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restoreData.py
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import numpy as np
import matplotlib.pyplot as plt
from matplotlib.backends.backend_pdf import PdfPages
#fname='plotData_main_zipf1.txt'
fname='f-ratio.txt'
file=open(fname, 'r')
lines=file.readlines()
temp_file=open('temp_file.txt','w')
for line in lines:
new_line=line[1:len(line)-2]
print(new_line,file=temp_file)
temp_file.close()
data=np.loadtxt('temp_file.txt',delimiter=',')
# 散点图用下面的代码
plt.scatter(np.linspace(0.1,0.7,20),data[0],color='r',label='ranRFL',marker='o',s=100)
plt.scatter(np.linspace(0.1,0.7,20),data[1],color='g',label='GDS',marker='x',s=100)
plt.scatter(np.linspace(0.1,0.7,20),data[2],color='b',label='SLSQP',marker='*',s=100)
fontx={'size':22, 'weight':'normal'}
fonty={'size':23, 'weight':'normal'}
plt.xlabel("Proportion of Involved Data",fontx)
#plt.xlabel("Number of Candidate Devices",fontx)
plt.ylabel('Average Error Rate',fonty)
plt.xticks(fontsize=22)
plt.yticks(fontsize=22)
plt.legend(fontsize=18)
plt.tight_layout()
#plt.show()
# # 柱状图用下面的代码，虽然是三个图，但我遇到了bug，画四次才能正常画出来
# xposition=np.arange(3)
# bar_width=0.25
# plt.bar(x=xposition, height=data[2][0:3], label='SLSQP', color='b',align='center',width=bar_width)
# plt.bar(x=xposition+bar_width, height=data[1][0:3], label='GDS', color='g',align='center',width=bar_width)
# plt.bar(x=xposition+2*bar_width, height=data[0][0:3], label='ranRFL', color='r',align='center',width=bar_width)
# fontx={'size':22, 'weight':'normal'}
# fonty={'size':23, 'weight':'normal'}
# plt.legend()
# plt.tight_layout()
# plt.subplot(1,3,1)
# plt.bar(x=xposition, height=data[2][3:6], label='SLSQP', color='b',align='center',width=bar_width)
# plt.bar(x=xposition+bar_width, height=data[1][3:6], label='GDS', color='g',align='center',width=bar_width)
# plt.bar(x=xposition+2*bar_width, height=data[0][3:6], label='ranRFL', color='r',align='center',width=bar_width)
# fontx={'size':22, 'weight':'normal'}
# fonty={'size':23, 'weight':'normal'}
# # plt.xlabel("Different F Distribution",fontx)
# plt.ylabel('Error Rate',fonty)
# plt.xticks([1.5],labels=('F',),fontsize=22)
# plt.yticks(fontsize=22)
# plt.legend()
# plt.tight_layout()
# plt.subplot(1,3,2)
# plt.bar(x=xposition, height=data[2][6:9], label='SLSQP', color='b',align='center',width=bar_width)
# plt.bar(x=xposition+bar_width, height=data[1][6:9], label='GDS', color='g',align='center',width=bar_width)
# plt.bar(x=xposition+2*bar_width, height=data[0][6:9], label='ranRFL', color='r',align='center',width=bar_width)
# fontx={'size':22, 'weight':'normal'}
# fonty={'size':23, 'weight':'normal'}
# plt.xticks([1.5],labels=('Zipf',),fontsize=22)
# plt.yticks(fontsize=22)
# plt.legend()
# plt.tight_layout()
# plt.subplot(1,3,3)
# plt.bar(x=xposition, height=data[2][0:3], label='SLSQP', color='b',align='center',width=bar_width)
# plt.bar(x=xposition+bar_width, height=data[1][0:3], label='GDS', color='g',align='center',width=bar_width)
# plt.bar(x=xposition+2*bar_width, height=data[0][0:3], label='ranRFL', color='r',align='center',width=bar_width)
# fontx={'size':22, 'weight':'normal'}
# fonty={'size':23, 'weight':'normal'}
# plt.xticks([1.5],labels=('Normal',),fontsize=22)
# plt.yticks(fontsize=22)
# plt.legend()
# plt.tight_layout()
# plt.subplot(1,3,3)
pdf=PdfPages('delicate picture/figure3.pdf')
pdf.savefig()
pdf.close()
plt.show()