plateform stringclasses 1
value | repo_name stringlengths 13 113 | name stringlengths 3 74 | ext stringclasses 1
value | path stringlengths 12 229 | size int64 23 843k | source_encoding stringclasses 9
values | md5 stringlengths 32 32 | text stringlengths 23 843k |
|---|---|---|---|---|---|---|---|---|
github | isetbio/ISETBioCSF-master | plotSignalToNoiseResults.m | .m | ISETBioCSF-master/paperscripts/CSFpaper2/pCurrentModelDemos/plotSignalToNoiseResults.m | 15,579 | utf_8 | 0fac4f3f16927113fa0e08cc17f203f9 | function plotSignalToNoiseResults(timeAxis, photoCurrents, noisyPhotoCurrentsInstances, ...
timeAxisConeExcitations, coneExcitations, noisyConeExcitationInstances, ...
photocurrentSNR, coneExcitationSNR, transformDecibelsToRatios, adaptationPhotonRates, stepWeberContrasts, SNRLims, SNRTicks, ...
spontaneous... |
github | isetbio/ISETBioCSF-master | demonstratePhotocurrentModel.m | .m | ISETBioCSF-master/paperscripts/CSFpaper2/pCurrentModelDemos/demonstratePhotocurrentModel.m | 10,337 | utf_8 | 46806f4353160ea982720c23871250bd | function demonstratePhotocurrentModel
% eccentricity for biophysical model
eccentricity = 'foveal';
% time step for biophysical model
simulationTimeStepSeconds = 0.1/1000;
doImpulseResponseAnalysis = ~true;
doOnOffAsymmetryAnalysis = ~true;
doSignalToNoiseAnalysis = ~true;... |
github | isetbio/ISETBioCSF-master | runPhotocurrentModel.m | .m | ISETBioCSF-master/paperscripts/CSFpaper2/pCurrentModelDemos/runPhotocurrentModel.m | 14,121 | utf_8 | 27fa699961dd0183326ef4a6d8a8cfc2 | function modelResponse = runPhotocurrentModel(stimulus, eccentricity, noisyInstancesNum, useDefaultImplementation)
% Run the photocurrent model for a singe stimulus
%
% Syntax:
% modelResponse = runPhotocurrentModel(stimulus, eccentricity, noisyInstancesNum, useDefaultImplementation);
%
% Description:
% Run the ou... |
github | isetbio/ISETBioCSF-master | testPhotocurrentNoise.m | .m | ISETBioCSF-master/paperscripts/CSFpaper2/photoCurrentAnalysis/testPhotocurrentNoise.m | 4,912 | utf_8 | aedf4dcba1c4cafc7838324318e27341 | function testPhotocurrentNoise
% Generate desired spectral power distribution
sampleTime = 0.5/1000;
totalTimeSeconds = 0.15*4;
nInstances = 1024;
nSamples = round(totalTimeSeconds/sampleTime);
[freqAxis, noiseSPD, noiseSPDlowFreq, ...
noiseSPDhighFreq, cornerFreqLow, cornerFreqHi... |
github | isetbio/ISETBioCSF-master | generateSpatioTemporalPhotocurrentResponse.m | .m | ISETBioCSF-master/paperscripts/CSFpaper2/photoCurrentAnalysis/generateSpatioTemporalPhotocurrentResponse.m | 7,712 | utf_8 | d31273e00540cbf9817c171c55acd1ac | function generateSpatioTemporalPhotocurrentResponse()
recomputeXTresponses = ~true;
if (recomputeXTresponses)
load('/Users/nicolas/Documents/MATLAB/projects/IBIOColorDetect/LconeProfile_null.mat')
adaptationPhotonRates = signal/(5/1000);
[C, ia, ic] = unique(coneXpos,'sorted');
... |
github | isetbio/ISETBioCSF-master | photocurrentModel.m | .m | ISETBioCSF-master/paperscripts/CSFpaper2/photoCurrentAnalysis/photocurrentModel.m | 16,587 | utf_8 | 06f5790821b528730ef031404c66363e | function modelResponse = photocurrentModel(stimulus, eccentricity, noisyInstancesNum, photonIntegrationTime, useDefaultImplementation)
% Run the photocurrent model for a singe stimulus
%
% Syntax:
% modelResponse = photocurrentModel(stimulus, eccentricity, noisyInstancesNum, photonIntegrationTime, useDefaultImplement... |
github | isetbio/ISETBioCSF-master | plotResponses.m | .m | ISETBioCSF-master/paperscripts/CSFpaper2/photoCurrentAnalysis/plotResponses.m | 17,879 | utf_8 | 41ea0dbbe6d242880e928604693c1dd4 | function plotResponses(modelResponse, modelResponseOpositePolarity, adaptationLevel, contrastLevel, ...
pulseDurationSeconds, photoCurrentRange, showSNR, showSNRcomponents, coneExcitationRange, figNo)
if (showSNR)
[coneExcitation.SNR, ...
coneExcitation.noiseEstimationLatency, ...
co... |
github | isetbio/ISETBioCSF-master | plotSNRanalysis.m | .m | ISETBioCSF-master/paperscripts/CSFpaper2/photoCurrentAnalysis/plotSNRanalysis.m | 9,281 | utf_8 | e762415bb0aea6f76a273c24549a4fa4 | function plotSNRanalysis(adaptationLevels, theConeExcitationSNR, thePhotoCurrentSNR, contrastLevels, ...
SNRLims, SNRTicks, SNRratioLims, SNRratioTicks, pulseDurationSeconds, figNo, independentParamName)
if (strcmp(independentParamName, 'adaptationLevel'))
plotSNRanalysisFunctionOfAdaptationLevel(adapt... |
github | isetbio/ISETBioCSF-master | examineSNR.m | .m | ISETBioCSF-master/paperscripts/CSFpaper2/photoCurrentAnalysis/examineSNR.m | 4,278 | utf_8 | 6058ebfaa96e76a3dde1aa8b5c1d25fe | function examineSNR()
pulseDurations = [50 100 200 400]/1000;
if (1==1)
for pulseDurationIndex = 1:numel(pulseDurations)
pulseDurationSeconds = pulseDurations(pulseDurationIndex);
dataFileName = sprintf('results_%dmsec.mat', pulseDurationSeconds*1000);
load(data... |
github | isetbio/ISETBioCSF-master | run_stimulusAreaVaryConditions.m | .m | ISETBioCSF-master/paperscripts/areasummationscripts/run_stimulusAreaVaryConditions.m | 12,711 | utf_8 | 67405f928ec9ced62be1184743ab8334 | function run_stimulusAreaVaryConditions
%% Inference engine and spatial summation sigma
thresholdSignal = 'isomerizations'; % choose from {'isomerizations', 'photocurrents'}
thresholdMethod = 'mlptGaussianRF'; % choose from {'mlpt', 'mlptGaussianRF'}
%% Optics to employ. Choose from:
% ... |
github | isetbio/ISETBioCSF-master | loadSummationData.m | .m | ISETBioCSF-master/paperscripts/areasummationscripts/loadSummationData.m | 5,852 | utf_8 | 1db49beab3e729a2f7a3f692cc47ba65 | function loadSummationData()
classifiersList = {'mlpt', 'svm', 'svmGaussianRF'};
summaryData = containers.Map();
for classifierIndex = 1:numel(classifiersList)
classifierType = classifiersList{classifierIndex};
employedOptics1 = 'AOoptics80mmPupil';
emplo... |
github | isetbio/ISETBioCSF-master | plotSummaryData.m | .m | ISETBioCSF-master/paperscripts/areasummationscripts/plotSummaryData.m | 3,790 | utf_8 | 2473d0fdf14b684a35ad8c6cede52214 | function plotSummaryData
load('summaryData');
for classifierIndex = 1:numel(classifiersList)
classifierType = classifiersList{classifierIndex};
s = summaryData(classifierType);
thresholdsEnergy = [];
thresholdContrasts = [];
summationAreasList = [];
for optic... |
github | isetbio/ISETBioCSF-master | run_summationExperiment.m | .m | ISETBioCSF-master/paperscripts/areasummationscripts/run_summationExperiment.m | 14,021 | utf_8 | eca2f7f07dfafe07ed5b5aeacf6760a1 | function run_summationExperiment
%% Optics to employ. Choose from:
% 'None': delta function PSF
% 'AOoptics80mmPupil' : diffraction-limited with forced 8.0 mm pupil
% 'WvfHuman' : default human wavefront - based optics with mean (across subjects) Z-coeffs
% 'WvfHumanMeanOTFmagMeanOTFphase' : human ... |
github | isetbio/ISETBioCSF-master | run_debugAreaVaryConditionsFinal.m | .m | ISETBioCSF-master/paperscripts/areasummationscripts/run_debugAreaVaryConditionsFinal.m | 13,025 | utf_8 | 8a460d9a303cf7b939decb0ce42d4096 | function run_debugAreaVaryConditionsFinal
%% Inference engine and spatial summation sigma
thresholdSignal = 'isomerizations'; % choose from {'isomerizations', 'photocurrents'}
thresholdMethod = 'mlpt'; % choose from {'mlpt', 'mlptGaussianRF', 'svmGaussianRF'}
%% Optics to employ. Choose fro... |
github | isetbio/ISETBioCSF-master | run_Paper1FinalConditions2vs3mmPupil.m | .m | ISETBioCSF-master/paperscripts/CSFpaper/run_Paper1FinalConditions2vs3mmPupil.m | 5,448 | utf_8 | d10c06adc7c2d816ddeddcc4af130b8e | function run_Paper1FinalConditions2vs3mmPupil
% This is the script used to assess how the final conditions in paper1
% with a 2 vs 3mm pupil compare to the Banks prediction.
