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Update calibration

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- Update normalization of window
- Clean up exception logging
- Fix edge case
This commit is contained in:
linarphy 2023-07-27 12:15:11 +02:00
parent 920374b144
commit d97c041ea0
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GPG key ID: 3D4AAAC3AD16E79C
1 changed files with 8 additions and 10 deletions
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18
wavelength_calibration.py
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@ -9,13 +9,13 @@ def remove_peaks( signal , peaks ):
for peak in peaks: for peak in peaks:
first = peak first = peak
peak , old = first - 2 , first - 1 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 old = peak
peak -= 1 peak -= 1
peakless_signal[ peak : first ] = peakless_signal[ peak ] * np.ones( first - peak ) peakless_signal[ peak : first ] = peakless_signal[ peak ] * np.ones( first - peak )
peak , old = first + 2 , first + 1 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 old = peak
peak += 1 peak += 1
peakless_signal[ first : peak ] = peakless_signal[ peak ] * np.ones( peak - first ) peakless_signal[ first : peak ] = peakless_signal[ peak ] * np.ones( peak - first )
@ -61,7 +61,7 @@ def get_extremities( signal , peaks ):
peaks_inside = np.where( peaks_inside = np.where(
argmin_1 < peaks, argmin_1 < peaks,
)[0] )[0]
if len( peaks_inside ) < 1: if len( peaks_inside ) == 0:
raise Exception( 'unknown plage, cannot autocalibrate' ) raise Exception( 'unknown plage, cannot autocalibrate' )
return ( first_peak , peaks_inside[0] ) 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 only keep data peaks corresponding to calibration
""" """
diff_calib = ( peaks_calib[ 1 : ] - peaks_calib[ : -1 ] ).astype( float ) diff_calib = ( peaks_calib[ 1 : ] - peaks_calib[ : -1 ] ).astype( float )
diff_calib -= np.min( diff_calib ) diff_calib /= np.sum( diff_calib )
diff_calib /= np.max( diff_calib )
diff_data = ( peaks_data[ 1 : ] - peaks_data[ : -1 ] ).astype( float ) diff_data = ( peaks_data[ 1 : ] - peaks_data[ : -1 ] ).astype( float )
diff_data -= np.min( diff_data ) diff_data /= np.sum( diff_data )
diff_data /= np.max( diff_data )
peaks = [ -1 ] peaks = [ -1 ]
for i in range( len( diff_calib ) ): 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 ) ): for j in range( peaks[ - 1 ] + 1 , len( diff_data ) ):
sum_ += diff_data[ j ] sum_ += diff_data[ j ]
if sum_ - diff_calib[ i ] > 0.002: if sum_ - diff_calib[ i ] > 0.002:
print( sum_ - diff_calib[ i ] )
raise Exception( 'reference peak not found' ) raise Exception( 'reference peak not found' )
if sum_ - diff_calib[ i ] > - 0.002: if sum_ - diff_calib[ i ] > - 0.002:
good = j good = j
@ -94,5 +91,6 @@ def only_keep_calib( peaks_data , peaks_calib ):
peaks.append( peaks[-1] + 1 ) # append the last peak peaks.append( peaks[-1] + 1 ) # append the last peak
return np.array( return np.array(
[ peaks_data[ i ] for i in peaks[ 1 : ] ] # remove the first -1 value [ peaks_data[ i ] for i in peaks[ 1 : ] ], # remove the first -1 value
).astype( int ) dtyp = int,
)