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fixed performance plotting

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This commit is contained in:
Kevin Dee
2026-01-11 14:41:27 -08:00
parent ec202d7790
commit 796e2f322a
5 changed files with 51 additions and 39 deletions
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6
@agent/initialize.m
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@@ -1,4 +1,4 @@
function obj = initialize(obj, pos, vel, pan, tilt, collisionGeometry, sensorModel, comRange, label, plotCommsGeometry)
function obj = initialize(obj, pos, vel, pan, tilt, collisionGeometry, sensorModel, comRange, maxIter, label, plotCommsGeometry)
arguments (Input)
obj (1, 1) {mustBeA(obj, 'agent')};
pos (1, 3) double;
@@ -8,6 +8,7 @@ function obj = initialize(obj, pos, vel, pan, tilt, collisionGeometry, sensorMod
collisionGeometry (1, 1) {mustBeGeometry};
sensorModel (1, 1) {mustBeSensor};
comRange (1, 1) double;
maxIter (1, 1) double;
label (1, 1) string = "";
plotCommsGeometry (1, 1) logical = false;
end
@@ -24,6 +25,9 @@ function obj = initialize(obj, pos, vel, pan, tilt, collisionGeometry, sensorMod
obj.label = label;
obj.plotCommsGeometry = plotCommsGeometry;
% Initialize performance vector
obj.performance = [0, NaN(1, maxIter), 0];
% Add spherical geometry based on com range
obj.commsGeometry = obj.commsGeometry.initialize(obj.pos, comRange, REGION_TYPE.COMMS, sprintf("%s Comms Geometry", obj.label));

3
@agent/run.m
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@@ -59,6 +59,9 @@ function obj = run(obj, domain, partitioning, timestepIndex, index, agents)
C_delta(ii) = sum(C(~isnan(C)));
end
% Store agent performance at current time and place
obj.performance(timestepIndex + 1) = C_delta(1);
% Compute gradient by finite central differences
gradC = [(C_delta(2)-C_delta(3))/(2*delta), (C_delta(4)-C_delta(5))/(2*delta), (C_delta(6)-C_delta(7))/(2*delta)];

2
@miSim/run.m
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@@ -46,7 +46,7 @@ function [obj] = run(obj)
obj.posHist(1:size(obj.agents, 1), obj.timestepIndex + 1, 1:3) = reshape(cell2mat(cellfun(@(x) x.pos, obj.agents, 'UniformOutput', false)), size(obj.agents, 1), 1, 3);
% Update total performance
obj.performance = [obj.performance, sum(cellfun(@(x) x.performance(end), obj.agents))];
obj.performance = [obj.performance, sum(cellfun(@(x) x.performance(obj.timestepIndex+1), obj.agents))];
% Update adjacency matrix
obj = obj.updateAdjacency();

12
@miSim/updatePlots.m
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@@ -53,12 +53,12 @@ function [obj] = updatePlots(obj, updatePartitions)
% Update performance plot
% Re-normalize performance plot
normalizingFactor = 1/max(obj.performance(end));
obj.performancePlot(1).YData(1:length(obj.performance)) = obj.performance * normalizingFactor;
obj.performancePlot(1).XData(obj.timestepIndex) = obj.t;
for ii = 2:(size(obj.agents, 1) + 1)
obj.performancePlot(ii).YData(1:length(obj.performance)) = obj.agents{ii - 1}.performance * normalizingFactor;
obj.performancePlot(ii).XData(obj.timestepIndex) = obj.t;
normalizingFactor = 1/max(obj.performance);
obj.performancePlot(1).YData(1:(length(obj.performance) + 1)) = [obj.performance, 0] * normalizingFactor;
obj.performancePlot(1).XData([obj.timestepIndex, obj.timestepIndex + 1]) = [obj.t, obj.t + obj.timestep];
