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Whitney O'Meara
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Added matlab scripts for plotting benchmark results
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‎geowave-benchmark/src/main/resources/matlab/FeatureCollectionDataAdapterBenchmark/compare/plotQueryTimes.m‎

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function plotQueryTimes(plotTitle, pointsPerTile, rastFeatQueryTimes, rastCollQueryTimes, rastMinTimes, rastMaxTimes, rastStanDev, vecFeatQueryTimes, vecCollQueryTimes, vecMinTimes, vecMaxTimes, vecStanDev)
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for i=1:size(rastCollQueryTimes, 2)
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myFig = figure;
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semilogx(pointsPerTile, ones(size(pointsPerTile))*rastFeatQueryTimes(i)/1000, 'r--') % feature data - raster
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hold on;
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semilogx(pointsPerTile, ones(size(pointsPerTile))*vecFeatQueryTimes(i)/1000, 'b--') %feature data - vector
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xlim([pointsPerTile(1)*0.8 pointsPerTile(end)*1.2])
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text(pointsPerTile(1), rastFeatQueryTimes(i)/1000, sprintf('%.2f', rastFeatQueryTimes(i)/1000))
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text(pointsPerTile(1), vecFeatQueryTimes(i)/1000, sprintf('%.2f', vecFeatQueryTimes(i)/1000))
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semilogx(pointsPerTile, rastCollQueryTimes(:,i)./1000, 'rx-')
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semilogx(pointsPerTile, vecCollQueryTimes(:,i)./1000, 'bx-')
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% now plot error bars
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for j=1:size(pointsPerTile, 2)
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semilogx([pointsPerTile(j) pointsPerTile(j)], [(rastCollQueryTimes(j,i)-rastStanDev(j,i))/1000 (rastCollQueryTimes(j,i)+rastStanDev(j,i))/1000], 'm+-')
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semilogx([pointsPerTile(j) pointsPerTile(j)], [(vecCollQueryTimes(j,i)-vecStanDev(j,i))/1000 (vecCollQueryTimes(j,i)+vecStanDev(j,i))/1000], 'c+-')
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end
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title(sprintf('%s - Query %d', plotTitle, i))
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ylabel('Time in Seconds')
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xlabel('Points Per Tile')
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legend('FeatureData (Raster)', 'FeatureData (Vector)', 'FeatureCollectionData (Raster)', 'FeatureCollectionData (Vector)')
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for j=1:size(pointsPerTile, 2)
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text(pointsPerTile(j), rastCollQueryTimes(j,i)/1000, sprintf('[%.0f, %.2f]', pointsPerTile(j), rastCollQueryTimes(j,i)/1000))
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text(pointsPerTile(j), vecCollQueryTimes(j,i)/1000, sprintf('[%.0f, %.2f]', pointsPerTile(j), vecCollQueryTimes(j,i)/1000))
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end
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hold off;
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saveas(myFig, sprintf('%s - Query %d', plotTitle, i), 'png');
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end
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end

‎geowave-benchmark/src/main/resources/matlab/FeatureCollectionDataAdapterBenchmark/compare/plotResults.m‎

