added performance plot legend, rolling normalization
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@@ -24,5 +24,13 @@ function obj = plotPerformance(obj)
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hold(obj.fPerf.Children(1), 'off');
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end
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% Add legend
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agentStrings = repmat("Agent %d", size(obj.perf, 1) - 1, 1);
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for ii = 1:size(agentStrings, 1)
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agentStrings(ii) = sprintf(agentStrings(ii), ii);
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end
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agentStrings = ["Total"; agentStrings];
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legend(obj.fPerf.Children(1), agentStrings, 'Location', 'northwest');
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obj.performancePlot = o;
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end
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@@ -40,13 +40,15 @@ function [obj] = updatePlots(obj, updatePartitions)
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% Update performance plot
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if updatePartitions
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% find index corresponding to the current time
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nowIdx = [0; obj.partitioningTimes] == obj.t;
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% set(obj.performancePlot(1), 'YData', obj.perf(end, 1:find(nowIdx)));
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obj.performancePlot(1).YData(nowIdx) = obj.perf(end, nowIdx);
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for ii = 2:size(obj.performancePlot, 1)
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obj.performancePlot(ii).YData(nowIdx) = obj.perf(ii, nowIdx);
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end
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drawnow;
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end
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nowIdx = find(nowIdx);
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% Re-normalize performance plot
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normalizingFactor = 1/max(obj.perf(end, 1:nowIdx));
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obj.performancePlot(1).YData(1:nowIdx) = obj.perf(end, 1:nowIdx) * normalizingFactor;
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for ii = 2:size(obj.performancePlot, 1)
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obj.performancePlot(ii).YData(1:nowIdx) = obj.perf(ii - 1, 1:nowIdx) * normalizingFactor;
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end
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end
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end
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@@ -104,7 +104,7 @@ classdef test_miSim < matlab.unittest.TestCase
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if ii == 1
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while agentsCrowdObjective(tc.domain.objective, candidatePos, mean(tc.domain.dimensions) / 2)
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candidatePos = tc.domain.random();
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candidatePos(3) = 2 + rand * 2; % place agents at decent altitudes for sensing
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candidatePos(3) = 2 + rand * 1.5; % place agents at decent altitudes for sensing
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end
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else
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candidatePos = tc.agents{randi(ii - 1)}.pos + sign(randn([1, 3])) .* (rand(1, 3) .* tc.comRange/sqrt(2));
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