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1077 lines
459 KiB
1077 lines
459 KiB
{ |
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"cells": [ |
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{ |
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"cell_type": "markdown", |
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"metadata": {}, |
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"source": [ |
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"# Setup\n", |
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"\n", |
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"`TRAINING_RANGE` und `TEST_RANGE` müssen je nach Länge des Datensatzes angepasst werden.\n", |
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"\n", |
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"**Keine Anpassung erforderlich** (Siehe Datensatz herunterladen)\n", |
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"- 30% Training-Daten (0-30%)\n", |
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"- 70% Test-Daten (30%-100%)" |
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] |
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}, |
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{ |
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"cell_type": "code", |
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"execution_count": 1, |
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"metadata": {}, |
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"outputs": [ |
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{ |
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"name": "stdout", |
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"output_type": "stream", |
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"text": [ |
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"['curvature', 'radius', 'phiSegment', 'flt_DB_counter', 'flt_setup_id', 'flt_altitude', 'flt_go_elevation', 'flt_go_eleResolution', 'flt_osm_trafficSignal', 'flt_osm_w_wood', 'flt_join_idx', 'flt_curvature', 'flt_radius', 'flt_phiSegment', 'hr_latitude', 'hr_longitude', 'hr_elevation', 'hr_SpeedLimit', 'hr_LinkID', 'hr_shapeFirstPoint', 'hr_shapeLastPoint', 'hr_lengthSegemnt', 'hr_actualManeuver', 'hr_traficSpeed', 'hr_traficTime', 'hr_baseSpeed', 'hr_baseTime', 'hr_JamFactor', 'hr_FunctionalRoadClass', 'hr_consumption', 'hr_mTravelTime', 'hr_mLenght', 'hr_mFirstPoint', 'hr_mLastPoint', 'hr_mNextManeuver', 'hr_mTrafficTime', 'hr_mStartAngle', 'hr_leg_firtPoint', 'hr_leg_lastPoint', 'hr_leg_length', 'hr_leg_travelTime', 'hr_leg_trafficTime', 'hr_leg_baseTime', 'hr_leg_spot', 'hr_leg_shapeIndex', 'hr_IdxNP', 'hr_NearestPoint_1', 'hr_NearestPoint_2', 'hr_PointOnRoute_1', 'hr_PointOnRoute_2', 'hr_Dist2Origin', 'hr_Dist2Route', 'hr_osm_trafficSignal', 'hr_osm_w_wood', 'hr_join_idx', 'hr_curvature', 'hr_radius', 'hr_phiSegment', 'go_start_latitude', 'go_start_longitude', 'go_end_latitude', 'go_end_longitude', 'go_duration', 'go_latitude', 'go_longitude', 'go_routing_flag', 'go_mean_velocity_calc_pre', 'go_mean_velocity_calc', 'go_IdxNP', 'go_NearestPoint_1', 'go_NearestPoint_2', 'go_PointOnRoute_1', 'go_PointOnRoute_2', 'go_Dist2Origin', 'go_Dist2Route', 'go_join_idx', 'go_curvature', 'go_radius', 'go_phiSegment', 'osrm_latitude', 'osrm_longitude', 'osrm_seg_datasources', 'osrm_seg_weight', 'osrm_seg_duration', 'osrm_seg_nodeID', 'osrm_step_weight', 'osrm_step_duration', 'osrm_mn_bearing_before', 'osrm_mn_bearing_after', 'osrm_mn_exit', 'osrm_i_lanes_valid_1', 'osrm_i_lanes_valid_2', 'osrm_i_lanes_valid_3', 'osrm_i_lanes_valid_4', 'osrm_i_lanes_valid_5', 'osrm_i_lanes_valid_6', 'osrm_i_bearings_1', 'osrm_i_bearings_2', 'osrm_i_bearings_3', 'osrm_i_bearings_4', 'osrm_i_bearings_5', 'osrm_i_bearings_6', 'osrm_i_entry_1', 'osrm_i_entry_2', 'osrm_i_entry_3', 'osrm_i_entry_4', 'osrm_i_entry_5', 'osrm_i_entry_6', 'osrm_i_in', 'osrm_i_out', 'osrm_i_laneNumber', 'osrm_seg_speed', 'osrm_IdxNP', 'osrm_NearestPoint_1', 'osrm_NearestPoint_2', 'osrm_PointOnRoute_1', 'osrm_PointOnRoute_2', 'osrm_Dist2Origin', 'osrm_Dist2Route', 'osrm_join_idx', 'osrm_curvature', 'osrm_radius', 'osrm_phiSegment', 'ors_latitude', 'ors_longitude', 'ors_elevation', 'ors_long_duration', 'ors_ascent_route', 'ors_descent_route', 'ors_detourfactor', 'ors_percentage', 'ors_avgspeed', 'ors_seg_duration', 'ors_type', 'ors_maneuver_bearing_before', 'ors_maneuver_bearing_after', 'ors_seg_speed', 'ors_long_speed', 'ors_IdxNP', 'ors_NearestPoint_1', 'ors_NearestPoint_2', 'ors_PointOnRoute_1', 'ors_PointOnRoute_2', 'ors_Dist2Origin', 'ors_Dist2Route', 'ors_join_idx', 'ors_curvature', 'ors_radius', 'ors_phiSegment', 'osm_w_lanes', 'osm_w_lanes_forward', 'osm_w_lanes_backward', 'osm_w_maxspeed', 'osm_w_maxspeed_forward', 'osm_w_maxspeed_backward', 'osm_Node_ID_osrm', 'osm_Way_ID', 'osm_Way_direction', 'osm_Calc_Lanes', 'osm_w_maxspeed_new', 'osm_latitude', 'osm_longitude', 'osm_IdxNP', 'osm_NearestPoint_1', 'osm_NearestPoint_2', 'osm_PointOnRoute_1', 'osm_PointOnRoute_2', 'osm_Dist2Origin', 'osm_Dist2Route', 'osm_f_filt', 'osm_join_idx', 'osm_curvature', 'osm_radius', 'osm_phiSegment', 'tt_latitude', 'tt_longitude', 'tt_sec_Motorway', 'tt_sec_traffic', 'tt_calc_speedInKmPerH', 'tt_IdxNP', 'tt_NearestPoint_1', 'tt_NearestPoint_2', 'tt_PointOnRoute_1', 'tt_PointOnRoute_2', 'tt_Dist2Origin', 'tt_Dist2Route', 'tt_join_idx', 'tt_curvature', 'tt_radius', 'tt_phiSegment', 'weat_precipIntensity', 'weat_visibility', 'weat_cloudCover', 'weat_sunriseTime', 'weat_sunsetTime', 'weat_curvature', 'weat_radius', 'weat_phiSegment', 'mb_latitude', 'mb_longitude', 'mb_seg_speed', 'mb_seg_duration', 'mb_step_duration', 'mb_mn_bearing_before', 'mb_mn_bearing_after', 'mb_mn_exit', 'mb_mn_modifier', 'mb_i_bearings_1', 'mb_i_bearings_2', 'mb_i_bearings_3', 'mb_i_bearings_4', 'mb_i_bearings_5', 'mb_i_bearings_6', 'mb_i_bearings_7', 'mb_i_bearings_8', 'mb_i_entry_1', 'mb_i_entry_2', 'mb_i_entry_3', 'mb_i_entry_4', 'mb_i_entry_5', 'mb_i_entry_6', 'mb_i_entry_7', 'mb_i_entry_8', 'mb_i_in', 'mb_i_out', 'mb_i_laneNumber', 'mb_seg_speed_calc', 'mb_IdxNP', 'mb_NearestPoint_1', 'mb_NearestPoint_2', 'mb_PointOnRoute_1', 'mb_PointOnRoute_2', 'mb_Dist2Origin', 'mb_Dist2Route', 'mb_seg_congestion_calc', 'mb_join_idx', 'mb_curvature', 'mb_radius', 'mb_phiSegment', 'gh_latitude', 'gh_longitude', 'gh_elevation', 'gh_avgspeed', 'gh_sign', 'gh_IdxNP', 'gh_NearestPoint_1', 'gh_NearestPoint_2', 'gh_PointOnRoute_1', 'gh_PointOnRoute_2', 'gh_Dist2Origin', 'gh_Dist2Route', 'gh_join_idx', 'gh_curvature', 'gh_radius', 'gh_phiSegment', 'mq_latitude', 'mq_longitude', 'mq_duration', 'mq_avgspeed', 'mq_avgspeed_leg', 'mq_IdxNP', 'mq_NearestPoint_1', 'mq_NearestPoint_2', 'mq_PointOnRoute_1', 'mq_PointOnRoute_2', 'mq_Dist2Origin', 'mq_Dist2Route', 'mq_join_idx', 'mq_curvature', 'mq_radius', 'mq_phiSegment', 'bg_latitude', 'bg_longitude', 'bg_duration', 'bg_avgspeed', 'bg_avgspeed_subleg', 'bg_avgspeed_leg', 'bg_roadShiedType', 'bg_IdxNP', 'bg_NearestPoint_1', 'bg_NearestPoint_2', 'bg_PointOnRoute_1', 'bg_PointOnRoute_2', 'bg_Dist2Origin', 'bg_Dist2Route', 'bg_join_idx', 'bg_curvature', 'bg_radius', 'bg_phiSegment', 'ei_latitude', 'ei_longitude', 'ei_Cumul_Kilometers', 'ei_Cumul_TravelTime', 'ei_avgspeed', 'ei_IdxNP', 'ei_NearestPoint_1', 'ei_NearestPoint_2', 'ei_PointOnRoute_1', 'ei_PointOnRoute_2', 'ei_Dist2Origin', 'ei_Dist2Route', 'ei_join_idx', 'ei_curvature', 'ei_radius', 'ei_phiSegment', 'go_alpha', 'hr_alpha', 'ors_alpha', 'go_alpha_filt', 'hr_alpha_filt', 'ors_alpha_filt']\n" |
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] |
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} |
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], |
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"source": [ |
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"INPUT_FILE = 'data.csv'\n", |
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"TARGET_COLUMN = 'flt_obd_speed'\n", |
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"# Still contains positional information and acceleration; however we currently train\n", |
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"# sample by sample without knowledge of previous or other data, so it should not be\n", |
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"# possible for the Regressor to simply \"calculate\" the speed.\n", |
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"EXCLUDED_COLUMNS = ('flt_gps_speed', 'flt_obd_engine_load', 'flt_obd_engine_rpm',\n", |
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" 'flt_obd_maf', 'flt_obd_accelerator_pedal','flt_time','flt_time_system_clock',\n", |
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" 'flt_time_utc','flt_ax','flt_ay','flt_az','flt_gx','flt_gy','flt_gz','flt_compass',\n", |
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" 'flt_number_of_satelites','flt_accuracy','flt_gps_bearing','flt_calc_dist_gps',\n", |
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" 'flt_calc_dist_vt','flt_calc_ax_vt','flt_timeIP',\n", |
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" 'weat_latitude','weat_longitude','weat_distanceIP','weat_timeIP','weat_join_idx',\n", |
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" 'hAccel_1','hAccel_2','hAccel_3','flt_mAccel_1','flt_mAccel_2','flt_mAccel_3',\n", |
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" 'flt_mGier_1','flt_mGier_2','flt_mGier_3','rot_Accel_1','rot_Accel_2','rot_Accel_3',\n", |
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" 'rot_Gier_1','rot_Gier_2','rot_Gier_3','rot_Accel_flt_1','rot_Accel_flt_2','rot_Accel_flt_3',\n", |
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" 'rot_Gier_flt_1','rot_Gier_flt_2','rot_Gier_flt_3'\n", |
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" )\n", |
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"# See explanation below the feature importance plot\n", |
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"OVERFITTING_COLUMNS = ('weat_temperature', 'weat_humidity', 'join_idx', 'weat_windBearing', 'weat_windSpeed',\n", |
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" 'latitude', 'longitude', 'flt_latitude', 'flt_longitude',\n", |
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" 'ors_percentage_cumsum', 'flt_obd_air_temperature',\n", |
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" 'mb_step_weight')\n", |
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"# Since there are a lot of fields containing those\n", |
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"# Note: This breaks the map plotting\n", |
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"OVERFITTING_SUBWORDS = ('distance', 'remainDistance', 'remainDistanze', 'cumsumDistance', 'segDistance', 'time', 'remainTime')\n", |
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"\n", |
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"from runsql import runsql\n", |
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"DATA_COLUMNS = [c['Field']\n", |
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" for c in runsql('show columns from computeddata')\n", |
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" if c['Type'] == 'double'\n", |
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" and c['Field'] != TARGET_COLUMN\n", |
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" and c['Field'] not in EXCLUDED_COLUMNS\n", |
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" and c['Field'] not in OVERFITTING_COLUMNS\n", |
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" and not any([w in c['Field'] for w in OVERFITTING_SUBWORDS])]\n", |
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"len(DATA_COLUMNS)\n", |
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"print(DATA_COLUMNS)" |
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] |
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}, |
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{ |
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"cell_type": "code", |
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"execution_count": 2, |
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"metadata": {}, |
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"outputs": [], |
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"source": [ |
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"DECISION_TREE_IMPORTANT = ('gh_avgspeed', 'mq_avgspeed', 'osm_w_maxspeed', 'hr_traficSpeed', 'bg_avgspeed_leg',\n", |
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" 'mb_seg_speed', 'osm_w_maxspeed_new', 'hr_baseSpeed', 'hr_SpeedLimit', 'gh_elevation',\n", |
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" 'ors_seg_speed', 'osm_w_lanes', 'osrm_step_weight', 'mb_seg_speed_calc', 'hr_elevation',\n", |
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" 'bg_avgspeed', 'osrm_seg_speed', 'bg_avgspeed_subleg', 'go_mean_velocity_calc_pre', 'mb_i_laneNumber',\n", |
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" 'osrm_i_entry_1', 'ors_long_speed', 'mb_radius', 'ei_avgspeed', )#'flt_DB_counter') # overfitting -.-" |
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] |
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}, |
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{ |
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"cell_type": "markdown", |
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"metadata": {}, |
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"source": [ |
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"# Datensatz herunterladen\n", |
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"\n", |
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"`SETUP_ID` anpassen, Rest läuft automatisch" |
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] |
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}, |
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{ |
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"cell_type": "code", |
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"execution_count": 3, |
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"metadata": {}, |
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"outputs": [], |
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"source": [ |
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"SETUP_ID = 868\n", |
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"import csv\n", |
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"from runsql import runsql\n", |