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function plotResults(pointsPerColl, pointsPerTile, numQueries, numRuns)
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rasterSmall = load('./raster/smallQueryRuntimes.txt');
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rasterMed = load('./raster/medQueryRuntimes.txt');
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rasterLarge = load('./raster/largeQueryRuntimes.txt');
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vectorSmall = load('./vector/smallQueryRuntimes.txt');
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vectorMed = load('./vector/medQueryRuntimes.txt');
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vectorLarge = load('./vector/largeQueryRuntimes.txt');
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rasterSmallQueryRuntimes = reshape(rasterSmall, [numQueries(1), size(pointsPerTile, 2)+1, numRuns]);
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rasterMedQueryRuntimes = reshape(rasterMed, [numQueries(2), size(pointsPerTile, 2)+1, numRuns]);
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rasterLargeQueryRuntimes = reshape(rasterLarge, [numQueries(3), size(pointsPerTile, 2)+1, numRuns]);
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vectorSmallQueryRuntimes = reshape(vectorSmall, [numQueries(1), size(pointsPerTile, 2)+1, numRuns]);
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vectorMedQueryRuntimes = reshape(vectorMed, [numQueries(2), size(pointsPerTile, 2)+1, numRuns]);
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vectorLargeQueryRuntimes = reshape(vectorLarge, [numQueries(3), size(pointsPerTile, 2)+1, numRuns]);
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rasterFeatSmallQueryTimes = mean(rasterSmallQueryRuntimes(:, 1, :), 3);
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rasterFeatMedQueryTimes = mean(rasterMedQueryRuntimes(:, 1, :), 3);
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rasterFeatLargeQueryTimes = mean(rasterLargeQueryRuntimes(:, 1, :), 3);
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vectorFeatSmallQueryTimes = mean(vectorSmallQueryRuntimes(:, 1, :), 3);
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vectorFeatMedQueryTimes = mean(vectorMedQueryRuntimes(:, 1, :), 3);
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vectorFeatLargeQueryTimes = mean(vectorLargeQueryRuntimes(:, 1, :), 3);
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rasterCollSmallQueryTimes = mean(rasterSmallQueryRuntimes(:, 2:end, :), 3);
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rasterCollMedQueryTimes = mean(rasterMedQueryRuntimes(:, 2:end, :), 3);
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rasterCollLargeQueryTimes = mean(rasterLargeQueryRuntimes(:, 2:end, :), 3);
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vectorCollSmallQueryTimes = mean(vectorSmallQueryRuntimes(:, 2:end, :), 3);
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vectorCollMedQueryTimes = mean(vectorMedQueryRuntimes(:, 2:end, :), 3);
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vectorCollLargeQueryTimes = mean(vectorLargeQueryRuntimes(:, 2:end, :), 3);
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% Plot query times
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plotQueryTimes('Small Query Times',
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pointsPerTile,
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rasterFeatSmallQueryTimes, rasterCollSmallQueryTimes', min(rasterSmallQueryRuntimes(:, 2:end, :), [], 3)', max(rasterSmallQueryRuntimes(:, 2:end, :), [], 3)', std(rasterSmallQueryRuntimes(:, 2:end, :), 0, 3)',
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vectorFeatSmallQueryTimes, vectorCollSmallQueryTimes', min(vectorSmallQueryRuntimes(:, 2:end, :), [], 3)', max(vectorSmallQueryRuntimes(:, 2:end, :), [], 3)', std(vectorSmallQueryRuntimes(:, 2:end, :), 0, 3)')
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plotQueryTimes('Medium Query Times',
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pointsPerTile,
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rasterFeatMedQueryTimes, rasterCollMedQueryTimes', min(rasterMedQueryRuntimes(:, 2:end, :), [], 3)', max(rasterMedQueryRuntimes(:, 2:end, :), [], 3)', std(rasterMedQueryRuntimes(:, 2:end, :), 0, 3)',
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vectorFeatMedQueryTimes, vectorCollMedQueryTimes', min(vectorMedQueryRuntimes(:, 2:end, :), [], 3)', max(vectorMedQueryRuntimes(:, 2:end, :), [], 3)', std(vectorMedQueryRuntimes(:, 2:end, :), 0, 3)')
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plotQueryTimes('Large Query Times',
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pointsPerTile,
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rasterFeatLargeQueryTimes, rasterCollLargeQueryTimes', min(rasterLargeQueryRuntimes(:, 2:end, :), [], 3)', max(rasterLargeQueryRuntimes(:, 2:end, :), [], 3)', std(rasterLargeQueryRuntimes(:, 2:end, :), 0, 3)',
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vectorFeatLargeQueryTimes, vectorCollLargeQueryTimes', min(vectorLargeQueryRuntimes(:, 2:end, :), [], 3)', max(vectorLargeQueryRuntimes(:, 2:end, :), [], 3)', std(vectorLargeQueryRuntimes(:, 2:end, :), 0, 3)')
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end

