On Tue, 23 Oct 2012, wolf zinke wrote: > >Meanwhile, on your data, could you confirm that there is some variance > >in the obtained performances in a "good/lengthy" code, i.e. that values
> >np.std(distr_est.ca.dist_samples.samples[0], axis=1) > Thanks for the reply. Indeed, using a sphere_searchlight with the > Monte Carlo Testing, this gives me zeros only. This is a really nice one, i.e. the bug which is there "by design" so not that obvious from a first sight ;) Also good that it should not be relevant for 99% of other users since the constructs in this case are elaborate enough to not be too common ;) The reason for the observed abnormal behavior is the nproc > 1, when searchlights are parallelized. Then every child process acquires "a copy of numpy", including the state of its random number generator (RNG). That results in identical initial states of RNG in every one of those processes, leading to the same permutations, thus degenerate results in your case. quick resolution for you: set nproc=1 longer resolution for us: we would need to sacrifice "exact reproducibility of results with a single global seeding of RNG", i.e. mvpa2.seed() (or via MVPA_SEED environment variable). Every Permutator in this case should get its RNG randomly seeded (i.e. we should just use a new numpy.random.RandomState() in every one of them in _call, unless instructed explicitly otherwise). I have pushed an initial fix (only for Permutator, which is what important for your case here). More (I see at least a few of other similar spots) to follow + feeding rng in some of the tests -- Yaroslav O. Halchenko Postdoctoral Fellow, Department of Psychological and Brain Sciences Dartmouth College, 419 Moore Hall, Hinman Box 6207, Hanover, NH 03755 Phone: +1 (603) 646-9834 Fax: +1 (603) 646-1419 WWW: http://www.linkedin.com/in/yarik _______________________________________________ Pkg-ExpPsy-PyMVPA mailing list [email protected] http://lists.alioth.debian.org/cgi-bin/mailman/listinfo/pkg-exppsy-pymvpa
