mindspore.numpy.in1d

mindspore.numpy.in1d(ar1, ar2, invert=False)[source]

Tests whether each element of a 1-D array is also present in a second array.

Returns a boolean array the same length as ar1 that is True where an element of ar1 is in ar2 and False otherwise.

Note

Numpy argument assume_unique is not supported since the implementation does not rely on the uniqueness of the input arrays.

Parameters

ar1 (Union[int, float, bool, list, tuple, Tensor]) – Input array with shape (M,).
ar2 (Union[int, float, bool, list, tuple, Tensor]) – The values against which to test each value of ar1.
invert (boolean, 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: False .

Returns

Tensor, with shape (M,). The values ar1[in1d] are in ar2.

Supported Platforms:: Ascend GPU CPU

Examples

>>> import mindspore.numpy as np
>>> test = np.array([0, 1, 2, 5, 0])
>>> states = [0, 2]
>>> mask = np.in1d(test, states)
>>> print(mask)
[ True False  True False  True]
>>> mask = np.in1d(test, states, invert=True)
>>> print(mask)
[False  True False  True False]