You may be able to avoid the tostring() overhead by using tofile(): s.tofile(gzip.open('compressed.dat', 'wb')) You are probably SOL on the mmapping, though. w On Fri, 9 Sep 2005, Joost van Evert wrote:
On Fri, 2005-09-09 at 15:06 -0500, John Hunter wrote:
> "Joost" == Joost van Evert <phjoost@gmail.com> writes:
Joost> is it possible to use compression while storing Joost> numarray/Numeric objects?
Sure
In [35]: s = rand(10000)
In [36]: file('uncompressed.dat', 'wb').write(s.tostring())
In [37]: ls -l uncompressed.dat -rw-r--r-- 1 jdhunter jdhunter 80000 2005-09-09 15:04 uncompressed.dat
In [38]: gzip.open('compressed.dat', 'wb').write(s.tostring())
In [39]: ls -l compressed.dat -rw-r--r-- 1 jdhunter jdhunter 41393 2005-09-09 15:04 compressed.dat
Thanks, this helps me, but I think not enough, because the arrays I work on are sometimes >1Gb(Correlation matrices). The tostring method would explode the size, and result in a lot of swapping. Ideally the compression also works with memmory mapped arrays.
Greets,
Joost
------------------------------------------------------- SF.Net email is Sponsored by the Better Software Conference & EXPO September 19-22, 2005 * San Francisco, CA * Development Lifecycle Practices Agile & Plan-Driven Development * Managing Projects & Teams * Testing & QA Security * Process Improvement & Measurement * http://www.sqe.com/bsce5sf _______________________________________________ Numpy-discussion mailing list Numpy-discussion@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/numpy-discussion