xorbits.numpy.array_equiv#

xorbits.numpy.array_equiv(a1, a2)#

Returns True if input arrays are shape consistent and all elements equal.

Shape consistent means they are either the same shape, or one input array can be broadcasted to create the same shape as the other one.

参数
  • a1 (array_like) – Input arrays.

  • a2 (array_like) – Input arrays.

返回

out – True if equivalent, False otherwise.

返回类型

bool

实际案例

>>> np.array_equiv([1, 2], [1, 2])  
True
>>> np.array_equiv([1, 2], [1, 3])  
False

Showing the shape equivalence:

>>> np.array_equiv([1, 2], [[1, 2], [1, 2]])  
True
>>> np.array_equiv([1, 2], [[1, 2, 1, 2], [1, 2, 1, 2]])  
False
>>> np.array_equiv([1, 2], [[1, 2], [1, 3]])  
False

警告

This method has not been implemented yet. Xorbits will try to execute it with numpy.

This docstring was copied from numpy.