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fixed unit tests

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This commit is contained in:
Kevin Dee
2026-01-13 23:16:41 -08:00
parent bcb3bc3da3
commit 2604711c78
15 changed files with 160 additions and 89 deletions
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10
@agent/agent.m
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@@ -3,13 +3,13 @@ classdef agent
% Identifiers
label = "";
% Sensor
sensorModel;
% State
lastPos = NaN(1, 3); % position from previous timestep
pos = NaN(1, 3); % current position
% Sensor
sensorModel;
% Collision
collisionGeometry;
@@ -17,10 +17,10 @@ classdef agent
fovGeometry;
% Communication
comRange = NaN;
commsGeometry = spherical;
lesserNeighbors = [];
% Performance
performance = 0;
% Plotting
@@ -29,7 +29,7 @@ classdef agent
end
properties (SetAccess = private, GetAccess = public)
initialStepSize = 0.2;
initialStepSize = NaN;
stepDecayRate = NaN;
end

4
@agent/initialize.m
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@@ -1,4 +1,4 @@
function obj = initialize(obj, pos, collisionGeometry, sensorModel, comRange, maxIter, label, plotCommsGeometry)
function obj = initialize(obj, pos, collisionGeometry, sensorModel, comRange, maxIter, initialStepSize, label, plotCommsGeometry)
arguments (Input)
obj (1, 1) {mustBeA(obj, 'agent')};
pos (1, 3) double;
@@ -6,6 +6,7 @@ function obj = initialize(obj, pos, collisionGeometry, sensorModel, comRange, ma
sensorModel (1, 1) {mustBeSensor};
comRange (1, 1) double;
maxIter (1, 1) double;
initialStepSize (1, 1) double = 0.2;
label (1, 1) string = "";
plotCommsGeometry (1, 1) logical = false;
end
@@ -18,6 +19,7 @@ function obj = initialize(obj, pos, collisionGeometry, sensorModel, comRange, ma
obj.sensorModel = sensorModel;
obj.label = label;
obj.plotCommsGeometry = plotCommsGeometry;
obj.initialStepSize = initialStepSize;
obj.stepDecayRate = obj.initialStepSize / maxIter;
% Initialize performance vector

24
@miSim/constrainMotion.m
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@@ -14,7 +14,7 @@ function [obj] = constrainMotion(obj)
agents = [obj.agents{:}];
v = reshape(([agents.pos] - [agents.lastPos])./obj.timestep, 3, size(obj.agents, 1))';
if all(isnan(v)) || all(v == zeros(1, 3))
if all(isnan(v), 'all') || all(v == zeros(size(obj.agents, 1), 3), 'all')
% Agents are not attempting to move, so there is no motion to be
% constrained
return;
@@ -39,7 +39,7 @@ function [obj] = constrainMotion(obj)
A(kk, (3 * ii - 2):(3 * ii)) = -2 * (agents(ii).pos - agents(jj).pos);
A(kk, (3 * jj - 2):(3 * jj)) = -A(kk, (3 * ii - 2):(3 * ii));
b(kk) = obj.barrierGain * h(ii, jj)^3;
b(kk) = obj.barrierGain * h(ii, jj)^obj.barrierExponent;
kk = kk + 1;
end
end
@@ -54,7 +54,7 @@ function [obj] = constrainMotion(obj)
hObs(ii, jj) = dot(agents(ii).pos - cPos, agents(ii).pos - cPos) - agents(ii).collisionGeometry.radius^2;
A(kk, (3 * ii - 2):(3 * ii)) = -2 * (agents(ii).pos - cPos);
b(kk) = obj.barrierGain * hObs(ii, jj)^3;
b(kk) = obj.barrierGain * hObs(ii, jj)^obj.barrierExponent;
kk = kk + 1;
end
@@ -67,37 +67,37 @@ function [obj] = constrainMotion(obj)
% X minimum
h_xMin = (agents(ii).pos(1) - obj.domain.minCorner(1)) - agents(ii).collisionGeometry.radius;
A(kk, (3 * ii - 2):(3 * ii)) = [-1, 0, 0];
b(kk) = obj.barrierGain * h_xMin^3;
b(kk) = obj.barrierGain * h_xMin^obj.barrierExponent;
kk = kk + 1;
% X maximum
h_xMax = (obj.domain.maxCorner(1) - agents(ii).pos(1)) - agents(ii).collisionGeometry.radius;
A(kk, (3 * ii - 2):(3 * ii)) = [1, 0, 0];
b(kk) = obj.barrierGain * h_xMax^3;
b(kk) = obj.barrierGain * h_xMax^obj.barrierExponent;
kk = kk + 1;
% Y minimum
h_yMin = (agents(ii).pos(2) - obj.domain.minCorner(2)) - agents(ii).collisionGeometry.radius;
A(kk, (3 * ii - 2):(3 * ii)) = [0, -1, 0];
b(kk) = obj.barrierGain * h_yMin^3;
b(kk) = obj.barrierGain * h_yMin^obj.barrierExponent;
kk = kk + 1;
% Y maximum
h_yMax = (obj.domain.maxCorner(2) - agents(ii).pos(2)) - agents(ii).collisionGeometry.radius;
A(kk, (3 * ii - 2):(3 * ii)) = [0, 1, 0];
b(kk) = obj.barrierGain * h_yMax^3;
b(kk) = obj.barrierGain * h_yMax^obj.barrierExponent;
kk = kk + 1;
% Z minimum
h_zMin = (agents(ii).pos(3) - obj.domain.minCorner(3)) - agents(ii).collisionGeometry.radius;
A(kk, (3 * ii - 2):(3 * ii)) = [0, 0, -1];
b(kk) = obj.barrierGain * h_zMin^3;
b(kk) = obj.barrierGain * h_zMin^obj.barrierExponent;
kk = kk + 1;
% Z maximum
h_zMax = (obj.domain.maxCorner(2) - agents(ii).pos(2)) - agents(ii).collisionGeometry.radius;
A(kk, (3 * ii - 2):(3 * ii)) = [0, 0, 1];
b(kk) = obj.barrierGain * h_zMax^3;
b(kk) = obj.barrierGain * h_zMax^obj.barrierExponent;
kk = kk + 1;
end
@@ -114,11 +114,7 @@ function [obj] = constrainMotion(obj)
A(kk, (3 * ii - 2):(3 * ii)) = 2 * (agents(ii).pos - agents(jj).pos);
A(kk, (3 * jj - 2):(3 * jj)) = -A(kk, (3 * ii - 2):(3 * ii));
b(kk) = obj.barrierGain * hComms(ii, jj);
% dVNominal = v(ii, 1:3) - v(jj, 1:3); % nominal velocities
% h_dot_nom = -2 * (agents(ii).pos - agents(jj).pos) * dVNominal';
% b(kk) = -h_dot_nom + obj.barrierGain * hComms(ii, jj)^3;
b(kk) = obj.barrierGain * hComms(ii, jj)^obj.barrierExponent;
kk = kk + 1;
end

