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add option dominant freqs

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This commit is contained in:
François Boulogne 2026-01-06 11:03:58 +01:00
parent d007702712
commit 6f449512d1
2 changed files with 20 additions and 18 deletions
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2
mysignal/__init__.py
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@ -1 +1 @@
__version__ = '0.1.23'
__version__ = '0.1.24'

36
mysignal/phasefreq.py
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@ -12,7 +12,7 @@ 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, required_cycles=100):
def filter_signal_by_modes(time, signal, num_modes=1, bandwidth_factor=0.1, required_cycles=100, dominant_freqs=None):
"""
Filtre un signal pour extraire ses composantes fréquentielles dominantes.
@ -20,6 +20,7 @@ def filter_signal_by_modes(time, signal, num_modes=1, bandwidth_factor=0.1, requ
time (array-like): Array contenant les données temporelles.
signal (array-like): Array contenant les données du signal.
num_modes (int): Nombre de modes fréquentiels à extraire.
dominant_freqs: les frequences des modes, if None, computed internally
Returns:
tuple: (filtered_signals, frequencies, time_filtered)
@ -38,25 +39,26 @@ def filter_signal_by_modes(time, signal, num_modes=1, bandwidth_factor=0.1, requ
# Supprimer la composante DC
signal_clean = signal - np.mean(signal)
# Calculer la FFT
n = len(time)
fft_signal = fft(signal_clean)
freqs = fftfreq(n, dt)
if dominant_freqs is None:
# Calculer la FFT
n = len(time)
fft_signal = fft(signal_clean)
freqs = fftfreq(n, dt)
# Prendre seulement les fréquences positives
positive_mask = freqs > 0
freqs_pos = freqs[positive_mask]
fft_pos = fft_signal[positive_mask]
# Prendre seulement les fréquences positives
positive_mask = freqs > 0
freqs_pos = freqs[positive_mask]
fft_pos = fft_signal[positive_mask]
# Trouver les pics dans le spectre
magnitude = np.abs(fft_pos)
peaks, _ = find_peaks(magnitude, height=0.1*np.max(magnitude))
peak_freqs = freqs_pos[peaks]
peak_mags = magnitude[peaks]
# Trouver les pics dans le spectre
magnitude = np.abs(fft_pos)
peaks, _ = find_peaks(magnitude, height=0.1*np.max(magnitude))
peak_freqs = freqs_pos[peaks]
peak_mags = magnitude[peaks]
# Trier les pics par magnitude et sélectionner les num_modes plus importants
idx = np.argsort(peak_mags)[-num_modes:]
dominant_freqs = peak_freqs[idx]
# Trier les pics par magnitude et sélectionner les num_modes plus importants
idx = np.argsort(peak_mags)[-num_modes:]
dominant_freqs = peak_freqs[idx]
# Trier les fréquences par ordre croissant
dominant_freqs.sort()