我就废话不多说了，大家还是直接看代码吧~
import matplotlib.pyplot as plt import numpy as np def sigmoid(x): # 直接返回sigmoid函数 return 1. / (1. + np.exp(-x)) def plot_sigmoid(): # param:起点，终点，间距 x = np.arange(-8, 8, 0.2) y = sigmoid(x) plt.plot(x, y) plt.show() if __name__ == '__main__': plot_sigmoid()
如图：
补充知识：python：实现并绘制 sigmoid函数，tanh函数，ReLU函数，PReLU函数
如下所示：
# -*- coding:utf-8 -*-
from matplotlib import pyplot as plt
import numpy as np
import mpl_toolkits.axisartist as axisartist
def sigmoid(x):
return 1. / (1 + np.exp(-x))
def tanh(x):
return (np.exp(x) - np.exp(-x)) / (np.exp(x) + np.exp(-x))
def relu(x):
return np.where(x<0,0,x)
def prelu(x):
return np.where(x<0,0.5*x,x)
def plot_sigmoid():
x = np.arange(-10, 10, 0.1)
y = sigmoid(x)
fig = plt.figure()
# ax = fig.add_subplot(111)
ax = axisartist.Subplot(fig,111)
ax.spines['top'].set_color('none')
ax.spines['right'].set_color('none')
# ax.spines['bottom'].set_color('none')
# ax.spines['left'].set_color('none')
ax.axis['bottom'].set_axisline_style("-|>",size=1.5)
ax.spines['left'].set_position(('data', 0))
ax.plot(x, y)
plt.xlim([-10.05, 10.05])
plt.ylim([-0.02, 1.02])
plt.tight_layout()
plt.savefig("sigmoid.png")
plt.show()
def plot_tanh():
x = np.arange(-10, 10, 0.1)
y = tanh(x)
fig = plt.figure()
ax = fig.add_subplot(111)
ax.spines['top'].set_color('none')
ax.spines['right'].set_color('none')
# ax.spines['bottom'].set_color('none')
# ax.spines['left'].set_color('none')
ax.spines['left'].set_position(('data', 0))
ax.spines['bottom'].set_position(('data', 0))
ax.plot(x, y)
plt.xlim([-10.05, 10.05])
plt.ylim([-1.02, 1.02])
ax.set_yticks([-1.0, -0.5, 0.5, 1.0])
ax.set_xticks([-10, -5, 5, 10])
plt.tight_layout()
plt.savefig("tanh.png")
plt.show()
def plot_relu():
x = np.arange(-10, 10, 0.1)
y = relu(x)
fig = plt.figure()
ax = fig.add_subplot(111)
ax.spines['top'].set_color('none')
ax.spines['right'].set_color('none')
# ax.spines['bottom'].set_color('none')
# ax.spines['left'].set_color('none')
ax.spines['left'].set_position(('data', 0))
ax.plot(x, y)
plt.xlim([-10.05, 10.05])
plt.ylim([0, 10.02])
ax.set_yticks([2, 4, 6, 8, 10])
plt.tight_layout()
plt.savefig("relu.png")
plt.show()
def plot_prelu():
x = np.arange(-10, 10, 0.1)
y = prelu(x)
fig = plt.figure()
ax = fig.add_subplot(111)
ax.spines['top'].set_color('none')
ax.spines['right'].set_color('none')
# ax.spines['bottom'].set_color('none')
# ax.spines['left'].set_color('none')
ax.spines['left'].set_position(('data', 0))
ax.spines['bottom'].set_position(('data', 0))
ax.plot(x, y)
plt.xticks([])
plt.yticks([])
plt.tight_layout()
plt.savefig("prelu.png")
plt.show()
if __name__ == "__main__":
plot_sigmoid()
plot_tanh()
plot_relu()
plot_prelu()
以上这篇Python3 用matplotlib绘制sigmoid函数的案例就是小编分享给大家的全部内容了，希望能给大家一个参考，也希望大家多多支持。