%
% How to split the computation
% 0 (All mosaics), 1; (Largest mosaic), 2 (Second largest), 3 (all 2 largest)
computationInstance =... |
github | isetbio/ISETBioCSF-master | run_MosaicsVaryConditionsFor2MMPupil.m | .m | ISETBioCSF-master/paperscripts/CSFpaper/run_MosaicsVaryConditionsFor2MMPupil.m | 7,375 | utf_8 | 573e9d81b41bcc3fef593fd74967b752 | function run_MosaicsVaryConditionsFor2MMPupil
% This is the script used to assess the impact of different mosaic models on the CSF
%
% How to split the computation
% 0 (All mosaics), 1; (Largest mosaic), 2 (Second largest), 3 (all 2 largest)
computationInstance = 0;
% Whether to make a summary fi... |
github | isetbio/ISETBioCSF-master | make_SVMRepsComboFigure.m | .m | ISETBioCSF-master/paperscripts/CSFpaper/make_SVMRepsComboFigure.m | 18,959 | utf_8 | 73b0ed32c74b2f9c9bb94685f4d3aa5a | function make_SVMRepsComboFigure
% This is the script used to assess the generate panels of Figures 7 and 8
%
% Which spatial frequency to analyze
thePanelLabels = {' B ', ' C '}; % Label for the two psychometric function panels
thePanelLabels = {'', ''};
computationInstance = 8; % 4 (... |
github | isetbio/ISETBioCSF-master | run_Paper1FinalConditionsUsing2mmPupil.m | .m | ISETBioCSF-master/paperscripts/CSFpaper/run_Paper1FinalConditionsUsing2mmPupil.m | 7,465 | utf_8 | d1a3eaead02d7dd2c433c25652ddfe36 | function run_Paper1FinalConditionsUsing2mmPupil
% This is the script used to assess how the final conditions in paper1
% with a 2 mm pupil compare to the Banks prediction.
%
% How to split the computation
% 0 (All mosaics), 1; (Largest mosaic), 2 (Second largest), 3 (all but the 2 largest)
computationInst... |
github | isetbio/ISETBioCSF-master | run_SVMRepsVaryConditions.m | .m | ISETBioCSF-master/paperscripts/CSFpaper/run_SVMRepsVaryConditions.m | 9,688 | utf_8 | 21d284d618cee8e7ed0f3a1fbb13c07f | function run_SVMRepsVaryConditions
% This is the script used to assess the impact of different # of trials on the SVM-based CSF
%
% Which spatial frequency to analyze
computationInstance = 8; % 4 (4 c/deg) 8 (8 c/deg), 16 (16 c/deg) or 32 (32 c/deg)
performanceClassifier = 'svm'; %'; % Choose betwee... |
github | isetbio/ISETBioCSF-master | runSummaryCSF.m | .m | ISETBioCSF-master/paperscripts/CSFpaper/runSummaryCSF.m | 6,292 | utf_8 | 0fa1b981c5528307099b715931305c90 | function runSummaryCSF()
[theParams{1}, theLegends{1}] = paramsForBanksCondition();
[theParams{2}, theLegends{2}] = paramsForBanksGeislerOpticsEccMosaic();
[theParams{3}, theLegends{3}] = paramsForWvfOpticsEccMosaic();
[theParams{4}, theLegends{4}] = paramsForSVMQPhE();
[theParams{5}, theLegen... |
github | isetbio/ISETBioCSF-master | fitPolyToBanksData.m | .m | ISETBioCSF-master/paperscripts/CSFpaper/fitPolyToBanksData.m | 1,548 | utf_8 | 87d1e077272d75fba9ec28073ce7d5cf | function fitPolyToBanksData
load('BanksSubjects.mat', 'pjbSubjectSFs', 'pjbSubjectCSFs', 'msbSubjectSFs', 'msbSubjectCSFs');
figure(1); clf;
plot(pjbSubjectSFs, pjbSubjectCSFs, 'ro', 'MarkerSize', 12); hold on;
plot(msbSubjectSFs, msbSubjectCSFs, 'bo', 'MarkerSize', 12);
set(gca, 'XLim', [1 60], '... |
github | isetbio/ISETBioCSF-master | run_Paper2FinalConditionsUsing2mmPupil.m | .m | ISETBioCSF-master/paperscripts/CSFpaper/run_Paper2FinalConditionsUsing2mmPupil.m | 11,902 | utf_8 | 30c61b3561ea4a33b7035dcb028be627 | function run_Paper2FinalConditionsUsing2mmPupil
% This is the script used to assess how the final conditions in paper1
% with a 2 mm pupil compare to the Banks prediction.
