Yes, this is exactly what I was after, only the function name did not ring a bell (I still cannot associate it with something meaningful for my use case). Thanks!
-- Slaunger 2009/2/25 <josef.p...@gmail.com>: > On Wed, Feb 25, 2009 at 7:28 AM, Kim Hansen <slaun...@gmail.com> wrote: >> Hi Numpy discussions >> Quite often I find myself wanting to generate a boolean mask for fancy >> slicing of some array, where the mask itself is generated by checking >> if its value has one of several relevant values (corresponding to >> states) >> So at the the element level thsi corresponds to checking if >> element in iterable >> But I can't use the in operator on a numpy array: >> >> In [1]: test = arange(5) >> In [2]: states = [0, 2] >> In [3]: mask = test in states >> --------------------------------------------------------------------------- >> ValueError Traceback (most recent call last) >> C:\Documents and Settings\kha\<ipython console> in <module>() >> ValueError: The truth value of an array with more than one element is >> ambiguous. >> Use a.any() or a.all() >> >> I can however make my own utility function which works effectively the >> same way by iterating through the states >> >> In [4]: for i, state in enumerate(states): >> ...: if i == 0: >> ...: result = test == state >> ...: else: >> ...: result |= test == state >> ...: >> ...: >> In [5]: result >> Out[5]: array([ True, False, True, False, False], dtype=bool) >> >> However, I would have thought such an "array.is_in()" utility function >> was already available in the numpy package? >> >> But I can't find it, and I am curious to hear if it is there or if it >> just available in another form which I have simply overlooked. >> >> If it is not there I think it could be a nice extra utility funtion >> for the ndarray object. >> >> --Slaunger >> _______________________________________________ >> Numpy-discussion mailing list >> Numpy-discussion@scipy.org >> http://projects.scipy.org/mailman/listinfo/numpy-discussion >> > > does this help: > >>>> np.setmember1d(test,states) > array([ True, False, True, False, False], dtype=bool) > > Josef > _______________________________________________ > Numpy-discussion mailing list > Numpy-discussion@scipy.org > http://projects.scipy.org/mailman/listinfo/numpy-discussion > _______________________________________________ Numpy-discussion mailing list Numpy-discussion@scipy.org http://projects.scipy.org/mailman/listinfo/numpy-discussion
