np.setmember1d(a,b) does the same as your
reduce(np.logical_or, [a == i for i in b]) but it's actually slower on my machine! Gary R. Ernest Adrogué wrote: > Hi, > > Suppose I have a flat array, and I want to know the > indices corresponding to values contained in a list > of arbitrary lenght. > > Intuitively I would have done: > > a = np.array([1,2,3,4]) > np.nonzero(a in (0,2,4)) > > However the "in" operator doesn't work element-wise, > instead it compares the whole array with each member > of the list. > > I have found that this does the trick: > > b = (0,2,4) > reduce(np.logical_or, [a == i for i in b]) > > then pass the result to np.nonzero to get the indices, > but, is there a numpy function that can handle this > situation? > > Cheers. > Ernest _______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
