightDirection, f_eyeDirection, f_data, f_position;\\nvarying vec4 f_color;\\nvarying vec2 f_uv;\\n\\nvoid main() {\\n // Scale the vector magnitude to stay constant with\\n // model & view changes.\\n vec3 normal;\\n vec3 XYZ = getTubePosition(mat3(model) * (tubeScale * vector.w * normalize(vector.xyz)), position.w, normal);\\n vec4 tubePosition = model * vec4(position.xyz, 1.0) + vec4(XYZ, 0.0);\\n\\n //Lighting geometry parameters\\n vec4 cameraCoordinate = view * tubePosition;\\n cameraCoordinate.xyz /= cameraCoordinate.w;\\n f_lightDirection = lightPosition - cameraCoordinate.xyz;\\n f_eyeDirection = eyePosition - cameraCoordinate.xyz;\\n f_normal = normalize((vec4(normal, 0.0) * inverseModel).xyz);\\n\\n // vec4 m_position = model * vec4(tubePosition, 1.0);\\n vec4 t_position = view * tubePosition;\\n gl_Position = projection * t_position;\\n\\n f_color = color;\\n f_data = tubePosition.xyz;\\n f_position = position.xyz;\\n f_uv = uv;\\n}\\n\"]),a=n([\"#extension GL_OES_standard_derivatives : enable\\n\\nprecision highp float;\\n#define GLSLIFY 1\\n\\nfloat beckmannDistribution(float x, float roughness) {\\n float NdotH = max(x, 0.0001);\\n float cos2Alpha = NdotH * NdotH;\\n float tan2Alpha = (cos2Alpha - 1.0) / cos2Alpha;\\n float roughness2 = roughness * roughness;\\n float denom = 3.141592653589793 * roughness2 * cos2Alpha * cos2Alpha;\\n return exp(tan2Alpha / roughness2) / denom;\\n}\\n\\nfloat cookTorranceSpecular(\\n vec3 lightDirection,\\n vec3 viewDirection,\\n vec3 surfaceNormal,\\n float roughness,\\n float fresnel) {\\n\\n float VdotN = max(dot(viewDirection, surfaceNormal), 0.0);\\n float LdotN = max(dot(lightDirection, surfaceNormal), 0.0);\\n\\n //Half angle vector\\n vec3 H = normalize(lightDirection + viewDirection);\\n\\n //Geometric term\\n float NdotH = max(dot(surfaceNormal, H), 0.0);\\n float VdotH = max(dot(viewDirection, H), 0.000001);\\n float LdotH = max(dot(lightDirection, H), 0.000001);\\n float G1 = (2.0 * NdotH * VdotN) / VdotH;\\n float G2 = (2.0 * NdotH * LdotN) / LdotH;\\n float G = min(1.0, min(G1, G2));\\n \\n //Distribution term\\n float D = beckmannDistribution(NdotH, roughness);\\n\\n //Fresnel term\\n float F = pow(1.0 - VdotN, fresnel);\\n\\n //Multiply terms and done\\n return G * F * D / max(3.14159265 * VdotN, 0.000001);\\n}\\n\\nbool outOfRange(float a, float b, float p) {\\n return ((p > max(a, b)) || \\n (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n return (outOfRange(a.x, b.x, p.x) ||\\n outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n return (outOfRange(a.x, b.x, p.x) ||\\n outOfRange(a.y, b.y, p.y) ||\\n outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nuniform vec3 clipBounds[2];\\nuniform float roughness, fresnel, kambient, kdiffuse, kspecular, opacity;\\nuniform sampler2D texture;\\n\\nvarying vec3 f_normal, f_lightDirection, f_eyeDirection, f_data, f_position;\\nvarying vec4 f_color;\\nvarying vec2 f_uv;\\n\\nvoid main() {\\n if (outOfRange(clipBounds[0], clipBounds[1], f_position)) discard;\\n vec3 N = normalize(f_normal);\\n vec3 L = normalize(f_lightDirection);\\n vec3 V = normalize(f_eyeDirection);\\n\\n if(gl_FrontFacing) {\\n N = -N;\\n }\\n\\n float specular = min(1.0, max(0.0, cookTorranceSpecular(L, V, N, roughness, fresnel)));\\n float diffuse = min(kambient + kdiffuse * max(dot(N, L), 0.0), 1.0);\\n\\n vec4 surfaceColor = f_color * texture2D(texture, f_uv);\\n vec4 litColor = surfaceColor.a * vec4(diffuse * surfaceColor.rgb + kspecular * vec3(1,1,1) * specular, 1.0);\\n\\n gl_FragColor = litColor * opacity;\\n}\\n\"]),o=n([\"precision highp float;\\n\\nprecision highp float;\\n#define GLSLIFY 1\\n\\nvec3 getOrthogonalVector(vec3 v) {\\n // Return up-vector for only-z vector.\\n // Return ax + by + cz = 0, a point that lies on the plane that has v as a normal and that isn't (0,0,0).\\n // From the above if-statement we have ||a|| > 0 U ||b|| > 0.\\n // Assign z = 0, x = -b, y = a:\\n // a*-b + b*a + c*0 = -ba + ba + 0 = 0\\n if (v.x*v.x > v.z*v.z || v.y*v.y > v.z*v.z) {\\n return normalize(vec3(-v.y, v.x, 0.0));\\n } else {\\n return normalize(vec3(0.0, v.z, -v.y));\\n }\\n}\\n\\n// Calculate the tube vertex and normal at the given index.\\n//\\n// The returned vertex is for a tube ring with its center at origin, radius of length(d), pointing in the direction of d.\\n//\\n// Each tube segment is made up of a ring of vertices.\\n// These vertices are used to make up the triangles of the tube by connecting them together in the vertex array.\\n// The indexes of tube segments run from 0 to 8.\\n//\\nvec3 getTubePosition(vec3 d, float index, out vec3 normal) {\\n float segmentCount = 8.0;\\n\\n float angle = 2.0 * 3.14159 * (index / segmentCount);\\n\\n vec3 u = getOrthogonalVector(d);\\n vec3 v = normalize(cross(u, d));\\n\\n vec3 x = u * cos(angle) * length(d);\\n vec3 y = v * sin(angle) * length(d);\\n vec3 v3 = x + y;\\n\\n normal = normalize(v3);\\n\\n return v3;\\n}\\n\\nattribute vec4 vector;\\nattribute vec4 position;\\nattribute vec4 id;\\n\\nuniform mat4 model, view, projection;\\nuniform float tubeScale;\\n\\nvarying vec3 f_position;\\nvarying vec4 f_id;\\n\\nvoid main() {\\n vec3 normal;\\n vec3 XYZ = getTubePosition(mat3(model) * (tubeScale * vector.w * normalize(vector.xyz)), position.w, normal);\\n vec4 tubePosition = model * vec4(position.xyz, 1.0) + vec4(XYZ, 0.0);\\n\\n gl_Position = projection * view * tubePosition;\\n f_id = id;\\n f_position = position.xyz;\\n}\\n\"]),s=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nbool outOfRange(float a, float b, float p) {\\n return ((p > max(a, b)) || \\n (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n return (outOfRange(a.x, b.x, p.x) ||\\n outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n return (outOfRange(a.x, b.x, p.x) ||\\n outOfRange(a.y, b.y, p.y) ||\\n outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nuniform vec3 clipBounds[2];\\nuniform float pickId;\\n\\nvarying vec3 f_position;\\nvarying vec4 f_id;\\n\\nvoid main() {\\n if (outOfRange(clipBounds[0], clipBounds[1], f_position)) discard;\\n\\n gl_FragColor = vec4(pickId, f_id.xyz);\\n}\"]);r.meshShader={vertex:i,fragment:a,attributes:[{name:\"position\",type:\"vec4\"},{name:\"color\",type:\"vec4\"},{name:\"uv\",type:\"vec2\"},{name:\"vector\",type:\"vec4\"}]},r.pickShader={vertex:o,fragment:s,attributes:[{name:\"position\",type:\"vec4\"},{name:\"id\",type:\"vec4\"},{name:\"vector\",type:\"vec4\"}]}},{glslify:231}],143:[function(t,e,r){\"use strict\";var n=t(\"gl-vec3\"),i=t(\"gl-vec4\"),a=[\"xyz\",\"xzy\",\"yxz\",\"yzx\",\"zxy\",\"zyx\"],o=function(t,e,r,a){for(var o=0,s=0;s<t.length;s++)for(var l=t[s].velocities,c=0;c<l.length;c++)o=Math.max(o,n.length(l[c]));var u=t.map((function(t){return function(t,e,r,a){for(var o=t.points,s=t.velocities,l=t.divergences,c=[],u=[],f=[],h=[],p=[],d=[],m=0,g=0,v=i.create(),y=i.create(),x=0;x<o.length;x++){var b=o[x],_=s[x],w=l[x];0===e&&(w=.05*r),g=n.length(_)/a,v=i.create(),n.copy(v,_),v[3]=w;for(var T=0;T<8;T++)p[T]=[b[0],b[1],b[2],T];if(h.length>0)for(T=0;T<8;T++){var k=(T+1)%8;c.push(h[T],p[T],p[k],p[k],h[k],h[T]),f.push(y,v,v,v,y,y),d.push(m,g,g,g,m,m);var A=c.length;u.push([A-6,A-5,A-4],[A-3,A-2,A-1])}var M=h;h=p,p=M;var S=y;y=v,v=S;var E=m;m=g,g=E}return{positions:c,cells:u,vectors:f,vertexIntensity:d}}(t,r,a,o)})),f=[],h=[],p=[],d=[];for(s=0;s<u.length;s++){var m=u[s],g=f.length;f=f.concat(m.positions),p=p.concat(m.vectors),d=d.concat(m.vertexIntensity);for(c=0;c<m.cells.length;c++){var v=m.cells[c],y=[];h.push(y);for(var x=0;x<v.length;x++)y.push(v[x]+g)}}return{positions:f,cells:h,vectors:p,vertexIntensity:d,colormap:e}},s=function(t,e){var r,n=t.length;for(r=0;r<n;r++){var i=t[r];if(i===e)return r;if(i>e)return r-1}return r},l=function(t,e,r){return t<e?e:t>r?r:t},c=function(t){var e=1/0;t.sort((function(t,e){return t-e}));for(var r=t.length,n=1;n<r;n++){var i=Math.abs(t[n]-t[n-1]);i<e&&(e=i)}return e};e.exports=function(t,e){var r=t.startingPositions,i=t.maxLength||1e3,u=t.tubeSize||1,f=t.absoluteTubeSize,h=t.gridFill||\"+x+y+z\",p={};-1!==h.indexOf(\"-x\")&&(p.reversedX=!0),-1!==h.indexOf(\"-y\")&&(p.reversedY=!0),-1!==h.indexOf(\"-z\")&&(p.reversedZ=!0),p.filled=a.indexOf(h.replace(/-/g,\"\").replace(/\\+/g,\"\"));var d=t.getVelocity||function(e){return function(t,e,r){var i=e.vectors,a=e.meshgrid,o=t[0],c=t[1],u=t[2],f=a[0].length,h=a[1].length,p=a[2].length,d=s(a[0],o),m=s(a[1],c),g=s(a[2],u),v=d+1,y=m+1,x=g+1;if(d=l(d,0,f-1),v=l(v,0,f-1),m=l(m,0,h-1),y=l(y,0,h-1),g=l(g,0,p-1),x=l(x,0,p-1),d<0||m<0||g<0||v>f-1||y>h-1||x>p-1)return n.create();var b,_,w,T,k,A,M=a[0][d],S=a[0][v],E=a[1][m],L=a[1][y],C=a[2][g],P=(o-M)/(S-M),I=(c-E)/(L-E),O=(u-C)/(a[2][x]-C);switch(isFinite(P)||(P=.5),isFinite(I)||(I=.5),isFinite(O)||(O=.5),r.reversedX&&(d=f-1-d,v=f-1-v),r.reversedY&&(m=h-1-m,y=h-1-y),r.reversedZ&&(g=p-1-g,x=p-1-x),r.filled){case 5:k=g,A=x,w=m*p,T=y*p,b=d*p*h,_=v*p*h;break;case 4:k=g,A=x,b=d*p,_=v*p,w=m*p*f,T=y*p*f;break;case 3:w=m,T=y,k=g*h,A=x*h,b=d*h*p,_=v*h*p;break;case 2:w=m,T=y,b=d*h,_=v*h,k=g*h*f,A=x*h*f;break;case 1:b=d,_=v,k=g*f,A=x*f,w=m*f*p,T=y*f*p;break;default:b=d,_=v,w=m*f,T=y*f,k=g*f*h,A=x*f*h}var z=i[b+w+k],D=i[b+w+A],R=i[b+T+k],F=i[b+T+A],B=i[_+w+k],N=i[_+w+A],j=i[_+T+k],U=i[_+T+A],V=n.create(),H=n.create(),q=n.create(),G=n.create();n.lerp(V,z,B,P),n.lerp(H,D,N,P),n.lerp(q,R,j,P),n.lerp(G,F,U,P);var Y=n.create(),W=n.create();n.lerp(Y,V,q,I),n.lerp(W,H,G,I);var X=n.create();return n.lerp(X,Y,W,O),X}(e,t,p)},m=t.getDivergence||function(t,e){var r=n.create(),i=1e-4;n.add(r,t,[i,0,0]);var a=d(r);n.subtract(a,a,e),n.scale(a,a,1/i),n.add(r,t,[0,i,0]);var o=d(r);n.subtract(o,o,e),n.scale(o,o,1/i),n.add(r,t,[0,0,i]);var s=d(r);return n.subtract(s,s,e),n.scale(s,s,1/i),n.add(r,a,o),n.add(r,r,s),r},g=[],v=e[0][0],y=e[0][1],x=e[0][2],b=e[1][0],_=e[1][1],w=e[1][2],T=function(t){var e=t[0],r=t[1],n=t[2];return!(e<v||e>b||r<y||r>_||n<x||n>w)},k=10*n.distance(e[0],e[1])/i,A=k*k,M=1,S=0,E=r.length;E>1&&(M=function(t){for(var e=[],r=[],n=[],i={},a={},o={},s=t.length,l=0;l<s;l++){var u=t[l],f=u[0],h=u[1],p=u[2];i[f]||(e.push(f),i[f]=!0),a[h]||(r.push(h),a[h]=!0),o[p]||(n.push(p),o[p]=!0)}var d=c(e),m=c(r),g=c(n),v=Math.min(d,m,g);return isFinite(v)?v:1}(r));for(var L=0;L<E;L++){var C=n.create();n.copy(C,r[L]);var P=[C],I=[],O=d(C),z=C;I.push(O);var D=[],R=m(C,O),F=n.length(R);isFinite(F)&&F>S&&(S=F),D.push(F),g.push({points:P,velocities:I,divergences:D});for(var B=0;B<100*i&&P.length<i&&T(C);){B++;var N=n.clone(O),j=n.squaredLength(N);if(0===j)break;if(j>A&&n.scale(N,N,k/Math.sqrt(j)),n.add(N,N,C),O=d(N),n.squaredDistance(z,N)-A>-1e-4*A){P.push(N),z=N,I.push(O);R=m(N,O),F=n.length(R);isFinite(F)&&F>S&&(S=F),D.push(F)}C=N}}var U=o(g,t.colormap,S,M);return f?U.tubeScale=f:(0===S&&(S=1),U.tubeScale=.5*u*M/S),U};var u=t(\"./lib/shaders\"),f=t(\"gl-cone3d\").createMesh;e.exports.createTubeMesh=function(t,e){return f(t,e,{shaders:u,traceType:\"streamtube\"})}},{\"./lib/shaders\":142,\"gl-cone3d\":79,\"gl-vec3\":169,\"gl-vec4\":205}],144:[function(t,e,r){var n=t(\"gl-shader\"),i=t(\"glslify\"),a=i([\"precision highp float;\\n#define GLSLIFY 1\\n\\nattribute vec4 uv;\\nattribute vec3 f;\\nattribute vec3 normal;\\n\\nuniform vec3 objectOffset;\\nuniform mat4 model, view, projection, inverseModel;\\nuniform vec3 lightPosition, eyePosition;\\nuniform sampler2D colormap;\\n\\nvarying float value, kill;\\nvarying vec3 worldCoordinate;\\nvarying vec2 planeCoordinate;\\nvarying vec3 lightDirection, eyeDirection, surfaceNormal;\\nvarying vec4 vColor;\\n\\nvoid main() {\\n vec3 localCoordinate = vec3(uv.zw, f.x);\\n worldCoordinate = objectOffset + localCoordinate;\\n vec4 worldPosition = model * vec4(worldCoordinate, 1.0);\\n vec4 clipPosition = projection * view * worldPosition;\\n gl_Position = clipPosition;\\n kill = f.y;\\n value = f.z;\\n planeCoordinate = uv.xy;\\n\\n vColor = texture2D(colormap, vec2(value, value));\\n\\n //Lighting geometry parameters\\n vec4 cameraCoordinate = view * worldPosition;\\n cameraCoordinate.xyz /= cameraCoordinate.w;\\n lightDirection = lightPosition - cameraCoordinate.xyz;\\n eyeDirection = eyePosition - cameraCoordinate.xyz;\\n surfaceNormal = normalize((vec4(normal,0) * inverseModel).xyz);\\n}\\n\"]),o=i([\"precision highp float;\\n#define GLSLIFY 1\\n\\nfloat beckmannDistribution(float x, float roughness) {\\n float NdotH = max(x, 0.0001);\\n float cos2Alpha = NdotH * NdotH;\\n float tan2Alpha = (cos2Alpha - 1.0) / cos2Alpha;\\n float roughness2 = roughness * roughness;\\n float denom = 3.141592653589793 * roughness2 * cos2Alpha * cos2Alpha;\\n return exp(tan2Alpha / roughness2) / denom;\\n}\\n\\nfloat beckmannSpecular(\\n vec3 lightDirection,\\n vec3 viewDirection,\\n vec3 surfaceNormal,\\n float roughness) {\\n return beckmannDistribution(dot(surfaceNormal, normalize(lightDirection + viewDirection)), roughness);\\n}\\n\\nbool outOfRange(float a, float b, float p) {\\n return ((p > max(a, b)) || \\n (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n return (outOfRange(a.x, b.x, p.x) ||\\n outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n return (outOfRange(a.x, b.x, p.x) ||\\n outOfRange(a.y, b.y, p.y) ||\\n outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nuniform vec3 lowerBound, upperBound;\\nuniform float contourTint;\\nuniform vec4 contourColor;\\nuniform sampler2D colormap;\\nuniform vec3 clipBounds[2];\\nuniform float roughness, fresnel, kambient, kdiffuse, kspecular, opacity;\\nuniform float vertexColor;\\n\\nvarying float value, kill;\\nvarying vec3 worldCoordinate;\\nvarying vec3 lightDirection, eyeDirection, surfaceNormal;\\nvarying vec4 vColor;\\n\\nvoid main() {\\n if (\\n kill > 0.0 ||\\n vColor.a == 0.0 ||\\n outOfRange(clipBounds[0], clipBounds[1], worldCoordinate)\\n ) discard;\\n\\n vec3 N = normalize(surfaceNormal);\\n vec3 V = normalize(eyeDirection);\\n vec3 L = normalize(lightDirection);\\n\\n if(gl_FrontFacing) {\\n N = -N;\\n }\\n\\n float specular = max(beckmannSpecular(L, V, N, roughness), 0.);\\n float diffuse = min(kambient + kdiffuse * max(dot(N, L), 0.0), 1.0);\\n\\n //decide how to interpolate color \\u2014 in vertex or in fragment\\n vec4 surfaceColor =\\n step(vertexColor, .5) * texture2D(colormap, vec2(value, value)) +\\n step(.5, vertexColor) * vColor;\\n\\n vec4 litColor = surfaceColor.a * vec4(diffuse * surfaceColor.rgb + kspecular * vec3(1,1,1) * specular, 1.0);\\n\\n gl_FragColor = mix(litColor, contourColor, contourTint) * opacity;\\n}\\n\"]),s=i([\"precision highp float;\\n#define GLSLIFY 1\\n\\nattribute vec4 uv;\\nattribute float f;\\n\\nuniform vec3 objectOffset;\\nuniform mat3 permutation;\\nuniform mat4 model, view, projection;\\nuniform float height, zOffset;\\nuniform sampler2D colormap;\\n\\nvarying float value, kill;\\nvarying vec3 worldCoordinate;\\nvarying vec2 planeCoordinate;\\nvarying vec3 lightDirection, eyeDirection, surfaceNormal;\\nvarying vec4 vColor;\\n\\nvoid main() {\\n vec3 dataCoordinate = permutation * vec3(uv.xy, height);\\n worldCoordinate = objectOffset + dataCoordinate;\\n vec4 worldPosition = model * vec4(worldCoordinate, 1.0);\\n\\n vec4 clipPosition = projection * view * worldPosition;\\n clipPosition.z += zOffset;\\n\\n gl_Position = clipPosition;\\n value = f + objectOffset.z;\\n kill = -1.0;\\n planeCoordinate = uv.zw;\\n\\n vColor = texture2D(colormap, vec2(value, value));\\n\\n //Don't do lighting for contours\\n surfaceNormal = vec3(1,0,0);\\n eyeDirection = vec3(0,1,0);\\n lightDirection = vec3(0,0,1);\\n}\\n\"]),l=i([\"precision highp float;\\n#define GLSLIFY 1\\n\\nbool outOfRange(float a, float b, float p) {\\n return ((p > max(a, b)) || \\n (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n return (outOfRange(a.x, b.x, p.x) ||\\n outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n return (outOfRange(a.x, b.x, p.x) ||\\n outOfRange(a.y, b.y, p.y) ||\\n outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nuniform vec2 shape;\\nuniform vec3 clipBounds[2];\\nuniform float pickId;\\n\\nvarying float value, kill;\\nvarying vec3 worldCoordinate;\\nvarying vec2 planeCoordinate;\\nvarying vec3 surfaceNormal;\\n\\nvec2 splitFloat(float v) {\\n float vh = 255.0 * v;\\n float upper = floor(vh);\\n float lower = fract(vh);\\n return vec2(upper / 255.0, floor(lower * 16.0) / 16.0);\\n}\\n\\nvoid main() {\\n if ((kill > 0.0) ||\\n (outOfRange(clipBounds[0], clipBounds[1], worldCoordinate))) discard;\\n\\n vec2 ux = splitFloat(planeCoordinate.x / shape.x);\\n vec2 uy = splitFloat(planeCoordinate.y / shape.y);\\n gl_FragColor = vec4(pickId, ux.x, uy.x, ux.y + (uy.y/16.0));\\n}\\n\"]);r.createShader=function(t){var e=n(t,a,o,null,[{name:\"uv\",type:\"vec4\"},{name:\"f\",type:\"vec3\"},{name:\"normal\",type:\"vec3\"}]);return e.attributes.uv.location=0,e.attributes.f.location=1,e.attributes.normal.location=2,e},r.createPickShader=function(t){var e=n(t,a,l,null,[{name:\"uv\",type:\"vec4\"},{name:\"f\",type:\"vec3\"},{name:\"normal\",type:\"vec3\"}]);return e.attributes.uv.location=0,e.attributes.f.location=1,e.attributes.normal.location=2,e},r.createContourShader=function(t){var e=n(t,s,o,null,[{name:\"uv\",type:\"vec4\"},{name:\"f\",type:\"float\"}]);return e.attributes.uv.location=0,e.attributes.f.location=1,e},r.createPickContourShader=function(t){var e=n(t,s,l,null,[{name:\"uv\",type:\"vec4\"},{name:\"f\",type:\"float\"}]);return e.attributes.uv.location=0,e.attributes.f.location=1,e}},{\"gl-shader\":132,glslify:231}],145:[function(t,e,r){\"use strict\";e.exports=function(t){var e=t.gl,r=y(e),n=b(e),s=x(e),l=_(e),c=i(e),u=a(e,[{buffer:c,size:4,stride:40,offset:0},{buffer:c,size:3,stride:40,offset:16},{buffer:c,size:3,stride:40,offset:28}]),f=i(e),h=a(e,[{buffer:f,size:4,stride:20,offset:0},{buffer:f,size:1,stride:20,offset:16}]),p=i(e),d=a(e,[{buffer:p,size:2,type:e.FLOAT}]),m=o(e,1,256,e.RGBA,e.UNSIGNED_BYTE);m.minFilter=e.LINEAR,m.magFilter=e.LINEAR;var g=new M(e,[0,0],[[0,0,0],[0,0,0]],r,n,c,u,m,s,l,f,h,p,d,[0,0,0]),v={levels:[[],[],[]]};for(var w in t)v[w]=t[w];return v.colormap=v.colormap||\"jet\",g.update(v),g};var n=t(\"bit-twiddle\"),i=t(\"gl-buffer\"),a=t(\"gl-vao\"),o=t(\"gl-texture2d\"),s=t(\"typedarray-pool\"),l=t(\"colormap\"),c=t(\"ndarray-ops\"),u=t(\"ndarray-pack\"),f=t(\"ndarray\"),h=t(\"surface-nets\"),p=t(\"gl-mat4/multiply\"),d=t(\"gl-mat4/invert\"),m=t(\"binary-search-bounds\"),g=t(\"ndarray-gradient\"),v=t(\"./lib/shaders\"),y=v.createShader,x=v.createContourShader,b=v.createPickShader,_=v.createPickContourShader,w=[1,0,0,0,0,1,0,0,0,0,1,0,0,0,0,1],T=[[0,0],[0,1],[1,0],[1,1],[1,0],[0,1]],k=[[0,0,0,0,0,0,0,0,0],[0,0,0,0,0,0,0,0,0],[0,0,0,0,0,0,0,0,0]];function A(t,e,r,n,i){this.position=t,this.index=e,this.uv=r,this.level=n,this.dataCoordinate=i}!function(){for(var t=0;t<3;++t){var e=k[t],r=(t+2)%3;e[(t+1)%3+0]=1,e[r+3]=1,e[t+6]=1}}();function M(t,e,r,n,i,a,o,l,c,u,h,p,d,m,g){this.gl=t,this.shape=e,this.bounds=r,this.objectOffset=g,this.intensityBounds=[],this._shader=n,this._pickShader=i,this._coordinateBuffer=a,this._vao=o,this._colorMap=l,this._contourShader=c,this._contourPickShader=u,this._contourBuffer=h,this._contourVAO=p,this._contourOffsets=[[],[],[]],this._contourCounts=[[],[],[]],this._vertexCount=0,this._pickResult=new A([0,0,0],[0,0],[0,0],[0,0,0],[0,0,0]),this._dynamicBuffer=d,this._dynamicVAO=m,this._dynamicOffsets=[0,0,0],this._dynamicCounts=[0,0,0],this.contourWidth=[1,1,1],this.contourLevels=[[1],[1],[1]],this.contourTint=[0,0,0],this.contourColor=[[.5,.5,.5,1],[.5,.5,.5,1],[.5,.5,.5,1]],this.showContour=!0,this.showSurface=!0,this.enableHighlight=[!0,!0,!0],this.highlightColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.highlightTint=[1,1,1],this.highlightLevel=[-1,-1,-1],this.enableDynamic=[!0,!0,!0],this.dynamicLevel=[NaN,NaN,NaN],this.dynamicColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.dynamicTint=[1,1,1],this.dynamicWidth=[1,1,1],this.axesBounds=[[1/0,1/0,1/0],[-1/0,-1/0,-1/0]],this.surfaceProject=[!1,!1,!1],this.contourProject=[[!1,!1,!1],[!1,!1,!1],[!1,!1,!1]],this.colorBounds=[!1,!1],this._field=[f(s.mallocFloat(1024),[0,0]),f(s.mallocFloat(1024),[0,0]),f(s.mallocFloat(1024),[0,0])],this.pickId=1,this.clipBounds=[[-1/0,-1/0,-1/0],[1/0,1/0,1/0]],this.snapToData=!1,this.pixelRatio=1,this.opacity=1,this.lightPosition=[10,1e4,0],this.ambientLight=.8,this.diffuseLight=.8,this.specularLight=2,this.roughness=.5,this.fresnel=1.5,this.vertexColor=0,this.dirty=!0}var S=M.prototype;S.genColormap=function(t,e){var r=!1,n=u([l({colormap:t,nshades:256,format:\"rgba\"}).map((function(t,n){var i=e?function(t,e){if(!e)return 1;if(!e.length)return 1;for(var r=0;r<e.length;++r){if(e.length<2)return 1;if(e[r][0]===t)return e[r][1];if(e[r][0]>t&&r>0){var n=(e[r][0]-t)/(e[r][0]-e[r-1][0]);return e[r][1]*(1-n)+n*e[r-1][1]}}return 1}(n/255,e):t[3];return i<1&&(r=!0),[t[0],t[1],t[2],255*i]}))]);return c.divseq(n,255),this.hasAlphaScale=r,n},S.isTransparent=function(){return this.opacity<1||this.hasAlphaScale},S.isOpaque=function(){return!this.isTransparent()},S.pickSlots=1,S.setPickBase=function(t){this.pickId=t};var E=[0,0,0],L={showSurface:!1,showContour:!1,projections:[w.slice(),w.slice(),w.slice()],clipBounds:[[[0,0,0],[0,0,0]],[[0,0,0],[0,0,0]],[[0,0,0],[0,0,0]]]};function C(t,e){var r,n,i,a=e.axes&&e.axes.lastCubeProps.axis||E,o=e.showSurface,s=e.showContour;for(r=0;r<3;++r)for(o=o||e.surfaceProject[r],n=0;n<3;++n)s=s||e.contourProject[r][n];for(r=0;r<3;++r){var l=L.projections[r];for(n=0;n<16;++n)l[n]=0;for(n=0;n<4;++n)l[5*n]=1;l[5*r]=0,l[12+r]=e.axesBounds[+(a[r]>0)][r],p(l,t.model,l);var c=L.clipBounds[r];for(i=0;i<2;++i)for(n=0;n<3;++n)c[i][n]=t.clipBounds[i][n];c[0][r]=-1e8,c[1][r]=1e8}return L.showSurface=o,L.showContour=s,L}var P={model:w,view:w,projection:w,inverseModel:w.slice(),lowerBound:[0,0,0],upperBound:[0,0,0],colorMap:0,clipBounds:[[0,0,0],[0,0,0]],height:0,contourTint:0,contourColor:[0,0,0,1],permutation:[1,0,0,0,1,0,0,0,1],zOffset:-1e-4,objectOffset:[0,0,0],kambient:1,kdiffuse:1,kspecular:1,lightPosition:[1e3,1e3,1e3],eyePosition:[0,0,0],roughness:1,fresnel:1,opacity:1,vertexColor:0},I=w.slice(),O=[1,0,0,0,1,0,0,0,1];function z(t,e){t=t||{};var r=this.gl;r.disable(r.CULL_FACE),this._colorMap.bind(0);var n=P;n.model=t.model||w,n.view=t.view||w,n.projection=t.projection||w,n.lowerBound=[this.bounds[0][0],this.bounds[0][1],this.colorBounds[0]||this.bounds[0][2]],n.upperBound=[this.bounds[1][0],this.bounds[1][1],this.colorBounds[1]||this.bounds[1][2]],n.objectOffset=this.objectOffset,n.contourColor=this.contourColor[0],n.inverseModel=d(n.inverseModel,n.model);for(var i=0;i<2;++i)for(var a=n.clipBounds[i],o=0;o<3;++o)a[o]=Math.min(Math.max(this.clipBounds[i][o],-1e8),1e8);n.kambient=this.ambientLight,n.kdiffuse=this.diffuseLight,n.kspecular=this.specularLight,n.roughness=this.roughness,n.fresnel=this.fresnel,n.opacity=this.opacity,n.height=0,n.permutation=O,n.vertexColor=this.vertexColor;var s=I;for(p(s,n.view,n.model),p(s,n.projection,s),d(s,s),i=0;i<3;++i)n.eyePosition[i]=s[12+i]/s[15];var l=s[15];for(i=0;i<3;++i)l+=this.lightPosition[i]*s[4*i+3];for(i=0;i<3;++i){var c=s[12+i];for(o=0;o<3;++o)c+=s[4*o+i]*this.lightPosition[o];n.lightPosition[i]=c/l}var u=C(n,this);if(u.showSurface){for(this._shader.bind(),this._shader.uniforms=n,this._vao.bind(),this.showSurface&&this._vertexCount&&this._vao.draw(r.TRIANGLES,this._vertexCount),i=0;i<3;++i)this.surfaceProject[i]&&this.vertexCount&&(this._shader.uniforms.model=u.projections[i],this._shader.uniforms.clipBounds=u.clipBounds[i],this._vao.draw(r.TRIANGLES,this._vertexCount));this._vao.unbind()}if(u.showContour){var f=this._contourShader;n.kambient=1,n.kdiffuse=0,n.kspecular=0,n.opacity=1,f.bind(),f.uniforms=n;var h=this._contourVAO;for(h.bind(),i=0;i<3;++i)for(f.uniforms.permutation=k[i],r.lineWidth(this.contourWidth[i]*this.pixelRatio),o=0;o<this.contourLevels[i].length;++o)o===this.highlightLevel[i]?(f.uniforms.contourColor=this.highlightColor[i],f.uniforms.contourTint=this.highlightTint[i]):0!==o&&o-1!==this.highlightLevel[i]||(f.uniforms.contourColor=this.contourColor[i],f.uniforms.contourTint=this.contourTint[i]),this._contourCounts[i][o]&&(f.uniforms.height=this.contourLevels[i][o],h.draw(r.LINES,this._contourCounts[i][o],this._contourOffsets[i][o]));for(i=0;i<3;++i)for(f.uniforms.model=u.projections[i],f.uniforms.clipBounds=u.clipBounds[i],o=0;o<3;++o)if(this.contourProject[i][o]){f.uniforms.permutation=k[o],r.lineWidth(this.contourWidth[o]*this.pixelRatio);for(var m=0;m<this.contourLevels[o].length;++m)m===this.highlightLevel[o]?(f.uniforms.contourColor=this.highlightColor[o],f.uniforms.contourTint=this.highlightTint[o]):0!==m&&m-1!==this.highlightLevel[o]||(f.uniforms.contourColor=this.contourColor[o],f.uniforms.contourTint=this.contourTint[o]),this._contourCounts[o][m]&&(f.uniforms.height=this.contourLevels[o][m],h.draw(r.LINES,this._contourCounts[o][m],this._contourOffsets[o][m]))}for(h.unbind(),(h=this._dynamicVAO).bind(),i=0;i<3;++i)if(0!==this._dynamicCounts[i])for(f.uniforms.model=n.model,f.uniforms.clipBounds=n.clipBounds,f.uniforms.permutation=k[i],r.lineWidth(this.dynamicWidth[i]*this.pixelRatio),f.uniforms.contourColor=this.dynamicColor[i],f.uniforms.contourTint=this.dynamicTint[i],f.uniforms.height=this.dynamicLevel[i],h.draw(r.LINES,this._dynamicCounts[i],this._dynamicOffsets[i]),o=0;o<3;++o)this.contourProject[o][i]&&(f.uniforms.model=u.projections[o],f.uniforms.clipBounds=u.clipBounds[o],h.draw(r.LINES,this._dynamicCounts[i],this._dynamicOffsets[i]));h.unbind()}}S.draw=function(t){return z.call(this,t,!1)},S.drawTransparent=function(t){return z.call(this,t,!0)};var D={model:w,view:w,projection:w,inverseModel:w,clipBounds:[[0,0,0],[0,0,0]],height:0,shape:[0,0],pickId:0,lowerBound:[0,0,0],upperBound:[0,0,0],zOffset:0,objectOffset:[0,0,0],permutation:[1,0,0,0,1,0,0,0,1],lightPosition:[0,0,0],eyePosition:[0,0,0]};function R(t,e){return Array.isArray(t)?[e(t[0]),e(t[1]),e(t[2])]:[e(t),e(t),e(t)]}function F(t){return Array.isArray(t)?3===t.length?[t[0],t[1],t[2],1]:[t[0],t[1],t[2],t[3]]:[0,0,0,1]}function B(t){if(Array.isArray(t)){if(Array.isArray(t))return[F(t[0]),F(t[1]),F(t[2])];var e=F(t);return[e.slice(),e.slice(),e.slice()]}}S.drawPick=function(t){t=t||{};var e=this.gl;e.disable(e.CULL_FACE);var r=D;r.model=t.model||w,r.view=t.view||w,r.projection=t.projection||w,r.shape=this._field[2].shape,r.pickId=this.pickId/255,r.lowerBound=this.bounds[0],r.upperBound=this.bounds[1],r.objectOffset=this.objectOffset,r.permutation=O;for(var n=0;n<2;++n)for(var i=r.clipBounds[n],a=0;a<3;++a)i[a]=Math.min(Math.max(this.clipBounds[n][a],-1e8),1e8);var o=C(r,this);if(o.showSurface){for(this._pickShader.bind(),this._pickShader.uniforms=r,this._vao.bind(),this._vao.draw(e.TRIANGLES,this._vertexCount),n=0;n<3;++n)this.surfaceProject[n]&&(this._pickShader.uniforms.model=o.projections[n],this._pickShader.uniforms.clipBounds=o.clipBounds[n],this._vao.draw(e.TRIANGLES,this._vertexCount));this._vao.unbind()}if(o.showContour){var s=this._contourPickShader;s.bind(),s.uniforms=r;var l=this._contourVAO;for(l.bind(),a=0;a<3;++a)for(e.lineWidth(this.contourWidth[a]*this.pixelRatio),s.uniforms.permutation=k[a],n=0;n<this.contourLevels[a].length;++n)this._contourCounts[a][n]&&(s.uniforms.height=this.contourLevels[a][n],l.draw(e.LINES,this._contourCounts[a][n],this._contourOffsets[a][n]));for(n=0;n<3;++n)for(s.uniforms.model=o.projections[n],s.uniforms.clipBounds=o.clipBounds[n],a=0;a<3;++a)if(this.contourProject[n][a]){s.uniforms.permutation=k[a],e.lineWidth(this.contourWidth[a]*this.pixelRatio);for(var c=0;c<this.contourLevels[a].length;++c)this._contourCounts[a][c]&&(s.uniforms.height=this.contourLevels[a][c],l.draw(e.LINES,this._contourCounts[a][c],this._contourOffsets[a][c]))}l.unbind()}},S.pick=function(t){if(!t)return null;if(t.id!==this.pickId)return null;var e=this._field[2].shape,r=this._pickResult,n=e[0]*(t.value[0]+(t.value[2]>>4)/16)/255,i=Math.floor(n),a=n-i,o=e[1]*(t.value[1]+(15&t.value[2])/16)/255,s=Math.floor(o),l=o-s;i+=1,s+=1;var c=r.position;c[0]=c[1]=c[2]=0;for(var u=0;u<2;++u)for(var f=u?a:1-a,h=0;h<2;++h)for(var p=i+u,d=s+h,g=f*(h?l:1-l),v=0;v<3;++v)c[v]+=this._field[v].get(p,d)*g;for(var y=this._pickResult.level,x=0;x<3;++x)if(y[x]=m.le(this.contourLevels[x],c[x]),y[x]<0)this.contourLevels[x].length>0&&(y[x]=0);else if(y[x]<this.contourLevels[x].length-1){var b=this.contourLevels[x][y[x]],_=this.contourLevels[x][y[x]+1];Math.abs(b-c[x])>Math.abs(_-c[x])&&(y[x]+=1)}for(r.index[0]=a<.5?i:i+1,r.index[1]=l<.5?s:s+1,r.uv[0]=n/e[0],r.uv[1]=o/e[1],v=0;v<3;++v)r.dataCoordinate[v]=this._field[v].get(r.index[0],r.index[1]);return r},S.padField=function(t,e){var r=e.shape.slice(),n=t.shape.slice();c.assign(t.lo(1,1).hi(r[0],r[1]),e),c.assign(t.lo(1).hi(r[0],1),e.hi(r[0],1)),c.assign(t.lo(1,n[1]-1).hi(r[0],1),e.lo(0,r[1]-1).hi(r[0],1)),c.assign(t.lo(0,1).hi(1,r[1]),e.hi(1)),c.assign(t.lo(n[0]-1,1).hi(1,r[1]),e.lo(r[0]-1)),t.set(0,0,e.get(0,0)),t.set(0,n[1]-1,e.get(0,r[1]-1)),t.set(n[0]-1,0,e.get(r[0]-1,0)),t.set(n[0]-1,n[1]-1,e.get(r[0]-1,r[1]-1))},S.update=function(t){t=t||{},this.objectOffset=t.objectOffset||this.objectOffset,this.dirty=!0,\"contourWidth\"in t&&(this.contourWidth=R(t.contourWidth,Number)),\"showContour\"in t&&(this.showContour=R(t.showContour,Boolean)),\"showSurface\"in t&&(this.showSurface=!!t.showSurface),\"contourTint\"in t&&(this.contourTint=R(t.contourTint,Boolean)),\"contourColor\"in t&&(this.contourColor=B(t.contourColor)),\"contourProject\"in t&&(this.contourProject=R(t.contourProject,(function(t){return R(t,Boolean)}))),\"surfaceProject\"in t&&(this.surfaceProject=t.surfaceProject),\"dynamicColor\"in t&&(this.dynamicColor=B(t.dynamicColor)),\"dynamicTint\"in t&&(this.dynamicTint=R(t.dynamicTint,Number)),\"dynamicWidth\"in t&&(this.dynamicWidth=R(t.dynamicWidth,Number)),\"opacity\"in t&&(this.opacity=t.opacity),\"opacityscale\"in t&&(this.opacityscale=t.opacityscale),\"colorBounds\"in t&&(this.colorBounds=t.colorBounds),\"vertexColor\"in t&&(this.vertexColor=t.vertexColor?1:0),\"colormap\"in t&&this._colorMap.setPixels(this.genColormap(t.colormap,this.opacityscale));var e=t.field||t.coords&&t.coords[2]||null,r=!1;if(e||(e=this._field[2].shape[0]||this._field[2].shape[2]?this._field[2].lo(1,1).hi(this._field[2].shape[0]-2,this._field[2].shape[1]-2):this._field[2].hi(0,0)),\"field\"in t||\"coords\"in t){var i=(e.shape[0]+2)*(e.shape[1]+2);i>this._field[2].data.length&&(s.freeFloat(this._field[2].data),this._field[2].data=s.mallocFloat(n.nextPow2(i))),this._field[2]=f(this._field[2].data,[e.shape[0]+2,e.shape[1]+2]),this.padField(this._field[2],e),this.shape=e.shape.slice();for(var a=this.shape,o=0;o<2;++o)this._field[2].size>this._field[o].data.length&&(s.freeFloat(this._field[o].data),this._field[o].data=s.mallocFloat(this._field[2].size)),this._field[o]=f(this._field[o].data,[a[0]+2,a[1]+2]);if(t.coords){var l=t.coords;if(!Array.isArray(l)||3!==l.length)throw new Error(\"gl-surface: invalid coordinates for x/y\");for(o=0;o<2;++o){var c=l[o];for(v=0;v<2;++v)if(c.shape[v]!==a[v])throw new Error(\"gl-surface: coords have incorrect shape\");this.padField(this._field[o],c)}}else if(t.ticks){var u=t.ticks;if(!Array.isArray(u)||2!==u.length)throw new Error(\"gl-surface: invalid ticks\");for(o=0;o<2;++o){var p=u[o];if((Array.isArray(p)||p.length)&&(p=f(p)),p.shape[0]!