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second attempt at plot1

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This commit is contained in:
Kevin Dee
2026-03-16 14:35:52 -07:00
parent 01f2af9102
commit a3837a6ef4
18 changed files with 165 additions and 160 deletions
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10
plot1.m
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@@ -1,6 +1,6 @@
clear;
% Load data
dataPath = fullfile('.', 'sandbox', 'plot1');
dataPath = fullfile('.', 'sandbox', 'plot1_3');
simHists = dir(dataPath); simHists = simHists(3:end);
simInits = simHists(endsWith({simHists.name}, 'miSimInits.mat'));
simHists = simHists(endsWith({simHists.name}, 'miSimHist.mat'));
@@ -83,11 +83,13 @@ for ii = 1:length(n_unique)
C = [C; [Cfinal(nIdx)]'];
end
bar(C);
set(x1, 'XTickLabel', string(n_unique));
xlabel("Number of agents");
ylabel("Final coverage (fraction of maximum)");
ylabel("Final coverage (normalized)");
title("Final performance of parameterizations");
legend(["$AI\alpha$"; "$AI\beta$"; "$AII\alpha$"; "$BI\beta$"], "Interpreter", "latex");
legend(["$AI\alpha$"; "$AI\beta$"; "$AII\alpha$"; "$BI\beta$"], "Interpreter", "latex", "Location", "northwest");
grid("on");
ylim([0, 1]);
f2 = figure;
x2 = axes;
@@ -152,4 +154,4 @@ grid(x2, "on");
yline(collisionRadius, 'r--', "Label", "Collision Radius", "LabelHorizontalAlignment", "left", "HandleVisibility", "off");
yline(commsRadius, 'r--', "Label", "Communications Radius", "LabelHorizontalAlignment", "left", "HandleVisibility", "off");
ylim([0, commsRadius + 5]);
ylim([0, inf]);

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<?xml version="1.0" encoding="UTF-8"?>
<Info/>

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<?xml version="1.0" encoding="UTF-8"?>
<Info location="1" type="DIR_SIGNIFIER"/>

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<?xml version="1.0" encoding="UTF-8"?>
<Info>
<Category UUID="FileClassCategory">
<Label UUID="test"/>
</Category>
</Info>

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<?xml version="1.0" encoding="UTF-8"?>
<Info location="results.m" type="File"/>

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<?xml version="1.0" encoding="UTF-8"?>
<Info/>

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<?xml version="1.0" encoding="UTF-8"?>
<Info location="1" type="DIR_SIGNIFIER"/>

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<?xml version="1.0" encoding="UTF-8"?>
<Info/>

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<?xml version="1.0" encoding="UTF-8"?>
<Info location="plot3" type="File"/>

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<?xml version="1.0" encoding="UTF-8"?>
<Info/>

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<?xml version="1.0" encoding="UTF-8"?>
<Info location="plot1_2" type="File"/>

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<?xml version="1.0" encoding="UTF-8"?>
<Info/>

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<?xml version="1.0" encoding="UTF-8"?>
<Info location="plot1_3" type="File"/>

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<?xml version="1.0" encoding="UTF-8"?>
<Info>
<Category UUID="FileClassCategory">
<Label UUID="design"/>
</Category>
</Info>

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<?xml version="1.0" encoding="UTF-8"?>
<Info location="plot1.m" type="File"/>

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<?xml version="1.0" encoding="UTF-8"?>
<Info/>

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<?xml version="1.0" encoding="UTF-8"?>
<Info location="1" type="DIR_SIGNIFIER"/>