‎geowave-benchmark/src/main/resources/matlab/FeatureCollectionDataAdapterBenchmark/histogram/loadHistograms.m‎

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% use this code to load all of the histograms in the directory
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function [hists, featsPerQuery, runtimes] = loadHistograms(loadFullData)
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global tileSizes;
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if nargin < 1
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loadFullData = false;
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end
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% load the number of features returned for each query
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featsPerQuery = load('large-results.txt');
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% load the runtimes
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load('largeQueryRuntimes.txt');
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largeQueryRuntimes = reshape(largeQueryRuntimes, [size(featsPerQuery, 1), size(tileSizes, 1)+1, 10]);
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runtimes = mean(largeQueryRuntimes(:, 2:end, :), 3);
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% initialize data for numTiles x numQueries
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hists = cell(size(tileSizes, 1), size(featsPerQuery, 1));
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% load each histogram
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if ~loadFullData
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for i=1:size(tileSizes, 1)
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for j=1:size(featsPerQuery, 1)
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hists(i, j) = load(sprintf('./data/hist_%d_%d.txt', j, tileSizes(i)));
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end
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end
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else
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% load the unfiltered histograms
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for i=1:size(tileSizes, 1)
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for j=1:size(featsPerQuery, 1)
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hists(i, j) = load(sprintf('./data/hist_full_%d_%d.txt', j, tileSizes(i)));
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end
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end
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end
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end

‎geowave-benchmark/src/main/resources/matlab/FeatureCollectionDataAdapterBenchmark/histogram/plotHist.m‎

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% use this function to plot a single histogram
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% - assumes runtimes, featsPerQuery, tileSizes and hists are loaded
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function plotHist(tileSize, queryNum, lineFormat, color)
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global tileSizes;
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global hists;
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global featsPerQuery;
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global runtimes;
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hist = hists{find(tileSizes == tileSize), queryNum};
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x = (0:(size(hist, 1)-1))*2;
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if nargin == 2
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p1 = plot(x, hist / sum(hist));
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elseif nargin == 3
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p1 = plot(x, hist / sum(hist), lineFormat);
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elseif nargin == 4
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p1 = plot(x, hist / sum(hist), lineFormat, 'Color', color);
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end
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xlabel('Features Per Collection')
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% get the current title for the figure
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t = get(get(gca,'Title'),'String');
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% update the title
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title(
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sprintf('%sQuery %d - %d Features - %.2fs - Tile Size %d\n',
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t,
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queryNum,
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featsPerQuery(queryNum),
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runtimes(queryNum, find(tileSizes == tileSize))/1000,
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tileSize))
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% Get object handles
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[LEGH,OBJH,OUTH,OUTM] = legend;
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legend([OUTH p1],OUTM,sprintf('Query %d - %d', queryNum, tileSize))
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end

‎geowave-benchmark/src/main/resources/matlab/FeatureCollectionDataAdapterBenchmark/histogram/plotHists.m‎

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% use this function to plot multiple histograms automatically
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function plotHists(tileSizes, queryNums)
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figure
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colors = hsv(size(tileSizes, 1));
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hold on
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for i=1:size(tileSizes, 1)
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plotHist(tileSizes(i), queryNums(i), '-', colors(i,:))
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end
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hold off
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end

‎geowave-benchmark/src/main/resources/matlab/FeatureCollectionDataAdapterBenchmark/histogram/setup.m‎

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% this will setup the environment for looking at histograms
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global hists = [];
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global featsPerQuery = [];
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global runtimes = [];
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global tileSizes = [100; 500; 1000; 5000; 10000; 50000];
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[hists, featsPerQuery, runtimes] = loadHistograms();

‎geowave-benchmark/src/main/resources/matlab/FeatureCollectionDataAdapterBenchmark/single/plotQueryTimes.m‎

