Pythone 3はmatplotlibでsigmoid関数を描いたケースです。

import matplotlib.pyplot as plt
import numpy as np 
def sigmoid(x):
  #     sigmoid  
  return 1. / (1. + np.exp(-x)) 
 
def plot_sigmoid():
  # param:  ，  ，  
  x = np.arange(-8, 8, 0.2)
  y = sigmoid(x)
  plt.plot(x, y)
  plt.show() 
 
if __name__ == '__main__':
  plot_sigmoid()

# -*- 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()