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.bar...@noaa.gov
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