265
test/results.m
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@@ -1,6 +1,7 @@
classdef results < matlab.unittest.TestCase
properties (Constant, Access = private)
seed = 1;
domainSize = [150, 150, 100]; % fixed domain size [X, Y, Z]
end
properties (Access = private)
@@ -25,16 +26,16 @@ classdef results < matlab.unittest.TestCase
%% Fixed Test Parameters
useFixedTopology = true; % No lesser neighbor, fixed network instead
minDimension = 50; % minimum domain size
maxDimension = 100; % maximum domain size
discretizationStep = 0.1;
discretizationStep = 0.5;
protectedRange = 5;
collisionRadius = 5;
sensorPerformanceMinimum = 0.005;
comRange = 20;
maxIter = 250;
maxIter = 400;
initialStepSize = 1;
numObstacles = 3;
% Each row: [minX minY minZ maxX maxY maxZ]
obstacleCorners = [results.domainSize(1)/2, results.domainSize(2)*5/8, 0, results.domainSize(1)*5/8, results.domainSize(2), 35;
results.domainSize(1)/3, 0, 0, results.domainSize(1)/2, results.domainSize(2)*3/8, 40];
barrierGain = 1;
barrierExponent = 1;
timestep = 0.5;
@@ -54,35 +55,35 @@ classdef results < matlab.unittest.TestCase
end
end
methods (Static, Access = private)
methods (Static, Access = public)
function c = makeConfigs()
rng(results.seed);
abMin = 6; % alpha*beta >= 6 ensures membership(0) = tanh(3) >= 0.995
alphaDist = rand(1, 2) .* [100, 100];
alphaDist = rand(1, 2) .* [75, 40];
betaDist = abMin ./ alphaDist + rand(1, 2) .* (20 - abMin ./ alphaDist);
alphaTilt = 10 + rand(1, 2) .* [20, 20];
betaTilt = abMin ./ alphaTilt + rand(1, 2) .* (50 - abMin ./ alphaTilt);
sensors = struct('alphaDist', num2cell(alphaDist), 'alphaTilt', num2cell(alphaTilt), 'betaDist', num2cell(betaDist), 'betaTilt', num2cell(betaTilt));
sensor1 = sigmoidSensor;
sensor2 = sigmoidSensor;
sensor1 = sensor1.initialize(sensors(1).alphaDist, sensors(1).betaDist, sensors(1).alphaTilt, sensors(1).betaTilt);
sensor2 = sensor2.initialize(sensors(2).alphaDist, sensors(2).betaDist, sensors(2).alphaTilt, sensors(2).betaTilt);
sensor1.plotParameters;
sensor2.plotParameters;
c = struct('A_1_alpha', struct('numDist', 1, 'sensor', sensors(1), 'doubleIntegrator', false), ...
'A_1_beta', struct('numDist', 1, 'sensor', sensors(1), 'doubleIntegrator', true), ...
'A_2_alpha', struct('numDist', 1, 'sensor', sensors(2), 'doubleIntegrator', false), ...
'B_1_beta', struct('numDist', 2, 'sensor', sensors(1), 'doubleIntegrator', true));
% sensor1 = sigmoidSensor;
% sensor2 = sigmoidSensor;
% sensor1 = sensor1.initialize(sensors(1).alphaDist, sensors(1).betaDist, sensors(1).alphaTilt, sensors(1).betaTilt);
% sensor2 = sensor2.initialize(sensors(2).alphaDist, sensors(2).betaDist, sensors(2).alphaTilt, sensors(2).betaTilt);
% sensor1.plotParameters;
% sensor2.plotParameters;
c = struct('A_1_alpha', struct('objectivePos', [3, 1] / 4 .* results.domainSize(1:2), 'sensor', sensors(1), 'doubleIntegrator', false), ...
'A_1_beta', struct('objectivePos', [3, 1] / 4 .* results.domainSize(1:2), 'sensor', sensors(1), 'doubleIntegrator', true), ...
'A_2_alpha', struct('objectivePos', [3, 1] / 4 .* results.domainSize(1:2), 'sensor', sensors(2), 'doubleIntegrator', false), ...
'B_1_beta', struct('objectivePos', [[3, 1] / 4 .* results.domainSize(1:2); [3, 1] / 4 .* results.domainSize(1:2) + 12.5 .* [-1, 1] ./ sqrt(2)], 'sensor', sensors(1), 'doubleIntegrator', true));
end
end
methods (Test)
function plot1_runs(tc, n, config)
% OVERRIDES
% function plot1_runs(tc)
% n = 3;
