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 | lichao14442/RiGi-master | TestSuite.m | .m | RiGi-master/util/xunit/TestSuite.m | 13,145 | utf_8 | a2f83a7c15ba0ad13fa330aa59d1451a | %TestSuite Collection of TestComponent objects
% The TestSuite class defines a collection of TestComponent objects.
%
% TestSuite methods:
% TestSuite - Constructor
% add - Add test component to test suite
% print - Display test suite summary to Comman... |
github | lichao14442/RiGi-master | runtests.m | .m | RiGi-master/util/xunit/runtests.m | 4,841 | utf_8 | a24f89548b654b7bf0fc9ec25be2e2f2 | function out = runtests(varargin)
%runtests Run unit tests
% runtests runs all the test cases that can be found in the current directory
% and summarizes the results in the Command Window.
%
% Test cases can be found in the following places in the current directory:
%
% * An M-file function whose name start... |
github | lichao14442/RiGi-master | isTestCaseSubclass.m | .m | RiGi-master/util/xunit/+xunit/+utils/isTestCaseSubclass.m | 894 | utf_8 | 5c7e3f1d9b1eb3e2148cad3cde93c5c7 | function tf = isTestCaseSubclass(name)
%isTestCaseSubclass True for name of a TestCase subclass
% tf = isTestCaseSubclass(name) returns true if the string name is the name of
% a TestCase subclass on the MATLAB path.
% Steven L. Eddins
% Copyright 2008-2009 The MathWorks, Inc.
tf = false;
class_meta = meta.c... |
github | lichao14442/RiGi-master | arrayToString.m | .m | RiGi-master/util/xunit/+xunit/+utils/arrayToString.m | 2,972 | utf_8 | 173fdeb3960985834f7a252c7916fa32 | function s = arrayToString(A)
%arrayToString Convert array to string for display.
% S = arrayToString(A) converts the array A into a string suitable for
% including in assertion messages. Small arrays are converted using disp(A).
% Large arrays are displayed similar to the way structure field values display
% ... |
github | lichao14442/RiGi-master | compareFloats.m | .m | RiGi-master/util/xunit/+xunit/+utils/compareFloats.m | 4,376 | utf_8 | f77141ccf2a6b351c309eb9be4211065 | function result = compareFloats(varargin)
%compareFloats Compare floating-point arrays using tolerance.
% result = compareFloats(A, B, compare_type, tol_type, tol, floor_tol)
% compares the floating-point arrays A and B using a tolerance. compare_type
% is either 'elementwise' or 'vector'. tol_type is either 'r... |
github | lichao14442/RiGi-master | batchnorm_backward.m | .m | RiGi-master/layer/batchnorm_backward.m | 2,925 | utf_8 | ea5aed5d439f89e06ab2db7607187739 | function batchnorm_model = batchnorm_backward(batchnorm_model,ops, delta)
% forward of fullLinear layer
% model:
% ops: option
% lichao , 20160725
%
%% params
param_dim = batchnorm_model.param_dim;
outmap_size = batchnorm_model.outmap_size;
outmaps_num = batchnorm_model.outmaps_num;
axis_to_norm = batchnorm_model.axi... |
github | lichao14442/RiGi-master | batchnorm_forward.m | .m | RiGi-master/layer/batchnorm_forward.m | 4,162 | utf_8 | 25879507364b6939489090d4db3a02ff | function batchnorm_model = batchnorm_forward(batchnorm_model, x)
% forward of pooling2d layer
% model:
% x : input
% lichao , 20160717
%% params
param_dim = batchnorm_model.param_dim;
outmap_size = batchnorm_model.outmap_size;
outmaps_num = batchnorm_model.outmaps_num;
axis_to_norm = batchnorm_model.axis_to_norm;
run... |
github | lichao14442/RiGi-master | pooling2d_forward.m | .m | RiGi-master/layer/pooling2d_forward.m | 2,893 | utf_8 | 0ac9509963d28c655c1678a0a1d08acf | function pool2d_model = pooling2d_forward(pool2d_model, x)
% forward of pooling2d layer
% model:
% x : input
% lichao , 20160717
% only support 4d tensor 'whcn' order, 20160915
%% params
inmaps_num = pool2d_model.inmaps_num;
inmap_size = pool2d_model.inmap_size;
outmaps_num = pool2d_model.outmaps_num;
outmap_size = p... |
github | lichao14442/RiGi-master | check_grad_with_dummy.m | .m | RiGi-master/test/common/check_grad_with_dummy.m | 2,333 | utf_8 | 128e605165c839a164e5f1322914a428 | function check_grad_with_dummy(layer, x, y, p)
% used to check grad by stack a unit|stack layer with linear layer and a cost layer
% lichao, 20160830
%% (0) default paramters
if nargin < 4 % Linear
le_tol = 1e-11;
ge_tol = 1e-16;
epsilon = 1e-7;
iterations = 1;
verbose = 'true';
add_linear = 'f... |
github | hasanmdal/GraTFEL-Source-master | checkNumericalGradient.m | .m | GraTFEL-Source-master/GraTFEL/UnsupervisedFeatureExtractionLinkPrediction/MatlabImplSA/checkNumericalGradient.m | 1,982 | utf_8 | 689a352eb2927b0838af5dc508f6374d | function [] = checkNumericalGradient()
% This code can be used to check your numerical gradient implementation
% in computeNumericalGradient.m
% It analytically evaluates the gradient of a very simple function called
% simpleQuadraticFunction (see below) and compares the result with your numerical
% solution. Your num... |
github | hasanmdal/GraTFEL-Source-master | ExtractHiddenLayerBackUp.m | .m | GraTFEL-Source-master/GraTFEL/UnsupervisedFeatureExtractionLinkPrediction/MatlabImplSA/ExtractHiddenLayerBackUp.m | 2,817 | utf_8 | a0518f8ce238dd13054191d8ef9d717d | %trainFile: Train data features and labels
%testFile: Test data features and labels
%HS: Hidden layer size
%SP: sparsity parameter
%LM: weight decay parameter
%I: maximum iteration
%b: weight of sparsity penalty term
%n: number of nodes in graph
%et: number of edges missed due to preselection
function [TrainPC, Trai... |
github | hasanmdal/GraTFEL-Source-master | ExtractHiddenLayer.m | .m | GraTFEL-Source-master/GraTFEL/UnsupervisedFeatureExtractionLinkPrediction/MatlabImplSA/ExtractHiddenLayer.m | 2,944 | utf_8 | e8d2656b07c15305c545fe52f809c415 | %trainFile: Train data features and labels
%testFile: Test data features and labels
%HS: Hidden layer size
%SP: sparsity parameter
%LM: weight decay parameter
%I: maximum iteration
%b: weight of sparsity penalty term
%n: number of nodes in graph
%et: number of edges missed due to preselection
function [TrainPC, Trai... |
github | hasanmdal/GraTFEL-Source-master | sparseAutoencoderCost.m | .m | GraTFEL-Source-master/GraTFEL/UnsupervisedFeatureExtractionLinkPrediction/MatlabImplSA/sparseAutoencoderCost.m | 4,829 | utf_8 | 5ab7b6fd168e2104346561c25b532ad5 | function [cost,grad] = sparseAutoencoderCost(theta, visibleSize, hiddenSize, ...
