按元素获取 NumPy 数组值的幂

NumPy 是一个强大的 N 维数组对象，它用于线性代数、傅里叶变换和随机数功能。它提供的数组对象比传统的Python列表快得多。 numpy.power() 用于计算元素的幂。它按元素处理从第二个数组提升到幂的第一个数组元素。

Syntax: numpy.power(arr1, arr2, out = None, where = True, casting = ‘same_kind’, order = ‘K’, dtype = None)

Parameters :

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.

因此，让我们讨论一些与获取数组功能相关的示例。

示例 1：计算具有不同元素值的数组的幂。

Python3

# import required modules
import numpy as np
 
 
# creating the array
sample_array1 = np.arange(5)
sample_array2 = np.arange(0, 10, 2)
 
print("Original array ")
print("array1 ", sample_array1)
print("array2 ", sample_array2)
 
# calculating element-wise power
power_array = np.power(sample_array1, sample_array2)
 
print("power to the array1 and array 2 : ", power_array)

输出：

Original array 
array1  [0 1 2 3 4]
array2  [0 2 4 6 8]
power to the array1 and array 2 :  [    1     1    16   729 65536]

示例 2：为数组中的每个元素计算相同的幂。

Python3

# import required module
import numpy as np
 
 
# creating the array
array = np.arange(8)
print("Original array")
print(array)
 
# computing the power of array
print("power of 3 for every element-wise:")
print(np.power(array, 3))

输出：

Original array
[0 1 2 3 4 5 6 7]
power of 3 for every element-wise:
[  0   1   8  27  64 125 216 343]

示例 3：计算十进制值的幂。

Python3

# import required modules
import numpy as np
 
 
# creating the array
sample_array1 = np.arange(5)
 
# initialization the decimal number
sample_array2 = [1.0, 2.0, 3.0, 3.0, 2.0]
 
print("Original array ")
print("array1 ", sample_array1)
print("array2 ", sample_array2)
 
# calculating element-wise power
power_array = np.power(sample_array1, sample_array2)
 
print("power to the array1 and array 2 : ", power_array)

输出：

Original array 
array1  [0 1 2 3 4]
array2  [1.0, 2.0, 3.0, 3.0, 2.0]
power to the array1 and array 2 :  [ 0.  1.  8. 27. 16.]

注意：你不能计算负功率

示例 4：

Python3

# importing module
import numpy as np
 
 
# creating the array
array = np.arange(8)
print("Original array")
print(array)
print("power of 3 for every element-wise:")
 
# computing the negative power element
print(np.power(array, -3))

输出：