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"reader = runsql('select * from computeddata where setup_id = {} order by distance asc'.format(SETUP_ID))\n", |
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"reader_data = list(reader) # list(...) so that following cells can be repeated" |
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] |
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}, |
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{ |
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"cell_type": "code", |
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"execution_count": 4, |
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"metadata": {}, |
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"outputs": [], |
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"source": [ |
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"import math\n", |
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"data = []\n", |
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"target = []\n", |
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"for row in reader_data:\n", |
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" data += [[float(row[c]) if row[c] != '' else math.nan for c in DATA_COLUMNS]]\n", |
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" target += [float(row[TARGET_COLUMN])] # Errors if NaN in TARGET_COLUMN" |
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] |
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}, |
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{ |
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"cell_type": "code", |
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"execution_count": 5, |
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"metadata": {}, |
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"outputs": [], |
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"source": [ |
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"tr_st = 0\n", |
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"tr_ed = math.floor(len(data)*0.3)\n", |
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"TRAINING_RANGE = (tr_st, tr_ed)\n", |
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"TEST_RANGE = (tr_ed, len(data)) # TEST_RANGE = (len(data)-tr_ed, len(data))" |
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] |
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}, |
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{ |
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"cell_type": "markdown", |
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"metadata": {}, |
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"source": [ |
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"# Leere Zellen füllen\n", |
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"\n", |
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"Da nicht alle Datensätze alle Spalten haben – gäbe sicherlich bessere Strategien, aber das funktioniert erstaunlich gut (wahrscheinlich sind die \"wichtigen\" Spalten immer vorhanden)." |
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] |
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}, |
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{ |
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"cell_type": "code", |
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"execution_count": 6, |
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"metadata": {}, |
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"outputs": [ |
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{ |
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"data": { |
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"text/plain": [ |
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"(7228, 311)" |
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] |
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}, |
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"execution_count": 6, |
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"metadata": {}, |
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"output_type": "execute_result" |
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} |
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], |
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"source": [ |
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"from sklearn.impute import SimpleImputer\n", |
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"imp = SimpleImputer(strategy='constant', fill_value=0) # Other strategies remove fully null columns\n", |
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"data = imp.fit_transform(data)\n", |
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"import numpy as np\n", |
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"np.shape(data)" |
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] |
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}, |
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{ |
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"cell_type": "markdown", |
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"metadata": {}, |
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"source": [ |
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"CSV-Export, für MATLAB o.Ä." |
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] |
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}, |
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{ |
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"cell_type": "code", |
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"execution_count": 7, |
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"metadata": {}, |
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"outputs": [], |
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"source": [ |
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"np.savetxt('imputed-{}.csv'.format(SETUP_ID), data, delimiter=',')\n", |
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"np.savetxt('target-{}.csv'.format(SETUP_ID), target, delimiter=',')" |
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] |
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}, |
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{ |
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"cell_type": "markdown", |
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"metadata": {}, |
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"source": [ |
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"# Analyze INPUT DATA\n", |
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"Eingangsdaten analysieren" |
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] |
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}, |
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{ |
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"cell_type": "code", |
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"execution_count": 8, |
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"metadata": { |
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"scrolled": false |
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}, |
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"outputs": [ |
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{ |
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"ename": "ModuleNotFoundError", |
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"evalue": "No module named 'astropy'", |
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"output_type": "error", |
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"traceback": [ |
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"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", |
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"\u001b[0;31mModuleNotFoundError\u001b[0m Traceback (most recent call last)", |
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"\u001b[0;32m<ipython-input-8-ed5ca62780b2>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m 1\u001b[0m \u001b[0;31m# Convert to Table\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 2\u001b[0m \u001b[0;32mimport\u001b[0m \u001b[0msys\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 3\u001b[0;31m \u001b[0;32mfrom\u001b[0m \u001b[0mastropy\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mtable\u001b[0m \u001b[0;32mimport\u001b[0m \u001b[0mTable\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 4\u001b[0m \u001b[0mt\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mTable\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdata\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mnames\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mDATA_COLUMNS\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 5\u001b[0m \u001b[0;31m#lat = t['latitude']\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", |
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"\u001b[0;31mModuleNotFoundError\u001b[0m: No module named 'astropy'" |
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] |
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} |
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], |
|
"source": [ |
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"# Convert to Table\n", |
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"import sys\n", |
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"from astropy.table import Table\n", |
|
"t = Table(data, names=DATA_COLUMNS)\n", |
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"#lat = t['latitude']\n", |
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"#lng = t['longitude']\n", |
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"# Subsampling ... use points every 50m for plotting\n", |
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"#lat = lat[::10]\n", |
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"#lng = lng[::10]\n", |
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"\n", |
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"# determine range to print based on min, max lat and lon of the data\n", |
|
"#margin = 0 # buffer to add to the range\n", |
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"#lat_min = min(lat) - margin\n", |
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"#lat_max = max(lat) + margin\n", |
|
"#lon_min = min(lng) - margin\n", |
|
"#lon_max = max(lng) + margin\n", |
|
"t" |
|
] |
|
}, |
|
{ |
|
"cell_type": "code", |
|
"execution_count": 9, |
|
"metadata": {}, |
|
"outputs": [ |
|
{ |
|
"ename": "NameError", |
|
"evalue": "name 'lon_min' is not defined", |
|
"output_type": "error", |
|
"traceback": [ |
|
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", |
|
"\u001b[0;31mNameError\u001b[0m Traceback (most recent call last)", |
|
"\u001b[0;32m<ipython-input-9-d80dd05874af>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m 6\u001b[0m \u001b[0;31m# Converts given lat/lon in WGS84 Datum to XY in Spherical Mercator EPSG:900913\"\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 7\u001b[0m \u001b[0moriginShift\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;36m2\u001b[0m \u001b[0;34m*\u001b[0m \u001b[0mmath\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mpi\u001b[0m \u001b[0;34m*\u001b[0m \u001b[0;36m6378137\u001b[0m\u001b[0;34m/\u001b[0m\u001b[0;36m2.0\u001b[0m\u001b[0;34m;\u001b[0m \u001b[0;31m# 20037508.342789244\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 8\u001b[0;31m \u001b[0mxExtent_min\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mlon_min\u001b[0m \u001b[0;34m*\u001b[0m \u001b[0moriginShift\u001b[0m \u001b[0;34m/\u001b[0m \u001b[0;36m180\u001b[0m\u001b[0;34m;\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 9\u001b[0m \u001b[0myExtent_min\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mmath\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mlog\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mmath\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mtan\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m90\u001b[0m \u001b[0;34m+\u001b[0m \u001b[0mlat_min\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m*\u001b[0m \u001b[0mmath\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mpi\u001b[0m \u001b[0;34m/\u001b[0m \u001b[0;36m360\u001b[0m \u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m/\u001b[0m \u001b[0;34m(\u001b[0m\u001b[0mmath\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mpi\u001b[0m \u001b[0;34m/\u001b[0m \u001b[0;36m180\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m;\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 10\u001b[0m \u001b[0myExtent_min\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0myExtent_min\u001b[0m \u001b[0;34m*\u001b[0m \u001b[0moriginShift\u001b[0m \u001b[0;34m/\u001b[0m \u001b[0;36m180\u001b[0m\u001b[0;34m;\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", |
|
"\u001b[0;31mNameError\u001b[0m: name 'lon_min' is not defined" |
|
] |
|
} |
|
], |
|
"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": 10, |
|
"metadata": {}, |
|
"outputs": [ |
|
{ |
|
"ename": "ModuleNotFoundError", |
|
"evalue": "No module named 'plotly'", |
|
"output_type": "error", |
|
"traceback": [ |
|
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", |
|
"\u001b[0;31mModuleNotFoundError\u001b[0m Traceback (most recent call last)", |
|
"\u001b[0;32m<ipython-input-10-546f749e9267>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m 1\u001b[0m \u001b[0;31m# Analyze Data\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 2\u001b[0;31m \u001b[0;32mimport\u001b[0m \u001b[0mplotly\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 3\u001b[0m \u001b[0;32mimport\u001b[0m \u001b[0mplotly\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mgraph_objs\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0mgo\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 4\u001b[0m \u001b[0;32mimport\u001b[0m \u001b[0mplotly\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mplotly\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0mpy\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 5\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n", |
|
"\u001b[0;31mModuleNotFoundError\u001b[0m: No module named 'plotly'" |
|
] |
|
} |
|
], |
|
"source": [ |
|
"# Analyze Data\n", |
|
"import plotly\n", |
|
"import plotly.graph_objs 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')" |
|
] |
|
}, |
|
{ |
|
"cell_type": "code", |
|
"execution_count": 11, |
|
"metadata": {}, |
|
"outputs": [ |
