From a7d664f21a249df152ff3cc5717c9b7e6053ed59 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Fran=C3=A7ois=20Boulogne?= Date: Fri, 29 Aug 2025 18:42:03 +0200 Subject: [PATCH] upd --- mysignal/phasefreq.py | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) 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: