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Diffstat (limited to 'dnn/torch/osce/stndrd/evaluation/make_boxplots_moctest.py')
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diff --git a/dnn/torch/osce/stndrd/evaluation/make_boxplots_moctest.py b/dnn/torch/osce/stndrd/evaluation/make_boxplots_moctest.py new file mode 100644 index 00000000..ca65aba9 --- /dev/null +++ b/dnn/torch/osce/stndrd/evaluation/make_boxplots_moctest.py @@ -0,0 +1,109 @@ +""" +/* Copyright (c) 2023 Amazon + Written by Jan Buethe */ +/* + Redistribution and use in source and binary forms, with or without + modification, are permitted provided that the following conditions + are met: + + - Redistributions of source code must retain the above copyright + notice, this list of conditions and the following disclaimer. + + - Redistributions in binary form must reproduce the above copyright + notice, this list of conditions and the following disclaimer in the + documentation and/or other materials provided with the distribution. + + THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS + ``AS IS'' AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT + LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR + A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER + OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, + EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, + PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR + PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF + LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING + NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS + SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. +*/ +""" + +import os +import argparse + +import numpy as np +import matplotlib.pyplot as plt +from prettytable import PrettyTable +from matplotlib.patches import Patch + +parser = argparse.ArgumentParser() +parser.add_argument('folder', type=str, help='path to folder with pre-calculated metrics') +parser.add_argument('--metric', choices=['pesq', 'moc', 'warpq', 'nomad', 'laceloss', 'all'], default='all', help='default: all') +parser.add_argument('--output', type=str, default=None, help='alternative output folder, default: folder') + +def load_data(folder): + data = dict() + + if os.path.isfile(os.path.join(folder, 'results_moc.npy')): + data['moc'] = np.load(os.path.join(folder, 'results_moc.npy'), allow_pickle=True).item() + + if os.path.isfile(os.path.join(folder, 'results_pesq.npy')): + data['pesq'] = np.load(os.path.join(folder, 'results_pesq.npy'), allow_pickle=True).item() + + if os.path.isfile(os.path.join(folder, 'results_warpq.npy')): + data['warpq'] = np.load(os.path.join(folder, 'results_warpq.npy'), allow_pickle=True).item() + + if os.path.isfile(os.path.join(folder, 'results_nomad.npy')): + data['nomad'] = np.load(os.path.join(folder, 'results_nomad.npy'), allow_pickle=True).item() + + if os.path.isfile(os.path.join(folder, 'results_laceloss.npy')): + data['laceloss'] = np.load(os.path.join(folder, 'results_laceloss.npy'), allow_pickle=True).item() + + return data + +def plot_data(filename, data, title=None): + compare_dict = dict() + for br in data.keys(): + compare_dict[f'Opus {br/1000:.1f} kb/s'] = data[br][:, 0] + compare_dict[f'LACE (MOC only) {br/1000:.1f} kb/s'] = data[br][:, 1] + compare_dict[f'LACE (MOC + TD) {br/1000:.1f} kb/s'] = data[br][:, 2] + + plt.rcParams.update({ + "text.usetex": True, + "font.family": "Helvetica", + "font.size": 32 + }) + colors = ['pink', 'lightblue', 'lightgreen'] + legend_elements = [Patch(facecolor=colors[0], label='Opus SILK'), + Patch(facecolor=colors[1], label='MOC loss only'), + Patch(facecolor=colors[2], label='MOC + TD loss')] + + fig, ax = plt.subplots() + fig.set_size_inches(40, 20) + bplot = ax.boxplot(compare_dict.values(), showfliers=False, notch=True, patch_artist=True) + + for i, patch in enumerate(bplot['boxes']): + patch.set_facecolor(colors[i%3]) + + ax.set_xticklabels(compare_dict.keys(), rotation=290) + + if title is not None: + ax.set_title(title) + + ax.legend(handles=legend_elements) + + fig.savefig(filename, bbox_inches='tight') + +if __name__ == "__main__": + args = parser.parse_args() + data = load_data(args.folder) + + + metrics = list(data.keys()) if args.metric == 'all' else [args.metric] + folder = args.folder if args.output is None else args.output + os.makedirs(folder, exist_ok=True) + + for metric in metrics: + print(f"Plotting data for {metric} metric...") + plot_data(os.path.join(folder, f"boxplot_{metric}.png"), data[metric], title=metric.upper()) + + print("Done.")
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