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import os
import sys
import numpy as np
import argparse
import h5py
import math
import time
import logging
import pickle
import matplotlib.pyplot as plt
def load_sdrs(workspace, task_name, filename, config, gpus):
stat_path = os.path.join(
workspace,
"statistics",
task_name,
filename,
"config={},gpus={}".format(config, gpus),
"statistics.pkl",
)
stat_dict = pickle.load(open(stat_path, 'rb'))
median_sdrs = [e['sdr'] for e in stat_dict['test']]
return median_sdrs
def plot_statistics(args):
# arguments & parameters
workspace = args.workspace
select = args.select
task_name = "vctk-musdb18"
filename = "train"
# paths
fig_path = os.path.join('results', task_name, "sdr_{}.pdf".format(select))
os.makedirs(os.path.dirname(fig_path), exist_ok=True)
linewidth = 1
lines = []
fig, ax = plt.subplots(1, 1, figsize=(8, 6))
ylim = 30
expand = 1
if select == '1a':
sdrs = load_sdrs(workspace, task_name, filename, config='unet', gpus=1)
(line,) = ax.plot(sdrs, label='UNet,l1_wav', linewidth=linewidth)
lines.append(line)
else:
raise Exception('Error!')
eval_every_iterations = 10000
total_ticks = 50
ticks_freq = 10
ax.set_ylim(0, ylim)
ax.set_xlim(0, total_ticks)
ax.xaxis.set_ticks(np.arange(0, total_ticks + 1, ticks_freq))
ax.xaxis.set_ticklabels(
np.arange(
0,
total_ticks * eval_every_iterations + 1,
ticks_freq * eval_every_iterations,
)
)
ax.yaxis.set_ticks(np.arange(ylim + 1))
ax.yaxis.set_ticklabels(np.arange(ylim + 1))
ax.grid(color='b', linestyle='solid', linewidth=0.3)
plt.legend(handles=lines, loc=4)
plt.savefig(fig_path)
print('Save figure to {}'.format(fig_path))
if __name__ == '__main__':
parser = argparse.ArgumentParser()
parser.add_argument('--workspace', type=str, required=True)
parser.add_argument('--select', type=str, required=True)
args = parser.parse_args()
plot_statistics(args)
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