-- Sync with v1.1.1 Utils library: add some diagnostic data simulation scripts...

1.1.0

1.1.1

function generateSimData(dirname, format)

if ~exist('dirname','var')

    dirname = pwd;

end

if ~exist('format','var')

    format = '.snirf';

end

dirname = filesepStandard(dirname);

files = DataFilesClass(dirname, format, 'standalone').files;

for ii = 1:length(files)

    if ~isempty(findstr(files(ii).name, '_sim'))

        continue;

    end

    obj = generateSimDataOneFile([files(ii).rootdir, files(ii).name]);

    [p,f,e] = fileparts([files(ii).rootdir, files(ii).name]);

    fname = [filesepStandard(p),f,'_sim',e];

    fprintf('Saving simulated data in %s\n', fname);

    obj.Save(fname);

end

% ---------------------------------------------------------------

function obj = generateSimDataOneFile(obj)

d = [];

if ischar(obj)

    obj = SnirfClass(obj);

    d = obj.data;

elseif isa(obj, 'SnirfClass')

    d = obj.data;

elseif isa(obj, 'DataClass')

    d = obj;

    obj = SnirfClass(d);

end

ml = d.GetMeasurementList('matrix');

for iBlk = length(d)

    nTpts = size(d(iBlk).dataTimeSeries,1);

    for iM = 1:length(d(iBlk).measurementList)

        data = ml(iM,:);

        stepsize = floor(nTpts / length(data));

        for iDt = 1:length(data)

            y = data(iDt);

            iTptS = (iDt-1) * stepsize + 1;

            iTptE = iTptS + stepsize - 1;            

            if nTpts-iTptE < stepsize

                iTptE = nTpts;

            end

            d(iBlk).dataTimeSeries(iTptS:iTptE, iM) = y;

        end

    end

end

obj.data = d;

function [t, y] = simulateDataTimeSeries(N, alpha, sigma)

if ~exist('N','var')

    N = 1e3; 

end

if ~exist('alpha','var')

    alpha = 1;

end

if ~exist('sigma','var')

    sigma = .4; 

end

% generate time

nTpts = N;

sampleRate = 10;

timeTotal = 1/sampleRate * nTpts;

t = 0:1/sampleRate:timeTotal;

t(N+1:end) = [];

% Generate data

y = zeros(N, 1); 

y(1) = randn; % Initialize

fprintf('Rand = %0.4f\n', y(1));

for k = 2:N

    y(k) = alpha*y(k-1) + randn*sigma;

end

function snirf = simulateProbeData(probefile, ntpts)

snirf = SnirfClass.empty();

if ~exist('probefile','var')

    return;

end

if ~exist('ntpts','var')

    ntpts = 1e3;

end

if ~ispathvalid(probefile)

    return;

end

nirs = NirsClass(probefile);

for iM = 1:length(nirs.SD.MeasList)

    [nirs.t, nirs.d(:,iM)] = simulateDataTimeSeries(ntpts);

end

snirf = SnirfClass(nirs.d, nirs.t, nirs.SD, [], []);

[p,f] = fileparts(probefile);

snirf.Save(['./',f,'.snirf']);