diff --git a/wavelength_calibration.py b/wavelength_calibration.py
index e02908d..c526d46 100644
--- a/wavelength_calibration.py
+++ b/wavelength_calibration.py
@@ -1,8 +1,11 @@
 import numpy as np
+import scipy.signal as sig
 import matplotlib.backends.backend_qtagg as qt
 import matplotlib.figure as fig
 import utils
 
+rect = [0.125,0.11,0.775,0.77]
+
 calib_top  = np.load( 'asset/calib_top.npy' )
 calib_down = np.load( 'asset/calib_down.npy' )
 reference  = np.load( 'asset/reference.npy' )
@@ -15,17 +18,6 @@ peaks_reference = utils.retrieve_peaks( reference[1] , window_size = 1 , max_win
 
 polyval = np.polyfit( peaks_calib_top , peaks_reference[ 2 : ] , 1 )
 
-manager = qt.FigureManager(
-    qt.FigureCanvas(
-        fig.Figure(
-        ),
-    ),
-    1,
-)
-manager.canvas.figure.add_axes( ( 0.05 , 0.15 , 0.9 , 0.7 ) ).plot( peaks_calib_top , np.array( peaks_reference[ 2 : ] ) - np.polyval( polyval , peaks_calib_top ) )
-manager.show()
-manager.start_main_loop()
-
 peaks_values = [ reference[ 1 , i ] for i in np.array( peaks_reference ).astype( int ) ]
 sorting = np.argsort( peaks_values )[ :: -1 ]
 wavelength = [ reference[ 0 , i ] for i in np.array( [ peaks_reference[ j ] for j in sorting ] ).astype( int ) ]
@@ -34,6 +26,7 @@ polyval_wavelength = np.polyfit( peaks_reference , np.sort( wavelength ) , 1 )
 
 wavelength = np.polyval( polyval_wavelength , np.polyval( polyval , np.arange( 0 , len( mean_calib_top ) , 1 ) ) )
 
+"""
 manager = qt.FigureManager(
     qt.FigureCanvas(
         fig.Figure(
@@ -57,3 +50,59 @@ manager.canvas.figure.axes[1].set_title( 'reference' )
 
 manager.show()
 manager.start_main_loop()
+"""
+for peak in np.array( peaks_calib_top ).astype( int ):
+    first = peak
+    peak , old = first - 2 , first - 1
+    while mean_calib_top[ peak ] <= mean_calib_top[ old ]:
+        old   = peak
+        peak -= 1
+    mean_calib_top[ peak : first ] = mean_calib_top[ peak ] * np.ones( first - peak )
+
+    peak , old = first + 2 , first + 1
+    while mean_calib_top[ peak ] <= mean_calib_top[ old ]:
+        old   = peak
+        peak += 1
+    mean_calib_top[ first : peak ] = mean_calib_top[ peak ] * np.ones( peak - first )
+
+manager = qt.FigureManager(
+    qt.FigureCanvas(
+        fig.Figure(
+            figsize = ( 10 , 5 )
+        ),
+    ),
+    0,
+)
+manager.canvas.figure.gca().plot(
+    mean_calib_top
+)
+manager.canvas.figure.gca().plot(
+    sig.medfilt( mean_calib_top , 71 )
+)
+manager.show()
+manager.start_main_loop()
+
+manager = qt.FigureManager(
+    qt.FigureCanvas(
+        fig.Figure(),
+    ),
+    1,
+)
+signal_calib = sig.convolve(
+    sig.medfilt( mean_calib_top , 71 ),
+    np.ones( 50 ),
+    'same'
+)
+manager.canvas.figure.gca().plot(
+    signal
+)
+manager.canvas.figure.gca().vlines(
+    [
+        np.argmin( signal[ 25 : -25 ] )
+    ]                           ,
+    np.min( signal[ 25 : -25 ] ),
+    np.max( signal[ 25 : -25 ] ),
+    color = 'red'               ,
+)
+manager.show()
+manager.start_main_loop()