%
% How to split the computation
% 0 (All mosaics), 1; (Largest mosaic), 2 (Second largest), 3 (all 2 largest)
computationInstance = 0... |
github | isetbio/ISETBioCSF-master | runPaper2InferenceEngineVaryUsing2mmPupil.m | .m | ISETBioCSF-master/paperscripts/CSFpaper/runPaper2InferenceEngineVaryUsing2mmPupil.m | 10,980 | utf_8 | 9d959ab3a6b81af1f77b3826bf11edab | function runPaper2InferenceEngineVaryUsing2mmPupil
% How to split the computation
% 0 (All mosaics), 1; (Largest mosaic), 2 (Second largest), 3 (all 2 largest)
computationInstance = 0 ;
% Whether to make a summary figure with CSF from all examined conditions
makeSummaryFigure = true;
... |
github | isetbio/ISETBioCSF-master | run_OpticsVaryConditions.m | .m | ISETBioCSF-master/paperscripts/CSFpaper/run_OpticsVaryConditions.m | 8,616 | utf_8 | e646c52d16fa5eb25df103d2de8a7b85 | function run_OpticsVaryConditions
% This is the script used to assess the impact of different optics models on the CSF
%
% How to split the computation
% 0 (All mosaics), 1; (Largest mosaic), 2 (Second largest), 3 (all 2 largest)
computationInstance = 0;
% Whether to make a summary figure with CS... |
github | isetbio/ISETBioCSF-master | run_GratingOrientationVaryConditions.m | .m | ISETBioCSF-master/paperscripts/CSFpaper/run_GratingOrientationVaryConditions.m | 6,036 | utf_8 | 0a922c07ae557932b4bf4f60347678c4 | function run_GratingOrientationVaryConditions
% This is the script used to assess the impact of different grating orientations for
% the typical subject PSF
%
% How to split the computation
% 0 (All mosaics), 1; (Largest mosaic), 2 (Second largest), 3 (all but 2 largest)
computationInstance = 0;
... |
github | isetbio/ISETBioCSF-master | run_MosaicsVaryConditionsReviewer.m | .m | ISETBioCSF-master/paperscripts/CSFpaper/run_MosaicsVaryConditionsReviewer.m | 8,973 | utf_8 | 1d9431ffa7c68e933c1c325dd7c07293 | function run_MosaicsVaryConditionsReviewer
% This is the script used to assess the impact of different mosaic models on the CSF
%
% How to split the computation
% 0 (All mosaics), 1; (Largest mosaic), 2 (Second largest), 3 (all 2 largest)
computationInstance = 0;
% Whether to make a summary figur... |
github | isetbio/ISETBioCSF-master | run_MosaicsVaryConditions.m | .m | ISETBioCSF-master/paperscripts/CSFpaper/run_MosaicsVaryConditions.m | 10,037 | utf_8 | 2a7a271e6c1ca52120be1cfad0f5db8a | function run_MosaicsVaryConditions
% This is the script used to assess the impact of different mosaic models on the CSF
%
% How to split the computation
% 0 (All mosaics), 1; (Largest mosaic), 2 (Second largest), 3 (all 2 largest)
computationInstance = 0;
% Whether to make a summary figure with C... |
github | isetbio/ISETBioCSF-master | run_OpticsVaryConditionsReviewerFigure.m | .m | ISETBioCSF-master/paperscripts/CSFpaper/run_OpticsVaryConditionsReviewerFigure.m | 11,145 | utf_8 | 1322ff2097d1c363d2aef43d12fbba1b | function run_OpticsVaryConditionsReviewerFigure
% This is the script used to assess the impact of different optics models on the CSF
%
% How to split the computation
% 0 (All mosaics), 1; (Largest mosaic), 2 (Second largest), 3 (all 2 largest)
computationInstance = 0;
% Whether to make a summary ... |
github | isetbio/ISETBioCSF-master | generateUpdatedFig1Components.m | .m | ISETBioCSF-master/FVM2018Scripts/scripts/generateUpdatedFig1Components.m | 20,878 | utf_8 | 5b435c128f67a3ac347bafc02d90affd | function generateUpdatedFig1Components
[rootPath0,~] = fileparts(which(mfilename));
cd(rootPath0);
rootPath = strrep(rootPath0, 'scripts', 'resources');
videoOutDir = strrep(rootPath0, 'scripts', 'updatedComponentFigs');
%hFig = runConditionToVisualizePsychometricCurve();
%NicePlot.exportFi... |
github | isetbio/ISETBioCSF-master | generatePhotocurrentNoiseFigure.m | .m | ISETBioCSF-master/FVM2018Scripts/scripts/generatePhotocurrentNoiseFigure.m | 5,845 | utf_8 | 34bdf372386a081361f9984853fea9b7 | function generatePhotocurrentNoiseFigure
FOV = 1;
meanLuminance = 30;
uniformScene = uniformFieldSceneCreate(FOV, meanLuminance);
theOI = oiCreate('human');
theOI = oiCompute(theOI, uniformScene);
integrationTime = 1/1000;
theMosaic = coneMosaicGenerate(nan, integrationTime);
fixationalEyeMovementsNum = 1.0/integra... |
github | isetbio/ISETBioCSF-master | GenerateFixationalEyeMovements3mmPupilSpecificInferenceEngineCS.m | .m | ISETBioCSF-master/FVM2018Scripts/SlideGenerationScripts/GenerateFixationalEyeMovements3mmPupilSpecificInferenceEngineCS.m | 6,766 | utf_8 | 22c2b1d1b04dd6d9f9125aba364a6073 | function GenerateFixationalEyeMovements3mmPupilSpecificInferenceEngineCS
% Script to generate the slide with the Banks'87 ideal and human observer data
% 0 (All mosaics), 1; (Largest mosaic), 2 (Second largest), 3 (all 2 largest)
computationInstance = 0;
% Whether to make a summary figure wit... |
github | isetbio/ISETBioCSF-master | GenerateValidationCSF.m | .m | ISETBioCSF-master/FVM2018Scripts/SlideGenerationScripts/GenerateValidationCSF.m | 5,354 | utf_8 | 589e1ff38b4ded8a2485257272bd737f | function GenerateValidationCSF
% Script to generate the slide with the Banks'87 ideal and human observer data
% 0 (All mosaics), 1; (Largest mosaic), 2 (Second largest), 3 (all 2 largest)
computationInstance = 0;
% Whether to make a summary figure with CSF from all examined conditions
ma... |
github | isetbio/ISETBioCSF-master | GenerateMosaicEffectCSFs.m | .m | ISETBioCSF-master/FVM2018Scripts/SlideGenerationScripts/GenerateMosaicEffectCSFs.m | 5,878 | utf_8 | ace19b6875d32c9d25071a8b0ea309c5 | function GenerateMosaicEffectCSFs
% Script to generate the slide with the Banks'87 ideal and human observer data
% 0 (All mosaics), 1; (Largest mosaic), 2 (Second largest), 3 (all 2 largest)
computationInstance = 0;
% Whether to make a summary figure with CSF from all examined conditions
... |
github | isetbio/ISETBioCSF-master | GenerateFixationalEyeMovementsCSFs.m | .m | ISETBioCSF-master/FVM2018Scripts/SlideGenerationScripts/GenerateFixationalEyeMovementsCSFs.m | 9,251 | utf_8 | fc3df60d484a5e556bb9109979fdd74b | function GenerateFixationalEyeMovementsCSFs
% Script to generate the slide with the Banks'87 ideal and human observer data
% 0 (All mosaics), 1; (Largest mosaic), 2 (Second largest), 3 (all 2 largest)
computationInstance = 0;
% Whether to make a summary figure with CSF from all examined condi... |
github | isetbio/ISETBioCSF-master | GenerateInferenceEngineCSF.m | .m | ISETBioCSF-master/FVM2018Scripts/SlideGenerationScripts/GenerateInferenceEngineCSF.m | 7,226 | utf_8 | bdab12a48447b8c2776a3719094f4dfe | function GenerateInferenceEngineCSF
% Script to generate the slide with the Banks'87 ideal and human observer data
% 0 (All mosaics), 1; (Largest mosaic), 2 (Second largest), 3 (all 2 largest)
computationInstance = 0;
% Whether to make a summary figure with CSF from all examined conditions
... |
github | isetbio/ISETBioCSF-master | GenerateRealisticMosaicAndOpticsCSF.m | .m | ISETBioCSF-master/FVM2018Scripts/SlideGenerationScripts/GenerateRealisticMosaicAndOpticsCSF.m | 11,714 | utf_8 | 9b95802e050fcbd6b56d20fef862fafd | function GenerateRealisticMosaicAndOpticsCSF
% Script to generate the slide with the Banks'87 ideal and human observer data
% 0 (All mosaics), 1; (Largest mosaic), 2 (Second largest), 3 (all 2 largest)
computationInstance = 0;
% Whether to make a summary figure with CSF from all examined con... |
github | isetbio/ISETBioCSF-master | GeneratePhotocurrentCSFs.m | .m | ISETBioCSF-master/FVM2018Scripts/SlideGenerationScripts/GeneratePhotocurrentCSFs.m | 9,268 | utf_8 | b500d103517bed6321dc26f4ecacfc51 | function GeneratePhotocurrentCSFs
% Script to generate the slide with the Banks'87 ideal and human observer data
% 0 (All mosaics), 1; (Largest mosaic), 2 (Second largest), 3 (all 2 largest)
computationInstance = 0;
% Whether to make a summary figure with CSF from all examined conditions
... |
github | isetbio/ISETBioCSF-master | GenerateInferenceEngineCSFsFor3mmPupilAndEyeMovementScenario.m | .m | ISETBioCSF-master/FVM2018Scripts/SlideGenerationScripts/GenerateInferenceEngineCSFsFor3mmPupilAndEyeMovementScenario.m | 7,159 | utf_8 | e663598e11d3a067477cce5c37d25a1e | function GenerateInferenceEngineCSFsFor3mmPupilAndEyeMovementScenario
% Script to generate the slide with the Banks'87 ideal and human observer data
% 0 (All mosaics), 1; (Largest mosaic), 2 (Second largest), 3 (all 2 largest)
computationInstance = 0;
% Whether to make a summary figure with C... |
github | isetbio/ISETBioCSF-master | startGUI.m | .m | ISETBioCSF-master/manager/startGUI.m | 8,997 | utf_8 | c72f10d1b3049c87be4d8e6b6edb85e3 | function startGUI(targetDir, dataFormat)
targetDir = uigetdir(targetDir);
[varNamesLevel1, varValuesLevel1, varFormatsLevel1, varEditablesLevel1, varWidthsLevel1] = ...