lambda, sparsityParam, beta, data)
% visibleSize: the number of input units (probably 64)
% hiddenSize: the number of hidden units (probably 25)
% la... |
github | hasanmdal/GraTFEL-Source-master | sampleIMAGES.m | .m | GraTFEL-Source-master/GraTFEL/UnsupervisedFeatureExtractionLinkPrediction/MatlabImplSA/sampleIMAGES.m | 2,203 | utf_8 | ec0a50de07fd0e3c2e3a6bcd0531c7e7 | function patches = sampleIMAGES()
% sampleIMAGES
% Returns 10000 patches for training
load IMAGES; % load images from disk
patchsize = 8; % we'll use 8x8 patches
numpatches = 10000;
% Initialize patches with zeros. Your code will fill in this matrix--one
% column per patch, 10000 columns.
patches = zeros(pat... |
github | hasanmdal/GraTFEL-Source-master | WolfeLineSearch.m | .m | GraTFEL-Source-master/GraTFEL/UnsupervisedFeatureExtractionLinkPrediction/MatlabImplSA/minFunc/WolfeLineSearch.m | 11,478 | utf_8 | d10187f2fedfa4143ebd6300537b6be4 | function [t,f_new,g_new,funEvals,H] = WolfeLineSearch(...
x,t,d,f,g,gtd,c1,c2,LS,maxLS,tolX,debug,doPlot,saveHessianComp,funObj,varargin)
%
% Bracketing Line Search to Satisfy Wolfe Conditions
%
% Inputs:
% x: starting location
% t: initial step size
% d: descent direction
% f: function value at st... |
github | hasanmdal/GraTFEL-Source-master | minFunc_processInputOptions.m | .m | GraTFEL-Source-master/GraTFEL/UnsupervisedFeatureExtractionLinkPrediction/MatlabImplSA/minFunc/minFunc_processInputOptions.m | 3,704 | utf_8 | dc74c67d849970de7f16c873fcf155bc |
function [verbose,verboseI,debug,doPlot,maxFunEvals,maxIter,tolFun,tolX,method,...
corrections,c1,c2,LS_init,LS,cgSolve,qnUpdate,cgUpdate,initialHessType,...
HessianModify,Fref,useComplex,numDiff,LS_saveHessianComp,...
DerivativeCheck,Damped,HvFunc,bbType,cycle,...
HessianIter,outputFcn,useMex,use... |
github | Aritra-D/CRFAttentionProject-master | getMicrosaccadeData.m | .m | CRFAttentionProject-master/microsaccadeCodes/getMicrosaccadeData.m | 7,048 | utf_8 | 1522f76977765fcd851404597f0db63d | % Needs to be fixed
function getMicrosaccadeData
% Extract microsaccades. % MD: 02-07-2019;
% MD: modified 01-July-2020: removed option to save eye-data here, as it is saved in decimatedData file already.
if mainFlags.eyeDataFlag
try
clear saveFolder
if strcmpi(protocolType,'CON'); protType = 'Contrast';... |
github | Aritra-D/CRFAttentionProject-master | displayMicrosaccades_v2.m | .m | CRFAttentionProject-master/microsaccadeCodes/displayMicrosaccades_v2.m | 28,725 | utf_8 | 89ead97d11afb5dc13948527733383f7 | function figH = displayMicrosaccades_v2(folderSave,eyeDataDegXOrig,eyeDataDegYOrig,trialNums,protNumForTrial,subjectName,protocolType,FsEyes,eyeRangeMS,saveDataFlag,threshold,timeRange,minCutOff,minMSLength,fixationWindowWidth,optimiseFlag)
% Defaults
if ~exist('threshold','var') || isempty(threshold); threshold = 3; ... |
github | Aritra-D/CRFAttentionProject-master | findBadTrialsWithEEG_Nilanjana.m | .m | CRFAttentionProject-master/extractionCodes/findBadTrialsWithEEG_Nilanjana.m | 14,553 | utf_8 | 9940d5ee93f2db98d3850d508560921b | % This is the main program used to find bad trials in EEG data.
% Note: This program was built on top of findBadTrialsEEG_GAV_v2 to _v5.
% This program was used for finding bad trials for 350 subjects who were
% part of ADGammaProject. This program will be modified in future commits
% to be compatible with the data fo... |
github | Aritra-D/CRFAttentionProject-master | findBadTrialsWithEEG_SRCLong_v10.m | .m | CRFAttentionProject-master/extractionCodes/findBadTrialsWithEEG_SRCLong_v10.m | 17,376 | utf_8 | 4571d71955372458a5a4e0ca72328770 | function [badTrials,allBadTrials,badTrialsUnique,badElecs,totalTrials,slopeValsVsFreq]=findBadTrialsWithEEG_SRCLong_v10(subjectName,expDate,protocolName,folderSourceString,gridType,badEEGElectrodes,nonEEGElectrodes,impedanceTag,capType,saveDataFlag,badTrialNameStr,displayResultsFlag)
if ~exist('gridType','var'); ... |
github | Aritra-D/CRFAttentionProject-master | findGoodPosBL.m | .m | CRFAttentionProject-master/extractionCodes/findGoodPosBL.m | 1,692 | utf_8 | 1aba54f72a8f59e5076048671f9d134d | % find goodStimNums for Baseline for SF-Ori Protocols without interStim
% Period
function [goodBLPos,goodBLPos_trialNum] = findGoodPosBL(subjectName,expDate,protocolName,gridType,folderSourceString)
folderExtract = fullfile(folderSourceString,'data',subjectName,gridType,expDate,protocolName,'extractedData');
lo... |
github | Aritra-D/CRFAttentionProject-master | plotComparison.m | .m | CRFAttentionProject-master/analysisCodes/MonkeyLFP-HumanEEG_Comparison/plotComparison.m | 8,869 | utf_8 | e7ca7feaab4b0588215524af63704559 | function plotComparison
load('E:\Projects\Aritra_AttentionEEGProject\Figures\Mayo Project- Monkey V4 LFP Attention\figure_1_and_3_data\Figure1Dataset_allAllStimulatedOri23_tapers23.mat'); %#ok<LOAD>
close all;
hFig = figure(1);
set(hFig,'units','normalized','outerposition',[0 0 1 1])
hPlotsFig.hPlot2 = getPlotHandles(... |
github | Aritra-D/CRFAttentionProject-master | plotBehavior_SRCProtocols.m | .m | CRFAttentionProject-master/analysisCodes/IndividualSubject/plotBehavior_SRCProtocols.m | 19,165 | utf_8 | 1c972b27115b7bcb101d0034b102f89c | function plotBehavior_SRCProtocols(protocolType,subjectIdx,convertOriValsInLogScale)
close all;
if ~exist('folderSourceString','var'); folderSourceString='E:\'; end
if ~exist('gridType','var'); gridType='EEG'; end
fileName = fullfile(folderSourceString,'Projects\Aritra_AttentionEEGProject\save... |
github | Aritra-D/CRFAttentionProject-master | plotFigures_MappingProtocol_HumanEEG_IndividualSubjects.m | .m | CRFAttentionProject-master/analysisCodes/IndividualSubject/plotFigures_MappingProtocol_HumanEEG_IndividualSubjects.m | 11,918 | utf_8 | 9622163229b58787bb0e20f23b032b8a | function plotFigures_MappingProtocol_HumanEEG_IndividualSubjects(protocolType)
if ~exist('folderSourceString','var'); folderSourceString='E:\'; end
if ~exist('gridType','var'); gridType='EEG'; end
tapers = [1 1];
timingParamters.blRange = [-0.5 0];
timingParamters.stRange = [0.25 0.75... |
github | Aritra-D/CRFAttentionProject-master | displayBehavioralData_SRCProtocol.m | .m | CRFAttentionProject-master/analysisCodes/IndividualSubject/displayBehavioralData_SRCProtocol.m | 8,287 | utf_8 | 0cabebb9007933a68f0f06b680c8f1c9 |
function [side0,side1,eotByType,colorNames,contrastIndices,correctResults,xValAll,reactTimesAll]= displayBehavioralData_SRCProtocol(subjectName,expDate,protocolName,gridType,folderSourceString)
% LL File Info
LLFileName = fullfile(folderSourceString,'data',subjectName,gridType,expDate,protocolName,'extractedData... |
github | Aritra-D/CRFAttentionProject-master | displayResultsCommonProtocolsHumanEEG.m | .m | CRFAttentionProject-master/analysisCodes/IndividualSubject/displayResultsCommonProtocolsHumanEEG.m | 33,031 | utf_8 | 1cd72061ee84b043f1b454735a56ccfe | % This program displays PSDs of Eyes Open vs Eyes Closed, SSVEP PSD, and
% PSDs for each SF and Ori conditions set in a GRF protocol
% for Unipolar (Figure 1) and Bipolar Referencing (Figure 2)
% It has an additional option to plot difference in PSDs.
function displayResultsCommonProtocolsHumanEEG(subjectName,ex... |
github | Aritra-D/CRFAttentionProject-master | displayLLInforAllDaysSRC_CRFAttention.m | .m | CRFAttentionProject-master/analysisCodes/IndividualSubject/displayLLInforAllDaysSRC_CRFAttention.m | 28,498 | utf_8 | d0e528dbe9db8184809bd75a953452d1 | % This program is adapted from displayLLInforAllDaysSRC. This has been
% modified for the CRFAttention project.
function displayLLInforAllDaysSRC_CRFAttention(subjectName,expDates,protocolNames,folderSourceString,gridType,removeBreaks,removeIgnores,convertOriValsInLogScale)
if ~exist('removeBreaks','var'); ... |
github | Aritra-D/CRFAttentionProject-master | displayResultsMappingProtocolsHumanEEG_v2.m | .m | CRFAttentionProject-master/analysisCodes/IndividualSubject/displayResultsMappingProtocolsHumanEEG_v2.m | 25,092 | utf_8 | b6e1300cd630a0f6fb84b7d4b13c8c9d | function displayResultsMappingProtocolsHumanEEG_v2...
(subjectName,expDate,protocolIDs,folderSourceString,gridType,...
sideChoice,analysisType,tapers_MT,stimType,plotPSDFlag,displayDeltaPSDFlag)
if ~exist('folderSourceString','var'); folderSourceString='E:\data\human\SFOri-Mapping'; end
if ~exist(... |
github | Aritra-D/CRFAttentionProject-master | getGoodStimNums_SRCLong.m | .m | CRFAttentionProject-master/analysisCodes/allSubjects/getGoodStimNums_SRCLong.m | 3,082 | utf_8 | b1dd52a0ff582f9f5434ec335e2c9c7f | % This program is used to find a subset of stimuli for matching hit and
% miss conditions such that the target onset times are matched in
% histograms of size targetTimeBinWidthMS. See code for details.
% allTargetOnsetTimes - cell array of size numSession x 12, where the 12
% conditions are
% {'H0V_0Hz','H1V_0Hz','H... |
github | Aritra-D/CRFAttentionProject-master | plotBehaviorSummary_SRCLongProtocols_Attention.m | .m | CRFAttentionProject-master/analysisCodes/allSubjects/plotBehaviorSummary_SRCLongProtocols_Attention.m | 8,860 | utf_8 | cd2e06d49102095632a58578a5851792 | function plotBehaviorSummary_SRCLongProtocols_Attention(subjectIdx,getTFIndexFromTargetDescFlag,statTest)
close all;
if ~exist('folderSourceString','var'); folderSourceString='E:\'; end
% if ~exist('gridType','var'); gridType='EEG'; end
protocolType = 'SRC-Long';
fileName = fullfile(folderSour... |
github | Aritra-D/CRFAttentionProject-master | getData_SRCLongProtocols_v1.m | .m | CRFAttentionProject-master/analysisCodes/allSubjects/getData_SRCLongProtocols_v1.m | 32,648 | utf_8 | 9402b3eec8c20f4fe901e2c17726e2a4 | function [erpData,fftData,energyData,freqRanges_SubjectWise,badHighPriorityElecs,badElecs] = getData_SRCLongProtocols_v1(protocolType,gridType,timingParameters,tapers,badTrialStr,removeBadEyeTrialsFlag)
[subjectNames,expDates,protocolNames,dataFolderSourceString] = dataInformationSRCProtocols_HumanEEG(gridType,protoco... |
github | Aritra-D/CRFAttentionProject-master | displayChapter5Figure6.m | .m | CRFAttentionProject-master/analysisCodes/allSubjects/displayChapter5Figure6.m | 43,892 | utf_8 | 913b94a5e495bbeb019c24795b1c3c2e | % This program displays Topoplots,change in Power wrt to Baseline for
% flickering stimuli, PSD, deltaPSD and Delta Power Changes for selected electrodes
% for attended and Ignored conditions
function displayChapter5Figure6(protocolType,...
subjectIdx,timeEpoch,eotCodeIdx,removeBadElectrodeData,...
BaselineCon... |
github | Aritra-D/CRFAttentionProject-master | getData_MappingProtocols.m | .m | CRFAttentionProject-master/analysisCodes/allSubjects/getData_MappingProtocols.m | 17,717 | utf_8 | 5ecef8d1753ae82bfe497f9d8f51b18c | function [fftData,energyData,energyDataTF,badHighPriorityElecs,badElecs] = getData_MappingProtocols(protocolType,gridType,timingParameters,tapers,freqRanges,badTrialStr,removeBadEyeTrialsFlag)
[subjectNames,expDates,protocolNames,dataFolderSourceString] = dataInformationMappingProtocols_HumanEEG(gridType,protocolTyp... |
github | Aritra-D/CRFAttentionProject-master | displayResults_HitsVsMisses_StaticResults.m | .m | CRFAttentionProject-master/analysisCodes/allSubjects/displayResults_HitsVsMisses_StaticResults.m | 30,135 | utf_8 | d1d19415e52dae1c481f39e7681589f1 | function displayResults_HitsVsMisses_StaticResults...
(protocolType,analysisMethodFlag,...
subjectIdx,timeEpoch,removeBadElectrodeData,...
BaselineCondition,topoplot_style,colorMap) %#ok<*INUSL,*INUSD>
close all;
if ~exist('gridType','var'); gridType='EEG'; end
capType = 'actiCap64';
numFre... |
github | Aritra-D/CRFAttentionProject-master | displayResults_AttendVsIgnored.m | .m | CRFAttentionProject-master/analysisCodes/allSubjects/displayResults_AttendVsIgnored.m | 47,767 | utf_8 | dd2aeb17705edf218fa3c31b57769924 | % This program change in Power wrt to Baseline Topoplots for static
% and flickering stimuli, ERP,PSD and Delta Power Changes for attended and
% Ignored conditions
function displayResults_AttendVsIgnored(protocolType,analysisMethodFlag,...
subjectIdx,timeEpoch,eotCodeIdx,removeBadElectrodeData,...
plotBaseline... |
github | Aritra-D/CRFAttentionProject-master | displayChapter5Figure5.m | .m | CRFAttentionProject-master/analysisCodes/allSubjects/displayChapter5Figure5.m | 28,305 | utf_8 | 5efd4d41330594930a4fffe5d5805db9 | % This program change in Power wrt to Baseline Topoplots for static
% stimuli, PSD, deltaPSD and Delta Power Changes for attended and
% Ignored conditions
function displayChapter5Figure5(protocolType,analysisMethodFlag,...
subjectIdx,timeEpoch,eotCodeIdx,removeBadElectrodeData,...
plotBaselineSubtractedPowerFl... |
github | Aritra-D/CRFAttentionProject-master | getData_SFORIProtocols.m | .m | CRFAttentionProject-master/analysisCodes/allSubjects/getData_SFORIProtocols.m | 21,256 | utf_8 | c782b40a0121199ac20c5bcfccf7c7c0 | function [fftData,energyData,energyDataTF,badHighPriorityElecs,badElecs] = getData_SFORIProtocols(protocolType,gridType,timingParameters,tapers,freqRanges,badTrialStr,removeBadEyeTrialsFlag)
[subjectNames,expDates,protocolNames,maxGamma_SFIndex,...
maxGamma_OriIndex,dataFolderSourceString]...
