Hi Francesc,
Thanks for confirming my guess.
I would vote for a different solution than removing this warning in the
'expert' mode.
How about explicitly declaring ordering somewhere in pytables?
Or is this warning the only place where the ordering matters?
Thanks,
Dominik
On Mon, Dec 13, 2010 at 9:27 AM, Francesc Alted <fal...@pytables.org> wrote:
> A Friday 10 December 2010 21:24:35 Dominik Szczerba escrigué:
> > Hi,
> >
> > When calling:
> >
> > f = tables.openFile(fname)
> > points = array(f.getNode("/points").read())
> > tets = array(f.getNode("/tetrahedrons").read())
> > domain = array(f.getNode("/domain").read())
> > f.close()
> >
> > I am getting the following error:
> >
> > /usr/lib/python2.6/dist-packages/tables/leaf.py:415:
> > PerformanceWarning: The Leaf ``/tetrahedrons`` is exceeding the
> > maximum recommended rowsize (13107200 bytes);
> > be ready to see PyTables asking for *lots* of memory and possibly
> > slow I/O. You may want to reduce the rowsize by trimming the value
> > of dimensions that are orthogonal (and preferably close) to the main
> > dimension of this leave. Alternatively, in case you have specified
> > a very small/large chunksize, you may want to increase/decrease it.
> > PerformanceWarning)
> >
> > I only found one similar thread in the archives, unfortunately, never
> > concluded.
> >
> > My file is:
> > > h5ls Obese-00000.h5
> >
> > domain Dataset {4622544}
> > points Dataset {3, 793418}
> > tetrahedrons Dataset {4, 4622544}
> >
> > No error is reported for the other two arrays.
> >
> > Can it be that pytables silently assumes row-major ordering for
> > matrices? I need to store my data in the fortran order.
>
> Yes, it assumes row-major order (the default for NumPy). The above
> warning is to prevent people about the potentially high memory
> consumption of iterating the dataset like this:
>
> for row in tetrahedrons:
> # do things with row
>
> But, while warning inexpert people about this is generally a good thing,
> I recognize that these warning can be rather annoying for 'expert'
> people. Hmmm, I'm thinking that adding an 'EXPERT_MODE' parameter would
> be nice. Added a ticket:
>
> http://pytables.org/trac/ticket/327
>
> Meanwhile, you can get rid of such a warning using the Python machinery:
>
> http://docs.python.org/library/warnings.html
>
> Hope this helps,
>
> --
> Francesc Alted
>
>
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