Add files via upload

3D_app/filtrage.py

@@ -0,0 +1,42 @@
+import pandas as pd
+import numpy as np
+import matplotlib.pyplot as plt
+from scipy.signal import hilbert,butter, filtfilt,wiener,hamming, convolve
+
+#transformer du Hilbert
+def transformer_hilbert(data_input):
+    data_output=np.abs(hilbert(data_input))
+    return data_output
+
+#filtre de moyenne mobile
+def filtre_moyenne_mobile(data_input,window_size):
+    data_output=pd.Series(data_input).rolling(window=window_size).mean()
+    return data_output
+
+# filtre passe bas
+def filtre_passe_bas(data_input,fs,cut_off,order):
+    nyq=0.5*fs
+    normal_cut_off=cut_off/nyq
+    [b,a]=butter(order,normal_cut_off,btype='low', analog=False)
+    data_output=filtfilt(b,a,data_input)
+    return data_output
+
+#filtre adaptatif de réduction de bruit
+def filtre_adaptatif(data_input):
+    data_output=wiener(data_input)
+    return data_output
+
+#Le filtre à réponse impulsionnelle infinie
+
+def filtre_RII(data_input,window_size):
+    b1=hamming(window_size)/np.sum(window_size)
+    data_output=filtfilt(b1,1,data_input)
+    return data_output
+
+# Le filtre à réponse impulsionnelle finie
+
+def filtre_RIF(data_input,window_size):
+    h=hamming(window_size)/np.sum(window_size)
+    data_output=convolve(data_input, h, mode='same')
+    return data_output
+    

3D_app/selection_filtre.py

@@ -0,0 +1,19 @@
+from filtrage import *
+def switch_case(data_input,select,fs=1,cut_off=1,order=1,window_size=1):
+    match select:
+        case 1:
+            return transformer_hilbert(data_input)
+        case 2:
+            return data_input
+        case 3:
+            return filtre_passe_bas(data_input,fs,cut_off,order)
+        case 4:
+            return filtre_moyenne_mobile(data_input,window_size)
+        case 5:
+            return filtre_adaptatif(data_input)
+        case 6:
+            return filtre_RII(data_input,window_size)
+        case 7:
+            return filtre_RIF(data_input,window_size)
+        case _:
+            return data_input