diff --git a/mysignal/__init__.py b/mysignal/__init__.py
index a96d65a..641e1a8 100644
--- a/mysignal/__init__.py
+++ b/mysignal/__init__.py
@@ -1 +1 @@
-__version__ = '0.1.25'
+__version__ = '0.1.26'
diff --git a/mysignal/phasefreq.py b/mysignal/phasefreq.py
index 0a6943a..238fc2b 100644
--- a/mysignal/phasefreq.py
+++ b/mysignal/phasefreq.py
@@ -254,6 +254,7 @@ def analyze_signal_Hilbert(time, e_signal, s_signal, freq_rtol=0.01):
 
     return res
 
+
 def analyze_signal_sinfit(time, e_signal, s_signal, freq_rtol=0.01):
     """
     Analyzes the dominant frequencies, phase shift, time shift, and periods between two signals e_signal(t) and s_signal(t) from a DataFrame.
@@ -360,7 +361,6 @@ def analyze_signal_sinfit(time, e_signal, s_signal, freq_rtol=0.01):
     return res
 
 
-
 def analyze_signal_cross_correlation(time, e_signal, s_signal, freq_rtol=0.01):
     """
     Analyzes signals using cross-correlation method for phase shift calculation (single mode only).
@@ -468,7 +468,6 @@ def analyze_signal_cross_correlation(time, e_signal, s_signal, freq_rtol=0.01):
     return res
 
 
-
 def analyze_signal_wavelet(time, e_signal, s_signal, freq_rtol=0.01):
     """
     Analyzes signals using wavelet transform for phase shift calculation (single mode only).
@@ -579,13 +578,29 @@ def analyze_signal_wavelet(time, e_signal, s_signal, freq_rtol=0.01):
     return res
 
 
-def plot_phases(e_time, e_filtered, e_frequencies, s_filtered, n_modes, callback=analyze_signal_wavelet, output=None):
+def get_phases(e_time, e_filtered, e_frequencies, s_filtered, n_modes, callback=analyze_signal_wavelet):
+    """
+    """
+    res = []
 
+    for mod in range(n_modes):
+        output = callback(e_time, e_filtered[mod], s_filtered[mod], freq_rtol=0.3)
+        res.append({
+                    'mode': mod,
+                    'freq': output['freq_e'],
+                    'phase': output['phase'],
+                    'delay': output['delay']
+            })
+    return pd.DataFrame(res)
+
+
+def plot_phases(e_time, e_filtered, e_frequencies, s_filtered, n_modes, callback=analyze_signal_wavelet, output=None):
+    """
+    """
 
     fig, ax = plt.subplots(nrows=n_modes, ncols=2, figsize=(12, 2 * n_modes), gridspec_kw={'width_ratios': [3, 1]})
 
     for mod in range(n_modes):
-
         res = callback(e_time, e_filtered[mod], s_filtered[mod], freq_rtol=0.3)
 
         ax[mod, 0].set_title(f'Freq: {res['freq_e']:.3f}, Phase: {res['phase']:.3f}, Delay: {res['delay']:.3f}' )