19
@miSim/initialize.m
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@@ -1,8 +1,10 @@
function obj = initialize(obj, domain, agents, minAlt, timestep, maxIter, obstacles, makePlots, makeVideo)
function [obj] = initialize(obj, domain, agents, barrierGain, barrierExponent, minAlt, timestep, maxIter, obstacles, makePlots, makeVideo)
arguments (Input)
obj (1, 1) {mustBeA(obj, 'miSim')};
domain (1, 1) {mustBeGeometry};
agents (:, 1) cell;
barrierGain (1, 1) double = 100;
barrierExponent (1, 1) double = 3;
minAlt (1, 1) double = 1;
timestep (:, 1) double = 0.05;
maxIter (:, 1) double = 1000;
@@ -24,6 +26,9 @@ function obj = initialize(obj, domain, agents, minAlt, timestep, maxIter, obstac
end
obj.makeVideo = makeVideo;
% Generate artifact(s) name
obj.artifactName = strcat(string(datetime('now'), 'yyyy_MM_dd_HH_mm_ss'));
% Define simulation time parameters
obj.timestep = timestep;
obj.timestepIndex = 0;
@@ -37,10 +42,9 @@ function obj = initialize(obj, domain, agents, minAlt, timestep, maxIter, obstac
% Add an additional obstacle spanning the domain's footprint to
% represent the minimum allowable altitude
obj.minAlt = minAlt;
if obj.minAlt > 0
if minAlt > 0
obj.obstacles{end + 1, 1} = rectangularPrism;
obj.obstacles{end, 1} = obj.obstacles{end, 1}.initialize([obj.domain.minCorner; obj.domain.maxCorner(1:2), obj.minAlt], "OBSTACLE", "Minimum Altitude Domain Constraint");
obj.obstacles{end, 1} = obj.obstacles{end, 1}.initialize([obj.domain.minCorner; obj.domain.maxCorner(1:2), minAlt], "OBSTACLE", "Minimum Altitude Domain Constraint");
end
% Define agents
@@ -61,6 +65,10 @@ function obj = initialize(obj, domain, agents, minAlt, timestep, maxIter, obstac
end
end
% Set CBF parameters
obj.barrierGain = barrierGain;
obj.barrierExponent = barrierExponent;
% Compute adjacency matrix and lesser neighbors
obj = obj.updateAdjacency();
obj = obj.lesserNeighbor();
@@ -83,4 +91,7 @@ function obj = initialize(obj, domain, agents, minAlt, timestep, maxIter, obstac
% Set up plots showing initialized state
obj = obj.plot();
% Run validations
obj.validate();
end