==a[o])throw new Error(\"gl-surface: invalid tick length\");var d=f(p.data,a);d.stride[o]=p.stride[0],d.stride[1^o]=0,this.padField(this._field[o],d)}}else{for(o=0;o<2;++o){var m=[0,0];m[o]=1,this._field[o]=f(this._field[o].data,[a[0]+2,a[1]+2],m,0)}this._field[0].set(0,0,0);for(var v=0;v<a[0];++v)this._field[0].set(v+1,0,v);for(this._field[0].set(a[0]+1,0,a[0]-1),this._field[1].set(0,0,0),v=0;v<a[1];++v)this._field[1].set(0,v+1,v);this._field[1].set(0,a[1]+1,a[1]-1)}var y=this._field,x=f(s.mallocFloat(3*y[2].size*2),[3,a[0]+2,a[1]+2,2]);for(o=0;o<3;++o)g(x.pick(o),y[o],\"mirror\");var b=f(s.mallocFloat(3*y[2].size),[a[0]+2,a[1]+2,3]);for(o=0;o<a[0]+2;++o)for(v=0;v<a[1]+2;++v){var _=x.get(0,o,v,0),w=x.get(0,o,v,1),k=x.get(1,o,v,0),A=x.get(1,o,v,1),M=x.get(2,o,v,0),S=x.get(2,o,v,1),E=k*S-A*M,L=M*w-S*_,C=_*A-w*k,P=Math.sqrt(E*E+L*L+C*C);P<1e-8?(P=Math.max(Math.abs(E),Math.abs(L),Math.abs(C)))<1e-8?(C=1,L=E=0,P=1):P=1/P:P=1/Math.sqrt(P),b.set(o,v,0,E*P),b.set(o,v,1,L*P),b.set(o,v,2,C*P)}s.free(x.data);var I=[1/0,1/0,1/0],O=[-1/0,-1/0,-1/0],z=1/0,D=-1/0,F=(a[0]-1)*(a[1]-1)*6,N=s.mallocFloat(n.nextPow2(10*F)),j=0,U=0;for(o=0;o<a[0]-1;++o)t:for(v=0;v<a[1]-1;++v){for(var V=0;V<2;++V)for(var H=0;H<2;++H)for(var q=0;q<3;++q){var G=this._field[q].get(1+o+V,1+v+H);if(isNaN(G)||!isFinite(G))continue t}for(q=0;q<6;++q){var Y=o+T[q][0],W=v+T[q][1],X=this._field[0].get(Y+1,W+1),Z=this._field[1].get(Y+1,W+1);G=this._field[2].get(Y+1,W+1),E=b.get(Y+1,W+1,0),L=b.get(Y+1,W+1,1),C=b.get(Y+1,W+1,2),t.intensity&&(J=t.intensity.get(Y,W));var J=t.intensity?t.intensity.get(Y,W):G+this.objectOffset[2];N[j++]=Y,N[j++]=W,N[j++]=X,N[j++]=Z,N[j++]=G,N[j++]=0,N[j++]=J,N[j++]=E,N[j++]=L,N[j++]=C,I[0]=Math.min(I[0],X+this.objectOffset[0]),I[1]=Math.min(I[1],Z+this.objectOffset[1]),I[2]=Math.min(I[2],G+this.objectOffset[2]),z=Math.min(z,J),O[0]=Math.max(O[0],X+this.objectOffset[0]),O[1]=Math.max(O[1],Z+this.objectOffset[1]),O[2]=Math.max(O[2],G+this.objectOffset[2]),D=Math.max(D,J),U+=1}}for(t.intensityBounds&&(z=+t.intensityBounds[0],D=+t.intensityBounds[1]),o=6;o<j;o+=10)N[o]=(N[o]-z)/(D-z);this._vertexCount=U,this._coordinateBuffer.update(N.subarray(0,j)),s.freeFloat(N),s.free(b.data),this.bounds=[I,O],this.intensity=t.intensity||this._field[2],this.intensityBounds[0]===z&&this.intensityBounds[1]===D||(r=!0),this.intensityBounds=[z,D]}if(\"levels\"in t){var K=t.levels;for(K=Array.isArray(K[0])?K.slice():[[],[],K],o=0;o<3;++o)K[o]=K[o].slice(),K[o].sort((function(t,e){return t-e}));for(o=0;o<3;++o)for(v=0;v<K[o].length;++v)K[o][v]-=this.objectOffset[o];t:for(o=0;o<3;++o){if(K[o].length!==this.contourLevels[o].length){r=!0;break}for(v=0;v<K[o].length;++v)if(K[o][v]!==this.contourLevels[o][v]){r=!0;break t}}this.contourLevels=K}if(r){y=this._field,a=this.shape;for(var Q=[],$=0;$<3;++$){var tt=this.contourLevels[$],et=[],rt=[],nt=[0,0,0];for(o=0;o<tt.length;++o){var it=h(this._field[$],tt[o]);et.push(Q.length/5|0),U=0;t:for(v=0;v<it.cells.length;++v){var at=it.cells[v];for(q=0;q<2;++q){var ot=it.positions[at[q]],st=ot[0],lt=0|Math.floor(st),ct=st-lt,ut=ot[1],ft=0|Math.floor(ut),ht=ut-ft,pt=!1;e:for(var dt=0;dt<3;++dt){nt[dt]=0;var mt=($+dt+1)%3;for(V=0;V<2;++V){var gt=V?ct:1-ct;for(Y=0|Math.min(Math.max(lt+V,0),a[0]),H=0;H<2;++H){var vt=H?ht:1-ht;if(W=0|Math.min(Math.max(ft+H,0),a[1]),G=dt<2?this._field[mt].get(Y,W):(this.intensity.get(Y,W)-this.intensityBounds[0])/(this.intensityBounds[1]-this.intensityBounds[0]),!isFinite(G)||isNaN(G)){pt=!0;break e}var yt=gt*vt;nt[dt]+=yt*G}}}if(pt){if(q>0){for(var xt=0;xt<5;++xt)Q.pop();U-=1}continue t}Q.push(nt[0],nt[1],ot[0],ot[1],nt[2]),U+=1}}rt.push(U)}this._contourOffsets[$]=et,this._contourCounts[$]=rt}var bt=s.mallocFloat(Q.length);for(o=0;o<Q.length;++o)bt[o]=Q[o];this._contourBuffer.update(bt),s.freeFloat(bt)}},S.dispose=function(){this._shader.dispose(),this._vao.dispose(),this._coordinateBuffer.dispose(),this._colorMap.dispose(),this._contourBuffer.dispose(),this._contourVAO.dispose(),this._contourShader.dispose(),this._contourPickShader.dispose(),this._dynamicBuffer.dispose(),this._dynamicVAO.dispose();for(var t=0;t<3;++t)s.freeFloat(this._field[t].data)},S.highlight=function(t){var e,r;if(!t)return this._dynamicCounts=[0,0,0],this.dyanamicLevel=[NaN,NaN,NaN],void(this.highlightLevel=[-1,-1,-1]);for(e=0;e<3;++e)this.enableHighlight[e]?this.highlightLevel[e]=t.level[e]:this.highlightLevel[e]=-1;for(r=this.snapToData?t.dataCoordinate:t.position,e=0;e<3;++e)r[e]-=this.objectOffset[e];if(this.enableDynamic[0]&&r[0]!==this.dynamicLevel[0]||this.enableDynamic[1]&&r[1]!==this.dynamicLevel[1]||this.enableDynamic[2]&&r[2]!==this.dynamicLevel[2]){for(var n=0,i=this.shape,a=s.mallocFloat(12*i[0]*i[1]),o=0;o<3;++o)if(this.enableDynamic[o]){this.dynamicLevel[o]=r[o];var l=(o+1)%3,c=(o+2)%3,u=this._field[o],f=this._field[l],p=this._field[c],d=h(u,r[o]),m=d.cells,g=d.positions;for(this._dynamicOffsets[o]=n,e=0;e<m.length;++e)for(var v=m[e],y=0;y<2;++y){var x=g[v[y]],b=+x[0],_=0|b,w=0|Math.min(_+1,i[0]),T=b-_,k=1-T,A=+x[1],M=0|A,S=0|Math.min(M+1,i[1]),E=A-M,L=1-E,C=k*L,P=k*E,I=T*L,O=T*E,z=C*f.get(_,M)+P*f.get(_,S)+I*f.get(w,M)+O*f.get(w,S),D=C*p.get(_,M)+P*p.get(_,S)+I*p.get(w,M)+O*p.get(w,S);if(isNaN(z)||isNaN(D)){y&&(n-=1);break}a[2*n+0]=z,a[2*n+1]=D,n+=1}this._dynamicCounts[o]=n-this._dynamicOffsets[o]}else this.dynamicLevel[o]=NaN,this._dynamicCounts[o]=0;this._dynamicBuffer.update(a.subarray(0,2*n)),s.freeFloat(a)}}},{\"./lib/shaders\":144,\"binary-search-bounds\":31,\"bit-twiddle\":32,colormap:53,\"gl-buffer\":78,\"gl-mat4/invert\":98,\"gl-mat4/multiply\":100,\"gl-texture2d\":146,\"gl-vao\":150,ndarray:259,\"ndarray-gradient\":252,\"ndarray-ops\":254,\"ndarray-pack\":255,\"surface-nets\":302,\"typedarray-pool\":308}],146:[function(t,e,r){\"use strict\";var n=t(\"ndarray\"),i=t(\"ndarray-ops\"),a=t(\"typedarray-pool\");e.exports=function(t){if(arguments.length<=1)throw new Error(\"gl-texture2d: Missing arguments for texture2d constructor\");o||c(t);if(\"number\"==typeof arguments[1])return v(t,arguments[1],arguments[2],arguments[3]||t.RGBA,arguments[4]||t.UNSIGNED_BYTE);if(Array.isArray(arguments[1]))return v(t,0|arguments[1][0],0|arguments[1][1],arguments[2]||t.RGBA,arguments[3]||t.UNSIGNED_BYTE);if(\"object\"==typeof arguments[1]){var e=arguments[1],r=u(e)?e:e.raw;if(r)return y(t,r,0|e.width,0|e.height,arguments[2]||t.RGBA,arguments[3]||t.UNSIGNED_BYTE);if(e.shape&&e.data&&e.stride)return x(t,e)}throw new Error(\"gl-texture2d: Invalid arguments for texture2d constructor\")};var o=null,s=null,l=null;function c(t){o=[t.LINEAR,t.NEAREST_MIPMAP_LINEAR,t.LINEAR_MIPMAP_NEAREST,t.LINEAR_MIPMAP_NEAREST],s=[t.NEAREST,t.LINEAR,t.NEAREST_MIPMAP_NEAREST,t.NEAREST_MIPMAP_LINEAR,t.LINEAR_MIPMAP_NEAREST,t.LINEAR_MIPMAP_LINEAR],l=[t.REPEAT,t.CLAMP_TO_EDGE,t.MIRRORED_REPEAT]}function u(t){return\"undefined\"!=typeof HTMLCanvasElement&&t instanceof HTMLCanvasElement||\"undefined\"!=typeof HTMLImageElement&&t instanceof HTMLImageElement||\"undefined\"!=typeof HTMLVideoElement&&t instanceof HTMLVideoElement||\"undefined\"!=typeof ImageData&&t instanceof ImageData}var f=function(t,e){i.muls(t,e,255)};function h(t,e,r){var n=t.gl,i=n.getParameter(n.MAX_TEXTURE_SIZE);if(e<0||e>i||r<0||r>i)throw new Error(\"gl-texture2d: Invalid texture size\");return t._shape=[e,r],t.bind(),n.texImage2D(n.TEXTURE_2D,0,t.format,e,r,0,t.format,t.type,null),t._mipLevels=[0],t}function p(t,e,r,n,i,a){this.gl=t,this.handle=e,this.format=i,this.type=a,this._shape=[r,n],this._mipLevels=[0],this._magFilter=t.NEAREST,this._minFilter=t.NEAREST,this._wrapS=t.CLAMP_TO_EDGE,this._wrapT=t.CLAMP_TO_EDGE,this._anisoSamples=1;var o=this,s=[this._wrapS,this._wrapT];Object.defineProperties(s,[{get:function(){return o._wrapS},set:function(t){return o.wrapS=t}},{get:function(){return o._wrapT},set:function(t){return o.wrapT=t}}]),this._wrapVector=s;var l=[this._shape[0],this._shape[1]];Object.defineProperties(l,[{get:function(){return o._shape[0]},set:function(t){return o.width=t}},{get:function(){return o._shape[1]},set:function(t){return o.height=t}}]),this._shapeVector=l}var d=p.prototype;function m(t,e){return 3===t.length?1===e[2]&&e[1]===t[0]*t[2]&&e[0]===t[2]:1===e[0]&&e[1]===t[0]}function g(t){var e=t.createTexture();return t.bindTexture(t.TEXTURE_2D,e),t.texParameteri(t.TEXTURE_2D,t.TEXTURE_MIN_FILTER,t.NEAREST),t.texParameteri(t.TEXTURE_2D,t.TEXTURE_MAG_FILTER,t.NEAREST),t.texParameteri(t.TEXTURE_2D,t.TEXTURE_WRAP_S,t.CLAMP_TO_EDGE),t.texParameteri(t.TEXTURE_2D,t.TEXTURE_WRAP_T,t.CLAMP_TO_EDGE),e}function v(t,e,r,n,i){var a=t.getParameter(t.MAX_TEXTURE_SIZE);if(e<0||e>a||r<0||r>a)throw new Error(\"gl-texture2d: Invalid texture shape\");if(i===t.FLOAT&&!t.getExtension(\"OES_texture_float\"))throw new Error(\"gl-texture2d: Floating point textures not supported on this platform\");var o=g(t);return t.texImage2D(t.TEXTURE_2D,0,n,e,r,0,n,i,null),new p(t,o,e,r,n,i)}function y(t,e,r,n,i,a){var o=g(t);return t.texImage2D(t.TEXTURE_2D,0,i,i,a,e),new p(t,o,r,n,i,a)}function x(t,e){var r=e.dtype,o=e.shape.slice(),s=t.getParameter(t.MAX_TEXTURE_SIZE);if(o[0]<0||o[0]>s||o[1]<0||o[1]>s)throw new Error(\"gl-texture2d: Invalid texture size\");var l=m(o,e.stride.slice()),c=0;\"float32\"===r?c=t.FLOAT:\"float64\"===r?(c=t.FLOAT,l=!1,r=\"float32\"):\"uint8\"===r?c=t.UNSIGNED_BYTE:(c=t.UNSIGNED_BYTE,l=!1,r=\"uint8\");var u,h,d=0;if(2===o.length)d=t.LUMINANCE,o=[o[0],o[1],1],e=n(e.data,o,[e.stride[0],e.stride[1],1],e.offset);else{if(3!==o.length)throw new Error(\"gl-texture2d: Invalid shape for texture\");if(1===o[2])d=t.ALPHA;else if(2===o[2])d=t.LUMINANCE_ALPHA;else if(3===o[2])d=t.RGB;else{if(4!==o[2])throw new Error(\"gl-texture2d: Invalid shape for pixel coords\");d=t.RGBA}}c!==t.FLOAT||t.getExtension(\"OES_texture_float\")||(c=t.UNSIGNED_BYTE,l=!1);var v=e.size;if(l)u=0===e.offset&&e.data.length===v?e.data:e.data.subarray(e.offset,e.offset+v);else{var y=[o[2],o[2]*o[0],1];h=a.malloc(v,r);var x=n(h,o,y,0);\"float32\"!==r&&\"float64\"!==r||c!==t.UNSIGNED_BYTE?i.assign(x,e):f(x,e),u=h.subarray(0,v)}var b=g(t);return t.texImage2D(t.TEXTURE_2D,0,d,o[0],o[1],0,d,c,u),l||a.free(h),new p(t,b,o[0],o[1],d,c)}Object.defineProperties(d,{minFilter:{get:function(){return this._minFilter},set:function(t){this.bind();var e=this.gl;if(this.type===e.FLOAT&&o.indexOf(t)>=0&&(e.getExtension(\"OES_texture_float_linear\")||(t=e.NEAREST)),s.indexOf(t)<0)throw new Error(\"gl-texture2d: Unknown filter mode \"+t);return e.texParameteri(e.TEXTURE_2D,e.TEXTURE_MIN_FILTER,t),this._minFilter=t}},magFilter:{get:function(){return this._magFilter},set:function(t){this.bind();var e=this.gl;if(this.type===e.FLOAT&&o.indexOf(t)>=0&&(e.getExtension(\"OES_texture_float_linear\")||(t=e.NEAREST)),s.indexOf(t)<0)throw new Error(\"gl-texture2d: Unknown filter mode \"+t);return e.texParameteri(e.TEXTURE_2D,e.TEXTURE_MAG_FILTER,t),this._magFilter=t}},mipSamples:{get:function(){return this._anisoSamples},set:function(t){var e=this._anisoSamples;if(this._anisoSamples=0|Math.max(t,1),e!==this._anisoSamples){var r=this.gl.getExtension(\"EXT_texture_filter_anisotropic\");r&&this.gl.texParameterf(this.gl.TEXTURE_2D,r.TEXTURE_MAX_ANISOTROPY_EXT,this._anisoSamples)}return this._anisoSamples}},wrapS:{get:function(){return this._wrapS},set:function(t){if(this.bind(),l.indexOf(t)<0)throw new Error(\"gl-texture2d: Unknown wrap mode \"+t);return this.gl.texParameteri(this.gl.TEXTURE_2D,this.gl.TEXTURE_WRAP_S,t),this._wrapS=t}},wrapT:{get:function(){return this._wrapT},set:function(t){if(this.bind(),l.indexOf(t)<0)throw new Error(\"gl-texture2d: Unknown wrap mode \"+t);return this.gl.texParameteri(this.gl.TEXTURE_2D,this.gl.TEXTURE_WRAP_T,t),this._wrapT=t}},wrap:{get:function(){return this._wrapVector},set:function(t){if(Array.isArray(t)||(t=[t,t]),2!==t.length)throw new Error(\"gl-texture2d: Must specify wrap mode for rows and columns\");for(var e=0;e<2;++e)if(l.indexOf(t[e])<0)throw new Error(\"gl-texture2d: Unknown wrap mode \"+t);this._wrapS=t[0],this._wrapT=t[1];var r=this.gl;return this.bind(),r.texParameteri(r.TEXTURE_2D,r.TEXTURE_WRAP_S,this._wrapS),r.texParameteri(r.TEXTURE_2D,r.TEXTURE_WRAP_T,this._wrapT),t}},shape:{get:function(){return this._shapeVector},set:function(t){if(Array.isArray(t)){if(2!==t.length)throw new Error(\"gl-texture2d: Invalid texture shape\")}else t=[0|t,0|t];return h(this,0|t[0],0|t[1]),[0|t[0],0|t[1]]}},width:{get:function(){return this._shape[0]},set:function(t){return h(this,t|=0,this._shape[1]),t}},height:{get:function(){return this._shape[1]},set:function(t){return t|=0,h(this,this._shape[0],t),t}}}),d.bind=function(t){var e=this.gl;return void 0!==t&&e.activeTexture(e.TEXTURE0+(0|t)),e.bindTexture(e.TEXTURE_2D,this.handle),void 0!==t?0|t:e.getParameter(e.ACTIVE_TEXTURE)-e.TEXTURE0},d.dispose=function(){this.gl.deleteTexture(this.handle)},d.generateMipmap=function(){this.bind(),this.gl.generateMipmap(this.gl.TEXTURE_2D);for(var t=Math.min(this._shape[0],this._shape[1]),e=0;t>0;++e,t>>>=1)this._mipLevels.indexOf(e)<0&&this._mipLevels.push(e)},d.setPixels=function(t,e,r,o){var s=this.gl;this.bind(),Array.isArray(e)?(o=r,r=0|e[1],e=0|e[0]):(e=e||0,r=r||0),o=o||0;var l=u(t)?t:t.raw;if(l){this._mipLevels.indexOf(o)<0?(s.texImage2D(s.TEXTURE_2D,0,this.format,this.format,this.type,l),this._mipLevels.push(o)):s.texSubImage2D(s.TEXTURE_2D,o,e,r,this.format,this.type,l)}else{if(!(t.shape&&t.stride&&t.data))throw new Error(\"gl-texture2d: Unsupported data type\");if(t.shape.length<2||e+t.shape[1]>this._shape[1]>>>o||r+t.shape[0]>this._shape[0]>>>o||e<0||r<0)throw new Error(\"gl-texture2d: Texture dimensions are out of bounds\");!function(t,e,r,o,s,l,c,u){var h=u.dtype,p=u.shape.slice();if(p.length<2||p.length>3)throw new Error(\"gl-texture2d: Invalid ndarray, must be 2d or 3d\");var d=0,g=0,v=m(p,u.stride.slice());\"float32\"===h?d=t.FLOAT:\"float64\"===h?(d=t.FLOAT,v=!1,h=\"float32\"):\"uint8\"===h?d=t.UNSIGNED_BYTE:(d=t.UNSIGNED_BYTE,v=!1,h=\"uint8\");if(2===p.length)g=t.LUMINANCE,p=[p[0],p[1],1],u=n(u.data,p,[u.stride[0],u.stride[1],1],u.offset);else{if(3!==p.length)throw new Error(\"gl-texture2d: Invalid shape for texture\");if(1===p[2])g=t.ALPHA;else if(2===p[2])g=t.LUMINANCE_ALPHA;else if(3===p[2])g=t.RGB;else{if(4!==p[2])throw new Error(\"gl-texture2d: Invalid shape for pixel coords\");g=t.RGBA}p[2]}g!==t.LUMINANCE&&g!==t.ALPHA||s!==t.LUMINANCE&&s!==t.ALPHA||(g=s);if(g!==s)throw new Error(\"gl-texture2d: Incompatible texture format for setPixels\");var y=u.size,x=c.indexOf(o)<0;x&&c.push(o);if(d===l&&v)0===u.offset&&u.data.length===y?x?t.texImage2D(t.TEXTURE_2D,o,s,p[0],p[1],0,s,l,u.data):t.texSubImage2D(t.TEXTURE_2D,o,e,r,p[0],p[1],s,l,u.data):x?t.texImage2D(t.TEXTURE_2D,o,s,p[0],p[1],0,s,l,u.data.subarray(u.offset,u.offset+y)):t.texSubImage2D(t.TEXTURE_2D,o,e,r,p[0],p[1],s,l,u.data.subarray(u.offset,u.offset+y));else{var b;b=l===t.FLOAT?a.mallocFloat32(y):a.mallocUint8(y);var _=n(b,p,[p[2],p[2]*p[0],1]);d===t.FLOAT&&l===t.UNSIGNED_BYTE?f(_,u):i.assign(_,u),x?t.texImage2D(t.TEXTURE_2D,o,s,p[0],p[1],0,s,l,b.subarray(0,y)):t.texSubImage2D(t.TEXTURE_2D,o,e,r,p[0],p[1],s,l,b.subarray(0,y)),l===t.FLOAT?a.freeFloat32(b):a.freeUint8(b)}}(s,e,r,o,this.format,this.type,this._mipLevels,t)}}},{ndarray:259,\"ndarray-ops\":254,\"typedarray-pool\":308}],147:[function(t,e,r){\"use strict\";e.exports=function(t,e,r){e?e.bind():t.bindBuffer(t.ELEMENT_ARRAY_BUFFER,null);var n=0|t.getParameter(t.MAX_VERTEX_ATTRIBS);if(r){if(r.length>n)throw new Error(\"gl-vao: Too many vertex attributes\");for(var i=0;i<r.length;++i){var a=r[i];if(a.buffer){var o=a.buffer,s=a.size||4,l=a.type||t.FLOAT,c=!!a.normalized,u=a.stride||0,f=a.offset||0;o.bind(),t.enableVertexAttribArray(i),t.vertexAttribPointer(i,s,l,c,u,f)}else{if(\"number\"==typeof a)t.vertexAttrib1f(i,a);else if(1===a.length)t.vertexAttrib1f(i,a[0]);else if(2===a.length)t.vertexAttrib2f(i,a[0],a[1]);else if(3===a.length)t.vertexAttrib3f(i,a[0],a[1],a[2]);else{if(4!==a.length)throw new Error(\"gl-vao: Invalid vertex attribute\");t.vertexAttrib4f(i,a[0],a[1],a[2],a[3])}t.disableVertexAttribArray(i)}}for(;i<n;++i)t.disableVertexAttribArray(i)}else{t.bindBuffer(t.ARRAY_BUFFER,null);for(i=0;i<n;++i)t.disableVertexAttribArray(i)}}},{}],148:[function(t,e,r){\"use strict\";var n=t(\"./do-bind.js\");function 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"/*!\n",
