Update to use wavelength_calibration

ETA.py

@@ -384,39 +384,58 @@ else:
 # Calibration
 
 if calibration != None:
-    calib_peaks   = np.loadtxt( calibration )
-    mean_calib_up = np.mean( data[
+    import wavelength_calibration as wave_calib
+    peaks_calib   = np.loadtxt( calibration ) # sorted list
+    peaks_calib = np.sort( peaks_calib )
+    mean_up = np.mean( data[
         calibrations[ 'top' ][ 'y' ][ 'min' ] : calibrations[ 'top' ][ 'y' ][ 'max' ],
         calibrations[ 'top' ][ 'x' ][ 'min' ] : calibrations[ 'top' ][ 'x' ][ 'max' ]
     ] , axis = 0 )
-    mean_calib_up -= np.min( mean_calib_up )
-    mean_calib_up /= np.max( mean_calib_up )
+    peaks_up      = np.array(
+        utils.retrieve_peaks(
+            mean_up            ,
+            window_size = 1    ,
+            max_window_size = 1,
+        )
+    ).astype( int )
 
-    peaks_up = find_peaks( mean_calib_up , height = 0.5 )[0] + calibrations[ 'top' ][ 'x' ][ 'min' ]
-    diff     = np.array( [ np.inf ] )
-    polyval = np.polyfit( peaks_up[ : len( calib_peaks ) ] , calib_peaks[ : len( peaks_up ) ] , 1 )
+    peakless_up = wave_calib.remove_peaks( mean_up , peaks_up )
+    calib = { # hard-coded for now
+        'first': 3 ,
+        'last':  20,
+    }
+    first , last = wave_calib.get_extremities( peakless_up , peaks_up , mean_up )
+    up    = {
+        'first': first,
+        'last' : last ,
+    }
+    peaks_up    = peaks_up[    up[ 'first' ]    : up[ 'last' ]    + 1 ]
+    peaks_calib = peaks_calib[ calib[ 'first' ] : calib[ 'last' ] + 1 ]
 
-    while np.max( diff ) > 1000: # we do not have the exact same number of peak (and the same peaks) in calibration model
-        diff            = abs( np.polyval( polyval , peaks_up[ : len( calib_peaks ) ] ) - calib_peaks[ : len( peaks_up ) ] )
-        point_to_delete = np.argmax( diff ) # get the "worst" point
-        peaks_up_new    = np.delete( peaks_up    , [ point_to_delete ] ) # remove from data value ( other peak detected )
-        calib_peaks_new = np.delete( calib_peaks , [ point_to_delete ] ) # remove from model ( peak not detected )
+    peaks_up = wave_calib.only_keep_calib( peaks_up , peaks_calib )
 
-        polyfull_up    = np.polyfit( peaks_up_new[ : len( calib_peaks ) ] , calib_peaks[ : len( peaks_up_new ) ] , 1 , full = True )
-        polyfull_calib = np.polyfit( peaks_up[ : len( calib_peaks_new ) ] , calib_peaks_new[ : len( peaks_up ) ] , 1 , full = True )
+    polyval_wavelength = np.polyfit( # x = 0 begins at the start of
+        peaks_up   ,                 # calibartions[ 'top' ][ 'x' ][ 'min' ]
+        peaks_calib,
+        1          ,
+    )
 
-        if polyfull_up[ 1 ][ 0 ] < polyfull_calib[ 1 ][ 0 ]: # which one is a better fit ?
-            peaks_up = peaks_up_new
-            polyval  = polyfull_up[ 0 ]
-        else:
-            calib_peaks = calib_peaks_new
-            polyval     = polyfull_calib[ 0 ]
+    wavelength = np.polyval(
+        polyval_wavelength,
+        np.arange(
+            0             ,
+            len( mean_up ),
+            1             ,
+        )
+    )
 
-    x = np.arange( calibrations[ 'top' ][ 'x' ][ 'min' ] , calibrations[ 'top' ][ 'x' ][ 'max' ] , 1 )
-    x = np.polyval( polyval , x )
-
-    plt.margins( x = 0 )
-    plt.plot( x , mean_calib_up )
+    plt.plot(
+        peaks_up,
+        peaks_calib - np.polyval(
+            polyval_wavelength,
+            peaks_up          ,
+        )       ,
+    )
     plt.show()
     exit()