9
@miSim/miSim.m
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@@ -5,7 +5,6 @@ classdef miSim
properties (SetAccess = private, GetAccess = public)
timestep = NaN; % delta time interval for simulation iterations
timestepIndex = NaN; % index of the current timestep (useful for time-indexed arrays)
partitioningFreq = NaN; % number of simulation timesteps at which the partitioning routine is re-run
maxIter = NaN; % maximum number of simulation iterations
domain = rectangularPrism;
objective = sensingObjective;
@@ -16,9 +15,9 @@ classdef miSim
partitioning = NaN;
perf; % sensor performance timeseries array
performance = 0; % simulation performance timeseries vector
barrierGain = 100; % collision avoidance parameter
minAlt = 1; % minimum allowed altitude constraint
barrierGain = 100; % CBF gain parameter
barrierExponent = 3; % CBF exponent parameter
artifactName = "";
fPerf; % performance plot figure
end
@@ -55,7 +54,7 @@ classdef miSim
end
methods (Access = public)
[obj] = initialize(obj, domain, agents, timestep, partitoningFreq, maxIter, obstacles);
[obj] = initialize(obj, domain, agents, barrierGain, barrierExponent, minAlt, timestep, maxIter, obstacles, makePlots, makeVideo);
[obj] = run(obj);
[obj] = lesserNeighbor(obj);
[obj] = constrainMotion(obj);

3
@miSim/plot.m
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@@ -51,4 +51,7 @@ function obj = plot(obj)
% Plot h functions
obj = obj.plotH();
% Switch back to primary figure
figure(obj.f);
end

4
@miSim/setupVideoWriter.m
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@@ -7,9 +7,9 @@ function v = setupVideoWriter(obj)
end
if ispc || ismac
v = VideoWriter(fullfile('sandbox', strcat(string(datetime('now'), 'yyyy_MM_dd_HH_mm_ss'), '_miSimHist')), 'MPEG-4');
v = VideoWriter(fullfile(matlab.project.rootProject().RootFolder, 'sandbox', strcat(obj.artifactName, "_miSimHist")), 'MPEG-4');
elseif isunix
v = VideoWriter(fullfile('.', strcat(string(datetime('now'), 'yyyy_MM_dd_HH_mm_ss'), '_miSimHist')), 'Motion JPEG AVI');
v = VideoWriter(fullfile(matlab.project.rootProject().RootFolder, 'sandbox', strcat(obj.artifactName, "_miSimHist")), 'Motion JPEG AVI');
end
v.FrameRate = 1 / obj.timestep;

10
@miSim/validate.m
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@@ -14,6 +14,14 @@ function validate(obj)
warning("Eliminated network connections that were necessary");
end
%%
%% Obstacle Validators
AO_collisions = cellfun(@(a) cellfun(@(o) o.contains(a.pos), obj.obstacles), obj.agents, 'UniformOutput', false);
AO_collisions = vertcat(AO_collisions{:});
if any(AO_collisions)
[idx, idy] = find(AO_collisions);
for ii = 1:size(idx, 1)
error("Agent(s) %d colliding with obstacle(s) %d", idx(ii), idy(ii));
end
end
end

25
@miSim/writeParams.m Normal file
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@@ -0,0 +1,25 @@
function writeParams(obj)
arguments (Input)
obj (1, 1) {mustBeA(obj, 'miSim')};
end
arguments (Output)
end
% Collect agent parameters
collisionRadii = cellfun(@(x) x.collisionGeometry.radius, obj.agents);
alphaDist = cellfun(@(x) x.sensorModel.alphaDist, obj.agents);
betaDist = cellfun(@(x) x.sensorModel.betaDist, obj.agents);
alphaTilt = cellfun(@(x) x.sensorModel.alphaTilt, obj.agents);
betaTilt = cellfun(@(x) x.sensorModel.alphaDist, obj.agents);
comRange = cellfun(@(x) x.commsGeometry.radius, obj.agents);
% Combine with simulation parameters
params = struct('timestep', obj.timestep, 'maxIter', obj.maxIter, 'minAlt', obj.obstacles{end}.maxCorner(3), 'discretizationStep', obj.domain.objective.discretizationStep, ...
'collisionRadius', collisionRadii, 'alphaDist', alphaDist, 'betaDist', betaDist, ...
'alphaTilt', alphaTilt, 'betaTilt', betaTilt, 'comRange', comRange);
% Save all parameters to output file
paramsFile = strcat(obj.artifactName, "_miSimParams");
paramsFile = fullfile(matlab.project.rootProject().RootFolder, 'sandbox', paramsFile);
save(paramsFile, "-struct", "params");
end