= dataInformation... |
github | Aritra-D/CRFAttentionProject-master | displayFigure6.m | .m | CRFAttentionProject-master/analysisCodes/allSubjects/displayFigure6.m | 43,007 | utf_8 | f1ce29e797347b7aa17fa21c0ae09ac6 |
% This program displays Topoplots,change in Power wrt to Baseline for
% flickering stimuli, PSD, deltaPSD and Delta Power Changes for selected electrodes
% for attended and Ignored conditions
function displayFigure6(protocolType,...
subjectIdx,timeEpoch,eotCodeIdx,removeBadElectrodeData,...
BaselineCondition,... |
github | Aritra-D/CRFAttentionProject-master | displayPhotoDiodeData_SRCLongProtocol.m | .m | CRFAttentionProject-master/analysisCodes/allSubjects/displayPhotoDiodeData_SRCLongProtocol.m | 19,374 | utf_8 | 545a1b7fae67d1bc8d1ee29a382c0527 | function displayPhotoDiodeData_SRCLongProtocol(protocolType,analysisTypeFlag,analysisMethodFlag,SubjectNum,AttendLoc)
% close all;
if ~exist('folderSourceString','var'); folderSourceString='E:\'; end
if ~exist('gridType','var'); gridType='EEG'; end
tapers = [1 1];
timingParamters.blRang... |
github | Aritra-D/CRFAttentionProject-master | getData_HitsVsMisses_SRCLong.m | .m | CRFAttentionProject-master/analysisCodes/allSubjects/getData_HitsVsMisses_SRCLong.m | 16,167 | utf_8 | b8991ec9ef666a3e299240d41ce1c694 | function [psdData,freqRanges_SubjectWise,badHighPriorityElecs,badElecs] = getData_HitsVsMisses_SRCLong(protocolType,gridType,badTrialStr,targetOnsetMatchingChoice,targetTimeBinWidthMS,bootstrapTimes)
close all;
if ~exist('gridType','var'); gridType='EEG'; end
[subjectNames,expDates,protocolNames,data... |
github | Aritra-D/CRFAttentionProject-master | displayCombinedResults_AttendVsIgnored.m | .m | CRFAttentionProject-master/analysisCodes/allSubjects/displayCombinedResults_AttendVsIgnored.m | 25,839 | utf_8 | dd24a3ec1d5ff4f0d05a1ca9c8477fa4 | % This program change in Power wrt to Baseline Topoplots for static
% and flickering stimuli, ERP,PSD and Delta Power Changes for attended and
% Ignored conditions. This program furthermore combines the band powers for
% static and flickering stimuli and combines SSVEP powers for 24 and 32 Hz
function statData = displ... |
github | Aritra-D/CRFAttentionProject-master | displayResults_HitsVsMisses_ConsolidatedResults.m | .m | CRFAttentionProject-master/analysisCodes/allSubjects/displayResults_HitsVsMisses_ConsolidatedResults.m | 36,443 | utf_8 | 95b5a68edb0bc77cbf633a32e1bcd0f4 | function displayResults_HitsVsMisses_ConsolidatedResults...
(protocolType,analysisMethodFlag,...
subjectIdx,timeEpoch,removeBadElectrodeData,...
BaselineCondition,topoplot_style,colorMap,...
showNeuralMeasure,statTest) %#ok<*INUSL,*INUSD>
close all;
if ~exist('gridType','var'); gridType='EEG... |
github | Aritra-D/CRFAttentionProject-master | displayFigure5.m | .m | CRFAttentionProject-master/analysisCodes/allSubjects/displayFigure5.m | 27,874 | utf_8 | 0276c6be794a9344ca49e23ce23a77c7 | % This program change in Power wrt to Baseline Topoplots for static
% stimuli, PSD, deltaPSD and Delta Power Changes for attended and
% Ignored conditions
function displayFigure5(protocolType,analysisMethodFlag,...
subjectIdx,timeEpoch,eotCodeIdx,removeBadElectrodeData,...
plotBaselineSubtractedPowerFlag,topop... |
github | Aritra-D/CRFAttentionProject-master | plotFigures_SFORIProtocols_HumanEEG_v2.m | .m | CRFAttentionProject-master/analysisCodes/allSubjects/plotFigures_SFORIProtocols_HumanEEG_v2.m | 18,966 | utf_8 | bec25943583577191b409266728fa4d7 | % This version only analyzes total Gamma for Unipolar Ref Scheme; used in
% Thesis and Paper
function plotFigures_SFORIProtocols_HumanEEG_v2(protocolType,...
SSVEPAnalysisMethod,removeBadElectrodeData,subjectIdx,topoplot_style,badTrialStr)
close all;
if ~exist('folderSourceString','var'); folderSourceString='E:\... |
github | Aritra-D/CRFAttentionProject-master | getData_SRCLongProtocols.m | .m | CRFAttentionProject-master/analysisCodes/allSubjects/getData_SRCLongProtocols.m | 16,591 | utf_8 | 48cc82639678bdfaa1c85d07bdc3893e | function [full_data] = getData_SRCLongProtocols(protocolType,gridType)
capType = 'actiCap64';
get_data_for_all_subjects(protocolType, gridType, capType);
end
% Accessory Functions
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%%%%%%%%%%%%%%%%%%%%%%%%%%% Accessory Functions %%%... |
github | Aritra-D/CRFAttentionProject-master | displayResults_AttVsIgn_FlickerStimuli.m | .m | CRFAttentionProject-master/analysisCodes/allSubjects/displayResults_AttVsIgn_FlickerStimuli.m | 40,811 | utf_8 | d0c3111a0dc01f07d1fd94a14fbb0389 | % This program displays Topoplots,change in Power wrt to Baseline for
% flickering stimuli, PSD and Delta Power Changes for selected electrodes
% for attended and Ignored conditions
function displayResults_AttVsIgn_FlickerStimuli(protocolType,analysisMethodFlag,...
subjectIdx,timeEpoch,eotCodeIdx,removeBadElectrod... |
github | Aritra-D/CRFAttentionProject-master | getData_HitsVsMisses_SRCLong_trialWise.m | .m | CRFAttentionProject-master/analysisCodes/allSubjects/getData_HitsVsMisses_SRCLong_trialWise.m | 16,315 | utf_8 | 74c48fcfa4880a9aa309457260be4985 | function [psdData,freqRanges_SubjectWise,badHighPriorityElecs,badElecs] =...
getData_HitsVsMisses_SRCLong_trialWise(protocolType,gridType,...
badTrialStr,bootstrapTimes,targetOnsetMatchingChoice,targetTimeBinWidthMS)
[subjectNames,expDates,protocolNames,dataFolderSourceString] = dataInformationSRCProtocols_Hu... |
github | Aritra-D/CRFAttentionProject-master | plotFigures_MappingProtocols_HumanEEG.m | .m | CRFAttentionProject-master/analysisCodes/allSubjects/plotFigures_MappingProtocols_HumanEEG.m | 36,115 | utf_8 | 192cceaba866002159014ba068865877 | function plotFigures_MappingProtocols_HumanEEG(protocolType2,...
