[Numpy-discussion] array metadata

[Emmanuel Mayssat]

subclassing is what I was looking for.
Indeed the code is almost available at
http://docs.scipy.org/doc/numpy/user/basics.subclassing.html#simple-example-adding-an-extra-attribute-to-ndarray
I just created a dictionary variable which I called 'metadata'
I had to overload the __repr__ method to print my parameters in the
python shell.

As far as saving the data on the disk.... let me start a new thread ;-)
--
Emmanuel

On Thu, Jan 26, 2012 at 5:49 AM, Derek Homeier
<derek at astro.physik.uni-goettingen.de> wrote:
> On 26 Jan 2012, at 13:30, Paul Anton Letnes wrote:
>
>> If by "store" you mean "store on disk", I recommend h5py datasets andhttp://docs.scipy.org/doc/numpy/user/basics.subclassing.html
>> attributes. Reportedly pytables is also good but I don't have any
>> first hand experience there. Both python modules use the hdf5 library,
>> written in C/C++/Fortran.
>>
>> Paul
>>
>> On Wed, Jan 25, 2012 at 7:47 PM, Val Kalatsky <kalatsky at gmail.com> wrote:
>>>
>>> I believe there are no provisions made for that in ndarray.
>>> But you can subclass ndarray.
>>
> You could probably use structured arrays with string and datetype fields for the
> metadata and multidimensional fields (i.e. effectively subarrays within the
> structured array) for the actual data. For file storage, they could probably be directly
> saved as .npy, if interoperability is not a concern. Otherwise I'd also highly recommend
> hdf5; with both h5py and pytables allowing quite transparent conversion of structured
> arrays to datasets in the HDF5, but you also have the option to store other objects,
> like dictionary elements, within the same data structure.
> Pytables is generally regarded as having a more database-oriented approach,
> while h5py appears more straightforward to use from a numerics background
> (at least in my experience).
>
> Cheers,
>                                                Derek
>
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