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François Boulogne 2025-08-29 18:42:03 +02:00
parent e1ae1c6236
commit a7d664f21a
1 changed files with 3 additions and 3 deletions
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mysignal/phasefreq.py
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@ -9,7 +9,7 @@ from scipy.stats import linregress
from scipy.optimize import curve_fit 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. 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 lowcut_norm = lowcut / nyq
highcut_norm = highcut / 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 # Vérifier si le signal est suffisamment long
period = 1 / lowcut if lowcut > 0 else 0 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 min_length = required_cycles * period * fs
if len(signal_clean) < min_length: if len(signal_clean) < min_length: