python绘制激活函数图像
1，Relu
函数表达式：f(x)=max{0,x}, x∈(-∞,+∞)
绘图程序
# __author__ = 'czx'
# coding=utf-8
import numpy as np
from numpy import *
import matplotlib.pyplot as plt
def relu(x):
y = x.copy()
y[y < 0] = 0
return y
x = np.arange(-10, 10, 0.01)
plt.tick_params(labelsize=14) # 刻度字体大小14
y_relu = relu(x)
plt.plot(x, y_relu, 'b', linewidth=2.5, label=u'relu')
plt.legend(loc='upper left',fontsize=16, frameon=False) # 图例字体大小16
plt.tight_layout() # 去除边缘空白
plt.savefig("F:/激活函数/relu.jpeg", dpi=600, format="jpeg")
#savefig要写在show前面,不然保存的就是空白图片
plt.show()
2，Sigmoid
函数表达式：f(x)=1/(1+e^(-x) ) , x∈(-∞,+∞)
绘图程序
# __author__ = 'czx'
# coding=utf-8
import numpy as np
from numpy import *
import matplotlib.pyplot as plt
def sigmoid(x):
return 1.0 / (1.0 + exp(-x))
x = np.arange(-10, 10, 0.01)
plt.tick_params(labelsize=14) # 刻度字体大小14
y_sigmoid = sigmoid(x)
plt.plot(x, y_sigmoid, 'b', linewidth=2.5, label=u'sigmoid')
plt.legend(loc='upper left', fontsize=16, frameon=False) # 图例字体大小16
plt.tight_layout() # 去除边缘空白
plt.savefig("F:/激活函数/sigmoid.jpeg", dpi=600, format="jpeg")
# savefig要写在show前面,不然保存的就是空白图片
plt.show()
3，Tanh
绘图程序
# __author__ = 'czx'
# coding=utf-8
import numpy as np
from numpy import *
import matplotlib.pyplot as plt
def tanh(x):
return 2.0 / (1.0 + exp(-2 * x)) - 1
x = np.arange(-10, 10,0.01)
plt.tick_params(labelsize=14) # 刻度字体大小14
y_tanh = tanh(x)
plt.plot(x, y_tanh, 'b', linewidth=2.5, label=u'tanh')
plt.legend(loc='upper left', fontsize=16, frameon=False) # 图例字体大小16
plt.tight_layout() # 去除边缘空白
plt.savefig("F:/激活函数/tanh.jpeg", dpi=600, format="jpeg")
# savefig要写在show前面,不然保存的就是空白图片
plt.show()
4，leakyrelu
绘图程序
# __author__ = 'czx'
# coding=utf-8
import numpy as np
from numpy import *
import matplotlib.pyplot as plt
import mpl_toolkits.axisartist as axisartist
def leakyrelu(x):
y = x.copy()
for i in range(y.shape[0]):
if y[i] < 0:
y[i] = 0.2 * y[i]
return y
x = np.arange(-10, 10, 0.01)
plt.tick_params(labelsize=14) # 刻度字体大小14
y_relu = leakyrelu(x)
plt.plot(x, y_relu, 'b', linewidth=2.5, label=u'leakyrelu')
plt.legend(loc='upper left', fontsize=16, frameon=False) # 图例字体大小16
plt.tight_layout() # 去除边缘空白
plt.savefig("F:/激活函数/leakyrelu.jpeg", dpi=600, format="jpeg")
# savefig要写在show前面,不然保存的就是空白图片
plt.show()
5，Elu
绘图程序
在这里插入# __author__ = 'czx'
# coding=utf-8
import numpy as np
from numpy import *
import matplotlib.pyplot as plt
def elu(x, a):
y = x.copy()
for i in range(y.shape[0]):
if y[i] < 0:
y[i] = a * (exp(y[i]) - 1)
return y
x = np.arange(-10, 10, 0.01)
plt.tick_params(labelsize=14) # 刻度字体大小14
y_relu = elu(x, 0.3)
plt.plot(x, y_relu, 'b', linewidth=2.5, label=u'elu')
plt.legend(loc='upper left', fontsize=16, frameon=False) # 图例字体大小16
plt.tight_layout() # 去除边缘空白
plt.savefig("F:/激活函数/elu.jpeg", dpi=600, format="jpeg")
# savefig要写在show前面,不然保存的就是空白图片
plt.show()
代码片
6，Gaussian
绘图程序
# __author__ = 'czx'
# coding=utf-8
import numpy as np
from numpy import *
import matplotlib.pyplot as plt
import mpl_toolkits.axisartist as axisartist