12
@sensingObjective/sensingObjective.m
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@@ -2,15 +2,15 @@ classdef sensingObjective
% Sensing objective definition parent class
properties (SetAccess = private, GetAccess = public)
label = "";
groundAlt = 0;
groundPos = [0, 0];
discretizationStep = 1;
objectiveFunction = @(x, y) 0; % define objective functions over a grid in this manner
groundAlt = NaN;
groundPos = [NaN, NaN];
discretizationStep = NaN;
objectiveFunction = @(x, y) NaN; % define objective functions over a grid in this manner
X = [];
Y = [];
values = [];
protectedRange = 1; % keep obstacles from crowding objective
sensorPerformanceMinimum = 1e-6; % minimum sensor performance to allow assignment of a point in the domain to a partition
protectedRange = NaN; % keep obstacles from crowding objective
sensorPerformanceMinimum = NaN; % minimum sensor performance to allow assignment of a point in the domain to a partition
end
methods (Access = public)

2
geometries/@rectangularPrism/initializeRandom.m
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@@ -6,7 +6,7 @@ function [obj] = initializeRandom(obj, tag, label, minDimension, maxDimension, d
minDimension (1, 1) double = 10;
maxDimension (1, 1) double = 20;
domain (1, 1) {mustBeGeometry} = rectangularPrism;
minAlt (1, 1) double = 0;
minAlt (1, 1) double = 1;
end
arguments (Output)
obj (1, 1) {mustBeA(obj, 'rectangularPrism')};

6
resources/project/SIL3u_W39LwE7HHYsarfFmr9gVQ/BtZvZtLyHugR7nfGjg6ukY77EG0d.xml Normal file
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@@ -0,0 +1,6 @@
<?xml version="1.0" encoding="UTF-8"?>
<Info>
<Category UUID="FileClassCategory">
<Label UUID="design"/>
</Category>
</Info>

2
resources/project/SIL3u_W39LwE7HHYsarfFmr9gVQ/BtZvZtLyHugR7nfGjg6ukY77EG0p.xml Normal file
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@@ -0,0 +1,2 @@
<?xml version="1.0" encoding="UTF-8"?>
<Info location="writeParams.m" type="File"/>

25
test/parametricTestSuite.m
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@@ -7,7 +7,6 @@ classdef parametricTestSuite < matlab.unittest.TestCase
%% Diagnostic Parameters
% No effect on simulation dynamics
timestep = 1;
makeVideo = true; % disable video writing for big performance increase
makePlots = true; % disable plotting for big performance increase (also disables video)
plotCommsGeometry = false; % disable plotting communications geometries
@@ -15,16 +14,25 @@ classdef parametricTestSuite < matlab.unittest.TestCase
end
properties (TestParameter)
%% Simulation Parameters
timestep = num2cell([1]); % duration of one simulation timestep
maxIter = num2cell([25]); % number of timesteps to run
% Domain parameters
minAlt = num2cell([1]); % minimum allowed agent altitude, make sure test cases don't conflict with this
% Constraint parameters
barrierGain = num2cell([100]);
barrierExponent = num2cell([3]);
% Sensing Objective Parameters
discretizationStep = num2cell([0.01]);
sensorPerformanceMinimum = num2cell([1e-6]); % sensor performance threshhold for partition assignment
discretizationStep = num2cell([0.01]); % sensing objective discretization step size
% this value goes on to determine central differences used in
% gradient ascent and partitioning element sizes
% Agent Parameters
collisionRadius = num2cell([0.1]);
initialStepSize = num2cell([0.2]); % gradient ascent step size at the first iteration. Decreases linearly to 0 based on maxIter.
% Sensor Model Parameters
alphaDist = num2cell([2.5, 5]);
@@ -38,23 +46,26 @@ classdef parametricTestSuite < matlab.unittest.TestCase
methods (Test, ParameterCombination = "exhaustive")
% Test cases
function single_agent_gradient_ascent(tc, maxIter, minAlt, discretizationStep, collisionRadius, alphaDist, betaDist, alphaTilt, betaTilt, comRange)
function single_agent_gradient_ascent(tc, timestep, maxIter, barrierGain, barrierExponent, minAlt, sensorPerformanceMinimum, discretizationStep, collisionRadius, initialStepSize, alphaDist, betaDist, alphaTilt, betaTilt, comRange)
% Set up square domain
l = 10;
tc.domain = tc.domain.initialize([zeros(1, 3); l * ones(1, 3)], REGION_TYPE.DOMAIN, "Domain");
tc.domain.objective = tc.domain.objective.initialize(objectiveFunctionWrapper([.75 * l, 0.75 * l]), tc.domain, discretizationStep, tc.protectedRange);
tc.domain.objective = tc.domain.objective.initialize(objectiveFunctionWrapper([.75 * l, 0.75 * l]), tc.domain, discretizationStep, tc.protectedRange, sensorPerformanceMinimum);
% Set up agent
sensorModel = sigmoidSensor;
sensorModel = sensorModel.initialize(alphaDist, betaDist, alphaTilt, betaTilt);
agentPos = [l/4, l/4, 3*l/4];
agentPos = [l/4, l/4, l/4];
collisionGeometry = spherical;
collisionGeometry = collisionGeometry.initialize(agentPos, collisionRadius, REGION_TYPE.COLLISION, "Agent 1 Collision Region");
agents = {agent};
agents{1} = agents{1}.initialize(agentPos, collisionGeometry, sensorModel, comRange, maxIter, "Agent 1", tc.plotCommsGeometry);
agents{1} = agents{1}.initialize(agentPos, collisionGeometry, sensorModel, comRange, maxIter, initialStepSize, "Agent 1", tc.plotCommsGeometry);
% Set up simulation
tc.testClass = tc.testClass.initialize(tc.domain, agents, minAlt, tc.timestep, maxIter, tc.obstacles, tc.makePlots, tc.makeVideo);
tc.testClass = tc.testClass.initialize(tc.domain, agents, barrierGain, barrierExponent, minAlt, timestep, maxIter, tc.obstacles, tc.makePlots, tc.makeVideo);
% Save simulation parameters to output file
tc.testClass.writeParams();
% Run
tc.testClass = tc.testClass.run();

