Hi Alex,
In general, HDF5 files are very portable to many platforms and many
languages. Indeed, that is sort of the purpose behind the HDF Group.
While there are some incompatible edge cases, you sort of have to look for
them. Josh did a very good job of outlining the support for HDF5 across
the board. However, I would like to add that I have been using HDF5 /
PyTables for 3 - 4 years and have never had a compatibility issue.
Be Well
Anthony
On Mon, May 21, 2012 at 2:31 PM, Josh Ayers <josh.ay...@gmail.com> 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.
>
> 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.
>
> Hope that helps,
>
> Josh
>
>
> On Mon, May 21, 2012 at 10:12 AM, Alex Liberzon
> <alex.liber...@gmail.com>wrote:
>
>> Dear PyTables developers,
>>
>> Thanks for the great project.
>>
>> I would like to suggest to a small scientific community (Lagrangian
>> particle tracking velocimetry and numerical simulations of turbulent flows)
>> to start using PyTables as a common platform for exchanging of large
>> datasets (few gigas to tens of terabytes). The major advantage I see in the
>> great query and on-disk analysis capabilities that are not present in the
>> original HDF5. However, one major drawback from some of the groups is the
>> question of software: people work with C, C#, Fortran, Python, Matlab and
>> use a wide range of visualization software platforms. In order to get to a
>> common ground we need something that I couldn't find so far: C, Fortran
>> libraries to access PyTables HDF files created by this great Python
>> library. What are the suggestions? Does somebody have a similar experience
>> of sharing data between groups that do not use Python?
>>
>> Thank you,
>> Alex Liberzon
>> Turbulence Structure Laboratory
>> Tel Aviv University
>>
>>
>>
>>
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