research/mysignal
1
0
Fork 0
Code Issues Pull requests Projects Releases Packages Wiki Activity Actions

upd

Browse source
This commit is contained in:
François Boulogne 2025-08-29 16:45:25 +02:00
parent 6b66a2f3da
commit d4983f45f2
2 changed files with 13 additions and 12 deletions
Download patch file Download diff file Expand all files Collapse all files

2
mysignal/__init__.py
View file

@ -1 +1 @@
__version__ = '0.1.1'
__version__ = '0.1.2'

7
mysignal/phasefreq.py
View file

@ -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, nyquist=False):
"""
Filtre un signal pour extraire ses composantes fréquentielles dominantes.
@ -68,6 +68,7 @@ def filter_signal_by_modes(time, signal, num_modes=1, bandwidth_factor=0.1):
lowcut = freq - bandwidth
highcut = freq + bandwidth
if nyquist:
# Éviter les fréquences négatives ou supérieures à la fréquence de Nyquist
nyq = 0.5 * fs
if lowcut <= 0:
@ -76,8 +77,8 @@ def filter_signal_by_modes(time, signal, num_modes=1, bandwidth_factor=0.1):
highcut = nyq - 0.01
# Créer le filtre Butterworth
low = lowcut / nyq
high = highcut / nyq
lowcut = lowcut / nyq
highcut = highcut / nyq
b, a = butter(4, [low, high], btype='band')
# Appliquer le filtre (filtfilt pour éviter le déphasage)