diff --git a/usedMcode/callAll.m b/usedMcode/callAll.m
index cc1ae66..76a725d 100644
--- a/usedMcode/callAll.m
+++ b/usedMcode/callAll.m
@@ -45,10 +45,11 @@
     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);
-    [meanAccurancysEEG(j),maxCEEG(j,:),cmScaledEEG(j,:,:)]=svmEciton(pathToFile,subject,number,EEG,k,maxExpC,maxPerClass,windowEMG,windowEEG,shift,minEEGFreq,maxEEGFreq,pause);
-    [correlationEMG(j,:)]=ridgeCV(pathToFile,subject,number,false,k,ridgeParams,windowEMG,windowEEG,shift,minEEGFreq,maxEEGFreq,pause);
-    [correlationEEG(j,:)]=ridgeCV(pathToFile,subject,number,EEG,k,ridgeParams,windowEMG,windowEEG,shift,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);
+    fprintf('%s%i finished %s\n',subject,number,datestr(datetime('now')))
 end
 
 save(strcat(pathToFile,sprintf('../matlabData/%s_callAll.mat',datestr(datetime('now')))));
diff --git a/usedMcode/readEEG.m b/usedMcode/readEEG.m
index 8a9b347..a60b41f 100644
--- a/usedMcode/readEEG.m
+++ b/usedMcode/readEEG.m
@@ -43,7 +43,7 @@
         kinematics=kinMat(smoothClassification~=-1,:);
 
         clear smoothClassification i
-        save(strcat(pathToFile,sprintf('../matlabData/%s%i%imsWindowEMG%isWindowEEG%imsShift1sPauseFreq%ito%iPause%i.mat',subject,number,windowEMG*1000,windowEEG,shift*1000,minEEGFreq,maxEEGFreq,pause)),'trainingDataEEG','trainingDataEMG','classification','kinematics','-v7.3');
+        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');
 
 
         %fprintf('finished reading %s%i %s\n',subject,number,datestr(datetime('now')));
diff --git a/usedMcode/ridgeCV.m b/usedMcode/ridgeCV.m
index ee1fc2a..fa5f021 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)
-    load(strcat(pathToFile,sprintf('../matlabData/%s%i%imsWindowEMG%isWindowEEG%imsShift1sPauseFreq%ito%iPause%i.mat',subject,number,windowEMG*1000,windowEEG,shift*1000,minEEGFreq,maxEEGFreq,pause)));
+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)));
     clear classification;
     if EEG
         trainingData=trainingDataEEG;
diff --git a/usedMcode/svmEciton.m b/usedMcode/svmEciton.m
index b575127..268f704 100644
--- a/usedMcode/svmEciton.m
+++ b/usedMcode/svmEciton.m
@@ -1,5 +1,5 @@
-function [meanAccurancy,maxC, cmScaled]= svmEciton(pathToFile,subject,number,EEG,k,maxExpC,maxPerClass,windowEMG,windowEEG,shift,minEEGFreq,maxEEGFreq,pause)
-    load(strcat(pathToFile,sprintf('../matlabData/%s%i%imsWindowEMG%isWindowEEG%imsShift1sPauseFreq%ito%iPause%i.mat',subject,number,windowEMG*1000,windowEEG,shift*1000,minEEGFreq,maxEEGFreq,pause)));
+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))
     addpath('/nfs/wsi/ti/messor/hohlochj/libsvm/matlab');
 
@@ -43,5 +43,4 @@
 %     colorbar();
     %saveas(fig,strcat(pathToFile,sprintf('../plots/%s%i%icm200ms1sPause.fig',subject,number,EEG)),'fig');
     %save(strcat(pathToFile,sprintf('../matlabData/%s%i%i200ms1sPause.mat',subject,number,EEG)),'meanAccurancy','maxC','cmScaled','-v7.3');
-    fprintf('%s%i%i finished %s\n',subject,number,EEG,datestr(datetime('now')))
 end