我就废话不多说了，大家还是直接看代码吧~

import matplotlib.pyplot as pltimport 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 pltimport numpy as npimport 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。