% config = struct('numDist', 1, 'sensor', struct('alphaDist', 100, 'alphaTilt', 2, 'betaDist', 10, 'betaTilt', 0.5), 'doubleIntegrator', false);
% if n == 5 && config.doubleIntegrator == true
% tc.makePlots = true;
% else
% tc.makePlots = false;
% end
% Compute test case index for reinit lookup
nKeys = fieldnames(tc.n);
configKeys = fieldnames(tc.config);
@@ -95,27 +96,21 @@ classdef results < matlab.unittest.TestCase
for reroll = 0:reinitCount
% Set up random cube domain
minAlt = tc.minDimension(1) * rand() * 0.5;
tc.testClass.domain = tc.testClass.domain.initializeRandom(REGION_TYPE.DOMAIN, "Domain", tc.minDimension, tc.maxDimension, tc.testClass.domain, minAlt);
% Place sensing objective(s)
objectiveMu = [];
% Set up fixed-size domain
minAlt = tc.domainSize(3)/10 + rand * 1/10 * tc.domainSize(3);
% Place sensing objective(s) at fixed positions from config
objectiveMu = config.objectivePos;
numDist = size(objectiveMu, 1);
objectiveSigma = [];
for ii = 1:config.numDist
mu = tc.testClass.domain.minCorner;
while tc.testClass.domain.distance(mu) < tc.protectedRange * 1.01
mu = tc.testClass.domain.random();
for ii = 1:numDist
sig = [200, 140; 140, 280];
if ~mod(ii, 2)
sig = rot90(sig, 2);
end
notPosDef = true;
while notPosDef
sig = reshape(sort(rand(1, 4) * min(tc.testClass.domain.dimensions(1:2))), [1, 2, 2]);
sig(1, 2, 1) = max([sig(1, 1, 2), sig(1, 2, 1)]);
sig(1, 1, 2) = sig(1, 2, 1);
[~, notPosDef] = chol(squeeze(sig));
end
objectiveMu = [objectiveMu; mu(1:2)];
sig = reshape(sig, [1, 2, 2]);
objectiveSigma = cat(1, objectiveSigma, sig);
end
tc.testClass.domain = tc.testClass.domain.initialize([zeros(1, 3); tc.domainSize], REGION_TYPE.DOMAIN, "Domain");
tc.testClass.domain.objective = tc.testClass.domain.objective.initialize(objectiveFunctionWrapper(objectiveMu, objectiveSigma), tc.testClass.domain, tc.discretizationStep, tc.protectedRange, tc.sensorPerformanceMinimum, objectiveMu, objectiveSigma);
% Initialize agents
@@ -126,28 +121,44 @@ classdef results < matlab.unittest.TestCase
sensorModel = sigmoidSensor;
sensorModel = sensorModel.initialize(config.sensor.alphaDist, config.sensor.betaDist, config.sensor.alphaTilt, config.sensor.betaTilt);
% Place agents in a quadrant that contains no objective peaks
% Initialize fixed obstacles from corner coordinates
nObs = size(tc.obstacleCorners, 1);
obstacles = cell(nObs, 1);
for jj = 1:nObs
corners = [tc.obstacleCorners(jj, 1:3); tc.obstacleCorners(jj, 4:6)];
obstacles{jj} = rectangularPrism;
obstacles{jj} = obstacles{jj}.initialize(corners, REGION_TYPE.OBSTACLE, sprintf("Obstacle %d", jj));
end
% Place agents in small-x, large-y quadrant (opposite objectives)
% with chain topology: each agent connected only to its neighbors
midXY = (tc.testClass.domain.minCorner(1:2) + tc.testClass.domain.maxCorner(1:2)) / 2;
occupied = false(2, 2);
for ii = 1:size(objectiveMu, 1)
occupied(1 + (objectiveMu(ii, 1) >= midXY(1)), ...
1 + (objectiveMu(ii, 2) >= midXY(2))) = true;
quadrantSize = tc.testClass.domain.maxCorner(1:2) / 2;
margin = quadrantSize / 6;
agentBounds = [tc.testClass.domain.minCorner(1) + margin(1), ...
midXY(2) + margin(2); ...
midXY(1) - margin(1), ...
tc.testClass.domain.maxCorner(2) - margin(2)];
% Find a fixed altitude where sensor performance passes at ALL
% corners of the placement bounds (worst-case XY)
corners = [agentBounds(1,1), agentBounds(1,2);
agentBounds(2,1), agentBounds(1,2);
agentBounds(1,1), agentBounds(2,2);
agentBounds(2,1), agentBounds(2,2)];
