You can not select more than 25 topics
Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
257 lines
8.1 KiB
257 lines
8.1 KiB
3 years ago
|
function compareTimings(statusBefore, statusAfter)
|
||
|
|
% COMPARETIMINGS compare timing of matlab2tikz test suite runs
|
||
|
|
%
|
||
|
|
% This function plots some analysis plots of the timings of different test
|
||
|
|
% cases. When the test suite is run repeatedly, the median statistics are
|
||
|
|
% reported as well as the individual runs.
|
||
|
|
%
|
||
|
|
% Usage:
|
||
|
|
% COMPARETIMINGS(statusBefore, statusAfter)
|
||
|
|
%
|
||
|
|
% Parameters:
|
||
|
|
% - statusBefore and statusAfter are expected to be
|
||
|
|
% N x R cell arrays, each cell contains a status of a test case
|
||
|
|
% where there are N test cases, repeated R times each.
|
||
|
|
%
|
||
|
|
% You can build such cells, e.g. with the following snippet.
|
||
|
|
%
|
||
|
|
% suite = @ACID
|
||
|
|
% N = numel(suite(0)); % number of test cases
|
||
|
|
% R = 10; % number of repetitions of each test case
|
||
|
|
%
|
||
|
|
% statusBefore = cell(N, R);
|
||
|
|
% for r = 1:R
|
||
|
|
% statusBefore(:, r) = testHeadless;
|
||
|
|
% end
|
||
|
|
%
|
||
|
|
% % now check out the after commit
|
||
|
|
%
|
||
|
|
% statusAfter = cell(N, R);
|
||
|
|
% for r = 1:R
|
||
|
|
% statusAfter(:, r) = testHeadless;
|
||
|
|
% end
|
||
|
|
%
|
||
|
|
% compareTimings(statusBefore, statusAfter)
|
||
|
|
%
|
||
|
|
% See also: testHeadless
|
||
|
|
|
||
|
|
%% Extract timing information
|
||
|
|
time_cf = extract(statusBefore, statusAfter, @(s) s.tikzStage.cleanfigure_time);
|
||
|
|
time_m2t = extract(statusBefore, statusAfter, @(s) s.tikzStage.m2t_time);
|
||
|
|
%% Construct plots
|
||
|
|
hax(1) = subplot(3,2,1);
|
||
|
|
histograms(time_cf, 'cleanfigure');
|
||
|
|
legend('show')
|
||
|
|
|
||
|
|
hax(2) = subplot(3,2,3);
|
||
|
|
histograms(time_m2t, 'matlab2tikz');
|
||
|
|
legend('show')
|
||
|
|
linkaxes(hax([1 2]),'x');
|
||
|
|
|
||
|
|
hax(3) = subplot(3,2,5);
|
||
|
|
histogramSpeedup('cleanfigure', time_cf, 'matlab2tikz', time_m2t);
|
||
|
|
legend('show');
|
||
|
|
|
||
|
|
hax(4) = subplot(3,2,2);
|
||
|
|
plotByTestCase(time_cf, 'cleanfigure');
|
||
|
|
legend('show')
|
||
|
|
|
||
|
|
hax(5) = subplot(3,2,4);
|
||
|
|
plotByTestCase(time_m2t, 'matlab2tikz');
|
||
|
|
legend('show')
|
||
|
|
|
||
|
|
hax(6) = subplot(3,2,6);
|
||
|
|
plotSpeedup('cleanfigure', time_cf, 'matlab2tikz', time_m2t);
|
||
|
|
legend('show');
|
||
|
|
|
||
|
|
linkaxes(hax([4 5 6]), 'x');
|
||
|
|
|
||
|
|
% ------------------------------------------------------------------------------
|
||
|
|
end
|
||
|
|
%% Data processing
|
||
|
|
function timing = extract(statusBefore, statusAfter, func)
|
||
|
|
otherwiseNaN = {'ErrorHandler', @(varargin) NaN};
|
||
|
|
|
||
|
|
timing.before = cellfun(func, statusBefore, otherwiseNaN{:});
|
||
|
|
timing.after = cellfun(func, statusAfter, otherwiseNaN{:});
|
||
|
|
end
|
||
|
|
function [names,timings] = splitNameTiming(vararginAsCell)
|
||
|
|
names = vararginAsCell(1:2:end-1);
|
||
|
|
timings = vararginAsCell(2:2:end);
|
||
|
|
end
|
||
|
|
|
||
|
|
%% Plot subfunctions
|
||
|
|
function [h] = histograms(timing, name)
|
||
|
|
% plot histogram of time measurements
|
||
|
|
colors = colorscheme;
|
||
|
|
histostyle = {'DisplayStyle', 'bar',...