for ii = 1:(size(obj.agents, 1))
obj.performancePlot(ii + 1).YData(1:(length(obj.performance) + 1)) = [obj.agents{ii}.performance(1:length(obj.performance)), 0] * normalizingFactor;
obj.performancePlot(ii + 1).XData([obj.timestepIndex, obj.timestepIndex + 1]) = [obj.t, obj.t + obj.timestep];
end
% Update h function plots

67
test/test_miSim.m
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@@ -162,7 +162,7 @@ classdef test_miSim < matlab.unittest.TestCase
sensor = sensor.initialize(tc.alphaDistMin + rand * (tc.alphaDistMax - tc.alphaDistMin), tc.betaDistMin + rand * (tc.betaDistMax - tc.betaDistMin), NaN, NaN, tc.alphaTiltMin + rand * (tc.alphaTiltMax - tc.alphaTiltMin), tc.betaTiltMin + rand * (tc.betaTiltMax - tc.betaTiltMin));
% Initialize candidate agent
newAgent = tc.agents{ii}.initialize(candidatePos, zeros(1,3), 0, 0, candidateGeometry, sensor, tc.comRange);
newAgent = tc.agents{ii}.initialize(candidatePos, zeros(1,3), 0, 0, candidateGeometry, sensor, tc.comRange, tc.maxIter);
% Make sure candidate agent doesn't collide with
% domain
@@ -296,7 +296,7 @@ classdef test_miSim < matlab.unittest.TestCase
sensor = sensor.initialize(tc.alphaDistMin + rand * (tc.alphaDistMax - tc.alphaDistMin), tc.betaDistMin + rand * (tc.betaDistMax - tc.betaDistMin), NaN, NaN, tc.alphaTiltMin + rand * (tc.alphaTiltMax - tc.alphaTiltMin), tc.betaTiltMin + rand * (tc.betaTiltMax - tc.betaTiltMin));
% Initialize candidate agent
newAgent = tc.agents{ii}.initialize(candidatePos, zeros(1,3), 0, 0, candidateGeometry, sensor, tc.comRange);
newAgent = tc.agents{ii}.initialize(candidatePos, zeros(1,3), 0, 0, candidateGeometry, sensor, tc.comRange, tc.maxIter);
% Make sure candidate agent doesn't collide with
% domain
@@ -378,8 +378,8 @@ classdef test_miSim < matlab.unittest.TestCase
% Initialize agents
tc.agents = {agent; agent};
tc.agents{1} = tc.agents{1}.initialize(tc.domain.center + dh + [d, 0, 0], zeros(1,3), 0, 0, geometry1, sensor, 3*d);
tc.agents{2} = tc.agents{2}.initialize(tc.domain.center + dh - [d, 0, 0], zeros(1,3), 0, 0, geometry2, sensor, 3*d);
tc.agents{1} = tc.agents{1}.initialize(tc.domain.center + dh + [d, 0, 0], zeros(1,3), 0, 0, geometry1, sensor, 3*d, tc.maxIter);
tc.agents{2} = tc.agents{2}.initialize(tc.domain.center + dh - [d, 0, 0], zeros(1,3), 0, 0, geometry2, sensor, 3*d, tc.maxIter);
% Optional third agent along the +Y axis
geometry3 = rectangularPrism;
@@ -420,7 +420,7 @@ classdef test_miSim < matlab.unittest.TestCase
% Initialize agents
tc.agents = {agent};
tc.agents{1} = tc.agents{1}.initialize([tc.domain.center(1:2), 3], zeros(1,3), 0, 0, geometry1, sensor, 3);
tc.agents{1} = tc.agents{1}.initialize([tc.domain.center(1:2), 3], zeros(1,3), 0, 0, geometry1, sensor, 3, tc.maxIter);
% Initialize the simulation
tc.testClass = tc.testClass.initialize(tc.domain, tc.domain.objective, tc.agents, tc.minAlt, tc.timestep, tc.partitoningFreq, tc.maxIter, cell(0, 1), false, false);
@@ -453,7 +453,7 @@ classdef test_miSim < matlab.unittest.TestCase
% Initialize agents
tc.agents = {agent};
tc.agents{1} = tc.agents{1}.initialize([tc.domain.center(1:2)-tc.domain.dimensions(1)/3, 3], zeros(1,3), 0, 0, geometry1, sensor, 3, "", false);
tc.agents{1} = tc.agents{1}.initialize([tc.domain.center(1:2)-tc.domain.dimensions(1)/3, 3], zeros(1,3), 0, 0, geometry1, sensor, 3, tc.maxIter);
