Hi, you can probably use PyTables for this. Even though it's meant to save/load data to/from disk (in HDF5 format) as far as I understand, it can be used to make your task solvable - even on a 32bit system !! It's free (pytables.org) -- so maybe you can try it out and tell me if I'm right .... Or someone else here would know right away...
Cheers, Sebastian Haase On Wed, Sep 9, 2009 at 6:19 AM, Sturla Molden<stu...@molden.no> wrote: > Daniel Platz skrev: >> data1 = numpy.zeros((256,2000000),dtype=int16) >> data2 = numpy.zeros((256,2000000),dtype=int16) >> >> This works for the first array data1. However, it returns with a >> memory error for array data2. I have read somewhere that there is a >> 2GB limit for numpy arrays on a 32 bit machine but shouldn't I still >> be below that? I use Windows XP Pro 32 bit with 3GB of RAM. > > There is a 2 GB limit for user space on Win32, this is about 1.9 GB. You > have other programs running as well, so this is still too much. Also > Windows reserves 50% of RAM for itself, so you have less than 1.5 GB to > play with. > > S.M. > > _______________________________________________ > NumPy-Discussion mailing list > NumPy-Discussion@scipy.org > http://mail.scipy.org/mailman/listinfo/numpy-discussion > _______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