def gaussian(x):
return exp(-x**2)
x = np.arange(-10, 10, 0.01)
plt.tick_params(labelsize=14) # 刻度字体大小14
y_gaussian = gaussian(x)
plt.plot(x, y_gaussian, 'b', linewidth=2.5, label=u'gaussian')
plt.legend(loc='upper left', fontsize=16, frameon=False) # 图例字体大小16
plt.tight_layout() # 去除边缘空白
plt.savefig("F:/激活函数/gaussian.jpeg", dpi=600, format="jpeg")
# savefig要写在show前面,不然保存的就是空白图片
plt.show()
7，Binary
绘图程序
# __author__ = 'czx'
# coding=utf-8
import numpy as np
from numpy import *
import matplotlib.pyplot as plt
import mpl_toolkits.axisartist as axisartist
def binary(x):
y = x.copy()
y[y < 0] = 0
y[y > 0] = 1
return y
x = np.arange(-10, 10, 0.01)
plt.tick_params(labelsize=14) # 刻度字体大小14
y_binary = binary(x)
plt.plot(x, y_binary, 'b', linewidth=2.5, label=u'binary')
plt.legend(loc='upper left',fontsize=16, frameon=False) # 图例字体大小16
plt.tight_layout() # 去除边缘空白
plt.savefig("F:/激活函数/binary.jpeg", dpi=600, format="jpeg")
#savefig要写在show前面,不然保存的就是空白图片
plt.show()
8，sinx
绘图程序
# __author__ = 'czx'
# coding=utf-8
import numpy as np
from numpy import *
import matplotlib.pyplot as plt
import mpl_toolkits.axisartist as axisartist
def sinx(x):
return sin(x)/x
x = np.arange(-10, 10, 0.01)
plt.tick_params(labelsize=14) # 刻度字体大小14
y_sinx = sinx(x)
plt.plot(x, y_sinx, 'b', linewidth=2.5, label=u'sinx')
plt.legend(loc='upper left', fontsize=16, frameon=False) # 图例字体大小16
plt.tight_layout() # 去除边缘空白
plt.savefig("F:/激活函数/sinx.jpeg", dpi=600, format="jpeg")
# savefig要写在show前面,不然保存的就是空白图片
plt.show()
9，softpulx
绘图程序
# __author__ = 'czx'
# coding=utf-8
import numpy as np
from math import log10
from numpy import *
import matplotlib.pyplot as plt
import mpl_toolkits.axisartist as axisartist
def Softplus(x):
return log10(exp(x)+1)
x = np.arange(-10, 10, 0.01)
plt.tick_params(labelsize=14) # 刻度字体大小14
y_Softplus = Softplus(x)
plt.plot(x, y_Softplus, 'b', linewidth=2.5, label=u'Softplus')
plt.legend(loc='upper left', fontsize=16, frameon=False) # 图例字体大小16
plt.tight_layout() # 去除边缘空白
plt.savefig("F:/激活函数/Softplus.jpeg", dpi=600, format="jpeg")
# savefig要写在show前面,不然保存的就是空白图片
plt.show()
合在一起的激活函数图
# __author__ = 'czx'
# coding=utf-8
import numpy as np
from numpy import *
import matplotlib
import matplotlib.pyplot as plt
def sigmoid(x):
return 1.0 / (1.0 + exp(-x))
def tanh(x):
return 2.0 / (1.0 + exp(-2 * x)) - 1
def relu(x):
y = x.copy()
y[y < 0] = 0
return y
def elu(x, a):
y = x.copy()
for i in range(y.shape[0]):
if y[i] < 0:
y[i] = a * (exp(y[i]) - 1)
return y
if __name__ == '__main__':
x = arange(-3.0, 3.0, 0.01)
y_sigmoid = sigmoid(x)
y_tanh = tanh(x)
y_relu = relu(x)
y_elu = elu(x, 0.25)
plt.plot(x, y_sigmoid, 'r', linewidth=2.5, label=u'sigmoid')
plt.plot(x, y_tanh, 'g', linewidth=2.5, label=u'tanh')
plt.plot(x, y_relu, 'b', linewidth=2.5, label=u'relu')
plt.plot(x, y_elu, 'k', linewidth=2.5, label=u'elu')
plt.ylim([-1, 1])
plt.xlim([-1, 1])
plt.legend()
plt.grid(color='b', linewidth='0.3', linestyle='--')
plt.show()