scanDirToRetrieveVarValues(targetDir, dataFormat);
hFig = figure(1); clf;
set(hFig, 'Position', [10 10 1670 500]... |
github | hypro/hypro-master | findSafetyProperties.m | .m | hypro-master/include/hypro/util/matlab/CORA_benchmarks/findSafetyProperties.m | 1,433 | utf_8 | dfede01d588c6f44ff763c36dfc2b733 | function out = findSafetyProperties(spec, ReachableSet)
% Create vector with variable values
min = zeros(size(spec,1),1);
max = zeros(size(spec,1),1);
spec_counter = 1;
for row = 1:size(spec,1)
values = zeros((length(ReachableSet) * length(ReachableSet{1})), 2);
counter = 1;
for i=1:lengt... |
github | hypro/hypro-master | verifySafetyPropertiesCORA.m | .m | hypro-master/include/hypro/util/matlab/CORA_benchmarks/verifySafetyPropertiesCORA.m | 2,877 | utf_8 | 6f124915e89fb2ea072b8ae0743c2a5d | function out = verifySafetyProperties(spec_matrix, ReachableSet)
%--------------------------------------------------------------------------
% spec_matrix: The rows of the matrix contain coefficients of a single
% safety specification
%
% ReachableSet: Contains the reachable set computed by CORA (OT)
%
... |
github | hypro/hypro-master | MHyProSupportFunctionTest.m | .m | hypro-master/include/hypro/util/matlab/tests/MHyProSupportFunctionTest.m | 3,426 | utf_8 | 494d47244bdaaaca608d49fe8dcefc92 | function tests = MHyProSupportFunctionTest
tests = functiontests(localfunctions);
end
function testSupportFunctions(testCase)
% This script contains tests for all functions for HyPro support functions.
fct = MHyProSupportFunction();
mat_fct = MHyProSupportFunction([1 0 0; 0 1 0; 0 0 1]);
int_fct = MHyProSupportF... |
github | hypro/hypro-master | MHyProEllipsoidTest.m | .m | hypro-master/include/hypro/util/matlab/tests/MHyProEllipsoidTest.m | 1,497 | utf_8 | cfb6a1d0db823c90555708ea67fe5a8b | function tests = MHyProEllipsoidTest
tests = functiontests(localfunctions);
end
function testEllipsoid(testCase)
% This script contains tests for all functions for HyPro Ellipsoids.
rad_eli = MHyProEllipsoid(2.1, 2);
mat_eli = MHyProEllipsoid([1 2; 3 4]);
copied_eli = MHyProEllipsoid(rad_eli);
% Check if ellipso... |
github | hypro/hypro-master | MHyProLocationTest.m | .m | hypro-master/include/hypro/util/matlab/tests/MHyProLocationTest.m | 2,403 | utf_8 | 636a17775eec54492649094abc07a451 | function tests = MHyProLocationTest
tests = functiontests(localfunctions);
end
function testLocation(testCase)
loc1 = MHyProLocation();
loc2 = MHyProLocation([1 0 1; 2 1 3; 1 1 1]);
loc3 = MHyProLocation([1 0; 2 1]);
loc4 = MHyProLocation([1 0; 0 1]);
tran1_2 = MHyProTransition(loc1, loc2);
tran1_3 = MHyProTransi... |
github | hypro/hypro-master | MHyProBoxTest.m | .m | hypro-master/include/hypro/util/matlab/tests/MHyProBoxTest.m | 7,782 | utf_8 | e128855c2f710e7a02df0be9efd9a2ed | function tests = MHyProBoxTest
tests = functiontests(localfunctions);
end
function testBox(testCase)
%Test Basic Functionality
%This script contains tests for all functions for HyPro Boxes.
inter = [-6 27; 23 179; 5 153; -41 -24; -25 145];
points = [0 2; 0 1; 32 -109];
% Construct an empty box
empty_box = MHyPro... |
github | hypro/hypro-master | MHyProHAutomatonTest.m | .m | hypro-master/include/hypro/util/matlab/tests/MHyProHAutomatonTest.m | 1,849 | utf_8 | f4ea5b40907efccd6b040780b8d17346 | function tests = MHyProHAutomatonTest
tests = functiontests(localfunctions);
end
function testHAutomaton(testCase)
automaton = MHyProHAutomaton();
loc = MHyProLocation();
tran = MHyProTransition();
reset = MHyProReset();
guard = MHyProCondition();
% Set invariant
inv_mat = [-1 0];
inv_vec = 0;
inv = MHyProCondi... |
github | hypro/hypro-master | MHyProResetTest.m | .m | hypro-master/include/hypro/util/matlab/tests/MHyProResetTest.m | 1,074 | utf_8 | b3225e1af4bf6e6c4656dbe0fe88028c | function tests = MHyProResetTest
tests = functiontests(localfunctions);
end
function testReset(testCase)
reset_empty = MHyProReset();
empty = reset_empty.isempty();
assert(empty == 1);
size = reset_empty.size();
assert(size == 0);
reset = MHyProReset();
reset.setVector([1; 2; 2]);
empty = reset.isempty();
asse... |
github | hypro/hypro-master | MHyProZonotopeTest.m | .m | hypro-master/include/hypro/util/matlab/tests/MHyProZonotopeTest.m | 1,219 | utf_8 | 3dd2b85160b6125691abb638cc73122f | function tests = MHyProZonotopeTest
tests = functiontests(localfunctions);
end
function testZonotopes(testCase)
disp('z1');
z1 = MHyProZonotope();
disp('z2');
z2 = MHyProZonotope('dimension', 13);
disp('z3');
z3 = MHyProZonotope([1 1 0], [1 0 0; 0 1 0; 0 0 1]);
disp('z4');
z4 = MHyProZonotope(z3, 0, 2);
disp('z5'... |
github | hypro/hypro-master | MHyProTransitionTest.m | .m | hypro-master/include/hypro/util/matlab/tests/MHyProTransitionTest.m | 1,656 | utf_8 | b48e7d96ee3aa238549b178090bfbe6f | function tests = MHyProTransitionTest
tests = functiontests(localfunctions);
end
function testTransition(testCase)
tran = MHyProTransition();
copied_tran = MHyProTransition(tran);
loc1 = MHyProLocation([1 0; 2 1]);
loc2 = MHyProLocation([1 0; 0 1]);
tran_1_2 = MHyProTransition(loc1, loc2);
guard = MHyProConditi... |
github | hypro/hypro-master | MHyProLabelTest.m | .m | hypro-master/include/hypro/util/matlab/tests/MHyProLabelTest.m | 793 | utf_8 | fa266d23e9aea4c74df7f218d7bce0de | function tests = MHyProLabelTest
tests = functiontests(localfunctions);
end
function testLabel(testCase)
% Test Basic Functionality
lab1 = MHyProLabel('lab1');
lab2 = MHyProLabel(lab1);
% Get label names
name1 = lab1.getName();
name2 = lab2.getName();
assert(isequal(name1,'lab1'));
assert(isequal(name2,'lab1'));
... |
github | hypro/hypro-master | MHyProConstraintSetTest.m | .m | hypro-master/include/hypro/util/matlab/tests/MHyProConstraintSetTest.m | 3,714 | utf_8 | ada9b778726e55d870a571d95c66d412 | function tests = MHyProConstraintTest
tests = functiontests(localfunctions);
end
function testConstraintSet(testCase)
% Test Basic Functionality
set = MHyProConstraintSet();
mat_vec_set = MHyProConstraintSet([1 0 0 0; 0 1 0 0; 0 0 1 0],[1;2;3]);
copied_set = MHyProConstraintSet(mat_vec_set);
assert(isequal(mat_ve... |
github | hypro/hypro-master | MHyProConditionTest.m | .m | hypro-master/include/hypro/util/matlab/tests/MHyProConditionTest.m | 865 | utf_8 | 9d738e76a58a9a9428692cb4e66223b8 | function tests = MHyProConditionTest
tests = functiontests(localfunctions);
end
function testCondition(testCase)
cond1 = MHyProCondition();
cond2 = MHyProCondition([1 2; 3 4], [1; 2]);
cond3 = MHyProCondition(cond2);
s = cond1.size();
assert(s == 0);
empty = cond2.isempty();
assert(empty == 0);
mat = cond3.get... |
github | hypro/hypro-master | MHyProFlowTest.m | .m | hypro-master/include/hypro/util/matlab/tests/MHyProFlowTest.m | 1,438 | utf_8 | 2185766c3157b62347082c9d9e6cf7bb | function tests = MHyProFlowTest
tests = functiontests(localfunctions);
end
function testFlow(testCase)
%% Test Basic Functionality
linFlow = MHyProFlow(9);
% Check if it has flow
flow = linFlow.hasNoFlow();
assert(flow == 0);
% Add flow matrix to linFlow
flowMatrix = [1 2 0; 3 4 1; 1 0 1];
linFlow.setFlowMatr... |
github | hypro/hypro-master | findSafetyProperties.m | .m | hypro-master/src/hypro/util/matlab/CORA_benchmarks/findSafetyProperties.m | 1,433 | utf_8 | dfede01d588c6f44ff763c36dfc2b733 | function out = findSafetyProperties(spec, ReachableSet)
% Create vector with variable values
min = zeros(size(spec,1),1);
max = zeros(size(spec,1),1);
spec_counter = 1;
for row = 1:size(spec,1)
values = zeros((length(ReachableSet) * length(ReachableSet{1})), 2);
counter = 1;
for i=1:lengt... |
github | hypro/hypro-master | verifySafetyPropertiesCORA.m | .m | hypro-master/src/hypro/util/matlab/CORA_benchmarks/verifySafetyPropertiesCORA.m | 2,877 | utf_8 | 6f124915e89fb2ea072b8ae0743c2a5d | function out = verifySafetyProperties(spec_matrix, ReachableSet)
%--------------------------------------------------------------------------
% spec_matrix: The rows of the matrix contain coefficients of a single
% safety specification
%
% ReachableSet: Contains the reachable set computed by CORA (OT)
%
... |
github | hypro/hypro-master | MHyProSupportFunctionTest.m | .m | hypro-master/src/hypro/util/matlab/tests/MHyProSupportFunctionTest.m | 3,426 | utf_8 | 494d47244bdaaaca608d49fe8dcefc92 | function tests = MHyProSupportFunctionTest
tests = functiontests(localfunctions);
end
function testSupportFunctions(testCase)
% This script contains tests for all functions for HyPro support functions.
