diff --git a/text/TODO.txt b/text/TODO.txt
index 451e512..6160808 100644
--- a/text/TODO.txt
+++ b/text/TODO.txt
@@ -63,19 +63,20 @@
 
 Unterschied pburg / pwelch
 
-
-Calculations todo:
+Calculations done:
 - offset (0,1,2)
 - pause (0,1)
-- Pos
+- Pos (offset 0-2)
+
+Calculations todo:
 - c
 - ridge
 - maxFreq 
 - maxPerclass?
 - noLFsample höher, Frequenzen testen?
 
-Aus EEG EMG vorhersagen (WL) (regression, dann corr)
-Aus Synergien kin
-Aus EEG (über Synergien) kinematik
+Aus EEG EMG vorhersagen (WL) (regression, dann corr) (running)
+Aus Synergien kin (running)
+Aus EEG (über Synergien) kinematik (testing)
 
 Intro nur Motivation, Rest in II
diff --git a/usedMcode/callAll.m b/usedMcode/callAll.m
index 366eb56..704cb24 100644
--- a/usedMcode/callAll.m
+++ b/usedMcode/callAll.m
@@ -6,7 +6,7 @@
 EMGChannels={'AbdPolLo','Biceps','Triceps','FrontDelt','MidDelt','BackDelt'};
 noSynergies=3;
 
-allSubjects=true; %run all subjects and days or only one random day for one random subject
+allSubjects=false; %run all subjects and days or only one random day for one random subject
 name='EEGtoEMG'; %suffix for the output, has to be valid name for file (no space, /, ...)
 windowEMG=0.2;
 windowEEG=1;
@@ -22,7 +22,7 @@
 k=10;
 maxExpC=0;
 maxPerClass=250;
-poolObj=parpool(32);
+poolObj=parpool(4);
 
 [subjects,numbers]=namesAndNumbers(pathToFile);
 numbersMat=cell2mat(numbers);
@@ -75,8 +75,11 @@
 %     correlationLFnnmf=zeros([j,noSynergies]);
     maxRidgeParamIndexEEGemg=zeros([j,noSynergies,k]);
     correlationEMGemg=zeros([j,noSynergies]);
-    maxRidgeParamIndexAutoecKin=zeros([j,noSynergies,k]);
-    correlationAutoecKin=zeros([j,noSynergies]);
+    maxRidgeParamIndexAutoencKin=zeros([j,noSynergies,k]);
+    correlationAutoencKin=zeros([j,noSynergies]);
+    correlationViaAutoenc=zeros(j);
+    correlationViaPCA=zeros(j);
+    correlationViaNNMF=zeros(j);
     
     parfor j=1:size(numbersMat,2)
         number=numbersMat(j);
@@ -99,6 +102,10 @@
 %         [correlationLFnnmf(j,:),maxRidgeParamIndexLFnnmf(j,:,:)]=ridgeCV(savePath,'LF','NNMF',k,ridgeParams,eegOffset);
         [correlationEEGemg(j,:),maxRidgeParamIndexEEGemg(j,:,:)]=ridgeCV(savePath,'EEG','EMG',k,ridgeParams,eegOffset);
         [correlationAutoencKin(j,:),maxRidgeParamIndexAutoencKin(j,:,:)]=ridgeCV(savePath,'Autoenc','kin',k,ridgeParams,eegOffset);
+        correlationViaAutoenc(j)=ridgeCVvia(savePath,'EEG','Autoenc','kin',k,ridgeParams,eegOffset);
+        correlationViaPCA(j)=ridgeCVvia(savePath,'EEG','PCA','kin',k,ridgeParams,eegOffset);
+        correlationViaNNMF(j)=ridgeCVvia(savePath,'EEG','NNMF','kin',k,ridgeParams,eegOffset);
+        
         fprintf('%s%i finished %s\n',subject,number,datestr(datetime('now')))
     end
     
@@ -124,8 +131,11 @@
 %     [correlationEMGnnmf,maxRidgeParamIndexEMGnnmf(:,:)]=ridgeCV(savePath,'EMG','NNMF',k,ridgeParams,eegOffset);
 %     [correlationEEGnnmf,maxRidgeParamIndexEEGnnmf(:,:)]=ridgeCV(savePath,'EEG','NNMF',k,ridgeParams,eegOffset);
 %     [correlationLFnnmf,maxRidgeParamIndexLFnnmf(:,:)]=ridgeCV(savePath,'LF','NNMF',k,ridgeParams,eegOffset);
-    [correlationEEGemg,maxRidgeParamIndexEEGemg(:,:)]=ridgeCV(savePath,'EEG','EMG',k,ridgeParams,eegOffset);
-    [correlationAutoencKin,maxRidgeParamIndexAutoencKin(:,:)]=ridgeCV(savePath,'Autoenc','kin',k,ridgeParams,eegOffset);
+%     [correlationEEGemg,maxRidgeParamIndexEEGemg(:,:)]=ridgeCV(savePath,'EEG','EMG',k,ridgeParams,eegOffset);
+%     [correlationAutoencKin,maxRidgeParamIndexAutoencKin(:,:)]=ridgeCV(savePath,'Autoenc','kin',k,ridgeParams,eegOffset);
+    correlationViaAutoenc=ridgeCVvia(savePath,'EEG','Autoenc','kin',k,[100],eegOffset);
+    correlationViaPCA=ridgeCVvia(savePath,'EEG','PCA','kin',k,[100],eegOffset);
+    correlationViaNNMF=ridgeCVvia(savePath,'EEG','NNMF','kin',k,[100],eegOffset);
     fprintf('%s%i finished %s\n',subject,number,datestr(datetime('now')))
     
     save(strcat(pathToFile,sprintf('../matlabData/%s_call%s%i-%s.mat',datestr(datetime('now')),subject,number,name)));
diff --git a/usedMcode/ridgeCVvia.m b/usedMcode/ridgeCVvia.m
new file mode 100644
index 0000000..25e5d7d
--- /dev/null
+++ b/usedMcode/ridgeCVvia.m
@@ -0,0 +1,70 @@
+function [correlation]=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
+
+    viaDataPredicted=zeros(size(viaData));
+    correlation=zeros(size(predicted,2));
+
+    parfor j=1:size(viaData,2)
+        pred=viaData(:,j);
+        
+        coeffs=ridge(pred,trainingData,ridgeParams(1),0);
+        
+        viaDataPredicted(:,j)=coeffs(1)+trainingData*coeffs(2:end);
+
+    end
+    
+    parfor j=1:size(predicted,2)
+        pred=predicted(:,j);
+        
+        coeffs=ridge(pred,viaDataPredicted,ridgeParams(1),0);
+        
+        correlation(j)=ridgeCorrelation(viaDataPredicted,pred,coeffs);
+
+    end
+end
\ No newline at end of file