2014-08-21 22:17 GMT+02:00 Daniel Wheeler <daniel.wheel...@gmail.com>:
> On Wed, Aug 20, 2014 at 6:12 PM, Seufzer, William J. (LARC-D307) < > bill.seuf...@nasa.gov> wrote: > >> Thanks Dan, >> >> This works... but I also made the change to nonUniformGrid3D.py as well. >> I noticed the simple edits, made them by hand, and re-installed FiPY in >> both environments. >> > > I missed that. Thanks for pointing it out. > > >> >> Just a note (mainly for anyone else who runs into this): >> >> Any data files created with the old code will still not be readable with >> this code update in the non-Trilinos environment. Both environments need to >> have the updated code. >> >> Hope I stated that clearly! >> > > > In my experience, pickling doesn't work very well for long term or medium > term data storage. For medium/short term storage (life time of a project) I > always just save the numpy arrays (not with pickle, but with Pandas or > numpy.savetxt), but not the FiPy objects to avoid the kinds of problems > that you're having. I don't currently have a good solution for long term > data storage. > For long term storage, specific serialize and deserialize methods are needed. In text format for very long term (over OS and arch boundaries) For example, boost serialize in C++ classes ( http://www.boost.org/doc/libs/1_56_0/libs/serialization/doc/index.html ). Easy to add in C++ to a class. For python, working on top of json https://docs.python.org/2/library/json.html seems like the way to go. Benny > > -- > Daniel Wheeler > > _______________________________________________ > fipy mailing list > fipy@nist.gov > http://www.ctcms.nist.gov/fipy > [ NIST internal ONLY: https://email.nist.gov/mailman/listinfo/fipy ] > >
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