Re: [Numpy-discussion] numpy : your experiences?
> > In particular for the simulation yes, depending on the level of detail > > of course. But only parts, eg. random number generation for certain > > distributions had to be coded in C/C++. > > Are you saying you extended the scipy/numpy tools for this? > Do you think it would make sense to put some of that stuff on the wiki? No, this is very special to my application and not really numpy specific. I had to write a Metropolis-Hastings sampler, which worked in python but was too slow. I've coded this for a specific distribution in C++ and pass numpy arrays and python lists from and to C++ functions using boost::python. Bernhard ___ Numpy-discussion mailing list Numpy-discussion@scipy.org http://projects.scipy.org/mailman/listinfo/numpy-discussion
[Numpy-discussion] Numpy matrix and Blitz Matrix
Hi Everyone,
*) numpy arrays are automatically converted to blitz arrays. That's fine.
*) I need to work with blitz Matrix objects, but I noticed that
numpy matrix objects are not converted to them and I get a
compilation error too
3) Does someone on the list succeeded doing that?
Or is there a workaround to create quickly a blitz matrix object
from a numpy 2D array or numpy-matrix without wasting time
in casting operations?
It would be nice having an automatic translation of numpy.matrix to
blitz Matrix as matrices are used frequently in scientific computing.
Any suggestion or help would be very glad.
Paolo
#-- EXAMPLE CODE ---
import numpy
import scipy
#Dot product with arrays (it works)
x=numpy.array([[1,2,],[3,4]])
y=numpy.zeros((2,2))
scipy.weave.inline("""y=x*x;""",['x','y'],type_converters=weave.converters.blitz,compiler='gcc',force=1)
#Matrix multiplication with matrix (gives compilation error)
X=numpy.matlib.mat('1 2; 3 4')
Y=numpy.matlib.zeros((2,2))
scipy.weave.inline("""Y=X*X;""",['X','Y'],type_converters=weave.converters.blitz,compiler='gcc')
#
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[Numpy-discussion] Adding ACML support
Hi, I'm trying to get numpy work with AMD's MKL. The problem is that they not give a CBLAS interface, only the BLAS one. Can the numpy distutils check the existence of the cblas interface somewhere ? For the moment, it checks something with BLAS (but no actual testing takes place), but not CBLAS. Matthieu -- French PhD student Website : http://miles.developpez.com/ Blogs : http://matt.eifelle.com and http://blog.developpez.com/?blog=92 LinkedIn : http://www.linkedin.com/in/matthieubrucher ___ Numpy-discussion mailing list Numpy-discussion@scipy.org http://projects.scipy.org/mailman/listinfo/numpy-discussion
[Numpy-discussion] loadtxt bug?
In numpy.core.numeric.py you will find loadtxt, which uses the following:: line = line[:line.find(comments)].strip() I believe there is a bug here (when a line has no comment). To illustrate:: >>> line = "12345" >>> comments = "#" >>> line[:line.find(comments)] '1234' So I propose this should be:: try: line = line[:line.index(comments)].strip() except ValueError: line = line.strip() Am I right? Cheers, Alan Isaac ___ Numpy-discussion mailing list Numpy-discussion@scipy.org http://projects.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] numpy : your experiences?
On 17.11.2007, at 03:50, Rahul Garg wrote: > It would be awesome if you guys could respond to some of the following > questions : > a) Can you guys tell me briefly about the kind of problems you are > tackling with numpy and scipy? For me, NumPy is an important building block in a set of computational Python libraries that form the basis of my daily work in molecular simulations. The main building block is my Molecular Modelling Toolkit (http://dirac.cnrs-orleans.fr/MMTK/), but NumPy provides the basic data structure (arrays) for much of what MMTK does, and even more so for interfacing with the rest of the world. I don't use SciPy at all. > b) Have you ever felt that numpy/scipy was slow and had to switch to > C/C++/Fortran? There is some C code (and an increasing amount of Pyrex code) in my Python environment, and it is essential for good performance. However, in terms of code quantity, it is negligible. > c) Do you use any form of parallel processing? Multicores? SMPs? > Clusters? If yes how did u utilize them? All of them. I use threading (multicores and SMPs) in MMTK, and coarse-grained parallelization as implemented in ScientificPython for analyzing large data sets. ScientificPython has two parallel computing modules. The easiest to use implements a master-slave model in which a master process delegates computational tasks to an arbitrary (and possibly varying) number of slave processes: http://dirac.cnrs-orleans.fr/hg/ScientificPython/main/file/ 73cc270217fc/Examples/master_slave_demo.py The other parallelization package is based on the BSP model of parallel computing: http://dirac.cnrs-orleans.fr/hg/ScientificPython/main/file/ 73cc270217fc/Examples/BSP/ http://dirac.cnrs-orleans.fr/ScientificPython/ScientificPythonManual/ It probably has a steeper learning curve, but it is suitable for more complex parallel programs because it permits the construction of parallel libraries. Konrad. -- - Konrad Hinsen Centre de Biophysique Moléculaire, CNRS Orléans Synchrotron Soleil - Division Expériences Saint Aubin - BP 48 91192 Gif sur Yvette Cedex, France Tel. +33-1 69 35 97 15 E-Mail: [EMAIL PROTECTED] - ___ Numpy-discussion mailing list Numpy-discussion@scipy.org http://projects.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] loadtxt bug?
On Thu, Nov 22, 2007 at 11:14:07PM -0500, Alan G Isaac wrote: > In numpy.core.numeric.py you will find loadtxt, which uses > the following:: > line = line[:line.find(comments)].strip() > I believe there is a bug here (when a line has no comment). > To illustrate:: > >>> line = "12345" > >>> comments = "#" > >>> line[:line.find(comments)] > '1234' Unless you are sure that line always ends with a "\n". This is the case in the code you are refering too. Unless I am missing some thing. Gaël ___ Numpy-discussion mailing list Numpy-discussion@scipy.org http://projects.scipy.org/mailman/listinfo/numpy-discussion
