HI folks, Is there a way to get a view of a subset of a structured array? I know that an arbitrary subset will not fit into the numpy "strides"offsets" model, but some will, and it would be nice to have a view: For example, here we have a stuctured array: In [56]: a Out[56]: array([(1, 2.0, 3.0, 4), (7, 8.0, 9.0, 10), (5, 123.4, 7.0, 8), (9, 10.0, 11.0, 12), (13, 14.0, 15.0, 16)], dtype=[('i', '<i4'), ('f1', '<f8'), ('f2', '<f8'), ('i2', '<i4')]) if I pull out one "field" a get a view: In [57]: b = a['f1'] In [58]: b[0] = 1000 In [59]: a Out[59]: array([(1, 1000.0, 3.0, 4), (7, 8.0, 9.0, 10), (5, 123.4, 7.0, 8), (9, 10.0, 11.0, 12), (13, 14.0, 15.0, 16)], dtype=[('i', '<i4'), ('f1', '<f8'), ('f2', '<f8'), ('i2', '<i4')]) However, if I pull out more than one field, I get a copy: In [60]: b = a[['f1','f2']] In [61]: b Out[61]: array([(1000.0, 3.0), (8.0, 9.0), (123.4, 7.0), (10.0, 11.0), (14.0, 15.0)], dtype=[('f1', '<f8'), ('f2', '<f8')]) In [62]: b[1] = (2000,3000) In [63]: b Out[63]: array([(1000.0, 3.0), (2000.0, 3000.0), (123.4, 7.0), (10.0, 11.0), (14.0, 15.0)], dtype=[('f1', '<f8'), ('f2', '<f8')]) In [64]: a Out[64]: array([(1, 1000.0, 3.0, 4), (7, 8.0, 9.0, 10), (5, 123.4, 7.0, 8), (9, 10.0, 11.0, 12), (13, 14.0, 15.0, 16)], dtype=[('i', '<i4'), ('f1', '<f8'), ('f2', '<f8'), ('i2', '<i4')]) However, in this case, the two fields are contiguous, and thus I'm pretty sure one could build a numpy array that was a view. Is there any way to do so? Ideally without manipulating the strides by hand, but I may want to do that if it's the only way. -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.Barker@noaa.gov