bundles / scipy latest / scipy / _lib / array_api_extra / _delegation / isin
function
scipy._lib.array_api_extra._delegation:isin
Signature
def isin ( a : Array , b : Array , / , assume_unique : bool = False , invert : bool = False , kind : str | None = None , xp : ModuleType | None = None ) → Array Summary
Determine whether each element in a is present in b.
Extended Summary
Return a boolean array of the same shape as a that is True for elements that are in b and False otherwise.
Parameters
a: arrayInput elements.
b: arrayThe elements against which to test each element of
a.assume_unique: bool, optionalIf True, the input arrays are both assumed to be unique which can speed up the calculation. Default: False.
invert: bool, optionalIf True, the values in the returned array are inverted. Default: False.
kind: str | None, optionalThe algorithm or method to use. This will not affect the final result, but will affect the speed and memory use. For NumPy the options are {None, "sort", "table"}. For Jax the mapped parameter is instead
methodand the options are {"compare_all", "binary_search", "sort", and "auto" (default)} For CuPy, Dask, Torch and the default case this parameter is not present and thus ignored. Default: None.xp: array_namespace, optionalThe standard-compatible namespace for
aandb. Default: infer.
Returns
: arrayAn array having the same shape as that of
athat is True for elements that are inband False otherwise.
Aliases
-
scipy.differentiate.xpx.isin