function [correlation,viaCorrelation]=ridgeCVvia(savePath,data,via,goal,k,ridgeParams,eegOffset)
load(savePath);
clear classification;
eeg=false;
if strcmp(data,'EEG')
eeg=true;
trainingData=trainingDataEEG(eegOffset+1:end,:);
elseif strcmp(data,'EMG')
trainingData=trainingDataEMG;
elseif strcmp(data,'LF')
eeg=true;
trainingData=trainingDataEEGlf(eegOffset+1:end,:);
else
error('only EEG, EMG and LF are valid inputs for data');
end
factor=size(trainingDataEMG,1)/(size(trainingData,1)+eegOffset);
if strcmp(via,'Autoenc')
viaData=shiftingMean(synergiesAutoenc,factor);
elseif strcmp(via,'PCA')
viaData=shiftingMean(synergiesPCA,factor);
elseif strcmp(via,'NNMF')
viaData=shiftingMean(synergiesNNMF,factor);
else
error('only Autoenc, PCA nad NNMF are valid inputs for via');
end
if strcmp(goal,'kin')
predicted=shiftingMean(kinematics,factor);
elseif strcmp(goal,'EMG')
predicted=trainingDataEMG;
else
error('only kin and EMG are valid inputs for goal');
end
clear trainingDataEEG;
clear trainingDataEEGlf;
clear trainingDataEMG;
clear kinematics;
clear synergies*;
if eeg
viaData=viaData(1:end-eegOffset,:);
predicted=predicted(1:end-eegOffset,:);
end
viaCorr=zeros([k,size(viaData,2)]);
finalCorr=zeros([k,size(predicted,2)]);
randMap=randperm(size(trainingData,1));
for i=1:k
leaveData=trainingData(mod(randMap,k)==i-1,:);
leaveVia=viaData(mod(randMap,k)==i-1,:);
leavePred=predicted(mod(randMap,k)==i-1,:);
remainingData=trainingData(mod(randMap,k)~=i-1,:);
remainingVia=viaData(mod(randMap,k)~=i-1,:);
remainingPred=predicted(mod(randMap,k)~=i-1,:);
coeffs=zeros(size(viaData));
for j=1:size(viaData,2)
coeffs(:,j)=ridge(remainingVia(:,j),remainingData,ridgeParams(1),0);
via=coeffs(1,j)+leaveData*coeffs(2:end,j);
viaCorr(i,j)=corr(leaveVia(:,j),via);
end
[~,maxIndex]=max(mean(viaCorr,2));
viaDataPredicted=coeffs(1,maxIndex)+leaveData*coeffs(2:end,maxIndex);
clear coeffs
viaDataPredictedLeave=viaDataPredicted(mod(randMap,k)==i-1,:);
viaDataPredictedRemaining=viaDataPredicted(mod(randMap,k)~=i-1,:);
for j=1:size(predicted,2)
coeffs=ridge(remainingPred(:,j),viaDataPredictedRemaining,ridgeParams(1),0);
finalCorr(i,j)=ridgeCorrelation(viaDataPredictedLeave,leavePred,coeffs);
end
end
viaCorrelation=mean(viaCorr,1);
correlation=mean(finalCorr,1);
end