On this page
numpy.array_equiv
numpy.array_equiv(a1, a2)[source]-
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.
Parameters: -
a1, a2 : array_like -
Input arrays.
Returns: -
out : bool -
True if equivalent, False otherwise.
Examples
>>> np.array_equiv([1, 2], [1, 2]) True >>> np.array_equiv([1, 2], [1, 3]) FalseShowing 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 -
© 2005–2019 NumPy Developers
Licensed under the 3-clause BSD License.
https://docs.scipy.org/doc/numpy-1.17.0/reference/generated/numpy.array_equiv.html