Re: [SciPy-user] Problem with scipy.optimize.leastsq: Improper input parameters
OK... follow-up... can anyone help me re-compile __minpack.h with the patch in place? I have no idea how to do it, and I can't get scipy itself to compile, I think because it's failing a lot of dependencies. I installed scipy from a .deb package originally, not from source, and I'm really not sure whether it will be worse to try to resolve all those dependencies or just work around the problem. Thanks, Adam
Hi,I hope this is the right mailing list.I need to perform matrix multiplication with big matrices and I realized that numpy is much slower with compared to matlab? does anyone know why?for example to multiply two perform this calculationa= matrix 2000x10000b= matrix 10000x2000c=a x b (c matrix 2000 x 2000)it takes roughly 100-300 sec, depending on the pc...while on matlab it is almost instantaneous...what can I do?This is my python installation:Python 2.5.1 (r251:54863, Mar 7 2008, 04:10:12) [GCC 4.1.3 20070929 (prerelease) (Ubuntu 4.1.2-16ubuntu2)] on linux2 Type "help", "copyright", "credits" or "license" for more information.
import numpy numpy.__version__ '1.0.3'
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In my experience numpy can be _much_ faster than matlab. Do you have a code snippet? Furthermore, did you compile numpy on your machine and with what? Do you have a fortran compiler? Something sounds fishy because I've multiplied much larger matrices in no time at all eg. your example x100. You may have not linked the BLAS or ATLAS libs during compile time. Even writing a raw python function to multiple matrices of the size your dealing with should take less time. 1. Make sure you linked BLAS or ATLAS as well as compilers check the config file 2. A code snippet of how went about this would help. 3. Pick up a copy of the numpy manual. HTH, Conor On Thu, Mar 27, 2008 at 10:32 AM, Chiara Caronna <chiaracaronna@hotmail.com> wrote:
Hi,I hope this is the right mailing list.I need to perform matrix multiplication with big matrices and I realized that numpy is much slower with compared to matlab? does anyone know why?for example to multiply two perform this calculationa= matrix 2000x10000b= matrix 10000x2000c=a x b (c matrix 2000 x 2000)it takes roughly 100-300 sec, depending on the pc...while on matlab it is almost instantaneous...what can I do?This is my python installation:Python 2.5.1 (r251:54863, Mar 7 2008, 04:10:12) [GCC 4.1.3 20070929 (prerelease) (Ubuntu 4.1.2-16ubuntu2)] on linux2 Type "help", "copyright", "credits" or "license" for more information.
import numpy numpy.__version__ '1.0.3'
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Conor Robinson wrote:
In my experience numpy can be _much_ faster than matlab.
For matrix multiplication, relative speed between matlab and numpy will mostly depend on the blas. Up to 6.5 at least, matlab used atlas, which means that numpy should be as fast, if not faster (if you compiled ATLAS by yourself). Here, the problem is that the debian package does not use ATLAS for numpy.dot, I think. If you build numpy by yourself, the problem is easy to fix, and that's what I would recomment if speed really is an issue. But for packages, it is not so easy to fix, because numpy.dot uses the cblas interface. Not all BLAS implementations have a CBLAS implementation, which is problematic since debian packages have to use the lowest common interface between all the available BLAS. It may be possible to use the BLAS interface instead as well in numpy, which is the best solution I think in the mid-term, but this requires someone to step in to do the work. cheers, David
participants (4)
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Adam Ginsburg -
Chiara Caronna -
Conor Robinson -
David Cournapeau