AI Python 中的 numpy.array_equiv()

Python 中的 numpy.array_equiv()

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numpy.array_equiv(arr1，arr2) : 检查两个数组是否有相同元素且形状一致的逻辑函数。

形状一致表示它们具有相同的形状，或者一个输入数组可以被广播以创建与另一个相同的形状。

参数:

arr1    : [array_like]Input array, we need to test.
arr2    : [array_like]Input array, we need to test.

返回:

True, if both arrays are equivalent; otherwise False

代码:解释工作

# Python program explaining
# array_equiv() function
import numpy as np

# input
arr1 = np.arange(4)
arr2 = [7, 4, 6, 7]
print ("arr1 : ", arr1)
print ("arr2 : ", arr2)

print ("\nResult : ", np.array_equiv(arr1, arr2))

arr1 = np.arange(4)
arr2 = np.arange(4)
print ("\n\narr1 : ", arr1)
print ("arr2 : ", arr2)

print ("\nResult : ", np.array_equiv(arr1, arr2))

arr1 = np.arange(4)
arr2 = np.arange(5)
print ("\n\narr1 : ", arr1)
print ("arr2 : ", arr2)

print ("\nResult : ", np.array_equiv(arr1, arr2))

a = np.array_equiv([1, 2], [[1, 2, 1, 2], [1, 2, 1, 2]])

b = np.array_equiv([1, 2], [[1, 2], [1, 2]])

print ("\n\na : ", a)
print ("\nb : ", b)

输出:

arr1 :  [0 1 2 3]
arr2 :  [7, 4, 6, 7]

Result :  False

arr1 :  [0 1 2 3]
arr2 :  [0 1 2 3]

Result :  True

arr1 :  [0 1 2 3]
arr2 :  [0 1 2 3 4]

Result :  False

a :  False

b :  True

参考文献: https://docs . scipy . org/doc/numpy-1 . 13 . 0/reference/generated/numpy . array _ equiv . html # numpy . array _ equiv 。