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Add peak deletion part

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Try to start from the same point for each spectrum by comparing 'ground' part without peaks
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linarphy 2023-05-23 11:28:54 +02:00
parent 902259cc2e
commit 3d90b03a6d
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GPG key ID: 3D4AAAC3AD16E79C
1 changed files with 60 additions and 11 deletions
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71
wavelength_calibration.py
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@ -1,8 +1,11 @@
import numpy as np import numpy as np
import scipy.signal as sig
import matplotlib.backends.backend_qtagg as qt import matplotlib.backends.backend_qtagg as qt
import matplotlib.figure as fig import matplotlib.figure as fig
import utils import utils
rect = [0.125,0.11,0.775,0.77]
calib_top = np.load( 'asset/calib_top.npy' ) calib_top = np.load( 'asset/calib_top.npy' )
calib_down = np.load( 'asset/calib_down.npy' ) calib_down = np.load( 'asset/calib_down.npy' )
reference = np.load( 'asset/reference.npy' ) reference = np.load( 'asset/reference.npy' )
@ -15,17 +18,6 @@ peaks_reference = utils.retrieve_peaks( reference[1] , window_size = 1 , max_win
polyval = np.polyfit( peaks_calib_top , peaks_reference[ 2 : ] , 1 ) polyval = np.polyfit( peaks_calib_top , peaks_reference[ 2 : ] , 1 )
manager = qt.FigureManager(
qt.FigureCanvas(
fig.Figure(
),
),
1,
)
manager.canvas.figure.add_axes( ( 0.05 , 0.15 , 0.9 , 0.7 ) ).plot( peaks_calib_top , np.array( peaks_reference[ 2 : ] ) - np.polyval( polyval , peaks_calib_top ) )
manager.show()
manager.start_main_loop()
peaks_values = [ reference[ 1 , i ] for i in np.array( peaks_reference ).astype( int ) ] peaks_values = [ reference[ 1 , i ] for i in np.array( peaks_reference ).astype( int ) ]
sorting = np.argsort( peaks_values )[ :: -1 ] sorting = np.argsort( peaks_values )[ :: -1 ]
wavelength = [ reference[ 0 , i ] for i in np.array( [ peaks_reference[ j ] for j in sorting ] ).astype( int ) ] wavelength = [ reference[ 0 , i ] for i in np.array( [ peaks_reference[ j ] for j in sorting ] ).astype( int ) ]
@ -34,6 +26,7 @@ polyval_wavelength = np.polyfit( peaks_reference , np.sort( wavelength ) , 1 )
wavelength = np.polyval( polyval_wavelength , np.polyval( polyval , np.arange( 0 , len( mean_calib_top ) , 1 ) ) ) wavelength = np.polyval( polyval_wavelength , np.polyval( polyval , np.arange( 0 , len( mean_calib_top ) , 1 ) ) )
"""
manager = qt.FigureManager( manager = qt.FigureManager(
qt.FigureCanvas( qt.FigureCanvas(
fig.Figure( fig.Figure(
@ -57,3 +50,59 @@ manager.canvas.figure.axes[1].set_title( 'reference' )
manager.show() manager.show()
manager.start_main_loop() manager.start_main_loop()
"""
for peak in np.array( peaks_calib_top ).astype( int ):
first = peak
peak , old = first - 2 , first - 1
while mean_calib_top[ peak ] <= mean_calib_top[ old ]:
old = peak
peak -= 1
mean_calib_top[ peak : first ] = mean_calib_top[ peak ] * np.ones( first - peak )
peak , old = first + 2 , first + 1
while mean_calib_top[ peak ] <= mean_calib_top[ old ]:
old = peak
peak += 1
mean_calib_top[ first : peak ] = mean_calib_top[ peak ] * np.ones( peak - first )
manager = qt.FigureManager(
qt.FigureCanvas(
fig.Figure(
figsize = ( 10 , 5 )
),
),
0,
)
manager.canvas.figure.gca().plot(
mean_calib_top
)
manager.canvas.figure.gca().plot(
sig.medfilt( mean_calib_top , 71 )
)
manager.show()
manager.start_main_loop()
manager = qt.FigureManager(
qt.FigureCanvas(
fig.Figure(),
),
1,
)
signal_calib = sig.convolve(
sig.medfilt( mean_calib_top , 71 ),
np.ones( 50 ),
'same'
)
manager.canvas.figure.gca().plot(
signal
)
manager.canvas.figure.gca().vlines(
[
np.argmin( signal[ 25 : -25 ] )
] ,
np.min( signal[ 25 : -25 ] ),
np.max( signal[ 25 : -25 ] ),
color = 'red' ,
)
manager.show()
manager.start_main_loop()