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numpy.intersect1d(ar1, ar2, assume_unique=False)[source] -
Find the intersection of two arrays.
Return the sorted, unique values that are in both of the input arrays.
Parameters: ar1, ar2 : array_like
Input arrays.
assume_unique : bool
If True, the input arrays are both assumed to be unique, which can speed up the calculation. Default is False.
Returns: intersect1d : ndarray
Sorted 1D array of common and unique elements.
See also
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numpy.lib.arraysetops - Module with a number of other functions for performing set operations on arrays.
Examples
>>> np.intersect1d([1, 3, 4, 3], [3, 1, 2, 1]) array([1, 3])
To intersect more than two arrays, use functools.reduce:
>>> from functools import reduce >>> reduce(np.intersect1d, ([1, 3, 4, 3], [3, 1, 2, 1], [6, 3, 4, 2])) array([3])
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numpy.intersect1d()
2017-01-10 18:14:27
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