% Initialize the simulation
tc.testClass = tc.testClass.initialize(tc.domain, tc.domain.objective, tc.agents, tc.minAlt, tc.timestep, tc.partitoningFreq, tc.maxIter, cell(0, 1));
@@ -490,12 +490,13 @@ classdef test_miSim < matlab.unittest.TestCase
sensor = sensor.initialize(alphaDist, 3, NaN, NaN, 15, 3);
% Initialize agents
nIter = 50;
tc.agents = {agent; agent};
tc.agents{1} = tc.agents{1}.initialize(tc.domain.center + d, zeros(1,3), 0, 0, geometry1, sensor, 5);
tc.agents{2} = tc.agents{2}.initialize(tc.domain.center - d, zeros(1,3), 0, 0, geometry2, sensor, 5);
tc.agents{1} = tc.agents{1}.initialize(tc.domain.center + d, zeros(1,3), 0, 0, geometry1, sensor, 5, nIter);
tc.agents{2} = tc.agents{2}.initialize(tc.domain.center - d, zeros(1,3), 0, 0, geometry2, sensor, 5, nIter);
% Initialize the simulation
tc.testClass = tc.testClass.initialize(tc.domain, tc.domain.objective, tc.agents, tc.minAlt, tc.timestep, tc.partitoningFreq, 50, cell(0, 1), tc.makeVideo, tc.makePlots);
tc.testClass = tc.testClass.initialize(tc.domain, tc.domain.objective, tc.agents, tc.minAlt, tc.timestep, tc.partitoningFreq, nIter, cell(0, 1), tc.makeVideo, tc.makePlots);
% Run the simulation
tc.testClass.run();
@@ -540,8 +541,8 @@ classdef test_miSim < matlab.unittest.TestCase
% Initialize agents
commsRadius = (2*radius + obstacleLength) * 0.9; % defined such that they cannot go around the obstacle on both sides
tc.agents = {agent; agent;};
tc.agents{1} = tc.agents{1}.initialize(tc.domain.center - d + [0, radius * 1.1 - yOffset, 0], zeros(1,3), 0, 0, geometry1, sensor, commsRadius);
tc.agents{2} = tc.agents{2}.initialize(tc.domain.center - d - [0, radius *1.1 + yOffset, 0], zeros(1,3), 0, 0, geometry2, sensor, commsRadius);
tc.agents{1} = tc.agents{1}.initialize(tc.domain.center - d + [0, radius * 1.1 - yOffset, 0], zeros(1,3), 0, 0, geometry1, sensor, commsRadius, tc.maxIter);
tc.agents{2} = tc.agents{2}.initialize(tc.domain.center - d - [0, radius *1.1 + yOffset, 0], zeros(1,3), 0, 0, geometry2, sensor, commsRadius, tc.maxIter);
% Initialize the simulation
tc.testClass = tc.testClass.initialize(tc.domain, tc.domain.objective, tc.agents, tc.minAlt, tc.timestep, tc.partitoningFreq, tc.maxIter, tc.obstacles, tc.makeVideo);
@@ -578,13 +579,14 @@ classdef test_miSim < matlab.unittest.TestCase
tc.obstacles = {};
% Initialize agents
nIter = 75;
commsRadius = 4; % defined such that they cannot reach their objective without breaking connectivity
tc.agents = {agent; agent;};
tc.agents{1} = tc.agents{1}.initialize(dom.center + d, zeros(1,3), 0, 0, geometry1, sensor, commsRadius);
tc.agents{2} = tc.agents{2}.initialize(dom.center - d, zeros(1,3), 0, 0, geometry2, sensor, commsRadius);
tc.agents{1} = tc.agents{1}.initialize(dom.center + d, zeros(1,3), 0, 0, geometry1, sensor, commsRadius, nIter);
tc.agents{2} = tc.agents{2}.initialize(dom.center - d, zeros(1,3), 0, 0, geometry2, sensor, commsRadius, nIter);
% Initialize the simulation
tc.testClass = tc.testClass.initialize(dom, dom.objective, tc.agents, tc.minAlt, tc.timestep, tc.partitoningFreq, 75, tc.obstacles, true, false);
tc.testClass = tc.testClass.initialize(dom, dom.objective, tc.agents, tc.minAlt, tc.timestep, tc.partitoningFreq, nIter, tc.obstacles, true, false);
% Run the simulation
tc.testClass = tc.testClass.run();
