A Monday 13 December 2010 14:05:28 Dominik Szczerba escrigué:
> On Mon, Dec 13, 2010 at 1:48 PM, Francesc Alted <fal...@pytables.org>
wrote:
> > As we know, HDF5 is ignorant on how the data in file is ordered.
> > So, if you have created the dataset using a Fortran program, then
> > clearly the data is ordered column-wise on disk. But, as you are
> > reading the file by using a C-based app, then columns and rows
> > will appear to be *transposed*.
> >
> > So, if what you want is to read column i *of your original Fortran
> > array*, then the correct way to do this in PyTables should be:
> >
> > for i in range(NCELL):
> > col = tetrahedrons[i,:]
>
> This does not work. It only works as I wrote previously. Please see
> below:
>
> In [3]: tets = array(fid.getNode("/tetrahedrons").read())
> In [4]: tets.shape
> Out[4]: (4, 4624802)
> In [5]: tets[:,0]
> Out[5]: array([715692, 707733, 707734, 159966], dtype=int32)
> In [6]: tets[0,:]
> Out[6]: array([715692, 365237, 555693, ..., 706208, 706208, 511217],
> dtype=int32)
>
> so tetrahedrons[i,:] runs 0..3 and not 0...NC-1
>
> Did you make a typo above, or we do not arrive at a conclusion?
That was not a typo, but a mistake on my part (I forgot that HDF5
reverses the shape of the matrices when using the Fortran binding). So,
yes, your version is okay for accessing columns.
But, for knowing if accessing columns this is efficient for your case,
I'd need more info on your datasets. Are they contiguous or chunked?
If chunked, which is the chunkshape you have chosen?
--
Francesc Alted
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