X-lanni
254 lines
6.8 KiB
Matlab
254 lines
6.8 KiB
Matlab
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close all
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clear all
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pkg load signal
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# Use with files generated by export_stats.sh
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dataDir = 'SET_PATH_TO_RESULTS_DIR';
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resultsToShow = 1; % 1=single loc, 2=merged loc, 3=consecutive
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datasetPrefix = 'Stat';
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datasets = [0 1 6 7 9 14 11 111]; % 0 1 6 7 8 9 11 12
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datasetsName = {'SURF' 'SIFT' 'ORB' 'FAST/FREAK' 'FAST/BRIEF' 'GFTT/FREAK' 'GFTT/BRIEF' 'BRISK' 'GFTT/ORB' 'KAZE' 'ORB-OCTREE' 'SuperPoint' 'SURF/FREAK' 'GFTT/DAISY' 'SURF/DAISY'};
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datasetsName{112} = 'SuperGlue'
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sep = [0, 1000, 3000, 5000, 7000, 9000, 12000];
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sepName = {'16:51', '17:31', '17:58', '18:30', '18:59', '19:42'};
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if resultsToShow == 3
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sep = [0, 1000, 3000, 5000, 7000, 9000];
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sepName = {'17:27', '17:54', '18:27', '18:56', '19:35'};
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datasetPrefix = 'Consecutive'
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endif
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percentResults = {};
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totalResults = {};
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locResults = {};
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figure
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colors = get(gca, 'ColorOrder');
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tmp=colors(3,:);
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colors(3,:) = colors(5,:);
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colors(5,:) = tmp;
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globalSeparators = [];
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globalx = [];
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globaly = [];
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globalc = [];
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for d=1:length(datasets)
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data = dlmread([dataDir '/' datasetPrefix num2str(datasets(d)) '-Loop-Map_id-' '.txt'], '\t', 1, 0, "emptyvalue", NaN);
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curvesBeg = 2;
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curvesEnd = size(data,2)-5; % -4 for '0', -5 for '1'
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if resultsToShow == 2
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curvesBeg = 8; % 2 if only 4 merged_reduced in stats, 8 to skip first 6
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curvesEnd = size(data,2);
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elseif resultsToShow == 3
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curvesEnd = size(data,2);
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endif
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curves = curvesEnd - curvesBeg + 1;
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percentResultsTmp = zeros(curves, length(sep)-1);
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totalResultsTmp = zeros(curves, length(sep)-1);
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locResultsTmp = zeros(curves, length(sep)-1);
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offset = 1;
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for i = 1:curves
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index = i + curvesBeg - 1;
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separators = [];
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x_all = [];
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y_all = [];
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m_all = [];
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previousMax = 0;
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for j = 1:length(sep)-1
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x = data(:,1);
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y = data(:,index);
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y = y(x>=sep(j) & x<=sep(j+1), :);
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x = x(x>=sep(j) & x<=sep(j+1), :);
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minimum = x(1,1);
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separators = [separators previousMax];
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x = x - (minimum-previousMax);
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previousMax = x(end,1);
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y = y + 1;
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m = y;
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y(y>0) = 1;
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y(isnan(y)) = 0;
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percent = sum(y)/length(y);
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percentResultsTmp(i,j) = percent;
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locResultsTmp(i,j) = sum(y);
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totalResultsTmp(i,j) = length(y);
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y(y>0) = -(d-1)*curves -i - (d-1)*offset;
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%x(y==0) = nan;
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m(y==0) = nan;
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y(y==0) = nan;
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if resultsToShow == 2
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if i==1 %% Merged 1, 6
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m(m==1) = 1;
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m(m==2) = 6;
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elseif i==2 %% Merged 1,3(2 sessions),5
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m(m==1) = 1;
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m(m==2) = 3;
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m(m==3) = 3;
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m(m==4) = 5;
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elseif i==3 %% Merged 2(2 sessions),4,6
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m(m==1) = 2;
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m(m==2) = 2;
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m(m==4) = 6;
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m(m==3) = 4;
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elseif i>=4 %% Merged 1, 2(2 sessions), 3(2 sessions),4,5,6
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m(m==1) = 1;
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m(m==2) = 2;
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m(m==3) = 2;
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m(m==4) = 3;
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m(m==5) = 3;
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m(m==6) = 4;
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m(m==7) = 5;
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m(m==8) = 6;
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endif
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endif
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x = upsample(x, 2);
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y = upsample(y, 2);
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m = upsample(m, 2);
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x(2:2:end-1) = x(3:2:end);
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y(2:2:end-1) = y(3:2:end);
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m(2:2:end) = m(1:2:end);
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x = x(1:end-1);
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y = y(1:end-1);
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m = m(1:end-1);
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x_all = [x_all nan x'];
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y_all = [y_all nan y'];
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m_all = [m_all nan m'];
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endfor
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if resultsToShow == 2
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globalx = [globalx x_all];
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globaly = [globaly y_all];
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globalc = [globalc m_all];
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else
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plot(x_all,y_all, 'linewidth', 3, 'color', colors(i,:))
