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?
Dominik
i.e. read a row. This is, in fact, basically equivalent to:
>
> for col in tetrahedrons:
> # get indices of one element
>
> So, I'd say that you can use both methods and get similar performance.
>
> Hope this makes sense,
>
> --
> Francesc Alted
>
>
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