last plot updates
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110
test/results.m
110
test/results.m
@@ -10,8 +10,8 @@ classdef results < matlab.unittest.TestCase
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%% Diagnostic Parameters
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% No effect on simulation dynamics
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makeVideo = true; % disable video writing for big performance increase
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makePlots = true; % disable plotting for big performance increase (also disables video)
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makeVideo = false; % disable video writing for big performance increase
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makePlots = false; % disable plotting for big performance increase (also disables video)
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plotCommsGeometry = false; % disable plotting communications geometries
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%% Scenario Reinitialization
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@@ -72,8 +72,8 @@ classdef results < matlab.unittest.TestCase
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sensor2 = sigmoidSensor;
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sensor1 = sensor1.initialize(sensors(1).alphaDist, sensors(1).betaDist, sensors(1).alphaTilt, sensors(1).betaTilt);
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sensor2 = sensor2.initialize(sensors(2).alphaDist, sensors(2).betaDist, sensors(2).alphaTilt, sensors(2).betaTilt);
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sensor1.plotParameters;
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sensor2.plotParameters;
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% sensor1.plotParameters;
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% sensor2.plotParameters;
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c = struct('A_1_alpha', struct('objectivePos', [3, 1] / 4 .* results.domainSize(1:2), 'sensor', sensors(1), 'doubleIntegrator', false), ...
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'A_1_beta', struct('objectivePos', [3, 1] / 4 .* results.domainSize(1:2), 'sensor', sensors(1), 'doubleIntegrator', true), ...
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'A_2_alpha', struct('objectivePos', [3, 1] / 4 .* results.domainSize(1:2), 'sensor', sensors(2), 'doubleIntegrator', false), ...
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@@ -269,57 +269,57 @@ classdef results < matlab.unittest.TestCase
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tc.testClass = tc.testClass.teardown();
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close all;
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end
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function AIIbeta_plots_3_4(tc)
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% test-specific parameters
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tc.makePlots = true;
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tc.makeVideo = true;
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maxIters = 400;
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configs = results.makeConfigs();
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c = configs.A_2_alpha;
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c.doubleIntegrator = true; % make a2alpha into a2beta
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% Set up fixed-size domain
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minAlt = tc.domainSize(3)/10 + rand * 1/10 * tc.domainSize(3);
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tc.testClass.domain = tc.testClass.domain.initialize([zeros(1, 3); tc.domainSize], REGION_TYPE.DOMAIN, "Domain");
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% Set objective
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objectiveMu = [tc.domainSize(1) * 2 / 3, tc.domainSize(2) * 3 / 4];
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objectiveSigma = reshape([215, 100; 100, 175], [1, 2, 2]);
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tc.testClass.domain.objective = tc.testClass.domain.objective.initialize(objectiveFunctionWrapper(objectiveMu, objectiveSigma), tc.testClass.domain, tc.discretizationStep, tc.protectedRange, tc.sensorPerformanceMinimum, objectiveMu, objectiveSigma);
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% Set agent initial states (fully connected network of 4)
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centerPos = [tc.domainSize(1) / 4, tc.domainSize(2) / 4];
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d = tc.collisionRadius + (tc.comRange - tc.collisionRadius) / 4;
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agentsPos = centerPos + [1, 1; 1, -1; -1, -1; -1, 1] / sqrt(2) * d;
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agentAlt = minAlt * 1.5;
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agentsPos = [agentsPos, agentAlt * ones(4, 1) + rand * 5 - 2.5];
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agents = {agent, agent, agent, agent};
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cg = spherical;
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sensorModel = sigmoidSensor;
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sensorModel = sensorModel.initialize(c.sensor.alphaDist, c.sensor.betaDist, c.sensor.alphaTilt, c.sensor.betaTilt);
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agents{1} = agents{1}.initialize(agentsPos(1, :), cg.initialize(agentsPos(1, :), tc.collisionRadius, REGION_TYPE.COLLISION, "Agent 1 Collision Geometry"), sensorModel, tc.comRange, maxIters, tc.initialStepSize, "Agent 1", false);
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agents{2} = agents{2}.initialize(agentsPos(2, :), cg.initialize(agentsPos(2, :), tc.collisionRadius, REGION_TYPE.COLLISION, "Agent 2 Collision Geometry"), sensorModel, tc.comRange, maxIters, tc.initialStepSize, "Agent 2", false);
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agents{3} = agents{3}.initialize(agentsPos(3, :), cg.initialize(agentsPos(3, :), tc.collisionRadius, REGION_TYPE.COLLISION, "Agent 3 Collision Geometry"), sensorModel, tc.comRange, maxIters, tc.initialStepSize, "Agent 3", false);
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agents{4} = agents{4}.initialize(agentsPos(4, :), cg.initialize(agentsPos(4, :), tc.collisionRadius, REGION_TYPE.COLLISION, "Agent 4 Collision Geometry"), sensorModel, tc.comRange, maxIters, tc.initialStepSize, "Agent 4", false);
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obstacles = cell(1, 1);
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obstacles{1} = rectangularPrism;