@@ -614,10 +616,11 @@ classdef test_miSim < matlab.unittest.TestCase
sensor = sensor.initialize(alphaDist, 3, NaN, NaN, 15, 3);
% Initialize agents
nIter = 125;
commsRadius = 5;
tc.agents = {agent; agent;};
tc.agents{1} = tc.agents{1}.initialize(tc.domain.center - [d, 0, 0], zeros(1,3), 0, 0, geometry1, sensor, commsRadius);
tc.agents{2} = tc.agents{2}.initialize(tc.domain.center - [0, d, 0], zeros(1,3), 0, 0, geometry2, sensor, commsRadius);
tc.agents{1} = tc.agents{1}.initialize(tc.domain.center - [d, 0, 0], zeros(1,3), 0, 0, geometry1, sensor, commsRadius, nIter);
tc.agents{2} = tc.agents{2}.initialize(tc.domain.center - [0, d, 0], zeros(1,3), 0, 0, geometry2, sensor, commsRadius, nIter);
% Initialize obstacles
obstacleLength = 1.5;
@@ -625,7 +628,7 @@ classdef test_miSim < matlab.unittest.TestCase
tc.obstacles{1} = tc.obstacles{1}.initialize([tc.domain.center(1:2) - obstacleLength, 0; tc.domain.center(1:2) + obstacleLength, tc.domain.maxCorner(3)], REGION_TYPE.OBSTACLE, "Obstacle 1");
% Initialize the simulation
tc.testClass = tc.testClass.initialize(tc.domain, tc.domain.objective, tc.agents, 0, tc.timestep, tc.partitoningFreq, 125, tc.obstacles, false, false);
tc.testClass = tc.testClass.initialize(tc.domain, tc.domain.objective, tc.agents, 0, tc.timestep, tc.partitoningFreq, nIter, tc.obstacles, false, false);
% No communications link should be established
tc.assertEqual(tc.testClass.adjacency, logical(eye(2)));
@@ -659,16 +662,17 @@ classdef test_miSim < matlab.unittest.TestCase
sensor = sensor.initialize(alphaDist, 3, NaN, NaN, 15, 3);
% Initialize agents
nIter = 125;
commsRadius = d;
tc.agents = {agent; agent; agent; agent; agent;};
tc.agents{1} = tc.agents{1}.initialize(tc.domain.center + [d, 0, 0], zeros(1,3), 0, 0, geometry1, sensor, commsRadius);
tc.agents{2} = tc.agents{2}.initialize(tc.domain.center, zeros(1,3), 0, 0, geometry2, sensor, commsRadius);
tc.agents{3} = tc.agents{3}.initialize(tc.domain.center + [-d, d, 0], zeros(1,3), 0, 0, geometry3, sensor, commsRadius);
tc.agents{4} = tc.agents{4}.initialize(tc.domain.center + [-2*d, d, 0], zeros(1,3), 0, 0, geometry4, sensor, commsRadius);
tc.agents{5} = tc.agents{5}.initialize(tc.domain.center + [0, d, 0], zeros(1,3), 0, 0, geometry5, sensor, commsRadius);
tc.agents{1} = tc.agents{1}.initialize(tc.domain.center + [d, 0, 0], zeros(1,3), 0, 0, geometry1, sensor, commsRadius, nIter);
tc.agents{2} = tc.agents{2}.initialize(tc.domain.center, zeros(1,3), 0, 0, geometry2, sensor, commsRadius, nIter);
tc.agents{3} = tc.agents{3}.initialize(tc.domain.center + [-d, d, 0], zeros(1,3), 0, 0, geometry3, sensor, commsRadius, nIter);
tc.agents{4} = tc.agents{4}.initialize(tc.domain.center + [-2*d, d, 0], zeros(1,3), 0, 0, geometry4, sensor, commsRadius, nIter);
tc.agents{5} = tc.agents{5}.initialize(tc.domain.center + [0, d, 0], zeros(1,3), 0, 0, geometry5, sensor, commsRadius, nIter);
% Initialize the simulation
tc.testClass = tc.testClass.initialize(tc.domain, tc.domain.objective, tc.agents, 0, tc.timestep, tc.partitoningFreq, 125, tc.obstacles, false, false);
tc.testClass = tc.testClass.initialize(tc.domain, tc.domain.objective, tc.agents, 0, tc.timestep, tc.partitoningFreq, nIter, tc.obstacles, false, false);
% Constraint adjacency matrix defined by LNA should be as follows
tc.assertEqual(tc.testClass.constraintAdjacencyMatrix, logical( ...
