numpy NaN, not surviving pickle/unpickle?
pavlovevidence at gmail.com
Mon Sep 14 01:17:39 CEST 2009
On Sep 13, 3:18 pm, John Ladasky <john_lada... at sbcglobal.net> wrote:
> In my leisure time, I would like to dig deeper into the issue of why
> object identities are not guaranteed for elements in numpy arrays...
> with elements of type "float", at least, I thought this would be
Unlike Python lists, numpy arrays don't store objects. It stores the
underlying number, not the object containing the number. So whenever
you get a value from a numpy array, Python (usually) has to create a
new object for it.
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