kdee/miSim
1
0
Fork 0
Code Issues Pull Requests Actions Packages Projects Releases Wiki Activity

lots of cleanup and simplification in test case construction

Browse Source
This commit is contained in:
Kevin Dee
2026-01-13 21:17:35 -08:00
parent 08e396c155
commit bcb3bc3da3
65 changed files with 150 additions and 265 deletions
Download Patch File Download Diff File Expand all files Collapse all files

14
test/test_sigmoidSensor.m
View File

@@ -21,7 +21,7 @@ classdef test_sigmoidSensor < matlab.unittest.TestCase
function tc = setup(tc)
% Reinitialize sensor with random parameters
tc.testClass = sigmoidSensor;
tc.testClass = tc.testClass.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));
tc.testClass = tc.testClass.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));
end
end
@@ -34,28 +34,28 @@ classdef test_sigmoidSensor < matlab.unittest.TestCase
alphaTilt = 15; % degrees
betaTilt = 3;
h = 1e-6;
tc.testClass = tc.testClass.initialize(alphaDist, betaDist, NaN, NaN, alphaTilt, betaTilt);
tc.testClass = tc.testClass.initialize(alphaDist, betaDist, alphaTilt, betaTilt);
% Plot (optional)
% tc.testClass.plotParameters();
% Anticipate perfect performance for a point directly below and
% extremely close
tc.verifyEqual(tc.testClass.sensorPerformance([0, 0, h], NaN, 0, [0, 0, 0]), 1, 'RelTol', 1e-3);
tc.verifyEqual(tc.testClass.sensorPerformance([0, 0, h], 0, [0, 0, 0]), 1, 'RelTol', 1e-3);
% It looks like mu_t can max out at really low values like 0.37
% when alphaTilt and betaTilt are small, which seems wrong
% Performance at nadir point, distance alphaDist should be 1/2 exactly
tc.verifyEqual(tc.testClass.sensorPerformance([0, 0, alphaDist], NaN, 0, [0, 0, 0]), 1/2);
tc.verifyEqual(tc.testClass.sensorPerformance([0, 0, alphaDist], 0, [0, 0, 0]), 1/2);
% Performance at (almost) 0 distance, alphaTilt should be 1/2
tc.verifyEqual(tc.testClass.sensorPerformance([0, 0, h], NaN, 0, [tand(alphaTilt)*h, 0, 0]), 1/2, 'RelTol', 1e-3);
tc.verifyEqual(tc.testClass.sensorPerformance([0, 0, h], 0, [tand(alphaTilt)*h, 0, 0]), 1/2, 'RelTol', 1e-3);
% Performance at great distance should be 0
tc.verifyEqual(tc.testClass.sensorPerformance([0, 0, 10], NaN, 0, [0, 0, 0]), 0, 'AbsTol', 1e-9);
tc.verifyEqual(tc.testClass.sensorPerformance([0, 0, 10], 0, [0, 0, 0]), 0, 'AbsTol', 1e-9);
% Performance at great tilt should be 0
tc.verifyEqual(tc.testClass.sensorPerformance([0, 0, h], NaN, 0, [5, 5, 0]), 0, 'AbsTol', 1e-9);
tc.verifyEqual(tc.testClass.sensorPerformance([0, 0, h], 0, [5, 5, 0]), 0, 'AbsTol', 1e-9);
end
end