EH公式的分段线性插值绘图源代码

import matplotlib.pyplot as pltimport numpy as npPH = 0.5# 结论的先验概率PE = 0.4# 证据的先验概率LS = 5# 充分性度量LN = 0.1# 必要性度量def calculation(x):PHNE = LN * PH / ((LN-1)*PH + 1)PHE = LS * PH / ((LS-1)*PH + 1)if x &g

YulongYang1896

528人浏览 · 2020-11-29 22:15:03

YulongYang1896 · 2020-11-29 22:15:03 发布

import matplotlib.pyplot as plt
import numpy as np

PH = 0.5   # 结论的先验概率
PE = 0.4   # 证据的先验概率
LS = 5     # 充分性度量
LN = 0.1   # 必要性度量

def calculation(x):
    PHNE = LN * PH / ((LN-1)*PH + 1)
    PHE = LS * PH / ((LS-1)*PH + 1)
    if x >=0 and x <= PE:
        return PHNE + (PH-PHNE) / PE * x
    elif x >= PE and x <= 1:
        return PH + (PHE - PH) / (1 - PE) * (x - PE)
    else:
        print("输入非法！")
        return

x = float(input("请输入P(E|S):"))
print("P(H|S)=", calculation(x))

plt_x = np.arange(0,1,0.01)
plt_y = np.zeros(len(plt_x))
for i in range(len(plt_x)):
    plt_y[i]= calculation(plt_x[i])
plt.plot(plt_x, plt_y)
plt.xlabel('P(E|S)')
plt.ylabel('P(H|S)')
axes = plt.gca()
axes.set_xlim([0,1])
axes.set_ylim([0,1])
plt.show()