On 5/27/11 9:48 AM, Michael Katz wrote: > I have a numpy array, records, with named fields including a field named > "integer_field". I have an array (or list) of values of interest, and I > want to get the indexes where integer_field has any of those values. > > Because I can do > > indexes = np.where( records.integer_field > 5 ) > > I thought I could do > > indexes = np.where( records.integer_field in values ) > > But that doesn't work. (As a side question I'm interested in why that > doesn't work, when values is a python list.)
that doesn't work because the python list "in" operator doesn't understand arrays -- so it is looking ot see if the entire array is in the list. actually, it doesn't even get that far: In [16]: a in l --------------------------------------------------------------------------- ValueError Traceback (most recent call last) /Users/chris.barker/<ipython console> in <module>() ValueError: The truth value of an array with more than one element is ambiguous. Use a.any() or a.all() The ValueError results because it was decided that numpy array should not have a boolean value to avoid confusion -- i.e. is na array true whenever it is non-empty (like a list), or when all it's elements are true, or???? When I read this question, I thought -- hmmm, numpy needs something like "in", as the usual way: np.any(), would require a loop in this case. Then I read Skipper's message: On 5/27/11 9:55 AM, Skipper Seabold wrote: > Check out this recent thread. I think the proposed class does what you > want. It's more efficient than in1d, if values is small compared to > the length of records. So that class may be worthwhile, but I think np.in1d is exactly what you are looking for: indexes = np.in1d( records.integer_field, values ) Funny I'd never noticed that before. -Chris -- Christopher Barker, Ph.D. Oceanographer Emergency Response Division NOAA/NOS/OR&R (206) 526-6959 voice 7600 Sand Point Way NE (206) 526-6329 fax Seattle, WA 98115 (206) 526-6317 main reception chris.bar...@noaa.gov _______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
