Python numpy.float_power()用法及代碼示例

numpy.float_power(arr1，arr2，out = None，其中= True，強製轉換=“ same_kind”，order =“ K”，dtype = None)：
來自第一個數組的數組元素被提升為來自第二個元素的元素的冪(所有情況都逐個元素發生)。 arr1和arr2必須具有相同的形狀。
float_power與冪函數的不同之處在於，將整數float16和float32提升為float64的最小精度為float64，因此結果始終是不精確的。此函數將為負冪返回可用結果，而對於+ ve冪則很少溢出。

參數：

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

代碼1：將arr1提升為arr2

# Python program explaining 
# float_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.float_power(arr1, arr2) 
print ("\nOutput array : ", out)

輸出：

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

Output array :  [  4.   8.  16.  32.  64.]

代碼2：將arr1的元素提高到指數2

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

輸出：

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

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

代碼3：如果arr2具有-ve元素，則float_power處理結果

# Python program explaining 
# float_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.float_power(arr1, arr2) 
print ("\nOutput array : ", out)

輸出：

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

Output array :  [  4.00000000e+00   1.25000000e-01   1.60000000e+01   
                3.12500000e-02   6.40000000e+01]

參考文獻：
https://docs.scipy.org/doc/numpy-1.13.0/reference/generated/numpy.float_power.html#numpy.float_power
。