agentAlt = tc.testClass.domain.maxCorner(3) - tc.collisionRadius;
while agentAlt > minAlt + 2 * tc.collisionRadius
worstPerf = inf;
for cc = 1:4
p = sensorModel.sensorPerformance([corners(cc,:), agentAlt], [corners(cc,:), 0]);
worstPerf = min(worstPerf, p);
end
freeQ = find(~occupied);
if isempty(freeQ)
qi = 1;
else
qi = freeQ(randi(numel(freeQ)));
if worstPerf >= tc.sensorPerformanceMinimum * 10
break;
end
[xi, yi] = ind2sub([2, 2], qi);
xLim = [tc.testClass.domain.minCorner(1), midXY(1), tc.testClass.domain.maxCorner(1)];
yLim = [tc.testClass.domain.minCorner(2), midXY(2), tc.testClass.domain.maxCorner(2)];
agentBounds = [max(xLim(xi), tc.testClass.domain.minCorner(1) + tc.collisionRadius), ...
max(yLim(yi), tc.testClass.domain.minCorner(2) + tc.collisionRadius), ...
minAlt + tc.collisionRadius; ...
min(xLim(xi+1), tc.testClass.domain.maxCorner(1) - tc.collisionRadius), ...
min(yLim(yi+1), tc.testClass.domain.maxCorner(2) - tc.collisionRadius), ...
tc.testClass.domain.maxCorner(3) - tc.collisionRadius];
agentAlt = agentAlt - 1;
end
chainSpacingMin = 0.7 * tc.comRange;
chainSpacingMax = 0.9 * tc.comRange;
collisionGeometry = spherical;
for jj = 1:n
retry = true;
@@ -155,54 +166,66 @@ classdef results < matlab.unittest.TestCase
retry = false;
if jj == 1
% First agent: uniform random within placement bounds
agentPos = agentBounds(1, :) + (agentBounds(2, :) - agentBounds(1, :)) .* rand(1, 3);
% First agent: random XY within bounds, fixed altitude
agentPos = [agentBounds(1, :) + (agentBounds(2, :) - agentBounds(1, :)) .* rand(1, 2), agentAlt];
else
% Sample near centroid of existing agents to maximize
% probability of being within comRange of all others
positions = cell2mat(cellfun(@(x) x.pos, agents(1:(jj-1)), 'UniformOutput', false));
centroid = mean(positions, 1);
maxSpread = max(vecnorm(positions - centroid, 2, 2));
safeRadius = tc.comRange - maxSpread;
if safeRadius > 2 * tc.collisionRadius
% Uniform random within guaranteed-connected sphere
dir = randn(1, 3);
% Place at 0.7-0.9 * comRange in XY from previous agent, same altitude
dir = randn(1, 2);
dir = dir / norm(dir);
r = safeRadius * rand()^(1/3);
agentPos = centroid + r * dir;
else
% Safe sphere too small; sample within comms sphere
% of random existing agent (comRange check below)
baseIdx = randi(jj - 1);
agentPos = agents{baseIdx}.commsGeometry.random();
end
r = chainSpacingMin + rand * (chainSpacingMax - chainSpacingMin);
agentPos = [agents{jj-1}.pos(1:2) + r * dir, agentAlt];
end
% Check within placement bounds
if any(agentPos <= agentBounds(1, :)) || any(agentPos >= agentBounds(2, :))
% Check within placement bounds (XY only, Z is fixed)
if any(agentPos(1:2) <= agentBounds(1, :)) || any(agentPos(1:2) >= agentBounds(2, :))
retry = true;
continue;
end
% Check sensor performance threshold
% Check sensor performance threshold; lower altitude if it fails
if sensorModel.sensorPerformance(agentPos, [agentPos(1:2), 0]) < tc.sensorPerformanceMinimum * 10
agentAlt = max(agentAlt - tc.collisionRadius, minAlt + 1.1 * tc.collisionRadius);
agentPos(3) = agentAlt;
% If we've hit the floor and still failing, widen XY search
if agentAlt <= minAlt + 2 * tc.collisionRadius
agentBounds = [tc.testClass.domain.minCorner(1) + tc.collisionRadius, ...
tc.testClass.domain.minCorner(2) + tc.collisionRadius; ...
tc.testClass.domain.maxCorner(1) - tc.collisionRadius, ...
tc.testClass.domain.maxCorner(2) - tc.collisionRadius];
end
retry = true;
continue;