" * pad-left <https://github.com/jonschlinkert/pad-left>\n",
" *\n",
" * Copyright (c) 2014-2015, Jon Schlinkert.\n",
" * Licensed under the MIT license.\n",
" */\n",
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m=t[s];i[m[0]]&&i[m[1]]&&d.push([h[m[0]],h[m[1]]])}return[d,p]};var n=t(\"edges-to-adjacency-list\")},{\"edges-to-adjacency-list\":66}],268:[function(t,e,r){\"use strict\";e.exports=function(t,e){var r=c(t,e);t=r[0];for(var f=(e=r[1]).length,h=(t.length,n(t,e.length)),p=0;p<f;++p)if(h[p].length%2==1)throw new Error(\"planar-graph-to-polyline: graph must be manifold\");var d=i(t,e);var m=(d=d.filter((function(t){for(var r=t.length,n=[0],i=0;i<r;++i){var a=e[t[i]],l=e[t[(i+1)%r]],c=o(-a[0],a[1]),u=o(-a[0],l[1]),f=o(l[0],a[1]),h=o(l[0],l[1]);n=s(n,s(s(c,u),s(f,h)))}return n[n.length-1]>0}))).length,g=new Array(m),v=new Array(m);for(p=0;p<m;++p){g[p]=p;var y=new Array(m),x=d[p].map((function(t){return e[t]})),b=a([x]),_=0;t:for(var w=0;w<m;++w)if(y[w]=0,p!==w){for(var T=(H=d[w]).length,k=0;k<T;++k){var A=b(e[H[k]]);if(0!==A){A<0&&(y[w]=1,_+=1);continue t}}y[w]=1,_+=1}v[p]=[_,p,y]}v.sort((function(t,e){return e[0]-t[0]}));for(p=0;p<m;++p){var 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e=this.computedUp,r=this.computedRight,n=0,i=0,a=0;a<3;++a)i+=e[a]*r[a],n+=e[a]*e[a];var l=Math.sqrt(n),u=0;for(a=0;a<3;++a)r[a]-=e[a]*i/n,u+=r[a]*r[a],e[a]/=l;var f=Math.sqrt(u);for(a=0;a<3;++a)r[a]/=f;var h=this.computedToward;o(h,e,r),s(h,h);var p=Math.exp(this.computedRadius[0]),d=this.computedAngle[0],m=this.computedAngle[1],g=Math.cos(d),v=Math.sin(d),y=Math.cos(m),x=Math.sin(m),b=this.computedCenter,_=g*y,w=v*y,T=x,k=-g*x,A=-v*x,M=y,S=this.computedEye,E=this.computedMatrix;for(a=0;a<3;++a){var L=_*r[a]+w*h[a]+T*e[a];E[4*a+1]=k*r[a]+A*h[a]+M*e[a],E[4*a+2]=L,E[4*a+3]=0}var C=E[1],P=E[5],I=E[9],O=E[2],z=E[6],D=E[10],R=P*D-I*z,F=I*O-C*D,B=C*z-P*O,N=c(R,F,B);R/=N,F/=N,B/=N,E[0]=R,E[4]=F,E[8]=B;for(a=0;a<3;++a)S[a]=b[a]+E[2+4*a]*p;for(a=0;a<3;++a){u=0;for(var j=0;j<3;++j)u+=E[a+4*j]*S[j];E[12+a]=-u}E[15]=1},p.getMatrix=function(t,e){this.recalcMatrix(t);var r=this.computedMatrix;if(e){for(var n=0;n<16;++n)e[n]=r[n];return e}return r};var d=[0,0,0];p.rotate=function(t,e,r,n){if(this.angle.move(t,e,r),n){this.recalcMatrix(t);var i=this.computedMatrix;d[0]=i[2],d[1]=i[6],d[2]=i[10];for(var o=this.computedUp,s=this.computedRight,l=this.computedToward,c=0;c<3;++c)i[4*c]=o[c],i[4*c+1]=s[c],i[4*c+2]=l[c];a(i,i,n,d);for(c=0;c<3;++c)o[c]=i[4*c],s[c]=i[4*c+1];this.up.set(t,o[0],o[1],o[2]),this.right.set(t,s[0],s[1],s[2])}},p.pan=function(t,e,r,n){e=e||0,r=r||0,n=n||0,this.recalcMatrix(t);var i=this.computedMatrix,a=(Math.exp(this.computedRadius[0]),i[1]),o=i[5],s=i[9],l=c(a,o,s);a/=l,o/=l,s/=l;var u=i[0],f=i[4],h=i[8],p=u*a+f*o+h*s,d=c(u-=a*p,f-=o*p,h-=s*p),m=(u/=d)*e+a*r,g=(f/=d)*e+o*r,v=(h/=d)*e+s*r;this.center.move(t,m,g,v);var y=Math.exp(this.computedRadius[0]);y=Math.max(1e-4,y+n),this.radius.set(t,Math.log(y))},p.translate=function(t,e,r,n){this.center.move(t,e||0,r||0,n||0)},p.setMatrix=function(t,e,r,n){var a=1;\"number\"==typeof r&&(a=0|r),(a<0||a>3)&&(a=1);var o=(a+2)%3;e||(this.recalcMatrix(t),e=this.computedMatrix);var s=e[a],l=e[a+4],f=e[a+8];if(n){var h=Math.abs(s),p=Math.abs(l),d=Math.abs(f),m=Math.max(h,p,d);h===m?(s=s<0?-1:1,l=f=0):d===m?(f=f<0?-1:1,s=l=0):(l=l<0?-1:1,s=f=0)}else{var g=c(s,l,f);s/=g,l/=g,f/=g}var v,y,x=e[o],b=e[o+4],_=e[o+8],w=x*s+b*l+_*f,T=c(x-=s*w,b-=l*w,_-=f*w),k=l*(_/=T)-f*(b/=T),A=f*(x/=T)-s*_,M=s*b-l*x,S=c(k,A,M);if(k/=S,A/=S,M/=S,this.center.jump(t,q,G,Y),this.radius.idle(t),this.up.jump(t,s,l,f),this.right.jump(t,x,b,_),2===a){var E=e[1],L=e[5],C=e[9],P=E*x+L*b+C*_,I=E*k+L*A+C*M;v=R<0?-Math.PI/2:Math.PI/2,y=Math.atan2(I,P)}else{var O=e[2],z=e[6],D=e[10],R=O*s+z*l+D*f,F=O*x+z*b+D*_,B=O*k+z*A+D*M;v=Math.asin(u(R)),y=Math.atan2(B,F)}this.angle.jump(t,y,v),this.recalcMatrix(t);var N=e[2],j=e[6],U=e[10],V=this.computedMatrix;i(V,e);var H=V[15],q=V[12]/H,G=V[13]/H,Y=V[14]/H,W=Math.exp(this.computedRadius[0]);this.center.jump(t,q-N*W,G-j*W,Y-U*W)},p.lastT=function(){return 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{\"template\":{\"data\":{\"histogram2dcontour\":[{\"type\":\"histogram2dcontour\",\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]]}],\"choropleth\":[{\"type\":\"choropleth\",\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}],\"histogram2d\":[{\"type\":\"histogram2d\",\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]]}],\"heatmap\":[{\"type\":\"heatmap\",\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]]}],\"heatmapgl\":[{\"type\":\"heatmapgl\",\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]]}],\"contourcarpet\":[{\"type\":\"contourcarpet\",\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}],\"contour\":[{\"type\":\"contour\",\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]]}],\"surface\":[{\"type\":\"surface\",\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]]}],\"mesh3d\":[{\"type\":\"mesh3d\",\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}],\"scatter\":[{\"fillpattern\":{\"fillmode\":\"overlay\",\"size\":10,\"solidity\":0.2},\"type\":\"scatter\"}],\"parcoords\":[{\"type\":\"parcoords\",\"line\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}}],\"scatterpolargl\":[{\"type\":\"scatterpolargl\",\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}}],\"bar\":[{\"error_x\":{\"color\":\"#2a3f5f\"},\"error_y\":{\"color\":\"#2a3f5f\"},\"marker\":{\"line\":{\"color\":\"#E5ECF6\",\"width\":0.5},\"pattern\":{\"fillmode\":\"overlay\",\"size\":10,\"solidity\":0.2}},\"type\":\"bar\"}],\"scattergeo\":[{\"type\":\"scattergeo\",\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}}],\"scatterpolar\":[{\"type\":\"scatterpolar\",\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}}],\"histogram\":[{\"marker\":{\"pattern\":{\"fillmode\":\"overlay\",\"size\":10,\"solidity\":0.2}},\"type\":\"histogram\"}],\"scattergl\":[{\"type\":\"scattergl\",\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}}],\"scatter3d\":[{\"type\":\"scatter3d\",\"line\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}}],\"scattermapbox\":[{\"type\":\"scattermapbox\",\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}}],\"scatterternary\":[{\"type\":\"scatterternary\",\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}}],\"scattercarpet\":[{\"type\":\"scattercarpet\",\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}}],\"carpet\":[{\"aaxis\":{\"endlinecolor\":\"#2a3f5f\",\"gridcolor\":\"white\",\"linecolor\":\"white\",\"minorgridcolor\":\"white\",\"startlinecolor\":\"#2a3f5f\"},\"baxis\":{\"endlinecolor\":\"#2a3f5f\",\"gridcolor\":\"white\",\"linecolor\":\"white\",\"minorgridcolor\":\"white\",\"startlinecolor\":\"#2a3f5f\"},\"type\":\"carpet\"}],\"table\":[{\"cells\":{\"fill\":{\"color\":\"#EBF0F8\"},\"line\":{\"color\":\"white\"}},\"header\":{\"fill\":{\"color\":\"#C8D4E3\"},\"line\":{\"color\":\"white\"}},\"type\":\"table\"}],\"barpolar\":[{\"marker\":{\"line\":{\"color\":\"#E5ECF6\",\"width\":0.5},\"pattern\":{\"fillmode\":\"overlay\",\"size\":10,\"solidity\":0.2}},\"type\":\"barpolar\"}],\"pie\":[{\"automargin\":true,\"type\":\"pie\"}]},\"layout\":{\"autotypenumbers\":\"strict\",\"colorway\":[\"#636efa\",\"#EF553B\",\"#00cc96\",\"#ab63fa\",\"#FFA15A\",\"#19d3f3\",\"#FF6692\",\"#B6E880\",\"#FF97FF\",\"#FECB52\"],\"font\":{\"color\":\"#2a3f5f\"},\"hovermode\":\"closest\",\"hoverlabel\":{\"align\":\"left\"},\"paper_bgcolor\":\"white\",\"plot_bgcolor\":\"#E5ECF6\",\"polar\":{\"bgcolor\":\"#E5ECF6\",\"angularaxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\"},\"radialaxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\"}},\"ternary\":{\"bgcolor\":\"#E5ECF6\",\"aaxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\"},\"baxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\"},\"caxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\"}},\"coloraxis\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"colorscale\":{\"sequential\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]],\"sequentialminus\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]],\"diverging\":[[0,\"#8e0152\"],[0.1,\"#c51b7d\"],[0.2,\"#de77ae\"],[0.3,\"#f1b6da\"],[0.4,\"#fde0ef\"],[0.5,\"#f7f7f7\"],[0.6,\"#e6f5d0\"],[0.7,\"#b8e186\"],[0.8,\"#7fbc41\"],[0.9,\"#4d9221\"],[1,\"#276419\"]]},\"xaxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\",\"title\":{\"standoff\":15},\"zerolinecolor\":\"white\",\"automargin\":true,\"zerolinewidth\":2},\"yaxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\",\"title\":{\"standoff\":15},\"zerolinecolor\":\"white\",\"automargin\":true,\"zerolinewidth\":2},\"scene\":{\"xaxis\":{\"backgroundcolor\":\"#E5ECF6\",\"gridcolor\":\"white\",\"linecolor\":\"white\",\"showbackground\":true,\"ticks\":\"\",\"zerolinecolor\":\"white\",\"gridwidth\":2},\"yaxis\":{\"backgroundcolor\":\"#E5ECF6\",\"gridcolor\":\"white\",\"linecolor\":\"white\",\"showbackground\":true,\"ticks\":\"\",\"zerolinecolor\":\"white\",\"gridwidth\":2},\"zaxis\":{\"backgroundcolor\":\"#E5ECF6\",\"gridcolor\":\"white\",\"linecolor\":\"white\",\"showbackground\":true,\"ticks\":\"\",\"zerolinecolor\":\"white\",\"gridwidth\":2}},\"shapedefaults\":{\"line\":{\"color\":\"#2a3f5f\"}},\"annotationdefaults\":{\"arrowcolor\":\"#2a3f5f\",\"arrowhead\":0,\"arrowwidth\":1},\"geo\":{\"bgcolor\":\"white\",\"landcolor\":\"#E5ECF6\",\"subunitcolor\":\"white\",\"showland\":true,\"showlakes\":true,\"lakecolor\":\"white\"},\"title\":{\"x\":0.05},\"mapbox\":{\"style\":\"light\"}}},\"margin\":{\"l\":0,\"t\":0,\"b\":0,\"r\":0},\"mapbox\":{\"center\":{\"lon\":11.397024727771651,\"lat\":48.61890305099375},\"style\":\"stamen-terrain\",\"zoom\":6}}, {\"responsive\": true} ).then(function(){\n",
" \n",
"var gd = document.getElementById('b72fc5f1-eeb2-4a9e-a1e9-120c0b7ecfff');\n",
"var x = new MutationObserver(function (mutations, observer) {{\n",
" var display = window.getComputedStyle(gd).display;\n",
" if (!display || display === 'none') {{\n",
" console.log([gd, 'removed!']);\n",
" Plotly.purge(gd);\n",
" observer.disconnect();\n",
" }}\n",
"}});\n",
"\n",
"// Listen for the removal of the full notebook cells\n",
"var notebookContainer = gd.closest('#notebook-container');\n",
"if (notebookContainer) {{\n",
" x.observe(notebookContainer, {childList: true});\n",
"}}\n",
"\n",
"// Listen for the clearing of the current output cell\n",
"var outputEl = gd.closest('.output');\n",
"if (outputEl) {{\n",
" x.observe(outputEl, {childList: true});\n",
"}}\n",
"\n",
" }) }; }); </script> </div>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"import plotly.graph_objects as go\n",
"\n",
"\n",
"fig = go.Figure(go.Scattermapbox(\n",
" mode = \"markers+lines+text\",\n",
" lon = lng,\n",
" lat = lat,\n",
" marker = {'size': 8, 'color':'rgb(180,50,50)','opacity' : 0.25},\n",
" text=('Setup ID: %d' % (SETUP_ID)),\n",
" name=('Setup ID: %d' % (SETUP_ID))\n",
" ))\n",
"\n",
"fig.add_trace(go.Scattermapbox(\n",
" mode = \"markers\",\n",
" lon = [str(lng[-1])],\n",
" lat = [str(lat[-1])],\n",
" marker = {'size': 25, 'color':'rgb(180,50,50)','opacity' : 0.8},\n",
" text='destination',\n",
" name='destination'\n",
" ))\n",
"fig.add_trace(go.Scattermapbox(\n",
" mode = \"markers\",\n",
" lon = [str(lng[0])],\n",
" lat = [str(lat[0])],\n",
" marker = {'size': 25, 'color':'rgb(180,50,50)','opacity' : 0.8},\n",
" text='start',\n",
" name='start'\n",
" ))\n",
"\n",
"fig.update_layout(\n",
" margin ={'l':0,'t':0,'b':0,'r':0},\n",
" mapbox = {\n",
" #'center': {'lon': lng_s, 'lat': lat_s},\n",
" 'style': \"stamen-terrain\",\n",
" 'center': {'lon': (lng[-1]+lng[0])/2, 'lat': (lat[-1]+lat[0])/2},\n",
" 'zoom': 6})\n",
"\n",
"fig.show()"
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"\"\\n# Analyze Data\\n#import plotly\\n#import plotly.graph_objs as go\\n#import plotly.plotly as py\\nimport plotly.graph_objects as go\\nimport plotly.plotly as py\\n\\nplotly.tools.set_credentials_file(username='ziegmann', api_key='yGii8dk78Sjz7jzzad1n')\\nmapbox_access_token = 'pk.eyJ1Ijoiam9oYW5ubmVzLXppZWdtYW5uIiwiYSI6ImNqbDJmamo5bDFxNjQzcWxtd2IzejNhcXoifQ.iVXGH-jpe2FH3f52MM9yHQ'\\n\\ndata_p = [\\n go.Scattermapbox(\\n lat=lat,\\n lon=lng,\\n mode='markers',\\n marker=dict(size=6))\\n]\\n\\nlayout = go.Layout(\\n title='OBD-II GPS Logging',\\n autosize=True,\\n hovermode='closest',\\n mapbox=dict(\\n accesstoken=mapbox_access_token,\\n bearing=0,\\n center=dict(\\n lon=(lon_max-lon_min)/2+lon_min,\\n lat=(lat_max-lat_min)/2+lat_min,\\n ),\\n style='dark',\\n pitch=0,\\n zoom=zoomlevel\\n ),\\n)\\n\\nfig = dict(data=data_p, layout=layout)\\n#plotly.offline.plot(fig, filename='Mapbox.html')\\npy.iplot(fig, filename='Mapbox.html')\\n\\n\""
]
},
"execution_count": 11,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"'''\n",
"# Analyze Data\n",
"#import plotly\n",
"#import plotly.graph_objs as go\n",
"#import plotly.plotly as py\n",
"import plotly.graph_objects as go\n",
"import plotly.plotly as py\n",
"\n",
"plotly.tools.set_credentials_file(username='ziegmann', api_key='yGii8dk78Sjz7jzzad1n')\n",
"mapbox_access_token = 'pk.eyJ1Ijoiam9oYW5ubmVzLXppZWdtYW5uIiwiYSI6ImNqbDJmamo5bDFxNjQzcWxtd2IzejNhcXoifQ.iVXGH-jpe2FH3f52MM9yHQ'\n",
"\n",
"data_p = [\n",
" go.Scattermapbox(\n",
" lat=lat,\n",
" lon=lng,\n",
" mode='markers',\n",
" marker=dict(size=6))\n",
"]\n",
"\n",
"layout = go.Layout(\n",
" title='OBD-II GPS Logging',\n",
" autosize=True,\n",
" hovermode='closest',\n",
" mapbox=dict(\n",
" accesstoken=mapbox_access_token,\n",
" bearing=0,\n",
" center=dict(\n",
" lon=(lon_max-lon_min)/2+lon_min,\n",
" lat=(lat_max-lat_min)/2+lat_min,\n",
" ),\n",
" style='dark',\n",
" pitch=0,\n",
" zoom=zoomlevel\n",
" ),\n",
")\n",
"\n",
"fig = dict(data=data_p, layout=layout)\n",
"#plotly.offline.plot(fig, filename='Mapbox.html')\n",
"py.iplot(fig, filename='Mapbox.html')\n",
"\n",
"'''"
]
},
{
"cell_type": "code",
"execution_count": 12,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<matplotlib.legend.Legend at 0x7fcd77c4bac0>"
]
},
"execution_count": 12,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
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\n",
"text/plain": [
"<Figure size 1080x720 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"import matplotlib.pyplot as plot\n",
"temp_d=t['distance']\n",
"xaxis = temp_d # range(int(temp_d[0]), int(temp_d[-1]))\n",
"plot.figure(figsize=(15,10))\n",
"plot.axvline(x=temp_d[TRAINING_RANGE[0]])\n",
"plot.axvline(x=temp_d[TEST_RANGE[0]])\n",
"plot.plot(temp_d[TEST_RANGE[0]:TEST_RANGE[1]], target[TEST_RANGE[0]:TEST_RANGE[1]], 'b',\n",
" xaxis, t['hr_traficSpeed']*3.6, 'r',\n",
" xaxis, t['hr_SpeedLimit'],\n",
" )\n",
"plot.legend(['Training','Test','OBD Speed','HERE Traffic Speed', 'HERE Speed Limint'])"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Hyperparametersuche\n",
"\n",
"Utility-Methode; wurde zum Testen verschiedener Ansätze verwendet (könnte man jetzt vermutlich inlinen)"
]
},
{
"cell_type": "code",
"execution_count": 13,
"metadata": {},
"outputs": [],
"source": [
"def gridsearch(base, params, n_jobs = None, scoring = 'neg_mean_squared_error', cv = 5):\n",
" if n_jobs == None:\n",
" import os\n",
" n_jobs = os.cpu_count()\n",
" from sklearn.model_selection import GridSearchCV\n",
" return GridSearchCV(base, params, n_jobs = n_jobs, scoring = scoring, cv = cv)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Training\n",
"\n",
"Bei großen Datensätzen kann es zur Fehlerausgabe \"UserWarning: A worker stopped while some jobs were given to the executor. This can be caused by a too short worker timeout or by a memory leak.\" kommen. Scheint vereinzelt am Ergebnis aber nicht viel zu ändern.\n",
"\n",
"Es werden alle gegebenen Parameterkombinationen mittels Cross-Validation getestet; die besten für die Vorhersage verwendet und dann auch ausgegeben."
