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- #!/usr/bin/env python3
- from ChildProject.projects import ChildProject
- from ChildProject.annotations import AnnotationManager
- from ChildProject.metrics import segments_to_grid, conf_matrix
- import numpy as np
- import pandas as pd
- from sklearn.metrics import confusion_matrix
- from sklearn.preprocessing import normalize
- import seaborn as sns
- import matplotlib
- import matplotlib.pyplot as plt
- matplotlib.use("pgf")
- matplotlib.rcParams.update({
- "pgf.texsystem": "pdflatex",
- 'font.family': 'serif',
- "font.serif" : "Times New Roman",
- 'text.usetex': True,
- 'pgf.rcfonts': False,
- })
- import sys
- speakers = ['CHI', 'OCH', 'FEM', 'MAL']
- path = sys.argv[1]
- if __name__ == '__main__':
- project = ChildProject(path)
- am = AnnotationManager(project)
- am.read()
- intersection = AnnotationManager.intersection(am.annotations, ['vtc', 'eaf'])
- segments = am.get_collapsed_segments(intersection)
- segments = segments[segments['speaker_type'].isin(speakers)]
- vtc = segments_to_grid(segments[segments['set'] == 'vtc'], 0, segments['segment_offset'].max(), 100, 'speaker_type', speakers)
- eaf = segments_to_grid(segments[segments['set'] == 'eaf'], 0, segments['segment_offset'].max(), 100, 'speaker_type', speakers)
- speakers.extend(['none'])
- confusion_counts = conf_matrix(vtc, eaf)
- plt.rcParams.update({'font.size': 12})
- plt.rc('xtick', labelsize = 10)
- plt.rc('ytick', labelsize = 10)
- fig, axes = plt.subplots(nrows = 1, ncols = 2, figsize=(6.4*2, 4.8))
- confusion = confusion_counts/np.sum(vtc, axis = 0)[:,None]
- sns.heatmap(confusion, annot = True, fmt = '.2f', ax = axes[0], cmap = 'Reds')
- axes[0].set_xlabel('eaf')
- axes[0].set_ylabel('vtc')
- axes[0].xaxis.set_ticklabels(speakers)
- axes[0].yaxis.set_ticklabels(speakers)
- confusion_counts = np.transpose(confusion_counts)
- confusion = confusion_counts/np.sum(eaf, axis = 0)[:,None]
- sns.heatmap(confusion, annot = True, fmt = '.2f', ax = axes[1], cmap = 'Reds')
- axes[1].set_xlabel('vtc')
- axes[1].set_ylabel('eaf')
- axes[1].xaxis.set_ticklabels(speakers)
- axes[1].yaxis.set_ticklabels(speakers)
- plt.savefig('Fig7.pdf', bbox_inches = 'tight')
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