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setdiff1d(ar1, ar2, assume_unique=False)

Return the unique values in :None:None:`ar1` that are not in :None:None:`ar2`.

Parameters

ar1 : array_like

Input array.

ar2 : array_like

Input comparison array.

assume_unique : bool

If True, the input arrays are both assumed to be unique, which can speed up the calculation. Default is False.

Returns

setdiff1d : ndarray

1D array of values in :None:None:`ar1` that are not in :None:None:`ar2`. The result is sorted when :None:None:`assume_unique=False`, but otherwise only sorted if the input is sorted.

Find the set difference of two arrays.

See Also

numpy.lib.arraysetops

Module with a number of other functions for performing set operations on arrays.

Examples

>>> a = np.array([1, 2, 3, 2, 4, 1])
... b = np.array([3, 4, 5, 6])
... np.setdiff1d(a, b) array([1, 2])
See :

Back References

The following pages refer to to this document either explicitly or contain code examples using this.

numpy.ma.extras.setdiff1d

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GitHub : /numpy/lib/arraysetops.py#784
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