from scipy import integrate
import matplotlib.pyplot as plt
import numpy as np
%matplotlib inline
def sigmoid(x, a):
return (1/(1 + np.exp(-(x-a))))
x = np.arange(0, 20., 0.2)
# sig = sigmoid(x)
plt.plot(x, sigmoid(x, 10))
生成的圖像如下:
def sigmoid(x, a, b):
return (b/(1 + np.exp(-(x-a))))
x = np.arange(0, 100., 0.2)
# sig = sigmoid(x)
plt.plot(x, sigmoid(x, 10, 360))
x2 = lambda x: x**2
integrate.quad(x2, 0, 4)
# 結果第一個數值代表運算結果, 第二個數值代表誤差
(21.333333333333336, 2.368475785867001e-13)
sig = lambda x: (1/(1 + np.exp(-x - 10)))
integrate.quad(sig, 0, 20)
(19.99995460110088, 6.343754535252856e-12)