[Numpy-discussion] Home for pyhdf5io?
Thu May 21 15:54:08 CDT 2009
On Thu, May 21, 2009 at 22:38, David Warde-Farley <email@example.com> wrote:
> Hi Albert,
> So this is a wrapper on top of PyTables to implement load() and
> save()? Neat.
Yes, you got the idea. in its most simplest form you can type:
And all your local variables are saved to a file with the default file
Of course it also allows you to specify a file name and what variables
you would like to save.
As it is based on hdf5 you can also store the variables to a certain
group within the file
(If you know how hdf5 works, you probably know what I'm talking
about). Appending data to existing
hdf5-files is also possible.
> Obviously if you're installing PyTables, you can do a lot better and
> organize your data hierarchically without the messiness of Matlab
> structures, walk the node tree, all kinds of fun stuff, but if you're
> an expatriate matlab user and just want to save some matrices... this
> is great. Notably, that was one of my gripes about ipython+numpy+scipy
> +matplotlib when I first came from Matlab.
> I think you should send a message to the PyTables list, ask Francesc
> if he thinks it has a place in PyTables for it as a 'lite' wrapper or
> something, for people who need to save data but don't need/are
> intimidated by all the features that PyTables provides.
Actually, I just e-mail Francesc, see what he thinks.
Thanks for your reply. Also thanks to the others who also have replied
> On 21-May-09, at 4:04 PM, firstname.lastname@example.org wrote:
>> Dear list,
>> I'm writing this because i have developed a small python module that
>> might be of interest to you the readers of this list:
>> It basically implements load/save functions that mimic the behaviour
>> of those found in Matlab, ie with them you can store your variables
>> from within the interactive shell (IPython, python) or from within a
>> function, and then load them back in again. One important difference
>> is that the hdf5 format is used to store the variables, which comes
>> with aa number of benefits:
>> - a open standard file format which is supported by many applications.
>> - completely portable file format across different platforms.
>> Read more here: http://www.hdfgroup.org/HDF5/whatishdf5.html
>> And now to the question:
>> I think that this module is to small to be developed and maintained
>> on its on, I think It would be better if it could be part of some
>> larger project. So where would pyhdf5io fit in?
>> Any tips and ideas are highly appreciated.
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