Python numpy.expm1()用法及代码示例

numpy.expm1(数组，out =无，其中= True，强制转换='same_kind'，order ='K'，dtype = None)：
该数学函数可帮助用户计算所有输入数组元素中所有元素的指数减1。

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]

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