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hold on
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endif
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separators = [separators previousMax];
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globalSeparators = separators;
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endfor
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percentResults{1,d} = percentResultsTmp;
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totalResults{1,d} = totalResultsTmp;
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locResults{1,d} = locResultsTmp;
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endfor
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if resultsToShow == 2
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indColors = ones(length(globalc), 3);
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for j=1:length(globalc)
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if ~isnan(globalc(j))
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indColors(j,:) = colors(globalc(j),:);
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endif
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endfor
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for i=1:6
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tmpx = globalx;
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tmpy = globaly;
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tmpx(globalc~=i) = nan;
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tmpy(globalc~=i) = nan;
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plot(tmpx, tmpy, 'linewidth', 3, 'color', colors(i,:));
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if i==1
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hold on
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endif
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endfor
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endif
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for j=1:length(globalSeparators)
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x = globalSeparators(j);
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plot([x,x],[(-length(datasets)*(curves+1)) ,0], 'k','linewidth', 2);
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endfor
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for d=1:length(datasets)
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annotation ("textbox", [0, 0.96-((d-0.5)/length(datasets))*0.95, 0,0], 'string', datasetsName{datasets(d)+1})
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endfor
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for s=1:length(sep)-1
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annotation ("textbox", [0.1 + ((separators(s+1)-separators(s))/2+separators(s))/separators(end)*0.75, 0.98, 0,0], 'string', sepName{s})
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endfor
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axis('tight')
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set(gca, 'units', 'normalized');
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Tight = get(gca, 'Position');
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NewPos = [Tight(1) 0.01 0.77 0.95]; %New plot position [X Y W H]
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set(gca, 'Position', NewPos);
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if length(sep) == 7
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legend('16:46', '17:27', '17:54', '18:27', '18:56', '19:35', "location", 'northeastoutside' )
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else
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legend('16:46', '17:27', '17:54', '18:27', '18:56', "location", 'northeastoutside' )
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endif
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box off
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axis off
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#disp(percentResults);
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#disp(totalResults);
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figure;
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for d=1:length(datasets)
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subplot(4,2,d)
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data=percentResults{1,d}*100;
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data(isnan(data)) = 0;
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hAxes = gca;
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% Upscaling the image to reduce anti-aliasing effect in pfd viewers
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scale = 50;
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tickXStep = zeros(1, size(data, 2));
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tickYStep = zeros(1, size(data, 1));
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dataUp = upsample(upsample(data',scale)',scale);
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for x=0:size(data, 2)-1
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for y=1:scale-1
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dataUp(:,(x*scale+1)+y) = dataUp(:,x*scale+1);
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endfor
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tickXStep(1,x+1) = scale/2 + scale*x;
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endfor
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for x=0:size(data, 1)-1
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for y=1:scale-1
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dataUp((x*scale+1)+y,:) = dataUp(x*scale+1,:);
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endfor
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tickYStep(1,x+1) = scale/2 + scale*x;
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endfor
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imagesc( hAxes, dataUp, [0, 100])
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%title({"",datasetsName{datasets(d)+1}})
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colors = [ones(100,1) [1:100]'*0.01 [1:100]'*0];
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colors(1,:) = 1;
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colormap( hAxes , colors)
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c = colorbar;
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labels = {};
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for v=get(c,'ytick'), labels{end+1} = sprintf('%d%%',v); end
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set(c,'yticklabel',labels);
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if mod(d,2) == 1
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ylabel("Map")
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endif
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xlabel([datasetsName{datasets(d)+1} " Localization"])
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set(gca, "xaxislocation", "top");
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set(gca, 'XTick', tickXStep)
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set(gca, 'XTickLabel', sepName, 'fontsize',7)
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set(gca, 'YTick', tickYStep)
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if resultsToShow == 3
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set(gca, 'YTickLabel', {'16:46', '17:27', '17:54', '18:27', '18:56'}, 'fontsize',7)
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elseif resultsToShow == 2
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set(gca, 'YTickLabel', {'1+6', '1+3+5', '2+4+6', '1+2+3+4+5+6', '1-2-3-4-5-6', 'not set'}, 'fontsize',7)
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else
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set(gca, 'YTickLabel', {'16:46', '17:27', '17:54', '18:27', '18:56', '19:35'}, 'fontsize',7)
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endif
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endfor
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% compute cumulative localizations
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cumResults = zeros(curves+2, length(datasets)+1);
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for d=1:length(datasets)
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cumResults(1,d+1) = datasets(d);
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cumResults(2:end-1,d+1) = round(sum(locResults{1,d}, 2) ./ sum(totalResults{1,d}, 2) * 100);
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if resultsToShow == 1
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cumResults(end,d+1) = round(sum(sum(locResults{1,d}.*eye(curves,curves))) / sum(totalResults{1,d},2)(1,1) * 100);
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endif
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end
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cumResults(2:end-1,1) = 1:curves;
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cumResults
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