]
},
{
"cell_type": "code",
"execution_count": 14,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning:\n",
"\n",
"`max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
"\n"
]
},
{
"data": {
"text/plain": [
"{'max_depth': 10, 'max_features': 'auto', 'n_estimators': 30}"
]
},
"execution_count": 14,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"from sklearn.ensemble import ExtraTreesRegressor\n",
"clf = gridsearch(ExtraTreesRegressor(),\n",
" [{'n_estimators': range(10, 151, 10), # range(50, 151, 25) woher kommt dieser Range ??? bzw. wie hast du diesen bestimmt\n",
" #'criterion': 'mse', # or mae\n",
" 'max_depth': [None] + list(range(5, 30, 5)), # [None] + list(range(5, 30, 5)) woher kommt die Tiefe???\n",
" 'max_features': ['auto', 'sqrt', 'log2']}])\n",
"clf.fit(data[TRAINING_RANGE[0]:TRAINING_RANGE[1]], target[TRAINING_RANGE[0]:TRAINING_RANGE[1]])\n",
"\n",
"clf.best_params_"
]
},
{
"cell_type": "code",
"execution_count": 15,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"{'mean_fit_time': array([ 0.76742554, 1.59367871, 2.40716705, 2.96876788, 3.60309072,\n",
" 4.28540802, 6.41443558, 8.59517479, 10.40094461, 11.78280692,\n",
" 11.96198049, 12.37141967, 13.30578485, 14.33118324, 15.4039238 ,\n",
" 0.0971467 , 0.18501339, 0.27197189, 0.37351727, 0.44626327,\n",
" 0.54063849, 0.62397966, 0.70640478, 0.80144973, 0.89924922,\n",
" 0.9861989 , 1.08484874, 1.17318306, 1.25696516, 1.34836216,\n",
" 0.06538944, 0.12961268, 0.19013028, 0.2449873 , 0.31496029,\n",
" 0.37015281, 0.42959089, 0.48539529, 0.55683017, 0.60459528,\n",
" 0.66702285, 0.74246244, 0.79646344, 0.85169735, 0.93041267,\n",
" 0.45165439, 0.93129153, 1.44718623, 1.8834106 , 2.36375217,\n",
" 2.83906541, 3.27285752, 3.81540036, 4.26078887, 4.65904646,\n",
" 5.20145745, 5.81503711, 6.59189768, 7.31425605, 7.92685132,\n",
" 0.06030006, 0.1277493 , 0.16155777, 0.23977342, 0.24831529,\n",
" 0.29288745, 0.37313361, 0.4231317 , 0.51296096, 0.49702225,\n",
" 0.59252167, 0.62507353, 0.68378577, 0.75570283, 0.89288979,\n",
" 0.04556255, 0.08406444, 0.11632085, 0.14685063, 0.18042641,\n",
" 0.2154984 , 0.25383406, 0.30398922, 0.32567778, 0.36112418,\n",
" 0.48039455, 0.52644672, 0.52096038, 0.51773038, 0.56254635,\n",
" 0.96349216, 1.74700031, 2.70880475, 3.62742443, 4.3028729 ,\n",
" 5.77277036, 6.80227175, 7.26135564, 8.1784349 , 8.6220912 ,\n",
" 10.13566604, 11.06224728, 11.43535333, 12.37456284, 13.60931439,\n",
" 0.09814224, 0.15538816, 0.2159039 , 0.29649816, 0.41454825,\n",
" 0.53023758, 0.497264 , 0.69957666, 0.70203705, 0.86992202,\n",
" 0.79455457, 0.84653654, 0.92664423, 0.97785325, 1.17697105,\n",
" 0.06753793, 0.12679672, 0.14422169, 0.23811879, 0.23826828,\n",
" 0.26836357, 0.31834483, 0.38612328, 0.56462793, 0.6106349 ,\n",
" 0.61000533, 0.63838878, 0.64548755, 0.68801641, 0.82744946,\n",
" 1.28273034, 2.2976233 , 3.19391055, 4.23532619, 5.05803943,\n",
" 6.05001693, 6.99997153, 8.01234241, 9.53076463, 12.02376814,\n",
" 12.36792831, 12.126021 , 13.09200311, 14.13422008, 16.62731056,\n",
" 0.08919706, 0.1698678 , 0.25351162, 0.33951597, 0.49406657,\n",
" 0.6814466 , 0.80368805, 0.8940032 , 1.00371003, 1.0727994 ,\n",
" 1.14241657, 1.31141276, 1.31504812, 1.4657331 , 1.59373441,\n",
" 0.07627368, 0.13848834, 0.19201021, 0.27288852, 0.35024786,\n",
" 0.38515248, 0.48116674, 0.56142673, 0.61736202, 0.73496246,\n",
" 0.77362952, 0.81729612, 0.755093 , 0.90420108, 1.14810071,\n",
" 1.4651566 , 2.60681229, 3.46762018, 4.56561823, 5.61182561,\n",
" 6.78867111, 7.36766567, 8.23273888, 9.22503781, 10.98636432,\n",
" 12.07987528, 12.56972394, 13.31171155, 14.99303727, 16.25762091,\n",
" 0.10615735, 0.19916868, 0.29162807, 0.34974694, 0.48922839,\n",
" 0.53560462, 0.63702908, 0.71479955, 0.81328707, 0.90826068,\n",
" 0.98779678, 1.09777308, 1.2377511 , 1.24945588, 1.35365701,\n",
" 0.06768188, 0.12184019, 0.18550196, 0.24661398, 0.29960589,\n",
" 0.3644762 , 0.43709788, 0.48740253, 0.54465303, 0.61489768,\n",
" 0.68303862, 0.73757834, 0.77604957, 0.83795037, 0.88728266,\n",
" 1.05350041, 2.11901388, 3.14330039, 4.14605684, 5.23948989,\n",
" 6.2884563 , 8.12185059, 10.80232301, 11.63278837, 13.36440754,\n",
" 15.27960968, 17.5897079 , 19.25841675, 20.69372396, 21.49457574,\n",
" 0.12101407, 0.23543725, 0.36546841, 0.46100888, 0.63621306,\n",
" 0.70659566, 0.77198524, 0.87742248, 0.99621396, 1.14121447,\n",
" 1.26780167, 1.38912587, 1.54055686, 1.60529227, 1.77414746,\n",
" 0.08419523, 0.16974587, 0.24338508, 0.30881424, 0.38646231,\n",
" 0.48374453, 0.65572577, 0.72378554, 0.796841 , 0.84118133,\n",
" 0.96884942, 1.21152925, 1.38423066, 1.36233373, 1.21298108]),\n",
" 'std_fit_time': array([0.06464199, 0.05500136, 0.08120297, 0.11348235, 0.16066446,\n",
" 0.41081766, 0.70999249, 0.47763909, 0.60133171, 0.30110774,\n",
" 0.16680913, 0.44446263, 0.65642721, 0.68984789, 0.69413378,\n",
" 0.00325938, 0.00768321, 0.01324165, 0.01380224, 0.02528446,\n",
" 0.01543103, 0.02921876, 0.02508836, 0.02475037, 0.01742597,\n",
" 0.01737943, 0.03182488, 0.06467832, 0.07186308, 0.04486085,\n",
" 0.00343642, 0.00889601, 0.0106354 , 0.01216083, 0.01680061,\n",
" 0.00822477, 0.01733437, 0.01026052, 0.01669627, 0.02853267,\n",
" 0.01927786, 0.03238217, 0.02916449, 0.01556056, 0.05130542,\n",
" 0.01401331, 0.02306618, 0.01774401, 0.07395947, 0.03343157,\n",
" 0.09659112, 0.06380957, 0.12081681, 0.17240564, 0.12484342,\n",
" 0.19623006, 0.22262577, 0.36024329, 0.37212147, 0.31125946,\n",
" 0.00562678, 0.02571752, 0.03049214, 0.03486516, 0.01386237,\n",
" 0.0235969 , 0.03765273, 0.06299097, 0.03998502, 0.02116283,\n",
" 0.03655334, 0.06192981, 0.05820345, 0.06717839, 0.08655225,\n",
" 0.00914498, 0.01410367, 0.01397523, 0.01086611, 0.02239815,\n",
" 0.02345575, 0.0140728 , 0.02545504, 0.03707134, 0.03227538,\n",
" 0.08096537, 0.02978201, 0.02319001, 0.04327471, 0.03824807,\n",
" 0.06756352, 0.1119552 , 0.13415938, 0.21334524, 0.18782295,\n",
" 0.26697412, 0.18110621, 0.27891507, 0.14395822, 0.40127743,\n",
" 0.57754718, 0.37185264, 0.31194259, 0.50714875, 0.28913512,\n",
" 0.02437782, 0.00676064, 0.0120839 , 0.02135435, 0.04677282,\n",
" 0.06161429, 0.01325148, 0.08114917, 0.04769311, 0.04244566,\n",
" 0.01702779, 0.02789691, 0.02763224, 0.01232092, 0.04773943,\n",
" 0.01059273, 0.02297445, 0.00626139, 0.04026825, 0.01115798,\n",
" 0.00318693, 0.00622551, 0.02398376, 0.04361096, 0.06738242,\n",
" 0.04243992, 0.07662459, 0.01791227, 0.100096 , 0.08657557,\n",
" 0.05046906, 0.09480074, 0.12867909, 0.07023567, 0.12424587,\n",
" 0.25048963, 0.37101955, 0.33814325, 0.6200113 , 0.96429621,\n",
" 0.39231427, 0.37292496, 0.48875776, 0.89358708, 1.6282067 ,\n",
" 0.0043924 , 0.00506721, 0.00858216, 0.00915771, 0.0510767 ,\n",
" 0.07115914, 0.09714446, 0.05487629, 0.05602676, 0.08702971,\n",
" 0.09467973, 0.07602358, 0.05188081, 0.09441497, 0.0292244 ,\n",
" 0.0182541 , 0.01769038, 0.03332164, 0.0307917 , 0.0379745 ,\n",
" 0.01679562, 0.01538247, 0.05237519, 0.05585883, 0.02795474,\n",
" 0.03455242, 0.04403889, 0.03789796, 0.04187474, 0.08907306,\n",
" 0.13298527, 0.12253059, 0.10182726, 0.26233453, 0.28685625,\n",
" 0.22673226, 0.21923754, 0.44989556, 0.49433689, 0.78963928,\n",
" 0.36239013, 0.61723021, 0.57097072, 0.89657865, 0.64087246,\n",
" 0.01087369, 0.01935174, 0.02909633, 0.0130759 , 0.03963792,\n",
" 0.02553224, 0.02946354, 0.03532289, 0.03627692, 0.03896694,\n",
" 0.05169964, 0.0659835 , 0.06114282, 0.0602301 , 0.08166079,\n",
" 0.00269181, 0.00347375, 0.00761557, 0.00899742, 0.01479951,\n",
" 0.00912168, 0.01297913, 0.02145531, 0.01849212, 0.05476298,\n",
" 0.02659954, 0.03403707, 0.02177341, 0.02433494, 0.02175655,\n",
" 0.05739407, 0.13464125, 0.17524456, 0.17855824, 0.27682519,\n",
" 0.34395082, 0.79029346, 0.77593114, 0.33810646, 0.64187128,\n",
" 0.93569643, 1.18959621, 0.91120781, 0.80828914, 0.92532714,\n",
" 0.00680129, 0.01251057, 0.03857748, 0.04913605, 0.05646905,\n",
" 0.01578821, 0.03999989, 0.03026651, 0.03942417, 0.05202579,\n",
" 0.04194488, 0.08207969, 0.11158577, 0.08321467, 0.09175438,\n",
" 0.00564495, 0.02376698, 0.02237792, 0.01371333, 0.01883753,\n",
" 0.05260976, 0.0998498 , 0.07089127, 0.06547787, 0.02570303,\n",
" 0.08032804, 0.08028469, 0.10397331, 0.02321052, 0.07423155]),\n",
" 'mean_score_time': array([0.00452852, 0.00484481, 0.00640888, 0.00786819, 0.00826864,\n",
" 0.01181622, 0.01676283, 0.02476449, 0.02182479, 0.02295032,\n",
" 0.02766442, 0.02855144, 0.02865987, 0.03241129, 0.03569822,\n",
" 0.00413156, 0.00590577, 0.00845709, 0.01005473, 0.0121736 ,\n",
" 0.01450925, 0.01726356, 0.01873512, 0.02129636, 0.0234273 ,\n",
" 0.02571497, 0.02863927, 0.03088174, 0.03232265, 0.0366075 ,\n",
" 0.00401688, 0.00688334, 0.00902791, 0.0115706 , 0.01454148,\n",
" 0.01594253, 0.01886983, 0.02117286, 0.02394705, 0.02545257,\n",
" 0.02801614, 0.03051262, 0.03328266, 0.03722401, 0.03856516,\n",
" 0.00397949, 0.00603323, 0.0084074 , 0.01008835, 0.0122479 ,\n",
" 0.01450629, 0.01655335, 0.01905565, 0.02119598, 0.02365971,\n",
" 0.02605529, 0.03902617, 0.03033624, 0.03891091, 0.03838139,\n",
" 0.00556636, 0.0059052 , 0.00818176, 0.01527534, 0.01450849,\n",
" 0.0155643 , 0.02076406, 0.01937737, 0.02954912, 0.02346501,\n",
" 0.02693658, 0.03075662, 0.02928061, 0.03240824, 0.04539824,\n",
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" 0.01451745, 0.02104278, 0.02288523, 0.02279959, 0.02793698,\n",
" 0.04132662, 0.04381971, 0.03740573, 0.03564205, 0.05376897,\n",
" 0.00391097, 0.00637665, 0.01039014, 0.01055241, 0.0128891 ,\n",
" 0.01533022, 0.01735902, 0.01853957, 0.02138271, 0.02447791,\n",
" 0.02833724, 0.0295856 , 0.02884974, 0.0331306 , 0.04144182,\n",
" 0.00442109, 0.00603709, 0.00816936, 0.01154685, 0.01399469,\n",
" 0.01492615, 0.01637979, 0.02032027, 0.02641864, 0.0274291 ,\n",
" 0.02594638, 0.02922206, 0.03182273, 0.03419614, 0.0488512 ,\n",
" 0.0086772 , 0.00732126, 0.00969324, 0.01254983, 0.01370182,\n",
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" 0.03411169, 0.03083434, 0.03813024, 0.05278506, 0.0510457 ,\n",
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" 0.01669068, 0.01644249, 0.01851931, 0.02185898, 0.03230128,\n",
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" 0.02594395, 0.03872509, 0.02981634, 0.03281074, 0.03925781,\n",
" 0.00430145, 0.00629382, 0.00910544, 0.0110363 , 0.01362572,\n",
" 0.01550555, 0.0190002 , 0.02094321, 0.02280731, 0.0260191 ,\n",
" 0.02842917, 0.03133187, 0.03222871, 0.03544221, 0.03426471,\n",
" 0.00389962, 0.00828581, 0.00803781, 0.01052713, 0.01265931,\n",
" 0.01505861, 0.02027674, 0.02306232, 0.02556081, 0.02884874,\n",
" 0.03343568, 0.03886037, 0.04013634, 0.0456296 , 0.05673361,\n",
" 0.00459757, 0.00800929, 0.01374063, 0.01519065, 0.01654444,\n",
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" 0.03179197, 0.03642645, 0.03790665, 0.04841967, 0.04666719,\n",
" 0.00544157, 0.00801959, 0.01132307, 0.01423631, 0.0174819 ,\n",
" 0.02188525, 0.03151264, 0.03045154, 0.03928127, 0.0353384 ,\n",
" 0.05195818, 0.05258384, 0.05584388, 0.04835625, 0.03330698]),\n",
" 'std_score_time': array([2.59237298e-03, 6.45427085e-04, 1.45073419e-03, 2.19102585e-03,\n",
" 4.79020423e-04, 3.07619344e-03, 3.92321654e-04, 6.42884078e-03,\n",
" 1.46665951e-03, 9.43327344e-04, 6.13692830e-03, 5.95888777e-04,\n",
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" 7.13303014e-04, 2.62682551e-03, 8.95419691e-05, 4.72274875e-04,\n",
" 1.94441506e-04, 6.12734887e-04, 1.04546978e-03, 8.85551763e-04,\n",
" 1.28618828e-03, 9.82161609e-04, 1.59607867e-03, 9.03890628e-04,\n",
" 1.55675056e-03, 1.93951946e-03, 1.32585721e-03, 1.79145842e-03,\n",
" 1.65720272e-03, 1.83890592e-04, 1.98461057e-04, 2.00178113e-04,\n",
" 6.63855127e-04, 4.32578843e-04, 6.75365433e-04, 7.57824192e-04,\n",
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" 3.83921501e-03, 2.79202133e-03, 5.92307844e-03, 1.41692493e-03,\n",
" 9.51666604e-03, 5.74148346e-04, 1.65960342e-03, 5.51892849e-03,\n",
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" 2.49357778e-04, 1.49415049e-03, 5.78962392e-03, 1.22463233e-03,\n",
" 1.10259600e-03, 5.14647684e-03, 6.49408142e-03, 1.14453145e-03,\n",
" 7.28947606e-03, 1.02327854e-02, 2.70959344e-02, 2.51848590e-03,\n",
" 2.71435640e-03, 1.63370640e-02, 1.71930142e-04, 9.88637413e-04,\n",
" 3.67161322e-03, 1.40868389e-03, 5.55268229e-04, 2.40177951e-03,\n",
" 2.54546248e-03, 8.53011267e-04, 1.22859295e-03, 1.70221014e-03,\n",
" 3.39281125e-03, 3.66692771e-03, 1.73607339e-03, 2.98205206e-03,\n",
" 1.05154773e-02, 9.62234968e-04, 4.00257281e-04, 2.17367065e-04,\n",
" 2.93397155e-03, 1.89571163e-03, 1.30116371e-03, 1.40284748e-03,\n",
" 1.67474297e-03, 8.70760753e-03, 2.99745069e-03, 1.53896226e-03,\n",
" 1.27988421e-03, 1.25922982e-03, 1.78332435e-03, 1.62936380e-02,\n",
" 5.99848469e-03, 1.39219666e-03, 8.33121643e-04, 1.46417829e-03,\n",
" 5.01243945e-04, 3.06031904e-04, 1.16862019e-03, 6.74815879e-03,\n",
" 1.00439949e-02, 4.24354406e-03, 7.86192005e-03, 4.06955446e-03,\n",
" 1.41390802e-02, 1.38915244e-02, 1.04152094e-02, 2.93805427e-04,\n",
" 5.97770133e-04, 8.91939010e-04, 3.23290860e-04, 7.76779565e-04,\n",
" 1.71543857e-03, 1.63105484e-03, 3.87858215e-03, 2.26138982e-02,\n",
" 1.56748038e-02, 1.20432746e-03, 2.85049612e-03, 2.67188894e-03,\n",
" 5.74098505e-03, 3.32468033e-03, 2.24352293e-04, 3.56526535e-04,\n",
" 6.39140072e-04, 3.73455106e-04, 2.55334443e-03, 5.54307661e-03,\n",
" 1.05203601e-02, 3.75591269e-03, 5.52707610e-03, 8.13877237e-03,\n",
" 1.40549719e-03, 7.23507638e-03, 1.00688409e-03, 1.15929885e-02,\n",
" 1.07211797e-02, 3.43232448e-03, 2.69563427e-03, 3.32275498e-03,\n",
" 4.04132272e-03, 4.65152281e-03, 8.13681703e-04, 4.98190994e-03,\n",
" 1.75891474e-03, 1.58136837e-03, 1.92466425e-02, 1.01625998e-02,\n",
" 1.61362984e-03, 5.42831296e-03, 1.39292870e-02, 1.06408163e-02,\n",
" 4.55020529e-03, 1.11092288e-03, 5.80973478e-03, 1.55078864e-03,\n",
" 3.80800197e-03, 3.14153698e-03, 8.58779557e-04, 6.28125258e-04,\n",
" 2.30619833e-03, 1.40704371e-02, 2.12773384e-03, 2.48152370e-04,\n",
" 1.09411799e-03, 2.43377965e-03, 1.70181640e-03, 3.82446867e-04,\n",
" 3.83256287e-04, 9.33432944e-04, 9.05118195e-03, 7.13220696e-04,\n",
" 2.04072355e-04, 4.61010904e-04, 9.64691264e-04, 2.17905565e-03,\n",
" 1.59484581e-03, 1.42743530e-03, 1.72717471e-02, 2.28743439e-03,\n",
" 1.50971173e-03, 8.45731062e-03, 2.99272042e-04, 2.44525582e-04,\n",
" 2.02040130e-04, 4.13281166e-04, 5.04831456e-04, 4.60384041e-04,\n",
" 4.01803107e-04, 1.90224876e-03, 1.14414096e-03, 1.12986574e-03,\n",
" 1.75138067e-03, 1.40746323e-03, 4.21362518e-04, 1.79859250e-03,\n",
" 1.76554585e-03, 2.63390422e-04, 3.83895076e-03, 7.30524969e-04,\n",
" 1.05309113e-03, 8.10915544e-04, 4.53370155e-04, 4.54575603e-04,\n",
" 6.73626718e-04, 8.02536662e-04, 1.18332082e-03, 2.11734666e-03,\n",
" 8.97299490e-03, 7.24847150e-03, 8.13302938e-03, 2.66808475e-02,\n",
" 1.11229011e-04, 1.32900452e-03, 4.64371457e-03, 4.15856877e-03,\n",
" 1.90272014e-03, 2.44008302e-03, 4.34243570e-04, 2.82202777e-03,\n",
" 1.21127245e-03, 1.83141329e-03, 1.52463602e-03, 2.66730123e-03,\n",
" 9.07645759e-04, 1.53912160e-02, 1.50172233e-03, 4.40142410e-04,\n",
" 2.34275080e-04, 5.76509191e-04, 7.45278976e-04, 8.04067831e-04,\n",
" 1.52569633e-03, 5.17490695e-03, 6.68139254e-03, 1.21261966e-02,\n",
" 4.83483683e-03, 1.00024555e-02, 1.03115818e-02, 1.43492817e-02,\n",
" 8.09002546e-03, 1.04912226e-02]),\n",
" 'param_max_depth': masked_array(data=[None, None, None, None, None, None, None, None, None,\n",
" None, None, None, None, None, None, None, None, None,\n",
" None, None, None, None, None, None, None, None, None,\n",
" None, None, None, None, None, None, None, None, None,\n",
" None, None, None, None, None, None, None, None, None,\n",
" 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5,\n",
" 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5,\n",
" 5, 5, 5, 5, 5, 5, 5, 5, 5, 10, 10, 10, 10, 10, 10, 10,\n",
" 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10,\n",
" 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10,\n",
" 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 15, 15, 15, 15,\n",
" 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15,\n",
" 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15,\n",
" 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 20,\n",
" 20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20,\n",
" 20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20,\n",
" 20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20,\n",
" 20, 20, 25, 25, 25, 25, 25, 25, 25, 25, 25, 25, 25, 25,\n",
" 25, 25, 25, 25, 25, 25, 25, 25, 25, 25, 25, 25, 25, 25,\n",
" 25, 25, 25, 25, 25, 25, 25, 25, 25, 25, 25, 25, 25, 25,\n",
" 25, 25, 25, 25, 25],\n",
" mask=[False, False, False, False, False, False, False, False,\n",
" False, False, False, False, False, False, False, False,\n",
" False, False, False, False, False, False, False, False,\n",
" False, False, False, False, False, False, False, False,\n",
" False, False, False, False, False, False, False, False,\n",
" False, False, False, False, False, False, False, False,\n",
" False, False, False, False, False, False, False, False,\n",
" False, False, False, False, False, False, False, False,\n",
