On 5/21/12 9:31 PM, Josh Ayers wrote:
> Hi Alex,
>
> Reading a PyTables file in another platform should be easy, as long as 
> you use a compression library that is supported on both platforms.  
> The most widely available is likely to be zlib, since it is included 
> in the pre-built binaries available from the HDF group's website.  
> There are C and Fortran versions available here: 
> http://www.hdfgroup.org/HDF5/release/obtain5.html.  It looks like 
> there's also a partial .NET wrapper of the library here: http://hdf5.net/.
>
> Recent versions of Matlab also have support for HDF5 (the v7.3 
> "mat-file" format is based on it).  Since I have it available, I just 
> verified that Matlab R2011b can read PyTables files in uncompressed 
> and zlib compressed formats, using Matlab's h5read function.  It 
> failed when the PyTables file was compressed with bzip2, lzo, or 
> blosc.  I only tested it with a PyTables table, which is read into 
> Matlab as a struct.

Blosc is prepared to interact with the generic HDF5 library, so your 
current HDF5 applications can read datasets compressed with it.  But you 
need to re-compile your HDF5 library for getting this support:

https://github.com/FrancescAlted/blosc/tree/master/hdf5


>
> As far as writing files on another platform and then reading them in 
> PyTables, that will be a little more difficult.  There are certain 
> HDF5 attributes that are required by PyTables on each group and 
> dataset.  All the details are documented here: 
> http://pytables.github.com/usersguide/file_format.html.

Nope.  These attributes are not required, they are optional.  PyTables 
generally makes a good job at accessing HDF5 without this info.  FYI, 
these attributes are a superset of the High Level HDF5 library:

http://www.hdfgroup.org/HDF5/hdf5_hl/

-- 
Francesc Alted


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