diff --git a/ETA.py b/ETA.py
index 01b7aff..ed4f964 100644
--- a/ETA.py
+++ b/ETA.py
@@ -387,21 +387,38 @@ if calibration != None:
     calib_peaks   = np.loadtxt( calibration )
     mean_calib_up = np.mean( data[
         calibrations[ 'top' ][ 'y' ][ 'min' ] : calibrations[ 'top' ][ 'y' ][ 'max' ],
-        border[ 'x' ][ 'min' ] : border[ 'x' ][ 'max' ]
+        calibrations[ 'top' ][ 'x' ][ 'min' ] : calibrations[ 'top' ][ 'x' ][ 'max' ]
     ] , axis = 0 )
     mean_calib_up -= np.min( mean_calib_up )
     mean_calib_up /= np.max( mean_calib_up )
 
-    peaks_up = find_peaks( mean_calib_up , height = 0.6 )[0] + border[ 'x' ][ 'min' ]
+    peaks_up = find_peaks( mean_calib_up , height = 0.5 )[0] + calibrations[ 'top' ][ 'x' ][ 'min' ]
+    diff     = np.array( [ np.inf ] )
+    polyval = np.polyfit( peaks_up[ : len( calib_peaks ) ] , calib_peaks[ : len( peaks_up ) ] , 1 )
 
-    if len( peaks_up ) != len( calib_peaks ):
-        print( calib_peaks , peaks_up )
-        print( len( calib_peaks ) , len( peaks_up ) )
-        plt.plot( mean_calib_up )
-        plt.show()
-        exit()
-    polyval = np.polyfit( peaks_up , calib_peaks , 1 )
-    print( polyval )
+    while np.max( diff ) > 1000: # we do not have the exact same number of peak (and the same peaks) in calibration model
+        diff            = abs( np.polyval( polyval , peaks_up[ : len( calib_peaks ) ] ) - calib_peaks[ : len( peaks_up ) ] )
+        point_to_delete = np.argmax( diff ) # get the "worst" point
+        peaks_up_new    = np.delete( peaks_up    , [ point_to_delete ] ) # remove from data value ( other peak detected )
+        calib_peaks_new = np.delete( calib_peaks , [ point_to_delete ] ) # remove from model ( peak not detected )
+
+        polyfull_up    = np.polyfit( peaks_up_new[ : len( calib_peaks ) ] , calib_peaks[ : len( peaks_up_new ) ] , 1 , full = True )
+        polyfull_calib = np.polyfit( peaks_up[ : len( calib_peaks_new ) ] , calib_peaks_new[ : len( peaks_up ) ] , 1 , full = True )
+
+        if polyfull_up[ 1 ][ 0 ] < polyfull_calib[ 1 ][ 0 ]: # which one is a better fit ?
+            peaks_up = peaks_up_new
+            polyval  = polyfull_up[ 0 ]
+        else:
+            calib_peaks = calib_peaks_new
+            polyval     = polyfull_calib[ 0 ]
+
+    x = np.arange( calibrations[ 'top' ][ 'x' ][ 'min' ] , calibrations[ 'top' ][ 'x' ][ 'max' ] , 1 )
+    x = np.polyval( polyval , x )
+
+    plt.margins( x = 0 )
+    plt.plot( x , mean_calib_up )
+    plt.show()
+    exit()
 
 # First deformation