" False, False, False, False, False, False, False, False,\n",
" False, False, False, False, False, False, False, False,\n",
" False, False, False, False, False, False, False, False,\n",
" False, False, False, False, False, False, False, False,\n",
" False, False, False, False, False, False, False, False,\n",
" False, False, False, False, False, False, False, False,\n",
" False, False, False, False, False, False, False, False,\n",
" False, False, False, False, False, False, False, False,\n",
" False, False, False, False, False, False, False, False,\n",
" False, False, False, False, False, False, False, False,\n",
" False, False, False, False, False, False, False, False,\n",
" False, False, False, False, False, False, False, False,\n",
" False, False, False, False, False, False, False, False,\n",
" False, False, False, False, False, False, False, False,\n",
" False, False, False, False, False, False, False, False,\n",
" False, False, False, False, False, False, False, False,\n",
" False, False, False, False, False, False, False, False,\n",
" False, False, False, False, False, False, False, False,\n",
" False, False, False, False, False, False, False, False,\n",
" False, False, False, False, False, False, False, False,\n",
" False, False, False, False, False, False, False, False,\n",
" False, False, False, False, False, False, False, False,\n",
" False, False, False, False, False, False, False, False,\n",
" False, False, False, False, False, False, False, False,\n",
" False, False, False, False, False, False, False, False,\n",
" False, False, False, False, False, False],\n",
" fill_value='?',\n",
" dtype=object),\n",
" 'param_max_features': masked_array(data=['auto', 'auto', 'auto', 'auto', 'auto', 'auto', 'auto',\n",
" 'auto', 'auto', 'auto', 'auto', 'auto', 'auto', 'auto',\n",
" 'auto', 'sqrt', 'sqrt', 'sqrt', 'sqrt', 'sqrt', 'sqrt',\n",
" 'sqrt', 'sqrt', 'sqrt', 'sqrt', 'sqrt', 'sqrt', 'sqrt',\n",
" 'sqrt', 'sqrt', 'log2', 'log2', 'log2', 'log2', 'log2',\n",
" 'log2', 'log2', 'log2', 'log2', 'log2', 'log2', 'log2',\n",
" 'log2', 'log2', 'log2', 'auto', 'auto', 'auto', 'auto',\n",
" 'auto', 'auto', 'auto', 'auto', 'auto', 'auto', 'auto',\n",
" 'auto', 'auto', 'auto', 'auto', 'sqrt', 'sqrt', 'sqrt',\n",
" 'sqrt', 'sqrt', 'sqrt', 'sqrt', 'sqrt', 'sqrt', 'sqrt',\n",
" 'sqrt', 'sqrt', 'sqrt', 'sqrt', 'sqrt', 'log2', 'log2',\n",
" 'log2', 'log2', 'log2', 'log2', 'log2', 'log2', 'log2',\n",
" 'log2', 'log2', 'log2', 'log2', 'log2', 'log2', 'auto',\n",
" 'auto', 'auto', 'auto', 'auto', 'auto', 'auto', 'auto',\n",
" 'auto', 'auto', 'auto', 'auto', 'auto', 'auto', 'auto',\n",
" 'sqrt', 'sqrt', 'sqrt', 'sqrt', 'sqrt', 'sqrt', 'sqrt',\n",
" 'sqrt', 'sqrt', 'sqrt', 'sqrt', 'sqrt', 'sqrt', 'sqrt',\n",
" 'sqrt', 'log2', 'log2', 'log2', 'log2', 'log2', 'log2',\n",
" 'log2', 'log2', 'log2', 'log2', 'log2', 'log2', 'log2',\n",
" 'log2', 'log2', 'auto', 'auto', 'auto', 'auto', 'auto',\n",
" 'auto', 'auto', 'auto', 'auto', 'auto', 'auto', 'auto',\n",
" 'auto', 'auto', 'auto', 'sqrt', 'sqrt', 'sqrt', 'sqrt',\n",
" 'sqrt', 'sqrt', 'sqrt', 'sqrt', 'sqrt', 'sqrt', 'sqrt',\n",
" 'sqrt', 'sqrt', 'sqrt', 'sqrt', 'log2', 'log2', 'log2',\n",
" 'log2', 'log2', 'log2', 'log2', 'log2', 'log2', 'log2',\n",
" 'log2', 'log2', 'log2', 'log2', 'log2', 'auto', 'auto',\n",
" 'auto', 'auto', 'auto', 'auto', 'auto', 'auto', 'auto',\n",
" 'auto', 'auto', 'auto', 'auto', 'auto', 'auto', 'sqrt',\n",
" 'sqrt', 'sqrt', 'sqrt', 'sqrt', 'sqrt', 'sqrt', 'sqrt',\n",
" 'sqrt', 'sqrt', 'sqrt', 'sqrt', 'sqrt', 'sqrt', 'sqrt',\n",
" 'log2', 'log2', 'log2', 'log2', 'log2', 'log2', 'log2',\n",
" 'log2', 'log2', 'log2', 'log2', 'log2', 'log2', 'log2',\n",
" 'log2', 'auto', 'auto', 'auto', 'auto', 'auto', 'auto',\n",
" 'auto', 'auto', 'auto', 'auto', 'auto', 'auto', 'auto',\n",
" 'auto', 'auto', 'sqrt', 'sqrt', 'sqrt', 'sqrt', 'sqrt',\n",
" 'sqrt', 'sqrt', 'sqrt', 'sqrt', 'sqrt', 'sqrt', 'sqrt',\n",
" 'sqrt', 'sqrt', 'sqrt', 'log2', 'log2', 'log2', 'log2',\n",
" 'log2', 'log2', 'log2', 'log2', 'log2', 'log2', 'log2',\n",
" 'log2', 'log2', 'log2', 'log2'],\n",
" mask=[False, False, False, False, False, False, False, False,\n",
" False, False, False, False, False, False, False, False,\n",
" False, False, False, False, False, False, False, False,\n",
" False, False, False, False, False, False, False, False,\n",
" False, False, False, False, False, False, False, False,\n",
" False, False, False, False, False, False, False, False,\n",
" False, False, False, False, False, False, False, False,\n",
" False, False, False, False, False, False, False, False,\n",
" False, False, False, False, False, False, False, False,\n",
" False, False, False, False, False, False, False, False,\n",
" False, False, False, False, False, False, False, False,\n",
" False, False, False, False, False, False, False, False,\n",
" False, False, False, False, False, False, False, False,\n",
" False, False, False, False, False, False, False, False,\n",
" False, False, False, False, False, False, False, False,\n",
" False, False, False, False, False, False, False, False,\n",
" False, False, False, False, False, False, False, False,\n",
" False, False, False, False, False, False, False, False,\n",
" False, False, False, False, False, False, False, False,\n",
" False, False, False, False, False, False, False, False,\n",
" False, False, False, False, False, False, False, False,\n",
" False, False, False, False, False, False, False, False,\n",
" False, False, False, False, False, False, False, False,\n",
" False, False, False, False, False, False, False, False,\n",
" False, False, False, False, False, False, False, False,\n",
" False, False, False, False, False, False, False, False,\n",
" False, False, False, False, False, False, False, False,\n",
" False, False, False, False, False, False, False, False,\n",
" False, False, False, False, False, False, False, False,\n",
" False, False, False, False, False, False, False, False,\n",
" False, False, False, False, False, False, False, False,\n",
" False, False, False, False, False, False, False, False,\n",
" False, False, False, False, False, False, False, False,\n",
" False, False, False, False, False, False],\n",
" fill_value='?',\n",
" dtype=object),\n",
" 'param_n_estimators': masked_array(data=[10, 20, 30, 40, 50, 60, 70, 80, 90, 100, 110, 120, 130,\n",
" 140, 150, 10, 20, 30, 40, 50, 60, 70, 80, 90, 100, 110,\n",
" 120, 130, 140, 150, 10, 20, 30, 40, 50, 60, 70, 80, 90,\n",
" 100, 110, 120, 130, 140, 150, 10, 20, 30, 40, 50, 60,\n",
" 70, 80, 90, 100, 110, 120, 130, 140, 150, 10, 20, 30,\n",
" 40, 50, 60, 70, 80, 90, 100, 110, 120, 130, 140, 150,\n",
" 10, 20, 30, 40, 50, 60, 70, 80, 90, 100, 110, 120, 130,\n",
" 140, 150, 10, 20, 30, 40, 50, 60, 70, 80, 90, 100, 110,\n",
" 120, 130, 140, 150, 10, 20, 30, 40, 50, 60, 70, 80, 90,\n",
" 100, 110, 120, 130, 140, 150, 10, 20, 30, 40, 50, 60,\n",
" 70, 80, 90, 100, 110, 120, 130, 140, 150, 10, 20, 30,\n",
" 40, 50, 60, 70, 80, 90, 100, 110, 120, 130, 140, 150,\n",
" 10, 20, 30, 40, 50, 60, 70, 80, 90, 100, 110, 120, 130,\n",
" 140, 150, 10, 20, 30, 40, 50, 60, 70, 80, 90, 100, 110,\n",
" 120, 130, 140, 150, 10, 20, 30, 40, 50, 60, 70, 80, 90,\n",
" 100, 110, 120, 130, 140, 150, 10, 20, 30, 40, 50, 60,\n",
" 70, 80, 90, 100, 110, 120, 130, 140, 150, 10, 20, 30,\n",
" 40, 50, 60, 70, 80, 90, 100, 110, 120, 130, 140, 150,\n",
" 10, 20, 30, 40, 50, 60, 70, 80, 90, 100, 110, 120, 130,\n",
" 140, 150, 10, 20, 30, 40, 50, 60, 70, 80, 90, 100, 110,\n",
" 120, 130, 140, 150, 10, 20, 30, 40, 50, 60, 70, 80, 90,\n",
" 100, 110, 120, 130, 140, 150],\n",
" mask=[False, False, False, False, False, False, False, False,\n",
" False, False, False, False, False, False, False, False,\n",
" False, False, False, False, False, False, False, False,\n",
" False, False, False, False, False, False, False, False,\n",
" False, False, False, False, False, False, False, False,\n",
" False, False, False, False, False, False, False, False,\n",
" False, False, False, False, False, False, False, False,\n",
" False, False, False, False, False, False, False, False,\n",
" False, False, False, False, False, False, False, False,\n",
" False, False, False, False, False, False, False, False,\n",
" False, False, False, False, False, False, False, False,\n",
" False, False, False, False, False, False, False, False,\n",
" False, False, False, False, False, False, False, False,\n",
" False, False, False, False, False, False, False, False,\n",
" False, False, False, False, False, False, False, False,\n",
" False, False, False, False, False, False, False, False,\n",
" False, False, False, False, False, False, False, False,\n",
" False, False, False, False, False, False, False, False,\n",
" False, False, False, False, False, False, False, False,\n",
" False, False, False, False, False, False, False, False,\n",
" False, False, False, False, False, False, False, False,\n",
" False, False, False, False, False, False, False, False,\n",
" False, False, False, False, False, False, False, False,\n",
" False, False, False, False, False, False, False, False,\n",
" False, False, False, False, False, False, False, False,\n",
" False, False, False, False, False, False, False, False,\n",
" False, False, False, False, False, False, False, False,\n",
" False, False, False, False, False, False, False, False,\n",
" False, False, False, False, False, False, False, False,\n",
" False, False, False, False, False, False, False, False,\n",
" False, False, False, False, False, False, False, False,\n",
" False, False, False, False, False, False, False, False,\n",
" False, False, False, False, False, False, False, False,\n",
" False, False, False, False, False, False],\n",
" fill_value='?',\n",
" dtype=object),\n",
" 'params': [{'max_depth': None, 'max_features': 'auto', 'n_estimators': 10},\n",
" {'max_depth': None, 'max_features': 'auto', 'n_estimators': 20},\n",
" {'max_depth': None, 'max_features': 'auto', 'n_estimators': 30},\n",
" {'max_depth': None, 'max_features': 'auto', 'n_estimators': 40},\n",
" {'max_depth': None, 'max_features': 'auto', 'n_estimators': 50},\n",
" {'max_depth': None, 'max_features': 'auto', 'n_estimators': 60},\n",
" {'max_depth': None, 'max_features': 'auto', 'n_estimators': 70},\n",
" {'max_depth': None, 'max_features': 'auto', 'n_estimators': 80},\n",
" {'max_depth': None, 'max_features': 'auto', 'n_estimators': 90},\n",
" {'max_depth': None, 'max_features': 'auto', 'n_estimators': 100},\n",
" {'max_depth': None, 'max_features': 'auto', 'n_estimators': 110},\n",
" {'max_depth': None, 'max_features': 'auto', 'n_estimators': 120},\n",
" {'max_depth': None, 'max_features': 'auto', 'n_estimators': 130},\n",
" {'max_depth': None, 'max_features': 'auto', 'n_estimators': 140},\n",
" {'max_depth': None, 'max_features': 'auto', 'n_estimators': 150},\n",
" {'max_depth': None, 'max_features': 'sqrt', 'n_estimators': 10},\n",
" {'max_depth': None, 'max_features': 'sqrt', 'n_estimators': 20},\n",
" {'max_depth': None, 'max_features': 'sqrt', 'n_estimators': 30},\n",
" {'max_depth': None, 'max_features': 'sqrt', 'n_estimators': 40},\n",
" {'max_depth': None, 'max_features': 'sqrt', 'n_estimators': 50},\n",
" {'max_depth': None, 'max_features': 'sqrt', 'n_estimators': 60},\n",
" {'max_depth': None, 'max_features': 'sqrt', 'n_estimators': 70},\n",
" {'max_depth': None, 'max_features': 'sqrt', 'n_estimators': 80},\n",
" {'max_depth': None, 'max_features': 'sqrt', 'n_estimators': 90},\n",
" {'max_depth': None, 'max_features': 'sqrt', 'n_estimators': 100},\n",
" {'max_depth': None, 'max_features': 'sqrt', 'n_estimators': 110},\n",
" {'max_depth': None, 'max_features': 'sqrt', 'n_estimators': 120},\n",
" {'max_depth': None, 'max_features': 'sqrt', 'n_estimators': 130},\n",
" {'max_depth': None, 'max_features': 'sqrt', 'n_estimators': 140},\n",
" {'max_depth': None, 'max_features': 'sqrt', 'n_estimators': 150},\n",
" {'max_depth': None, 'max_features': 'log2', 'n_estimators': 10},\n",
" {'max_depth': None, 'max_features': 'log2', 'n_estimators': 20},\n",
" {'max_depth': None, 'max_features': 'log2', 'n_estimators': 30},\n",
" {'max_depth': None, 'max_features': 'log2', 'n_estimators': 40},\n",
" {'max_depth': None, 'max_features': 'log2', 'n_estimators': 50},\n",
" {'max_depth': None, 'max_features': 'log2', 'n_estimators': 60},\n",
" {'max_depth': None, 'max_features': 'log2', 'n_estimators': 70},\n",
" {'max_depth': None, 'max_features': 'log2', 'n_estimators': 80},\n",
" {'max_depth': None, 'max_features': 'log2', 'n_estimators': 90},\n",
" {'max_depth': None, 'max_features': 'log2', 'n_estimators': 100},\n",
" {'max_depth': None, 'max_features': 'log2', 'n_estimators': 110},\n",
" {'max_depth': None, 'max_features': 'log2', 'n_estimators': 120},\n",
" {'max_depth': None, 'max_features': 'log2', 'n_estimators': 130},\n",
" {'max_depth': None, 'max_features': 'log2', 'n_estimators': 140},\n",
" {'max_depth': None, 'max_features': 'log2', 'n_estimators': 150},\n",
" {'max_depth': 5, 'max_features': 'auto', 'n_estimators': 10},\n",
" {'max_depth': 5, 'max_features': 'auto', 'n_estimators': 20},\n",
" {'max_depth': 5, 'max_features': 'auto', 'n_estimators': 30},\n",
" {'max_depth': 5, 'max_features': 'auto', 'n_estimators': 40},\n",
" {'max_depth': 5, 'max_features': 'auto', 'n_estimators': 50},\n",
" {'max_depth': 5, 'max_features': 'auto', 'n_estimators': 60},\n",
" {'max_depth': 5, 'max_features': 'auto', 'n_estimators': 70},\n",
" {'max_depth': 5, 'max_features': 'auto', 'n_estimators': 80},\n",
" {'max_depth': 5, 'max_features': 'auto', 'n_estimators': 90},\n",
" {'max_depth': 5, 'max_features': 'auto', 'n_estimators': 100},\n",
" {'max_depth': 5, 'max_features': 'auto', 'n_estimators': 110},\n",
" {'max_depth': 5, 'max_features': 'auto', 'n_estimators': 120},\n",
" {'max_depth': 5, 'max_features': 'auto', 'n_estimators': 130},\n",
" {'max_depth': 5, 'max_features': 'auto', 'n_estimators': 140},\n",
" {'max_depth': 5, 'max_features': 'auto', 'n_estimators': 150},\n",
" {'max_depth': 5, 'max_features': 'sqrt', 'n_estimators': 10},\n",
" {'max_depth': 5, 'max_features': 'sqrt', 'n_estimators': 20},\n",
" {'max_depth': 5, 'max_features': 'sqrt', 'n_estimators': 30},\n",
" {'max_depth': 5, 'max_features': 'sqrt', 'n_estimators': 40},\n",
" {'max_depth': 5, 'max_features': 'sqrt', 'n_estimators': 50},\n",
" {'max_depth': 5, 'max_features': 'sqrt', 'n_estimators': 60},\n",
" {'max_depth': 5, 'max_features': 'sqrt', 'n_estimators': 70},\n",
" {'max_depth': 5, 'max_features': 'sqrt', 'n_estimators': 80},\n",
" {'max_depth': 5, 'max_features': 'sqrt', 'n_estimators': 90},\n",
" {'max_depth': 5, 'max_features': 'sqrt', 'n_estimators': 100},\n",
" {'max_depth': 5, 'max_features': 'sqrt', 'n_estimators': 110},\n",
" {'max_depth': 5, 'max_features': 'sqrt', 'n_estimators': 120},\n",
" {'max_depth': 5, 'max_features': 'sqrt', 'n_estimators': 130},\n",
" {'max_depth': 5, 'max_features': 'sqrt', 'n_estimators': 140},\n",
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" -26.64780641, -31.94041323, -31.56101119, -22.02540469,\n",
" -28.50616442, -40.87381484, -28.89974282, -39.86271409,\n",
" -34.2233088 , -134.99507684, -30.67442101, -63.59099033,\n",
" -39.70169114, -53.75028623, -62.49052087, -62.72902273,\n",
" -41.05338488, -63.25199058, -39.4152885 , -35.92570004,\n",
" -58.15455518, -86.51559444, -27.98077973, -47.82761562,\n",
" -23.69167813, -19.3159365 , -30.78433673, -16.80154095,\n",
" -16.34799852, -25.78557753, -28.44095432, -17.80683965,\n",
" -26.41574192, -20.58563141, -23.49556252, -30.97228585,\n",
" -29.46856717, -26.00845057, -20.29182977, -15.04500744,\n",
" -16.62637776, -15.17098324, -32.9751911 , -18.69636368,\n",
" -26.22455329, -34.39479742, -45.55520044, -32.52776532,\n",
" -40.43616115, -48.52913943, -49.44993097, -31.66730207,\n",
" -36.54401048, -23.55858001, -205.69465576, -31.87862172,\n",
" -50.12719952, -76.1897053 , -68.87346684, -37.28793404,\n",
" -94.26172412, -41.86442322, -58.15000865, -44.21113705,\n",
" -99.20394684, -88.36915198, -53.05786252, -37.7794551 ,\n",
" -59.75652838, -27.41332441, -17.43844634, -24.50770653,\n",
" -24.34636316, -19.42246322, -26.88901849, -20.35994159,\n",
" -27.98566332, -25.57539725, -31.23840437, -23.16705785,\n",
" -25.40470676, -26.88740055, -20.96314157, -26.51656895,\n",
" -49.89468679, -12.87594271, -35.67376215, -35.23848668,\n",
" -27.6266006 , -17.76210503, -27.37053924, -48.56779533,\n",
" -70.83049529, -51.59210865, -23.18887148, -38.47665829,\n",
" -23.56483964, -29.02174305, -34.32092805, -33.98985538,\n",
" -105.72711731, -80.19683901, -51.70988855, -26.29311754,\n",
" -31.42876276, -75.38780555, -68.46567022, -63.13263364,\n",
" -69.73215739, -78.5232553 , -58.25055678, -47.437882 ,\n",
" -47.61114157, -48.03952623]),\n",
" 'mean_test_score': array([ -77.47614299, -78.31825657, -61.03439174, -62.20066576,\n",
" -62.23392412, -59.25753254, -63.01503765, -67.02837925,\n",
" -70.90764857, -70.35651292, -63.65816973, -64.2181851 ,\n",
" -59.7901169 , -60.95742191, -66.17925045, -99.01566208,\n",
" -110.71911439, -96.45233492, -110.62429876, -103.94020179,\n",
" -95.71320568, -98.25690933, -95.75601697, -100.11318056,\n",
" -100.41373377, -100.0241686 , -97.93293109, -97.46380635,\n",