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function plotQueryTimes(plotTitle, pointsPerTile, featQueryTimes, collQueryTimes, minTimes, maxTimes, vars)
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for i=1:size(collQueryTimes, 2)
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myFig = figure;
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semilogx(pointsPerTile, ones(size(pointsPerTile))*featQueryTimes(i)/1000, '--')
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xlim([pointsPerTile(1)*0.8 pointsPerTile(end)*1.2])
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text(pointsPerTile(1), featQueryTimes(i)/1000, sprintf('%.2f', featQueryTimes(i)/1000))
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hold on;
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semilogx(pointsPerTile, collQueryTimes(:,i)./1000, 'rx-')
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% now plot error bars
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for j=1:size(pointsPerTile, 2)
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semilogx([pointsPerTile(j) pointsPerTile(j)], [(collQueryTimes(j,i)-vars(j,i))/1000 (collQueryTimes(j,i)+vars(j,i))/1000], 'm+-')
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end
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title(sprintf('%s - Query %d', plotTitle, i))
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ylabel('Time in Seconds')
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xlabel('Points Per Tile')
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legend('FeatureData', 'FeatureCollectionData')
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for j=1:size(pointsPerTile, 2)
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text(pointsPerTile(j), collQueryTimes(j,i)/1000, sprintf('[%.0f, %.2f]', pointsPerTile(j), collQueryTimes(j,i)/1000))
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end
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hold off;
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saveas(myFig, sprintf('%s - Query %d', plotTitle, i), 'png');
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end
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end

‎geowave-benchmark/src/main/resources/matlab/FeatureCollectionDataAdapterBenchmark/single/plotResults.m‎

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function plotResults(pointsPerColl, pointsPerTile, numQueries, numRuns)
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load('smallQueryRuntimes.txt');
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load('medQueryRuntimes.txt');
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load('largeQueryRuntimes.txt');
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smallQueryRuntimes = reshape(smallQueryRuntimes, [numQueries(1), size(pointsPerTile, 2)+1, numRuns]);
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medQueryRuntimes = reshape(medQueryRuntimes, [numQueries(2), size(pointsPerTile, 2)+1, numRuns]);
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largeQueryRuntimes = reshape(largeQueryRuntimes, [numQueries(3), size(pointsPerTile, 2)+1, numRuns]);
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featSmallQueryTimes = mean(smallQueryRuntimes(:, 1, :), 3);
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featMedQueryTimes = mean(medQueryRuntimes(:, 1, :), 3);
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featLargeQueryTimes = mean(largeQueryRuntimes(:, 1, :), 3);
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collSmallQueryTimes = mean(smallQueryRuntimes(:, 2:end, :), 3);
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collMedQueryTimes = mean(medQueryRuntimes(:, 2:end, :), 3);
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collLargeQueryTimes = mean(largeQueryRuntimes(:, 2:end, :), 3);
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% Plot query times
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plotQueryTimes('Small Query Runtime', pointsPerTile, featSmallQueryTimes, collSmallQueryTimes', min(smallQueryRuntimes(:, 2:end, :), [], 3)', max(smallQueryRuntimes(:, 2:end, :), [], 3)', std(smallQueryRuntimes(:, 2:end, :), 0, 3)')
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plotQueryTimes('Medium Query Runtime', pointsPerTile, featMedQueryTimes, collMedQueryTimes', min(medQueryRuntimes(:, 2:end, :), [], 3)', max(medQueryRuntimes(:, 2:end, :), [], 3)', std(medQueryRuntimes(:, 2:end, :), 0, 3)')
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plotQueryTimes('Large Query Runtime', pointsPerTile, featLargeQueryTimes, collLargeQueryTimes', min(largeQueryRuntimes(:, 2:end, :), [], 3)', max(largeQueryRuntimes(:, 2:end, :), [], 3)', std(largeQueryRuntimes(:, 2:end, :), 0, 3)')
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end

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