jax.numpy.intersect1d#

jax.numpy.intersect1d(ar1, ar2, assume_unique=False, return_indices=False)[source]#

Find the intersection of two arrays.

LAX-backend implementation of numpy.intersect1d().

Original docstring below.

Return the sorted, unique values that are in both of the input arrays.

Parameters:

  • ar1 (array_like) – Input arrays. Will be flattened if not already 1D.

  • ar2 (array_like) – Input arrays. Will be flattened if not already 1D.

  • assume_unique (bool) – If True, the input arrays are both assumed to be unique, which can speed up the calculation. If True but ar1 or ar2 are not unique, incorrect results and out-of-bounds indices could result. Default is False.

  • return_indices (bool) – If True, the indices which correspond to the intersection of the two arrays are returned. The first instance of a value is used if there are multiple. Default is False.

Return type:

Union[Array, Tuple[Array, Array, Array]]

Returns:

  • intersect1d (ndarray) – Sorted 1D array of common and unique elements.

  • comm1 (ndarray) – The indices of the first occurrences of the common values in ar1. Only provided if return_indices is True.

  • comm2 (ndarray) – The indices of the first occurrences of the common values in ar2. Only provided if return_indices is True.