SSVEPAnalysisMethod,removeBadElectrodeData,subjectIdx,plotConsolidatedResultsFlag,topoplot_style,badTrialStr)
close all;
if ~exist('folderSourceString','var'); folderSourceString='E:\'; end
if ~exist('gridType','var'); gridT... |
github | Aritra-D/CRFAttentionProject-master | plotFigures_SRCProtocols_HumanEEG.m | .m | CRFAttentionProject-master/analysisCodes/allSubjects/plotFigures_SRCProtocols_HumanEEG.m | 30,477 | utf_8 | 6f8add0ff57b2846ee06bce4dc6ea060 | function plotFigures_SRCProtocols_HumanEEG(protocolType,analysisMethod,SSVEP_AnalysisMethodFlag,plotPSDFlag,plotDeltaPSDFlag,subjectIdx,eotCodeIdx)
close all;
if ~exist('folderSourceString','var'); folderSourceString='E:\'; end
if ~exist('gridType','var'); gridType='EEG'; end
tapers = [1... |
github | Aritra-D/CRFAttentionProject-master | displayResults_HitsVsMisses.m | .m | CRFAttentionProject-master/analysisCodes/allSubjects/displayResults_HitsVsMisses.m | 45,052 | utf_8 | c407a6764b014ef0252863ce0ec3afb3 | function displayResults_HitsVsMisses(protocolType,analysisMethodFlag,...
subjectIdx,timeEpoch,removeBadElectrodeData,...
plotBaselineSubtractedPowerFlag,topoplot_style,colorMap)
close all;
if ~exist('folderSourceString','var'); folderSourceString='E:\'; end
if ~exist('gridType','var'); gridT... |
github | Aritra-D/CRFAttentionProject-master | displayConsolidatedResults_AttendVsIgnored.m | .m | CRFAttentionProject-master/analysisCodes/allSubjects/displayConsolidatedResults_AttendVsIgnored.m | 41,950 | utf_8 | 80ac5f09a3764d9eb2f0f6cc43e11243 | % This program change in Power wrt to Baseline Topoplots for static
% and flickering stimuli, ERP,PSD and Delta Power Changes for attended and
% Ignored conditions
function displayConsolidatedResults_AttendVsIgnored(protocolType,...
subjectIdx,timeEpoch,eotCodeIdx,removeBadElectrodeData,...
plotBaselineSubtrac... |
github | Aritra-D/CRFAttentionProject-master | plotFigures_SFORIProtocols_HumanEEG.m | .m | CRFAttentionProject-master/analysisCodes/allSubjects/plotFigures_SFORIProtocols_HumanEEG.m | 17,004 | utf_8 | 89b30930b1661a15d7bc21236df5f60e | % Plots Gamma power in Bipolar Ref Scheme; prior to finalizing of Thesis
% and Paper
function plotFigures_SFORIProtocols_HumanEEG(protocolType,...
SSVEPAnalysisMethod,removeBadElectrodeData,subjectIdx,topoplot_style)
close all;
if ~exist('folderSourceString','var'); folderSourceString='E:\'; end
if ~exist... |
github | Aritra-D/CRFAttentionProject-master | getAllTargetOnsetTimes.m | .m | CRFAttentionProject-master/analysisCodes/allSubjects/getAllTargetOnsetTimes.m | 3,146 | utf_8 | 34347804963d526c86498db68a1578c9 | function allTargetOnsetTimes = getAllTargetOnsetTimes(gridType,protocolType,badTrialStr)
[subjectNames,expDates,protocolNames,dataFolderSourceString] = dataInformationSRCProtocols_HumanEEG(gridType,protocolType);
allTargetOnsetTimes = cell(1,length(subjectNames));
for iSub=1:length(subjectNames)
% Load Target Ons... |
github | Aritra-D/CRFAttentionProject-master | displayBadTrialsPercentage.m | .m | CRFAttentionProject-master/unusedCodes/displayBadTrialsPercentage.m | 5,316 | utf_8 | a3595e1c971aa8783eff468213ae8ac8 | function [badTrialPercentage,badElecs,UnipolarbadElecPercentage,BipolarbadElecPercentage] = displayBadTrialsPercentage(protocolType,gridType,BadEyeTrialsFlag,badTrialStr)
if strcmp(protocolType,'SRC-Long')
[subjectNames,expDates,protocolNames,dataFolderSourceString] = dataInformationSRCProtocols_HumanEEG(gridType,p... |
github | Aritra-D/CRFAttentionProject-master | findBadTrialsWithEEG_SRCLong_v10.m | .m | CRFAttentionProject-master/unusedCodes/findBadTrialsWithEEG_SRCLong_v10.m | 17,345 | utf_8 | 4be8966832dbc8f40d296ee6e28af654 | function [badTrials,allBadTrials,badTrialsUnique,badElecs,totalTrials,slopeValsVsFreq]=findBadTrialsWithEEG_SRCLong_v10(subjectName,expDate,protocolName,folderSourceString,gridType,badEEGElectrodes,nonEEGElectrodes,impedanceTag,capType,saveDataFlag,badTrialNameStr,displayResultsFlag)
if ~exist('gridType','var'); ... |
github | Aritra-D/CRFAttentionProject-master | findBadTrialsWithEEG_SRCLong_v7.m | .m | CRFAttentionProject-master/unusedCodes/findBadTrialsWithEEG_SRCLong_v7.m | 17,308 | utf_8 | d62300ac7e4182eb88fc34be369fb3ac | % This is the main program used to find bad trials in EEG data.
% Note: This program was built on top of findBadTrialsEEG_GAV_v2 to _v5.
% This program was used for finding bad trials for 350 subjects who were
% part of ADGammaProject. This program will be modified in future commits
% to be compatible with the data fo... |
github | Aritra-D/CRFAttentionProject-master | getElectrodeList.m | .m | CRFAttentionProject-master/informationFiles/getElectrodeList.m | 8,936 | utf_8 | 8c28856ed0f756da352f1ebfe10b58c2 | function [electrodeList,elecTags,elecNums] = getElectrodeList(capLayout,refType,topoplotFlag)
if ~exist('topoplotFlag','var'); topoplotFlag=0; end
if topoplotFlag
electrodeList = getElectrodeListForTopoplots(capLayout,refType);
elecTags = [];
elecNums = [];
else % get selected ... |
github | Aritra-D/CRFAttentionProject-master | removeDimIfSingleton.m | .m | CRFAttentionProject-master/miscCodes/removeDimIfSingleton.m | 266 | utf_8 | c4c3e8ebbd58973acbe17704ffe1b7cb | % MD: 06/05/2016
function newMatrix = removeDimIfSingleton(oldMatrix,dim)
z = size(oldMatrix);
if nargin<2; dim = 1; end
if z(dim) == 1
z(dim) = [];
newMatrix = reshape(oldMatrix,[z 1]);
else
newMatrix = oldMatrix;
end
end |
github | Aritra-D/CRFAttentionProject-master | concatenateCellArrayToMatrix.m | .m | CRFAttentionProject-master/miscCodes/concatenateCellArrayToMatrix.m | 1,219 | utf_8 | f5a9416c592864df3355afe3f9059977 | % cellArray must be 1xN cell; each vector of the cell must be a matrix of size Mx1
% This function returns an MxN matrix
function newMatrix = concatenateCellArrayToMatrix(cellArray)
cols = size(cellArray,2);
cellElementRows = cellfun(@length,cellArray);
numRowsElement = unique(cellElementRows);
discor... |
github | Aritra-D/CRFAttentionProject-master | topoplot_murty.m | .m | CRFAttentionProject-master/displayCodes/topoplot_murty.m | 70,356 | utf_8 | fead94c5d693ecf6d2be92bfa37b8021 | % topoplot() - plot a topographic map of a scalp data field in a 2-D circular view
% (looking down at the top of the head) using interpolation on a fine
% cartesian grid. Can also show specified channnel location(s), or return
% an interpolated value at an arbitrary scalp locat... |
github | Aritra-D/CRFAttentionProject-master | makeBox.m | .m | CRFAttentionProject-master/displayCodes/makeBox.m | 1,936 | utf_8 | 2bca3177a34dd028db16bbd1db8cc58e | % code by Supratim; Modified by MD
function makeBox(h,xRange,yRange,colorName,lineWidth,lineStyle,boxType)
if ~exist('colorName','var') || isempty(colorName); colorName=[0 0 0]; end
if ~exist('lineWidth','var') || isempty(lineWidth); lineWidth=0.5; end
if ~exist('lineS... |
github | Aritra-D/CRFAttentionProject-master | displayAnalyzedData.m | .m | CRFAttentionProject-master/displayCodes/displayAnalyzedData.m | 13,368 | utf_8 | 7add71edac9eb98dea6df67bf0347a40 | % This program displays the data saved in the analyzedData folder
% subjectNameList is a cell array, with each cell containing a list of
% subjects. For example, subjectNameList{1} could contain all MCI/AD subjects
% while subjectNameList{2} could contain all their controls.