@@ -709,18 +713,19 @@ classdef test_miSim < matlab.unittest.TestCase
sensor = sensor.initialize(alphaDist, 3, NaN, NaN, 15, 3);
% Initialize agents
nIter = 125;
commsRadius = d;
tc.agents = {agent; agent; agent; agent; agent; agent; agent;};
tc.agents{1} = tc.agents{1}.initialize(tc.domain.center + [-0.9 * d/sqrt(2), 0.9 * d/sqrt(2), 0], zeros(1,3), 0, 0, geometry1, sensor, commsRadius);
tc.agents{2} = tc.agents{2}.initialize(tc.domain.center + [-0.5 * d, 0.25 * d, 0], zeros(1,3), 0, 0, geometry2, sensor, commsRadius);
tc.agents{3} = tc.agents{3}.initialize(tc.domain.center + [0.9 * d, 0, 0], zeros(1,3), 0, 0, geometry3, sensor, commsRadius);
tc.agents{4} = tc.agents{4}.initialize(tc.domain.center + [0.9 * d/sqrt(2), -0.9 * d/sqrt(2), 0], zeros(1,3), 0, 0, geometry4, sensor, commsRadius);
tc.agents{5} = tc.agents{5}.initialize(tc.domain.center + [0, 0.9 * d, 0], zeros(1,3), 0, 0, geometry5, sensor, commsRadius);
tc.agents{6} = tc.agents{6}.initialize(tc.domain.center, zeros(1,3), 0, 0, geometry6, sensor, commsRadius);
tc.agents{7} = tc.agents{7}.initialize(tc.domain.center + [d/2, d/2, 0], zeros(1,3), 0, 0, geometry7, sensor, commsRadius);
tc.agents{1} = tc.agents{1}.initialize(tc.domain.center + [-0.9 * d/sqrt(2), 0.9 * d/sqrt(2), 0], zeros(1,3), 0, 0, geometry1, sensor, commsRadius, nIter);
tc.agents{2} = tc.agents{2}.initialize(tc.domain.center + [-0.5 * d, 0.25 * d, 0], zeros(1,3), 0, 0, geometry2, sensor, commsRadius, nIter);
tc.agents{3} = tc.agents{3}.initialize(tc.domain.center + [0.9 * d, 0, 0], zeros(1,3), 0, 0, geometry3, sensor, commsRadius, nIter);
tc.agents{4} = tc.agents{4}.initialize(tc.domain.center + [0.9 * d/sqrt(2), -0.9 * d/sqrt(2), 0], zeros(1,3), 0, 0, geometry4, sensor, commsRadius, nIter);
tc.agents{5} = tc.agents{5}.initialize(tc.domain.center + [0, 0.9 * d, 0], zeros(1,3), 0, 0, geometry5, sensor, commsRadius, nIter);
tc.agents{6} = tc.agents{6}.initialize(tc.domain.center, zeros(1,3), 0, 0, geometry6, sensor, commsRadius, nIter);
tc.agents{7} = tc.agents{7}.initialize(tc.domain.center + [d/2, d/2, 0], zeros(1,3), 0, 0, geometry7, sensor, commsRadius, nIter);
% Initialize the simulation
tc.testClass = tc.testClass.initialize(tc.domain, tc.domain.objective, tc.agents, 0, tc.timestep, tc.partitoningFreq, 125, tc.obstacles, false, false);
tc.testClass = tc.testClass.initialize(tc.domain, tc.domain.objective, tc.agents, 0, tc.timestep, tc.partitoningFreq, nIter, tc.obstacles, false, false);
% Constraint adjacency matrix defined by LNA should be as follows
tc.assertEqual(tc.testClass.constraintAdjacencyMatrix, logical( ...