|
||
|
|
'Normalization','pdf',...
|
||
|
|
'EdgeColor','none',...
|
||
|
|
'BinWidth',0.025};
|
||
|
|
|
||
|
|
hold on;
|
||
|
|
h{1} = myHistogram(timing.before, histostyle{:}, ...
|
||
|
|
'FaceColor', colors.before, ...
|
||
|
|
'DisplayName', 'Before');
|
||
|
|
h{2} = myHistogram(timing.after , histostyle{:}, ...
|
||
|
|
'FaceColor', colors.after,...
|
||
|
|
'DisplayName', 'After');
|
||
|
|
|
||
|
|
xlabel(sprintf('%s runtime [s]',name))
|
||
|
|
ylabel('Empirical PDF');
|
||
|
|
end
|
||
|
|
function [h] = histogramSpeedup(varargin)
|
||
|
|
% plot histogram of observed speedup
|
||
|
|
histostyle = {'DisplayStyle', 'bar',...
|
||
|
|
'Normalization','pdf',...
|
||
|
|
'EdgeColor','none'};
|
||
|
|
|
||
|
|
[names,timings] = splitNameTiming(varargin);
|
||
|
|
nData = numel(timings);
|
||
|
|
h = cell(nData, 1);
|
||
|
|
minTime = NaN; maxTime = NaN;
|
||
|
|
for iData = 1:nData
|
||
|
|
name = names{iData};
|
||
|
|
timing = timings{iData};
|
||
|
|
|
||
|
|
hold on;
|
||
|
|
speedup = computeSpeedup(timing);
|
||
|
|
color = colorOptionsOfName(name, 'FaceColor');
|
||
|
|
|
||
|
|
h{iData} = myHistogram(speedup, histostyle{:}, color{:},...
|
||
|
|
'DisplayName', name);
|
||
|
|
|
||
|
|
[minTime, maxTime] = minAndMax(speedup, minTime, maxTime);
|
||
|
|
end
|
||
|
|
xlabel('Speedup')
|
||
|
|
ylabel('Empirical PDF');
|
||
|
|
set(gca,'XScale','log', 'XLim', [minTime, maxTime].*[0.9 1.1]);
|
||
|
|
end
|
||
|
|
function [h] = plotByTestCase(timing, name)
|
||
|
|
% plot all time measurements per test case
|
||
|
|
colors = colorscheme;
|
||
|
|
hold on;
|
||
|
|
if size(timing.before, 2) > 1
|
||
|
|
h{3} = plot(timing.before, '.',...
|
||
|
|
'Color', colors.before, 'HandleVisibility', 'off');
|
||
|
|
h{4} = plot(timing.after, '.',...
|
||
|
|
'Color', colors.after, 'HandleVisibility', 'off');
|
||
|
|
end
|
||
|
|
h{1} = plot(median(timing.before, 2), '-',...
|
||
|
|
'LineWidth', 2, ...
|
||
|
|
'Color', colors.before, ...
|
||
|
|
'DisplayName', 'Before');
|
||
|
|
h{2} = plot(median(timing.after, 2), '-',...
|
||
|
|
'LineWidth', 2, ...
|
||
|
|
'Color', colors.after,...
|
||
|
|
'DisplayName', 'After');
|
||
|
|
|
||
|
|
ylabel(sprintf('%s runtime [s]', name));
|
||
|
|
set(gca,'YScale','log')
|
||
|
|
end
|
||
|
|
function [h] = plotSpeedup(varargin)
|
||
|
|
% plot speed up per test case
|
||
|
|
[names, timings] = splitNameTiming(varargin);
|
||
|
|
|
||
|
|
nDatasets = numel(names);
|
||
|
|
minTime = NaN;
|
||
|
|
maxTime = NaN;
|
||
|
|
h = cell(nDatasets, 1);
|
||
|
|
for iData = 1:nDatasets
|
||
|
|
name = names{iData};
|
||
|
|
timing = timings{iData};
|
||
|
|
color = colorOptionsOfName(name);
|
||
|
|
|
||
|
|
hold on
|
||
|
|
[speedup, medSpeedup] = computeSpeedup(timing);
|
||
|
|
if size(speedup, 2) > 1
|
||
|
|
plot(speedup, '.', color{:}, 'HandleVisibility','off');
|
||
|
|
end
|
||
|
|
h{iData} = plot(medSpeedup, color{:}, 'DisplayName', name, ...
