diff --git a/mysignal/phasefreq.py b/mysignal/phasefreq.py
index 32f2fb2..1860eec 100644
--- a/mysignal/phasefreq.py
+++ b/mysignal/phasefreq.py
@@ -9,7 +9,7 @@ from scipy.stats import linregress
 from scipy.optimize import curve_fit
 
 
-def filter_signal_by_modes(time, signal, num_modes=1, bandwidth_factor=0.1):
+def filter_signal_by_modes(time, signal, num_modes=1, bandwidth_factor=0.1,required_cycles=40):
     """
     Filtre un signal pour extraire ses composantes fréquentielles dominantes.
 
@@ -76,11 +76,11 @@ def filter_signal_by_modes(time, signal, num_modes=1, bandwidth_factor=0.1):
         lowcut_norm = lowcut / nyq
         highcut_norm = highcut / nyq
         
-        print(f"Filtrage à {freq:.2f} Hz: [{lowcut_norm:.3f}, {highcut_norm:.3f}] (normalisé)")
+        print(f"Filtrage à {freq:.2f} Hz, bande : [{lowcut_norm:.5f}, {highcut_norm:.5f}] (normalisé)")
         
         # Vérifier si le signal est suffisamment long
         period = 1 / lowcut if lowcut > 0 else 0
-        required_cycles = 40  # Vous avez mentionné 30 cycles
+        #required_cycles = 40  # Vous avez mentionné 40 cycles
         min_length = required_cycles * period * fs
         
         if len(signal_clean) < min_length: