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draw_graph.py
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draw_graph.py
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import numpy as np
import matplotlib.mlab as mlab
import matplotlib.pyplot as plt
def jsjiami():
labels=['Parse and \nRegeneration','Inter-procedure Deob-\nfuscation Detection','Inter-procedure Deob-\nfuscation Resolution','dictionary replacement']
X=[0.075384906, 0.168265702, 0.81832427, 0.224871286]
fig = plt.figure()
plt.pie(X,labels=labels,autopct='%1.2f%%') #画饼图(数据,数据对应的标签,百分数保留两位小数点)
plt.title("Pie chart")
plt.show()
plt.savefig("time_jsjismi.jpg")
return
def job():
labels=['Parse and Regeneration','Inter-procedure Deobfuscation Detection','Inter-procedure Deobfuscation Resolution','dictionary replacement','Control-Flow Flattening','Statement-level Deobfuscation']
X=[0.075049478, 0.090475193, 0.150990089, 0.074776232, 0.129486904, 0.075904759]
fig = plt.figure()
plt.pie(X,labels=labels,autopct='%1.2f%%') #画饼图(数据,数据对应的标签,百分数保留两位小数点)
plt.title("Pie chart")
plt.show()
plt.savefig("time_job.jpg")
return
def combine():
labels=['Parse and Regeneration','Inter-procedure Deobfuscation Detection','Inter-procedure Deobfuscation Resolution','dictionary replacement','Control-Flow Flattening','Statement-level Deobfuscation']
colors = ['red','pink','green','purple','orange', 'blue']
sizes = [0.075049478, 0.090475193, 0.150990089, 0.074776232, 0.129486904, 0.075904759]
sizes1 = [0.075384906, 0.168265702, 0.81832427, 0.224871286, 0, 0]
s1, s2 = sum(sizes), sum(sizes1)
for i in range(len(sizes)):
sizes[i] = sizes[i] / s1
for i in range(len(sizes1)):
sizes1[i] = sizes1[i] / s2
explode = (0, 0, 0, 0, 0, 0) # 设置各部分距离圆心的距离
fig1 = plt.figure(facecolor='white',figsize=(16,8))
ax1=plt.subplot(1,2,1)
ax1.pie(sizes, explode=explode,autopct='%1.1f%%',
shadow=False, colors = colors, startangle=90)
ax1.axis('equal')
# ax1.legend(labels)
ax1=plt.subplot(1,2,2)
ax1.pie(sizes1, explode=explode,autopct='%1.1f%%',
shadow=False, colors = colors, startangle=90)
ax1.axis('equal')
ax1.legend(labels)
plt.tight_layout()
plt.show()
fig1.savefig('time_consumption_test.jpg',dpi=400)
if __name__ == '__main__':
combine()