fct = MHyProSupportFunction();
mat_fct = MHyProSupportFunction([1 0 0; 0 1 0; 0 0 1]);
int_fct = MHyProSupportF... |
github | hypro/hypro-master | MHyProEllipsoidTest.m | .m | hypro-master/src/hypro/util/matlab/tests/MHyProEllipsoidTest.m | 1,497 | utf_8 | cfb6a1d0db823c90555708ea67fe5a8b | function tests = MHyProEllipsoidTest
tests = functiontests(localfunctions);
end
function testEllipsoid(testCase)
% This script contains tests for all functions for HyPro Ellipsoids.
rad_eli = MHyProEllipsoid(2.1, 2);
mat_eli = MHyProEllipsoid([1 2; 3 4]);
copied_eli = MHyProEllipsoid(rad_eli);
% Check if ellipso... |
github | hypro/hypro-master | MHyProLocationTest.m | .m | hypro-master/src/hypro/util/matlab/tests/MHyProLocationTest.m | 2,403 | utf_8 | 636a17775eec54492649094abc07a451 | function tests = MHyProLocationTest
tests = functiontests(localfunctions);
end
function testLocation(testCase)
loc1 = MHyProLocation();
loc2 = MHyProLocation([1 0 1; 2 1 3; 1 1 1]);
loc3 = MHyProLocation([1 0; 2 1]);
loc4 = MHyProLocation([1 0; 0 1]);
tran1_2 = MHyProTransition(loc1, loc2);
tran1_3 = MHyProTransi... |
github | hypro/hypro-master | MHyProBoxTest.m | .m | hypro-master/src/hypro/util/matlab/tests/MHyProBoxTest.m | 7,782 | utf_8 | e128855c2f710e7a02df0be9efd9a2ed | function tests = MHyProBoxTest
tests = functiontests(localfunctions);
end
function testBox(testCase)
%Test Basic Functionality
%This script contains tests for all functions for HyPro Boxes.
inter = [-6 27; 23 179; 5 153; -41 -24; -25 145];
points = [0 2; 0 1; 32 -109];
% Construct an empty box
empty_box = MHyPro... |
github | hypro/hypro-master | MHyProHAutomatonTest.m | .m | hypro-master/src/hypro/util/matlab/tests/MHyProHAutomatonTest.m | 1,849 | utf_8 | f4ea5b40907efccd6b040780b8d17346 | function tests = MHyProHAutomatonTest
tests = functiontests(localfunctions);
end
function testHAutomaton(testCase)
automaton = MHyProHAutomaton();
loc = MHyProLocation();
tran = MHyProTransition();
reset = MHyProReset();
guard = MHyProCondition();
% Set invariant
inv_mat = [-1 0];
inv_vec = 0;
inv = MHyProCondi... |
github | hypro/hypro-master | MHyProResetTest.m | .m | hypro-master/src/hypro/util/matlab/tests/MHyProResetTest.m | 1,074 | utf_8 | b3225e1af4bf6e6c4656dbe0fe88028c | function tests = MHyProResetTest
tests = functiontests(localfunctions);
end
function testReset(testCase)
reset_empty = MHyProReset();
empty = reset_empty.isempty();
assert(empty == 1);
size = reset_empty.size();
assert(size == 0);
reset = MHyProReset();
reset.setVector([1; 2; 2]);
empty = reset.isempty();
asse... |
github | hypro/hypro-master | MHyProZonotopeTest.m | .m | hypro-master/src/hypro/util/matlab/tests/MHyProZonotopeTest.m | 1,219 | utf_8 | 3dd2b85160b6125691abb638cc73122f | function tests = MHyProZonotopeTest
tests = functiontests(localfunctions);
end
function testZonotopes(testCase)
disp('z1');
z1 = MHyProZonotope();
disp('z2');
z2 = MHyProZonotope('dimension', 13);
disp('z3');
z3 = MHyProZonotope([1 1 0], [1 0 0; 0 1 0; 0 0 1]);
disp('z4');
z4 = MHyProZonotope(z3, 0, 2);
disp('z5'... |
github | hypro/hypro-master | MHyProTransitionTest.m | .m | hypro-master/src/hypro/util/matlab/tests/MHyProTransitionTest.m | 1,656 | utf_8 | b48e7d96ee3aa238549b178090bfbe6f | function tests = MHyProTransitionTest
tests = functiontests(localfunctions);
end
function testTransition(testCase)
tran = MHyProTransition();
copied_tran = MHyProTransition(tran);
loc1 = MHyProLocation([1 0; 2 1]);
loc2 = MHyProLocation([1 0; 0 1]);
tran_1_2 = MHyProTransition(loc1, loc2);
guard = MHyProConditi... |
github | hypro/hypro-master | MHyProLabelTest.m | .m | hypro-master/src/hypro/util/matlab/tests/MHyProLabelTest.m | 793 | utf_8 | fa266d23e9aea4c74df7f218d7bce0de | function tests = MHyProLabelTest
tests = functiontests(localfunctions);
end
function testLabel(testCase)
% Test Basic Functionality
lab1 = MHyProLabel('lab1');
lab2 = MHyProLabel(lab1);
% Get label names
name1 = lab1.getName();
name2 = lab2.getName();
assert(isequal(name1,'lab1'));
assert(isequal(name2,'lab1'));
... |
github | hypro/hypro-master | MHyProConstraintSetTest.m | .m | hypro-master/src/hypro/util/matlab/tests/MHyProConstraintSetTest.m | 3,714 | utf_8 | ada9b778726e55d870a571d95c66d412 | function tests = MHyProConstraintTest
tests = functiontests(localfunctions);
end
function testConstraintSet(testCase)
% Test Basic Functionality
set = MHyProConstraintSet();
mat_vec_set = MHyProConstraintSet([1 0 0 0; 0 1 0 0; 0 0 1 0],[1;2;3]);
copied_set = MHyProConstraintSet(mat_vec_set);
assert(isequal(mat_ve... |
github | hypro/hypro-master | MHyProConditionTest.m | .m | hypro-master/src/hypro/util/matlab/tests/MHyProConditionTest.m | 865 | utf_8 | 9d738e76a58a9a9428692cb4e66223b8 | function tests = MHyProConditionTest
tests = functiontests(localfunctions);
end
function testCondition(testCase)
cond1 = MHyProCondition();
cond2 = MHyProCondition([1 2; 3 4], [1; 2]);
cond3 = MHyProCondition(cond2);
s = cond1.size();
assert(s == 0);
empty = cond2.isempty();
assert(empty == 0);
mat = cond3.get... |
github | hypro/hypro-master | MHyProFlowTest.m | .m | hypro-master/src/hypro/util/matlab/tests/MHyProFlowTest.m | 1,438 | utf_8 | 2185766c3157b62347082c9d9e6cf7bb | function tests = MHyProFlowTest
tests = functiontests(localfunctions);
end
function testFlow(testCase)
%% Test Basic Functionality
linFlow = MHyProFlow(9);
% Check if it has flow
flow = linFlow.hasNoFlow();
assert(flow == 0);
% Add flow matrix to linFlow
flowMatrix = [1 2 0; 3 4 1; 1 0 1];
linFlow.setFlowMatr... |
github | abbas-rahimi/HDC-EMG-master | binaryCode.m | .m | HDC-EMG-master/binaryCode.m | 20,224 | utf_8 | f0e3e0898e9ea38770f584e8f5116de0 | % This program implements the use of hyperdimensional (HD) computing to
% classify electromyography (EMG) signals for hand gesture recognition.
