Python中的 numpy.expm1()

numpy.expm1(array, out = None, where = True, cast = 'same_kind', order = 'K', dtype = None) ：
此数学函数可帮助用户计算从所有输入数组元素中减去 1 的所有元素的指数。

参数 ：

array    : [array_like]Input array or object whose elements, we need to test.
out      : [ndarray, optional]Output array with same dimensions as Input array, 
           placed with result.
**kwargs : allows you to pass keyword variable length of argument to a function. 
           It is used when we want to handle named argument in a function.
where    : [array_like, optional]True value means to calculate the universal 
           functions(ufunc) at that position, False value means to leave the 
           value in the output alone.

返回 ：

An array with exponential(all elements of input array) - 1. 

代码 1：工作

# Python program explaining
# expm1() function
  
import numpy as np
  
in_array = [1, 3, 5]
print ("Input array : \n", in_array)
  
exp_values = np.exp(in_array)
print ("\nExponential value of array element : "
       "\n", exp_values)
  
expm1_values = np.expm1(in_array)
print ("\n(Exponential value of array element) - (1) "
       ": \n", expm1_values)

输出 ：

Input array : 
 [1, 3, 5]

Exponential value of array element : 
 [   2.71828183   20.08553692  148.4131591 ]

(Exponential value of array element) - (1) : 
 [   1.71828183   19.08553692  147.4131591 ]

代码 2：图形表示

# Python program showing
# Graphical representation of 
# expm1() function
  
import numpy as np
import matplotlib.pyplot as plt
  
in_array = [1, 1.2, 1.4, 1.6, 1.8, 2]
out_array = np.expm1(in_array)
  
print("out_array : ", out_array)
  
y = [1, 1.2, 1.4, 1.6, 1.8, 2]
plt.plot(in_array, y, color = 'blue', marker = "*")
  
# red for numpy.expm1()
plt.plot(out_array, y, color = 'red', marker = "o")
plt.title("numpy.expm1()")
plt.xlabel("X")
plt.ylabel("Y")
plt.show()  

输出 ：
out_array：[1.71828183 2.32011692 3.05519997 3.95303242 5.04964746 6.3890561]

参考 ：
https://docs.scipy.org/doc/numpy-1.13.0/reference/generated/numpy.expm1.html#numpy.expm1
.