Current plot to common plot

as_seg/model/current_plot.py → as_seg/model/common_plot.py

@@ -5,46 +5,15 @@ Created on Fri Feb 22 16:29:17 2019
 @author: amarmore
 
 Defining common plotting functions.
-
-NB: This module's name actually comes from an incorrect translation
-from the french "courant" into "current", instead of "common".
-Please excuse me for this translation.
 """
 
 import numpy as np
 import matplotlib.pyplot as plt
 import matplotlib.cm as cm
 
-# %% Plotting utils
-def plot_me_this_spectrogram(spec, title = "Spectrogram", x_axis = "x_axis", y_axis = "y_axis", invert_y_axis = True, cmap = cm.Greys, figsize = None, norm = None, vmin = None, vmax = None):
-    """
-    Plots a spectrogram in a colormesh.
-    """
-    if figsize != None:
-        plt.figure(figsize=figsize)
-    elif spec.shape[0] == spec.shape[1]:
-        plt.figure(figsize=(7,7))
-    padded_spec = spec #pad_factor(spec)
-    plt.pcolormesh(np.arange(padded_spec.shape[1]), np.arange(padded_spec.shape[0]), padded_spec, cmap=cmap, norm = norm, vmin = vmin, vmax = vmax, shading='auto')
-    plt.title(title)
-    plt.xlabel(x_axis)
-    plt.ylabel(y_axis)
-    if invert_y_axis:
-        plt.gca().invert_yaxis()
-    plt.show()
-    
-def pad_factor(factor):
-    """
-    Pads the factor with zeroes on both dimension.
-    This is made because colormesh plots values as intervals (post and intervals problem),
-    and so discards the last value.
-    """
-    padded = np.zeros((factor.shape[0] + 1, factor.shape[1] + 1))
-    for i in range(factor.shape[0]):
-        for j in range(factor.shape[1]):
-            padded[i,j] = factor[i,j]
-    return np.array(padded)
+from base_audio.common_plot import *
 
+# %% Plotting utils
 def plot_lenghts_hist(lengths):
     """
     Plots the lengths of segments in an histogram
@@ -94,54 +63,6 @@ def plot_measure_with_annotations_and_prediction(measure, annotations, frontiers
             plt.plot([x, x], [0,np.amax(measure)], '-', linewidth=1, color = "orange")
     plt.show()
     
-def plot_spec_with_annotations(factor, annotations, color = "yellow", title = None):
-    """
-    Plots a spectrogram with the segmentation annotation.
-    """
-    if factor.shape[0] == factor.shape[1]:
-        plt.figure(figsize=(7,7))
-    plt.title(title)
-    padded_fac = pad_factor(factor)
-    plt.pcolormesh(np.arange(padded_fac.shape[1]), np.arange(padded_fac.shape[0]), padded_fac, cmap=cm.Greys)
-    plt.gca().invert_yaxis()
-    for x in annotations:
-        plt.plot([x,x], [0,len(factor)], '-', linewidth=1, color = color)
-    plt.show()
-    
-def plot_spec_with_annotations_abs_ord(factor, annotations, color = "green", title = None, cmap = cm.gray):
-    """
-    Plots a spectrogram with the segmentation annotation in both x and y axes.
-    """
-    if factor.shape[0] == factor.shape[1]:
-        plt.figure(figsize=(7,7))
-    plt.title(title)
-    padded_fac = pad_factor(factor)
-    plt.pcolormesh(np.arange(padded_fac.shape[1]), np.arange(padded_fac.shape[0]), padded_fac, cmap=cmap)
-    plt.gca().invert_yaxis()
-    for x in annotations:
-        plt.plot([x,x], [0,len(factor)], '-', linewidth=1, color = color)
-        plt.plot([0,len(factor)], [x,x], '-', linewidth=1, color = color)
-    plt.show()
-
-def plot_spec_with_annotations_and_prediction(factor, annotations, predicted_ends, title = "Title"):
-    """
-    Plots a spectrogram with the segmentation annotation and the estimated segmentation.
-    """
-    if factor.shape[0] == factor.shape[1]:
-        plt.figure(figsize=(7,7))
-    plt.title(title)
-    padded_fac = pad_factor(factor)
-    plt.pcolormesh(np.arange(padded_fac.shape[1]), np.arange(padded_fac.shape[0]), padded_fac, cmap=cm.Greys)
-    plt.gca().invert_yaxis()
-    for x in annotations:
-        plt.plot([x,x], [0,len(factor)], '-', linewidth=1, color = "#8080FF")
-    for x in predicted_ends:
-        if x in annotations:
-            plt.plot([x,x], [0,len(factor)], '-', linewidth=1, color = "green")#"#17becf")
-        else:
-            plt.plot([x,x], [0,len(factor)], '-', linewidth=1, color = "orange")
-    plt.show()
-    
 def plot_segments_with_annotations(seg, annot):
     """
     Plots the estimated labelling of segments next to with the frontiers in the annotation.