Thank you Camilo,
                     It is indeed an easy way and also the link is a ready to 
use save method. Thanks a lot for sharing it 

with best regards,
Sudheer

 
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>________________________________
> From: Camilo Andrés Jimenez Cruz <camilo.jimen...@gmail.com>
>To: Discussion of Numerical Python <numpy-discussion@scipy.org> 
>Sent: Sunday, 16 June 2013 11:37 PM
>Subject: Re: [Numpy-discussion] saving 3d array
> 
>
>
>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 <efir...@hawaii.edu> wrote:
>
>On 2013/06/15 6:06 AM, Pierre GM wrote:
>>>
>>> On Jun 15, 2013, at 17:35 , Matthew Brett <matthew.br...@gmail.com> wrote:
>>>
>>>> Hi,
>>>>
>>>> On Sat, Jun 15, 2013 at 2:51 PM, Sudheer Joseph
>>>> <sudheer.jos...@yahoo.com> 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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