" -96.83815912, -99.7505395 , -121.02313761, -107.32137831,\n",
" -113.98021069, -116.05354908, -107.59625029, -102.65673951,\n",
" -107.88576941, -106.43777886, -106.89638782, -107.36700233,\n",
" -104.18045867, -111.55225212, -103.50495825, -106.08990252,\n",
" -102.48506308, -118.35915465, -77.08278075, -56.59224811,\n",
" -67.85009033, -68.49111736, -63.2688823 , -73.88011444,\n",
" -60.38187524, -72.47359315, -70.95488902, -70.47047607,\n",
" -71.81841115, -68.93173685, -66.67849674, -67.53152769,\n",
" -195.73469948, -94.02085543, -111.64666241, -108.50270981,\n",
" -108.54196166, -113.64697073, -100.32397639, -99.2257659 ,\n",
" -110.16698184, -93.97684618, -103.09493474, -102.75553909,\n",
" -105.34858079, -99.66217181, -100.46772945, -120.97983558,\n",
" -160.12149274, -120.15403696, -134.11195133, -143.07260703,\n",
" -137.43131186, -131.32364091, -142.83232928, -128.7071415 ,\n",
" -146.22209407, -136.6936957 , -129.37563699, -130.9865114 ,\n",
" -136.26470719, -137.7196227 , -54.61209109, -72.2377874 ,\n",
" -54.5641659 , -58.80658252, -58.28197206, -64.27697854,\n",
" -65.37829018, -59.44768858, -66.31464603, -61.58981426,\n",
" -62.41336266, -60.43010693, -64.78181835, -64.61272501,\n",
" -58.81042918, -105.10967465, -92.48976299, -97.74028387,\n",
" -102.14603923, -90.06181589, -90.52630352, -104.08252343,\n",
" -98.44616994, -101.80043944, -98.14602818, -91.8235918 ,\n",
" -99.01288851, -102.71728504, -99.09508174, -97.83181432,\n",
" -133.34040584, -107.18129575, -110.59513865, -110.3142675 ,\n",
" -123.57791227, -95.24695739, -106.84012064, -111.06140343,\n",
" -109.1390985 , -123.10589298, -104.81290658, -101.88602355,\n",
" -106.59754006, -104.01364166, -112.14995059, -66.38023534,\n",
" -74.20574938, -67.32548362, -64.81373108, -64.84213703,\n",
" -58.53722855, -63.60897349, -60.88382105, -70.27315775,\n",
" -62.99193106, -58.08455185, -63.55147498, -56.89308503,\n",
" -59.95698702, -61.45499129, -139.03268319, -120.64824641,\n",
" -103.98406944, -92.0344498 , -103.85238367, -97.11711388,\n",
" -92.70217767, -93.86933432, -94.40171299, -100.73694348,\n",
" -94.79613269, -99.05620502, -97.74012876, -103.73881498,\n",
" -96.16699441, -129.01507405, -113.29833627, -122.72762792,\n",
" -102.44145995, -105.04371404, -112.46002532, -110.56310566,\n",
" -107.6303154 , -103.59540725, -99.73238755, -96.71703484,\n",
" -110.05211056, -110.55526188, -96.28738198, -101.72066677,\n",
" -58.90720353, -57.19325708, -66.86194437, -62.25983118,\n",
" -70.51530324, -61.55777413, -67.45354487, -62.7211389 ,\n",
" -65.26881118, -63.0833519 , -70.36142164, -67.48967147,\n",
" -60.47843468, -62.01070472, -62.76699149, -103.7018652 ,\n",
" -104.33722105, -98.50045598, -83.85731836, -101.39585578,\n",
" -88.10203058, -110.20443127, -99.56615351, -97.05821582,\n",
" -106.18887316, -100.55008858, -95.76888364, -97.44792468,\n",
" -94.92259854, -97.57154645, -176.24189787, -108.71631258,\n",
" -104.32452024, -106.38462895, -108.64477169, -111.95962394,\n",
" -108.06193376, -104.19128495, -106.16195949, -107.52565128,\n",
" -110.69745518, -112.09446519, -108.60676599, -98.15267498,\n",
" -109.72691357, -89.88605538, -59.97249703, -61.90321004,\n",
" -58.39825219, -63.10784319, -66.81117578, -70.71464804,\n",
" -68.64080563, -61.79611956, -66.82344998, -66.4420607 ,\n",
" -67.96016555, -57.75076535, -61.75538283, -61.91239469,\n",
" -112.67387916, -102.06776738, -121.52677964, -97.21329518,\n",
" -96.12221191, -93.53686706, -100.16553792, -103.21046154,\n",
" -96.4669859 , -100.27058916, -101.47066532, -105.20401702,\n",
" -99.4927585 , -94.13806222, -91.41590889, -110.47800011,\n",
" -127.4129971 , -105.09300791, -115.32228291, -97.50640525,\n",
" -99.41051875, -111.43688773, -109.27572187, -107.48301403,\n",
" -108.06355337, -109.95080828, -102.36112748, -106.80374602,\n",
" -108.9489739 , -105.58510313]),\n",
" 'std_test_score': array([ 58.26811574, 40.93420876, 42.57889031, 38.51244443,\n",
" 48.95357673, 38.00484638, 39.67837451, 41.52699034,\n",
" 49.65886433, 47.44017477, 44.80208713, 43.74924395,\n",
" 40.58362298, 39.57851723, 45.84472225, 53.67272192,\n",
" 74.93858955, 70.79862048, 66.58062834, 73.17575679,\n",
" 66.66646476, 70.38796144, 70.16157004, 72.9450207 ,\n",
" 65.29167556, 69.30706184, 67.91867528, 65.35232853,\n",
" 65.3531261 , 65.86861222, 76.88029229, 66.52756156,\n",
" 62.57921511, 55.53653269, 64.03469382, 61.27185536,\n",
" 54.7563661 , 69.83002197, 58.7694582 , 58.73637809,\n",
" 62.97690923, 67.39087495, 66.3327575 , 64.30052518,\n",
" 62.44060789, 103.80752078, 41.42195137, 36.62377723,\n",
" 48.86255527, 44.16236338, 41.64734721, 49.73866077,\n",
" 44.25780204, 46.16832373, 47.98773465, 47.99543365,\n",
" 48.22569061, 41.85795609, 45.47384508, 40.96599778,\n",
" 113.23991744, 53.76670302, 47.3650498 , 60.60883634,\n",
" 67.30180038, 50.56242995, 58.78921486, 74.44886876,\n",
" 59.36675839, 61.81265661, 64.23261225, 61.47776005,\n",
" 62.81987789, 66.53775094, 62.91728543, 78.82408106,\n",
" 75.97784543, 53.35222432, 69.10029803, 59.82189466,\n",
" 62.64297289, 63.75442876, 60.98606489, 69.27634713,\n",
" 68.27017422, 58.14211156, 60.01418728, 60.52424608,\n",
" 55.54841089, 55.95218315, 51.14649682, 47.5750827 ,\n",
" 36.71371784, 45.90410866, 39.49289594, 42.59720693,\n",
" 44.20235059, 40.73817023, 45.08137971, 41.84196781,\n",
" 43.39261309, 39.93783136, 47.03432351, 40.57991648,\n",
" 38.07764638, 53.77870351, 67.00039132, 68.42655287,\n",
" 71.0995293 , 72.48058599, 68.82307614, 57.05902698,\n",
" 68.40543877, 66.2110123 , 64.43862163, 73.20833086,\n",
" 69.86813384, 69.30081947, 66.99651661, 65.8552435 ,\n",
" 50.94899544, 55.1208268 , 71.43106681, 61.99320823,\n",
" 66.24971252, 68.60057495, 66.12459282, 55.11930868,\n",
" 63.22848927, 57.7677251 , 57.99557999, 66.15253292,\n",
" 60.80639378, 66.53747929, 61.68451872, 43.10091921,\n",
" 35.38442127, 40.06821297, 40.01534853, 42.08412901,\n",
" 41.35221124, 44.5199146 , 40.13053996, 48.09764459,\n",
" 46.65112227, 38.17403951, 41.84834514, 38.70945631,\n",
" 41.66711279, 41.77351106, 56.04418303, 69.77111058,\n",
" 56.80102631, 66.42403535, 55.33170042, 68.59177371,\n",
" 70.32367995, 61.80456625, 67.77483752, 67.21797309,\n",
" 66.86025118, 64.83020352, 71.61950429, 66.43454956,\n",
" 68.12388434, 41.50061811, 66.23260431, 69.35127096,\n",
" 73.34949483, 66.74830825, 62.87498967, 61.57916396,\n",
" 64.36250339, 61.70237329, 69.07709755, 65.49916847,\n",
" 61.53121861, 62.99314833, 68.11929812, 63.92123018,\n",
" 46.79987315, 38.16453198, 50.6240174 , 42.93082267,\n",
" 48.11852145, 44.41605485, 43.54897353, 43.62902036,\n",
" 43.71739788, 45.94561797, 48.1557157 , 43.55945253,\n",
" 40.03655983, 39.43689889, 45.2446645 , 74.45607523,\n",
" 78.43266925, 71.53667576, 64.79494311, 70.58138849,\n",
" 65.29166495, 77.71293101, 69.53292732, 67.12030653,\n",
" 72.64108811, 65.12792828, 66.30007516, 68.26781999,\n",
" 67.68260354, 71.97054944, 81.49961378, 68.50320821,\n",
" 66.0496272 , 69.24986739, 62.44569276, 64.4350026 ,\n",
" 61.43599146, 63.48800204, 66.73919761, 67.78376561,\n",
" 62.12482145, 59.54229732, 64.24007293, 66.91524515,\n",
" 68.86116965, 66.7497161 , 42.61686792, 47.56261132,\n",
" 44.41754577, 42.88799312, 43.47303828, 48.2944551 ,\n",
" 44.01055203, 41.95880797, 43.71595797, 44.04196032,\n",
" 49.17892961, 39.4711381 , 42.2245005 , 39.92212829,\n",
" 54.97385521, 80.54413074, 74.25304011, 68.05462511,\n",
" 69.98317156, 73.85500425, 65.13383818, 62.85791124,\n",
" 64.26307064, 61.86586373, 73.19491545, 61.87066544,\n",
" 74.33610377, 64.65603795, 71.77833228, 71.77267501,\n",
" 45.65033847, 57.90806333, 63.3248382 , 67.90977292,\n",
" 72.42420185, 62.78323642, 60.14690679, 61.38139799,\n",
" 63.09400312, 58.18294885, 64.3408189 , 71.45269433,\n",
" 64.97846643, 68.44704176]),\n",
" 'rank_test_score': array([ 87, 88, 24, 33, 34, 14, 40, 63, 79, 74, 46, 47, 16,\n",
" 23, 55, 135, 228, 114, 226, 174, 108, 131, 109, 146, 150, 145,\n",
" 128, 122, 117, 144, 247, 199, 240, 242, 203, 164, 205, 193, 197,\n",
" 200, 178, 231, 169, 189, 163, 243, 86, 3, 68, 70, 43, 84,\n",
" 19, 83, 80, 76, 81, 72, 59, 67, 270, 102, 232, 208, 209,\n",
" 239, 149, 138, 219, 101, 167, 166, 187, 142, 151, 246, 268, 244,\n",
" 259, 266, 262, 257, 265, 253, 267, 261, 255, 256, 260, 263, 2,\n",
" 82, 1, 11, 8, 48, 54, 15, 56, 27, 36, 20, 50, 49,\n",
" 12, 185, 97, 126, 160, 92, 93, 177, 132, 157, 129, 95, 134,\n",
" 165, 137, 127, 258, 198, 225, 221, 251, 107, 196, 229, 214, 250,\n",
" 182, 158, 194, 176, 235, 57, 85, 64, 51, 52, 10, 45, 22,\n",
" 73, 39, 7, 44, 4, 17, 25, 264, 245, 175, 96, 173, 119,\n",
" 98, 100, 104, 153, 105, 136, 125, 172, 112, 254, 238, 249, 162,\n",
" 183, 236, 224, 204, 170, 143, 116, 218, 223, 113, 156, 13, 5,\n",
" 62, 35, 77, 26, 65, 37, 53, 41, 75, 66, 21, 32, 38,\n",
" 171, 181, 133, 89, 154, 90, 220, 141, 118, 191, 152, 110, 121,\n",
" 106, 124, 269, 212, 180, 192, 211, 233, 206, 179, 190, 202, 227,\n",
" 234, 210, 130, 216, 91, 18, 30, 9, 42, 60, 78, 71, 29,\n",
" 61, 58, 69, 6, 28, 31, 237, 159, 248, 120, 111, 99, 147,\n",
" 168, 115, 148, 155, 186, 140, 103, 94, 222, 252, 184, 241, 123,\n",
" 139, 230, 215, 201, 207, 217, 161, 195, 213, 188], dtype=int32)}"
]
},
"execution_count": 15,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"clf.cv_results_"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Testen und Plotten\n",
"\n",
"Wenn mir anderem Datensatz getestet werden soll:\n",
"- Neuen Datensatz herunterladen und einlesen\n",
"- Eventuell `TEST_RANGE` anpassen\n",
"- Untere Zelle ausführen"
]
},
{
"cell_type": "code",
"execution_count": 16,
"metadata": {
"scrolled": true
},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 1080x720 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"xaxis = range(0, TEST_RANGE[1])\n",
"plot.figure(figsize=(15,10))\n",
"plot.axvline(x=TRAINING_RANGE[0])\n",
"plot.axvline(x=TRAINING_RANGE[1])\n",
"plot.plot(xaxis, target, 'b', xaxis, clf.predict(data), 'r')\n",
"plot.legend(['Training','Test','TARGET OBD Speed','PREDICTED OBD Speed'])\n",
"plot.xlabel('Sample #')\n",
"plot.ylabel('OBD-Geschwindigkeit / 100km/h')\n",
"plot.title(\"ExtreTreesRegressor\")\n",
"plot.savefig('plot-ExtraTreesRegressor.pdf')\n",
"plot.show()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Anscheinend wird immer die höchste Geschwindigkeit vorrausgesagt, die der Regressor je gesehen hat. Wird er beispielsweise mit einer Landstraßenfahrt trainiert, ist auch auf der Autobahn bei 100 km/h Schluss."
]
},
{
"cell_type": "code",
"execution_count": 17,
"metadata": {
"scrolled": true
},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 1080x1497.6 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"plot.figure(figsize = (15, 0.05*len(DATA_COLUMNS)))\n",
"importances = clf.best_estimator_.feature_importances_\n",
"stddev = np.var([t.feature_importances_ for t in clf.best_estimator_.estimators_], axis = 0)\n",
"sorted_indices = np.argsort(importances)[-30:]\n",
"plot.barh(np.array(DATA_COLUMNS)[sorted_indices], importances[sorted_indices], xerr = stddev[sorted_indices])\n",
"plot.ylabel('Feature')\n",
"plot.xlabel('Gewichtung (± Standardabweichung))')\n",
"plot.title(\"Feature-Gewichtung eines ExtreTreesRegressor\")\n",
"plot.savefig('plot-ExtraTreesRegressor-features.pdf')\n",
"plot.show()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Einige der Top-Features sprachen für starkes Overfitting:\n",
"- Temperatur und Luftfeuchtigkeit (`weat_temperature`, `weat_humidity`) bewegen kleinem Rahmen, und sollten auf das Fahrverhalten nur bedingten Einfluss haben (wenn überhaupt, nur auf längere Sicht gesehen; z.B. langsameres Fahren bei schlechtem Wetter).\n",
"- `join_idx` macht keinen Sinn.\n",
"- Position (Breiten- und Längengrad: `flt_latitude`, `latitude`, `longitude`, `flt_longitude`) funktionieren nur auf einer spezifischen Strecke. Das Lernen von Eigenheiten dieser Strecke ist nicht Aufgabe des Regressors; das sollte höchstens in anderen Datenquellen gespeichert und dann zur Berechnung hergezogen werden.\n",
"- Zeit und Entfernung (`hr_remainDistance`, `tt_calc_distance`, `ei_distance_lldist`, `hr_distance_lldist`, `gh_distance_lldist`, `time` etc.) sind schlecht auf andere Fahrten übertragbar; würde ich dieselbe Strecke von einem anderen Ausgangspunkt aus fahren, wäre die gesamte Vorhersage verschoben\n",
"- Windrichtung (`weat_windBearing`) hätte durchaus einen Einfluss (Rücken-/Gegenwind), allerdings nur, wenn die aktuelle Fahrtrichtung auch verwendet wird\n",
"\n",
"Diese Features wurden daher ausgeschlossen, was zu einer merklichen Verbesserung der Prädiktion führt (ist nun besser als HERE Maps in nahezu allen verwendeten Kriterien).\n",
"\n",
"Interessanterweise scheinen die Bäume allerdings vor allem eine Aggregation verschiedener Quellen für die Durchschnittsgeschwindigkeit zu sein …"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Gütekriterium - Prädiktion\n",
"\n",
"Berechung des Gütekritierums\n",
"- Root-mean-square deviation RMSE\n",
"- NRMSE Normalized root-mean-square deviation\n",
"- Mean absolute error MAE\n",
"- Mean absolute percentage error MAP\n",
"- Symmetric mean absolute percentage error\n",
"- https://en.wikipedia.org/wiki/Least_absolute_deviations\n",
"- https://en.wikipedia.org/wiki/Mean_signed_deviation\n",
"- Pearson Correlation Coefficient\n",
"- Accuracy (Interval of given size; absolute and relative)\n",
"- Median Absolute Deviation\n",
"\n",
"BITTE weitere Kriterien ergänzen\n"
]
},
{
"cell_type": "code",
"execution_count": 18,
"metadata": {
"scrolled": true
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"RMSE = 16.88 km/h\n",
"NRMSE = 26.48 %\n",
"MAE = 13.95 km/h\n",
"MAP = 21.98 %\n",
"SMAPE = 17.34 %\n",
"MSD = -9.15 km/h\n",
"CORR = 0.94\n",
"ACC_A = 40.67 %\n",
"ACC_R = 42.00 %\n",
"MAD = 13.49 km/h\n"
]
}
],
"source": [
"ta = target[TEST_RANGE[0]:TEST_RANGE[1]]\n",
"pr = clf.predict(data[TEST_RANGE[0]:TEST_RANGE[1]])\n",
"RMSE = math.sqrt(sum((ta-pr)**2)/len(ta))\n",
"print(\"RMSE = %.2f km/h\" %RMSE)\n",
"NRMSE = 1-math.sqrt(sum((ta-pr)**2))/math.sqrt(sum( (ta-np.mean(ta) )**2 ))\n",
"print(\"NRMSE = %.2f %%\" %(NRMSE*100))\n",
"MAE = sum(((ta-pr)**2)**(1/2))/len(ta)\n",
"print(\"MAE = %.2f km/h\" %MAE)\n",
"with np.errstate(divide = 'ignore'): map_elements = np.abs((ta - pr) / ta)\n",
"map_elements[map_elements == np.inf] = 0\n",
"MAP = np.sum(map_elements) / len(ta)\n",
"print(\"MAP = %.2f %%\" % (MAP*100))\n",
"SMAPE = np.sum(np.abs(ta - pr) / ((ta + pr) / 2)) / len(ta)\n",
"print(\"SMAPE = %.2f %%\" % (SMAPE*100))\n",
"MSD = np.sum(ta - pr) / len(ta)\n",
"print(\"MSD = %.2f km/h\" % MSD)\n",
"CORR = np.corrcoef(ta, pr)[1][0]\n",
"print(\"CORR = %.2f\" % CORR)\n",
"ACC_A_THRESHOLD = 10\n",
"ACC_A = (np.abs(ta - pr) < ACC_A_THRESHOLD).sum() / len(ta)\n",
"print(\"ACC_A = %.2f %%\" % (ACC_A*100))\n",
"ACC_R_THRESHOLD = 0.1\n",
"ACC_R = (np.abs(ta / pr - 1) < ACC_R_THRESHOLD).sum() / len(ta)\n",
"print(\"ACC_R = %.2f %%\" % (ACC_R*100))\n",
"MAD = np.median(np.abs(ta - pr))\n",
"print(\"MAD = %.2f km/h\" % MAD)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Vergleich mit HERE Maps Trafic Speed\n",
"Kann zum Vergleich sehr gut herangezogen werden ;)"
]
},
{
"cell_type": "code",
"execution_count": 19,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"RMSE = 16.82 km/h\n",
"NRMSE = 26.73 %\n",
"MAE = 14.06 km/h\n",
"MAP = 15.87 %\n",
"SMAPE = 16.62 %\n",
"MSD = 9.82 km/h\n",
"CORR = 0.81\n",
"ACC_A = 40.18 %\n",
"ACC_R = 32.00 %\n",
"MAD = 12.84 km/h\n"
]
}
],
"source": [
"ta = target[TEST_RANGE[0]:TEST_RANGE[1]]\n",
"pr = [row['hr_traficSpeed'] for row in reader_data] #t['hr_traficSpeed']\n",
"pr = np.array([float(d) if d != '' else 0.0 for d in pr])\n",
"pr = pr[TEST_RANGE[0]:TEST_RANGE[1]] * 3.6\n",
"RMSE = math.sqrt(sum((ta-pr)**2)/len(ta))\n",
"print(\"RMSE = %.2f km/h\" %RMSE)\n",
"NRMSE = 1-math.sqrt(sum((ta-pr)**2))/math.sqrt(sum( (ta-np.mean(ta) )**2 ))\n",
"print(\"NRMSE = %.2f %%\" %(NRMSE*100))\n",
"MAE = sum(((ta-pr)**2)**(1/2))/len(ta)\n",
"print(\"MAE = %.2f km/h\" %MAE)\n",
"with np.errstate(divide = 'ignore'): map_elements = np.abs((ta - pr) / ta)\n",
"map_elements[map_elements == np.inf] = 0\n",
"MAP = np.sum(map_elements) / len(ta)\n",
"print(\"MAP = %.2f %%\" % (MAP*100))\n",
"SMAPE = np.sum(np.abs(ta - pr) / ((ta + pr) / 2)) / len(ta)\n",
"print(\"SMAPE = %.2f %%\" % (SMAPE*100))\n",
"MSD = np.sum(ta - pr) / len(ta)\n",
"print(\"MSD = %.2f km/h\" % MSD)\n",
"CORR = np.corrcoef(ta, pr)[1][0]\n",
"print(\"CORR = %.2f\" % CORR)\n",
"ACC_A_THRESHOLD = 10\n",
"ACC_A = (np.abs(ta - pr) < ACC_A_THRESHOLD).sum() / len(ta)\n",
"print(\"ACC_A = %.2f %%\" % (ACC_A*100))\n",
"ACC_R_THRESHOLD = 0.1\n",
"ACC_R = (np.abs(ta / pr - 1) < ACC_R_THRESHOLD).sum() / len(ta)\n",
"print(\"ACC_R = %.2f %%\" % (ACC_R*100))\n",
"MAD = np.median(np.abs(ta - pr))\n",
"print(\"MAD = %.2f km/h\" % MAD)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Generalisierbarkeit\n",
"\n",
"Nach der abgeschlossenen Fahrt wird mit der ganzen Fahrt trainiert, und anschließend eine andere Fahrt vorhergesagt. Als Parameter werden die gefundenen Parameter der Grid Search beim ersten mal verwendet, wodurch sich der Vorgang erheblich beschleunigt."