|
{ |
|
"ename": "NameError", |
|
"evalue": "name 't' is not defined", |
|
"output_type": "error", |
|
"traceback": [ |
|
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", |
|
"\u001b[0;31mNameError\u001b[0m Traceback (most recent call last)", |
|
"\u001b[0;32m<ipython-input-11-6fad4a6b6b96>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m 1\u001b[0m \u001b[0;32mimport\u001b[0m \u001b[0mmatplotlib\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mpyplot\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0mplot\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 2\u001b[0;31m \u001b[0mtemp_d\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mt\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'distance'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 3\u001b[0m \u001b[0mxaxis\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mtemp_d\u001b[0m \u001b[0;31m# range(int(temp_d[0]), int(temp_d[-1]))\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 4\u001b[0m \u001b[0mplot\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mfigure\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfigsize\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m15\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;36m10\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 5\u001b[0m \u001b[0mplot\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0maxvline\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mx\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mtemp_d\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mTRAINING_RANGE\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", |
|
"\u001b[0;31mNameError\u001b[0m: name 't' is not defined" |
|
] |
|
} |
|
], |
|
"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": [ |
|
"# 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": 61, |
|
"metadata": {}, |
|
"outputs": [], |
|
"source": [ |
|
"import tensorflow as tf\n", |
|
"from tensorflow.keras import layers\n", |
|
"\n", |
|
"model = tf.keras.Sequential([\n", |
|
" layers.Lambda(lambda x: x, batch_input_shape = (1, np.shape(data)[1], 1)), # Hacky No-op layer for reshaping\n", |
|
" layers.LSTM(256, stateful = True),\n", |
|
" layers.Dense(1)\n", |
|
"])\n", |
|
"\n", |
|
"model.compile(optimizer = tf.keras.optimizers.Adam(0.001),\n", |
|
" loss = 'mse',\n", |
|
" metrics = ['mae'])" |
|
] |
|
}, |
|
{ |
|
"cell_type": "code", |
|
"execution_count": 62, |
|
"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": 63, |
|
"metadata": {}, |
|
"outputs": [], |
|
"source": [ |
|
"#from sklearn.decomposition import PCA\n", |
|
"#pca = PCA(n_components = 50)\n", |
|
"#pca_training_data = pca.fit_transform(scaled_training_data)\n", |
|
"#pca_data = pca.transform(scaled_data)\n", |
|
"pca_training_data = scaled_training_data\n", |
|
"pca_data = scaled_data" |
|
] |
|
}, |
|
{ |
|
"cell_type": "code", |
|
"execution_count": 64, |
|
"metadata": { |
|
"scrolled": false |
|
}, |
|
"outputs": [ |
|
{ |
|
"name": "stdout", |
|
"output_type": "stream", |
|
"text": [ |
|
"Train on 2168 samples\n", |
|
"Epoch 1/4\n", |
|
"2168/2168 [==============================] - 187s 86ms/sample - loss: 0.1007 - mae: 0.2363\n", |
|
"Epoch 2/4\n", |
|
"2168/2168 [==============================] - 182s 84ms/sample - loss: 0.0789 - mae: 0.2323\n", |
|
"Epoch 3/4\n", |
|
"2168/2168 [==============================] - 183s 84ms/sample - loss: 0.0702 - mae: 0.2182\n", |
|
"Epoch 4/4\n", |
|
"2168/2168 [==============================] - 179s 82ms/sample - loss: 0.0423 - mae: 0.1636\n" |
|
] |
|
}, |
|
{ |
|
"data": { |
|
"text/plain": [ |
|
"<tensorflow.python.keras.callbacks.History at 0x7fa202816610>" |
|
] |
|
}, |
|
"execution_count": 64, |
|
"metadata": {}, |
|
"output_type": "execute_result" |
|
} |
|
], |
|
"source": [ |
|
"import numpy as np\n", |
|
"model.fit(np.array(pca_training_data).reshape(*np.shape(pca_training_data), 1), np.array(scaled_target[TRAINING_RANGE[0]:TRAINING_RANGE[1]]).reshape(len(pca_training_data), 1),\n", |
|
" epochs = 4, batch_size = 1) # Seems to be the most common point of diminishing returns" |
|
] |
|
}, |
|
{ |
|
"cell_type": "markdown", |
|
"metadata": {}, |
|
"source": [ |
|
"# Testen und Plotten\n", |
|
"\n", |
|
"Wenn mit 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": 65, |
|
"metadata": { |
|
"scrolled": false |
|
}, |
|
"outputs": [ |
|
{ |
|
"data": { |
|
"text/plain": [ |
|
"<matplotlib.legend.Legend at 0x7fa202866580>" |
|
] |
|
}, |
|
"execution_count": 65, |
|
"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": [ |
|
"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", |
|
"from scipy.signal import savgol_filter\n", |
|
"# savgol_filter for smoothing (params are window size and polynomial degree)\n", |
|
"#plot.plot(xaxis, scaled_target, 'b', xaxis, savgol_filter(model.predict(pca_data.reshape(*np.shape(pca_data), 1)), 51, 3, axis=0), 'rx')\n", |
|
"plot.plot(xaxis, scaled_target, 'b', xaxis, model.predict(pca_data.reshape(*np.shape(pca_data), 1)), 'rx')\n", |
|
"plot.legend(['Training','Test','TARGET OBD Speed','PREDICTED OBD Speed'])\n", |
|
"#len(savgol_filter(model.predict(pca_data).reshape(*np.shape(pca_data), 1), 51, 3, axis=0))" |
|
] |
|
}, |
|
{ |
|
"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", |
|
"- Media Absolute Deviation\n", |
|
"\n", |
|
"BITTE weitere Kriterien ergänzen\n" |
|
] |
|
}, |
|
{ |
|
"cell_type": "code", |
|
"execution_count": 66, |
|
"metadata": {}, |
|
"outputs": [ |
|
{ |
|
"name": "stdout", |
|
"output_type": "stream", |
|
"text": [ |
|
"RMSE = 23.21 km/h\n", |
|
"NRMSE = -1.11 %\n", |
|
"MAE = 19.08 km/h\n", |
|
"MAP = 25.80 %\n", |
|
"SMAPE = 23.35 %\n", |
|
"MSD = 3.52 km/h\n", |
|
"CORR = 0.44\n", |
|
"ACC_A = 27.94 %\n", |
|
"ACC_R = 24.19 %\n", |
|
"MAD = 17.29 km/h\n" |
|
] |
|
} |
|
], |
|
"source": [ |
|
"ta = target[TEST_RANGE[0]:TEST_RANGE[1]]\n", |
|
"pr = np.squeeze(np.multiply(model.predict(pca_data[TEST_RANGE[0]:TEST_RANGE[1]].reshape(TEST_RANGE[1]-TEST_RANGE[0], np.shape(pca_data)[1], 1)), 100))\n", |
|
"RMSE = np.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": 67, |
|
"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 = [d['hr_traficSpeed'] for d 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": [ |
|
"# Generalisieren" |
|
] |
|
}, |
|
{ |
|
"cell_type": "code", |
|
"execution_count": 68, |
|
"metadata": {}, |
|
"outputs": [], |
|
"source": [ |
|
"model2 = tf.keras.Sequential([\n", |
|
" layers.Lambda(lambda x: x, batch_input_shape = (1, np.shape(data)[1], 1)), # Hacky No-op layer for reshaping\n", |
|
" layers.LSTM(256, stateful = True),\n", |
|
" layers.Dense(1)\n", |
|
"])\n", |
|
"\n", |
|
"model2.compile(optimizer = tf.keras.optimizers.Adam(0.001),\n", |
|
" loss = 'mse',\n", |
|
" metrics = ['mae'])" |
|
] |
|
}, |
|
{ |
|
"cell_type": "code", |
|
"execution_count": 69, |
|
"metadata": { |
|
"scrolled": true |
|
}, |
|
"outputs": [ |
|
{ |
|
"name": "stdout", |
|
"output_type": "stream", |
|
"text": [ |
|
"Train on 7228 samples\n", |
|
"Epoch 1/4\n", |
|
"7228/7228 [==============================] - 609s 84ms/sample - loss: 0.0670 - mae: 0.1998\n", |
|
"Epoch 2/4\n", |
|
"7228/7228 [==============================] - 584s 81ms/sample - loss: 0.0729 - mae: 0.2219\n", |
|
"Epoch 3/4\n", |
|
"7228/7228 [==============================] - 576s 80ms/sample - loss: 0.0709 - mae: 0.2189\n", |
|
"Epoch 4/4\n", |
|
"7228/7228 [==============================] - 577s 80ms/sample - loss: 0.0690 - mae: 0.2162\n" |
|
] |
|
}, |
|
{ |
|
"data": { |
|
"text/plain": [ |
|
"<tensorflow.python.keras.callbacks.History at 0x7fa2023aebe0>" |
|
] |
|
}, |
|
"execution_count": 69, |
|
"metadata": {}, |
|
"output_type": "execute_result" |
|
} |
|
], |
|
"source": [ |
|
"model2.fit(np.array(pca_data).reshape(*np.shape(pca_data), 1), np.array(scaled_target).reshape(len(pca_data), 1),\n", |
|
" epochs = 4, batch_size = 1)" |
|
] |
|
}, |
|
{ |
|
"cell_type": "code", |
|
"execution_count": 75, |
|
"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": 76, |
|
"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": 77, |
|
"metadata": {}, |
|
"outputs": [], |
|
"source": [ |
|
"from sklearn.impute import SimpleImputer\n", |
|
"imp = SimpleImputer(strategy='constant', fill_value=0) # Other strategies remove fully null columns\n", |
|
"data2 = imp.fit_transform(data2)" |
|
] |
|
}, |
|
{ |
|
"cell_type": "code", |
|
"execution_count": 78, |
|
"metadata": {}, |
|
"outputs": [], |
|
"source": [ |
|
"scaled_data2 = scaler.transform(data2)\n", |
|
"scaled_target2 = np.multiply(target2, 0.01)" |
|
] |
|
}, |
|
{ |
|
"cell_type": "code", |
|
"execution_count": 79, |
|
"metadata": {}, |
|
"outputs": [ |
|
{ |
|
"data": { |
|
"text/plain": [ |
|
"<matplotlib.legend.Legend at 0x7fa2028475e0>" |
|
] |
|
}, |
|
"execution_count": 79, |
|
"metadata": {}, |
|
"output_type": "execute_result" |
|
}, |
|
{ |
|
"data": { |
|
"image/png": 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KH3/8MaZPnw4AuPrqq9GgQQN07twZJ598MtavX4958+Zh5cqV+Pe//w0AOHjwIAoLCzFv3jzMmzcPffv2BQAcOXIEhYWFOHz4MC6//HLk5OQAgI+4JoQQQgiJJyUlUtICR0IhpDlwSqmOAPoC+Npv0wkAfrCsbz9WF6w++gwbJuLtkUekjFC8AeZct4KCAjzzzDPIyMjwqd+2bRsqKip85sA55fDhw9i6dSu6dOniU9+zZ08sW7Ys4rYHY/ny5ejevXtAfc+ePbF06VKfumXLltXOpbOSnp6Oiy66CJ999lnI1wGA3r17Y/z48fj444/x1ltv1db7C0ilFAzDwDPPPFP7PXz33XcYPnw4DMPAhAkTaus3bdpUK7DthCghhBBCSLw5ckTKysr4toMkFo4FnFIqF8BbAO41DMPf0GvXQzbqqLc7/21KqaVKqaV79+512qzgLFgglreHHpLSf05cFGjSpAmefvppPPXUU6gM4Zd45MgR3HnnnRg1alTAPLK77roLL7/8Mr7+2tTMM2bMwI8//hhxe7du3Yr77rsPd999d8C2cePGYfr06bXWw6KiIjzwwAO4//77A/Y1DANffPEFOnXqZLvt6aefxq5du3DRRRf5bDty5AgWLlxYu15QUIAOHTrUrr/55puoqanB5s2bsWXLFnTt2hUXXngh/vGPf9R+vhs3bkRJSQkuvPBCvPjiizhy7Em4Y8cO7NmzB2effTbeeecdlJaW4vDhw3jvvfdC/6AIIYQQQqIABRwJh3pdKAFAKZUOEW+vGYbxts0u2wG0t6y3A7ATQEaQ+gAMw3gewPMA0L9//8h8CfWcN+02OWyY73oU0SHxZ82ahSFDhtTOgdP87Gc/wz333AMAGDZsGAzDQE1NDS6//HI89NBDAedr1aoVZs2ahfvuuw979uxBgwYNcPbZZ+OKK66osx2zZ8/GokWLatefffZZtG3bFps3b0bfvn1RVlaGRo0a4e6778bNN98ccHybNm0wY8YM/PznP8fhw4dhGAbuvfdejBgxonafyZMnY8aMGaisrMSpp56KO++8s3bbb37zGzzyyCM4evQoTj/9dCxYsKDWYqkxDANPPPEEfvGLXyA7OxvHHXdcrfskAHTt2hXnnHMOdu/ejWnTpiErKwu33nortm7din79+sEwDLRo0QJz5szB8OHDsW7dutpgL7m5uZgxYwb69euHMWPGID8/Hx06dMCQIUPq/NwIIYQQQmIFBRwJB1XfvCsl/mcvAyg2DOPeIPtcCuAuAJcAGATgacMwBiqlGgLYCOA8ADsAfAPgOsMw1tidR9O/f3/D331v3bp1QV3wAnjiCQlYYhVrCxYA33wD2FiQiPe46aab8JOf/ASjR4+OyfVCur8IIYQQQlxAz/L45z+BW2+Nb1uI91BKLTMMo79/vRML3JkAbgCwSimlo3H8FsCJAGAYxjQAH0DE2yYARwHcfGxblVLqLgAfAUgD8GJ94s0V7ESatsQRQgghhBASZ6w2FFrgSCg4iUK5CPZz2az7GADGBdn2AUTgEeIYqyslIYQQQkiyYQ3PEIqAGzhQyiVL3G0PSRwczYEjhBBCCCGEuMfGjeZyKAKOKW1JSGkE4o2bedII0fC+IoQQQkis2bPHXK6oCP34pUuB2bPN9f37gd/8BthpGy6QJBMJI+CysrJQVFTEzjZxFcMwUFRUhKysrHg3hRBCCCEpxN69QOPGshzOHLgBA4BrrjHX33gDeOopIIx0xCTBSBgXynbt2mH79u1wJUccIRaysrLQrl27eDeDEEIIISnE+vVAy5aSSiAcC5w/OiXB0aORn4t4m4QRcOnp6TjppJPi3QxCCCGEEEIiorgYmD8fOO00ICPDuQWuujr4tvJyKelUlPwkjAslIYQQQgghyYAOYHLLLUB6unMLnLayWampkVILuMzMyNtHvA0FHCGEEEIIITFi1SrgnntkeciQ0Cxwhw4F1uljy8qk1IKOJC8UcIQQQgghhMSId96RVAA33AB07RqaBe7gwcA6fay2zmlLHEleEmYOHCGEEEIIIYnO1q1AmzbAK6/IeqQWOAq41IMWOEIIIYQQQmLEunWANS5fRoZzC9zhw4F1FHCpBwUcIYQQQgghMWLHDqBzZ3M9Pd25BY4CjgAUcIQQQgghhMQEwwB+/FFcKDXhWuCaNJFSCza9jQIu+aGAI4QQQgghJAYUF4u1rXVrsy4UC5y2sl11FfD738uyFn8lJVJSwCU/FHCEEEIIIYTEgB9/lLJVK7MuOxv44AOxzh04ACxdGvx4bWV79VWgSxdZrqgA9uwBVq6U9cWL7aNVkuSBAo4QQgghhJAYsH+/lHl5Zt2qVVJOnQqMGgUMGBDcpfLwYbHYZWaK6yUg+/bube7z44/ApZe633biHSjgCCGEEEIIiQHagtaokVmnhdiKFcDnn8tyUVHw4xs39j2uvFwscFa++sqd9hJvQgFHCCGEEEKIyxw+DPToAbz3nm8d4CvgtCtkVRVQUyPLpaX25zx0KFDA2c2fy8wMv93E+1DAEUIIIYQQ4jLbtknOt4cfNuvsBNzrr0vZvbtZF0zAHTwYKODs3C2zssJrM0kMKOAIIYQQQghxmY0bpdRWNcBewOmUAsXFZl1Zmf057SxwdgIuOzv09pLEgQKOEEIIIYQQl7nySikbNjTr7ARcw4ZAgwbA99+bdcHSChw6ZOZ/q0vA5eSE12aSGFDAEUIIIYQQEiWs7pCHD4t7o1XUATJnbds2c70uAUcLHKGAI4QQQgghJEqkpwNffAEoBXzzja/1TZOZCezYYa5XVdmf69Ah8/i6BFxubmRtJt6GAo4QQgghhBCXueACKfv0AWbNkuWFC4MLuN27zfVgFjhrGoH0dCl10u78fDOdAIOYJDcUcIQQQgghhLiMFmHl5b71wQScNXCJnYCrrhZ3TG1d0xY4Hfzk1luBFi2Ac88NvCZJLijgCCGEEEIIcZmSEinLywHDMOvtBJy/xcxOwB05ImUwAWett3OrJMkDBRwhhBBCCCEuc/SolP5iKpgFzkokAi4zkwIu2aGAI4QQQgghxGV09EmnLpRWnAg4PQfOzgJHF8rkhgKOEEIIIYQQl9EWuFAE3HHHSWkn4HQOOS3UGjSQdAR0oUw9KOAIIYQQQghxmXAscC1bSlmXgNNRKAERa3ShTD0o4AghhBBCCHEZqwVOKbPeTsC1bi1ls2ZS2gm4Q4ektAq47GwzdQBdKFMHCjhCCCGEEEJcpKrKN41AfQLu7LPN44C6BZz1+Fat7IOb0AKX3FDAEUIIIYQQ4iLafRIQAVdTY67bCbju3aXs00dKLeSs2LlQNmxoLtOFMnWggCOEEEIIIcRFrAKurMxXUNkJuCFDgOXLgb//XdadBDEBgE6dpFRK3CkBulCmAg3r34UQQgghhBDiFD3/rXFjEXNWQWUn4JQC8vNN4RYsjYBSQE6OWdeqlZTHHSdRKQERcDU1QHU1kJYW+f9CvActcIQQQgghhLiItsDl5clyfRY4jXaJtBNwJSUi1Kzz6XQuOKtVTke0pBtl8kIBRwghpJaiImDt2ni3ghBCEhfDAObNk+VmzUSMWV0q6xJwSokosxNfWsBZyciQ0irgdB3dKJMXulASQgip5fTTgU2bpANCCCEkdGbOBO69V5bz8qQ8eNDcXpeAA2Qum1XwaY4cCRRwdhY4LeBogUteaIEjhBBSy6ZNUlLAEUJIeBQWmss6r9uBA2ZdfQIuJ8ecQ2elpMRXqAGmWLMKO7pQJj8UcIQQQgLgi58QQsLDmjJACzirBa5p07qPDybg6rLAZWWZdXShTH4o4AghhASgE8MSQggJDWsAEu1CqS1wU6aY4f6DEY4FTlvdrMsciEteKOAIIYQEQAFHCCHhYU3CbXWhHDECGDeu/uPrEnDBLHBayFmXKyqAL78ENm923naSGDCICSGEkAAo4AghJDzsLHA1Nb5WsroIxYXSzgJndaE84wxZ5rzm5IIWOEIIIbXoRLAUcIQQEh7WuWdawAG+VrK6iNQCRxfK5IcCjhBCSC26E0ABRwgh4bF9u7lsDVgSqQWutFS22WHnQskgJskLBRwhhJBadAeDAo4QQsJj3z5z2Sq4IhVwR48GCjgt0uxcKGmBS14o4AghhNSiOwELFwJffAG8/XZcm0MIIXFl8WLgssuA3/wG+POfAaXk77zzpK5fP2DFCt9jrDnfrBEnQ3GhLCnxrausBKqrAyNYlpWZx2j0c9wuGThJDhjEhBBCSC2tWgF79gArVwIvvAAcPszJ74SQ1OWuu4CCgsD6Tz4BPv9chFV+vu9zcv9+c9man82pBa5xY3n2WtEWOX8L3KWXAi+9BFx7rVmnhaI19xxJLmiBI4QQUoueEF9cbHYgrCGxCSEkFSguBtavB7ZuDb7P7Nn29VYBZ7WYORVwTZqIa6S2rgHBBVyPHsDatWIJ1GgBd+iQs+uRxIMWOEIIIbXo8NfWEefycqAh3xaEkBShuBho27b+ICC9egXWVVb6HheOgDv+eCkPHjQteNodsr4k4Nbr0AKXvPCVTAghpBZr/iJNaWlg6GpCCElWNm4UEfbb3wIDB0oy7ooKoLAQmDtXLGR33w107iz7X3aZeay/62M4c+CaNJHy4EFxaweCW+DsoAtl8kMBRwghpBa7qGUMRU0ISSXWr5fy+uvFRVFz3nnA7bf77tu7twQ10fiLprQ0czlUC9xf/wqMHAlcckloFji6UCY/nANHCCGkFqsFTlvdrPMwCCEk2dECTlvY6iIjw3fga8+e4PuGKuCee06ClAChWeDoQpn81CvglFIvKqX2KKVWB9n+G6VUwbG/1UqpaqVUs2PbtiqlVh3bttTtxhNCSLJiGMB338X+ulYB17KllNEORb1vH7BrV3SvQQghTtm3T+bA6aBOdZGR4fvcrEvAOXWh1G6TVsKxwFHAJS9OLHDTAVwUbKNhGE8ahpFvGEY+gAkAPjUMo9iyy7Bj2/tH1lRCCEkdXn0VOPlkYNmy2F63shJo106Whw6VMtoWuDPPBPrzDUEI8Qj79gHNmzvbty4LnP9zzakFrm3bwLpQLHA66BRdKJOXegWcYRifASiub79jXAtgZkQtIoQQgk8+kXLlythet7ISuPJKcSG67jqpi7aA27gR2LkzutcghBCnFBUBeXnO9k1PtxdwmzYBCxf67utUwOXkAI0a+daFYoFTSq5FAZe8uDYHTimVA7HUvWWpNgDMU0otU0rd5ta1CCEk2dFJYa2T42NBZaV0SLp2NcNXR1PAHTkSvXMTQogTamqAa64R0aQUsHSpOQ+tPvwtcLt3y3k6dQqM3uvUhRKQyJdWQrHA6WvRhTJ5cTMK5QgAi/3cJ880DGOnUqolgI+VUuuPWfQCOCbwbgOAE0880cVmEUJI4qEFnC5jhRZwQGD+oWhQV5JcQgiJBUVFvkm5Bw8GbnNodvCfA/fjj0Dr1vb76meqE9q0AbZtM9f1QJrTc1DAJTduRqG8Bn7uk4Zh7DxW7gHwDoCBwQ42DON5wzD6G4bRv0WLFi42ixBCEg8t3N57DzhwIHbXrKoKFHDRtMAVW4b8Yi1WCSEECPQEmD4duCho9AdfMjJ8U63s2wf4d2O1J0UoAs7fAqitfE7dMDMz6eGQzLgi4JRSTQCcA+BdS91xSqlGehnAcAC2kSwJIYT4osXMO+8A990Xm2tWVUmpBZyeaxErAWeXRJwQQqJNSYnvul0QkWBkZfk+I+sKgBKKgBs1ynddi0Snbpj++3GALLmo14VSKTUTwFAAzZVS2wFMBJAOAIZhTDu22+UA5hmGYf0JtALwjpJhh4YAXjcM47/uNZ0QQpIXPd8BkPkYsUALqFi6UO7fby6Xl4c2R4QQQtzAKuDWrTOjODohJ8f3eb1vH9Cvn+8+SomACkXA3XYb8OWX4oUBmBY4J6kNgMBnqdW7giQ+9d6ihmFc62Cf6ZB0A9a6LQD6hNswQghJZaxzF9q0ic01tYDTL/5wXSiLiyUFwdGjco41a6T+ggvEpae0FPjPf4Bp04DHHjOPKysLjLxGCCHRxirgOnUK7dicHHOQyzBkPp2/BU67UDp1f9THNGtmPpcrKkSANXDoO+d/Lev8ZpL4uCCzAlMAACAASURBVBnEhBBCiEtYwz/HKq5TMAtcqAJu5Upg1Srg/POB+fPN+o8/NpdXrPAVb+FchxBC3MA6VyxUkZOdLYNVhiFlWZk7Ag4QS6BVwIXioeC/L13Ukws3g5gQQghxiYMHJax127ZAdXVsrukv4PQcOKt7UF3U1AD/+pdY1gBg6tTg+9rlJ7IGAiCEkFjhPwcuFLKz5dl39Ciwd6/U+Qs47VnQuHFo505PN+cmh+pi7r+vNdUBSXwo4AghxIMcPAg0aSIjsPEScA0aiBXO6Ry4pUuBn/9cwnF36gR06ABccon9vocPB9bRAkcIiQdawPXuHfqxCxZI+bvfATt3yrK/2/sf/iA54Zo0Ce3cWsAZRugWODsXSpI8UMARQogH0QIuLc0cgY02/gIOCJygXxdbtki5ciWwaZN0IN5/X9rvL0JpgSOEeAUt4BYuDP1Y/SxbuxbYvl2W27f33eeuu2S/tLTQzq2DqVRXi4ALxQWTLpTJDQUcIYR4jB9+EDHTuLG8wGMl4OyinIUi4HTnp2NHs04p6bQ0aOCb3Hb3bnNZdzT0SDYhhMSKpUuBe++V5eOOC/34U06RsnFjM/F2u3aB+zkNPmJFP4srK2mBI75QwBFCiMf4/nspTz45vi6UgAg4p/NDNm4EevUKHkly7lzg1VfFLfPHH816nTC3qCj0NhNCSCTMmmUuh5PG5KmnpDzzTGDrVokc6Z+EO1y0Ba6qKvI5cBRwyQUFHCEk5VmzRsLaewWdQuCkk7zhQul0Dtz27UCPHsG39+sH/PSnMsptFXBNmsifU0sfIYS4hdWtUUeLDIVmzaQsKwMKC+2tb+ESiQWOAi65YRoBQkjK06uXlIYR33ZotICLdxATwLkLZU2NjD5ffnn9+2ZlSa44TXq6uPtwDhwhJNaEOi/NH+2qWFoKrF4NDB4ceZs02gJHF0riDwUcIYTEmMpKGendt0/K444DcnNFQFZW+gq4tDSp27tXxFR6urzEi4slfHVmpswny8iQZcMQMZWVZa4bhv38i+Ji2S8nx2wXYC/gamqkrZWVclxOjrT7yBE5x4oVsq1Dh/r/f91+DQVcbKmulvuhtFT+mjb1vT9qauS70HmtrOkkGjcGDhyQUteT+FJdbX5PBw5Ipz8nxzcQkn4ulJVJqY/LyZG6rCw5R1aWnOfQITk2HItUohGpgFNKPreyMmD//tATgdeFfhZXVTGICfGFLpSEEBJjevSQF3ObNhLY4/jjgW++Af70J3lB61xC2gL34YdAy5Yi8jIzgRdfBPLyRECdeKLkimveXOaeNW4s58vKkpf+JZfYd1C++krOcfzxZkh/OwGXnS2d/LQ04M47JTl3mzZm2/S1Bg2S/U8+uf7/PyPDd75bw4byfzGNQPQxDPm8f/lLoEsXuW+uvNJ3n4wMU6C3aCH3XW6u3INZWXLPNm4MLFsWn/+BmGzdKt9n48byu23RQgR5ZqZ8X5mZsr1XL1lu0kS2N20q331OjrgA5uTIem6uPFOaNpXfeyrghkjNzhbBXFYWeqqAuojEAqf31bnnKOCSCwo4Qgg5RixecKWlEmIfEPEzcaKMhBcWAn/7m9SvXSuCKSfHfIG3aGGe49//llIpYMcOoHt34O9/N+diaHbtAv77X/t2rFolZWWlnEMvA76dBGsQk2nTJEXAsGHA1Vf7nu/880VoXnBB/Z9BZqZY7jRpabTAxQotkp95Rr53pUTMW3HisltVBaxf7377SGisWeNsvw0bnJ9TPw+cnpuIgNPzet0KYAL4WuBCDWKirXU6qBQFXHJBAUcISWnmzTOXnQbriISPPzaXmzaVxNeACBo9cvvRRzJqah0ZtgYH+fBDEVY6WWz//sA99wCnneZ7reuvt2/D+vXA7beb6/r/DuZCeeCAuX7woESN/OlPfc85ZIjUO3FH8u+ENGggdexgRJ/77/dd799fOp5apNslWA/G/v3utYuEx7p10Ts3LeLO2bnTDITlNQscBVxyQgFHCElp/vEPczkWAk7nSmvTRjrT+iVbUSFRJwHpGOtOwHffSdmzp5mrCJD5KjfeCAwYAFx7rdRNnux7LauVy8obb8g8GD1XQ+d/CybgrPPVABGKWjwCwBlnAD/5SdB/OQD/TohSck12MKJLeTkwZYosp6eLtXTsWFlfvlzKb7/1PeaWW4ARI8Q19he/kLrZs6WkgIs/K1ZImZ0t32mHDuYz5l//Mi3inTrJM2XQIBk0Gj4cWLzY93ebkwPcfLM8U5RKHYu4nhPoFtGwwGkBF84cOP0u4fM1uWAQE0JISqPnmwGxEXCrVwNdu5ruZzpgSWWlr7DRL129/brrJM/Q2LESjr9nT+CPf5Q/Tc+egZE0f/tb4MknzXXDAObPB1q1Ap5/HjjvPLOjFmwOnH8agz59gD17ZPmUU6QjGAr+nZAGDSjgYoG2sk2ebA4GfP65lNraosX68uVAfn7gOaZNk/JnP6OA8wLbt8tzYdEi33r9HLjllrqPf+89+/qrrxZ36VTAbaHqpgXOjTQCtMAlJ7TAEUJSmn37zOUvv4zutUpLxYXSOp9Nv6ArKkyxBpidAG1dO+UUKfPypLz4YmfXTE8XAaY7dP/9r3Ta27Y1hVRdAk5HqLSSl2fOt9NJuEPBvxNy2mkUcLFAC7jjjjPr/O8BHVxG32fBaNrU17WWxIctWyToiNukkkuzvve7dnXnfG5a4KweGqHOgdMDbxRwyQkFHCEkpdm713QjCmX+Tzho68aoUWad9QWtO9iAKeD+8hex1rVqJesnnigBCf70J2fXtE6CB0yXzBkzfEd3rWUwAXfttTLir5REIty4EfjrX521w4r+nzt3lkAJ115LARcLdD4/q4DLypLS3wLnHxDHn+OPp4CLN4YhgYqcpO4IlYwM07U62dECbunS8M+xe7e57KYFTv8+y8tDt8Dp33RurpR8viYXFHCEkJTFMMQNrHNnWV+1CrjhhuhN3tcd3nbtzLq0NBFEFRW+CbN1J6Bx48CR4S5dzMnt9aFf+PrlvWePXK9LF2cCztrZv/lm4IQTzPXOnX33dYpuU7NmZnAWCrjo48QCV1xsphGoC0YNjT+HDslvxmrRd4tUssCVlYkI1kInHHSaF6D+wY9Q0L/PsrLQBZz+fTKNQHJCAUcISVl0suLmzUXUTJkilqlPP43O9awJujVKmaPd1jl4bo3i+ou0PXvEPa5hQ2cCbuRIc1m74kSK7pRY3fQo4KKPFnBWcWYd4QfEhTIvr/7cWKlkofEqeh5qtARcqny/paXuJKVfsACYMMF3gCRSrBbyUIOY6PcJBVxywiAmhMQJw5CIb/6h30ns0J3WrCwJpKHzX0UyElsX2sLmf35tzbCzwEWKv0grLjZHiP236Q6bVcBZ59fojkCkWC1wmoYN2cGINnVZ4KwulE4sCKlkofEqev4uBVxkuCXg+veXPzehCyUJBi1whMSJF16Qh/2HH8a7JamLFnCZmb7Ji/2jLrqFfqHql7JGd5aiKeB0Z8zaWXFigbPitoDzt8BF63MngtM5cE4EXHp66nTwvcqhQ1K6OedKk0rfr1sCLhroAZaSEnlHhSLgdKCrQYOkTJXvM1WggCMkTqxdK2U0E7GSurEKOLt6twkm4LQFLhYulGVl8RdwDY69eaxCgS6U0cfpHLj6IlACtMB5AZ3nMRoeA/r79U9LkoyUlQU+k72CbpcW66EIuNGjxSVaCzj+XpMLCjhC4kwqvCC9SrwEnP/1MjPlBW29F5o2deeadgJOdwpCFXBudRR14lzOgYstdnPg/F0oi4pogUsUdNTcaAk4IDWs4uXloc0tiyX+Ai6Udiolv2X/5zxJDjgHjpA4UV+QABJ9rAJu7lxJXDthQvQ6psEEXEZGYEh2a7THSLATcMHmwFVWSlTMBkGG9oLVh8q4cWIFuvJK33aygxFd7CxwOom61QLndA4cBVx8ibYFDpDvOJxIs4lEqHPLYol+V2ixHk47KeCSE1rgCIkztMDFD6uAu+QS4PLLfevdRgs4//kWmZm+SbwB31QDkaBf3q+8IqO4paV1W+Bi0Vk79VTJH9e6tW872cGILnZz4AC5H8rKxNpSWurMVZYulPFHCzg3ox5qrAIu2Qk1umMs0e0Kx4VS06CB/PH3mlzQAkdInKGAix/+LpT+84Hcpq45cPv3y3LfvpKPrm1bd66pX/iPPy6RHuubA2cn4C67DPj8c3faEwwKuOhTUiL3g38OwawsueeDuRTbQRfK+KPnzEYjAEcqCbjycu9a4Bo2FK+ISAQcwOdrMkILHCFxQgs3ulLGD68IOKsL5YQJ0jFzyxJmfeFv2WI/B0530oIJuDlzZG5UNGEHI/qUlNgn6M7MlPsiFAFHF8r4o4VHNN4h/s+GZMbLFjhAnteRuFACfL4mIxRwhMQJHcjBrXlFJHRiLeDKy+X79reAWF0os7MDt0eCtWOiO+pawKWlSRlrF0o72MGIPiUl9u5227cDL70EbN4s604tcPy+4ks0oyfSAucddJArvRwO/L0mH+w6EhIn9MPUmn+MxBZ/ARftTovucPmPmGdmmtd02x3KX8BZ58Ap5ftij7eAq6kxBzaI+xw9Wvd8qTVrpKQFLjGIZvRE/SxMhU6/l4OYAPId0wJH/KGAIyRO+IduJ7EnHi6UdiPm1k5YNAVcRkZgG7wi4LTVMRXClseLYBY4zb59UjoVcHx2xZdYCLhUEOleTiMAUMAReyjgCIkT1nlHJD74C7iGDcUqFWsBZxVt0RRwSolAsl7DKwKOoa6jTzABd/bZUuqohqEEMWEQpvhBF8rIMQzvW+AyMszfJgUc0VDAERIndEALPlTjh7+AU0qWk1XA6TxgXrTAUcBFDy2yggUxee45KfUov1MLnGHQBTyeRNNylCpBTKqr5T72sgXOKuA4B45oKOAIiRO6M82Havywi7qXzALuX/+S0toGqyscBVzy8cUXEjjnyy+DW+D0Zx+KgOP3FX/oQhk5+lnvdQuc7i+E2066PCcfFHCExAndWeJDNX7YCbhoBmcoK7PvcMVKwGmsbm/W/5cCLvlYuFDKd9+VTmBubuA+ulMYqgUOSP4OvpexBiRym1QJYqLvX69b4OyWQ4EWuOSDibwJiSGffgo8+ijw3XdmyG6nD9X584E33gDGjgXeew/48Ud5mGdkAM2bA3v3ysu8pgZ48UXgyivlpdSwoQQn2LQJGDUK+P3vo/f/JRp2Am7vXmDaNKBNG+Css+Sz+/e/gTffBMaMAfLyxA3tuOPk5V9QAKxdC5x5ppynWTNJem0Yco7SUmDYMOCFF+Q7P/PMwHZYRZvbHTK7F771nrMmZK6ooIBLNho3lvLPf5by4osD9/G3wDm5B1Olgx9rpk8H/u//gK1bgQ4dgKZNgU6dJOXH2rXA6tXAFVdITseCAmDIkOi0I1UEeqJY4OyWQ4ECLvmggCMkhgwdGljn9KH6t78Bc+eKOFi/XoRERoZ0urR/vJWPPhIxt3u3WbdsGQWclboSF0+cKGXPnmZ49dmzg7tYbtsW/CX58cd1t8M6L8ltAWf3v1k7Zf4ulPHqyFDARYdGjXzXL7kkcB/9netk8nbz5PxJlTlSsebmm83lbdvkr6DAd5+33zaX9UCg26SKgNP/HwUcSTToQkmIC9TUiOUmHOp7qNbUAIWFwIYNsr5+vZSzZgE7d0oCXjs2bxYrHQlOeblYKOtKpv7dd+by8OHATTcF3/e88+q3YF1+eWCdf1RIN7ETcHYWuD176EKZjPi75P7kJ4H76E6hTibvRMClSgff6+TlRee8qfL9JpoLJYOYEA0FHCEu8Ne/Ai1bAj/8EPqx9T1U334b6NJFXCCtnHKKlC1a2B+nO269eoXeplTBSRCAo0fN5fPPNz93Ozp1Anr0MNf9rR+A/fHWTrZ/ku9IadAgsENubWNGBrByJdCqlQS6oIBLLqx59UaMsN9Hf/bhWOD4fcWX88+PznlTxcKaCC6U/nO0w4ECLvmgCyUhLjB7tpS7dgHt29vvYxUCmubN63+o7txpLk+ZAtx1lyx37GieQ9OvH/DttyIoNR99BCxYIC6B0XK3SVTsBNyOHfL3+OOmq9L774sQuvBCCUQyYICsl5SIaDt8WL7f/v3FkrVkicx7y8yUczRrBpxwglxv0KDAdrgduMSfDRuAyy6TewMARo82t2VkiJuWJt6JvNnJcBct4F57DRg50n6fcARcqlho4sWQIcD998scOO1WnZUlc2o7dZLvqrQU6Nw5OtdPle830SxwFHBEQwFHiAvU1Ej57LNmB/3OO6VT//LLwHXX+briaZo2rf+hahV+p54auN3qQtOzp3TSu3Qx69q2Ba6/Hli1Cpg82dn/kyrYCbi2beXvzDNNAde3r9QB0rk955zg5zzxRPnTjB1bfzuiLeDatZOAKoCITCv+gi3eFjirxYhEjn6+nHWWfQRKQAYjGjY059I6uR8ZxCS6/PWvgb9VK02bRvf6qfL9JoIFzi0Bl+xiPNWggCPEBbSAe/lls+7ZZ83l116T8uKLZd+rr5aIYvPn1/9Q1QLulluAgQOBxx4DTjvN3N6qlYiKO+4Q0diwoVh//MnOlmtVV0tEM1K3C6W1XoufaBFtAWe9hv//698hiLeAS/YOY6zRgri+7zUjQ/ZNT3d2D6SKi10ssSZF79Ytfu0AUs8ClwoCjs/W5IICjhAXsL546+KDD3zXBw50ZoHLyTGTME+Y4LtdKTPJJyApBOzQHfiyMvtkvqmIEwHXsKH789L8oYCjgIsW+vNsWM/bXn/+TtwngdTp4McS670fzFoaK1Ll+60rErFX0N9FfQG36oICLvlgEBNCXMDJS65Pn8A6Jw/Vo0fdEVy6Y2Y3Fy9VqUvA6Q5tLEZmYyng/NMUeM2Fkp0Md9GfpxMLHBC6gOP35R5eEkupYmFNJAtcJG2kgEs+aIEjxAX03JFGjYAVKyQiZVGRdJoNAzh0SIJY+ONUwDntVNWF7sCXlkZ+rmTBiYCLhaCJhYDTwo0WuNRCu1DWZ4ELVcClSgc/luh7/9FH49sOIHW+30QKYkIBR6xQwBHiAjoH3ODBwEknybLVataypf1x6em+7o92UMBFj1QScMFcKGmBS25ogUsctJiIVm63UNCBbZJdwCVSEBMKOGKFLpSEuMDJJ0v5yiuhHefkoVpS4o6AowtlIF4RcM2aRf8aWsD5/z+0wCU3oQQxAWiBiydOxXasyMhI/t9jIlng6rOi1wUFXPJBAUeICxw4APz85xIRMhRiOQeOFrhA6hJw+qWZbALOMHzrKeCSm8pKCcJTX/ADBjGJP/re94o1KCMj+b/fRLDAuSEuKeCSD7pQEhIhhgEUF4fXCXcq4Nzo4FujUBLBiQUuklFPpzRoAPTuDeTnR+8aeg6cTnmhoQtlcqNTA9QHXSjjjxZLXrLAJbuAS6QgJpGeg7/V5IICjpAIOXpUXgLhzFtwKuDatQuvbVZ0B54CzsSJgAs3bHOoLFsWXbFIC1xqUlnp7L7S94HT+Zh0oXQfr7lQpkLy50RKIxAJtMAlH3ShJCRCiouljKYFzo05cBRwgXhJwKWnRzffnO6Y+1vg/DsH8RqJpoCLDrTAJQ5eswbRAucNdNsieT+kp8uz3//5TxIXCjhCIoQCLnHxkoCLNvr/8aoLJQVBdHBqgQt1DhwtcO7jNQtcKrjdJZKAiwQOkCUfSdI1ISR+PPGElNEScCUl7gQxoYALxEkQk7S02LUnmuj/oz4LXLwFHAWBu1RWRtcCx+/LPRjEJPaUl8uz0cvPeQo4YgcFHCERsH8/8PrrshwNAWcYtMBFk7oEnLa8JYsFTuM/B84rFjh2MKJDVVV0LHC0mLoPg5jEnooKb89/AyjgiD31dk2UUi8qpfYopVYH2T5UKXVQKVVw7O9hy7aLlFIblFKblFIPutlwQrzAoUPmcpMmoR9fn4CrrASqqyngokVdAq66WspkEXD6//EfafaKBY4uedHBqQVOQxfK+OFFF8pk/37Ly71j8QyGbp//4FsoUMAlH066JtMBXFTPPp8bhpF/7O8PAKCUSgMwFcDFAHoAuFYp1SOSxhLiNY4cMZcbNQr9+PoEnE667aaAYx44oapK3AmDCTj9efXrF7s2RZM2baQ85RTfeq8IuAYNRFyyg+EuTi1w2rXW6bOG35f7eG0+VipEoayo8M7nHQzdvkgCkFDAJR/1PtYNw/hMKdUxjHMPBLDJMIwtAKCUmgXgMgBrwzgXIZ7EDQFX1wtSnz83N/Rz211LKVrgNPWFj+7eHfjwQ2Do0Jg1KaoMGQLMmQNccolvvVdcKIHUGPGPNU4tcKEKOCA1OvixxIsWuJKSeLciutTlheEV3IpCCVDAJRNuOQcNVkqtUEp9qJTqeazuBAA/WPbZfqyOkKTBKuDCyeGVkSFuEdq9zcr8+cC4cbLsRhATpeRF9eijwO23m9a9VMVJ/p+LLjItcYmOUsBllwV2Dv1Hn+PZmWGuIvdxmkZAu2eFIuAouN3Fi0FMkv33mEgWuBNPDP8cFHDJhxsC7lsAHQzD6APgGQBzjtXbjRUE9eBVSt2mlFqqlFq6d+9eF5pFSPTRo5O9eoV3fF2BACZPBubNAwYOBAYMCO/8/uh2PvccsGSJO+dMVBIhgWss8EoeOH1tCgJ3cZpGIBwLXCp08GMJg5jEnkQIYqIHeCN5NnPOavIRsYAzDOOQYRhHji1/ACBdKdUcYnFrb9m1HYCddZznecMw+huG0b9FixaRNosQR1RU+FrRKiuBw4edH6+tWG+8Ed71g4Xi3rcP2L4dOPdc4OuvA+cthctTT5nLei7cDz8AK1fKX7K7y1ihgLMnnp8HBYH7hGqBC8XiTBdKd/GiC2Wo3+/+/cDBg8CuXcCGDfIe8zKJEMREfwfhePloaIFLPiIWcEqp1kqJZ65SauCxcxYB+AZAZ6XUSUqpDADXAPhPpNcjxE0uuMB37tpllwGNGzs/XougcIOM2Am4oiKgRQsRVOGkJqiL7GxzubIS2LkT6NgR6NNH/q691t3reRkKOOH4433X3ZhvGS7p6eb3QtwhVAtcKPmwUsFCE0uSIYhJ9+7yTGnbFujWDWjfHvjf/6LTPjdIBAtcq1ZSnnde+OeggEs+6n2sK6VmAhgKoLlSajuAiQDSAcAwjGkARgO4QylVBaAUwDWGYRgAqpRSdwH4CEAagBcNw1gTlf+CkDD57DPf9Q8/lLK62llHRlvgrMIoFOzcGjZtMpfdmPtmxTq6XlkJfP+9dNweegiYO1dGTVMFCjhh+HDg88/F2ltZCXToEL+20ALnPk6DmGgLXCiBEjhn0V0S3QJ35Aiwe3dg/YIFkYmPaJIIFrjevYGvvgL69g3/HBRwyYeTKJR1jskbhjEFwJQg2z4A8EF4TSMkthw4YC7/7W/Ar39d/zGRhvm3s8CtXGkuuy3grEJz/nxg5kxZHjECWLNGXF5SBQo4oUED4KyzzBd7PD3YMzPDt+hMmwa0bAlccYW7bUp0KiqcPUe0cAsl7yEtcO7ixSAmoXy/zzxjX19V5U57okFFRfgDsLFk0KDIjqeASz6SJEUtIZGzbJm5PMV2SCKQSC1wdkFMVq82l6NpgZs2TeYqAEBenvwPqZQjjgLOl8WLgfvui38Qk3BdKO+4A7jySnfbkww4dRGbNg24+WZJN+EUWkzdxYtBTEL5fj84Nlzfv7+va3a3bu62y00SIQqlG1DAJR8RTIkkJHmorhZ3QgAYORL46CPgyy/lYXf0qJSVleJm9N13Mm/uxBPlmMzM0OaNWLGzwFmDsIYyGu6EYAEKmjcXKyIFXOpyxhnyF09o0XEfpx3UTp2AF18M7dwMYuIuie5CuWuXzKN+/XVZ/+EHeU962QJXWZkaAq6uiNckMaGAIwTSmdcWuKFDgf/8x3lntmnT8K9rJ+D27TOXBw4M/9x2BAtQ0aiRWOBSKTccBZz3yMwMzwKnA3CQQKI5x4eC210qKmQw0O2Bu3AJ5fs1DIk4OWqUWacHDMvK3G+bWzgN8pPo0AKXfHjkMUFIfCkvl4iMPXoA99wDvPyy82PDnf8GBBdwl1wC7NghpZtkZ/u6aA4ZAhQXy/wXulCSeBOuIDh0yP22JAvRjLJHF0p3cRpwJlboIDVG0Ay+JocPyzO1TRuzTgs4L0eWraqigCOJCQUcIZDJ13v3ShCEtDSJyOcUtwXckSOSyqBt2/DPWxft2pnLp5xiWhCzs6UdOmloskMB5z3CFXDFxe63JRlYskTc2Jx0wMOBLpTu4jV3vlDc7rTnSPPmZp1+tnrZAuc0T2KiQwGXfFDAkZTF6pc/caIIOB2B74QTgMceA955R+bEXXqp1FuF3UknSRmJgLNLI1BaGt2oWNaXlTUHnr6ml1+2bkIB5z3CdaHcv9/9tiQDv/iFlNbUJG5CC5y7VFR4S0xEKuDs3m9egy6UJFFJgduWEHs2b/Zd37/ftEYpBUyYIMtWn34rI0ZIQJNIxJadBe7o0chEYX1YOwjWOXH6/ygtrTv6ZVUV8OabZnCEbt0iy08TLyjgvActcO6iO6ah5HYLBVrg3MVrLpTW91N9EZHnz5eyWTOzTinv3yO0wJFEhQKOpCzdu/uuV1QEj9Joh97XDRdK60O1tDS6As462tixo7lsFXB18emnwHXXmeuNGiXmHCQKOO8RbhqBkhL325IM6E5btIJiMIiJu3gtpL3dAGMwfvc7KRs39q2PJLdjLOAcOJKo0IWSpCzWeSFnnhl6tDY3BZx+wRlG9F0oraPxt9xiLjsVcDrdwsKFwL33yuT1RHwpaKHgpQ5TqhOuIEjE+y8W6PQm0bLA0YXSXbxsgXOKv6XO6yKfLpQkUaGAIwTyggl19FNbbtwUcHr+WTQtcFasI/NakNYl4AwDuPtuWR44EOjQQZYT0QJCC5z3CHe0np0Se/QgFV0ovc/QoZI/zUsD8iiLXQAAIABJREFUSk7nsFkDX1nnVQPeF3B0oSSJCgUcIRDRUl0dWmdeCx4358DpPGyxEnBW9MhpXbngDh0SsTZypPzf+pgjR6LfPrfRn7mXOkypTmZmeEF0vNxBjCc6UFM088CxQ+gOn34qpZfEhFMLnDUgWF5e4Dm8/PukBY4kKhRwJOXJyjIFSKxdKP1HOLV4iqYLZTC0GKvLmrZ0qZTXXCNlIuT5CYaO+BYt6wQJnays8ASctVMSrZD5iYj+XUarg0oLnDusWGEue1HA1dfpr2t7Rgbwn/8A27a51y434Rw4kqhQwJGU58wzTQEXigVO7+umBU6Lp/oifkVKu3bAL3/pW6cjUtZlTdOjxKedJqUWcImYesBr802I3E/V1b4j+k6wdkrYQTEZMEBK7fbsNl63riQK+fnmspc8Apxa4OoTcMXFQK9e7rXLLQxDnjep8B7QIpXPx+QhBcYdCLGnb1/J99aiBbBokdSFMwcukjlU8RJwP/wQWFefBa6yUlIvtGkDdOkidYmQqDUYFHDew5qL0Jrioj6sHcxQgxElM8cfL6L4wgujc366ULqPl55JobpQPvNM8HN40c1etzsVLHBKyf/JAZfkgRY4krLocP3W0OWhdPx0AJBIXPD8XVS0eIrHHLgmTaR88EH77QMGyCR7HbgESGwXSgo47+EkkI4dVhGRiPditKiujm7nND1dPnu6rbqHlwYfnAYx0b8/u+epl5+xqSTgAPP3SpIDCjiSsuiE2dYXZijWNC3camrCb0OwICbRtsDZ0aoVcMop9i/rqipg5UrgiiuAV14x6+lCSdwk3PvJ2inhCLNJtOf36OdXqC6vJDheeiaFaoGzu9e8PMdYt9tLn3k0oYBLLijgSMpiJ+BCGf3UOZYiEXBpaWLJq6gAJk8GLr9c6uMh4ACJLrlnD3DrrZIjTingpz8Frr9eRtmHDwc6dzb3pwslcROrC2Uo0AJnT7QFnFMLDXHOrl3xboFJqHPg6nueRvKujAa63aligaPLc3KRIrctIYG4JeCsOXDCISNDXMZ+9SuzrlOnyM4ZLnre0auvmi/t116TNg4eLLmKrIST6NUrUMB5j3BdKK33XyLei9EiVha4ior4DTolGwUF8W6BidMolE4tWf/9L3DJJZG3yy1ogSOJDAUcSUkMQwRcdrZvBycUF0o9By5SAZeeLlG6NI8/Hr/OkE7COnIksHGjuE0CkrT7888D99efVyJ2mkNN3E6ijxsulLTAmVRVmQNN0cBpB58kJqFa4OobLPDaXMlUmwOXmcnnYzJBF0qSkugOYk6Or2gLpUOvIzF27x5ZW3SYZU3z5pGdLxK0gMvIAM47z6w/+WT7/fXnlYgvBVrgvId2oWQQE3egCyWJBLddKPUAjVdINRfKcPNsEm+SIrctIb7oYCE5Ob4WtFAE3IgRwFdfiXUqEjIygKIicz2eAk6P1mdmAo88IvnimjWT4CV20IWSuAmDmLhLtKNQ0gLnPnv3xrsFJk4FulNLlteEUqq5UNICl1zQAkcSkrfekoduw4YSaMPu7yc/kbJtW8n1phTwf/8nx1sFXLhz4ABg0KDIo2z5C7i8vMjOFwlawOXkiBvnr34F3HQT0Lix/f6J4EL58styv/hDAec9wrXAWe+/d9/13VZcDFx9NXDllcDFFwMnngi8/765fc4cCc5zzTXAjz86v+bBg8DYscDXX4fW1lhCC1ziEc8BPH/ctsBFOt3AbWiBC86SJcDEicCaNdLHmTQpqk0jYUABRxKS0aOlc1LXC2HuXCl37QL27ZNl/RCyCjhrZKyePV1var34C7h4BTABJOHvyJHAAw842z8RXChvuknuF38o4LyHGxa4J5/03bZoEfDmmxIc4r//lST21vv78suBjz8GZs8GPv3U+TU//VSC/UycGFpbY0ksg5iQyNFu+V4h1CAmdveadd6b1yy1qTgHzumzddAg4A9/APLzZV0PfhPvQAFHUhKrgNMvlXvvDW5piib+Aq5169i3QdO2rVgw2rd3tn8id+C++475q7yGvwXu0CHgiy/q/p6qqoILr40bRZwBvvsEsxyFYiH4/nspvRYa3UqsBJzXOuaJitcGA9y2wFVVyW/SK6SaC2VamljU6uPgQXOZ70jvQgFHEo5Q3Jzs0BEoARFwOq9Z796RnTdcMjJ8O45eTnzqj9ddKOuKerZtG/Dll7FrC6kffwvcQw8BZ54JPP108GPeekvEuPV388EH8t0PGgRMmQI0bSqJ6n/6U9muRc0LL/ieKxRL8vbtUkYzymOkRDsKJV0o3cWrFrhIBJz1d/nGG0DXruK27AVSzYVywQLxRvruu7r3e/DB2LSHRAYFHEk4dMfp0UdlNG/1ahmlX7tWRtnffls65rt2Sd22bWLhGjVKjquqMkf4c3JkrlxhIXDzzfH5f6wvvW++iU8bwiUtTV7QXnWh1K6zgG8nhKOK3sQ/kffmzVLWNWizZYuUH35o1i1bJr/5AweA3/5W9klPB/7xD4muqqO+6mPfflvKUISI7vx5ecCFFrjEICtL5mD27x/vlvjidhCTJUukXLUqsna5RapZ4DQ7dtS93c5K2oBqwXPwKyEJh+6UDxsm1rOePSXJdPfuwNlny5yW008XV8Tu3SVoQbNmMpIPiFvWBRfIck6OdMBOOSV+HTFr4JRu3eLThnBRStrv1RH4PXvM5f37zeVIrbgkOvgn8t65U8ojR3z3e+QREWOADOA0aSK/c01FhfzOAbFqHH+8LOfmiqV92za5d596SiKtnn22bLcORBw6JM+V9HTf4Ej9+gH/+58ZLfDQIZkropQESgk1AEs0iXYUSlrg3KGyMniqlniilNw/kVjgrN4l+vflFTGQanPgNHaBl/r3N59xn3ziuy0vT1zFvewunop45GdEiHO0gAs1Wpd299u0yazTI/7xRAs4peKXwDsSMjO924HT85QAXwGnRyCvvDK27SF1k5EhvwNtgdMiyd9i+vDDwJ13yvKGDSLKunQB+vSRuuOPB0pKZNn/N3XddeZgDiCDO/rZYBVw774raUL