-
Notifications
You must be signed in to change notification settings - Fork 0
/
Copy pathplots.py
191 lines (138 loc) · 5 KB
/
plots.py
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
import inspect
import os
import shutil
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import argparse
import logging
DEFAULT_LOG_LEVEL = logging.INFO
TIME_FORMAT = '%Y-%m-%d, %H:%M:%S'
def plot_mean(labels, mean, std, path_plots, name, ylabel, color, max_y, t, f, zero):
plt.figure(figsize=(20,10))
if zero == True:
plt.ylim([0, max_y*1.5])
yticks = np.arange(0, max_y*1.5, max_y*0.2)
print(yticks)
else:
plt.ylim([-(max_y*0.1), max_y*1.5])
yticksp = np.arange(0, max_y*1.5, max_y*0.2)
print(yticksp)
yticksn = np.flip(np.arange(0, -max_y*0.1, -max_y*0.2))
print(yticksn)
yticks = np.concatenate([yticksn, yticksp])
print(yticks)
# yticks = np.append(yticks, max_y)
m = plt.bar(x=labels, width = 0.55, height=mean, color=color)
# print(m.errorbar.set_label(alpha=0.3))
plt.errorbar(labels, mean, yerr=std, ls='', lw=1, capsize=5, color='red', alpha=0.5, capthick=1)
l = []
for e in std:
l.append('± '+f'{e:.{f}f}')
# print(l)
# plt.bar_label(m, labels=['± '+(':.'+str(t)+'f'.format(e)) for e in std], label_type='edge', fontsize=16, padding=2)
plt.bar_label(m, labels=l, label_type='edge', fontsize=25, padding=50, color='red', alpha=0.7)
if zero == True:
plt.bar_label(m, padding=20, fmt='%.'+str(t)+'f', fontsize=25, label_type='center', color='k')
else:
plt.bar_label(m, padding=-2, fmt='%.'+str(t)+'f', fontsize=25, label_type='center', color='k')
plt.tick_params(labelsize=30)
plt.ylabel(ylabel, fontsize=30)
# plt.xlabel(fontsize=30)
plt.yticks(yticks, fontsize=27)
plt.savefig(path_plots+'/'+name+'.svg', format='svg')
plt.savefig(path_plots+'/png/'+name+'.png', format='png')
# plt.show()
plt.cla()
plt.clf()
plt.close('all')
def main():
parser = argparse.ArgumentParser(description='plots')
parser.add_argument("--save", help='name plot', required=True, type=str)
# parser.add_argument("--exp", help='experiments', required=True, type=str)
parser.add_argument("--paths", nargs='+', help='list of paths', type=str)
parser.add_argument("--col", nargs='+', help='list columns of experiments', type=str)
# parser.add_argument('--zero', help='graph origin', required=True, action='store_true')
help_msg = "Logging level (INFO=%d DEBUG=%d)" % (logging.INFO, logging.DEBUG)
parser.add_argument("--log", "-l", help=help_msg, default=DEFAULT_LOG_LEVEL, type=int)
args = parser.parse_args()
if args.log == logging.DEBUG:
logging.basicConfig(format='%(asctime)s.%(msecs)03d: %(levelname)s {%(module)s} [%(funcName)s] %(message)s', datefmt=TIME_FORMAT, level=args.log)
else:
logging.basicConfig(format='%(asctime)s.%(msecs)03d: %(message)s', datefmt=TIME_FORMAT, level=args.log)
print(args)
filename = inspect.getframeinfo(inspect.currentframe()).filename
mypath = os.path.dirname(os.path.abspath(filename))
# path = mypath+'/mean/'+args.exp+'/'
path = mypath+'/mean/'
df_mse = pd.DataFrame()
df_times = pd.DataFrame()
for p in args.paths:
mse = pd.read_csv(path+'mse/'+p+'mean_mse_executions.csv', sep=' ', header=None)
times = pd.read_csv(path+'times/'+p+'mean_times_executions.csv', sep=' ', header=None)
# print(mse.to_numpy())
df_mse = pd.concat([df_mse, mse])
# df_mse.append(mse.to_numpy())
df_times = pd.concat([df_times, times])
print(df_mse)
print(df_times)
# print(df_mse[2].to_numpy()[0])
print('-------------')
# print(df_mse[2].tail(1))
# # print(df_mse.columns)
print(df_mse[2])
print(df_times[2])
# exit()
max_y_mse = np.max(df_mse[2].to_numpy())
max_y_times = np.max(df_times[2].to_numpy())
print(max_y_mse, max_y_times)
# path_plot_mse = mypath + '/plots/mse/'+args.exp+'/'
path_plot_mse = mypath + '/plots/mse/'
if not os.path.exists(path_plot_mse):
os.makedirs(path_plot_mse)
# else:
# shutil.rmtree(mypath + '/plots/mse')
# os.makedirs(path_plot_mse)
# path_plot_mse_png = mypath + '/plots/mse/'+args.exp+'/png'
path_plot_mse_png = mypath + '/plots/mse/png'
if not os.path.exists(path_plot_mse_png):
os.makedirs(path_plot_mse_png)
plot_mean(args.col,
df_mse[0].to_numpy(),
df_mse[1].to_numpy(),
path_plot_mse,
args.save+'-mse',
'Erro quadrático médio',
# df_mse[2].to_numpy()[0],
'cornflowerblue',
max_y_mse,
6,
6,
zero=False
)
# path_plot_times = mypath + '/plots/times/'+args.exp+'/'
path_plot_times = mypath + '/plots/times/'
if not os.path.exists(path_plot_times):
os.makedirs(path_plot_times)
# else:
# shutil.rmtree(mypath + '/plots/times')
# os.makedirs(path_plot_times)
# path_plot_times_png = mypath + '/plots/times/'+args.exp+'/png'
path_plot_times_png = mypath + '/plots/times/png'
if not os.path.exists(path_plot_times_png):
os.makedirs(path_plot_times_png)
plot_mean(args.col,
df_times[0].to_numpy(),
df_times[1].to_numpy(),
path_plot_times,
args.save+'-times',
'Segundos',
# df_times[2].to_numpy()[0],
'tab:green',
max_y_times,
2,
2,
zero=True
)
if __name__ == '__main__':
main()