|
||
|
|
'LineWidth', 2);
|
||
|
|
|
||
|
|
[minTime, maxTime] = minAndMax(speedup, minTime, maxTime);
|
||
|
|
end
|
||
|
|
|
||
|
|
nTests = size(speedup, 1);
|
||
|
|
plot([-nTests nTests*2], ones(2,1), 'k','HandleVisibility','off');
|
||
|
|
|
||
|
|
legend('show', 'Location','NorthWest')
|
||
|
|
set(gca,'YScale','log','YLim', [minTime, maxTime].*[0.9 1.1], ...
|
||
|
|
'XLim', [0 nTests+1])
|
||
|
|
xlabel('Test case');
|
||
|
|
ylabel('Speed-up (t_{before}/t_{after})');
|
||
|
|
end
|
||
|
|
|
||
|
|
%% Histogram wrapper
|
||
|
|
function [h] = myHistogram(data, varargin)
|
||
|
|
% this is a very crude wrapper that mimics Histogram in R2014a and older
|
||
|
|
if ~isempty(which('histogram'))
|
||
|
|
h = histogram(data, varargin{:});
|
||
|
|
else % no "histogram" available
|
||
|
|
options = struct(varargin{:});
|
||
|
|
|
||
|
|
minData = min(data(:));
|
||
|
|
maxData = max(data(:));
|
||
|
|
if isfield(options, 'BinWidth')
|
||
|
|
numBins = ceil((maxData-minData)/options.BinWidth);
|
||
|
|
elseif isfield(options, 'NumBins')
|
||
|
|
numBins = options.NumBins;
|
||
|
|
else
|
||
|
|
numBins = 10;
|
||
|
|
end
|
||
|
|
[counts, bins] = hist(data(:), numBins);
|
||
|
|
if isfield(options,'Normalization') && strcmp(options.Normalization,'pdf')
|
||
|
|
binWidth = mean(diff(bins));
|
||
|
|
counts = counts./sum(counts)/binWidth;
|
||
|
|
end
|
||
|
|
h = bar(bins, counts, 1);
|
||
|
|
|
||
|
|
% transfer properties as well
|
||
|
|
names = fieldnames(options);
|
||
|
|
for iName = 1:numel(names)
|
||
|
|
option = names{iName};
|
||
|
|
if isprop(h, option)
|
||
|
|
set(h, option, options.(option));
|
||
|
|
end
|
||
|
|
end
|
||
|
|
set(allchild(h),'FaceAlpha', 0.75); % only supported with OpenGL renderer
|
||
|
|
% but this should look a bit similar with matlab2tikz then...
|
||
|
|
end
|
||
|
|
end
|
||
|
|
|
||
|
|
%% Calculations
|
||
|
|
function [speedup, medSpeedup] = computeSpeedup(timing)
|
||
|
|
% computes the timing speedup (and median speedup)
|
||
|
|
dRep = 2; % dimension containing the repeated tests
|
||
|
|
speedup = timing.before ./ timing.after;
|
||
|
|
medSpeedup = median(timing.before, dRep) ./ median(timing.after, dRep);
|
||
|
|
end
|
||
|
|
function [minTime, maxTime] = minAndMax(speedup, minTime, maxTime)
|
||
|
|
% calculates the minimum/maximum time in an array and peviously
|
||
|
|
% computed min/max times
|
||
|
|
minTime = min([minTime; speedup(:)]);
|
||
|
|
maxTime = min([maxTime; speedup(:)]);
|
||
|
|
end
|
||
|
|
%% Color scheme
|
||
|
|
function colors = colorscheme()
|
||
|
|
% defines the color scheme
|
||
|
|
colors.matlab2tikz = [161 19 46]/255;
|
||
|
|
colors.cleanfigure = [ 0 113 188]/255;
|
||
|
|
colors.before = [236 176 31]/255;
|
||
|
|
colors.after = [118 171 47]/255;
|
||
|
|
end
|
||
|
|
function color = colorOptionsOfName(name, keyword)
|
||
|
|
% returns a cell array with a keyword (default: 'Color') and a named color
|
||
|
|
% if it exists in the colorscheme
|
||
|
|
if ~exist('keyword','var') || isempty(keyword)
|
||
|
|
keyword = 'Color';
|
||
|
|
end
|
||
|
|
colors = colorscheme;
|
||
|
|
if isfield(colors,name)
|
||
|
|
color = {keyword, colors.(name)};
|
||
|
|
else
|
||
|
|
color = {};
|
||
|
|
end
|
||
|
|
end
|