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@@ -4,6 +4,9 @@ from ChildProject.projects import ChildProject
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from ChildProject.annotations import AnnotationManager
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from ChildProject.metrics import segments_to_grid, conf_matrix, segments_to_annotation
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from pathlib import Path
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+import seaborn as sns
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+import matplotlib.pyplot as plt
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+import numpy as np
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def compare_vandam(set1: str, set2: str) :
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@@ -54,9 +57,41 @@ def compare_vandam(set1: str, set2: str) :
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#generates segments
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set1_segm = segments_to_grid(segments[segments['set'] == set1], 0, segments['segment_offset'].max(), 100, 'speaker_type', speakers)
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set2_segm = segments_to_grid(segments[segments['set'] == set2], 0, segments['segment_offset'].max(), 100, 'speaker_type', speakers)
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- matrix_df = pd.DataFrame(conf_matrix(set1_segm, set2_segm))
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- matrix_df.to_csv("{0}/{1}-{2}-confusion-matrix.csv".format(dirName, set1.replace("/",""), set2.replace("/","")), mode = "w", index=False)
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+
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+ speakers.extend(['none'])
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+
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+ confusion_counts = conf_matrix(set1_segm, set2_segm)
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+
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+ plt.rcParams.update({'font.size': 12})
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+ plt.rc('xtick', labelsize = 10)
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+ plt.rc('ytick', labelsize = 10)
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+
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+ fig, axes = plt.subplots(nrows = 1, ncols = 2, figsize=(6.4*2, 4.8))
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+
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+ confusion = confusion_counts/np.sum(set1_segm, axis = 0)[:,None]
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+
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+ sns.heatmap(confusion, annot = True, fmt = '.2f', ax = axes[0], cmap = 'Reds')
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+ axes[0].set_xlabel(set2)
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+ axes[0].set_ylabel(set1)
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+ axes[0].xaxis.set_ticklabels(speakers)
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+ axes[0].yaxis.set_ticklabels(speakers)
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+
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+ confusion_counts = np.transpose(confusion_counts)
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+ confusion = confusion_counts/np.sum(set2_segm, axis = 0)[:,None]
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+
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+ sns.heatmap(confusion, annot = True, fmt = '.2f', ax = axes[1], cmap = 'Reds')
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+ axes[1].set_xlabel(set1)
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+ axes[1].set_ylabel(set2)
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+ axes[1].xaxis.set_ticklabels(speakers)
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+ axes[1].yaxis.set_ticklabels(speakers)
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+
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+ plt.savefig("{0}/{1}-{2}-confusion-matrix.jpg".format(dirName, set1.replace("/",""), set2.replace("/",""), bbox_inches = 'tight'))
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+
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+
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+ #matrix_df = pd.DataFrame(conf_matrix(set1_segm, set2_segm))
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+ # matrix_df.to_csv("{0}/{1}-{2}-confusion-matrix.csv".format(dirName, set1.replace("/",""), set2.replace("/","")), mode = "w", index=False)
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print("Confusion matrix saved for {0} and {1}!".format(set1, set2))
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compare_vandam('eaf', 'cha')
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-compare_vandam('eaf', 'cha/aligned')
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+compare_vandam('eaf', 'cha/aligned')
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+compare_vandam('cha', 'cha/aligned')
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