Add intensity calibration
- Bump version - Add intensity calibration - Clean wavelength calibration (WIP) - Add --intensity option - Update --calibration option to --wavelength
This commit is contained in:
parent
f6970dce17
commit
fb0e548243
1 changed files with 123 additions and 25 deletions
148
spectrum.py
148
spectrum.py
|
|
@ -8,7 +8,7 @@ import shelve
|
|||
import pathlib
|
||||
from scipy.ndimage import rotate
|
||||
|
||||
cache , filename , output , calibration , verbose , no_cache = '' , None , None , None , False, False
|
||||
cache , filename , output , calibration , intensity_calibration , verbose , no_cache = '' , None , None , None , None , False, False
|
||||
if len( sys.argv ) < 2:
|
||||
raise Exception( 'spectrum.py: type \'spectrum.py -h\' for more information' )
|
||||
|
||||
|
|
@ -39,10 +39,16 @@ while i < len( argv ):
|
|||
argv[ i + 1 ] = '--output=' + argv[ i + 1 ]
|
||||
i += 1
|
||||
continue
|
||||
elif arg == '-a':
|
||||
elif arg == '-w':
|
||||
if i == len( sys.argv ) - 1:
|
||||
raise Exception( 'spectrum.py: calibration have to take a value' )
|
||||
argv[ i + 1 ] = '--calibration=' + argv[ i + 1 ]
|
||||
raise Exception( 'spectrum.py: wavelength have to take a value' )
|
||||
argv[ i + 1 ] = '--wavelength=' + argv[ i + 1 ]
|
||||
i += 1
|
||||
continue
|
||||
elif arg == '-i':
|
||||
if i == len( sys.argv ) - 1:
|
||||
raise Exception( 'spectrum.py: intensity have to take a value' )
|
||||
argv[ i + 1 ] = '--intensity=' + argv[ i + 1 ]
|
||||
i += 1
|
||||
continue
|
||||
else:
|
||||
|
|
@ -50,8 +56,10 @@ while i < len( argv ):
|
|||
if arg[1] == '-': # not elif because arg can change after last if
|
||||
if arg == '--help':
|
||||
print( 'spectrum.py [options...] filename\
|
||||
\n -a --calibration calibration file, default to no calibration.\
|
||||
\n -w --wavelength wavelength calibration file, default to no calibration.\
|
||||
\n No calibration means no wavelength interpolation\
|
||||
\n -i --intensity intensity calibration file, default to no calibration.\
|
||||
\n No calibration means no intensity interpolation\
|
||||
\n -c --cache use given cache\
|
||||
\n -h --help show this help and quit\
|
||||
\n -n --no-cache do not use cache and rewrite it\
|
||||
|
|
@ -62,7 +70,7 @@ while i < len( argv ):
|
|||
\nParse a naroo ETA fits' )
|
||||
exit()
|
||||
elif arg == '--version':
|
||||
print( '0.2' )
|
||||
print( '0.3' )
|
||||
exit()
|
||||
elif arg == '--verbose':
|
||||
verbose = True
|
||||
|
|
@ -72,8 +80,10 @@ while i < len( argv ):
|
|||
cache = arg[ 8 : ]
|
||||
elif len( arg ) > 9 and arg[ : 9 ] == '--output=':
|
||||
output = arg[ 9 : ]
|
||||
elif len( arg ) > 14 and arg[ : 14 ] == '--calibration=':
|
||||
calibration = arg[ 14 : ]
|
||||
elif len( arg ) > 13 and arg[ : 13 ] == '--wavelength=':
|
||||
calibration = arg[ 13 : ]
|
||||
elif len( arg ) > 12 and arg[ : 12 ] == '--intensity=':
|
||||
intensity = arg[ 12 : ]
|
||||
else:
|
||||
raise Exception( 'spectrum.py: unknown argument "' + arg + '", type \'ETA.py -h\' for more information' )
|
||||
else:
|
||||
|
|
@ -89,7 +99,8 @@ if verbose:
|
|||
print( f'spectrum.py: launching now with parameters:\
|
||||
\n --filename: {filename}\
|
||||
\n --cache: {cache} ( default: \'\' )\
|
||||
\n --calibration: {calibration} ( default to None )\
|
||||
\n --wavelength: {calibration} ( default to None )\
|
||||
\n --intensity: {intensity} ( default to None )\
|
||||
\n --output: {output} ( default to None )\
|
||||
\n --verbose: True ( default to False)\
|
||||
\n\
|
||||
|
|
@ -471,10 +482,52 @@ else:
|
|||
Calibration
|
||||
"""
|
||||
|
||||
wavelengths = np.arange( spectrum[ 'x' ][ 'max' ] - spectrum[ 'x' ][ 'min' ] )
|
||||
|
||||
if calibration != None:
|
||||
if verbose:
|
||||
print( 'starting calibration' )
|
||||
print( 'starting wavelength calibration' )
|
||||
|
||||
mean_data = np.mean( data[
|
||||
spectrum[ 'y' ][ 'min' ] : spectrum[ 'y' ][ 'max' ],
|
||||
spectrum[ 'x' ][ 'min' ] : spectrum[ 'x' ][ 'max' ]
|
||||
] , axis = 0 )
|
||||
abciss = np.arange( len( mean_data ) )
|
||||
|
||||
ref = np.array( [
|
||||
6562.79,
|
||||
4861.35,
|
||||
4340.47,
|
||||
4101.73,
|
||||
3970.08,
|
||||
3889.06,
|
||||
3835.40,
|
||||
# 3646 ,
|
||||
] ) * 1e-10
|
||||
start , end = 5000 , 18440
