103 lines
3.1 KiB
Python
103 lines
3.1 KiB
Python
# Copyright (c) 2021 Binbin Zhang(binbzha@qq.com)
|
||
# Menglong Xu
|
||
#
|
||
# Licensed under the Apache License, Version 2.0 (the "License");
|
||
# you may not use this file except in compliance with the License.
|
||
# You may obtain a copy of the License at
|
||
#
|
||
# http://www.apache.org/licenses/LICENSE-2.0
|
||
#
|
||
# Unless required by applicable law or agreed to in writing, software
|
||
# distributed under the License is distributed on an "AS IS" BASIS,
|
||
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||
# See the License for the specific language governing permissions and
|
||
# limitations under the License.
|
||
|
||
import argparse
|
||
import os
|
||
import numpy as np
|
||
import matplotlib.pyplot as plt
|
||
|
||
|
||
def load_stats_file(stats_file):
|
||
values = []
|
||
with open(stats_file, 'r', encoding='utf8') as fin:
|
||
for line in fin:
|
||
arr = line.strip().split()
|
||
threshold, fa_per_hour, frr = arr
|
||
values.append([float(fa_per_hour), float(frr) * 100])
|
||
values.reverse()
|
||
return np.array(values)
|
||
|
||
|
||
def plot_det_curve(
|
||
keywords,
|
||
stats_dir,
|
||
figure_file,
|
||
xlim,
|
||
x_step,
|
||
ylim,
|
||
y_step):
|
||
plt.figure(dpi=200)
|
||
plt.rcParams['xtick.direction'] = 'in'
|
||
plt.rcParams['ytick.direction'] = 'in'
|
||
plt.rcParams['font.size'] = 12
|
||
|
||
for index, keyword in enumerate(keywords):
|
||
stats_file = os.path.join(stats_dir, 'stats.' + str(index) + '.txt')
|
||
values = load_stats_file(stats_file)
|
||
plt.plot(values[:, 0], values[:, 1], label=keyword)
|
||
|
||
plt.xlim([0, xlim])
|
||
plt.ylim([0, ylim])
|
||
plt.xticks(range(0, xlim + x_step, x_step))
|
||
plt.yticks(range(0, ylim + y_step, y_step))
|
||
plt.xlabel('False Alarm Per Hour')
|
||
plt.ylabel('False Rejection Rate (\\%)')
|
||
plt.grid(linestyle='--')
|
||
plt.legend(loc='best', fontsize=16)
|
||
plt.savefig(figure_file)
|
||
|
||
|
||
if __name__ == '__main__':
|
||
parser = argparse.ArgumentParser(description='plot det curve')
|
||
parser.add_argument(
|
||
'--keywords_dict',
|
||
required=True,
|
||
help='path to the dictionary of keywords')
|
||
parser.add_argument('--stats_dir', required=True, help='dir of stats files')
|
||
parser.add_argument(
|
||
'--figure_file',
|
||
required=True,
|
||
help='path to save det curve')
|
||
parser.add_argument(
|
||
'--xlim',
|
||
type=int,
|
||
default=5,
|
||
help='xlim:range of x-axis, x is false alarm per hour')
|
||
parser.add_argument('--x_step', type=int, default=1, help='step on x-axis')
|
||
parser.add_argument(
|
||
'--ylim',
|
||
type=int,
|
||
default=35,
|
||
help='ylim:range of y-axis, y is false rejection rate')
|
||
parser.add_argument('--y_step', type=int, default=5, help='step on y-axis')
|
||
|
||
args = parser.parse_args()
|
||
|
||
keywords = []
|
||
with open(args.keywords_dict, 'r', encoding='utf8') as fin:
|
||
for line in fin:
|
||
keyword, index = line.strip().split()
|
||
if int(index) > -1:
|
||
keywords.append(keyword)
|
||
|
||
plot_det_curve(
|
||
keywords,
|
||
args.stats_dir,
|
||
args.figure_file,
|
||
args.xlim,
|
||
args.x_step,
|
||
args.ylim,
|
||
args.y_step)
|