forked from moreo/QuaPy
47 lines
1.5 KiB
Python
47 lines
1.5 KiB
Python
from pathlib import Path
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import matplotlib.pyplot as plt
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from os import makedirs
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from os.path import join
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from ClassifierAccuracy.util.commons import get_method_names, open_results
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def plot_diagonal(basedir, cls_name, measure_name, dataset_name='*'):
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methods = get_method_names()
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results = open_results(basedir, cls_name, measure_name, dataset_name=dataset_name, method_name=methods)
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methods, xs, ys = [], [], []
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for method_name in results.keys():
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methods.append(method_name)
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xs.append(results[method_name]['true_acc'])
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ys.append(results[method_name]['estim_acc'])
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plotsubdir = 'all' if dataset_name=='*' else dataset_name
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save_path = join('plots', basedir, measure_name, plotsubdir, 'diagonal.png')
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_plot_diagonal(methods, xs, ys, save_path, measure_name)
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def _plot_diagonal(methods_names, true_xs, estim_ys, save_path, measure_name, title=None):
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makedirs(Path(save_path).parent, exist_ok=True)
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# Create scatter plot
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plt.figure(figsize=(10, 10))
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plt.xlim(0, 1)
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plt.ylim(0, 1)
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plt.plot([0, 1], [0, 1], color='black', linestyle='--')
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for (method_name, xs, ys) in zip(methods_names, true_xs, estim_ys):
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plt.scatter(xs, ys, label=f'{method_name}', alpha=0.5, linewidths=0)
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plt.legend()
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# Add labels and title
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if title is not None:
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plt.title(title)
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plt.xlabel(f'True {measure_name}')
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plt.ylabel(f'Estimated {measure_name}')
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# Display the plot
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plt.savefig(save_path)
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plt.cla()
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