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drawsingle.py
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drawsingle.py
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import matplotlib.pyplot as plt
import matplotlib as mpl
import numpy as np
def drawfig(outputpath,accaury,signficace,truearray,nosurerate,nonerate,class_names,cnnaccuary,cnntruearray, cnnnosurerate, cnnnonearray):
signficace = np.array(signficace)
onearray = np.ones((len(signficace), 1))
t = onearray - signficace
for i in range(accaury.shape[0]):
plt.figure()
plt.plot(t[0], t[0], 'b--', label='Baseline Calibration', linewidth=1)
plt.plot(t[0], cnnaccuary[i, :], label='MCNN', color='brown', linewidth=1, linestyle='--', marker='')
plt.plot(t[0], accaury[i, :], label='CP-MCNN', color='darkblue', linewidth=1, linestyle='--', marker='+')
plt.xlabel('Confidence')
plt.ylabel('Accuracy')
plt.title(str(class_names[i]))
plt.legend(loc='best')
pigfure = outputpath + '/' + str(class_names[i]) + 'calibration'
plt.savefig(pigfure)
plt.close('all')
plt.figure()
plt.plot(t[0], nonerate[i, :], label='CP-MCNN empty prediction', color='darkblue', linewidth=1, linestyle='-',
marker='.')
plt.plot(t[0], cnnnonearray[i, :], label='MCNN empty prediction', color='brown', linewidth=1, linestyle='--',
marker='+')
plt.xlabel('Confidence')
plt.ylabel('Rate')
plt.title(str(class_names[i]))
pigfure = outputpath + '/' + str(class_names[i]) + 'empty'
# plt.axis([0,1,0,1])
plt.legend(loc='best')
# plt.grid()
plt.savefig(pigfure)
plt.close('all')
plt.figure()
plt.plot(t[0], nosurerate[i, :], label='CP-MCNN favorite prediction', color='darkblue', linewidth=1,
linestyle='-', marker='.')
plt.plot(t[0], cnnnosurerate[i, :], label='MCNN favorite prediction', color='brown', linewidth=1,
linestyle='--',
marker='+')
plt.xlabel('Confidence')
plt.ylabel('Rate')
plt.title(str(class_names[i]))
pigfure = outputpath + '/' + str(class_names[i]) + 'favorite'
plt.legend(loc='best')
plt.savefig(pigfure)
plt.close('all')
plt.figure()
plt.plot(t[0], truearray[i, :], label='CP-MCNN certain prediction', color='darkblue', linewidth=1,
linestyle='--',
marker='')
plt.plot(t[0], cnntruearray[i, :], label='MCNN certain prediction', color='brown', linewidth=1, linestyle='--',
marker='+')
plt.xlabel('Confidence')
plt.ylabel('Rate')
plt.title(str(class_names[i]))
pigfure = outputpath + '/' + str(class_names[i]) + 'cetrain'
# plt.axis([0,1,0,1])
plt.legend(loc='best')
# plt.grid()
plt.savefig(pigfure)
plt.close('all')