Update calibration

- Update normalization of window
- Clean up exception logging
- Fix edge case

wavelength_calibration.py

@@ -9,13 +9,13 @@ def remove_peaks( signal , peaks ):
     for peak in peaks:
         first = peak
         peak , old = first - 2 , first - 1
-        while peakless_signal[ peak ] <= peakless_signal[ old ]:
+        while peakless_signal[ peak ] <= peakless_signal[ old ] and peak > 0:
             old   = peak
             peak -= 1
         peakless_signal[ peak : first ] = peakless_signal[ peak ] * np.ones( first - peak )
 
         peak , old = first + 2 , first + 1
-        while peakless_signal[ peak ] <= peakless_signal[ old ]:
+        while peakless_signal[ peak ] <= peakless_signal[ old ] and peak < len( peakless_signal ) - 1:
             old   = peak
             peak += 1
         peakless_signal[ first : peak ] = peakless_signal[ peak ] * np.ones( peak - first )
@@ -61,7 +61,7 @@ def get_extremities( signal , peaks ):
     peaks_inside = np.where(
         argmin_1 < peaks,
     )[0]
-    if len( peaks_inside ) < 1:
+    if len( peaks_inside ) == 0:
         raise Exception( 'unknown plage, cannot autocalibrate' )
     return ( first_peak , peaks_inside[0] )
 
@@ -70,12 +70,10 @@ def only_keep_calib( peaks_data , peaks_calib ):
     only keep data peaks corresponding to calibration
     """
     diff_calib  = ( peaks_calib[ 1 : ] - peaks_calib[ : -1 ] ).astype( float )
-    diff_calib -= np.min( diff_calib )
-    diff_calib /= np.max( diff_calib )
+    diff_calib  /= np.sum( diff_calib )
 
     diff_data  = ( peaks_data[ 1 : ] - peaks_data[ : -1 ] ).astype( float )
-    diff_data -= np.min( diff_data )
-    diff_data /= np.max( diff_data )
+    diff_data /= np.sum( diff_data )
 
     peaks = [ -1 ]
     for i in range( len( diff_calib ) ):
@@ -83,7 +81,6 @@ def only_keep_calib( peaks_data , peaks_calib ):
         for j in range( peaks[ - 1 ] + 1 , len( diff_data ) ):
             sum_ += diff_data[ j ]
             if sum_ - diff_calib[ i ] >  0.002:
-                print( sum_ - diff_calib[ i ] )
                 raise Exception( 'reference peak not found' )
             if sum_ - diff_calib[ i ] > - 0.002:
                 good = j
@@ -94,5 +91,6 @@ def only_keep_calib( peaks_data , peaks_calib ):
     peaks.append( peaks[-1] + 1 ) # append the last peak
 
     return np.array(
-        [ peaks_data[ i ] for i in peaks[ 1 : ] ] # remove the first -1 value
-    ).astype( int )
+        [ peaks_data[ i ] for i in peaks[ 1 : ] ], # remove the first -1 value
+        dtyp = int,
+    )