jax.numpy.in1d
jax.numpy.in1d#
- jax.numpy.in1d(ar1, ar2, assume_unique=False, invert=False)[source]#
Test whether each element of a 1-D array is also present in a second array.
LAX-backend implementation of
numpy.in1d().In the JAX version, the assume_unique argument is not referenced.
Original docstring below.
Returns a boolean array the same length as ar1 that is True where an element of ar1 is in ar2 and False otherwise.
We recommend using
isin()instead of in1d for new code.- Parameters
ar1 ((M,) array_like) – Input array.
ar2 (array_like) – The values against which to test each value of ar1.
assume_unique (bool, optional) – If True, the input arrays are both assumed to be unique, which can speed up the calculation. Default is False.
invert (bool, optional) – If True, the values in the returned array are inverted (that is, False where an element of ar1 is in ar2 and True otherwise). Default is False.
np.in1d(a, b, invert=True)is equivalent to (but is faster than)np.invert(in1d(a, b)).
- Returns
in1d – The values ar1[in1d] are in ar2.
- Return type