-
Notifications
You must be signed in to change notification settings - Fork 0
/
result_graphics_accuracy.py
78 lines (66 loc) · 3.1 KB
/
result_graphics_accuracy.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
#!/usr/bin/env python3.7
import matplotlib.pyplot as plt
import numpy as np
if __name__ == "__main__":
n_clusters = 5
bwa_aligner = []
bwa_all = []
for values in {"c7":[1, 883, 230, 574, 2291], "c8":[1, 2546, 87, 141, 652], "c9":[1, 472, 132, 143, 255], "c10":[1, 443, 82, 88, 808], "c12":[1, 945, 252, 370, 1049]}.values():
bwa_aligner.append(round(sum(values[:-1]) / 60.0, 2))
bwa_all.append(round(sum(values) / 60.0, 2))
sbg_aligner = []
sbg_all = []
for values in {"c7":[351, 916, 2327], "c8":[468, 289, 616], "c9":[280, 145, 249], "c10":[152, 115, 794], "c12":[110, 193, 1024]}.values():
sbg_aligner.append(round(sum(values[:-1]) / 60.0, 2))
sbg_all.append(round(sum(values) / 60.0, 2))
vg_aligner = []
vg_all = []
for values in {"c7":[1, 43, 19035, 292, 2406], "c8":[1, 43, 6801, 117, 695], "c9":[1, 43, 2800, 72, 276], "c10":[1, 43, 5339, 85, 916], "c12":[1, 43, 10548, 184, 1056]}.values():
vg_aligner.append(round(sum(values[:-1]) / 60.0, 2))
vg_all.append(round(sum(values) / 60.0, 2))
index = np.arange(1,n_clusters+1)
bar_width = 0.3
opacity = 0.8
f, ((ax1, ax2)) = plt.subplots(1, 2)
ax1.bar(index - bar_width, sbg_aligner, bar_width, alpha=opacity, color='b', label='SBG')
ax1.bar(index, bwa_aligner, bar_width, alpha=opacity, color='g', label='bwa')
ax1.bar(index + bar_width, vg_aligner, bar_width, alpha=opacity, color='y', label='VG')
ax1.title.set_text("Aligner")
ax1.set_xlabel('cluster ID')
ax1.set_ylabel('run time in minutes')
ax1.grid(which='major', linestyle='-', linewidth='0.05', color = "black")
ax1.grid(which='minor', linestyle='--', linewidth='0.01', color = "black")
ax1.grid(True)
ax1.set_xticks(np.arange(1,6,1))
ax1.set_ylim([0, 400])
ax1.legend()
ax2.bar(index - bar_width, sbg_all, bar_width, alpha=opacity, color='b', label='SBG')
ax2.bar(index, bwa_all, bar_width, alpha=opacity, color='g', label='bwa')
ax2.bar(index + bar_width, vg_all, bar_width, alpha=opacity, color='y', label='VG')
ax2.title.set_text("Aligner and Estimation")
ax2.set_xlabel('cluster ID')
ax2.set_ylabel('run time in minutes')
ax2.grid(which='major', linestyle='-', linewidth='0.05', color = "black")
ax2.grid(which='minor', linestyle='--', linewidth='0.01', color = "black")
ax2.grid(True)
ax2.set_xticks(np.arange(1,6,1))
ax2.set_ylim([0, 400])
ax2.legend()
# sbg_accuracy = [100, 100, 100, 100, 100]
# bwa_accuracy = [100, 100, 100, 100, 100]
# vg_accuracy = [100, 100, 100, 100, 100]
# ax3.bar(index, sbg_accuracy, bar_width, alpha=opacity, color='b', label='bwa')
# ax3.bar(index + bar_width, bwa_accuracy, bar_width, alpha=opacity, color='g', label='SBG')
# ax3.bar(index + 2 * bar_width, vg_accuracy, bar_width, alpha=opacity, color='y', label='VG')
# ax3.title.set_text("Estimation")
# ax3.set_xlabel('cluster ID')
# ax3.set_ylabel('accuracy (100%)')
# ax3.grid(which='major', linestyle='-', linewidth='0.05', color = "black")
# ax3.grid(which='minor', linestyle='--', linewidth='0.01', color = "black")
# ax3.grid(True)
# ax3.set_xticks(np.arange(1,6,1))
# ax3.set_ylim([0, 100])
# ax3.legend()
plt.tight_layout()
plt.show()
# plt.savefig('common_labels.png', dpi=300)