% Option added to send a 2D array of subje... |
github | antran89/New-C3D-Caffe-master | classification_demo.m | .m | New-C3D-Caffe-master/matlab/demo/classification_demo.m | 5,412 | utf_8 | 8f46deabe6cde287c4759f3bc8b7f819 | function [scores, maxlabel] = classification_demo(im, use_gpu)
% [scores, maxlabel] = classification_demo(im, use_gpu)
%
% Image classification demo using BVLC CaffeNet.
%
% IMPORTANT: before you run this demo, you should download BVLC CaffeNet
% from Model Zoo (http://caffe.berkeleyvision.org/model_zoo.html)
%
% *****... |
github | VLAM3D/caffe-master | classification_demo.m | .m | caffe-master/matlab/demo/classification_demo.m | 5,412 | utf_8 | 8f46deabe6cde287c4759f3bc8b7f819 | function [scores, maxlabel] = classification_demo(im, use_gpu)
% [scores, maxlabel] = classification_demo(im, use_gpu)
%
% Image classification demo using BVLC CaffeNet.
%
% IMPORTANT: before you run this demo, you should download BVLC CaffeNet
% from Model Zoo (http://caffe.berkeleyvision.org/model_zoo.html)
%
% *****... |
github | cxj273/NI-SVM-master | classification_demo.m | .m | NI-SVM-master/0-Prerequisite/00-FeatureExtraction/caffe/matlab/demo/classification_demo.m | 5,412 | utf_8 | 8f46deabe6cde287c4759f3bc8b7f819 | function [scores, maxlabel] = classification_demo(im, use_gpu)
% [scores, maxlabel] = classification_demo(im, use_gpu)
%
% Image classification demo using BVLC CaffeNet.
%
% IMPORTANT: before you run this demo, you should download BVLC CaffeNet
% from Model Zoo (http://caffe.berkeleyvision.org/model_zoo.html)
%
% *****... |
github | cxj273/NI-SVM-master | fisherMat2C.m | .m | NI-SVM-master/0-Prerequisite/00-FeatureExtraction/traj_pipeline/src/fisher_pipe/fisherMat2C.m | 457 | utf_8 | d3fb87b94f41a2a15d8624c8a38c3b44 | function fisherMat2C(codebook_mat, pca_mat, codebook_out, pca_out)
load(codebook_mat);
load(pca_mat);
fid = fopen(codebook_out, 'w');
output(fid, codebook.mean);
output(fid, codebook.variance);
output(fid, codebook.coef);
fclose(fid);
fid = fopen(pca_out, 'w');
output(fid, pca_proj);
fclose(fid);
end
functio... |
github | cxj273/NI-SVM-master | prox_iso.m | .m | NI-SVM-master/2-NearlyIsotonicSVM/prox_iso.m | 2,523 | utf_8 | d7e617dc369e9cbecd8d83cb5593903a | function [z, r, ub] = prox_iso(g, w, eta, lambda, gamma, ind)
%GOAL ub = min_z <z-w, g> + 1/2/eta*|z-w|^2 + ...
% lambda*|z|_{iso} + [gamma*|z|_1 or gamma*|z|_2^2]
% r = lambda*|z|_{iso} + [gamma*|z|_1 or gamma*|z|_2^2]
% vector ind indicates which method we are using
% ind(1)... |
github | XiongDuan/deepsketch-master | voting_test.m | .m | deepsketch-master/voting_test.m | 3,498 | utf_8 | 43f5bd6e8571afbdb4f816dac774a609 | function voting_test(dbPath)
[net, IMAGE_MEAN] = set_net();
IMAGE_DIM = 227;
% first, record all the augmentation images set
subfolders = dir(dbPath);
voteclass = {};
for ii = 1:length(subfolders)
subname = subfolders(ii).name;
if ~strcmp(subname, '.') && ~strcmp(subname, '..') && subfolders(ii).isdir
... |
github | XiongDuan/deepsketch-master | prepare_data.m | .m | deepsketch-master/prepare_data.m | 2,936 | utf_8 | 0bf70da631bc7f8f6481605e12dc3c1d | function db_info = prepare_data(img_db, img_size, save_dir, resize_function, para)
augmentation_range = [-4:4];
if ~isdir(save_dir)
mkdir(save_dir);
end
parfor aug = augmentation_range
augdir = fullfile(save_dir, num2str(aug));
augdir_flip = fullfile(save_dir, [num2str(aug),'_flip']);
if ~isdi... |
github | obiwan87/compressive-shape-from-focus-master | showresult.m | .m | compressive-shape-from-focus-master/sff/showresult.m | 991 | utf_8 | b0a5cca76eb1b7911bc71626383db7ec | function showresult( z, cz, gz)
hFig = figure;
set(hFig, 'Position', [100 100 800 300])
subplot(1,3,1), surf(z), shading flat, colormap jet
set(gca, 'zdir', 'reverse', 'xtick', [], 'ytick', [])
%set(gca, 'xtick', [], 'ytick', [])
axis tight, grid off, box on
zlabel('pixel depth (mm)')
zlim([min(gz(:)) max(gz(:))])
t... |
github | obiwan87/compressive-shape-from-focus-master | focusmeasure.m | .m | compressive-shape-from-focus-master/sff/focusmeasure.m | 18,375 | utf_8 | 1fbffeb2f3f96cc3b19adfee372fbe40 | function FM = focusmeasure(Image, Measure, WSize)
%This function measures the relative degree of focus of
%an image. It may be invoked as:
%
% FM = focusmeasure(Image, Method, WSize)
%
%Where
% Image, is a DOUBLE Image and FM is a
% matrix the same size as Image with the
% computed focus m... |
github | obiwan87/compressive-shape-from-focus-master | blk_amp_spec_slope_eo_toy.m | .m | compressive-shape-from-focus-master/s3/blk_amp_spec_slope_eo_toy.m | 484 | utf_8 | 16466f33449d41d06fe1924da9ec040e |
function [res] = blk_amp_spec_slope_eo_toy(blk)
persistent N;
persistent wnd;
if (nargin == 0)
N = [];
wnd = [];
return;
end
if (nargin == 2 || isempty(N))
N = size(blk, 1);
wnd = hanning(N);
wnd = wnd * wnd';
end
if (~isa(blk, 'double'))
blk = double(blk);
end
blk_wnd_prod = blk .* wnd;
% blk_wnd_pr... |
github | obiwan87/compressive-shape-from-focus-master | disp_progress.m | .m | compressive-shape-from-focus-master/s3/disp_progress.m | 1,007 | utf_8 | a6489e6f67c1122df69d9dcbb7197946 |
function disp_progress(p, p_max)
persistent p_last;
if (nargin == 0)
p_last = [];
fprintf(1, '%s\n', '');
return;
end
p_done = p / p_max * 100;
p_done = round(p_done / 10) * 10;
%[p_done p_last]
if (p_done == p_last)
return;
end
if (~isempty(p_last))
% fprintf(1, '%d\n', p_last);
fprintf(1, '%s\b\b\b... |
github | obiwan87/compressive-shape-from-focus-master | s3_map.m | .m | compressive-shape-from-focus-master/s3/s3_map.m | 5,304 | utf_8 | b282d160cc91cd4e2767424d08fa0e87 | function [s_map1, s_map2, s3] = s3_map(img, show_res)
% Input: img is a gray scale image, in double type, range from 0 - 255.