end
% Check within comRange of ALL existing agents (complete graph)
% Must be within comRange of previous agent (chain link)
if jj > 1 && norm(agents{jj-1}.pos - agentPos) >= tc.comRange
retry = true;
continue;
end
% Must be BEYOND comRange of all non-adjacent agents (sparsity)
% for kk = 1:(jj - 2)
% if norm(agents{kk}.pos - agentPos) < tc.comRange
% retry = true;
% break;
% end
% end
% if retry, continue; end
% No collision with any existing agent
for kk = 1:(jj - 1)
if norm(agents{kk}.pos - agentPos) >= tc.comRange
if norm(agents{kk}.pos - agentPos) < agents{kk}.collisionGeometry.radius + tc.collisionRadius
retry = true;
break;
end
end
if retry, continue; end
% Check collision with ALL existing agents
for kk = 1:(jj - 1)
if norm(agents{kk}.pos - agentPos) < agents{kk}.collisionGeometry.radius + tc.collisionRadius
% No collision with any obstacle
for kk = 1:nObs
P = min(max(agentPos, obstacles{kk}.minCorner), obstacles{kk}.maxCorner);
d = agentPos - P;
if dot(d, d) <= tc.collisionRadius^2
retry = true;
break;
end
@@ -217,71 +240,6 @@ classdef results < matlab.unittest.TestCase
% Randomly shuffle agents to vary index-based topology
agents = agents(randperm(numel(agents)));
% Add random obstacles (each limited to 1/4 domain size in X and Y)
obstacles = cell(tc.numObstacles, 1);
[obstacles{:}] = deal(rectangularPrism);
% Define target region for obstacles (between agents and objective)
agentExtent = max(cell2mat(cellfun(@(x) x.pos(1:2), agents, "UniformOutput", false))) + max(cellfun(@(x) x.collisionGeometry.radius, agents));
objExtent = tc.testClass.domain.objective.groundPos - tc.testClass.domain.objective.protectedRange;
obsMin = zeros(1, 2);
obsMax = zeros(1, 2);
for dim = 1:2
if agentExtent(dim) < objExtent(dim)
obsMin(dim) = agentExtent(dim);
obsMax(dim) = objExtent(dim);
else
obsMin(dim) = tc.testClass.domain.minCorner(dim);
obsMax(dim) = tc.testClass.domain.maxCorner(dim);
end
end
maxObsSize = 3 * tc.collisionRadius * ones(1, 3);
for jj = 1:size(obstacles, 1)
retry = true;
while retry
retry = false;
% Generate random anchor point, then random size up to 3x collision radius
anchor = [obsMin + rand(1, 2) .* (obsMax - obsMin), minAlt];
obsSize = rand(1, 3) .* maxObsSize;
corners = [anchor; anchor + obsSize];
% Initialize obstacle using proposed coordinates
obstacles{jj} = obstacles{jj}.initialize(corners, REGION_TYPE.OBSTACLE, sprintf("Obstacle %d", jj));
% Make sure the obstacle doesn't crowd the objective
for kk = 1:size(tc.testClass.domain.objective.groundPos, 1)
if ~retry && obstacles{jj}.distance([tc.testClass.domain.objective.groundPos(kk, 1:2), minAlt]) <= tc.testClass.domain.objective.protectedRange
retry = true;
continue;
end
end
% Check if the obstacle collides with an existing obstacle
if ~retry && jj > 1 && tc.obstacleCollisionCheck(obstacles(1:(jj - 1)), obstacles{jj})
retry = true;
continue;
end
% Check if the obstacle collides with an agent
if ~retry
for kk = 1:size(agents, 1)
P = min(max(agents{kk}.pos, obstacles{jj}.minCorner), obstacles{jj}.maxCorner);
d = agents{kk}.pos - P;
if dot(d, d) <= agents{kk}.collisionGeometry.radius^2
retry = true;
break;
end
end
end
if retry
continue;
end
end
end
end % reroll loop
% Inspect scenario if enabled
@@ -305,6 +263,11 @@ classdef results < matlab.unittest.TestCase
% Cleanup
tc.testClass = tc.testClass.teardown();
close all;
end
function AIIbeta_plots_3_4(tc)
configs = results.makeConfigs();
config = configs.A_2_alpha;
end
end