-
Notifications
You must be signed in to change notification settings - Fork 4
/
plot.py
55 lines (41 loc) · 1.04 KB
/
plot.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
import matplotlib.pyplot as plt
import numpy as np
import os
import sh
import classify_predict
import classify_train
if __name__ == '__main__':
modi_file = "feature/0324_modi.txt"
X, Y = classify_train.load_data(modi_file)
result_file = "result/tran.txt"
classify_predict.run(modi_file, result_file)
Y_p = np.loadtxt(result_file)
plt.figure()
plt.plot(-0.2)
plt.plot(1.2)
plt.plot(Y,'b')
plt.plot(Y_p,'r')
plt.show()
# mfcc_dir = "feature/0324"
# mfcc_feat_list = os.listdir(mfcc_dir)
# modi_feat = []
# i = 0
# for file_name in mfcc_feat_list:
# if i > 5: break
# i+=1
# print mfcc_dir + "/" + file_name
# d = np.loadtxt(mfcc_dir + "/" + file_name)
# if len(modi_feat) == 0:
# modi_feat = d
# else:
# modi_feat = np.concatenate((modi_feat,d))
# modi_feat = np.loadtxt("feature/0324_modi.txt")[0:2700,:]
# print np.shape(modi_feat)
# plt.figure()
# plt.subplot(3,1,1)
# plt.plot(modi_feat[:,1])
# plt.subplot(3,1,2)
# plt.plot(modi_feat[:,2])
# plt.subplot(3,1,3)
# plt.plot(modi_feat[:,3])
# plt.show()