Remove display

spectrum.py

@@ -12,8 +12,8 @@ import pathlib
 from scipy.ndimage import rotate
 from astropy.io import fits
 
-cache , filename , output , calibration , intensity_calibration
-, verbose , no_cache = None , None , None , None , None , False, False
+cache , filename , output , calibration = None , None , None , None
+intensity_calibration , verbose , no_cache = None , False, False
 if len( sys.argv ) < 2:
     raise Exception( 'spectrum.py: type \'spectrum.py -h\' for more information' )
 
@@ -75,7 +75,7 @@ while i < len( argv ):
                       \nParse a naroo spectrum fits' )
                 exit()
             elif arg == '--version':
-                print( '0.3' )
+                print( '0.4' )
                 exit()
             elif arg == '--verbose':
                 verbose = True
@@ -110,8 +110,6 @@ if verbose:
            \n    --verbose:     True ( default to False)\
            \n\
            \n===========================================' )
-# TODO: check in advance file to check if exists or writeable
-
 files = {}
 if calibration != None:
     files[ 'wavelength' ] = pathlib.Path( calibration )
@@ -126,7 +124,6 @@ for name , path in files.items():
     if name in [
         'wavelength',
         'intensity' ,
-        'spectrum'  ,
     ] and not path.is_file():
         raise Exception(
             'spectrum.py: could not open the ' + name + ' file'
@@ -659,19 +656,11 @@ mean_bias = sp_convolve(
         axis = 0,
     )     ,
     np.ones(
-        (
         50,
     )     ,
-    )     ,
     'same',
 ) / 50
 
-plt.plot( bias[ 'top' ]  , label = 'top'  )
-plt.plot( bias[ 'down' ] , label = 'down' )
-plt.plot( mean_bias      , label = 'mean' )
-plt.legend()
-plt.show()
-
 data[
                            :                       ,
     spectrum[ 'x' ][ 'min' ] : spectrum[ 'x' ][ 'max' ]
@@ -683,13 +672,6 @@ data[
 if verbose:
     print( 'bias substraction finished' )
 
-ETA_bias = np.load( 'ETA_bias.npy' )
-
-plt.plot( mean_bias , label = 'spectrum' )
-plt.plot( ETA_bias  , label = 'ETA'      )
-plt.legend()
-plt.show()
-
 mean_data = np.mean( data[
     spectrum[ 'y' ][ 'min' ] : spectrum[ 'y' ][ 'max' ],
     spectrum[ 'x' ][ 'min' ] : spectrum[ 'x' ][ 'max' ]