diff --git a/usedMcode/callAll.m b/usedMcode/callAll.m
index 76a725d..d25121e 100644
--- a/usedMcode/callAll.m
+++ b/usedMcode/callAll.m
@@ -44,11 +44,11 @@
 parfor j=1:size(numbersMat,2)
     number=numbersMat(j);
     subject=subjectsForNumbers{j};
-    readEEG(pathToFile,subject,number,windowEMG,windowEEG,shift,maxFile,threshold,pburgOrder,minEEGFreq,maxEEGFreq,pause);
-    [meanAccurancysEMG(j),maxCEMG(j,:),cmScaledEMG(j,:,:)]=svmEciton(pathToFile,subject,number,~EEG,k,maxExpC,maxPerClass,windowEMG,windowEEG,shift,minEEGFreq,maxEEGFreq,pause,pburgOrder);
-    [meanAccurancysEEG(j),maxCEEG(j,:),cmScaledEEG(j,:,:)]=svmEciton(pathToFile,subject,number,EEG,k,maxExpC,maxPerClass,windowEMG,windowEEG,shift,minEEGFreq,maxEEGFreq,pause,pburgOrder);
-    [correlationEMG(j,:)]=ridgeCV(pathToFile,subject,number,false,k,ridgeParams,windowEMG,windowEEG,shift,minEEGFreq,maxEEGFreq,pause,pburgOrder);
-    [correlationEEG(j,:)]=ridgeCV(pathToFile,subject,number,EEG,k,ridgeParams,windowEMG,windowEEG,shift,minEEGFreq,maxEEGFreq,pause,pburgOrder);
+    savePath=readEEG(pathToFile,subject,number,windowEMG,windowEEG,shift,maxFile,threshold,pburgOrder,minEEGFreq,maxEEGFreq,pause);
+    [meanAccurancysEMG(j),maxCEMG(j,:),cmScaledEMG(j,:,:)]=svmEciton(savePath,~EEG,k,maxExpC,maxPerClass);
+    [meanAccurancysEEG(j),maxCEEG(j,:),cmScaledEEG(j,:,:)]=svmEciton(savePath,EEG,k,maxExpC,maxPerClass);
+    [correlationEMG(j,:)]=ridgeCV(savePath,false,k,ridgeParams);
+    [correlationEEG(j,:)]=ridgeCV(savePath,EEG,k,ridgeParams);
     fprintf('%s%i finished %s\n',subject,number,datestr(datetime('now')))
 end
 
diff --git a/usedMcode/readEEG.m b/usedMcode/readEEG.m
index a60b41f..ca13e5a 100644
--- a/usedMcode/readEEG.m
+++ b/usedMcode/readEEG.m
@@ -1,10 +1,11 @@
-function readEEG(pathToFile, subject,number,windowEMG,windowEEG,shift,maxFile,threshold,pburgOrder,minEEGFreq,maxEEGFreq,pause)
+function [savePath]=readEEG(pathToFile, subject,number,windowEMG,windowEEG,shift,maxFile,threshold,pburgOrder,minEEGFreq,maxEEGFreq,pause)
 
     %fprintf('start read %s%i %s\n',subject,number,datestr(datetime('now')));
+    savePath=strcat(pathToFile,sprintf('../matlabData/%s%i%imsWindowEMG%isWindowEEG%imsShiftFreq%ito%iPause%ipBurg%i.mat',subject,number,windowEMG*1000,windowEEG,shift*1000,minEEGFreq,maxEEGFreq,pause,pburgOrder));
     
     %only create file if it doesn't exist yet
-    if exist(strcat(pathToFile,sprintf('../matlabData/%s%i%imsWindowEMG%isWindowEEG%imsShift1sPauseFreq%ito%iPause%i.mat',subject,number,windowEMG*1000,windowEEG,shift*1000,minEEGFreq,maxEEGFreq,pause)), 'file') ~= 2
-        fprintf(strcat(pathToFile,sprintf('../matlabData/%s%i%imsWindowEMG%isWindowEEG%imsShift1sPauseFreq%ito%iPause%i.mat',subject,number,windowEMG*1000,windowEEG,shift*1000,minEEGFreq,maxEEGFreq,pause)),' not existanat; creating\n');
+    if exist(savePath, 'file') ~= 2
+        fprintf(strcat(savePath,' not existing; creating\n'));
         trainingDataEEGcell=cell(maxFile,1);
         trainingDataEMGcell=cell(maxFile,1);
         classesCell=cell(maxFile,1);
@@ -43,7 +44,7 @@
         kinematics=kinMat(smoothClassification~=-1,:);
 
         clear smoothClassification i
-        save(strcat(pathToFile,sprintf('../matlabData/%s%i%imsWindowEMG%isWindowEEG%imsShiftFreq%ito%iPause%ipBurg%i.mat',subject,number,windowEMG*1000,windowEEG,shift*1000,minEEGFreq,maxEEGFreq,pause,pburgOrder)),'trainingDataEEG','trainingDataEMG','classification','kinematics','-v7.3');
+        save(savePath,'trainingDataEEG','trainingDataEMG','classification','kinematics','-v7.3');
 
 
         %fprintf('finished reading %s%i %s\n',subject,number,datestr(datetime('now')));
diff --git a/usedMcode/ridgeCV.m b/usedMcode/ridgeCV.m
index fa5f021..bb686a3 100644
--- a/usedMcode/ridgeCV.m
+++ b/usedMcode/ridgeCV.m
@@ -1,5 +1,5 @@
-function [correlation]=ridgeCV(pathToFile,subject,number,EEG,k,ridgeParams,windowEMG,windowEEG,shift,minEEGFreq,maxEEGFreq,pause,pBurgOrder)
-    load(strcat(pathToFile,sprintf('../matlabData/%s%i%imsWindowEMG%isWindowEEG%imsShiftFreq%ito%iPause%i.mat',subject,number,windowEMG*1000,windowEEG,shift*1000,minEEGFreq,maxEEGFreq,pause,pBurgOrder)));
+function [correlation]=ridgeCV(savePath,EEG,k,ridgeParams)
+    load(savePath);
     clear classification;
     if EEG
         trainingData=trainingDataEEG;
diff --git a/usedMcode/svmEciton.m b/usedMcode/svmEciton.m
index 268f704..0295064 100644
--- a/usedMcode/svmEciton.m
+++ b/usedMcode/svmEciton.m
@@ -1,6 +1,6 @@
-function [meanAccurancy,maxC, cmScaled]= svmEciton(pathToFile,subject,number,EEG,k,maxExpC,maxPerClass,windowEMG,windowEEG,shift,minEEGFreq,maxEEGFreq,pause,pBurgOrder)
-    load(strcat(pathToFile,sprintf('../matlabData/%s%i%imsWindowEMG%isWindowEEG%imsShiftFreq%ito%iPause%ipBurg%i.mat',subject,number,windowEMG*1000,windowEEG,shift*1000,minEEGFreq,maxEEGFreq,pause,pBurgOrder)));
-%    fprintf('%i,%i,%i',size(trainingDataEMG,1),size(trainingDataEEG,1),size(classification,1))
+function [meanAccurancy,maxC, cmScaled]= svmEciton(savePath,EEG,k,maxExpC,maxPerClass)
+    load(savePath)
+    %    fprintf('%i,%i,%i',size(trainingDataEMG,1),size(trainingDataEEG,1),size(classification,1))
     addpath('/nfs/wsi/ti/messor/hohlochj/libsvm/matlab');
 
     %choose to estimate based on EEG or EMG