I'm not 100% sure that I get the question, but does this help at all? >>> a = numpy.array([3,2,8,7]) >>> b = numpy.array([1,3,2,4,5,7,6,8,9]) >>> c = set(a) & set(b) >>> c #contains elements of a that are in b (and vice versa) set([8, 2, 3, 7]) >>> indices = numpy.where([x in c for x in b])[0] >>> indices #indices of b where the elements of a in b occur array([1, 2, 5, 7], dtype=int64)
-Mark On Wed, Dec 30, 2015 at 6:45 AM, Nicolas P. Rougier < nicolas.roug...@inria.fr> wrote: > > I’m scratching my head around a small problem but I can’t find a > vectorized solution. > I have 2 arrays A and B and I would like to get the indices (relative to > B) of elements of A that are in B: > > >>> A = np.array([2,0,1,4]) > >>> B = np.array([1,2,0]) > >>> print (some_function(A,B)) > [1,2,0] > > # A[0] == 2 is in B and 2 == B[1] -> 1 > # A[1] == 0 is in B and 0 == B[2] -> 2 > # A[2] == 1 is in B and 1 == B[0] -> 0 > > Any idea ? I tried numpy.in1d with no luck. > > > Nicolas > > _______________________________________________ > NumPy-Discussion mailing list > NumPy-Discussion@scipy.org > https://mail.scipy.org/mailman/listinfo/numpy-discussion >
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