Update version number

- Add --output option (WIP)
- Add output generated (only missing thing is now the wavelength axis)

ETA.py

@@ -8,7 +8,7 @@ from scipy.signal import convolve as sp_convolve
 from scipy.signal import find_peaks
 from scipy.ndimage import rotate
 
-cache , filename = '' , None
+cache , filename , output = '' , None , None
 if len( sys.argv ) < 2:
     raise Exception( 'ETA.py: type \'ETA.py -h\' for more information' )
 
@@ -27,7 +27,13 @@ for i in range( 1 , len( sys.argv ) ):
             elif arg == '-c':
                 if i == len( sys.argv ) - 1:
                     raise Exception( 'ETA.py: cache have to take a value' )
-                arg == '--cache=' + arg[ i + 1 ]
+                arg[ i + 1 ] == '--cache=' + arg[ i + 1 ]
+                continue
+            elif arg == '-o':
+                if i == len( sys.argv ) - 1:
+                    raise Exception( 'ETA.py: output have to take a value' )
+                arg[ i + 1 ] == '--output=' + arg[ i + 1 ]
+                continue
             else:
                 raise Exception( 'ETA.py: unknown argument "' + arg + '", type \'ETA.py -h\' for more information' )
         if arg[1] == '-': # not elif because arg can change after last if
@@ -37,16 +43,19 @@ for i in range( 1 , len( sys.argv ) ):
                       \n    -v --version  show version number and quit\
                       \n    -n --no-cache do not use cache and rewrite it\
                       \n    -c --cache    use given cache\
+                      \n    -o --output   output file, default to standard output\
                       \n\
                       \nParse a naroo ETA fits' )
                 exit()
             elif arg == '--version':
-                print( '0.1' )
+                print( '0.2' )
                 exit()
             elif arg == '--no-cache':
                 cache = '' # hack, empty string mean this dir, so not a file
             elif len( arg ) > 8 and arg[ : 8 ] == '--cache=':
                 cache = arg[ 8 : ]
+            elif len( arg ) > 9 and arg[ : 9 ] == '--output=':
+                output = arg[ 9 : ]
             else:
                 raise Exception( 'ETA.py: unknown argument "' + arg + '", type \'ETA.py -h\' for more information' )
         else:
@@ -68,6 +77,7 @@ if cache_file.is_file():
         data         = cache[ 'rotated_data' ]
         border       = cache[    'border'    ]
         calibrations = cache[ 'calibrations' ]
+        stripes      = cache[   'stripes'    ]
 else:
     """
     find fill points
@@ -327,34 +337,43 @@ else:
         },
     }
 
+    """
+    stripes curves detection
+    """
+    list_ = data[
+        calibrations[ 'top' ][ 'y' ][ 'max' ] : calibrations[ 'down' ][ 'y' ][ 'min' ],
+        border[ 'x' ][ 'min' ] : border[ 'x' ][ 'max' ]
+    ].copy()
+    list_min = np.min( list_ , axis = 0 )
+    list_   -= list_min
+    list_max = np.max( list_ , axis = 0 )
+    list_   /= list_max
+    size     = list_.shape[1]
+
+    y_stripe = np.argmax( list_ , axis = 0 )
+    good_x   = np.where( y_stripe < 2 * np.mean( y_stripe ) )[0]
+    x_stripe = np.arange( 0 , size , 1 ).astype( int )[ good_x ]
+    y_stripe = y_stripe[ good_x ]
+
+    stripes = [ # list of polyval result for each stripe
+        np.polyfit( x_stripe , y_stripe , 3 )
+    ]
+
     if not cache_file.exists():
         with shelve.open( str( cache_file ) ) as cache:
             cache[ 'rotated_data' ] = data
             cache[ 'border' ]       = border
             cache[ 'calibrations']  = calibrations
+            cache[ 'stripes' ]      = stripes
+print( border )
+print( calibrations )
+exit()
+# First deformation
 
-"""
-stripes curves detection
-"""
 list_ = data[
     calibrations[ 'top' ][ 'y' ][ 'max' ] : calibrations[ 'down' ][ 'y' ][ 'min' ],
     border[ 'x' ][ 'min' ] : border[ 'x' ][ 'max' ]
-].copy()
-list_ -= np.min( list_ , axis = 0 )
-list_ /= np.max( list_ , axis = 0 )
-size     = list_.shape[1]
-
-y_stripe = np.argmax( list_ , axis = 0 )
-good_x   = np.where( y_stripe < 2 * np.mean( y_stripe ) )[0]
-x_stripe = np.arange( 0 , size , 1 ).astype( int )[ good_x ]
-y_stripe = y_stripe[ good_x ]
-
-stripes = [ # list of polyval result for each stripe
-    np.polyfit( x_stripe , y_stripe , 3 )
 ]
-
-# First deformation
-
 y_diff  = ( np.polyval( stripes[0] , np.arange( 0 , size , 1 ) ) ).astype( int )
 y_diff[ np.where( y_diff < 0 ) ] = 0
 results = np.zeros( ( list_.shape[0] + np.max( y_diff ) , list_.shape[1] ) )
@@ -369,7 +388,7 @@ list_results = np.convolve(
     'same'       ,
 )
 
-fall = utils.consecutive( np.where( list_results < - 0.02 )[0] )
+fall = utils.consecutive( np.where( list_results < 0.03 * np.min( list_results ) )[0] )
 fall = np.array( [
         np.argmax( list_results )
     ] + [
@@ -378,30 +397,12 @@ fall = np.array( [
     ) for consecutive in fall
 ] ).astype( int )
 
-mask = np.zeros_like( data )
+stairs = np.zeros_like( results )
-mask[
+for x in range( size ):
-    calibrations[ 'top' ][ 'y' ][ 'min' ] : calibrations[ 'top' ][ 'y' ][ 'max' ],
+    stairs[ : , x ] = results[ : , x ] # can be modified, but no used anymore so it's fine
-    calibrations[ 'top' ][ 'x' ][ 'min' ] : calibrations[ 'top' ][ 'x' ][ 'max' ]
+    stairs[ : fall[0] , x ] = 0
-] = -1
+    for i in range( len( fall ) - 1 ):
-mask[
+        stairs[ fall[ i ] : fall[ i + 1 ] , x ] = np.mean( stairs[ fall[ i ] : fall[ i + 1 ] ] )
-    calibrations[ 'down' ][ 'y' ][ 'min' ] : calibrations[ 'down' ][ 'y' ][ 'max' ],
+    stairs[ fall[ -1 ] : , x ] = 0
-    calibrations[ 'down' ][ 'x' ][ 'min' ] : calibrations[ 'down' ][ 'x' ][ 'max' ]
+plt.imshow( stairs )
-] = -1
-mask[
-    calibrations[ 'top' ][ 'y' ][ 'max' ] : calibrations[ 'down' ][ 'y' ][ 'min' ],
-    border[ 'x' ][ 'min' ]                : border[ 'x' ][ 'max' ]
-] = 1
-plt.imshow( data )
-plt.imshow( mask , alpha = 0.5 )
-plt.show()
-
-temp = results[ : , 10000 ].copy()
-temp[ : fall[ 0 ] ] = 0
-for i in range( len( fall ) - 1 ):
-    temp[ fall[ i ] : fall[ i + 1 ] ] = np.mean( temp[ fall[ i ] : fall[ i + 1 ] ] )
-temp[ fall[ - 1 ] : ] = np.mean( temp[ fall[ -1 ] : ] )
-
-plt.plot( results[ : , 10000 ] , label = 'raw' )
-plt.plot( temp , label = 'flat' )
-plt.legend()
 plt.show()