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array_equiv(a1, a2)

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.

Parameters

a1, a2 : array_like

Input arrays.

Returns

out : bool

True if equivalent, False otherwise.

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

Examples

>>> 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
See :

Back References

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numpy.array_equal

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GitHub : /numpy/core/numeric.py#2463
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