Update how to find start and stop position of a peak

classes/science/plate.py

@@ -271,16 +271,18 @@ class Plate:
         Set spectrum area
         """
         self.spectrum = Border()
-
+        list_ = convolve(
-        indexes = find_peak_low_high(
-            convolve(
             mean(
                 self.data[ self.border.slice() ],
                 axis = 1                        ,
             )          ,
             ones( 200 ),
             'valid'    ,
-            ),
+        )
+
+        indexes = find_peak_low_high(
+            list_                           ,
+            ( max( list_ ) + mean( list_ ) ) / 2,
         )[0]
 
         self.spectrum.y.min = indexes[0] + self.border.y.min + 100
@@ -289,15 +291,17 @@ class Plate:
         import matplotlib.pyplot as plt
         plt.imshow( self.data[ self.border.slice() ] , aspect = 'auto' )
         plt.show()
-        indexes = find_peak_low_high(
+        list_ = convolve(
-            convolve(
             mean(
                 self.data[ self.border.slice() ],
                 axis = 0                        ,
             )          ,
             ones( 200 ),
             'valid'    ,
-            ),
+        )
+        indexes = find_peak_low_high(
+            list_                           ,
+            mean( list_ ) + max( list_ ) / 2,
         )[0]
 
         self.spectrum.x.min = indexes[0] + self.border.x.min + 100

function/utils.py

@@ -208,10 +208,39 @@ def near_value( list_ , value ):
     index = np.append( index , np.where( list_ == value ) )
     return np.round( np.sort( index ) ).astype( int ) # triage
 
-def find_peak_low_high( list_ ):
+def find_peak_low_high( list_ , value ):
     """
     Return index of start and end of the biggest peak in a list
     """
+    indexes = near_value(
+        list_,
+        value,
+    )
+    list_ = np.gradient( list_ )
+    if list_[ indexes[0] ] < 0:
+        indexes.insert( 0 , 0 )
+        if list_[ indexes[0] ] < 0:
+            indexes.insert( 0 , 0 ) # start with a descent
+    if list_[ indexes[-1] ] > 0:
+        indexes.append( len( list_ ) - 1 )
+        if list_[ indexes[-1] ] > 0:
+            indexes.append( len( list_ ) - 1 ) # end with a rise
+
+    if len( indexes ) % 2 == 1:
+        raise Exception(
+            'number of peaks doesn\'t match what it should be'
+        )
+    rises    = [
+        indexes[ i ] for i in range( 0 , len( indexes ) , 2 )
+    ]
+    descents = [
+        indexes[ i ] for i in range( 1 , len( indexes ) , 2 )
+    ]
+    np.where( list_[ : rises[0] ] < 0 )[-1]
+    np.where( list_[ descents[ i - 1 ] : rises[ i ] ] < 0 )[-1]
+    np.where( list_[ rises[ i - 1 ] : descents[ i ] ] < 0 )[-1]
+    first_rise    , last_rise    = indexes[0] , indexes[0]
+    first_descent , last_descent = indexes[1] , indexes[1]
     min_diff = ( max( list_ ) - min( list_ ) ) * 0.001
     max_high_value = max( list_ )
     min_high_value = min( list_ )