% Copyright (C) 2016 Abbas Rahimi (e-mail:abbas@eecs.berkeley.edu).
% This program is free software: you can redistribute it and/or modify
% it under the terms of the GNU Ge... |
github | abbas-rahimi/HDC-EMG-master | ICRC.m | .m | HDC-EMG-master/ICRC.m | 14,991 | utf_8 | b68f8c4ad9100c8e223345e0e23376d9 | % This program implements the use of hyperdimensional (HD) computing to
% classify electromyography (EMG) signals for hand gesture recognition.
% Copyright (C) 2016 Abbas Rahimi (e-mail:abbas@eecs.berkeley.edu).
% This program is free software: you can redistribute it and/or modify
% it under the terms of the GNU Ge... |
github | icopavan/IndependentComponentAnalysis-1-master | pcamat.m | .m | IndependentComponentAnalysis-1-master/FastICA_25/pcamat.m | 12,075 | utf_8 | bcb1117d4132558d0d54d8b7b616a902 | function [E, D] = pcamat(vectors, firstEig, lastEig, s_interactive, ...
s_verbose);
%PCAMAT - Calculates the pca for data
%
% [E, D] = pcamat(vectors, firstEig, lastEig, ...
% interactive, verbose);
%
% Calculates the PCA matrices for given data (row) vectors. Returns
% the eigenvector (E) and diag... |
github | icopavan/IndependentComponentAnalysis-1-master | icaplot.m | .m | IndependentComponentAnalysis-1-master/FastICA_25/icaplot.m | 13,259 | utf_8 | dde3e6d852f657a3c1eaacbd03f5dcc7 | function icaplot(mode, varargin);
%ICAPLOT - plot signals in various ways
%
% ICAPLOT is mainly for plottinf and comparing the mixed signals and
% separated ica-signals.
%
% ICAPLOT has many different modes. The first parameter of the function
% defines the mode. Other parameters and their order depends on the
% mode. ... |
github | icsa-caps/c3d-protocol-master | C3D.m | .m | c3d-protocol-master/C3D.m | 32,521 | utf_8 | 4cf5309b981f06b61815d548b942be72 | --------------------------------------------------------------------------------
-- Murphi model of C3D protocol:
-- Cheng-Chieh Huang, Rakesh Kumar, Marco Elver, Boris Grot, and Vijay Nagarajan.
-- C3D: Mitigating the NUMA Bottleneck via Coherent DRAM Caches.
-- In IEEE/ACM International Symposium on Microarchit... |
github | juliacamps/OR-master | vl_compile.m | .m | OR-master/Practical_Session_Multiview_Analysis/code/vlfeat-0.9.16/toolbox/vl_compile.m | 5,060 | utf_8 | 978f5189bb9b2a16db3368891f79aaa6 | function vl_compile(compiler)
% VL_COMPILE Compile VLFeat MEX files
% VL_COMPILE() uses MEX() to compile VLFeat MEX files. This command
% works only under Windows and is used to re-build problematic
% binaries. The preferred method of compiling VLFeat on both UNIX
% and Windows is through the provided Makefile... |
github | juliacamps/OR-master | vl_noprefix.m | .m | OR-master/Practical_Session_Multiview_Analysis/code/vlfeat-0.9.16/toolbox/vl_noprefix.m | 1,875 | utf_8 | 97d8755f0ba139ac1304bc423d3d86d3 | function vl_noprefix
% VL_NOPREFIX Create a prefix-less version of VLFeat commands
% VL_NOPREFIX() creats prefix-less stubs for VLFeat functions
% (e.g. SIFT for VL_SIFT). This function is seldom used as the stubs
% are included in the VLFeat binary distribution anyways. Moreover,
% on UNIX platforms, the stub... |
github | juliacamps/OR-master | vl_override.m | .m | OR-master/Practical_Session_Multiview_Analysis/code/vlfeat-0.9.16/toolbox/misc/vl_override.m | 4,654 | utf_8 | e233d2ecaeb68f56034a976060c594c5 | function config = vl_override(config,update,varargin)
% VL_OVERRIDE Override structure subset
% CONFIG = VL_OVERRIDE(CONFIG, UPDATE) copies recursively the fileds
% of the structure UPDATE to the corresponding fields of the
% struture CONFIG.
%
% Usually CONFIG is interpreted as a list of paramters with their
... |
github | juliacamps/OR-master | vl_quickvis.m | .m | OR-master/Practical_Session_Multiview_Analysis/code/vlfeat-0.9.16/toolbox/quickshift/vl_quickvis.m | 3,696 | utf_8 | 27f199dad4c5b9c192a5dd3abc59f9da | function [Iedge dists map gaps] = vl_quickvis(I, ratio, kernelsize, maxdist, maxcuts)
% VL_QUICKVIS Create an edge image from a Quickshift segmentation.
% IEDGE = VL_QUICKVIS(I, RATIO, KERNELSIZE, MAXDIST, MAXCUTS) creates an edge
% stability image from a Quickshift segmentation. RATIO controls the tradeoff
% bet... |
github | juliacamps/OR-master | vl_demo_aib.m | .m | OR-master/Practical_Session_Multiview_Analysis/code/vlfeat-0.9.16/toolbox/demo/vl_demo_aib.m | 2,928 | utf_8 | 590c6db09451ea608d87bfd094662cac | function vl_demo_aib
% VL_DEMO_AIB Test Agglomerative Information Bottleneck (AIB)
D = 4 ;
K = 20 ;
randn('state',0) ;
rand('state',0) ;
X1 = randn(2,300) ; X1(1,:) = X1(1,:) + 2 ;
X2 = randn(2,300) ; X2(1,:) = X2(1,:) - 2 ;
X3 = randn(2,300) ; X3(2,:) = X3(2,:) + 2 ;
figure(1) ; clf ; hold on ;
vl_plotframe(X... |
github | juliacamps/OR-master | vl_demo_alldist.m | .m | OR-master/Practical_Session_Multiview_Analysis/code/vlfeat-0.9.16/toolbox/demo/vl_demo_alldist.m | 5,460 | utf_8 | 6d008a64d93445b9d7199b55d58db7eb | function vl_demo_alldist
%
numRepetitions = 3 ;
numDimensions = 1000 ;
numSamplesRange = [300] ;
settingsRange = {{'alldist2', 'double', 'l2', }, ...
{'alldist', 'double', 'l2', 'nosimd'}, ...
{'alldist', 'double', 'l2' }, ...
