A Friday 30 January 2009, David Froger escrigué: > ok for f2py! > > > Otherwise, you will have to figure out how your Fortran program > > writes the file. I.e. what padding, metainformation, etc. that are > > used. If you switch Fortran compiler, or even compiler version from > > the same vendor, you must start over again. > > In my experience, I never had this kind of problem. I just have to > convert files between big/little endian with uswap > (http://linux.die.net/man/1/uswap), but I never see, in my > experience, a Fortran program writting data differently given the > compilator. > > >For my own work, I just makes sure NEVER to do any I/O in Fortran! > > It is asking for trouble. I leave the I/O to Python or C, where it > > belongs. That way I know what data are written and what data are > > read. > > Unfortunately., binary files are mandatory in the contex I work. I > use a scientific code written in Fortran to compute fluid dynamics. > Typically the simulation is run on supercalculator and generate giga > and giga of datum, so we must use the binary format, which recquire > less memory for the stockage. Then, I like to post-trait the datum > using Python and Gnuplot.py. > > That's why I'm looking for a performantant, easy and 'standard' way > to read binary Fortran files. (I think many people have the same > need).
If you need to compact your datafiles to a maximum, you may want to write your data with the HDF5 library [1] that, besides using a binary format, it allows on-the-flight compression. HDF5 is a fairly growing standard in scientific computing and it has wrappers for the most important languages like C, Fortran, Java and, of course, Python ;-) In particular, the available HDF5 interfaces to Python allows to read/write HDF5 native files very easily. Also, many computational environments, like Matlab, Octave or IDL do support HDF5 files. [1] http://www.hdfgroup.org/HDF5/ Cheers, -- Francesc Alted _______________________________________________ Numpy-discussion mailing list [email protected] http://projects.scipy.org/mailman/listinfo/numpy-discussion
