On 1/13/07, Sebastian Haase <[EMAIL PROTECTED]> wrote: > On 1/13/07, Keith Goodman <[EMAIL PROTECTED]> wrote: > > On 1/13/07, Sebastian Haase <[EMAIL PROTECTED]> wrote: > > > On 1/13/07, Keith Goodman <[EMAIL PROTECTED]> wrote: > > > > On 1/11/07, Robert Kern <[EMAIL PROTECTED]> wrote: > > > > > Keith Goodman wrote: > > > > > > Why is the first element of the permutation always the same? Am I > > > > > > using random.permutation in the right way? > > > > > > > > > > >>> M.__version__ > > > > > > '1.0rc1' > > > > > > > > > > This has been fixed in more recent versions. > > > > > > > > > > http://projects.scipy.org/scipy/numpy/ticket/374 > > > > > > > > I don't see any unit tests for numpy.random. I guess randomness is hard > > > > to test. > > > > > > > > Would it help to seed the random number generator and at least check > > > > that you get the same result you got before? No existing problems > > > > would be found. But new ones might be caught. > > > > > > > Hi, > > > Is it guaranteed that a given seed produces the same sequence of > > > rand-number between different platforms ? > > > I thought this might only be guaranteed for "any given computer" to > > > reproduce the same numbers. > > > > I hope, and expect, that it is system independent. > > > > Here's what I get: > > > > >> rs = numpy.random.RandomState([123, 901, 789]) > > >> rs.randn(4,1) > > > > array([[ 0.76072026], > > [ 1.27712191], > > [ 0.03497453], > > [ 0.09056668]]) > > >> rs.rand(4,1) > > > > array([[ 0.184306 ], > > [ 0.58967936], > > [ 0.52425903], > > [ 0.33389408]]) > > >> numpy.__version__ > > '1.0.1' > > > > Linux kel 2.6.18-3-686 #1 SMP Mon Dec 4 16:41:14 UTC 2006 i686 GNU/Linux > import numpy > rs = numpy.random.RandomState([123, 901, 789]) > rs.randn(4,1) > [[ 0.76072026] > [ 1.27712191] > [ 0.03497453] > [ 0.09056668]] > rs.rand(4,1) > [[ 0.184306 ] > [ 0.58967936] > [ 0.52425903] > [ 0.33389408]] > numpy.__version__ > '1.0rc1' > > Windows XP- pentium4 - (non current numpy) - > > Looks promising - but how about PowerPC macs ...
The random numbers are generated by a fixed algorithm. So they are not random at all. As long as everyone is using float64 I would think we'd all get the same (pseudo) random numbers. _______________________________________________ Numpy-discussion mailing list Numpy-discussion@scipy.org http://projects.scipy.org/mailman/listinfo/numpy-discussion
