Folks, I've discovered somethign intertesting (bug?) with numpy scalars ans savz. If I save a numpy scalar, then reload it, ot comes back as rank-0 array -- similar, but not the same thing: In [144]: single_value, type(single_value) Out[144]: (2.0, numpy.float32) In [145]: np.savez('test.npz', single_value=single_value) In [146]: single_value2 = np.load('test.npz')['single_value'] In [147]: single_value, type(single_value) Out[147]: (2.0, numpy.float32) In [148]: single_value2, type(single_value2) Out[148]: (array(2.0, dtype=float32), numpy.ndarray) straight np.save has the same issue (which makes sense, I'm sure savez uses the save code under the hood): In [149]: single_value, type(single_value) Out[149]: (2.0, numpy.float32) In [150]: np.save('test.npy', single_value) In [151]: single_value2 = np.load('test.npy') In [152]: single_value2, type(single_value2) Out[152]: (array(2.0, dtype=float32), numpy.ndarray) This has been annoying, particular as rank-zero scalars are kind of a pain. -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