94
test/test_miSim.m
View File

@@ -9,7 +9,7 @@ classdef test_miSim < matlab.unittest.TestCase
plotCommsGeometry = false; % disable plotting communications geometries
% Sim
maxIter = 250;
maxIter = 50;
timestep = 0.05;
% Domain
@@ -30,6 +30,7 @@ classdef test_miSim < matlab.unittest.TestCase
objective = sensingObjective;
% Agents
initialStepSize = 0.2; % gradient ascent step size at the first iteration. Decreases linearly to 0 based on maxIter.
minAgents = 3; % Minimum number of agents to be randomly generated
maxAgents = 4; % Maximum number of agents to be randomly generated
agents = cell(0, 1);
@@ -51,6 +52,10 @@ classdef test_miSim < matlab.unittest.TestCase
% Communications
comRange = 8; % Maximum range between agents that forms a communications link
% Constraints
barrierGain = 100;
barrierExponent = 3;
end
% Setup for each test
@@ -160,7 +165,7 @@ classdef test_miSim < matlab.unittest.TestCase
sensor = sensor.initialize(tc.alphaDistMin + rand * (tc.alphaDistMax - tc.alphaDistMin), tc.betaDistMin + rand * (tc.betaDistMax - tc.betaDistMin), tc.alphaTiltMin + rand * (tc.alphaTiltMax - tc.alphaTiltMin), tc.betaTiltMin + rand * (tc.betaTiltMax - tc.betaTiltMin));
% Initialize candidate agent
newAgent = tc.agents{ii}.initialize(candidatePos, candidateGeometry, sensor, tc.comRange, tc.maxIter);
newAgent = tc.agents{ii}.initialize(candidatePos, candidateGeometry, sensor, tc.comRange, tc.maxIter, tc.initialStepSize);
% Make sure candidate agent doesn't collide with
% domain
@@ -208,7 +213,7 @@ classdef test_miSim < matlab.unittest.TestCase
end
% Initialize the simulation
tc.testClass = tc.testClass.initialize(tc.domain, tc.agents, tc.minAlt, tc.timestep, tc.maxIter, tc.obstacles, tc.makeVideo);
tc.testClass = tc.testClass.initialize(tc.domain, tc.agents, tc.barrierGain, tc.barrierExponent, tc.minAlt, tc.timestep, tc.maxIter, tc.obstacles, tc.makeVideo);
end
function misim_run(tc)
% randomly create obstacles
@@ -294,7 +299,7 @@ classdef test_miSim < matlab.unittest.TestCase
sensor = sensor.initialize(tc.alphaDistMin + rand * (tc.alphaDistMax - tc.alphaDistMin), tc.betaDistMin + rand * (tc.betaDistMax - tc.betaDistMin), tc.alphaTiltMin + rand * (tc.alphaTiltMax - tc.alphaTiltMin), tc.betaTiltMin + rand * (tc.betaTiltMax - tc.betaTiltMin));
% Initialize candidate agent
newAgent = tc.agents{ii}.initialize(candidatePos, candidateGeometry, sensor, tc.comRange, tc.maxIter);
newAgent = tc.agents{ii}.initialize(candidatePos, candidateGeometry, sensor, tc.comRange, tc.maxIter, tc.initialStepSize);
% Make sure candidate agent doesn't collide with
% domain
@@ -342,7 +347,10 @@ classdef test_miSim < matlab.unittest.TestCase
end
% Initialize the simulation
tc.testClass = tc.testClass.initialize(tc.domain, tc.agents, tc.minAlt, tc.timestep, tc.maxIter, tc.obstacles, tc.makeVideo);
tc.testClass = tc.testClass.initialize(tc.domain, tc.agents, tc.barrierGain, tc.barrierExponent, tc.minAlt, tc.timestep, tc.maxIter, tc.obstacles, tc.makeVideo);
% Write out parameters
tc.testClass.writeParams();
% Run simulation loop
tc.testClass = tc.testClass.run();
@@ -376,17 +384,17 @@ 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], geometry1, sensor, 3*d, tc.maxIter);
tc.agents{2} = tc.agents{2}.initialize(tc.domain.center + dh - [d, 0, 0], geometry2, sensor, 3*d, tc.maxIter);
tc.agents{1} = tc.agents{1}.initialize(tc.domain.center + dh + [d, 0, 0], geometry1, sensor, 3*d, tc.maxIter, tc.initialStepSize);
tc.agents{2} = tc.agents{2}.initialize(tc.domain.center + dh - [d, 0, 0], geometry2, sensor, 3*d, tc.maxIter, tc.initialStepSize);
% Optional third agent along the +Y axis
geometry3 = rectangularPrism;
geometry3 = geometry3.initialize([tc.domain.center + dh - [0, d, 0] - tc.collisionRanges(1) * ones(1, 3); tc.domain.center + dh - [0, d, 0] + tc.collisionRanges(1) * ones(1, 3)], REGION_TYPE.COLLISION);
tc.agents{3} = agent;
tc.agents{3} = tc.agents{3}.initialize(tc.domain.center + dh - [0, d, 0], geometry3, sensor, 3*d, tc.maxIter);
tc.agents{3} = tc.agents{3}.initialize(tc.domain.center + dh - [0, d, 0], geometry3, sensor, 3*d, tc.maxIter, tc.initialStepSize);
% Initialize the simulation
tc.testClass = tc.testClass.initialize(tc.domain, tc.agents, tc.minAlt, tc.timestep, tc.maxIter, cell(0, 1), false, false);
tc.testClass = tc.testClass.initialize(tc.domain, tc.agents, tc.barrierGain, tc.barrierExponent, tc.minAlt, tc.timestep, tc.maxIter, cell(0, 1), false, false);
tc.verifyEqual(tc.testClass.partitioning(500, 500:502), [2, 3, 1]); % all three near center
tc.verifyLessThan(sum(tc.testClass.partitioning == 1, 'all'), sum(tc.testClass.partitioning == 0, 'all')); % more non-assignments than partition 1 assignments
@@ -418,10 +426,10 @@ classdef test_miSim < matlab.unittest.TestCase
% Initialize agents
tc.agents = {agent};
tc.agents{1} = tc.agents{1}.initialize([tc.domain.center(1:2), 3], geometry1, sensor, 3, tc.maxIter);
tc.agents{1} = tc.agents{1}.initialize([tc.domain.center(1:2), 3], geometry1, sensor, 3, tc.maxIter, tc.initialStepSize);
% Initialize the simulation
tc.testClass = tc.testClass.initialize(tc.domain, tc.agents, tc.minAlt, tc.timestep, tc.maxIter, cell(0, 1), false, false);
tc.testClass = tc.testClass.initialize(tc.domain, tc.agents, tc.barrierGain, tc.barrierExponent, tc.minAlt, tc.timestep, tc.maxIter, cell(0, 1), false, false);
close(tc.testClass.fPerf);
tc.verifyEqual(unique(tc.testClass.partitioning), [0; 1]);
@@ -450,12 +458,12 @@ classdef test_miSim < matlab.unittest.TestCase
% f = sensor.plotParameters();
% Initialize agents
nIter = 100;
nIter = 75;
tc.agents = {agent};
tc.agents{1} = tc.agents{1}.initialize([tc.domain.center(1:2)-tc.domain.dimensions(1)/4, 3], geometry1, sensor, 3, nIter);
tc.agents{1} = tc.agents{1}.initialize([tc.domain.center(1:2)-tc.domain.dimensions(1)/4, 3], geometry1, sensor, 3, nIter, tc.initialStepSize);
% Initialize the simulation
tc.testClass = tc.testClass.initialize(tc.domain, tc.agents, tc.minAlt, tc.timestep, nIter, cell(0, 1));
tc.testClass = tc.testClass.initialize(tc.domain, tc.agents, tc.barrierGain, tc.barrierExponent, tc.minAlt, tc.timestep, nIter, cell(0, 1));
% Run the simulation
tc.testClass = tc.testClass.run();
@@ -489,13 +497,13 @@ classdef test_miSim < matlab.unittest.TestCase
sensor = sensor.initialize(alphaDist, 3, 15, 3);
% Initialize agents
nIter = 50;
nIter = 25;
tc.agents = {agent; agent};
tc.agents{1} = tc.agents{1}.initialize(tc.domain.center + d, geometry1, sensor, 5, nIter);
tc.agents{2} = tc.agents{2}.initialize(tc.domain.center - d, geometry2, sensor, 5, nIter);
tc.agents{1} = tc.agents{1}.initialize(tc.domain.center + d, geometry1, sensor, 5, nIter, tc.initialStepSize);
tc.agents{2} = tc.agents{2}.initialize(tc.domain.center - d, geometry2, sensor, 5, nIter, tc.initialStepSize);
% Initialize the simulation
tc.testClass = tc.testClass.initialize(tc.domain, tc.agents, tc.minAlt, tc.timestep, nIter, cell(0, 1), tc.makeVideo, tc.makePlots);
tc.testClass = tc.testClass.initialize(tc.domain, tc.agents, tc.barrierGain, tc.barrierExponent, tc.minAlt, tc.timestep, nIter, cell(0, 1), tc.makeVideo, tc.makePlots);
% Run the simulation
tc.testClass.run();
@@ -517,7 +525,7 @@ classdef test_miSim < matlab.unittest.TestCase
radius = 1.1;
d = [3, 0, 0];
yOffset = 0;
yOffset = 1;
% choice of 0 leads to the agents getting stuck attempting to go around the obstacle on both sides
% choice of 1 leads to one agent easily going around while the other gets stuck and the communications link is broken
@@ -539,10 +547,10 @@ 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], geometry1, sensor, commsRadius, tc.maxIter);
tc.agents{2} = tc.agents{2}.initialize(tc.domain.center - d - [0, radius *1.1 + yOffset, 0], geometry2, sensor, commsRadius, tc.maxIter);
tc.agents{1} = tc.agents{1}.initialize(tc.domain.center - d + [0, radius * 1.1 - yOffset, 0], geometry1, sensor, commsRadius, tc.maxIter, tc.initialStepSize);
tc.agents{2} = tc.agents{2}.initialize(tc.domain.center - d - [0, radius *1.1 + yOffset, 0], geometry2, sensor, commsRadius, tc.maxIter, tc.initialStepSize);
% Initialize the simulation
tc.testClass = tc.testClass.initialize(tc.domain, tc.agents, tc.minAlt, tc.timestep, tc.maxIter, tc.obstacles, tc.makeVideo);
tc.testClass = tc.testClass.initialize(tc.domain, tc.agents, tc.barrierGain, tc.barrierExponent, tc.minAlt, tc.timestep, tc.maxIter, tc.obstacles, tc.makeVideo);
% Run the simulation
tc.testClass.run();
@@ -576,14 +584,14 @@ classdef test_miSim < matlab.unittest.TestCase
tc.obstacles = {};
% Initialize agents
nIter = 75;
nIter = 50;
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, geometry1, sensor, commsRadius, nIter);
tc.agents{2} = tc.agents{2}.initialize(dom.center - d, geometry2, sensor, commsRadius, nIter);
tc.agents{1} = tc.agents{1}.initialize(dom.center + d, geometry1, sensor, commsRadius, nIter, tc.initialStepSize);
tc.agents{2} = tc.agents{2}.initialize(dom.center - d, geometry2, sensor, commsRadius, nIter, tc.initialStepSize);
% Initialize the simulation
tc.testClass = tc.testClass.initialize(dom, tc.agents, tc.minAlt, tc.timestep, nIter, tc.obstacles, true, false);
tc.testClass = tc.testClass.initialize(dom, tc.agents, tc.barrierGain, tc.barrierExponent, tc.minAlt, tc.timestep, nIter, tc.obstacles, true, false);
% Run the simulation
tc.testClass = tc.testClass.run();
@@ -616,8 +624,8 @@ classdef test_miSim < matlab.unittest.TestCase
nIter = 125;
commsRadius = 5;
tc.agents = {agent; agent;};
tc.agents{1} = tc.agents{1}.initialize(tc.domain.center - [d, 0, 0], geometry1, sensor, commsRadius, nIter);
tc.agents{2} = tc.agents{2}.initialize(tc.domain.center - [0, d, 0], geometry2, sensor, commsRadius, nIter);
tc.agents{1} = tc.agents{1}.initialize(tc.domain.center - [d, 0, 0], geometry1, sensor, commsRadius, nIter, tc.initialStepSize);
tc.agents{2} = tc.agents{2}.initialize(tc.domain.center - [0, d, 0], geometry2, sensor, commsRadius, nIter, tc.initialStepSize);
% Initialize obstacles
obstacleLength = 1.5;
@@ -625,7 +633,7 @@ 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.agents, 0, tc.timestep, nIter, tc.obstacles, false, false);
tc.testClass = tc.testClass.initialize(tc.domain, tc.agents, tc.barrierGain, tc.barrierExponent, 0, tc.timestep, nIter, tc.obstacles, false, false);
% No communications link should be established
tc.assertEqual(tc.testClass.adjacency, logical(true(2)));
@@ -662,14 +670,14 @@ classdef test_miSim < matlab.unittest.TestCase
nIter = 125;
commsRadius = d;
tc.agents = {agent; agent; agent; agent; agent;};
tc.agents{1} = tc.agents{1}.initialize(tc.domain.center + [d, 0, 0], geometry1, sensor, commsRadius, nIter);
tc.agents{2} = tc.agents{2}.initialize(tc.domain.center, 0, 0, geometry2, sensor, commsRadius, nIter);