|
||||
|
||||
polyval_before = np.polyfit( abciss[ : start ] , mean_data[ : start ] , 2 )
|
||||
polyval_middle = np.polyfit( abciss[ start : end ] , mean_data[ start : end ] , 2 )
|
||||
polyval_end = np.polyfit( abciss[ end : ] , mean_data[ end : ] , 2 )
|
||||
|
||||
mean_data[ : start ] = mean_data[ : start ] - np.polyval( polyval_before , abciss[ : start ] )
|
||||
mean_data[ start : end ] = mean_data[ start : end ] - np.polyval( polyval_middle , abciss[ start : end ] )
|
||||
mean_data[ end : ] = mean_data[ end : ] - np.polyval( polyval_end , abciss[ end : ] )
|
||||
|
||||
mean_data_normalized = mean_data.copy() # normalization
|
||||
mean_data_normalized -= np.min( mean_data_normalized )
|
||||
mean_data_normalized /= np.max( mean_data_normalized )
|
||||
|
||||
lines = [ np.mean( cons ) for cons in utils.consecutive( np.where( mean_data_normalized < 0.3 )[0] ) ]
|
||||
lines = np.array( lines[ : len( ref ) - 1 ] ) # Balmer discontinuity
|
||||
|
||||
ref = ref[ 1 : ] # start with H-beta
|
||||
|
||||
wavelength_polyval = np.polyfit( lines , ref , 1 )
|
||||
|
||||
wavelengths = np.polyval( wavelength_polyval , abciss )
|
||||
|
||||
"""
|
||||
mean_up = np.mean( data[
|
||||
calibrations[ 'top' ][ 'y' ][ 'min' ] : calibrations[ 'top' ][ 'y' ][ 'max' ],
|
||||
calibrations[ 'top' ][ 'x' ][ 'min' ] : claibrations[ 'top' ][ 'x' ][ 'max' ]
|
||||
|
|
@ -499,33 +552,78 @@ if calibration != None:
|
|||
) ,
|
||||
dtype = int,
|
||||
)
|
||||
"""
|
||||
|
||||
if verbose:
|
||||
print( 'calibration finished' )
|
||||
print( 'wavelength calibration finished' )
|
||||
|
||||
mean_data = np.mean( data[
|
||||
spectrum[ 'y' ][ 'min' ] : spectrum[ 'y' ][ 'max' ],
|
||||
spectrum[ 'x' ][ 'min' ] : spectrum[ 'x' ][ 'max' ]
|
||||
] , axis = 0 )
|
||||
|
||||
if intensity != None:
|
||||
if verbose:
|
||||
print( 'starting intensity calibration' )
|
||||
|
||||
intensity_file = pathlib.Path( intensity )
|
||||
|
||||
with shelve.open( str( intensity_file ) ) as storage:
|
||||
intensity_stairs = storage[ 'data' ]
|
||||
intensity_wavelengths = storage[ 'wavelength' ]
|
||||
|
||||
final_intensity = np.zeros( len( wavelengths ) )
|
||||
for index in range( len( wavelengths ) ):
|
||||
intensity_value = mean_data[ index ]
|
||||
intensity_wavelength = wavelengths[ index ]
|
||||
intensity_index = utils.near_value(
|
||||
intensity_wavelengths,
|
||||
intensity_wavelength ,
|
||||
)
|
||||
index_stair = np.where(
|
||||
intensity_stairs[
|
||||
: ,
|
||||
intensity_index,
|
||||
0 ,
|
||||
] < intensity_value
|
||||
)[0][-1]
|
||||
stair_before = intensity_stairs[ index_stair , intensity_index ]
|
||||
stair_after = intensity_stairs[ index_stair - 1 , intensity_index ]
|
||||
step = 0.2
|
||||
start_step = step * ( stairs.shape[0] - index_stair - 1 )
|
||||
|
||||
index_polyval = np.polyfit(
|
||||
[ index_stair , index_stair - 1 ],
|
||||
[ stair_before , stair_after ]
|
||||
)
|
||||
|
||||
stair_polyval = np.polyfit(
|
||||
[ stair_before , stair_after ],
|
||||
[ 0 , step ]
|
||||
)
|
||||
|
||||
final_intensity[index] = start_step + np.polyval( # the step fraction
|
||||
stair_polyval,
|
||||
np.polyval( index_polyval , intensity_index ), # the stair "fraction"
|
||||
)
|
||||
|
||||
plt.plot( final_intensity )
|
||||
plt.show()
|
||||
|
||||
if verbose:
|
||||
print( 'intensity calibration finished' )
|
||||
|
||||
if verbose:
|
||||
print( 'starting output writing' )
|
||||
|
||||
if output == None:
|
||||
print( np.mean(
|
||||
data[
|
||||
spectrum[ 'y' ][ 'min' ] : spectrum[ 'y' ][ 'max' ],
|
||||
specturm[ 'x' ][ 'min' ] : spectrum[ 'x' ][ 'max' ],
|
||||
] ,
|
||||
axis = 0,
|
||||
) )
|
||||
print( mean_data )
|
||||
else:
|
||||
if verbose:
|
||||
print( 'storing result in ' + output )
|
||||
output_file = pathlib.Path( output )
|
||||
with shelve.open( str( output_file ) ) as output:
|
||||
output[ 'data' ] = np.mean(
|
||||
data[
|
||||
spectrum[ 'y' ][ 'min' ] : spectrum[ 'y' ][ 'max' ],
|
||||
spectrum[ 'x' ][ 'min' ] : spectrum[ 'x' ][ 'max' ],
|
||||
] ,
|
||||
axis = 0,
|
||||
)
|
||||
output[ 'data' ] = mean_data
|
||||
if verbose:
|
||||
print( 'output writing finished' )
|
||||
print( '===========================================\
|
||||
|
|
|
|||
Loading…
Reference in a new issue