From d4983f45f255324b76446c3a349184a7239a447c Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Fran=C3=A7ois=20Boulogne?= <devel@sciunto.org>
Date: Fri, 29 Aug 2025 16:45:25 +0200
Subject: [PATCH] upd

---
 mysignal/__init__.py  |  2 +-
 mysignal/phasefreq.py | 23 ++++++++++++-----------
 2 files changed, 13 insertions(+), 12 deletions(-)

diff --git a/mysignal/__init__.py b/mysignal/__init__.py
index df9144c..10939f0 100644
--- a/mysignal/__init__.py
+++ b/mysignal/__init__.py
@@ -1 +1 @@
-__version__ = '0.1.1'
+__version__ = '0.1.2'
diff --git a/mysignal/phasefreq.py b/mysignal/phasefreq.py
index b9f8869..6e95106 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, nyquist=False):
     """
     Filtre un signal pour extraire ses composantes fréquentielles dominantes.
 
@@ -68,16 +68,17 @@ def filter_signal_by_modes(time, signal, num_modes=1, bandwidth_factor=0.1):
         lowcut = freq - bandwidth
         highcut = freq + bandwidth
 
-        # Éviter les fréquences négatives ou supérieures à la fréquence de Nyquist
-        nyq = 0.5 * fs
-        if lowcut <= 0:
-            lowcut = 0.01
-        if highcut >= nyq:
-            highcut = nyq - 0.01
-
-        # Créer le filtre Butterworth
-        low = lowcut / nyq
-        high = highcut / nyq
+        if nyquist:
+            # Éviter les fréquences négatives ou supérieures à la fréquence de Nyquist
+            nyq = 0.5 * fs
+            if lowcut <= 0:
+                lowcut = 0.01
+            if highcut >= nyq:
+                highcut = nyq - 0.01
+    
+            # Créer le filtre Butterworth
+            lowcut = lowcut / nyq
+            highcut = highcut / nyq
         b, a = butter(4, [low, high], btype='band')
 
         # Appliquer le filtre (filtfilt pour éviter le déphasage)