% You have to convert to gray scale if your image
% is color. You also have to cast img to double in order to run this code
% Parameter show_res = 1 to show results
% Output:
% s_map1: The s... |
github | obiwan87/compressive-shape-from-focus-master | fmeasure.m | .m | compressive-shape-from-focus-master/fmeasure/fmeasure.m | 9,062 | utf_8 | ddd88bb978206f149aff0960807c38e2 | function FM = fmeasure(Image, Measure, ROI)
%This function measures the relative degree of focus of
%an image. It may be invoked as:
%
% FM = fmeasure(IMAGE, METHOD, ROI)
%
%Where
% IMAGE, is a grayscale image and FM is the computed
% focus value.
% METHOD, is the focus measure algorithm as a string... |
github | obiwan87/compressive-shape-from-focus-master | fstack.m | .m | compressive-shape-from-focus-master/fstack/fstack.m | 5,614 | utf_8 | 8ed1d308c319c76b3f8581b162c2031c | function im = fstack(imlist, varargin)
% Focus stacking.
%
% SINTAX:
% im = fstack(imlist)
% im = fstack(imlist, opt1, val1, opt2, val2,...)
%
% DESCRIPTION:
% Generate extended depth-of-field image from focus sequence
% using noise-robust selective all-in-focus algorithm [1].
% Input images may be grayscale or co... |
github | obiwan87/compressive-shape-from-focus-master | simblur.m | .m | compressive-shape-from-focus-master/defocus/simblur.m | 5,612 | utf_8 | 2a7995e34eea5f6d521e1fc778622144 | function imdata = simblur(texmap, focus, impath, varargin)
%Defocus simulation.
% SINTAX:
% IMDATA = simblur(texmap, focus, impath);
% IMDATA = simblur(texmap, focus, impath, opt1, val1,...);
%
% DESCRIPTION:
% This function simulates defocus in order to generate
% a focus sequence. It works by mapping a texture (t... |
github | JiaoXianjun/home_nat_script-master | get_ip.m | .m | home_nat_script-master/get_ip.m | 554 | utf_8 | cda045ac17f02b437ea53546bf33f2c6 |
function ip = get_ip(iface_str)
[status, text] = system(['ifconfig ' iface_str]);
if status ~= 0 % exe failed!
disp('get_ip system failed.');
ip = -1;
return;
end
%disp('get_ip ifconfig succeedded.');
ip_str_start = strfind(text, 'inet addr:');
if isempty(ip_str_start)
disp('get_ip can not find ip.');... |
github | tommy-qichang/yolo.torch-master | main_Yolo.m | .m | yolo.torch-master/matlab/main_Yolo.m | 5,062 | utf_8 | 698beff36d873d558669ae66f0f187e2 | function main_Yolo()
clear ; close all; clc
baseUrl = 'http://128.6.5.14:3300/data/tags/';
pptlist = importdata('newlist.data','\n');
pptlist_test = importdata('newlist_test.data','\n');
% imgWidth = 512;
% imgHeight = 549;
resizeW = 448;
resizeH = 448;
savePrefix = '0712';
trDataPath = strcat('results/img_' , save... |
github | tommy-qichang/yolo.torch-master | main_Yolo_augment.m | .m | yolo.torch-master/matlab/main_Yolo_augment.m | 5,672 | utf_8 | 884087d299cdd3e758331f351d9f6d18 | function main_Yolo_augment()
clear ; close all; clc
baseUrl = 'http://128.6.5.14:3300/data/tags/';
pptlist = importdata('newlist.data','\n');
pptlist_test = importdata('newlist_test.data','\n');
% imgWidth = 512;
% imgHeight = 549;
resizeW = 448;
resizeH = 448;
celNum = 1;
savePrefix = '0721_1x1';
trDataPath = strc... |
github | ZhengyaoJiang/OLPS-master | experimenter.m | .m | OLPS-master/GUI/experimenter.m | 28,158 | utf_8 | 5f7fae289be1c6c2ee3f21027438e422 | function varargout = experimenter(varargin)
% EXPERIMENTER M-file for experimenter.fig
% EXPERIMENTER, by itself, creates a new EXPERIMENTER or raises the existing
% singleton*.
%
% H = EXPERIMENTER returns the handle to a new EXPERIMENTER or the handle to
% the existing singleton*.
%
% EXPERIM... |
github | ZhengyaoJiang/OLPS-master | resultManager2.m | .m | OLPS-master/GUI/resultManager2.m | 23,887 | utf_8 | 275fe70830186fe0fd52f560f4eb2d5d | function varargout = resultManager2(varargin)
% RESULTMANAGER2 MATLAB code for resultManager2.fig
% RESULTMANAGER2, by itself, creates a new RESULTMANAGER2 or raises the existing
% singleton*.
%
% H = RESULTMANAGER2 returns the handle to a new RESULTMANAGER2 or the handle to
% the existing singleton... |
github | ZhengyaoJiang/OLPS-master | aboutOLPS.m | .m | OLPS-master/GUI/aboutOLPS.m | 8,477 | utf_8 | bd54399631ab7e14151e0ef76d6f18a1 | function varargout = aboutOLPS(varargin)
% ABOUTOLPS MATLAB code for aboutOLPS.fig
% ABOUTOLPS, by itself, creates a new ABOUTOLPS or raises the existing
% singleton*.
%
% H = ABOUTOLPS returns the handle to a new ABOUTOLPS or the handle to
% the existing singleton*.
%
% ABOUTOLPS('CALLBACK',hO... |
github | ZhengyaoJiang/OLPS-master | tradingManager.m | .m | OLPS-master/GUI/tradingManager.m | 28,138 | utf_8 | d3fab273fe3e7dde18a714b22d719473 | function varargout = tradingManager(varargin)
% TRADINGMANAGER M-file for tradingManager.fig
% TRADINGMANAGER, by itself, creates a new TRADINGMANAGER or raises the existing
% singleton*.
%
% H = TRADINGMANAGER returns the handle to a new TRADINGMANAGER or the handle to
% the existing singleton*.
