Python中的 numpy.power()

numpy.power(arr1, arr2, out = None, where = True, cast = 'same_kind', order = 'K', dtype = None) ：
来自第一个数组的数组元素被提升到来自第二个元素的元素的幂（所有都发生在元素方面）。 arr1 和 arr2 必须具有相同的形状，并且 arr1 中的每个元素都必须从 arr2 提升到相应的 +ve 值；否则会引发ValueError 。
参数 ：

arr1     : [array_like]Input array or object which works as base.
arr2     : [array_like]Input array or object which works as exponent. 
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 elements of arr1 raised to exponents in arr2

代码 1：arr1 提升为 arr2

# Python program explaining
# power() function
import numpy as np
  
# input_array
arr1 = [2, 2, 2, 2, 2]
arr2 = [2, 3, 4, 5, 6]
print ("arr1         : ", arr1)
print ("arr1         : ", arr2)
  
# output_array
out = np.power(arr1, arr2)
print ("\nOutput array : ", out)

输出 ：

arr1         :  [2, 2, 2, 2, 2]
arr2         :  [2, 3, 4, 5, 6]

Output array :  [ 4  8 16 32 64]

代码 2：arr1 的元素提升到指数 2

# Python program explaining
# power() function
import numpy as np
  
# input_array
arr1 = np.arange(8)
exponent = 2
print ("arr1         : ", arr1)
  
# output_array
out = np.power(arr1, exponent)
print ("\nOutput array : ", out)

输出 ：

arr1         :  [0 1 2 3 4 5 6 7]

Output array :  [ 0  1  4  9 16 25 36 49]

代码 3：如果 arr2 有 -ve 元素，则会出错

# Python program explaining
# power() function
import numpy as np
  
# input_array
arr1 = [2, 2, 2, 2, 2]
arr2 = [2, -3, 4, -5, 6]
print ("arr1         : ", arr1)
print ("arr2         : ", arr2)
  
# output_array
out = np.power(arr1, arr2)
print ("\nOutput array : ", out)

输出 ：

arr1         :  [2, 2, 2, 2, 2]
arr2         :  [2, -3, 4, -5, 6]
ValueError: Integers to negative integer powers are not allowed.

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