A Friday 26 September 2008, filc ekab escrigué: > > Out of curiosity, may you be a bit more explicit on what > > you are after? Perhaps a code snippet would help us to better > > understand your need and suggest anything more specific. > > It is difficult to show a snippet of code for something I > do not know how to do, or to be more specific than what > I already said-- I have a numpy ndarray in an HDF5 file > and I want to be able to invoke ndarray methods of an > object representing the data without making a separate > in-memory copy of it by calling PyTables Array.read().
I see. In that case, you way want to do your own wrapper to access/modify Array data (for example, by using the Array __getitem__/__setitem__ methods). > > If you want to transparently manage on-disk data as if it > > was in-memory, you may want to try memory-mapped arrays. > > That would be great. How do I use PyTables to get numpy > memmap access to the data for an ndarray in an HDF5 file? You can't. Memmapped NumPy arrays have their own way to access to disk, and it doesn't go through HDF5 at all. Cheers, -- Francesc Alted Freelance developer Tel +34-964-282-249 ------------------------------------------------------------------------- This SF.Net email is sponsored by the Moblin Your Move Developer's challenge Build the coolest Linux based applications with Moblin SDK & win great prizes Grand prize is a trip for two to an Open Source event anywhere in the world http://moblin-contest.org/redirect.php?banner_id=100&url=/ _______________________________________________ Pytables-users mailing list Pytables-users@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/pytables-users