%
... |
github | ZhengyaoJiang/OLPS-master | resultManager.m | .m | OLPS-master/GUI/resultManager.m | 26,019 | utf_8 | 2d0ce5cde0693eda6012bed14328ebc2 | function varargout = resultManager(varargin)
% RESULTMANAGER MATLAB code for resultManager.fig
% RESULTMANAGER, by itself, creates a new RESULTMANAGER or raises the existing
% singleton*.
%
% H = RESULTMANAGER returns the handle to a new RESULTMANAGER or the handle to
% the existing singleton*.
%
% ... |
github | ZhengyaoJiang/OLPS-master | animation.m | .m | OLPS-master/GUI/animation.m | 4,567 | utf_8 | 2bde81bb136d3614ff76e26003036143 | function varargout = animation(varargin)
% ANIMATION M-file for animation.fig
% ANIMATION, by itself, creates a new ANIMATION or raises the existing
% singleton*.
%
% H = ANIMATION returns the handle to a new ANIMATION or the handle to
% the existing singleton*.
%
% ANIMATION('CALLBACK',hObject... |
github | ZhengyaoJiang/OLPS-master | configManager.m | .m | OLPS-master/GUI/configManager.m | 32,556 | utf_8 | 18866e6ce5419e734d816016a088a6bc | function varargout = configManager(varargin)
% CONFIGMANAGER MATLAB code for configManager.fig
% CONFIGMANAGER, by itself, creates a new CONFIGMANAGER or raises the existing
% singleton*.
%
% H = CONFIGMANAGER returns the handle to a new CONFIGMANAGER or the handle to
% the existing singleton*.
%
% ... |
github | ZhengyaoJiang/OLPS-master | errorMessage.m | .m | OLPS-master/GUI/errorMessage.m | 3,166 | utf_8 | 1778f58df8e4451eff3c162a15200530 | function varargout = errorMessage(varargin)
% ERRORMESSAGE M-file for errorMessage.fig
% ERRORMESSAGE, by itself, creates a new ERRORMESSAGE or raises the existing
% singleton*.
%
% H = ERRORMESSAGE returns the handle to a new ERRORMESSAGE or the handle to
% the existing singleton*.
%
% ERRORME... |
github | ZhengyaoJiang/OLPS-master | start.m | .m | OLPS-master/GUI/start.m | 4,644 | utf_8 | b45bc81ce4ac39734893b445551b0213 | function varargout = start(varargin)
% START MATLAB code for start.fig
% START, by itself, creates a new START or raises the existing
% singleton*.
%
% H = START returns the handle to a new START or the handle to
% the existing singleton*.
%
% START('CALLBACK',hObject,eventData,handles,...) cal... |
github | ZhengyaoJiang/OLPS-master | deletedMessage.m | .m | OLPS-master/GUI/deletedMessage.m | 3,303 | utf_8 | 3e4ea00255218ab063b187a517dcd2cf | function varargout = deletedMessage(varargin)
% DELETEDMESSAGE M-file for deletedMessage.fig
% DELETEDMESSAGE, by itself, creates a new DELETEDMESSAGE or raises the existing
% singleton*.
%
% H = DELETEDMESSAGE returns the handle to a new DELETEDMESSAGE or the handle to
% the existing singleton*.
%
... |
github | ZhengyaoJiang/OLPS-master | addStrategy.m | .m | OLPS-master/GUI/config/addStrategy.m | 1,894 | utf_8 | 41e7db27f7441ecd509f77de9c5add78 | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% This file is part of OLPS: http://OLPS.stevenhoi.org/
% Original authors: Doyen Sahoo
% Contributors: Bin LI, Steven C.H. Hoi
% Change log:
%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function [ ] = addStra... |
github | ZhengyaoJiang/OLPS-master | addData.m | .m | OLPS-master/GUI/config/addData.m | 781 | utf_8 | 9ce08932a5d0c66b1d5a8804a19cba8b | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% This file is part of OLPS: http://OLPS.stevenhoi.org/
% Original authors: Doyen Sahoo
% Contributors: Bin LI, Steven C.H. Hoi
% Change log:
%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function [ ] = addData... |
github | ZhengyaoJiang/OLPS-master | removeData.m | .m | OLPS-master/GUI/config/removeData.m | 786 | utf_8 | fc83bd2f2ef9af9ea19a2a3fb9d4b9bb | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% This file is part of OLPS: http://OLPS.stevenhoi.org/
% Original authors: Doyen Sahoo
% Contributors: Bin LI, Steven C.H. Hoi
% Change log:
%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function [ ] = remove... |
github | ZhengyaoJiang/OLPS-master | removeStrategy.m | .m | OLPS-master/GUI/config/removeStrategy.m | 877 | utf_8 | ed9bed15243286a2b7abcbc584bdcc0f | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% This file is part of OLPS: http://OLPS.stevenhoi.org/
% Original authors: Doyen Sahoo
% Contributors: Bin LI, Steven C.H. Hoi
% Change log:
%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function [ ] = remove... |
github | ZhengyaoJiang/OLPS-master | grw_lambda.m | .m | OLPS-master/Strategy/grw_lambda.m | 664 | utf_8 | f60d370c4ccb3c95ff789665c6a2fe6b | function [xi_norm] = grw_lambda(xi)
% This program normalizes a random xi
%
% function [xi_norm] = grw_lambda(xi)
%
% xi_norm: normalized xi
%
% xi; randomly generated xi
%
% Example: [xi_norm] = grw_lambda(xi)
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% This file is part of OLPS: htt... |
github | ZhengyaoJiang/OLPS-master | grw_expert.m | .m | OLPS-master/Strategy/grw_expert.m | 774 | utf_8 | 0c48686673965df6fd2792badce8d045 | function [weight] = grw_expert(data, xi)
% This program generates portfolio for a specified parameter setting.
% GRW expert
%
% function [weight] = eg_expert(data, weight_o, eta)
%
% weight: experts portfolio, used for next rebalance/combination
%
% data: market sequence vectors
% xi: randomly generated variable
%
% E... |
github | ZhengyaoJiang/OLPS-master | resultManager2.m | .m | OLPS-master/PGUI/resultManager2.m | 12,034 | utf_8 | 88288c3dca540988e464bf8a19a1eb1a | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% This file is part of OLPS: http://OLPS.stevenhoi.org/
% Original authors: Doyen Sahoo
% Contributors: Bin LI, Steven C.H. Hoi
% Change log:
%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function [] = resultMa... |
github | ZhengyaoJiang/OLPS-master | experimenterMenu.m | .m | OLPS-master/PGUI/experimenterMenu.m | 8,072 | utf_8 | 2f7c1f1305865117fab1f8b74f03c4d5 | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% This file is part of OLPS: http://OLPS.stevenhoi.org/
% Original authors: Doyen Sahoo
% Contributors: Bin LI, Steven C.H. Hoi
% Change log:
%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function [ ] = experim... |
github | ZhengyaoJiang/OLPS-master | homeMenu.m | .m | OLPS-master/PGUI/homeMenu.m | 2,015 | utf_8 | 388d46076a5fab011ed7550893bf3cfa | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% This file is part of OLPS: http://OLPS.stevenhoi.org/
% Original authors: Doyen Sahoo
% Contributors: Bin LI, Steven C.H. Hoi
% Change log:
%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function [ ] = homeMen... |
github | ZhengyaoJiang/OLPS-master | displayMenu.m | .m | OLPS-master/PGUI/displayMenu.m | 5,314 | utf_8 | 364f7899114afebf66bee3c111dc4b15 | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% This file is part of OLPS: http://OLPS.stevenhoi.org/
% Original authors: Doyen Sahoo
% Contributors: Bin LI, Steven C.H. Hoi
% Change log:
%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function [ ] = display... |
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