8r718OTBzpjlv9eBBc+7S22+LoPQKDGLifQxDRI5XrUBOBujqEkJWAee1+yTVXCg/+khK/WzUlJeL10IwWrWSkp4r3oICjiQc2qoSqoDTnQ09Mg/IiHy80e3KzfW2O1YwMjK860Jp/a6tAk639447YtseUjdKSYd2yhTgscdMd+lgHYeaGvleTzxR3Hl1J+SZZ4DnnpNlfwE3YADwpz+Z623a2Au4uqwEP/xgdoL8BdtnnwU/LtbQhdL7OA0AEi8yMur/fp1a4LSA88p7LtVcKIcPF68j/1yDK1cG7tuhg7lMAedNKOBIwvHdd9Lh0m5RTtGdNGun3gsWL90JatQovu0IFy+7UFo75HYCTt8TxFvs3w/87nfmerCOw/z5sm/TprKeliZumNu2AVOnSp3db9zqqnz99WY+SacDEStXBrp1arwSoAFgHrhEIBEEXCQulD/7mbnsNQGXahY4QDwVFi/2rfvnPwP3s6Yz0pGxKeC8BQUcSTiOHhXrW6h+9HYCzksWuEQVcF52obR2yHXgCms9BVxiYLUAWCOL7tkjgUq0gAOAhQt9j7UTcHl5IsCOHgVuuMGcy2m9X6ydzN27JSjSrl3A738v17U+R955Bzh8WObeeum3EO0olHShjJxkEHB1uVD+8pemy7rXAv+k4hy4wYNlgMvKDz9ILIEDB8R9/YcfgJ//3NxOAedNKOBIwlFR4Rv4wym6s27NcRLOedwm0QWcl10ore264QYzfDIFXGKhOw633uo76LJjhwg6q4DTaUE0TZrYn/O443znwGZm+t4vVqHYsqV0Ylq3Blq0ENfNwkLfa+bmimVvyRLgV78K7f+LFnSh9D5eF3Dp6fU/3+tLI6AHUfR+EyZIvdvBpEaOBM49F3jySXH700HKrH+3324u68jUqSTgWreWwUz9Gfzxj+J63ry5PCszMyWwk/W7pAulN6GAIwlHpALOOnLuBfSDMpEFnFdH4P07Hm+84VtPAec93nwTuO023zrd8XvvPTOHI2B2AK1WtmbNgMcfl9/TXXdJhFkn+FuS9bKe+K/xn3v75z8DPXrI8vjxUn7+ubNrRhtGofQ++rPzwmCiHU48LOqzZOl6fwEwb15kbbNSWirPhwULgGnTxEpuFxFWz421kkoDEJde6ru+aJF9MDfrd6kHyCjgvAUFHEk4KirC63jbWeC8QKJb4BLFhRIQ1xBrPQWc9xg9WjpZv/61WafvL//oaToirX/n94EHZKDmmWecX9ffAqc7db16+e6Xl+e7fv/9pkvYqafKqL5XLNK0wHkfr1vg/H8XdtT3P+h6q1XbbawRh7dsAUaMqNtVMyfHXPbq+ysadO/uu15UJM/R007zrbc+N4IJcBJfKOBIwhGuBc4/CmW7du61KRISXcAlggvlwIFSNm7sW08B512uuEJGftPS5PsqKwsu4Nz4Hv07qrpT598ptVrgrNEsg50nnjCIiffx+rPIyf1cXzTHYPVu5hXzt3r37g38/e/B9//zn83lLl3ca4fX8be2rVsnXg3+QeEo4LxPCnn+kmTBLRdKr4T71v+LFyJihoPXLXAZGZLPy9qJ0PeAVztNBDjjDJmrcd55cn9psWYlmgJOWxX8nzVWC9yDD9Z/nnjCPHDeJxkEXH3RHJWSgRhrSgHAXQG3c6eUhw9LJFrdlrvuktIwpB3V1dIWpYBx48z2pQo6VYthyACUjvbrH9BNf36dO1PAeRVa4EjC4ZaAy8pyr02RoP8Xr7QnVLxugcvMlJdW+/bywlJKXOwA73aaiEl6uszTaN/et75pUzOfUSwtcC1aSBksCq6Xfg+xikL5wAPAsGHRu04yk0wCri43ULttt9wCFBSE3zZA5rkpBUycKFak3FxfIamDdTRoIKVOGWLdlooo5euF5G+Z059hw4YUcF6FAo4kHG5FofTKC1P/L3YTiRMBrwcx0d/zSy8Bkyb5bvfKPUCCY823Zh0lbt/eXQucv/AKZoE77jgJhhMsUEkqWeCs5/ZP30CckQwCrqrKFEnBCCbuli8Pv22Ab1Lqa66J7FypxuWXm8v+HkDW+Yr6d865rt6CAo4kHMlmgdMj5F6dxF4fXneh1N/70KEySmsllcJHJyo6hxQgIcI1zZubc+LcssAtXQq88IKsV1SYrl/+XHWVuHgGO49XBFy0o1CmqvXCTXSUUy8LuLKyuveprKz//aW3d+zoW2/Nz+mE5cuBe+81Bwysbpl6rjNxRqNGwGWXybI1qAsgrqgAcPLJtMB5FQo4knDoeU2hol+QBw74rscbPQ8gmq5O0cRLLmP+2In9O+6Q8sILY98eEjpbt5rLV11lLluD/rgl4Pbvl1xzVVVy76Snhy5SvCTgom2BI5Hz6KNSeuV95I9TC5xTAWd9HqelhS7g/vY3CU7y8MOybhVwOp0Hcc7vfge0aSMDnFasqSEo4LwJH+0k4QjXAqc7fPv2yQPJK4JJPxS90p5QSRQXSs2zz8ofSSxKS8VqfsMNsq4jigLuCThNUZFYFcIdKKqulr99+8R6UV4uyXCDJRWPFrEUcKkUyS8aeFXAZWU5mwNX332mBZxV6DVrFrqA27RJSu1JY3XrGzQotHMRYMAAMwCMFe1CqZT5nVHAeQsKOJJwhCvg9PyZ8vLAiEvxRI8gJqqASxQXSpKYdO8uoa79XZ6jYYHT7N1rWuDCPc/GjYEWgZqa2LodxlLAecXqmEisX28ue/U55TSISTgWuHAE3BdfSHn0qJS876JD27ZS9ulDC5xXoQslSTjCTeTdoIHZ6fPSy5IulNGDAi7xWbQIWLXKXP/+e2Dz5ugKuD17IrPAAcDq1YHbYh0EINpRKAFg7VoJhuDVZ4CXsd7XXn1OZWXVPwfOyUCBGwJOz8sCzN8S77vocPrpIpYfeogCzqtQwJGEI1wLHGC6XXklgAmQ+Ba4RHOhJIlFs2ZAr17mevv2MrHeKuDciOBqvU+++CL854x+tvz614HbtPUgVsTCAte9u4zWe/UZ4GWsz3yvPqecCLhILHB2+R2DUVpqLuv7jQIuegweLPcoBZw3oYAjCYcbAs5LL0vrZOFEhC6UJB5Y58Dp3GyRYH2mHDzorFNqh3bP/uEH6aBaiTTnVSgYhlj3Y/Fc8VLglkTCGnbfq8+p7Gz5Lfgn4bbiZKBAb7f+ptq1A7Ztc94WfY9ZBw113c9/7vw8JDQo4LxJgnYZSSqwf7/8rVkj80b27JEX3uHD4Qs4nesk3OOjQTJY4KqqpLNYVx6gSNm4USIStmolI8JZWTL6n5Eh116yRCwB69dLXVqa3Cv+nWiSHGgLXH6+OyLF2oHeuVPu6Ujm2gLAlCnAtdeK5SAnR+7blStFcLZp43tcdTWwbJkEOunSJfK5cvq5EisB59VBHEA+Vx29uKIC6NfPW14YgHcFnP6cysoCc4VpnAx26N+S9X5s107e8a+8Ikm4S0uBiy/2HZyxosVao0YUcLGEAs6bUMARz1JXxztYEt36WLpUSuvk8Xhz1lnA1Km+bmKJhH4xV1REr1N05AjQtWtg/T33SEjpOXOAK6+0P5bR8ZITPeDhVqfC2oHesgVo3TqyaLeAebw+94YNwIQJQOfOMiBh5a23gDFjZPmdd4BRo0K/tpVYWvYzMqQTH+1BnHAoKgL69/ete+wx+R7ijVX0BBNH8Ua7J7st4Dp2FAEHADfe6LuvNYm0FS3WcnOB3bt967wqgJMBCjhv4rFHLSHOWLMm3i1wjzFjJCjDsGHxbkl46BdnNEfgrbnArLz/vpT+gvyRR0wLhn+CUpIcHDki5amnunM+q1irqQnfhdIq4Lp1k7JBA+kErVwp64WFgcetW2cub98e+nX9iaWAi8UzIFzsgmTs3x/7dtihBdH06d4Tvho9KGedf+aPExdKq4Dbs0cCuFjzOjrBaoHzD2JCARc99Hcb6yBMpG48+sggpG7at4/s+FiG8q4PpSQoQ6KiX8zRmgOzdy9wzjnBr20YwMSJvvUjRwJ5ebJMAZec6I6lW7nVrB3AHTsiT1cCiFuY9fzffmuu6zDogFxr0iRzvaQk9Ov6E8v8klYrvNewm3dYX1COWKHdXL38/Le6UAYjVAtcixbyOwn12azvr0aNzFyLFHDRpy4L3F/+AowdG9v2EIECjiQkM2eGd9z8+VLOmeNeW1KdaHfeFi3yHUVv0sR0Nz3lFHGR0i+W9u3FNadrVxF111wD/Oxn0WkXiS/XXScutI8+6s75rGJt587w88B17iyWtw4dfOe5+XcwrVbl77+XcsAAGdDR1sVIiIcFzouBTOy8NbxiSYilyA4X7ULppgVOo5R4oIweLdMIAJnjHAyrBQ6Q3ygFXPSpS8Dddx/w6qtmOiQSOzgHjnie2bOBq69251znnRfcv56ER7Q7b5s3S/nDD+acCUACESgF7Nol66+/LgEjNHfdJX8kOcnMlPmPbmEVcIYRfgCcjAxfd0iNfwfTatE4eFDK3/8e+OlP3bHAxTqICeBNAbdvn3yPRUWy3r69d9qZCAGsomGBszJrlrn85pt1R7v0F3Dl5RRwsUB/t3XNgTt4EGjaNDbtIQItcMTztG0b7xaQuoi2BU7nCfJ/OWRlyaiw7ix7LaocSSz8c8nt3+9utFrdwdQultbfy4EDUjZpIvOiEs0C52UXyiNHfINveClvZSxFdrhYg5gEo6oqfAFnpb6cc1qs6SiVFHCxIZgFzprD79NPY9ceItQr4JRSLyql9iilVgfZfr1SauWxvy+UUn0s27YqpVYppQqUUkvdbDhJfjp0kJDCZ50V75aQuoh2AAM9Ou0fAS07W172urPbr190rk9SA/+O5f794blQBkP/TrRbpfX3oi1wTZqIwHNzDlyqW+AOHPAd/PFSyoNEcKF0EsSksjI8F0q7a1HAeY9gAk5btQHfOb0kNjh5tE8HMAXAK0G2fwfgHMMw9iulLgbwPIBBlu3DDMPYZ38oSVTOOENcfe68M3rXqKyk9S0RiHYQk/Jy+/DVhw5JWohFi2Sd+d5IJGjX6pwc6YwcOOCuBU6LwbZtJQqlnYA7/njz+pFCC5ywf7+vgPOiBS4RBFy0XCit6EG5YPgLuA4dzG1etmImOsEEnH5uAd75TaUS9VrgDMP4DIBNIN7a7V8YhqGD8n4FoF2wfUny8OWXwLhx0b2Gk4nRJP5Eu/NWXm4/urpli7mcnu4b/Y+QcLFGxnPTAqctGCecIGUwC5xbAiOW1h0vW+D27/eNBkoBFxrRDGLiT6gWOBIbggm4Q4fMZeaIiz1uz4G7BcCHlnUDwDyl1DKl1G0uX4vEiVgFAQk3DxOJLdF2oSwvt7eEWF/0TZp4KzUESTz0/WOdC+emBU53drRXgd0cuMaN5ZpuCCEGMRH8XSgp4EJDD2jUZRV2ywKn5zUHgwIuPjixwHklsmsq4ZqAU0oNgwi4ByzVZxqG0Q/AxQDGKaXOruP425RSS5VSS/fu3etWs0gUiNUPlQIuMYi2C2VFhb0Fznq9/2fvzOOkqM69/6teZoaZYVPGUREFEYEMKgYhBINxEkzEBTExBNeYmCjjzWvyohLJvZAINxdBIIlvIppoEqNGIDcCLhiVzCRiTOJIjPsWRAVBQVlElmGm+7x/PHOoU9VVXVXd1bV0P9/Ppz/VVV1ddbq66pzzO89yOIEJUyyf/zwtv/UtfZufAm7yZOoInXIKrasiYu9euoeTSf9itHgeOGLnTuNcgX4JZD+Ig4CTng35EuuElcSECQY7AafeE2yBCx5fBJymaScCuAPAeUKIg2GNQojN3cutAFYAGGN3DCHEL4QQpwghTmloaPCjWEyJCKrxYwEXD8JyoVTTTUe5A8TEg0GDyLvgrLP0bX7WP7/4BT0jo0bRuvq8qJOG+22Bq3QXyo4O4wAPW+C84UbAeUliku+3soCLJvI/M4s09TnKN7AvBH3OUzj5S9ECTtO0owHcD+BSIcTryvY6TdN6yvcAvgDAMpMlEy/yVbB+wjFw8SAsF8ohQ/T37D7J+EWpXCgBuk+tBjzUQQq/LHBhuFBGRRipmNuRKGWhjIOAq66m8jkJOLcWuHzU1ND/ZWfNYQEXDppG94BZpKnPkfk/u/hi4Nhj6f2ll9L/P3VqactZaThW7Zqm3QfgdAD9NE3bBOAHANIAIIS4DcBsAIcCuFWjXlSXEOIUAI0AVnRvSwH4nRDijyX4DUzABDHKKgQ1bmyBiz5huVC2tQHTpgEPPcQCjvEPVcCV4r6yEnClsMCF4UIZNQtcNksvtR1hC5w3NM15agsvSUzyIZ+9jg7r43V00LVSEw0xwZBKebPA/e53+vs//5mWL7xQkqJVLI4CTghxocPn3wTwTYvtbwI4KfcbTNwJwgInKwMWcNEnLBfK/v2Bc84hAZfwOx0TU7GoAm7YMP+PH7QFrpJdKK2mUmAB5536+uItcHIwJJ8bnTplgdXUMfI54TnfgiedLsyF8vvf1yf8fuWV0pStUuFuD+OZIBppFnDxISwXSvXcLOAYv1AFXCnmFgzaAlfJ88BZtSMs4LzjJODcJDFxg9Ok4SzgwsPJAmfn9jpvHv1vMpYyKs9eOcDdHsYzbIFjVMJyoVTPzS6UjF+oAq5nT/+Pb/W8sAWuNNhZ4KJSznIRcG6SmEjcWuCsYAEXHnYCLpGg/yNfEpP164HZs+k9TzfgH5wigvFMEA9gkKPHTHGE5UKpnpstcIxfqINGVm5cfh3fbIGT93ic54GL2ui6nQWOBZw36uqKd6F0gxsBV1XFAi4M7ARcVZX1Zyp9+thPRcAUDnd7GM8EIeDYAhcfwnShlNs5PTHjF6o1txTJEjSN6jVzDJy8l6urOYmJX1gNBEYpC2U2S8uoD0Dls8AJ4S6JiRsvCWn9thNwcqCDBVzwOAk4c79wTPekYY89Rq7oVgNXTHFEvNpgokgQIygy6FU2cEx0kRVzqTpvbixwDFMKSmW9Mos09R73K0YrSOtOVAWc1UCgXwLZD+Jigcsn4ORvCMoCxwIuHPIJuHTaKOCeegp4+mmaRuCMM2hb3760/PBDMD7BAo7xTBAC7oc/pOVdd5X+XExxWFkU/ERN8GCGY+CYUnLccaU5rlmkqfd4dTUNXBVbzwbpQplM0itqo+t2FrhMRr8+YVIOAk5eY7cCzk0MnFMSEx64Cx4vLpSnnkrLN9/Utx1xBC23bCltOSsJFnCMZ4IQcLIjEJWRUiY/pRzVZgscExZqQhM/MQs4swUOKF4MBelCCUTLsiWxs8AB0ShrOQg4eY2dBgrcuLk7WeBktsuou5yWI1YCrrNTr6/eeSf/92UWSjtxzniHHwPGM0HEwA0dSstx40p/LqZ4SpmamwUcEzSaVjrrG5ArdswWOKB4gRG0OIhSbJnEzgIHsIDzghRwViLMrQXuE5+g5dix9vs4CThztsshQ/Kfk/EPqzg3WW9t2UKxbnv3Gj9Xp2GR8cTmfZjC4Rx/jGeCsMCNHk3Lb3+79OdiiqeUnbd8LpSyM8YulIyffPBBaadLMT8vpbTABZXJN0rZHSVxsMBpWvTrr/p6KmtHhy6yJG4tcGefDbz+en7R5cYCJ8+zYQOVq6HBufxM8eQTcJK9e42Jn5Yv19+zgPMftsAxnilEwF1+OTVSra3ezsHTCMSDzk7gl78EPvc54N13/TuuEPktcDLNOwe1M35yyCHAkUeW7vhmsVMOFrg9e4Bf/AJYsSKY87khDha4qFvfAN39zcqN0kvGaCeLmVMWSnXC8IEDgV696D3X/6UnlcqNGzULOPP/1ru3/p4FnP+wgGM8owo4N37tmYyejOTOO72dgwVcPJBZQ9vagGee8e+4XV10j9k10MceC8yYAdx9t3/nZJhSk8+F0i8LXJBJTAC9cz9vXjDnc4OVex8LOO9IAbdnT+5nfrbVXl0oq6ohBuO9AAAgAElEQVRoguh//KP4czP5yZfERCL/N2kVPekk/TMpzjkGzj+4e8x4RjWjqyNidrz8sv7e7ehL0J0Pxj927/bvWLJBMLvtSBIJYP58/87HMEFgjhlVXcP8EhhBJzGRRMkd0Mq9jwWcd/yywDnhlIXSar65G28s/ryMM14scAMG0Dxw6j0hBRxb4PyDLXCMZ9RRGDejxNdco7//6CNv54hD48YYcfsfu0F2sthFhiknzBY4tSPvtwUuqDr05JNpKd2ao0A+C1wUEq6Ug4DzOo1APuR/48aFkgkWNxY4Waft25ebwVdmD2ULnH+wgGM8oz7EbkYxt2yhxn3ECPcPL1vg4oufAs7JAscwccScxETtyPsdAxdUHbp2Lbk0R6mDzRY4f3BjgfPjPkul6GXXTzC7UDLBkU/ArVqlrwPWAk7TaBsLOP9gAcd4xqsF7rXXgBNOoLTcdnPJ2J2DK+v4MXMmJYC44YbijnPFFeSKAZRuPi6GCQNzEpNs1n8LXNBeDHV19LyWMnunVzgGzh+CcqEEKNmFFxdKJhjyCbiePWk9nwUOyP/fMt5hAcd4Ro2Bc9PJ6NGD9quvtw6CtoJdKONFayslEpETrG7ZAqxZU9wxf/Ur/f3ZZxd3LIaJElYWOPnsxDULJUCW8igJOLbA+YMbF0q/hFU+Kw27UIaHnYBLp3OfKTsBxxY4f2EBx3hGfYi3b8+/7/799MCeeKI+Gagb2IUyXjQ3A5dcYpykdd06PTulV9atM6737Vt42RgmapgtcFYxcH4lMQmyDo2agGMLnD/IuMYgLHD5OvnsQhkeVgLulVfomVefqddeozCKQgScEDQQ/M47/pW7nGEBx3hGfYiffz7/vjt20LJvX28Cjl0o48mkSbQ880xa/uY3hR2npUV/z/cAU26oSUyEMLpQys6QedJcr4RlgYuCMJKwBc4fgkpiArALZVQxC7itW2m5Z48xMdCECfS+EAH33HPAZZcB117rT5nLHRZwjGfUh9jJHC5TxtbW0ije3r3UWXF7jjg0bozO975H98Tq1bS+a1dhx3n7beCii6iTVWxHlmGihupCKefSlC6UcZ0HDoiXBS4K5cxm9f89yrixwAXhQpnJsIALC7OAk//ROecYvQY2baL3hQi4LVto+dJLxZe3EohB1cFEDbVD7dS5lg9rba2eSXD9eudzhDF6zPhDTQ1lnOrfH/jv/6b38jVmjPP3haC55A4/3JiimGHKBdWF0lzXxTWJCUDiKArCSOLFAnf66Xo9tXkzcNNN+vqJJ5amfHGxwCWT1PkOKomJXax8V1c8rlc5kkxaJ7BTY+AuuUT/3E7AqfPA/fWvxv7BWWfR9lde8bfs5QoLOMYzXrJQyoe1Rw9KMQ0AGze6O4emxWN0krHmzjtzt7W36xYHOz74gIT/0UeXplwMEzaqBa5UAk4eN8g6NA4WOHl91cHHbBb4y1/09XfeoWy6khdeKE354iLgAPsQCL/DHerq7AVcnK5XuWG2wKnC3WqeVqv7wWyB++tfrc91xBGFl7OS4O4x4xkvAk4+rD160DQCAFlX3JyDXSXizRe/aOw4HXMMLZ1iT+Q8cr16laZcDBM2qgVOupSXQsAFXYdGTcBZWeBknaRe39dfN35PuoGpFOoOno84CRK7LNJ+W+DyZavmfkF4pFL6oBCgPz9VVdYCzgpzfOOyZdb77dzpLtSm0mEBx3imq0s3j7u1wNXW6h1yNwKOfd3LA3WUW2aodJpKQmY25QqcKVeqq+n+7urKtZT5mYUyaHEgk5g4WdmDIp8FTm27Vq40fu/DD3OPVQorXNwEXBBJTOrq7JOdxel6lRteLXBWqBa4bJaSlqjIOnDfvtIMmJQbLOAYz3R20gObTLq3wNXU6ALOzYPJvu7lwWc+Q8vWVrLIAc6ZSOX9IV1uGabcULO2ldKFMgwBBxRfdr+wssBZuVC+/TZ1ROXg0Rtv0PK664C1a+m9GrvjF3GyKNkJOL+TmOTLVs0Du+FhFnBOFjirQRxVwO3aRf/n4sW0rxC0fttt9PmmTTTYu2MHWeSiMigUJVjAMZ6Rk2lWVTk31OroXO/e9F6NNcj3Pa6o409TEy0PPzx/KmqVM86gJbtQMuWKamUzCzhV3BVDGHVolDI8AtbWIXlN5PV94QXqNHZ2UhvVsyewaBF9VlVlLfj8oqPDvfUibIKywNm5UJqn22CCJZ8Fzuo/Oeqo3G2qgNu5Uz+uyoABtJRzBx9yCE1D9dOfFlf+coQFHOMZ2TFwI+DUzolsqGprnc/BI23lwU9+Avz5z8Dw4flTUVvBAo4pV1SRZo6BSyYpgVOxLpRhWuCiIuCsrEOaRp1O+dm//qV/lkgAjzyir3/lK/5ZRK3Yv1+/ZlEnKAtcXZ319DFhTIvB6NgJOLtM0WefnbtNFXDyXpID+5IvfpGscmbs4uUqGRZwjGekgEunvQk4ADj5ZOD9992dg0fa4k9NDfDZz9J7aYF75x133+UpBJhyxcoCJ+M/NM2YpbJQwkpiAkRHwNllSFTbLnNs26mn6r/juON0y1KpLHDlIuD8tMABuVY4nhs2XOxcKK3+9wEDrLPf9uhB90tXl56szJxxMpk0TkcgKXZAqxxhAcd4prOzMAscQGZ1OVmj0/d4pK28kBY4tx2h/v1LVxaGCZN8MXCAMUtloYSVxASITmers5M6kubOpNp2SVeu+fP1zx98EJg0ieqsUlvg2IXSiGwnzAJOzWjNBE8+F0ozv/ud9THkf7dvny7gevbM3a9fP+C884zbBg/2Vt4cFiwA2tqM29raaHtMYQHHeMZLDJy5c9Krl3MWyi1bOAauHOnXj5aqy5IVJ5wAnH8+//9M+aJOJm0l4PyywAUt4KIYA2dVj1RVURKFf/4TePZZYNgwYMYM/fMJE4BVq3R3S6A0FjjZlsaBIJOYAHSudeuAl1+mJDMyU6ibEAzGf+Q0AjKZiJrERGX9ej15mRm3Ak7T6P+WyU1OOomm+njuOX3AxTOjRwNTpugirq2N1kePLvCA4cNdJMYzaqPo1KhZCTj54Frxxz8CEydS4GqfPsWXlYkOhx9Oy5tvBq66yn5E7cCB+HRqGKYQVBdKaXHw2wLHLpTUPlnVJek08Nvf0gsADjvM/hiltMDFaaCyvp463uaBgVJZ4BYuBO64I/fzfP8VUzrkfSrrFTsLXD6LshTf+/ZRdknAXT8vnQaeeQYYOZLWC8pI2dwMLF9Ooq2lBViyhNabmws4WDRgCxzjmWJcKJ0E3D//Scvt2+PTsDHuqK6mRhkAtm2z36+zk+PfmPLGyoVSdfPzwwIXpgtlVARcPgucijmRgtW+pbLAxaWds3NtLJUFzkq8felLua51TDDIukQKdjsLXL62W7XAvfMO3TNyYDcf3/2ut7La0txM4m3uXFrGWLwBLOCYAig0CyVAAu7AAfsGXnWPiEvDxrhn3DhaXnihvYWBLXBMuZNvGgH5eZyzUEYpBs7OAqeSzwog92ULHC3NbpR+JzGRQtGKz36W3OuY4JH3qRRwdv+7WwH34IPU33NTR40aZVwveE64tjayvM2aRUtzTFzMYAHHeKaQeeDkQyofejs/ZlXAxSU7F+OeT36SOktvvUVxDVawBY4pd/JNIwC4q1udCEMcxNUC94Mf2B+DLXCEnYA7cIB+g1/C6oQTgAsuoGygktNOo6QyV1zhzzkY76gulIC9gMsn5M0xcI2N7s593HHAxRfr6wXFwcmYt+XLgTlzdHfKGIs4FnCMZzo7qbPhxQInH/7jjqOlXSITNcMUC7jyo7oa+NWv6L3VZK0AW+CY8scqiYnZhTKOFrgoJDF54w3KgvfQQ8B991nXJfK6/PCHNJpvNWeVhC1whF16fzsrZ6HU1QG//z3w5JN6Eou//IWSyuSzzjGlxWyBk9MBmWPe3Ai4yy6j7595pvtz33MPGc2AAuvG9nZjzJuMiWtvL+Bg0SAmVQcTJeTcNYkEsHdv/n2tXCgB+zg4tcMxaFBx5WSiyYABtHz7bZoX0MyBA2yBY8obNy6UPA9cYRx/vHFdTX0ukSJEtkf5kBOrswWOllYulFxflz9mAfePf9BSek1985sUt5jvfpYCbv36wspQ1ACRmmZW0twc6zg4tsAxnunooAcpnXYeCfEq4GTl8Kc/AXfdVXxZmejRty8t7e4Bv0d0GSZqOM0Dx0lM/GP48NxtMomSHEzKh5xKgC1wtLRyoeT6uvwxC7g9e8jNVf73t94KbN2a35XWPIef10zjqueCZxYsoAKovrltbcAxx8TWtMsCzokynPyvWLZsoeegutr7NAJyzo+33rLeXx7vuOOC73wwwSArcatOnhBsgWPKH9UCZxcDF0cXyrCTmLz0Uu62I47I3bZrFy3dzilWVcUWuHwWOBZw5Y8q4Nato7T+qtt3Og00NOQ/hvl58zqnnzrw5Zn166nT8dRTJOLa2mjCx3feKc3oTACwgHNi/XqaVVid/O/88wu3Acecjz8G3n2X5uMoJAul1ZxHKn5ntGKiR75Renm/sIBjyhmnaQRqangeuEJ45hn9/ZVXAtOmATfeaL//0KHujlsqC5yckicO5LPAcX1d/qgC7tpr6b3VgEk+jjlGzyj5qU8Bl1/u7fvqwJdn/vUv/f1TTwGf+5w+ejZkSAEHDJ+YVB0hMnUqsHQpibZrrgFuuYXMBFOnhl2yUJCVd79+7kYlzZ0T6UJpl8TE70lBmeiRr5MnO0n8/zPljFUSE7MLZbEiKAwXyrCTmEi37A8+AA491Hn/o45yd1w/YhKtKAcL3DPPAJs2BV8eJlhUAbd1K70//XRvx0gkjIMsXinKApdvAmLpGhYz2ALnRHMzsHIl3TFz59Jy5cpYBz4Wg4wd6NPHvQUukdD9ohsb6Xsyg5EZvycFZaJHvk6e/P95RJcpZ+T9nS8GLo4WuFSK6vuwBZxTf+yb39TbMDek0/67UAqhT8kTB+wE3Msv6/cwU76oAk6GkV10UbBlKMoCJ1OgW+Hk+xlRWMC5RSqQCp9F8v33aXnUUe7iNMxxGIkENQR2KeTZhbL8SSbp/2ULHFOpqBY4qxi4mpp4WuA0zZ+yF8pHH9H5nYTZL35BbZnb5rwUFjj5v8dlsLKqispqFnBMZSDv085O3ePQ7TQAflGUBS6f0aUYs2CIsIBzQsa8pVI0e3sqZYyJqzD27aOlbCTduFCaOxH5RjNZwFUGdp08WTGzBY4pZ2T9Vm7zwAH+xO8Vyq5d7qYG0DRvdUwpLHAyXCAuAk7TaPCVBVxlok7kHVY7XZQFbtky+8+kZSJmsIBz4oYbqOZeuZJmb1+5ktZvuCHskoWCnPetrs69C6UXARe3Ro0pDDsBJ7eZ0w0zTDkhBUSpXSjDEnBhWuDcCDivlMICF8e2zk7AjRgRfFmYYFFdKDs6qA4L+t4tygL33nv2n8U05TkLOCdGjsw1B6XTtL0CkQKutrZwAZdKWU+uCpCwSySMo9FM+WHXydu5k5ayomaYckW6oFsJOPl8CFH48cMScH4kYCmUjz/WY7X8pBTTCMg2ME59x7q6XAHX2GicWospT1QBd+AAPedBRxQVZYHLl8Rk9OiCyhM2MRr7CYnbb6eMk1OmAC0twJIlwIoVFZvERMauSQtcZyd1MuweZKssW04ulOw+Wf7YCbg33qClmwl2GSbOyMm6ZSyU2YWy2CQXlWiBK1VK+1JMI2AV+xh1rOLX45RJkykcs4ALo59WlAUuX4Hffbeg8oQN2zmckBN2t7RQFsqWFuP2CkNa4Hr00BvKfCOThcTAsYArf+w6eZs303LYsGDLwzBBI90k7VwogeLcKLNZFnB+UQoLnFXsY9SxcqFkAVcZqAIurOypRQm488+3tzScdFLBZQqTGFUdITF6NDB5Ms3/NmsWLSdPjq3JtVhkw6xm+sr3MHkVcD/+MQdJVwJ2nbx166iO7dMn+DIxTJA4uVACxQkhOYVL0ISZxKSzszQCbsMG4M9/Blat8u+YcbXAmdtnHnStDFQBF9YE9EW5UAL2Pun//neBBwwXFnBu0DT9j8/nL1gBdHRQpyCVKlzA5YuBYyoDOwHX1QX07l3RjxhTIZhdKP22wFWqC2UpxMTGjbT83//175hsgWPiROwtcE884WtZokCMqo6QaG+nmLfvfIdcKL/zHVpvbw+7ZKHQ0aGPDpfCAsdUBnadvPvvr9j8QEyFYbbAmWPggHgKuDCTmJTKAifx83qWiwWOBVxloM4DF9Z/rk6/4pnBg623DxgAfP3rBZcpTFjAOTFjBi2XLCEXyiVLjNsrjI4OvXPBAo4pFCsBt3u3boFjmHJHWuCsXCjd1K1OsAXOf/wUh+Vggctm6cUCrvyRz1WYLpRqGTyzbVvuw5ZIUAKT9euLLlsY8GPnRFsbZaBcvpwyTzY3G9crDL8EnN0IytixQM+exZeTiTZWnbx33qHlBRcEXx6GCRpOYuI/pUpiIvEzO26cLXAykkR2pDkGrvwxu1CGIeA0jZ4XXwwAyWR4gcI+Ed+SB0V7u1GsNTfTegW7UBYr4PLFwIU1aswEi1Un7447aDloUPDlYZigkfNoljIGjpOY+MOnP01LPycJj6sFLpPR/984zmXHFEYUYuBkOQoScF/9qrGylQ9gVRVNFRZDHKsOTdN+pWnaVk3TXrT5XNM07RZN0/6tadrzmqZ9UvnsTE3TXuv+7AY/Cx4YM2bkWtqam9mFEqVxoWQBVxlYCTg5RcW4ccGXh2GCxmyBK5cYuLAtcKXoWN53Hy39dP23srxGHTlJunSjlNeDLXDlTxQscEARITjLllGhUynjwzdwYGwNMm7Gfn4D4Mw8n08EMKT7dSWAJQCgaVoSwM+7P/8EgAs1TftEMYVlwqfUAi6bjdeIJFMYVp28HTto/jfOQMlUAvmmEYizgCvHJCaNjfrx/cJqAveowwKuconCNAJAEQJu5EhjRnlphYvxnEWOVYcQ4gkA2/Psch6A3wri7wD6aJp2BIAxAP4thHhTCHEAwNLufZkYwxY4xg+sBNz27UDfvuGUh2GCJl8SkzgLuHK0wMljsgWOlizgKo+ouFBWVRXxHGaz9OANGqRXkH//e2yz8Pgx9tMfwEZlfVP3NrvtTIzZv59j4JjikZ08dV7NHTuAQw4Jr0wMEyTShdLKEuNHFsowk5iosX1BUqokJskk/T/F/B9m4prEBNAFnGzHY9r/ZTwQJRfKgp7Dd9+lDubxxwMbNugibtiw2E5M7IeAs3J4Enm2Wx9E067UNO0ZTdOe2bZtmw/F8okFCygTpUpbG22vQFQLnByByfcwWT3oTi6UcWrQmMKoqSHxpt4HO3awBY6pHGQSk1Ja4MJKYgL4K3bc0tlZOsuA39PfxDWJCQDs2UNLtsBVDlFxoZT1pmeyWWDSJOCNNyid7IYNJOYGDYptTgs/qo5NANTkukcB2JxnuyVCiF8IIU4RQpzS0NDgQ7F8YvRomjZAijg5rcDo0eGWKySsXCjzdTIKcaGMU4PGFIbs5KmuVuxCyVQSpZ5GIEwXSiB4N0ohSuvaVXDH0YY4WuDq6mjJLpSVh3ki79i5UE6YADzwANC/P7BxIwm3118Hdu0CzjrL93IGgR9d5QcAXNadjXIsgF1CiC0A2gEM0TRtkKZpVQCmdu8bL+S0AVOmALNnx2oOuGwWOOkkitvUNKCpCTjnHH1dvk491dhROPxw/bPLLwdGjNDXN2zQG2gp4CZPBv70J+sy2Ak4dqGsbNRO3owZwI9+RPUoCzimUpBJTEo5jUBYSUyA4AVcqeckYwucboHbvZuWPA9c5RAVF0p1IOXhh/W+6dSptHzhBZsvrllDGSc3baJO7ltv0fpTT9EyhriZRuA+AH8DMFTTtE2apl2hado0TdOmde+yGsCbAP4N4JcArgYAIUQXgG8DeBTAKwCWCyFeKsFvKC3SVbKlBZg7l5bq9gizcyfw/PP6+ssv0w1v5qmnaCACoFHM99/XP7vrLuAl5V/bvj3XAgcAjz9uXQa7GDhOYlLZqALu5puB//ovWucYOKZSMCcxKadpBIDyE3BsgbN3oeQYuPJHPldhu1CqMXBf+pK+fdkyWs6cafPFCRNItPXqBbz3HtC7ty7iWltLV+AS4vgXCCEudPhcAPgPm89WgwRefBk9Gjj/fFI2s2YBP/0pcMstwIoVYZfMkWeecb+vfBitOgxq5lUg1wIH0KCGFZlMblA5x8Axdp08tsAxlUKpXSjDTGIC2Jc9mwUefRQ480x/pwzZtYuWpepYFpX9zoI4W+DYhbLykPdplCxwdXW5gyq9e9t8cc0a4LDDgK1bqYLduRPo0YNE3DnnlLLIJSNGVUeICKG3NGY1E2G+/339/bx5wHHH2e8rH4Knn879bNAg4Mgj9fVjj6XloYfq2157zfq4HAPHWMECjql0qqqoKZFCR60ni81CKQS9wkxiYmeBW7yYQk5WrfL3vI88QksZp+U3bIEDamtpyQKu8tA0PYN4VGLgrDLOyjkbc5gwgcQbQJVuMgns20frcnvM4K6yE+3twMqVwDXXkAvlNdfQegxmbt+5E/j858lf/YYbyDd42zZ6+Hbtokr417+mfWXDtLk7zcyzzwIffUSW5pdeogyse/eSe6V0d+vZk1wpvvIVvUI3w9MIMFbYdfLYhZKpFKSVTfYhrARcoRa4MOcYc4qBk4N9m21TmhWGPN/kyf4eV+K3gIujBS6ZJBHH0whUJqqAi4IFTsZifvnL1FeVn1uyZo1uQgb0B1A9UMyIUdUREjK96JIl5EK5ZIlxe4TZsYOmuJD3bE0N0K8fVcK9etFIpbSsyRENmWxz4EASaI2Neme7Rw+yQKtuL7W1uiuQFXYWuEzG2pDJAq4ykPfURx8Zt7MFjqkUZEdDCji1I69pepKTQghTwDlZ4LZsoeX69f6eV14rKSD9ppj/w4o4WuAAGshduJDyuX32s7SNLXCVgRRwUYmBk2U4+WTqq/btq8dn5jBhgr2lYcMG38sZBCzgnJDTBixfDsyZo2ekNM8NF0F27QL69Mm/j3kuNynOnL6nIidltsLOAgdYW+E4Bq4ykJ0885SPLOCYSiGfBU5+Xo4CbsQIWvr9rMvzyfP7jd8CLo4WOJXf/15/zwKuMoiKC6Xsr150ES2vv56W9fX2Gg1r1thXOp/8pK9lDIqYVh0B0t5unDZATisQcRfKbNY6gYgZ+bm0wH38sR7j5pbaWr0TYsargOMYuMpAdrLMrucs4JhKQQq4vXv1VNjmz70KhmXLaFBEWnfCjIGzK7v8nXZtRqGU2gJXXe1vEpNycj9kAVcZRMWFUn0OGxr0fmxdXR4BN2ECuaVZsXGjr2UMijKoOkqMlatkc3Pk54Fz2ziYLXB79hjdhN3Qowd1Qqywc6FUy+i0P1N+2FngSjV6zjBRQ3WhtBJaXi0+27bRXEhjxwJ//CNti6IFTtb7ZvfpYtm/n9qWUonWqip/p0aI6xxqo0YB69YZt5WDCGWckVNAhelCqVrgMhljOerq8rhQrllDrmU7d+Z+1r+/7+UMArZ1lCluGwdztrOPP/aexau21jifkYr5AQP0davRTBZwlYHs5H3wgb5t8OBwysIwYaC6UFrVeXKeOLfI+vStt6KdxESWbcMGGvizajcKoaOjdNY3wP8kJnGdQ+2ZZ/QspwMG0La4iVCmMKLgQqnGwHV1Geu4vAJuwgSjeFO/KF0WYgYLuDLFbeNgdqHcs8e7gJPzblidy/yAAfktcBwDVxlYWeC8Wn4ZJs7IunfvXnsB58UCJ10ThYh2DJys9x9+mNqaVAq44ILiz7t/f2kt+H4LuLha4FTk/RU3EcoURjodDRfKgixwXV36HAN1dfTlhgZa93NCygBhAVemBOlCeeml9p9xDBxjBQs4ptJxY4HzIuDkILKMfwaiLeBU/vCH4s/b0REvARdXC5xKnMvOeCcKWSjVGDhPFrj166nDcdRRtNMJJ5AL0NFHW7tVxgDuKjuxYEFuxsm2NtoeYdxOsOmHC2W+ubvyCTh2oaxcrARcz57hlIVhwkBNYmLVGfIq4NT6NMwMh05JTOxcJq3E0csvA9/+dm6srBX798fLhbIcLHCq1Zcpf2QMXFQtcPX1eQQcQDfspk1kdXjnHTrYli36fBgxgwWcE6NHG6cNkNMKjB4dbrkccGuBM7tQ+u2G4iWJifSrZwFX/siOFlvgmErFbxdKWZ+qLpRhiAOnGDgrCxwAvPRS7rYf/xj4+c/1pCz5YAtc8Nx+O2VgHzQo7JIwQZBK6c9A7GLgzAhhnf43RrCAc0JOGzBlCjB7tj4nXJlmoSw0Bm3yZIqFU5NSAN4scGGmvmaCJZmke+/DD/VtLOCYSkIKnT17rOtpr1koVQEn34cxGJZK0XnzCbiBA/UBOynOrKYVkJkqX3jB+bxRssBls8AbbwDvvUf/7/PP00D/unU0dUpnp/5742yBa26m31TK685Eh1RKv2/DdqGUA1XmGLjt2/NYhOvqgDPOAO6+GzjmGKpgv/AFGomIIdxVdkNzM9DSAsydS8uIizfAuwul3L/QGLRXXqGJwxsajFNqeImBCzNugwke82g5CzimknBjgfNi8bEScGF1smpq8gs4c6cLsJ6/aflyWt58s/M5o5TE5PbbgeOPB444guq1k04CjjwSOOUUyqNw3nnA//k/tG+cLXBMZaEOzIQp4AA9mYpad/boQctHHrH44u23A+PHA48/TulTX3iBMlNOnx75kCg7WMC5oa0NWLIEmDWLluaYuAji1YVS9SkuRECplre33tLfe3GhZAFXWZg7WzwHHFNJ+B0Dp9ansi6NooAzj5r36kXL3buN+9m5WtoRpWkE3ngj/+dqBzPOFjimskil9DoprPtW7bOa+5eXXUbLN9+0+OJVVwGPPUZf2LiRkpg8/jhZ4NavL3m5SwELOCdkzNvy5cCcObo7ZcRFnFv/es3yWOMAACAASURBVL9cKFV3yF//mpZ/+hNZ5dy6ULKAqyzMgo07MkwlIcXGgQP+xMDJ+jRsF0qAnm27sptHzaWAM0/sfeedxnUn8RSEBc7t/3Hbbe6Py/UeExeiYIFT+6xmAXf00bS0TXrU2UlfSqeB11+nbV1dwIoVJStvKWEB50R7uzHmTcbEtbeHWy4H3Ga4SibJZVK1wBXiQqmKMRmMPmGCfg4VOwscx8BVFizgmEpGjiQD/lrg4uZCKbPPmgWcjI2T9cSuXfnPGYQFrqvLOeNiR4cxns8qwcexxwInnkjva2v9KyPDlJJUKnwBl88Cl0pRVnTHrLVdXcbKVfpexgz2vnZixozcbc3NkY+D89KAq/NqFOpCKb//5S/TnD6//73+GcfAMVaYBRzHgjCVhDpQZTUNUXU1Zbp2m7Jb1qc7dwJLl9L7sJ6p6mr3LpRSwG3ebNxv927g05+msPPLLgOeeop+mxAkig4cAJqagLffpkRyL7xA66VCDjB1dhrFtxkpNH/2M+A//iP3889/nvqOxx1HvyfGSfCYCkO1wIXtQtnZae0x1tBARoT162mf449X6traWvoB0loA0Ie/+U0QRfcd7jKVKV5SFKtpWQt1obzwQkrsc/LJJOCmTNE/YxdKxgq2wDGVjJq0x2rE+J//pOWttwLXXON8PHVATMbkR9UCp9bxskNmJeD69KF5dwHKdGzm0EONmWzNx/ATteOYT8BJMd6nj/Xn9fVUZrOQZZioo8bARcUCZ/bYGjSIrPfHHUfrN90EfO97oCQmySTlsVCJcfA9O6uVKV4tcMW6UN55J3VCrAyWnMSEsYIFHFPJ1NUBF1xg//mmTbT861/dHc8q6UeYMXBuXSgBEjvm53/3brLOnX66/XlU8QaUVsCZ48XtkNk07bLq1tXRPmYhyzBRJwoulOpzaGVwuO8+4PLL9fV//KP7zVVXkYgzm7z37QNuuKFUxS0pLODKFDmZoUzRnA8/XCjTaaBfP+tOuPlB53ngGIBdKBlmyBD7z+QIstuBDXN9Gib5kphYWZ4OO4yycapIAadp5NnhhkMP9V5Wt5in3LHj73+npV1YTX09tc+dnTxoxcSLKCQxcbLA9elDk8tLVqxQ6qJslnywEwk9YFaI3BS4MYG7ymWKDAiXGb7yoVrgstniBVRrq3GdY+AYK+yEPcNUCt//PjB8uB6zpvL//h8t3T4XVha4ceMKL1sxeHGhBIDevXOTlEgBBwDXX68n+/jGNygE/ZpryHX/hBOASy8FLrlEv2alwK0FbssWWo4ebf15bS2JVbexjQwTFVQXynxuxKVEHUixMzhMmkT1gWTrVtMO6bSejSiRsJ6EMgZw9RFz/vY34Mknad6LY48F/vIXmjxUZoJ0I+BkDJy0gBUroJqb6dn4r/8CfvQjY7yoPB/AAq7SMf//PBrNVBr19cDLL1t/NnIkJeW46y7gU58Cnn+eMqx9/DHVr2PG0LbaWqo75dxizz2nZzgMi3xJTLq6cq3vffpQ3Mo3vkEJS7ZvJ0EnBdyFF9IrTGT99L3vAeefr7u/7ttHcd8PPgicey7w3/8N9O1LLyukgHvtNc5AycQLtW9Wyoyv+VAtcHY5G445hnIyfO5zVKcc7IMmk1SxrlunH+yTn7R/WCMOC7iY4zTC6tYCJzP6AP4JKHkcKcwknMSEAYD33qPleecBq1aFZy1gmKgiB+Kuvtr9d6IwEOJlIm9AD0v59a/1eUQB+ziyMJCWtd/9jl6bN9Ng6VVXUWcRoBmGAGDHDvvj1NaSiN2yhVxHGSYuqM9tWBY48zxw+TzG5GeZDIxJTBIJ3d3slVd4HriKYMGC3Am829r0lF8RxG0MXEeHLqD8ikEzPDwK6TTwEerQPOtU2tB9XY+44FR8hDr6XsSva+zx+14u4HjDhtHyy18GMrV1GHHVqcYPDz/ceANffTVtHzYst0ebTucGnWhabsByMsl5uwslhvUfAOv7Rd5LTmha7n3Vo4f9PeTXNbI4zulow/VwPk5gbnkNDTT6onLeeUBDg6eJvAHgiius9/UyD16p+eAD47oMU3jmGW/HkVa3XbvIYhcq6v191ll6nSnv78WLretRKxIJqrNVDj+8PIPazzqLro1KfT1dp2SSnoNhwyglYiJB21MpY71z6qn2HTR5zevqaD91m6bp6kn9z846i7YtXkyfl+C637tUQwYafoardQtcKkXnb2ige+lUpR1vayNzmJuOqEscLXDKNUsmgQw0HDO4+/r/9rfUV5DWiv37c4Nv44QQInKvUaNGicgwf74QAwYI0dIiRCIhhKbRK52m7XJd04QgzxZ6tbYKMXy4cZvKokVCTJxIr0WLrD9z4Pnn6bAZQGQAcTpaD56qq3ubmD8/94um8owZo+8PCHHTTS6ui6YJ0dho3NbYSNu7mTuXTvP973dvSCSEGDjwYHmzgOG6Zbu3v/r5FiFSKSGuvNJFQcqA+fP1/ySZpOvU2Gi8d9SXvMb19fq63X1mtU3d3tpK662t9vvmQ5a5poaWra20VLfbsLtHP7ECk8S99wr9N/TtK0S/frm/p6Ul9zpYbRs3jq6febv6m61e+a6VFbKM6jMwaZLx/xGC6gn1uFb/lfpfe8Wu/nC6F+bPF6J3byqzRNZZ/fpZn8vNPVNEfVYyUinr+0bdbqZfPyHq6vTPa2r0/zfffzVmDH1PvUZ1dbTdinRaiKYm4zblfpB1+nexyFBH2732Iy26auuN/0FTEz0TXv8Dpzpe3tvyHpLXJ50WLS1CNDRYH/bEE4WYPFnQvvX1QgghHnlEtlua4TfOmyfo/xo61FvZS4Bsz+Tr2Wdpu9X/kJH3jEpNjRCAWLJE3+/HPw7wB9TWUv2oot7fDQ3GH6HWI+Z7vqmJ6vf583PrNC+v1lb9PioEq+enqYm2e7kO48bRdjvUNsmqffHy6t3b+pp6PY7V/2Pe5tc16z6e7LdlAdGVr2zjxhnbh0L/Xwv+8Q863MMPCzFihBDnny8O1jvme9HQ15T7qGVKpYQ45xzrfnKEAPCMELlaKWdDFF6REnADBhT3sOZ7uOrq9BtKNrjqPmoHddw4vSHr21cIQByoqj3YWMiH6nS0ii5lPefBsaiQ5f6y4cyY91FverXM6vEtOqH/8z/Uodh8aJPh3Blz+bpfWfP23r1z/w/1epi3WVXALoRmXmTFPXCgvm3SJGNFITtralnUCqG74Q70pZZFXhs330skcn+LVYM1cGDRZcyk03Tf9Tss/75qRzqMa2e+HuaXldh2+o7dy9yIFns8q99jfpmFiXo+q7IAQsyalf88svNqrvO6B3EMDBxovO8KxeoaerlGfnxH3qt1dXSN1HWV2lpjvdDYSHWa6RxqB0TW0R8n6w9uHzWKNPcTPSfmdlbMr2HD9HrLy/WU9ae5jleP3auXYf3//l8hevY0/d7uOrupSYgLLlC+X18vslkh9qfrD/7On6FFZGDqJKrnVDnmGCGqq43bWltzO2WAPtgqf5O8Hi7ahP37hbj4Ytr9PfQTXam0yJ476WCRVmCS2Iu0eA/99DZUPgfKf/3zn+s/4957Tdfa6vq7ofs6GpADfOYBsXHjhDjMoc61e7W20h8o182DI8W8vGD+TfX1ufWYOhCl/ufm81q1b+qzWIxADftld68AuohT/0/5eY8elsfLwqKf5vf/CxgHP0zHyVi87M7pqqxjx7KA8/MVKQFX7GhLvtdhhwnRp4++Pn68/t5FpWEruOweHhc3+UHLXb6X0zURQoh0Wrx/WJNlh8LuocqalgbrgFX5zR2eVCr3/5Of2XVC8mE+X9++9v+LebRJHj+ulX/3IEFFvvz4z/I8b66+a/X9Yo5ZaBnyPQ/FlE+KOHUgwOmcbssRxn8mX04dYykS/Cx3d53mqWNlx9ChNFDoVMZ8HgKAuOEGejtsmBBTpypt1LhxYuhQIbpg3YaovyFvOyQH8FQRbFcHF3oPWN2HQoi1a42Dph+hzmiZSKbznmNXXePBjmdeK4bTf2X1PEgR5+f9FdTL5nrb/lY3LzkwLtfNg8/l/pLIgTOn/c3C2PQqWLxZDQyrZfRwLLOIdCpL3n1kX9bsNRIx7AScRp9Fi1NOOUU849WxvFSok6T5zaJFwLXXFvz1LIAkBDLQigpmtLoDiooS6tsX2LEDovvYmul4cpuA9XkObjffm05++DKdptsYJyH0fa2eA46VYsJAvS/DLgegl6WlhQLA7ciXucLt+RIJ/bxRuQ5+U6LfpdZgro8ur7W5nSvyv9yn1aBa7DfU8bKNkuW0q/uR5/OS4+K/kQnt7PaidjnPKUzrrn5nYyPw/vu525PJ3CDzODNpEvDAA8ZtattcjvVBqdA0PdbLp+tm12dzZPhwSrfrQzm89lfz1TdIpYBvfQt46y1g9epii1YyNE1bJ4Q4xby9DKNLfcbH4MscihBvkmLFmxVFP2JKCq6ijqUG7bp58Ds7vVUQ6r7mc3FDwYRFVO69QYOMZckn3oDixBtA56qEzlqJf5eno8u6zjxIWeR/WSPo+wnkDuDlK1/o/3gB/4359zm1x5rp5Qor8QaUl3gDcsUboN+jnJ7aG3Iwwsf6puAjbd+uJ1nxqRxun6G8n2cywC9/CUyYYNweh+RcYAHnjIdcqUHbMj01AC6OVSrMx3YzWsIwTMi89VbYJWA8ELr4MRG18vhFvnbXzzaZMWGeUJaJD++/r09UWSSFPF+23xECGDIEmDdPz/rb1gZMmQKMHl1gCYODBZwTYc1W6AK/Gwu/G56iRkYYhmEYT0SlTnWyukWlnIXAIo1hokNRg/6JBPDOO8DYsSTaZs+m5fLlQHOzX0UsGSzgnJCzDbsgyErdT0tVkNY3v/dnGIZhyoe4CCQvrqEMw/iL1z6w5f5CAPv2AUceSTHec+fSMgbiDQCCmvIzvnR1hV2Cg6gBpH43FlbJRkpJvmBYbggZhmG8UXCCgRJiV54oltULcS8/wxRCnO97y3ILQbGVK1bQ+1mzKNa7uTkWIo4tcE706uW4S9BxWxwnxjAMw8QFbrMYhvEbX+qVri7gww/JbXLOHFpOmaLHxEUYFnBOeEhiEgSlbAiFaRkWYZ+fYRgmjsSh7oxDGd1QLr+DYbwgp4cK8/y+omnAzTfrFrfmZhJx7e1+n8l3WMA5cUrO1Au2lPLGNh83qPOUkoptAK3mnKupKexYRx9dXFkYf3Ezr2bfvqUvB1OepNP6e00D5s8/uBrV+jSq5SqGuLqRMUyxhB2jKucQdovjvj16AK+9ZtzW3AzMmOGtYCHAAs4Jl5P7CZv3bvb3guf5Y0pYFk8MHUrBod10IuHfea3Ez9Ch7r47aRJQX2/c1q8fdcT9mHD3sMOApiZ93Tw5MgCMGVN4iuSPPiq8bEx+ChXVTmzfbuyIe8WNSIw6jY1hl6Bwwrz+Bw7o9042q3cy6usPzrkWNSJ5t7a06HW8RLYZiYSrej/Uay3bKIBieNzekwnu8jHFUZLnOeUtHYcA8F7f4Y5lcVXWYucvDRF+mn1AWt6yynrJGTjQvtKWlbT580WLXB3aVko0NtJ5zbS06J3dpiZq/IYO1RtIIYBXXwVuvfWgkDvmcBcTkJon9rWjs5P2SyT06/Lqq8Z9Jk0yHiudpkZw1Spg925jWbdt0/czn7+xMX/Hftw4oyDcvh148cXczkI2q2/76CPqmLlx1zWLTVlGvyacVxt4q//a6v8QAqit9ef8dixaRNe2FAihPxs1Nfr/sm+f/l+7uQ/lPm727d2b7knFgnKQ1lbrY6v3kHzfr5/zueyOZd7mlaoq+h1uGD5cf59IUHZf9TeZX5JkkgLL1Ul8CylrU1Pu98aP93YMtWzqdS9UjJ9zjvfzA1RXqL9FCKrDZP135ZX6Z07/j1MdK3+bT1Zjz14qxQx0jBtHv03WG+qzfeutSqGUNkoImtx34UK6NvL86TStm9tQK6HnNOG0vBfl81tfT8evraWyTpqkC7Rx42i7+fmQbZQQeqI1WZZ810wdKEwk9HYzitjdc3J7UxP9Vr8HVMxiQl4nPwZ0S8GAAbnb1HtF07wNmLmt0/1k8GDqR06cSM+YELQ+dCitT5xIbWVrKyAEDu0jMO+Sl/G0Ntbx0NJiZ3uXZLPA88/7+GMCRAgRudeoUaNE5OjbV38kNM1Qne5Ab7EXNeJvGCO2oa/I5O+aCAGIrHlbMmlcylciIYQQ4gAS+neamoxla2oSIp22L/vEiUIsWkTve/e2LEum+9UFiD/8QfmuLI9KS4sQQ4cWdTmPOkqIfclay7Ic/J29e+tfUPdrajL+H+bylQJNE6Kx0bitsZG2Dx0qRColxLhx+mctLULU1AhRW+t87DFj6P9zum9aWvTvNDXp5xZCiKOP1verqaF9zfeqEEK0tuY/RzH06+f8GwC6Vm72ky957wph3D5+vLfjFPubrf4L8/W12tdq3U/k/2x3D+WrG7zQ2kr3s6bRtdc0Wm9tpc/nzxeioUGIqiohevUSYtYsIerqqA4ZMMDbuWpq6Hvy2K2ttF5To//mvn2N35F1gko6bawvTfWqWLRI31bbXR8NHEivRIKeaXV/FfO1nTjR+Az266c/p3J7VZUQ1dX6dxYtomtTZH2ag/yv5O+S19FvamvpGqltzLhxtH3RIiEmThRvVg8V9x1Cz0tnJxXp6dHdbYi5XhfC/lmZP1+IK6+k35JI0H/U2krb5s/X/zNZJhVZJrdMnEjPuHoNW1r0/7i+3rh/fb2xvLI+rqmh56CmhtaPPtp9GYoh3/NhdT8XWneOGVPY99R+zrBhxv+n+77x/HvVe8bcPzCX2fw9WXfKe1jWC+a6c/58f9qcQl/yvjb/Xtne52tf1LbL1Ic9+NI0Yz1memVh6qP58SqAhgYhpk0T4pHERNf97Uy+cjc0FFSOoADwjBC5WilnQxRekRRw6gN0zjkH1zOA+C4WiQw08QDOEYAQu/qaKm/TjSTMN5K54yXXlUp26FAScYXe8AeRnedJk2i9pUVkAXEACfH6t+YLQIiVK4s7hRsGDRLif87IFROGyuHss/UvyG1qZ0xW0n51UMNE7UgCeuM7cKC7im7oUKPAE4LW+/XL7bwlEtaVmFUn1Suy86Seo2fP3HO4rdzr6ozHt2torRqiZFKIsWNzf2MxDYjddTZ3wK2OXUSD5QrZKMuBhsZG/Vr4wZVX0qDKpZfScS+9lNavvNK4nx/iYf783O+1ttL2YlCFhqSQDmPUaW0VokcP+g969CidgHPBiBH6bb9vH72fN0/ZwSyyhXAelCw1Y8ZQ+y0HInr1onW185+PAQNof3UAoqbG+0BGUFjVnU51c20tPftu6/LGRuMgixwA9av8ZsGqDhSqg33nnJP7fS/1gpvBVrcvtT2S9bba5qt9yERCv5+GDqX91UEJp4F1te2SAwxNTfp2gLbn+U99F28FPuP9+wvxjW/Q190IuK5Eyr7sw4cX366UGBZwxaKO6s2fTw93KiWyqZTYin7iu1gkVp5KAmhnb1PlrYx2WAq4ujrjDVVXl9PgHnusEBdf7MPvsOiAvjC+RbyMoeLBB+n0Dzzgw3kcGDJEiMcHGyuKHUefoD9k6XT5darsaG3Nfw/IkWW/UK116svP0eGzz6ZjmoWWFOVurXDDhhmPa9XQmkWa2jjIa9i7t95YDhigN4iqlTfu5LMS+4Gs9/r1o05Fv360bm78IiQeKpLWVhIcvXvT/9S7N62H9D/IvqEQQuzeTe9vvjmUorhH1imyrZQ/YuxYd98v1QBEqZg4kerDvn2p7enVS4gzzjDWp0Lkehyoda8q+jSN6u4rr6R2xYv10y+GDbNug8xtSqHHdfM67LD8nwuhW5NVpEVXHQCwGiwrlHwDkXkEnLRi+SbiCuzjDRxI44fJpIOA675++04eK7KA6NISet8AoPu8Vy//rmuJYAFXCrpHRm7ELAEI8etf0xV9bIKp8lZGWSwFXG0tudUAtJQjWwoDBghx+eWl+Rl33kmnXraMlg8/XJrzqAwfLsRvT5ivu5a0tIhly4T4GcgiKGpqotvY+Y0UO3V1utuZKnb8ppQWOInTiKbbCt7NiLdiETe81M6WFG1HHGFcRnVEPIq0thotuuZ1uS1C4qEikZbSUnX+PPLDH9KjlskIsXMnvV+8OJSiuGf+fN3VTLoLt7SUf5t05ZXG51XWpeq9I0WcEHpbJQe3J02i9Si036WytktRVlWVfyDSzSClHWEOAOQJs/Ak3pzEaxFCesgQIaZO7a5XXFzfzjMmis1oNJZdegalUrEVcBGNXo0QCxbkTujX1gZcdRWwZAk+vHoWWrAEp6MNqRRlJH1s5AzjLO6ZjH2697o6CjKtrqZg/epqy0DZri7PiXpcU11NS5mMJ4iY5nQauH9w93VqaQF+/3v0e6EN38at2DG1ha7Z6NGlL0gU2LaN7oMHH6SJJB98kNbVZCp+Yg5kt9peLKtXA9OnG7dNn+46q+tB3NyMMgB50iRjMpU339TfT5xIyQW2bAF69aJlMknbGXe0t9P8OPnmy1m6lOqvFSvoXl6xgtaXLg2nzJXI4MF03dX/acUK2h4CMjfTgQN6vo1StWW+8pWvAJ/5DLB2LS2/8pWwS1R6Bg8GVq7U7x0hKHGEeu/IBFwAdXgmTQL++ldaX7VKz+wcdhp2v9ogM/v30009b55+Hcwkk3SzDxpkf5x8bdsMUx8SCC61fXu7bX9VdOdePQAlUY5V0p6WFuD9940J39Jp4Iwz9PXt2wsuYjpN9QkAdFQrSVfURHBKMpbkFyegEe8jK3PHaholfpLvp04tuCxhwgLOidGjjbOyt7UhM2kyDtyzDNtvW47r9s7BFCzHckzBEa+2oaqKkiLmcOaZOTe6SCaxu88AiGSSKs05c2hp8UB0dhaXkCsf8p7ft4+WTkm0/CCV6r5Oq1dTRrDlyzHup1NwI2aj16O/Bx59NLcCK1e+/GUSbWqH68EHaXspaWoioaxOcxAUbkcJdu503kd2Iv7yF7qxZs2ih+WDD/TnduhQ6ngkEpT1M5GgdbfTTTDuOhUREw8VSZidPwvkmMrevTEScOvXA2edBTz5JGUrffJJWl+/PuySlRav9862bSTaVFatKt3gYxQ49VTgiitIwB1/PG1rbKSOk8y2m8mQWNm61b6tC6KjVSh2qfUTCTyPE1CFTj0jdiZjzIR59NHUp2trAzo69O2PPkr9YIn6mUfSab2IXcluC0QySapOXldpmQCg/WkNNuJomrxKzbyracAXvxiLSbutYAHnhBxlnjIFmD0bmDIFd3w8FV/cuwKHXtCM3/wG+DOaMQXLMWJ/O9JpGwG3eTOQySDbfcmFlgAyGWx8F1j5tZXGDs/KlTkdnnIUcLIxBwA0N+O1z7VgNubio4tbKke8AcF3uNJpEm0vvkjrL76op2QOikMPdbdfr17O+7z6KnD44VQpy4GQRx+lBkZaftasAc49V7cyZrO0vmZNYeVnrImYeGDCR/bz9uyhvh4Q7b4rACrg/v3UCTz9dFru3x+DgjMl5/rrgTvuIItsNkuDh5kMTd/Rsyd1bhoagMceo4FYO88Wy45iBEilSHhaILIZnIAX8QTGAx9/TBsTCWDjRl2obtxIfWU5TYoUtT/4AXDddTQtQGsr8P3vF1zEqirFYwxZmm5DdmSrqmhdve4TJmAA3kEGpjkT5fuYtk8s4Nwg3fzmzgVaWjANt+PPMHZSHtzdjMaFM+wF3NatQDoNDVk8gfHQRBaZRBofoRf+VuPc4QlSwAXlQmkQcG1tGPqnJZiDWej9uyW5bquMfxw4oIs3yYsv6j4JQTBokPONVl3tXuiZXX/MAyETJuiuqbNm6S6rEyYU/hsYhnFETlH58ccxssC99Ra1+ZpG7b6m0fpbb4VdMiZsmpuBm24CbrsNGDMGeOopYOZM4Pe/p8/nz9cFUHOz/dxxUX0IDB0zIwkA12IhPosn7OeeFYKemb17gWnTgMsvJyu2dEWePr3oQT3VAvfAxcup/1JVRW17VRWtL1+uf2HNGrTVT0ICpvmHBwwAnniCQqJiCAs4N7S1AUuWALNmQSyheDczcpTRVsA1NACdnbgWi/BZPIF/TFmEZLYT29DgSpiVUsBJS3MoLpQAXd8pU9A6bTl+gDn48NblRrdVpvz46ledY+46Ovy7GZctI18uNc6wtpa2M/5x1lnA4sXGbYsX03amIunRg5YbNsRIwK1eTRYW2fnWNFovNn6KKQ+mTwcuuQS4+26yMM2aRSJu5Ejgxhup7yJzJdjFydlNVB42M2YAffpYftSRqMFP0B1XePrptMxmSQiZ2/NEAvj1ryk+UnVFvvpqyi1RBOm07oF51rKv0eCzGnd94ADwta/pX5gwAc0fP3Awhu8g771n7y4aA1jAOdEtLrB8OTBnDvbfRfFuViIOyCPgsllg0aKDN/+zp0/HH89YhASyjo2ZEOXnQmmwwHUnR9g0hKwnnZ+xSI7AlBfLljnf0IkEcOSR7o63fj0webIhVhWTJ+sxK2HFGVYaEyaQm4wUcYsX0zpbOiuWQw6hpZrEJPKeiG1twPnn6zG1qRSt86AiA9B98MgjumXp1FMpJm7oUBL7554LnH02cO+9tL/Z20TGa0WV44/PtRz27QuccCIA8hTFY4/pn23caNxXCrr9+4EHHiBL3BNP0HLJEuD++4sqnmqB+6D/ibTy7LO04dlnaf3EE/UvrFmD99LHUAyc/C80jTrWX/gCcPvtRZUnLFjAOWHKvPbu8RTvNhrW4kIKuF/9CvjnP/Xtr/9kNe7opWdEWr0a+MHO6TgHziN6Mm6gnFwoDTFw3XEzhvgIjpspb7ot0rajF4kExae5rVinTqUKefJk8r+fPNmYXYpjs4Jh+nRg4UISbaedRsuFC3OzwTEVg/SC7ujQ27LIW+CWLjXG1K5cSeucTZW56ipqX2bOBF55Bbj0UmqrjjuOD9Ne/gAAIABJREFURNykSRTwuW8f3TPDhunflZ0tIaKbQOuqq4Dnnsu1HO7Ygeo3XjqYcT1vDN/GjcCoUfr6vfdSu3zvvZSZ0s4q6RI1Bu7BKx+iuDq1zVm0CHjoIf0LiQQO73wbGaRIWPbpQ2XQtFi3TSzgnDB1/N59l5KW3Azrjl86DbzwAiUpuvJKffvFFwPf+pa+/tBDuoHJKZa11G4nobtQdhObAHemeOTUCaecYv25186SzHbY1UX+911dxmyITHBMn25Mvx7jBpIpHtm+dHTEyIXSKaaWqWwyGRL2y5cDX/863dDr1tG0NHffrd/gnZ0UN5nNUqKwjg5aZrPASy+F+hPyomaIPOywg29FOo3lmII/jpmd//vjx9P1kAld1HZ59WrgH/8oqniqBS6ZhHOb078/BBJIoIumF9i5k8RbMumLS2dYsIDziJw6wo50Wo9fXbdO366+NyOT+dghhU6pLXCGB6LE5CQxge5CHYQFMHLYzTcY04rFEenSaDdNgBDAb3/r3mVpwQJynZAje0LQerlevyizeLEx5sEcE8dUFHIqqP37Y+RCyRZ7xo7bbycR1tmph9jcdBPd1PfeSyMWXV3UsZKmIk0DNm0iK9SmTdTJyWSczxUGt9+udzZHjdIzbQJIdOxHw6wWjHl0brcfpQ1r1+qdvAsuMLbLPqAKuEQCrtqcLi1NEXC7dulTCWSzlMX6iSd8KVfQVGJXuSh27crdpk6BkU7TNFNm8t23Tz+d/5xBCbigXSjZAqdgMd8gpkwp38nMZQfJPJnnUUfp7w8ccG+Fe+IJ4Npr6eadNYuW114b24o5tsiYt4UL6dpLd0oWcRWLTGKyb1+MXCgZJh833UTL7szkAMhqlc3STV5bSzf+nDk0gtGvH7Vnc+fScs0avcMVRY49lsTbunX0+1atAsaOJdHWndDPMflHZydZ737xC2OGyIkTgU99qqjiqUlMRra5aHP+9S+khNLhlB3ybJYqo/79iypPWLCA84g0GPzkJxTn9vDDFMsqUZOYuBUiMoOlHUELuFDmgUOFCziL+QbV2MuyJZuliT9ramji002bSMRpGmUudOuyJJOVmEf6yn3i3aixZo0x5k3GxPF8e8ERMWt+LCfyZhg7pLdHKkU398KFwA03UNKSIUPoJj/1VHLhb2sjoXPoocaMplH2DlmwgOJ/3n6bRNeSJSSG+vUDPviAYv/mzHE+TnU17Z/JABddRN+56CJSXkVaCaqq9P7qgNdctDlf/SrNFwfoLgGSIUNyk7DEBFfVqKZpZwL4KYAkgDuEEDeZPr8ewMXKMYcDaBBCbNc07S0AuwFkAHQJIWyCXuLBK6/Qcto0w0TvB1FFllvBZWXVUym1gDPHwIUyDxwqXMABxvkGZ80qf/EGUCzcggUUJ3DbbboLxLRpwMCB7l2WevWiijmToetXXU3rbiYCZ/zDKs369OkcBxck69cDP/qRHsMlM7LKhD4BU11NfdZ9+2LkQskwdqRSusVn505qbwByxfr732kg8vHHKUX9iy9SEpNXXyWxN2sWJdi49lqa6DqKLrnq75s+nRJ+XHcdDaguXEiJWnbuNHZMOzvpoZaduFmzgJ/+lLYffTS17S++SG37pElFT2KeTuunevy7q3HFFaYdzG3OsmXIIIUEuqCZLYevvEJCM4Y4dtU1TUsC+DmAiQA+AeBCTdM+oe4jhLhZCDFSCDESwEwAfxFCqL5Rzd2fx1q8AbrYsRJvgFFkuWmkPvlJ+zAgSbla4MzPcEXHwAGG+QaxpIImM1+7lir4CRPo/YQJtL52rftjjBxJS+lXcdC/YqS/ZWWYqOOUkTVgNI28yfbuZRdKpgzo6iIxI8VYjx40WHjnnfT+zDOBE06gbHYjRhgtb+rSp3gw3+nq0oXa7Nm0XLiQOmgnn6wPMgO6eBswwBjTJzO3ApT5b8QIas9HjCDL2IcfFlVE2WcFXPZXR46E0DTzLHA6n/50UeUJCzdd5TEA/i2EeFMIcQDAUgDn5dn/QgD3+VG4KJLJ5B/U9yLgvvc9YMwYZ/FfjgKOLXAmTPMNHnSnrAQRt3UrNWqPP04WuDVrqIf373+7dzMZOjTXJ3///uimamaYUhHBjKw9ehgtcCzgmNgyYwa1V3v30uu664DPf55i2+rrybr2wgu6iHvlFWDcOBJAc+fSsqUld+LrqDBjBlmvpFBraaH166+nuRB/+lM9zryzkyZ63LhRT2oi49uam2lKgkyGrsOAAbTcuxf46leLKqIq4NwO+CdEF2wl8+GHF1WesHDz0/sDUB1EN3Vvy0HTtFoAZwL4g7JZAHhM07R1mqZdafW9SGOKJ8hkgM9m7eMJvAi4dJpuxJ078yckuvVWWr77rttCeyMMF0qOgTNhmm/wYExcJUxmfthhemO2dq1unn3zTfdJXH7yk9wbJ5mk7QwTFFGKP/M581sx1NYaY+Aqso5nygf5TFVXk3Xqscfo/ebN1vv/7W96G5fNUoZlNftdlFiwgGLeVG+gxYv1uRGlBVH+nu3byaohU7S/+qp+rOOO09/7GGfm1dMNTzyBBIS1Ba6pKbYxcG666la/2a5FOBfAX03uk6cKIT4JcsH8D03TTrM8iaZdqWnaM5qmPbNt2zYXxQoIU3bAwRvb8Ks99tkB1RvLaZQxlaLJ7QHrzJUSmYivVPkYkkkSbexCGSKVnLb6yCONgcXyxvjCF9xbDfr3pxEA+dClUrQe0+xSTEyJQjZZGfOmZn6bPDlUa760wLELJRN72tpIsE2apHecOjvp5pYJDY44gqxN0iolBLn1jx9Pyz177MVe2MgYOJmsZOZMWn/3XXKLvOYassypGaPVDmxTk/5+zRqy4KntcktL0UmtPLtQnnYaMlrKWri89BLF28cQN13lTQDUoYKjANjdeVNhcp8UQmzuXm4FsALkkpmDEOIXQohThBCnNDQ0uChWQLS30w3cnR3wiken4JbambaWEauRATvrWjoNHHMMvc8XB6fe+6VCzeoTuAtl96h1JqOIt3KeA60cKcbyMHVq7k2XTntLfHHiiXQTd3XRyKach+fEE90fg2GKJQrZZJcupVHyFSuoA7ZiBa27nZKjBPToQf0kdqFkYk97O/DNbwIPPKDf0IkEvZcdmC1baKlOHJxO6/OjARQiEEXsYuBO67a9SMvc++8DjY3G7w4cSBNlS66/HrjrLuoEjx9Py7vuou1FUIgLJYSNBQ4AHnqoqPKEhZuf3g5giKZpgzRNqwKJtAfMO2ma1hvAZwGsUrbVaZrWU74H8AUAL/pR8MAYPZpu4IkTgblz8eJRE/GdffNcWeCkpXnvXutDp1L6vZ4vE+U3vkHLyy7zWHYPqAIucBfK7lHrY95so358uc+BVo4UY3mQrhny4UkmaUTT69xhNTUUd7BxIy3N6YIZJgjUbLItLcHHng0ebIx5kzFxbqfkKAHbt5O3CbtQMrFnxgwSIlVVegIPOZ+YnbuybNMAWtbU6IIoirz22sE+L1paKHnJ2rXAuefqcfrf/CaJOJW336YkZJLFi6ljqc7Rtm9f0fOCenah/Ne/oCn2N4NNZfhwfa6TmOHYVRdCdAH4NoBHAbwCYLkQ4iVN06ZpmjZN2fV8AI8JIfYo2xoBPKlp2nMAngbwsBDij/4VPwCam8kCd889wPjx+NS/78HP6mfaNsrqjSUbq48/tj50Ok0ZWgFgxw59++7dxsQm0lJdSpfp6uoQXSi7R60vXDkFP8xW0Bxo5USxlodslh6YSy8F6uqogVuzxr3b1+DBwMUXU6ri8eNpefHFoXZamQol7GyyEXTH/sQnKMcDu1AyZcETT9ANPWgQDRgOGkTtl5WAGzcud1syGVpWWEdGjwbuvZf6vJdeSklLzj2X2uM5c/S6Zd06fbRfdk4TCWDZMv1YmYz1HG35kj64wLMFTpkHLgMSPgf/qd69dStJzHBlaxFCrBZCHC+EGCyE+FH3ttuEELcp+/xGCDHV9L03hRAndb+a5HdjxVVX0U17ySXA2rV46thL8H93z6HtFlgJuD17LHdFKkV9VQB45x19+5AhgOpFKmPDNFv7b/EUZJIugnSa6rqDiZiam/G3k1rw/UxIo9ZM8RRjeRCCKvbf/pb87KuqaCTPbRKXVIqmHlBH+m67jXuKTLBUcjbZPFRVUegPu1AyZcGePdRR2rCBxMuGDfb7PvUU7avOQSVEqC7NjiSTZJX6wx/owd27l+aWVMMaEgk9o+Y779DSEAcDmhfUHAoxfbr1fKEe8BwDt2wZst1yJ4nuxB6ynH//e2wrpEpMF+Gdri5g1Spg1iycvHEVkuiy3VUVcNLCJC1bVvvK7KXqgITZKi0HdUoprDw/EEUin5fOThzMevTp55ZgfpWS9Yhj4OJFoZaHwYOBr32N3DQAEn4rV1JyE7esWWM90ldksDTDeCIK2WTPOivXRWnxYtoeEtXVNKsHu1AyZUFdHYmXRMKYwVCOsstEHocdRsuuLnoIZs3SZ7aPKjffDPzgB9SG7t1LAm7ChNy2dMcOEm0yTfqtt9K66k5WIjy7UAIQWuKg1U0A9P9pGjB2bGz7CfGUnUEydaoeFA4A0JDR7M3fqpCXAs48PVVVFVnf3cbABZGdUZ2YPKgkJkB3vdad9eixUxfiphen43sz+1DWo4ULS18Qxh9Uy0NzM73culHOmJH7fQC4/35ad4PViN706d4SoTBMsVi5KcrnISgmTKD6E6D7f/Hi0OvTHj2MAi6mA94MQ7zxBi3Nc7kJQaPyL79MYmbgQOA3v6GYspUr9bpg8uSgS+weOd9bZydZ4bq69AFSFXW6AIkUcyVGFXBuXSiTTz8NAMhCw0EpJwRlC33wQf8LGQBcjTrR3k4PXlsbMHcuHvnELDy4uxl3tbdbNspqwyQbK7OAk6TTepbZsAVc0C6U8jp1deFg1qMz/nMe/lPbCcxbQpWFeaI4Jrrkszy46byqMXQtLWTB4zhIhvGOHLS47jpqu5580midDoGaGmoHOQaOKQs+9SlyjTTTsyfw3nsUh62KmdGjjW3jypXRneN16VJ6WA8coNChBx4gA8Z//id5yUSgTVbrD28ulAJJiIOWOA0gF9gI/KZCYBdKJ+SIardr2Bn/XkICxyYgXL2xMhkS+K2txn2kS2Q6TTdfXR3lXLAjaAEXuAvljBnA9Ol4oqkF1+3rjp+aPr0y5kArF4pNnCDdZdUYOnU7wzDumT4d+MxnKHPcZz4TuiVazgPHLpRMWTBihLUb5O7dJN6efFJ3Y45gUiFHNI0s+XffTfPd1dR4i0kvMZ4tcACEplveNCgTXG/cGNsYZRZwTpiC0heOXo5Fm+yD0tUbC6D5Hn/4Q3194EBdwEkR09FB2VftKEcBp7pQAgDa2nDaS0uwuC6kzG1hUswcauXC6NHkVnLLLRQncMsttM5TSTCMNxYsAK6+mjqRsjN59dWh1idmCxwLOCbWbN5snXFy+HA9idZ11xWdLj8UBg8Gvv51cpscP56yUV50Eb2PiOj0bIFraEBSZCAAwwuaBhxyCMX9xRAWcE6YXMOeO6QZ3xtoH5Rudg158039/dNPk7utaoEDaIDUChlDF0QWSjUGLnAXym6RvKR5ORb3qcDMbcXMoRYV/BChmqY/HEJEO9CbYaLK/ffTINi0adSZnDaN1u+/P7Qi9ehBA5WyTWMXSibWbN2qd5R69dK3y5iYOCfRkhmdJ0wgC/6ECZHL6KwWxVV/df16ALrl7WDPQgiywKlz18UIFnBOmMzfmQzwbB9787f5HlfDuA45BKivz7XA9e1rnalSTgBe9lkou0Xyy4c107nDyNwWJsXOoRYFihWh7e002fB3vkMulN/5Dq1Xyj3AMH7x6qtUwd57L9Un995L61ZJBwKipoaWsk1jCxwTa3bvppH1SZMogcGkSfp2iQ/p8kNhzRp93rfx443rEcGzBe6005DV9A60wXY6dmxs8y2wgPNINpv/hjG7UB6crBp6I2a2wMn4ADOysSvHJCYGF8pukWy4tlH3EfebYuZQiwLFilBTrCmWLDFuZxjGHbNnU8W6bx/VJzL4bPbs0IrUowctP/6YlizgmFizbRuJtlWraH3VKlrfti3ccvnBhg2UuES1wD3wQP657gKmkGkEVNV20AqnacCJJ8a2n8ECziPmeQrNmC1wqoCTbopmC5xMsWwmSAEny6ZpwXiuyd8+fTqw7XpyvzNc20qLASt0DrUoUYwI5QmQmXIgCvGs06fT8ycbn85OPTFUSMjBy3nzaBkhbyyG8c62bbp4k6xaVR4CTvL442SBe/zxsEuSg2cXyieeQALGKR8EQJ3xzZv9LFqgsIDzSCaTX/G//rpxXbXMqnFmgG71ipIFLqiRUSkSH3oIuOM5cr8burmNzh/HGLBiKBfxUowIjcIEyAxTLFGIZ21rI7dJWZknk7QeYn0iLXAS1eODYZgIMXiw/n7tWuvtIePZhVLhYAITyZo18etrdcMCzgnTiGomA5yy235E1SzEVGuWudGKooALwn0SMLqKH/1+OzBzJr771BR8Z3u3+93MmZXTeW9vB770JX1dipelS+NjhSxWhMYx1TLDmIlCPOvSpTSHUyZDI+iZDK0vXRpcGUxIC5wkqHaGYRiP9O+f+8DW1ND2iODZAqdgSGICAA0N8eprKXA16oRpRPXED9vww1fsR1RVl0mAJrKX5BNw+/fnZqU1C7hSujYGbYFTrZGv9hwNzJuHfzZOxNUfzAUmTiRfm0qxwM2YAUydmit47r8/PtegWAvaWWflplxevJi2M0ycCDue9d13qUFZtIiyUC5aROvvvhtsORTM/UGGYSKMnO/Dbj1kPMfA9eplsLoZutp1dTRVwh/+4E/hAoQFnBOmEdUbX52C/z7BfkRVxrKNG0fLjg79M7MAk6JJNm7mODj53SBj4IIScBdcQJoFANb1agZmzsRpG+/ButrueUdmzoxfIo9iiMLIfTEUa0GbMME4b87ixbQe0/S+TAUTdjxrNkuiTca8TZ9O69ls/u+VENWF8tlnQysGwzBOPPIIWSJUF+zOTtoeEQqZB07tfhu64uvXk7WkocGfwgUICzg3KCOq9ze24MUG+061bCObmmi5Z4/9YVULHGAv4KRlLggLXFCuLTU1wH33UQbXpq1twLx5+HP/SzBq71rgkkvIAhdTv+SCCXvkPkzkvDnXXQecdhotFy4MNfECw3gmCvGsq1fnPjchpzRXLXAjR4ZWDIZhnNi+nZaqC7a6PQIUOg+cJZ2dVEFde62+LSZJ9FjAObFgAVkDukdUv/T+Enzp7cW2f+6MGeQ2eeaZtO5FwJnj4FQLXKkzQwYt4CTpNHDcDoqBG7X1EdxxxCwa6amkGDhJ2CP3YTN9Os1qv3YtLVm8MXGDk/FYwi6UDBMTpCUhmaS2WJq4rFKlh4RnC9yHH+b/XD1IjJLosYBzIpUia8DMmcCcOfjVYTPxzVevs82D/KlPkWg7+mhazyfg1HnggFwBJ7/rNPecH0gXyqAFXCoFvFRLMXA/Omk57ji6e9S6kmLggGiM3BeDH+nTFy8GnnySRv2efDI3Jo5hog4n47FEti9Dh4ZbDoZhHJCdQGl5k8sIZR7ybIEzpcEV5s8PHKB4+5iFr0TnH4kqXV3kyjVvHjB7Nr7+/jz8ummh48ztcsSxEAucvCG/8Q1aOs095weyLEHHqqbTwPEf0aj1s32a6XdW2qj1ggWUBclcaXzpS/G5BsWmT5cxbwsXUuIF6U7JIo6JE1GYBy6ChNW+MAzjkT59vG0PAc9JTEzWkRyHts5O4NBDYxe+wgLOiRkz9IlR587FskNasHrodMcRVSnKpICzCj8wJzGR95j5hgzCAifLYs6iWWpSKeA3DTRqbZhjr5JGrUePpsQtMrpfip84DVe3kxusIQmLFzfYNWuMMW8yJm7NmtKVmWH8JgrzwEUQaYE7cCDccjAM44A6x5Ob7SHg2QKXr2ObSJAifP/92IWvWPsBMjoLFtDd0h2b9NX/WYLaf/cBFnTlFRhmAXfUUfpnvXsDu3bZJzGRSX8k2WxwFjgHw6LvpNP6OZ0mSS9bmptp5Oe664B//UuPAZw3j6xycWD9erIinnce/ZZLLwVuvFFPNeqE1QjH9OkcB8fECzWbbEsLtRsxcccpJVLAqVmZGYaJIHaxbnGOgcvHEUdQjFxDA4WvNDfHxo2SLXBOmGLgbus7E5c+bx8DJ5FWtY8/pqV6ky1fDnzlK/o+di6UkiAEnGxgg3ZxSaV0sRqEpTGSyLnOLrkEuPtuYPhwsmIde2zkK5CDTJ1KN88991AM2z330LpbAccw5YB0lVSzyarbK5TGRuDLXwb+93/DLgnDMHHHs4DLZ4GT82aedBKtxyiEhy1wTqgxcDt3Ytr2JfjdyQtxiYOpymyBU2+yL3yBXuZ9pYAzT+gdpAUujBg41QIXoTjZ4JBzoPXoQeJn7Vra/tWvhlsur6RSdCOtXUsjAg6DHAYWLCA3M1WwtrVRJVoprrRM/PnDH2jwpaaG3HFuuYXu7ZNOquj7OJlk8cYwsSCdthY8auBZyHh2oTRnCLRC7Xg3N8di8LwSu8veMMXA3dOzBY+NcI6BkxYtKwucGbsslJIgBVzQqBa4inWhPPlkugn27gX+9rewS1MY7e3UcZU3aiJB625HsdavByZPNsYOTZ6cf/4Whokao0aRn6B0N9q/n9ZHjQq3XAzDMG6IQRITzxY4OUGzHXV1QP/+RZUpDFjAuUGZn+vi3Uto4mkHEgkScVYWODPmBCJyIKC+npZBulAGjWqBC+J3RpL2dnK3SqXoYowfDyxaRAIoJsG0GD2aYt6qqsjyUFVF626TN0ydSpMdTp5Mv3vyZFpnF0wmTgwcSIN9HR30THd00PrAgWGXjGEYxhlTyn3H7SGgGgN96TNedhlw++0+HChYKrG77A3T/FzT+i7H1X9xNz9XVRXw3nv0Pp+AkzejzNBlnnYjyGkEgoZj4EDW3NZWXbw9+SRtf/DBWPhhA6AEJpoGrFhBgcArVtD60qXuvt/cTN/p6qKOb1cXrcfAjYFhDjJjBgU4yyHiVIrWK9h9kmGYGLFxo/5+1izr7SHj2QLX0GD/maaRgeacc4ouV9CwgHPi5pspgUl3R3JtqhmPjJxJ2x1QM255scBJi5T8fpDTCARNMqkL1oq1wC1eTFkYFy0yzoH27LPx6fgNHmwUXFKQDR7s7TjS/GwOBGWYONDWRh2BTIYGYzIZWo+LJZ1hmMpGtr2trTQY29pq3B4BPAu4Qw81rBp+idY9K1wMwzUqsbvsjeuvpwQm3Q3w2H1tmPivebTdgZEj9fduLXBC6M+JXC/nGDhN039vxQq4cpgDbcaMXGuZl7n8ZMyb6oKpxsQxTBxYvJiCmdUJ6fft4wnpGYaJB/Pnk2hTB2NbW2l7RFD7ia76jB9+mP/zujrgtNOKKlMYcBZKJ0zz+tyxewl+NWk5vuPCtUtOEwC4t8BJa1RVFQm4TKa8Y+BYwIHnQAOMLpgyA9T559N2dqNk4kImkzsYA8RrMIZhmMrFatA1wlkZXVngtm07+PZNDMQgvKV/NmgQ8MtfxidcRaESu8veaW4+mIXyV1UtePMYdzey6j6cT5ioFjgp4Gpr9W1BWuCCjkFLJFjAMSD/+tmzjaN+s2dHyu+eYRxZvTp34GX6dOtBGoZhGKYovPQZp2MRBmMDbkWLvnHXLlrGJVxFgbvLblCyUH6jYwmGbnbn1qVmXXXjQtnZqce/hSXgevYs7XnMaJqe4ZUFXAUzYABlrVSnEbjxRtrOMAzDMAxjwpXRYeJErJ28CD/BdNyGq3Ax7sXaphb8qWoi3v3xcgrXuOqqkpfVb7i77IQpC+UlVctx2cPuslC6daFMJkm4qBY4mbG1oyNYF8qgBRS7UDIAeBoBhmEYhmE84arPuHo1nvuc6hmhYcGGr2DCgdV46CHoiUxiBneXnWhvJ/HW7drVhmb87rzlrvxl1WkznEYJqqqMMXDyu1LUsQslU9bwNAIMwzAMw3jArfaS+03D7fj/7d1/lGRlfefx97drenqAlSEKKD9GB5UQfyGGGSDosDQLLrA6aE5oUVlzPBp22rhrNq5zyI8ZjsPJ2ZV4XHUxTdxsjFk3wXYNMMfIRsAGJtHIgPJjEEkGM5whowERBBnmV9ezf9y6dE1PT1dVT1Xdvrffr3PqVNVTt7qesp7xPB++z3PvO7mBL+wc4eOs570bR7K5RgmvA+dJTFqZti52chIefeUwrO3sJCatgsng4Ox74HodrPJlnEVU4FxCqRd4GQFJktRFzUHvjhjmjxllfbqab/7yOs4r6X8odrrcoU7CVHMFrtVp+vMK3MH2wPW6wpv//X5Xkl1CKcDLCEiSpJ76GhdzbfoQ/yGNsYF1nPm9MfjQh+Dii4vuWsecLncgv0ZbuyHjUCpwzXvg9u6dqpD1Sr4H7pWv7O3nTGeAE7D/ZQQ2bMjuI7J2SZKkOcqLE9tYzihjjHMpV7GBLa+5NDtJ4fLlhfZvLlxC2YE8XLVbgWsOcK3Mtgdu3779rzzfC0cfDV/9av+vZegeOAHwqlftv+ct3xNXwmuzSJKk3hkbg2ef7fx9y9nG1wZWM1q/jjewhTPu+VtYvRq2bet6H3vNANeBTgNcJ2HkYHvgtm7NAlyvK3AAv/qrvf+M6dwDJ6B0Fw+VJEnFWLOms+PzCtwn+RhfSSM8wOs5h038+Ng38LJvfSs7WWHJOF3uQKcBrhOLF+8f4PIlje99b38qcEVxCaUkSZJ6bSWb+c7A2ZzKAzzKMl76+ANw9tmlXO3jdLkDeaWoFyFjcDBbQjnTZ+zdW90A5xJKSZIk9UpegXsF27h4ciN3czqvYDs/Ov502LixlEsonS53IA8avThT4/QK3NKlU6/1awllEVxCKUmSpF5bzjZuHlzN6XyXO1nFcTu+W9o9cE6XW7nmmheg98CJAAAcL0lEQVROZZ4HuJc/MpG1d9H0CtzKldn9qlUuoZQkSZLmIi+8PMYy3rz3dr7E5ZzDJh580+Vw++2wbFmh/ZsLp8utrFwJIyMwMUFKcC4TvO1/j0wlrC7JK3B5gKvV4Mwzs7NRVnkJpQFOkiRJvRbAIiZZzU1sYB2vfuimqaVvJeN0uZXh4ezsNCMjDP3BesYZ4a/fN971s+PlFbh8HA0MTLVVuQLnHjhJkiT1Sl6B+0rtMvZFjSzKkd3XanDZZUV1bc4qGgu6bHgYRkdZcvXVXMM6jvzF7p/afPFieOqp/StwixZl4a3KwSb/R5VStb+nJEmSivPR9Id8+kVXEc88zXquZtNZ61j19qPgD/+wdJctMsC1Y2ICxsZ4/r+sY/STY9y5dRjoTQWu+SyUg4Owa1cWbnpx4pT5wAAnSZKkXsnnmp8Z/BjXP/sOEsEG1rH225+F7ya48cZiOzgHTpdbmZjI9sCNj7Pzyg2MMM7FfzbywolNumX6WSibl1BWOcDlgc0AJ0mSpF65dPJ6FqVJINu7k0jZxPv664vt2Bw4XW5l8+ZsD9zwMCnB7Qxz8/vHu37Rv+kVuFota9uzp9oBLv9e9boBTpIkSd2VzzUjYDIWsZFLWM/VPPTqS0p7koly9rqf1q594WF+so0dpwzDh9tbQnnTTfDP/9z6uOlnoRwYgKEh2L07e1z1AGcFTpIkSd2WzzW31V7FxsPew+XPXMedrGLVg1+C0TWwfHmh/ZsLp8sdmMuFvFevhtHR1sctXnzgWSjzALcQKnAGOEmSJPXKZCziPc9cxy2czzls4gfLzofrritlFc7pcgfmEuDalS+XnKkCV+UAlwc2l1BKkiSp2/I59GDs4y+XruECbuVOVnHK9lthzZrslO8l43S5A70McNMrcLXawghwzXvgwAAnSZKk7rt/aCUX/fwrfInLOYdN3HXy5fCVr8DKlUV3rWNOlzvQzwpcrQZLllQ/wOWBrXnpqCRJktQN+Rz6vz0zyvcOO5uLuJkNrON122+Gs89ub6/TPON0uQP9rMAtlCWU+ffKq9cGOEmSJHXbt4bO47yfb2ScS7mKDdz18kth40Y477yiu9axtqbLEXFhRDwcEVsj4soZXj83In4WEfc2buvbfW+ZfP/72X2vKnD1ehbiYGoJ5eRkFm6qGmzy/y2twEmSJKnb8rnmsvo2Jl60mlGu4w7OYfgfrsvONrhtW6H9m4uW0+WIqAGfAy4CXgu8OyJeO8Ohm1JKpzVuGzp8bylccEF236sKHMCuXdl9HuDytqpW4FxCKUmSpF778aJlrHzuDh7g9ZzDJh5b+nq44w5YtqzornWsnenyGcDWlNIPU0p7gOuBS9r8+4fy3vnhmmtgYmK/puMfnsjau2hwMLvPA1y+hDJvq2qAcwmlJEmSeqX5Qt5D9Z2cygM8yjKW/ewB2Lmz2M7NUTvT5ROA7U3PH2u0TfcrEXFfRNwcEa/r8L3z18qVMDLyQog7lwnO++ORrp+xJq/APf98dr9QKnAuoZQkSVKvTUaNQfayjxqvYDt1atnepVqt6K51rJ3p8kzRIU17/l3gFSmlNwL/A7ixg/dmB0ZcERF3R8TdTzzxRBvd6pPhYRgfh5ERPs56xhlhYnQ8a++i6RW45gC3e3d1A5xLKCVJktQrL+yB27eNO5auZhHZpHOAyerugSOrmjUvDj0R2NF8QErpmZTSzxuPvw4MRsTR7by36W98PqW0IqW04phjjungK/TB8DCMjrKeqxljlH95TXfDGxy4B655CSVUN8C5hFKSJEm99uPBZZzx7G3sIptg7x0Ygttuq+weuM3AyRFxUkQsBi4DNjYfEBEvi8im4hFxRuPvPtnOe0thYgLGxtjAOkYZ47gfTLR+T4dmqsDt3j31etUDnBU4SZIkdVs+1zx23w4Oqz/HJDU2sI5JavDcc7BjxtrSvNZyupxS2gd8GPgb4CFgPKX0YESsiYg1jcN+DdgSEfcBnwUuS5kZ39uLL9IzExPZHrjxca5iAyOMc+7YyAEnNjlUM+2Be9nLpl6vaoBzCaUkSZJ67YnFx/N8HM4+sqpJfWAQDj8cjj++4J51blE7BzWWRX59Wtt1TY+vBa5t972lsnlztgeuseftdoa58zfHeevmzV3dBzdTBS4PdVDdAOcSSkmSJPVKPtd82d7t/OlJV/PTHz7Neq5mw751/MKyo/iP228ttoNz0FaAW9DWrj2g6fHXDcPl3d0HN9MeuIUU4KzASZIkqdvyueaPB5fxgW3r2d1YQvmf+AyL/mkSLnhvsR2cA6fLc9CLMJVX4JqXUC6EAJcHtuuvz+6r+j0lSZJUnG1Dp7CkvvOFs1AuYpLD2QmnnFJwzzpngJuDXoSMPKzlJy5ZaBW4T34yu//Od4rriyRJkqoln2v+ys9v5c+WrCFIrOdqgsQYa+DW8i2hNMDNQS8rcHmAi5hq69VnzgfTv1e9Xkw/JEmSVF1ffOnH+NXdf8EA2YkXBtjHe/kL+NjHCu5Z5wxwc9DLCtyePVOfsahph2JVA9z0PW+1WjH9kCRJUvXkc+gLn7qexWkXQ+zlTlYxxF6G2DW1j6dEDHCtXHPNAZcMeOn3J7L2LpqpArcQAtz071XV7ylJkqTiHLtvB0Ps4RbO5xw2cQvnM8Seal4HbsFbuTK7DlwjxJ3LBL/y6ZGsvYsWagWuqt9LkiRJxcvnmgNpko28nQu4lTtZxQXcykbePnUq9BIxwLUyPJxdB25khI+znnFG+Pv/PN7Va8DBwt0DN30JZVW/pyRJkopTHxhgNRv3q8CtZmMpr2FVvh4XYXgYRkdZz9WMMcpP3tDd8AYHnoVyoVbgqvo9JUmS1H/53PIngyewmyVcwC08d/oqLuAW9g0sgRNOKLaDc2CAa8fEBIyNsYF1jDLGsQ9OtH5Ph6ZX4AYGDHCSJElSt0wywB6GOOKeTeyNISZLGoXK2et+mpjI9sCNj3MVGxhhnDM/NXLAiU0O1ULdA+cSSkmSJPVKPrc8+fl7qVEnkbKGlBigDvfeW1zn5sgA18rmzdkeuMaet9sZ5q6PjmftXZQHuEceye4Xyh646d/rJS8pph+SJEmqrtte/C6WsIsh9vDc6asYZA+L67vgXe8qumsdW9T6kAVu7doDmp48dRje0ZuTmOQWSgVu+vf6rd8qph+SJEmqnnyuef5Pv8wulhAkjrhnE7tjCAiGvvxl+O3fLrSPnbICNwe9vJB382cshAA3fQnl0UcX0w9JkiRV19YjTmOS2n5LKOsDNTjttGI7NgcGuDnoRZiq1Q78jOZwU9UAV9XvJUmSpOI1zzVr7GOIvbBqFYPsZaC+r7iOHQIDXCvXXHPACUuOfmAia++iCDjzzP2fN1fhqhp0qvq9JEmSVLx8rnnOT29giN3cwvmwaRN3HXk+i9NuuOGGYjs4Bwa4VlauhJER6rdlIe5cJjj9mpGsvcu2bJl6nFff8spcVYNOCa+dKEmSpJL5/ovOJIALuAVWreKMZ27JXmiuoJSE0+dWhodhfJy4bISPs55xRvjelVNnpeym556bepwHtjzgVDXAVfV7SZIkqXj5XPPJxcdTHxwiADZtIoA9MQTHH19g7+bGANeO4WEmf2OU9VzNGKP89I3dD2/TGeAkSZKk7nj1c/dSqwXRmFzXGQDC68BV1sQEtf85xgbWMcoYL7m/uxfxzr397VOPF0qAkyRJknoln0M/vfgY2LUL6nVYtowB6ixOu+CYY4rt4BwY4FqZmICREXZ9cZyr2MAI47zpv44ccGKTbnj/+6ceG+AkSZKk7li658nsQa0G27czSeNEE08+WVyn5sgA18rmzTA+zt63ZMsmb2eY+35vPGvvsuZLCSyUAJdS0T2QJElSVeVz6FfuvB+WL4fJSQBqTLJjcDncf39hfZurRa0PWeDWrgWg/vRU01OnDcNbu78PbqYAV/WzUEqSJEm9tmvgCA7fti2rjtTr1Bng+L3b4CiXUFZP4zpwjbAOwIvv6/514GD/AJdX3qpegZMkSZJ6JZ9D76ktyR7U63DkkQxQz54vWVJMxw6BAa6VxnXgandOXQfu1D/ozXXgXEIpSZIkdd/i+q6pJ888M/V4164DD57nDHCtNK4Dd+RvTF0Hbsu63lwHrjnA5aoe4CRJkqReyefQR+49yMlKPIlJRQ0Ps/N9U9eB+9kv9+Y6cAY4SZIkqfvqzDDRhpkn4POcAa6Viy+GD32Iw784dR24X/z0h7L2Lptp/OTBraoBrnkJ5Qc/WFw/JEmSVD35HHoRe2c+YO/enpzbopcMcK1s2QJjY+x826VcxQbGuZTjN45l7V22EANcs+XLi+6BJEmSqmjyYBU4gGuv7V9HusDLCLRy6qmwfTtH/PkYd7CFt7Bpqr3LFnqA+/CHi+6BJEmSquSFuTSznDnv2Wf705kusQLXyjnnwOho9pBNBLDjktGsvcsWcoB75zth6dKieyFJkqQqyefQdfafTJd5am2Aa+WRR+ALX9iv6WVf/0LW3mWexESSJEnqvohZYs+RR/avI11ggGvl/vtfuD7EoywDYGDvrqy9yxZigPM6cJIkSeqVfK757KKjDn7Q44/3pzNdYoBr5aGHsvuBGq9gO/vyDZB5exfNFOC2bs3ud+7s+sdJkiRJlZYHuCWTs0ymS3YxbwNcOwYGoD4JwCImqc9Wgj0Es12G4tvf7slHSpIkSZWVB7jdtSOK7UgXGeBaec1roF7fr2kg1bP2LpstwC1e3PWPmxfyf1RVXSIqSZKk4rww16Q++4ElYoBr5emnO2s/BLMFuKGhrn+cJEmSVGl5gPv1i54otiNdZIBr5cknO2s/BLMFuMMO6/rHSZIkSZVWxdVeBrhWDnZhvx5c8G+2ADfba2VWxX9UkiRJmh+qONc0wLWyZEln7YdgIQa4XJX+UUmSJGl+MMAtRIODnbUfgqqHtJl4HThJkiT1SqsA98JUtEQJzwDXyhlndNZ+CBZygBtwJEqSJKlH2spnF1/c8350g9PmeWS2AFfVSlUVy9qSJEmaHzqaa958c0/70i0GuFYeeACANJClq73U9mvvpoVYgTv66Ox++fJCuyFJkqQKmi3AlbV+YIBrJSUYHCQdfgQbWMdOjqBeG+xJSWwhVuDOPx9uuAE2bCi6J5IkSaqag82h8+b9QlxJJtwGuFYuuggOO4x/vvZGrmID7+RG6ksOy9q7bCFW4ADe8Q5YvLjoXkiSJKlqqrhdxwDXyqteBTfeyHNnDANwO8Ns2XBj1t5lC7ECJ0mSJPVFvnenIdF0FkqAT32qn72ZMwNcK2vXwvDwfk1Pv2k4a+8yz8QoSZIkdc9+Zzx/4on9XqsDN7F6quGjH+1bvw6FkaFNzRWwXlXDZivtWoGTJEmSOnPAEspGFa4OLCLxTm6C1atnfO98tajoDpSFAUqSJEkqlwPm8I0q3KLmwslNN/WtP91gBa5Nt9029biIMGeAlCRJkubGk5gsQB/5SNE9kCRJktSJKhZB2gpwEXFhRDwcEVsj4soZXn9vRNzfuH0rIt7Y9Nq2iHggIu6NiLu72fmiWIGTJEmSyqNKFbiWe+AiogZ8DrgAeAzYHBEbU0rfbzrsn4B/nVJ6KiIuAj4PnNn0+nBK6Sdd7LckSZIkzepg14E75RR4+OH+96cb2qnAnQFsTSn9MKW0B7geuKT5gJTSt1JKTzWe/j1wYne7KStwkiRJUmcOFuA2bux/X7qlnQB3ArC96fljjbaD+QBwc9PzBHwjIu6JiCs67+L8U0QJ1gAnSZIkdeZgc+jDDutvP7qpncsIzBRXZvyfIiKGyQLcW5qa35xS2hERxwK3RMQPUkp3zvDeK4ArAF7+8pe30a1inHIKnHtu0b2QJEmS1K7pBZiBEp/KsZ2uPwYsa3p+IrBj+kERcSrwJ8AlKaUn8/aU0o7G/ePADWRLMg+QUvp8SmlFSmnFMccc0/436LNPfAJqtf5/rhU4SZIkqTMHm0MXMZ/vlnYC3Gbg5Ig4KSIWA5cB+60ajYiXA38F/PuU0j80tR8RES/KHwNvBbZ0q/NFKOoMNgY4SZIkaW4WVAUupbQP+DDwN8BDwHhK6cGIWBMRaxqHrQdeAvzRtMsFvBT424i4D7gL+OuU0v/r+rfoo34HuC9/Obs3wEmSJEndUeYA184eOFJKXwe+Pq3tuqbHHwQ+OMP7fgi8cXp7mfU7wOXlXQOcJEmS1JmDnYWyzEso2wpwmtLrAPd3fwfPP3/g5xngJEmSpM4cLMBVvgKnKb0OcGefPfPnGeAkSZKkzizUk5ioyaOP9vfzDHCSJEnSoalSBa7EXS/Gzp39/TwDnCRJkjQ3B5tDG+DUM3mAq9eL7YckSZJUVtMrcEVdGqwbDHCSJEmSKqmKJzEpcdeL0e+ljPngcgmlJEmS1JmDBTgrcOoZ98BJkiRJc3OwObQBTj1jgJMkSZIOjRU49c1xx2X3b3hDsf2QJEmSyqaKFTgv5N2hflfC3vQm+Pa3YcWK/n6uJEmSVBVVqsAZ4NrQHNqKOJ3/WWf1/zMlSZKksqviNiSXULah+YefnCyuH5IkSZLa9573wAUXwO///sGPKVvIswLXoTKXWyVJkqSFZOlS+MY3Zj+mXodarT/96QYrcG0oWyqXJEmS1J4itkgdCgNcG5oDnBU4SZIkqToMcBXUHOCsxkmSJEnVYYCroObQdtRRxfVDkiRJUncZ4CrIJZSSJElSNRngKs4AJ0mSJFXHffcV3YPOGODa4L43SZIkqZp+8pOie9AZA1wbDHCSJElSNS0q2ZWxDXBtcA+cJEmSVC2f+Ux2f9JJxfajUwa4NliBkyRJkqrluOOK7sHcGODaYICTJEmSqqlsc30DXBvK9qNKkiRJml2+Napsc30DXIfcAydJkiSVnwGuwsr2o0qSJEmanQGuwsr2o0qSJEmanQGuwsr2o0qSJEmanQGuwrwOnCRJklQtZZ3XG+DaULZULkmSJKk9ZZvrG+AkSZIkLTguoaywsv2okiRJkmZngKsw98BJkiRJ1WKAq7Cy/aiSJEmSZmeAq7Cy/aiSJEmSZmeAq7Cy/aiSJEmSZlfWrVEGuA6V9YeWJEmSdKCyFWsMcG0o248qSZIkaXYuoaywsv2okiRJkmZngKuwsv2okiRJkmZngFsg3AMnSZIklZ8BrsKaf9ShoeL6IUmSJKk7DHAVlv+oJ50E73pXsX2RJEmSdOjKurLOANeB3/1dqNWK7oUkSZKkbrECV0Fl+1ElSZIkzc4llAtAWcuskiRJkvZngKuwsv2okiRJkmZngKuw/Ee1AidJkiRVgwFuATDASZIkSdVggKuwsv2okiRJkmZX1uJMWwEuIi6MiIcjYmtEXDnD6xERn228fn9E/HK77y2Tsv7IkiRJkmZWtmJNywAXETXgc8BFwGuBd0fEa6cddhFwcuN2BTDWwXvnvbL9qJIkSZJmV+UllGcAW1NKP0wp7QGuBy6ZdswlwJ+nzN8DR0XEcW2+tzSswEmSJEnVUOUAdwKwven5Y422do5p573zXtl+VEmSJEmzq3KAm6nuNP1rHuyYdt6b/YGIKyLi7oi4+4knnmijW/0zOAi/9EuwdGnRPZEkSZLUDYcfns3xDz+86J50ZlEbxzwGLGt6fiKwo81jFrfxXgBSSp8HPg+wYsWKeZWDly2Dhx4quheSJEmSuuW008o5x2+nArcZODkiToqIxcBlwMZpx2wE3tc4G+VZwM9SSj9q872SJEmSpDa0rMCllPZFxIeBvwFqwJ+mlB6MiDWN168Dvg5cDGwFdgLvn+29PfkmkiRJklRxkebhrr0VK1aku+++u+huSJIkSVIhIuKelNKK6e1tXchbkiRJklQ8A5wkSZIklYQBTpIkSZJKwgAnSZIkSSVhgJMkSZKkkjDASZIkSVJJGOAkSZIkqSQMcJIkSZJUEgY4SZIkSSoJA5wkSZIklYQBTpIkSZJKwgAnSZIkSSVhgJMkSZKkkjDASZIkSVJJGOAkSZIkqSQMcJIkSZJUEgY4SZIkSSoJA5wkSZIklYQBTpIkSZJKwgAnSZIkSSURKaWi+3CAiHgCeLTofszgaOAnRXdClec4U7841tQvjjX1i2NN/dKPsfaKlNIx0xvnZYCbryLi7pTSiqL7oWpznKlfHGvqF8ea+sWxpn4pcqy5hFKSJEmSSsIAJ0mSJEklYYDrzOeL7oAWBMeZ+sWxpn5xrKlfHGvql8LGmnvgJEmSJKkkrMBJkiRJUkkY4NoQERdGxMMRsTUiriy6PyqHiPjTiHg8IrY0tb04Im6JiH9s3P9C02u/0xhjD0fEv21qPz0iHmi89tmIiEb7UER8udH+nYhY3s/vp/khIpZFxEREPBQRD0bERxrtjjV1VUQsiYi7IuK+xlj7eKPdsaaeiIhaRHwvIr7WeO5YU9dFxLbGGLk3Iu5utM3rsWaAayEiasDngIuA1wLvjojXFtsrlcSfARdOa7sSuC2ldDJwW+M5jTF1GfC6xnv+qDH2AMaAK4CTG7f8b34AeCql9GrgvwOf6Nk30Xy2D/hoSuk1wFnAbzbGk2NN3bYbOC+l9EbgNODCiDgLx5p65yPAQ03PHWvqleGU0mlNlwWY12PNANfaGcDWlNIPU0p7gOuBSwruk0ogpXQn8NNpzZcAX2w8/iLwjqb261NKu1NK/wRsBc6IiOOAI1NK307ZhtU/n/ae/G/9X+Df5P+1RwtHSulHKaXvNh4/SzbZOQHHmrosZX7eeDrYuCUca+qBiDgR+HfAnzQ1O9bUL/N6rBngWjsB2N70/LFGmzQXL00p/QiyiTdwbKP9YOPshMbj6e37vSeltA/4GfCSnvVc815jWcabgO/gWFMPNJa03Qs8DtySUnKsqVc+DawF6k1tjjX1QgK+ERH3RMQVjbZ5PdYWHcqbF4iZErKn7lS3HWyczTb+HJt6QUT8K+CrwG+llJ6Z5T/uOdY0ZymlSeC0iDgKuCEiXj/L4Y41zUlEvA14PKV0T0Sc285bZmhzrKldb04p7YiIY4FbIuIHsxw7L8aaFbjWHgOWNT0/EdhRUF9Ufv/SKLPTuH+80X6wcfZY4/H09v3eExGLgKUcuGRTC0BEDJKFt/+TUvqrRrNjTT2TUnoauJ1sj4djTd32ZmB1RGwj27pyXkR8CceaeiCltKNx/zhwA9n2qXk91gxwrW0GTo6IkyJiMdnGxY0F90nltRH49cbjXwduamq/rHGmopPINr/e1SjbPxsRZzXWS79v2nvyv/VrwDeTF3ZccBrj4n8BD6WUPtX0kmNNXRURxzQqb0TEYcD5wA9wrKnLUkq/k1I6MaW0nGze9c2U0uU41tRlEXFERLwofwy8FdjCfB9rKSVvLW7AxcA/AI8Av1d0f7yV4wb8JfAjYC/Zf335ANma59uAf2zcv7jp+N9rjLGHgYua2lc0/s/kEeBaIBrtS4CvkG2gvQt4ZdHf2Vsh4+wtZEsx7gfubdwudqx56/YNOBX4XmOsbQHWN9oda956dgPOBb7WeOxY89bt8fVK4L7G7cF8nj/fx1r+hyVJkiRJ85xLKCVJkiSpJAxwkiRJklQSBjhJkiRJKgkDnCRJkiSVhAFOkiRJkkrCACdJkiRJJWGAkyRJkqSSMMBJkiRJUkn8f74yuMkcwYjNAAAAAElFTkSuQmCC\n", |
|
"text/plain": [ |
|
"<Figure size 1080x720 with 1 Axes>" |
|
] |
|
}, |
|
"metadata": { |
|
"needs_background": "light" |
|
}, |
|
"output_type": "display_data" |
|
} |
|
], |
|
"source": [ |
|
"xaxis = range(0, len(target2))\n", |
|
"plot.figure(figsize=(15,10))\n", |
|
"plot.plot(xaxis, scaled_target2, 'b', xaxis, model2.predict(scaled_data2.reshape(*np.shape(scaled_data2), 1)), 'rx')\n", |
|
"plot.legend(['TARGET OBD Speed','PREDICTED OBD Speed'])" |
|
] |
|
}, |
|
{ |
|
"cell_type": "markdown", |
|
"metadata": {}, |
|
"source": [ |
|
"Ab hier Überbleibsel von vorherigem Test, schien mir aber keine wirklich neuen Erkenntnisse zu liefern und wurde daher mit anderer Architektur nicht weiter verfolgt.\n", |
|
"\n", |
|
"---\n", |
|
"\n", |
|
"Wie auch Regression Trees scheinen unbekannte Geschwindigkeiten starke Probleme zu machen, von daher nochmal (vgl. anderes Notebook)" |
|
] |
|
}, |
|
{ |
|
"cell_type": "code", |
|
"execution_count": 35, |
|
"metadata": {}, |
|
"outputs": [], |
|
"source": [ |
|
"model3 = tf.keras.Sequential([\n", |
|
" layers.Lambda(lambda x: x, batch_input_shape = (1, np.shape(data)[1], 1)),\n", |
|
" layers.LSTM(128, stateful = True),\n", |
|
" layers.Reshape((1, 128)),\n", |
|
" layers.LSTM(64, stateful = True),\n", |
|
" layers.Dense(1)\n", |
|
"])\n", |
|
"\n", |
|
"model3.compile(optimizer = tf.keras.optimizers.Adam(0.001),\n", |
|
" loss = 'mse',\n", |
|
" metrics = ['mae'])" |
|
] |
|
}, |
|
{ |
|
"cell_type": "code", |
|
"execution_count": 36, |
|
"metadata": {}, |
|
"outputs": [ |
|
{ |
|
"name": "stdout", |
|
"output_type": "stream", |
|
"text": [ |
|
"Train on 49135 samples\n", |
|
"Epoch 1/10\n", |
|
"49135/49135 [==============================] - 1888s 38ms/sample - loss: 0.0782 - mae: 0.2148\n", |
|
"Epoch 2/10\n", |
|
"49135/49135 [==============================] - 1858s 38ms/sample - loss: 0.0248 - mae: 0.1156\n", |
|
"Epoch 3/10\n", |
|
"49135/49135 [==============================] - 1853s 38ms/sample - loss: 0.0158 - mae: 0.0902\n", |
|
"Epoch 4/10\n", |
|
"49135/49135 [==============================] - 1849s 38ms/sample - loss: 0.0118 - mae: 0.0762\n", |
|
"Epoch 5/10\n", |
|
"49135/49135 [==============================] - 1917s 39ms/sample - loss: 0.0090 - mae: 0.0650\n", |
|
"Epoch 6/10\n", |
|
"49135/49135 [==============================] - 2046s 42ms/sample - loss: 0.0074 - mae: 0.0580\n", |
|
"Epoch 7/10\n", |
|
"49135/49135 [==============================] - 2023s 41ms/sample - loss: 0.0071 - mae: 0.0556\n", |
|
"Epoch 8/10\n", |
|
"49135/49135 [==============================] - 1841s 37ms/sample - loss: 0.0058 - mae: 0.0501\n", |
|
"Epoch 9/10\n", |
|
"49135/49135 [==============================] - 1982s 40ms/sample - loss: 0.0053 - mae: 0.0477\n", |
|
"Epoch 10/10\n", |
|
"49135/49135 [==============================] - 1960s 40ms/sample - loss: 0.0051 - mae: 0.0456\n" |
|
] |
|
}, |
|
{ |
|
"data": { |
|
"text/plain": [ |
|
"<tensorflow.python.keras.callbacks.History at 0x7fa219b94df0>" |
|
] |
|
}, |
|
"execution_count": 36, |
|
"metadata": {}, |
|
"output_type": "execute_result" |
|
} |
|
], |
|
"source": [ |
|
"model3.fit(np.array(scaled_data2).reshape(*np.shape(scaled_data2), 1), np.array(scaled_target2).reshape(len(scaled_data2), 1),\n", |
|
" epochs = 10, batch_size = 1)" |
|
] |
|
}, |
|
{ |
|
"cell_type": "code", |
|
"execution_count": 37, |
|
"metadata": {}, |
|
"outputs": [], |
|
"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)" |
|
] |
|
}, |
|
{ |
|
"cell_type": "code", |
|
"execution_count": 38, |
|
"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": 39, |
|
"metadata": {}, |
|
"outputs": [], |
|
"source": [ |
|
"data3 = imp.transform(data3)" |
|
] |
|
}, |
|
{ |
|
"cell_type": "code", |
|
"execution_count": 40, |
|
"metadata": {}, |
|
"outputs": [], |
|
"source": [ |
|
"scaled_data3 = scaler.transform(data3)\n", |
|
"scaled_target3 = np.multiply(target3, 0.01)" |
|
] |
|
}, |
|
{ |
|
"cell_type": "code", |
|
"execution_count": 41, |
|
"metadata": {}, |
|
"outputs": [ |
|
{ |
|
"data": { |
|
"text/plain": [ |
|
"<matplotlib.legend.Legend at 0x7fa21db42ac0>" |
|
] |
|
}, |
|
"execution_count": 41, |
|
"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": [ |
|
"xaxis = range(0, len(target3))\n", |
|
"plot.figure(figsize=(15,10))\n", |
|
"plot.plot(xaxis, scaled_target3, 'b', xaxis, model3.predict(scaled_data3.reshape(*np.shape(scaled_data3), 1)), 'rx')\n", |
|
"plot.legend(['TARGET OBD Speed','PREDICTED OBD Speed'])" |
|
] |
|
}, |
|
{ |
|
"cell_type": "code", |
|
"execution_count": 42, |
|
"metadata": {}, |
|
"outputs": [ |
|
{ |
|
"name": "stdout", |
|
"output_type": "stream", |
|
"text": [ |
|
"RMSE = 26.72 km/h\n", |
|
"NRMSE = 6.82 %\n", |
|
"MAE = 22.02 km/h\n", |
|
"MAP = 21.77 %\n", |
|
"SMAPE = 20.89 %\n", |
|
"MSD = -5.56 km/h\n", |
|
"CORR = 0.70\n", |
|
"ACC_A = 24.34 %\n", |
|
"ACC_R = 24.88 %\n", |
|
"MAD = 19.98 km/h\n" |
|
] |
|
} |
|
], |
|
"source": [ |
|
"ta = target3\n", |
|
"pr = np.squeeze(np.multiply(model3.predict(scaled_data3.reshape(*np.shape(scaled_data3), 1)), 100))\n", |
|
"RMSE = np.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": 44, |
|
"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" |
|
] |
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} |
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], |
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"source": [ |
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"ta = target3\n", |
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"pr = [d['hr_traficSpeed'] for d in reader_data3] #t['hr_traficSpeed']\n", |
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"pr = np.array([float(d) if d != '' else 0.0 for d in pr])\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)" |
|
] |
|
}, |
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{ |
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"cell_type": "code", |
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"execution_count": null, |
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"metadata": {}, |
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"outputs": [], |
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"source": [] |
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} |
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], |
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"metadata": { |
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"kernelspec": { |
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"display_name": "Python 3", |
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"language": "python", |
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"name": "python3" |
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}, |
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"language_info": { |
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"codemirror_mode": { |
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"name": "ipython", |
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"version": 3 |
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}, |
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"file_extension": ".py", |
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"mimetype": "text/x-python", |
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"name": "python", |
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"nbconvert_exporter": "python", |
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"pygments_lexer": "ipython3", |
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"version": "3.8.0" |
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"nbformat": 4, |
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"nbformat_minor": 2 |
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