/
analyzeVwExp.m
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/
analyzeVwExp.m
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function analyzeVwExp(overwrite, useFdr)
% Analyze data from hindi v-w experiments
if ~exist('overwrite', 'var') || isempty(overwrite), overwrite = 0; end
if ~exist('useFdr', 'var') || isempty(useFdr), useFdr = false; end
analysisDir = '/home/data/bubblesFeat/vw/Xagag/';
resultDir = '/home/data/bubblesResults/vw/Xagag/';
csvDir = '/home/data/bubbles/vw/XagagMixes/';
baseMixDir = '/home/data/bubbles/vw/XagagMixes/';
mixDir = baseMixDir;
% subjects.hindi = {'re', 'vikas2'};
% subjects.vikas2 = {'vikas2'};
% % subjects.vikas = {'vikas'};
subjects.mim = {'mim', 'mim2', 'mim3', 'mim4'};
% subjects.re = {'re'};
verbose = 1;
subNames = fieldnames(subjects);
for s=1:length(subNames)
resultFile = fullfile(resultDir, [subNames{s} '.mat']);
fprintf('%d: %s\n', s, resultFile);
if exist(resultFile, 'file') && (overwrite <= 0)
fprintf('\b <--- Skipping\n');
continue;
end
csvFiles = subjects.(subNames{s});
inCsvFiles = {};
for n=1:length(csvFiles)
inCsvFiles{n} = fullfile(csvDir, [csvFiles{n} '.csv']);
end
processListeningData(inCsvFiles, resultFile, verbose);
end
pattern = 'bps.*.wav';
noiseShape = '/home/data/bubbles/vw/speechRef.wav';
pcaDims = [100 1000]; % 100 dimensions from 1000 files
usePcaDims = 40;
win_s = 0.064;
trimFrames = 15 * 0.016/(win_s/4);
maxFreq_hz = 6000;
% Do bubbles processing on each subject separately
for i = 1:length(subNames)
resultFile = fullfile(resultDir, subNames{i});
load(resultFile);
%listenerCorrect(:,i) = [grouped{:,5}]';
%listenerResponse(:,i) = grouped(:,4);
mainBubbleAnalysis(mixDir, resultFile, analysisDir, pattern, noiseShape, pcaDims, usePcaDims, trimFrames, win_s, overwrite, 0, maxFreq_hz, '', useFdr)
end
%listenerResponse = cellfun(@(x) x{1}, listenerResponse, 'UniformOutput', false);
mainBubbleAnalysis(mixDir, resultFile, analysisDir, pattern, noiseShape, pcaDims, usePcaDims, trimFrames, win_s, overwrite, 0, maxFreq_hz, '', useFdr)