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obstacles{1} = obstacles{1}.initialize([0, tc.domainSize(2)/2, 0; tc.domainSize(1) * 0.4, tc.domainSize(2), 40],REGION_TYPE.OBSTACLE, "Obstacle 1");
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% Set up simulation
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tc.testClass = tc.testClass.initialize(tc.testClass.domain, agents, tc.barrierGain, tc.barrierExponent, minAlt, tc.timestep, maxIters, obstacles, tc.makePlots, tc.makeVideo, c.doubleIntegrator, tc.dampingCoeff, tc.useFixedTopology);
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% Save simulation parameters to output file
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tc.testClass.writeInits();
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% Run
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tc.testClass = tc.testClass.run();
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% Cleanup
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tc.testClass = tc.testClass.teardown();
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end
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% function AIIbeta_plots_3_4(tc)
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% % test-specific parameters
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% tc.makePlots = true;
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% tc.makeVideo = true;
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% maxIters = 400;
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%
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% configs = results.makeConfigs();
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% c = configs.A_2_alpha;
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% c.doubleIntegrator = true; % make a2alpha into a2beta
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%
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% % Set up fixed-size domain
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% minAlt = tc.domainSize(3)/10 + rand * 1/10 * tc.domainSize(3);
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% tc.testClass.domain = tc.testClass.domain.initialize([zeros(1, 3); tc.domainSize], REGION_TYPE.DOMAIN, "Domain");
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%
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% % Set objective
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% objectiveMu = [tc.domainSize(1) * 2 / 3, tc.domainSize(2) * 3 / 4];
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% objectiveSigma = reshape([215, 100; 100, 175], [1, 2, 2]);
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% tc.testClass.domain.objective = tc.testClass.domain.objective.initialize(objectiveFunctionWrapper(objectiveMu, objectiveSigma), tc.testClass.domain, tc.discretizationStep, tc.protectedRange, tc.sensorPerformanceMinimum, objectiveMu, objectiveSigma);
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%
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% % Set agent initial states (fully connected network of 4)
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% centerPos = [tc.domainSize(1) / 4, tc.domainSize(2) / 4];
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% d = tc.collisionRadius + (tc.comRange - tc.collisionRadius) / 4;
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% agentsPos = centerPos + [1, 1; 1, -1; -1, -1; -1, 1] / sqrt(2) * d;
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% agentAlt = minAlt * 1.5;
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% agentsPos = [agentsPos, agentAlt * ones(4, 1) + rand * 5 - 2.5];
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%
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% agents = {agent, agent, agent, agent};
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% cg = spherical;
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% sensorModel = sigmoidSensor;
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% sensorModel = sensorModel.initialize(c.sensor.alphaDist, c.sensor.betaDist, c.sensor.alphaTilt, c.sensor.betaTilt);
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% agents{1} = agents{1}.initialize(agentsPos(1, :), cg.initialize(agentsPos(1, :), tc.collisionRadius, REGION_TYPE.COLLISION, "Agent 1 Collision Geometry"), sensorModel, tc.comRange, maxIters, tc.initialStepSize, "Agent 1", false);
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% agents{2} = agents{2}.initialize(agentsPos(2, :), cg.initialize(agentsPos(2, :), tc.collisionRadius, REGION_TYPE.COLLISION, "Agent 2 Collision Geometry"), sensorModel, tc.comRange, maxIters, tc.initialStepSize, "Agent 2", false);
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% agents{3} = agents{3}.initialize(agentsPos(3, :), cg.initialize(agentsPos(3, :), tc.collisionRadius, REGION_TYPE.COLLISION, "Agent 3 Collision Geometry"), sensorModel, tc.comRange, maxIters, tc.initialStepSize, "Agent 3", false);
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% agents{4} = agents{4}.initialize(agentsPos(4, :), cg.initialize(agentsPos(4, :), tc.collisionRadius, REGION_TYPE.COLLISION, "Agent 4 Collision Geometry"), sensorModel, tc.comRange, maxIters, tc.initialStepSize, "Agent 4", false);
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%
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% obstacles = cell(1, 1);
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% obstacles{1} = rectangularPrism;
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% obstacles{1} = obstacles{1}.initialize([0, tc.domainSize(2)/2, 0; tc.domainSize(1) * 0.4, tc.domainSize(2), 40],REGION_TYPE.OBSTACLE, "Obstacle 1");
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%
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% % Set up simulation
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% tc.testClass = tc.testClass.initialize(tc.testClass.domain, agents, tc.barrierGain, tc.barrierExponent, minAlt, tc.timestep, maxIters, obstacles, tc.makePlots, tc.makeVideo, c.doubleIntegrator, tc.dampingCoeff, tc.useFixedTopology);
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%
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% % Save simulation parameters to output file
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% tc.testClass.writeInits();
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%
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% % Run
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% tc.testClass = tc.testClass.run();
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%
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% % Cleanup
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% tc.testClass = tc.testClass.teardown();
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% end
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end
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methods
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