]
},
{
"cell_type": "code",
"execution_count": 20,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning:\n",
"\n",
"`max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
"\n"
]
},
{
"data": {
"text/html": [
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],
"text/plain": [
"ExtraTreesRegressor(max_depth=10, max_features='auto', n_estimators=30)"
]
},
"execution_count": 20,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"clf2 = ExtraTreesRegressor(n_estimators = clf.best_params_['n_estimators'],\n",
" max_depth = clf.best_params_['max_depth'],\n",
" max_features = clf.best_params_['max_features'])\n",
"clf2.fit(data, target)"
]
},
{
"cell_type": "code",
"execution_count": 21,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<BarContainer object of 416 artists>"
]
},
"execution_count": 21,
"metadata": {},
"output_type": "execute_result"
},
{
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\n",
"text/plain": [
"<Figure size 1080x7488 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"plot.figure(figsize = (15, 0.25 * len(DATA_COLUMNS)))\n",
"importances = clf2.feature_importances_\n",
"stddev = np.var([t.feature_importances_ for t in clf2.estimators_], axis = 0)\n",
"sorted_indices = np.argsort(importances)\n",
"plot.barh(np.array(DATA_COLUMNS)[sorted_indices], importances[sorted_indices], xerr = stddev[sorted_indices])"
]
},
{
"cell_type": "code",
"execution_count": 22,
"metadata": {},
"outputs": [],
"source": [
"SETUP_ID_2 = 450\n",
"\n",
"reader2 = runsql('select * from computeddata where setup_id = {} order by distance asc'.format(SETUP_ID_2))\n",
"reader_data2 = list(reader2) # list(...) so that following cells can be repeated"
]
},
{
"cell_type": "code",
"execution_count": 23,
"metadata": {},
"outputs": [],
"source": [
"data2 = []\n",
"target2 = []\n",
"for row in reader_data2:\n",
" data2 += [[float(row[c]) if row[c] != '' else math.nan for c in DATA_COLUMNS]]\n",
" target2 += [float(row[TARGET_COLUMN]) if row[TARGET_COLUMN] != '' else math.nan]"
]
},
{
"cell_type": "code",
"execution_count": 24,
"metadata": {},
"outputs": [],
"source": [
"data2 = imp.transform(data2)"
]
},
{
"cell_type": "code",
"execution_count": 25,
"metadata": {},
"outputs": [],
"source": [
"np.savetxt('imputed-{}.csv'.format(SETUP_ID_2), data2, delimiter=',')\n",
"np.savetxt('target-{}.csv'.format(SETUP_ID_2), target2, delimiter=',')"
]
},
{
"cell_type": "code",
"execution_count": 26,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<matplotlib.legend.Legend at 0x7fcdd5567a30>"
]
},
"execution_count": 26,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 1080x720 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"plot.figure(figsize=(15,10))\n",
"xaxis = range(0, len(target2))\n",
"plot.plot(xaxis, target2, 'b', xaxis, clf2.predict(data2), 'r')\n",
"plot.legend(['TARGET OBD Speed','PREDICTED OBD Speed'])"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Wie bereits vorher festgestellt, scheint der Regressor mit höheren Geschwindigkeiten nicht vertraut. Trainieren wir also mit diesem Datensatz einen weiteren Regressor, und testen wieder mit einem anderen."
]
},
{
"cell_type": "code",
"execution_count": 27,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning:\n",
"\n",
"`max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
"\n"
]
},
{
"data": {
"text/html": [
"<style>#sk-container-id-2 {color: black;background-color: white;}#sk-container-id-2 pre{padding: 0;}#sk-container-id-2 div.sk-toggleable {background-color: white;}#sk-container-id-2 label.sk-toggleable__label {cursor: pointer;display: block;width: 100%;margin-bottom: 0;padding: 0.3em;box-sizing: border-box;text-align: center;}#sk-container-id-2 label.sk-toggleable__label-arrow:before {content: \"▸\";float: left;margin-right: 0.25em;color: #696969;}#sk-container-id-2 label.sk-toggleable__label-arrow:hover:before {color: black;}#sk-container-id-2 div.sk-estimator:hover label.sk-toggleable__label-arrow:before {color: black;}#sk-container-id-2 div.sk-toggleable__content {max-height: 0;max-width: 0;overflow: hidden;text-align: left;background-color: #f0f8ff;}#sk-container-id-2 div.sk-toggleable__content pre {margin: 0.2em;color: black;border-radius: 0.25em;background-color: #f0f8ff;}#sk-container-id-2 input.sk-toggleable__control:checked~div.sk-toggleable__content {max-height: 200px;max-width: 100%;overflow: auto;}#sk-container-id-2 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {content: \"▾\";}#sk-container-id-2 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-2 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-2 input.sk-hidden--visually {border: 0;clip: rect(1px 1px 1px 1px);clip: rect(1px, 1px, 1px, 1px);height: 1px;margin: -1px;overflow: hidden;padding: 0;position: absolute;width: 1px;}#sk-container-id-2 div.sk-estimator {font-family: monospace;background-color: #f0f8ff;border: 1px dotted black;border-radius: 0.25em;box-sizing: border-box;margin-bottom: 0.5em;}#sk-container-id-2 div.sk-estimator:hover {background-color: #d4ebff;}#sk-container-id-2 div.sk-parallel-item::after {content: \"\";width: 100%;border-bottom: 1px solid gray;flex-grow: 1;}#sk-container-id-2 div.sk-label:hover label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-2 div.sk-serial::before {content: \"\";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: 0;}#sk-container-id-2 div.sk-serial {display: flex;flex-direction: column;align-items: center;background-color: white;padding-right: 0.2em;padding-left: 0.2em;position: relative;}#sk-container-id-2 div.sk-item {position: relative;z-index: 1;}#sk-container-id-2 div.sk-parallel {display: flex;align-items: stretch;justify-content: center;background-color: white;position: relative;}#sk-container-id-2 div.sk-item::before, #sk-container-id-2 div.sk-parallel-item::before {content: \"\";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: -1;}#sk-container-id-2 div.sk-parallel-item {display: flex;flex-direction: column;z-index: 1;position: relative;background-color: white;}#sk-container-id-2 div.sk-parallel-item:first-child::after {align-self: flex-end;width: 50%;}#sk-container-id-2 div.sk-parallel-item:last-child::after {align-self: flex-start;width: 50%;}#sk-container-id-2 div.sk-parallel-item:only-child::after {width: 0;}#sk-container-id-2 div.sk-dashed-wrapped {border: 1px dashed gray;margin: 0 0.4em 0.5em 0.4em;box-sizing: border-box;padding-bottom: 0.4em;background-color: white;}#sk-container-id-2 div.sk-label label {font-family: monospace;font-weight: bold;display: inline-block;line-height: 1.2em;}#sk-container-id-2 div.sk-label-container {text-align: center;}#sk-container-id-2 div.sk-container {/* jupyter's `normalize.less` sets `[hidden] { display: none; }` but bootstrap.min.css set `[hidden] { display: none !important; }` so we also need the `!important` here to be able to override the default hidden behavior on the sphinx rendered scikit-learn.org. See: https://github.com/scikit-learn/scikit-learn/issues/21755 */display: inline-block !important;position: relative;}#sk-container-id-2 div.sk-text-repr-fallback {display: none;}</style><div id=\"sk-container-id-2\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>ExtraTreesRegressor(max_depth=10, max_features=&#x27;auto&#x27;, n_estimators=30)</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item\"><div class=\"sk-estimator sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-2\" type=\"checkbox\" checked><label for=\"sk-estimator-id-2\" class=\"sk-toggleable__label sk-toggleable__label-arrow\">ExtraTreesRegressor</label><div class=\"sk-toggleable__content\"><pre>ExtraTreesRegressor(max_depth=10, max_features=&#x27;auto&#x27;, n_estimators=30)</pre></div></div></div></div></div>"
],
"text/plain": [
"ExtraTreesRegressor(max_depth=10, max_features='auto', n_estimators=30)"
]
},
"execution_count": 27,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"clf3 = ExtraTreesRegressor(n_estimators = clf.best_params_['n_estimators'],\n",
" max_depth = clf.best_params_['max_depth'],\n",
" max_features = clf.best_params_['max_features'])\n",
"clf3.fit(data2, target2)"
]
},
{
"cell_type": "code",
"execution_count": 28,
"metadata": {
"scrolled": false
},
"outputs": [
{
"data": {
"text/plain": [
"<BarContainer object of 416 artists>"
]
},
"execution_count": 28,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
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\n",
"text/plain": [
"<Figure size 1080x7488 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"plot.figure(figsize = (15, 0.25 * len(DATA_COLUMNS)))\n",
"importances = clf3.feature_importances_\n",
"stddev = np.var([t.feature_importances_ for t in clf3.estimators_], axis = 0)\n",
"sorted_indices = np.argsort(importances)\n",
"plot.barh(np.array(DATA_COLUMNS)[sorted_indices], importances[sorted_indices], xerr = stddev[sorted_indices])"
]
},
{
"cell_type": "code",
"execution_count": 29,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n",
"/home/jz/.local/lib/python3.8/site-packages/sklearn/ensemble/_forest.py:416: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features=1.0` or remove this parameter as it is also the default value for RandomForestRegressors and ExtraTreesRegressors.\n",
" warn(\n"
]
}
],
"source": [
"SETUP_ID_3 = 888\n",
"\n",
"reader3 = runsql('select * from computeddata where setup_id = {} order by distance asc'.format(SETUP_ID_3))\n",
"reader_data3 = list(reader3) # list(...) so that following cells can be repeated"
]
},
{
"cell_type": "code",
"execution_count": 30,
"metadata": {},
"outputs": [],
"source": [
"data3 = []\n",
"target3 = []\n",
"for row in reader_data3:\n",
" data3 += [[float(row[c]) if row[c] != '' else math.nan for c in DATA_COLUMNS]]\n",
" target3 += [float(row[TARGET_COLUMN]) if row[TARGET_COLUMN] != '' else math.nan]"
]
},
{
"cell_type": "code",
"execution_count": 31,
"metadata": {},
"outputs": [],
"source": [
"data3 = imp.transform(data3)"
]
},
{
"cell_type": "code",
"execution_count": 32,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<matplotlib.legend.Legend at 0x7fcd8c9d5760>"
]
},
"execution_count": 32,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 1080x720 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"plot.figure(figsize=(15,10))\n",
"xaxis = range(0, len(target3))\n",
"plot.plot(xaxis, target3, 'b', xaxis, clf3.predict(data3), 'r')\n",
"plot.legend(['TARGET OBD Speed','PREDICTED OBD Speed'])"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Wir vergleichen die Prädiktion mit HERE Maps:"
]
},
{
"cell_type": "code",
"execution_count": 33,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"RMSE = 2.27 km/h\n",
"NRMSE = 92.08 %\n",
"MAE = 1.56 km/h\n",
"MAP = 1.72 %\n",
"SMAPE = 1.75 %\n",
"MSD = 0.94 km/h\n",
"CORR = 1.00\n",
"ACC_A = 99.78 %\n",
"ACC_R = 99.17 %\n",
"MAD = 1.15 km/h\n"
]
}
],
"source": [
"ta = target3\n",
"pr = clf3.predict(data3)\n",
"RMSE = math.sqrt(sum((ta-pr)**2)/len(ta))\n",
"print(\"RMSE = %.2f km/h\" %RMSE)\n",
"NRMSE = 1-math.sqrt(sum((ta-pr)**2))/math.sqrt(sum( (ta-np.mean(ta) )**2 ))\n",
"print(\"NRMSE = %.2f %%\" %(NRMSE*100))\n",
"MAE = sum(((ta-pr)**2)**(1/2))/len(ta)\n",
"print(\"MAE = %.2f km/h\" %MAE)\n",
"with np.errstate(divide = 'ignore'): map_elements = np.abs((ta - pr) / ta)\n",
"map_elements[map_elements == np.inf] = 0\n",
"MAP = np.sum(map_elements) / len(ta)\n",
"print(\"MAP = %.2f %%\" % (MAP*100))\n",
"SMAPE = np.sum(np.abs(ta - pr) / ((ta + pr) / 2)) / len(ta)\n",
"print(\"SMAPE = %.2f %%\" % (SMAPE*100))\n",
"MSD = np.sum(ta - pr) / len(ta)\n",
"print(\"MSD = %.2f km/h\" % MSD)\n",
"CORR = np.corrcoef(ta, pr)[1][0]\n",
"print(\"CORR = %.2f\" % CORR)\n",
"ACC_A_THRESHOLD = 10\n",
"ACC_A = (np.abs(ta - pr) < ACC_A_THRESHOLD).sum() / len(ta)\n",
"print(\"ACC_A = %.2f %%\" % (ACC_A*100))\n",
"ACC_R_THRESHOLD = 0.1\n",
"ACC_R = (np.abs(ta / pr - 1) < ACC_R_THRESHOLD).sum() / len(ta)\n",
"print(\"ACC_R = %.2f %%\" % (ACC_R*100))\n",
"MAD = np.median(np.abs(ta - pr))\n",
"print(\"MAD = %.2f km/h\" % MAD)"
]
},
{
"cell_type": "code",
"execution_count": 34,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"RMSE = 21.57 km/h\n",
"NRMSE = 24.75 %\n",
"MAE = 16.79 km/h\n",
"MAP = 14.52 %\n",
"SMAPE = 15.78 %\n",
"MSD = 12.98 km/h\n",
"CORR = 0.81\n",
"ACC_A = 42.47 %\n",
"ACC_R = 35.90 %\n",
"MAD = 12.00 km/h\n"
]
}
],
"source": [
"ta = target3\n",
"pr = np.array([float(d['hr_traficSpeed']) if d['hr_traficSpeed'] != '' else 0.0 for d in reader_data3])\n",
"pr = pr * 3.6\n",
"RMSE = math.sqrt(sum((ta-pr)**2)/len(ta))\n",
"print(\"RMSE = %.2f km/h\" %RMSE)\n",
"NRMSE = 1-math.sqrt(sum((ta-pr)**2))/math.sqrt(sum( (ta-np.mean(ta) )**2 ))\n",
"print(\"NRMSE = %.2f %%\" %(NRMSE*100))\n",
"MAE = sum(((ta-pr)**2)**(1/2))/len(ta)\n",
"print(\"MAE = %.2f km/h\" %MAE)\n",
"with np.errstate(divide = 'ignore'): map_elements = np.abs((ta - pr) / ta)\n",
"map_elements[map_elements == np.inf] = 0\n",
"MAP = np.sum(map_elements) / len(ta)\n",
"print(\"MAP = %.2f %%\" % (MAP*100))\n",
"SMAPE = np.sum(np.abs(ta - pr) / ((ta + pr) / 2)) / len(ta)\n",
"print(\"SMAPE = %.2f %%\" % (SMAPE*100))\n",
"MSD = np.sum(ta - pr) / len(ta)\n",
"print(\"MSD = %.2f km/h\" % MSD)\n",
"CORR = np.corrcoef(ta, pr)[1][0]\n",
"print(\"CORR = %.2f\" % CORR)\n",
"ACC_A_THRESHOLD = 10\n",
"ACC_A = (np.abs(ta - pr) < ACC_A_THRESHOLD).sum() / len(ta)\n",
"print(\"ACC_A = %.2f %%\" % (ACC_A*100))\n",
"ACC_R_THRESHOLD = 0.1\n",
"ACC_R = (np.abs(ta / pr - 1) < ACC_R_THRESHOLD).sum() / len(ta)\n",
"print(\"ACC_R = %.2f %%\" % (ACC_R*100))\n",
"MAD = np.median(np.abs(ta - pr))\n",
"print(\"MAD = %.2f km/h\" % MAD)"
]
},
{
"cell_type": "code",
"execution_count": 35,
"metadata": {},
"outputs": [],
"source": [
"from sklearn.preprocessing import StandardScaler\n",
"scaler = StandardScaler()\n",
"scaler.fit(data[TRAINING_RANGE[0]:TRAINING_RANGE[1]])\n",
"\n",
"scaled_training_data = scaler.transform(data[TRAINING_RANGE[0]:TRAINING_RANGE[1]])\n",
"scaled_data = scaler.transform(data)\n",
"scaled_target = np.multiply(target, 0.01)"
]
},
{
"cell_type": "code",
"execution_count": 36,
"metadata": {},
"outputs": [],
"source": [
"def gridsearch_train_and_plot(base, params = {}):\n",
" best_clf = gridsearch(base, params)\n",
" best_clf.fit(scaled_training_data, scaled_target[TRAINING_RANGE[0]:TRAINING_RANGE[1]])\n",
" xaxis = range(0, TEST_RANGE[1])\n",
" print(best_clf.best_params_)\n",
" plot.figure(figsize=(15,10))\n",
" plot.axvline(x=TRAINING_RANGE[0])\n",
" plot.axvline(x=TRAINING_RANGE[1])\n",
" plot.plot(xaxis, scaled_target, 'b', xaxis, np.maximum(-1.0, np.minimum(4.0, best_clf.predict(scaled_data))), 'rx')\n",
" plot.legend(['Training','Test','TARGET OBD Speed','PREDICTED OBD Speed'])\n",
" plot.xlabel('Sample #')\n",
" plot.ylabel('OBD-Geschwindigkeit / 100km/h')\n",
" name = type(base).__name__\n",
" plot.title(name)\n",
" plot.savefig(f'plot-{name}.pdf')\n",
" plot.show()"
]
},
{
"cell_type": "code",
"execution_count": 37,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"{'gamma': 'scale', 'kernel': 'linear'}\n"
]
},
{
"data": {
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\n",
"text/plain": [
"<Figure size 1080x720 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"from sklearn import svm\n",
"gridsearch_train_and_plot(svm.SVR(),\n",
" {'kernel': ['linear', 'poly', 'rbf', 'sigmoid'],\n",
" 'gamma': ['scale', 'auto']})"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"gridsearch_train_and_plot(svm.NuSVR(),\n",
" {'kernel': ['linear', 'poly', 'rbf', 'sigmoid'],\n",
" 'gamma': ['scale', 'auto']})"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"from sklearn import linear_model\n",
"gridsearch_train_and_plot(linear_model.SGDRegressor(),\n",
" {'loss': ['squared_loss', 'huber', 'epsilon_insensitive', 'squared_epsilon_insensitive'],\n",
" 'penalty': ['l1', 'l2', 'elasticnet']})"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"from sklearn import neighbors\n",
"gridsearch_train_and_plot(neighbors.KNeighborsRegressor(),\n",
" {'n_neighbors': [5, 10, 20, 50, 100, 200, 500],\n",
" 'weights': ['uniform', 'distance']})"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"# i think something is borked in there\n",
"gridsearch_train_and_plot(neighbors.RadiusNeighborsRegressor(),\n",
" {'radius': [0.0001, 0.0002, 0.0005, 0.001, 0.002, 0.005, 0.01, 0.02, 0.05, 0.1, 0.2, 0.5, 1.0],\n",
" 'weights': ['uniform', 'distance']})"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"from sklearn import gaussian_process\n",
"gridsearch_train_and_plot(gaussian_process.GaussianProcessRegressor(),\n",
" {'normalize_y': [True, False]})"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3 (ipykernel)",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.8.10"
}
},
"nbformat": 4,
"nbformat_minor": 2
}