tc.agents{3} = tc.agents{3}.initialize(tc.domain.center + [-d, d, 0], geometry3, sensor, commsRadius, nIter);
tc.agents{4} = tc.agents{4}.initialize(tc.domain.center + [-2*d, d, 0], geometry4, sensor, commsRadius, nIter);
tc.agents{5} = tc.agents{5}.initialize(tc.domain.center + [0, d, 0], geometry5, sensor, commsRadius, nIter);
tc.agents{1} = tc.agents{1}.initialize(tc.domain.center + [d, 0, 0], geometry1, sensor, commsRadius, nIter, tc.initialStepSize);
tc.agents{2} = tc.agents{2}.initialize(tc.domain.center, geometry2, sensor, commsRadius, nIter, tc.initialStepSize);
tc.agents{3} = tc.agents{3}.initialize(tc.domain.center + [-d, d, 0], geometry3, sensor, commsRadius, nIter, tc.initialStepSize);
tc.agents{4} = tc.agents{4}.initialize(tc.domain.center + [-2*d, d, 0], geometry4, sensor, commsRadius, nIter, tc.initialStepSize);
tc.agents{5} = tc.agents{5}.initialize(tc.domain.center + [0, d, 0], geometry5, sensor, commsRadius, nIter, tc.initialStepSize);
% Initialize the simulation
tc.testClass = tc.testClass.initialize(tc.domain, tc.agents, 0, tc.timestep, nIter, tc.obstacles, false, false);
tc.testClass = tc.testClass.initialize(tc.domain, tc.agents, tc.barrierGain, tc.barrierExponent, 0, tc.timestep, nIter, tc.obstacles, false, false);
% Constraint adjacency matrix defined by LNA should be as follows
tc.assertEqual(tc.testClass.constraintAdjacencyMatrix, logical( ...
@@ -713,16 +721,16 @@ classdef test_miSim < matlab.unittest.TestCase
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], geometry1, sensor, commsRadius, nIter);
tc.agents{2} = tc.agents{2}.initialize(tc.domain.center + [-0.5 * d, 0.25 * d, 0], geometry2, sensor, commsRadius, nIter);
tc.agents{3} = tc.agents{3}.initialize(tc.domain.center + [0.9 * d, 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], geometry4, sensor, commsRadius, nIter);
tc.agents{5} = tc.agents{5}.initialize(tc.domain.center + [0, 0.9 * d, 0], geometry5, sensor, commsRadius, nIter);
tc.agents{6} = tc.agents{6}.initialize(tc.domain.center, geometry6, sensor, commsRadius, nIter);
tc.agents{7} = tc.agents{7}.initialize(tc.domain.center + [d/2, d/2, 0], geometry7, sensor, commsRadius, nIter);
tc.agents{1} = tc.agents{1}.initialize(tc.domain.center + [-0.9 * d/sqrt(2), 0.9 * d/sqrt(2), 0], geometry1, sensor, commsRadius, nIter, tc.initialStepSize);
tc.agents{2} = tc.agents{2}.initialize(tc.domain.center + [-0.5 * d, 0.25 * d, 0], geometry2, sensor, commsRadius, nIter, tc.initialStepSize);
tc.agents{3} = tc.agents{3}.initialize(tc.domain.center + [0.9 * d, 0, 0], geometry3, sensor, commsRadius, nIter, tc.initialStepSize);
tc.agents{4} = tc.agents{4}.initialize(tc.domain.center + [0.9 * d/sqrt(2), -0.9 * d/sqrt(2), 0], geometry4, sensor, commsRadius, nIter, tc.initialStepSize);
tc.agents{5} = tc.agents{5}.initialize(tc.domain.center + [0, 0.9 * d, 0], geometry5, sensor, commsRadius, nIter, tc.initialStepSize);
tc.agents{6} = tc.agents{6}.initialize(tc.domain.center, geometry6, sensor, commsRadius, nIter, tc.initialStepSize);
tc.agents{7} = tc.agents{7}.initialize(tc.domain.center + [d/2, d/2, 0], geometry7, sensor, commsRadius, nIter, tc.initialStepSize);
% Initialize the simulation
tc.testClass = tc.testClass.initialize(tc.domain, tc.agents, 0, tc.timestep, nIter, tc.obstacles, false, false);
tc.testClass = tc.testClass.initialize(tc.domain, tc.agents, tc.barrierGain, tc.barrierExponent, 0, tc.timestep, nIter, tc.obstacles, false, false);
% Constraint adjacency matrix defined by LNA should be as follows
tc.assertEqual(tc.testClass.constraintAdjacencyMatrix, logical( ...