Fix timpermcluster class method to take baseline that was already included in the initial extractHGDataWithROI.m call

[Aaronearlerichardson]

class method:

IEEG_Pipelines/MATLAB/ieegClassDefinition/ieegStructClass.m

Lines 145 to 175 in b6933ab

	function chanSig = extractTimePermCluster(obj1,obj2)
	% Input
	% obj1 - active IEEG structure
	% obj2 - passive IEEG structure
	% Output
	% chanSig - cluster correction output
	chanSig = {};
	baseData = obj2.data;
	targetData = obj1.data;
	time2pad = size(targetData,3)/size(baseData,3);
	parfor iChan = 1:size(baseData,1)
	% Assumption - target data window is longer than base data
	% Correction - Random sampling & padding base window trials
	% to account for time difference
	baseDataChan = squeeze(baseData(iChan,:,:));
	targetDataChan = squeeze(targetData(iChan,:,:));
	baseDataChanPad = zeros(size(targetDataChan));
	for iTrial = 1:size(baseDataChan,1)
	randTrials = datasample(1:size(baseDataChan,1),time2pad-1,'Replace',false);
	trials2join = baseDataChan(randTrials,:);
	baseDataChanPad(iTrial,:) = [baseDataChan(iTrial,:) trials2join(:)'];
	end
	[zValsRawAct, pValsRaw, actClust]=timePermCluster(targetDataChan,baseDataChanPad,1000,1,1.645);
	chanSig{iChan}.zValsRawAct=zValsRawAct;
	chanSig{iChan}.pValsRaw=pValsRaw;
	chanSig{iChan}.actClust=actClust;
	disp(iChan)
	end
	end % Time Series permutation cluster

while obj1 accepts self as input, the baseline data is not saved in the extractHGDataWithROI.m output. Moreover the obj1 data is already z scored against the baseline, so using this method requires saving both of the original inputs from the extractHGDataWithROI.m call.