{'alldist2', 's... |
github | juliacamps/OR-master | vl_demo_svmpegasos.m | .m | OR-master/Practical_Session_Multiview_Analysis/code/vlfeat-0.9.16/toolbox/demo/vl_demo_svmpegasos.m | 1,304 | utf_8 | 5470b2cbce41c6323cb562dbcd37556b | % VL_DEMO_SVMPEGASOS Demo: SVMPEGASOS: 2D linear learning
function vl_demo_svmpegasos
% Set up training data
Np = 200 ;
Nn = 200 ;
Xp = diag([1 3])*randn(2, Np) ;
Xn = diag([1 3])*randn(2, Nn) ;
Xp(1,:) = Xp(1,:) + 2 ;
Xn(1,:) = Xn(1,:) - 2 ;
X = [Xp Xn] ;
y = [ones(1,Np) -ones(1,Nn)] ;
figure(1)
plot(Xn(1,:),Xn(... |
github | juliacamps/OR-master | vl_demo_kdtree_sift.m | .m | OR-master/Practical_Session_Multiview_Analysis/code/vlfeat-0.9.16/toolbox/demo/vl_demo_kdtree_sift.m | 6,832 | utf_8 | e676f80ac330a351f0110533c6ebba89 | function vl_demo_kdtree_sift
% VL_DEMO_KDTREE_SIFT
% Demonstrates the use of a kd-tree forest to match SIFT
% features. If FLANN is present, this function runs a comparison
% against it.
% AUTORIGHS
rand('state',0) ;
randn('state',0);
do_median = 0 ;
do_mean = 1 ;
% try to setup flann
if ~exist('flann_search'... |
github | juliacamps/OR-master | vl_impattern.m | .m | OR-master/Practical_Session_Multiview_Analysis/code/vlfeat-0.9.16/toolbox/imop/vl_impattern.m | 6,702 | utf_8 | 7f5d173ebd720f7b89eccfa416aa71d3 | function im = vl_impattern(varargin)
% VL_IMPATTERN Generate an image from a stock pattern
% IM=VLPATTERN(NAME) returns an instance of the specified
% pattern. These stock patterns are useful for testing algoirthms.
%
% All generated patterns are returned as an image of class
% DOUBLE. Both gray-scale and colou... |
github | juliacamps/OR-master | vl_tpsu.m | .m | OR-master/Practical_Session_Multiview_Analysis/code/vlfeat-0.9.16/toolbox/imop/vl_tpsu.m | 1,755 | utf_8 | 09f36e1a707c069b375eb2817d0e5f13 | function [U,dU,delta]=vl_tpsu(X,Y)
% VL_TPSU Compute the U matrix of a thin-plate spline transformation
% U=VL_TPSU(X,Y) returns the matrix
%
% [ U(|X(:,1) - Y(:,1)|) ... U(|X(:,1) - Y(:,N)|) ]
% [ ]
% [ U(|X(:,M) - Y(:,1)|) ... U(|X(:,M) - Y(:,N)|) ]
%
% where X... |
github | juliacamps/OR-master | vl_xyz2lab.m | .m | OR-master/Practical_Session_Multiview_Analysis/code/vlfeat-0.9.16/toolbox/imop/vl_xyz2lab.m | 1,570 | utf_8 | 09f95a6f9ae19c22486ec1157357f0e3 | function J=vl_xyz2lab(I,il)
% VL_XYZ2LAB Convert XYZ color space to LAB
% J = VL_XYZ2LAB(I) converts the image from XYZ format to LAB format.
%
% VL_XYZ2LAB(I,IL) uses one of the illuminants A, B, C, E, D50, D55,
% D65, D75, D93. The default illuminatn is E.
%
% See also: VL_XYZ2LUV(), VL_HELP().
% Copyright ... |
github | juliacamps/OR-master | vl_test_twister.m | .m | OR-master/Practical_Session_Multiview_Analysis/code/vlfeat-0.9.16/toolbox/xtest/vl_test_twister.m | 1,162 | utf_8 | 1ae9040a416db503ad73600f081d096b | function results = vl_test_twister(varargin)
% VL_TEST_TWISTER
vl_test_init ;
function test_illegal_args()
vl_assert_exception(@() vl_twister(-1), 'vl:invalidArgument') ;
vl_assert_exception(@() vl_twister(1, -1), 'vl:invalidArgument') ;
vl_assert_exception(@() vl_twister([1, -1]), 'vl:invalidArgument') ;
function te... |
github | juliacamps/OR-master | vl_test_kdtree.m | .m | OR-master/Practical_Session_Multiview_Analysis/code/vlfeat-0.9.16/toolbox/xtest/vl_test_kdtree.m | 2,448 | utf_8 | 66f429ff8286089a34c193d7d3f9f016 | function results = vl_test_kdtree(varargin)
% VL_TEST_KDTREE
vl_test_init ;
function s = setup()
randn('state',0) ;
s.X = single(randn(10, 1000)) ;
s.Q = single(randn(10, 10)) ;
function test_nearest(s)
for tmethod = {'median', 'mean'}
for type = {@single, @double}
conv = type{1} ;
tmethod = char(tmethod) ;... |
github | juliacamps/OR-master | vl_test_imwbackward.m | .m | OR-master/Practical_Session_Multiview_Analysis/code/vlfeat-0.9.16/toolbox/xtest/vl_test_imwbackward.m | 514 | utf_8 | 33baa0784c8f6f785a2951d7f1b49199 | function results = vl_test_imwbackward(varargin)
% VL_TEST_IMWBACKWARD
vl_test_init ;
function s = setup()
s.I = im2double(imread(fullfile(vl_root,'data','spots.jpg'))) ;
function test_identity(s)
xr = 1:size(s.I,2) ;
yr = 1:size(s.I,1) ;
[x,y] = meshgrid(xr,yr) ;
vl_assert_almost_equal(s.I, vl_imwbackward(xr,yr,s.I,... |
github | juliacamps/OR-master | vl_test_pegasos.m | .m | OR-master/Practical_Session_Multiview_Analysis/code/vlfeat-0.9.16/toolbox/xtest/vl_test_pegasos.m | 5,428 | utf_8 | cc28a57ce6cf6ecba349d21698228e2e | function results = vl_test_pegasos(varargin)
% VL_TEST_KDTREE
vl_test_init ;
function s = setup()
randn('state',0) ;
s.biasMultiplier = 10 ;
s.lambda = 0.01 ;
Np = 10 ;
Nn = 10 ;
Xp = diag([1 3])*randn(2, Np) ;
Xn = diag([1 3])*randn(2, Nn) ;
Xp(1,:) = Xp(1,:) + 2 + 1 ;
Xn(1,:) = Xn(1,:) - 2 + 1 ;
s.X = [Xp Xn] ;
s... |
github | juliacamps/OR-master | vl_test_alphanum.m | .m | OR-master/Practical_Session_Multiview_Analysis/code/vlfeat-0.9.16/toolbox/xtest/vl_test_alphanum.m | 1,624 | utf_8 | 2da2b768c2d0f86d699b8f31614aa424 | function results = vl_test_alphanum(varargin)
% VL_TEST_ALPHANUM
vl_test_init ;
function s = setup()
s.strings = ...
{'1000X Radonius Maximus','10X Radonius','200X Radonius','20X Radonius','20X Radonius Prime','30X Radonius','40X Radonius','Allegia 50 Clasteron','Allegia 500 Clasteron','Allegia 50B Clasteron','Al... |
github | juliacamps/OR-master | vl_test_svmpegasos.m | .m | OR-master/Practical_Session_Multiview_Analysis/code/vlfeat-0.9.16/toolbox/xtest/vl_test_svmpegasos.m | 5,802 | utf_8 | dcd13a3246830b74817e8c44100db022 | function results = vl_test_svmpegasos(varargin)
% VL_TEST_KDTREE
vl_test_init ;
function s = setup()
randn('state',0) ;
s.biasMultiplier = 10 ;
s.lambda = 0.01 ;
Np = 10 ;
Nn = 10 ;
Xp = diag([1 3])*randn(2, Np) ;
Xn = diag([1 3])*randn(2, Nn) ;
Xp(1,:) = Xp(1,:) + 2 + 1 ;
Xn(1,:) = Xn(1,:) - 2 + 1 ;
s.X = [Xp Xn] ... |
github | juliacamps/OR-master | vl_test_cummax.m | .m | OR-master/Practical_Session_Multiview_Analysis/code/vlfeat-0.9.16/toolbox/xtest/vl_test_cummax.m | 762 | utf_8 | 3dddb5736dfffacdd94b156e67cb9c14 | function results = vl_test_cummax(varargin)
% VL_TEST_CUMMAX
vl_test_init ;
function test_basic()
vl_assert_almost_equal(...
