Hi!
I know it is pretty much the same as you did before, but has been useful
for me in the past. Instead of saving each array separately, just create a
dictionary and save the it, something like
d= {put_all_your_arrays_here}
savez_compressed('file.npz', **d)
-- Camilo Jiménez
On Sat, Jun 15, 2013 at 2:11 PM, Eric Firing <[email protected]> wrote:
> On 2013/06/15 6:06 AM, Pierre GM wrote:
> >
> > On Jun 15, 2013, at 17:35 , Matthew Brett <[email protected]>
> wrote:
> >
> >> Hi,
> >>
> >> On Sat, Jun 15, 2013 at 2:51 PM, Sudheer Joseph
> >> <[email protected]> wrote:
> >>>
> >>> Thank you very much for this tip.
> >>> Is there a typical way to save masked and the rest separately?. Not
> much familiar with array handling in numpy.
> >>
> >> I don't use masked array myself, but it looks like it would be
> something like:
> >>
> >> eof1_unmasked = np.array(eof1)
> >> eof1_mask = eof1.mask
> >>
> >> then you could save those two. Maybe a more maskey person could
> comment?
> >
> > Instead of `eof1_unmasked=np.array(eof1)`, you could do `eof1_unmasked =
> eof1.data`. The '.data' attribute points to a view of the masked array as
> a simple ndarray.
> >
> > You may also wanna try `eof1.torecords()` that will return a structured
> array with dtype `[('_data',type_of_eof1),('_mask', bool)]`.
>
> For automated saving and restoring, try this:
>
>
> http://currents.soest.hawaii.edu/hgstage/pycurrents/file/686c2802a6c4/file/npzfile.py
>
> Eric
>
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