Python中的 numpy.logical_xor()

numpy.logical_xor(arr1, arr2, out=None, where = True, cast = 'same_kind', order = 'K', dtype = None, ufunc 'logical_xor') ：这是一个逻辑函数，它可以帮助用户找出arr1 XOR arr2 element-wise 的真值。两个阵列必须具有相同的形状。

参数：

arr1 : [array_like]Input array.
arr2 : [array_like]Input array.

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.

编程需要懂一点英语

返回：

An array with Boolean results of arr1 XOR arr2 element-wise(of the same shape).

代码 1：工作

# Python program explaining
# logical_xor() function
import numpy as np
  
# input
arr1 = [1, 3, False, 0]
arr2 = [3, 0, True, False]
  
# output
out_arr = np.logical_xor(arr1, arr2)
  
print ("Output Array : ", out_arr)

输出：

Output Array :  [False  True  True False]

代码 2：如果输入数组的形状不同，则值错误

# Python program explaining
# logical_xor() function
import numpy as np
  
# input
arr1 = [8, 2, False, 4]
arr2 = [3, 0, False, False, 8]
  
# output
out_arr = np.logical_xor(arr1, arr2)
  
print ("Output Array : ", out_arr)

输出：

ValueError: operands could not be broadcast together with shapes (4,) (5,)

代码3：可以检查条件

# Python program explaining
# logical_xor() function
import numpy as np
  
# input
arr1 = np.arange(8)
print ("arr1 : ", arr1)
  
print ("\narr1>3 : \n", arr1>3)
print ("\narr1<6 : \n", arr1<6)
  
print ("\nXOR Value  : \n", np.logical_xor(arr1>3, arr1<6))

输出：

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

arr1>3 : 
 [False False False False  True  True  True  True]

arr1<6 : 
 [ True  True  True  True  True  True False False]

XOR Value  : 
 [ True  True  True  True False False  True  True]

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