vl_cummax(1), 1) ;
vl_assert_almost_equal(...
vl_cummax([1 2 3 4], 2), [1 2 3 4]) ;
function test_multidim()
a = [1 2 3 4 3 2 1] ;
b = [1 2 3 4 4 4 4] ;
for k=1:6
dims = ones(1,6) ;
dim... |
github | juliacamps/OR-master | vl_test_imintegral.m | .m | OR-master/Practical_Session_Multiview_Analysis/code/vlfeat-0.9.16/toolbox/xtest/vl_test_imintegral.m | 1,429 | utf_8 | 4750f04ab0ac9fc4f55df2c8583e5498 | function results = vl_test_imintegral(varargin)
% VL_TEST_IMINTEGRAL
vl_test_init ;
function state = setup()
state.I = ones(5,6) ;
state.correct = [ 1 2 3 4 5 6 ;
2 4 6 8 10 12 ;
3 6 9 12 15 18 ;
4 8 12 ... |
github | juliacamps/OR-master | vl_test_sift.m | .m | OR-master/Practical_Session_Multiview_Analysis/code/vlfeat-0.9.16/toolbox/xtest/vl_test_sift.m | 1,318 | utf_8 | 806c61f9db9f2ebb1d649c9bfcf3dc0a | function results = vl_test_sift(varargin)
% VL_TEST_SIFT
vl_test_init ;
function s = setup()
s.I = im2single(imread(fullfile(vl_root,'data','box.pgm'))) ;
[s.ubc.f, s.ubc.d] = ...
vl_ubcread(fullfile(vl_root,'data','box.sift')) ;
function test_ubc_descriptor(s)
err = [] ;
[f, d] = vl_sift(s.I,...
... |
github | juliacamps/OR-master | vl_test_binsum.m | .m | OR-master/Practical_Session_Multiview_Analysis/code/vlfeat-0.9.16/toolbox/xtest/vl_test_binsum.m | 1,301 | utf_8 | 5bbd389cbc4d997e413d809fe4efda6d | function results = vl_test_binsum(varargin)
% VL_TEST_BINSUM
vl_test_init ;
function test_three_args()
vl_assert_almost_equal(...
vl_binsum([0 0], 1, 2), [0 1]) ;
vl_assert_almost_equal(...
vl_binsum([1 7], -1, 1), [0 7]) ;
vl_assert_almost_equal(...
vl_binsum([1 7], -1, [1 2 2 2 2 2 2 2]), [0 0]) ;
function te... |
github | juliacamps/OR-master | vl_test_lbp.m | .m | OR-master/Practical_Session_Multiview_Analysis/code/vlfeat-0.9.16/toolbox/xtest/vl_test_lbp.m | 1,056 | utf_8 | 3b5cca50109af84014e56a4280a3352a | function results = vl_test_lbp(varargin)
% VL_TEST_TWISTER
vl_test_init ;
function test_one_on()
I = {} ;
I{1} = [0 0 0 ; 0 0 1 ; 0 0 0] ;
I{2} = [0 0 0 ; 0 0 0 ; 0 0 1] ;
I{3} = [0 0 0 ; 0 0 0 ; 0 1 0] ;
I{4} = [0 0 0 ; 0 0 0 ; 1 0 0] ;
I{5} = [0 0 0 ; 1 0 0 ; 0 0 0] ;
I{6} = [1 0 0 ; 0 0 0 ; 0 0 0] ;
I{7} = [0 1 0 ;... |
github | juliacamps/OR-master | vl_test_colsubset.m | .m | OR-master/Practical_Session_Multiview_Analysis/code/vlfeat-0.9.16/toolbox/xtest/vl_test_colsubset.m | 828 | utf_8 | be0c080007445b36333b863326fb0f15 | function results = vl_test_colsubset(varargin)
% VL_TEST_COLSUBSET
vl_test_init ;
function s = setup()
s.x = [5 2 3 6 4 7 1 9 8 0] ;
function test_beginning(s)
vl_assert_equal(1:5, vl_colsubset(1:10, 5, 'beginning')) ;
vl_assert_equal(1:5, vl_colsubset(1:10, .5, 'beginning')) ;
function test_ending(s)
vl_assert_equa... |
github | juliacamps/OR-master | vl_test_alldist.m | .m | OR-master/Practical_Session_Multiview_Analysis/code/vlfeat-0.9.16/toolbox/xtest/vl_test_alldist.m | 2,373 | utf_8 | 9ea1a36c97fe715dfa2b8693876808ff | function results = vl_test_alldist(varargin)
% VL_TEST_ALLDIST
vl_test_init ;
function s = setup()
vl_twister('state', 0) ;
s.X = 3.1 * vl_twister(10,10) ;
s.Y = 4.7 * vl_twister(10,7) ;
function test_null_args(s)
vl_assert_equal(...
vl_alldist(zeros(15,12), zeros(15,0), 'kl2'), ...
zeros(12,0)) ;
vl_assert_equa... |
github | juliacamps/OR-master | vl_test_ihashsum.m | .m | OR-master/Practical_Session_Multiview_Analysis/code/vlfeat-0.9.16/toolbox/xtest/vl_test_ihashsum.m | 581 | utf_8 | edc283062469af62056b0782b171f5fc | function results = vl_test_ihashsum(varargin)
% VL_TEST_IHASHSUM
vl_test_init ;
function s = setup()
rand('state',0) ;
s.data = uint8(round(16*rand(2,100))) ;
sel = find(all(s.data==0)) ;
s.data(1,sel)=1 ;
function test_hash(s)
D = size(s.data,1) ;
K = 5 ;
h = zeros(1,K,'uint32') ;
id = zeros(D,K,'uint8');
next = zer... |
github | juliacamps/OR-master | vl_test_grad.m | .m | OR-master/Practical_Session_Multiview_Analysis/code/vlfeat-0.9.16/toolbox/xtest/vl_test_grad.m | 434 | utf_8 | 4d03eb33a6a4f68659f868da95930ffb | function results = vl_test_grad(varargin)
% VL_TEST_GRAD
vl_test_init ;
function s = setup()
s.I = rand(150,253) ;
s.I_small = rand(2,2) ;
function test_equiv(s)
vl_assert_equal(gradient(s.I), vl_grad(s.I)) ;
function test_equiv_small(s)
vl_assert_equal(gradient(s.I_small), vl_grad(s.I_small)) ;
function test_equiv... |
github | juliacamps/OR-master | vl_test_whistc.m | .m | OR-master/Practical_Session_Multiview_Analysis/code/vlfeat-0.9.16/toolbox/xtest/vl_test_whistc.m | 1,384 | utf_8 | 81c446d35c82957659840ab2a579ec2c | function results = vl_test_whistc(varargin)
% VL_TEST_WHISTC
vl_test_init ;
function test_acc()
x = ones(1, 10) ;
e = 1 ;
o = 1:10 ;
vl_assert_equal(vl_whistc(x, o, e), 55) ;
function test_basic()
x = 1:10 ;
e = 1:10 ;
o = ones(1, 10) ;
vl_assert_equal(histc(x, e), vl_whistc(x, o, e)) ;
x = linspace(-1,11,100) ;
o =... |
github | juliacamps/OR-master | vl_test_roc.m | .m | OR-master/Practical_Session_Multiview_Analysis/code/vlfeat-0.9.16/toolbox/xtest/vl_test_roc.m | 1,019 | utf_8 | 9b2ae71c9dc3eda0fc54c65d55054d0c | function results = vl_test_roc(varargin)
% VL_TEST_ROC
vl_test_init ;
function s = setup()
s.scores0 = [5 4 3 2 1] ;
s.scores1 = [5 3 4 2 1] ;
s.labels = [1 1 -1 -1 -1] ;
function test_perfect_tptn(s)
[tpr,tnr] = vl_roc(s.labels,s.scores0) ;
vl_assert_almost_equal(tpr, [0 1 2 2 2 2] / 2) ;
vl_assert_almost_equal(tnr,... |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.