[Numpy-discussion] distutils data_files target

Hi, I noticed that plain distutils and numpy.distutils differ in where they put the files specified with the keyword 'data_files' ( at least on windows XP). With distutils they go to 'PREFIX' and with numpy.distutils they go to 'PLATLIB', i.e. relative to the package installation directory. I gues

Re: [Numpy-discussion] Matrices for testing

On 10/26/06, jeremito <[EMAIL PROTECTED]> wrote: Hmmm.  I guess I'll have to find another way to get some"standard/well-known" matrices to work with.  Thanks for your help.Well if all you want is some matrices, there's nothing stopping you from grabbing the matrices in the LAPACK distribution and u

Re: [Numpy-discussion] Matrices for testing

Robert Kern wrote: > Robert Kern wrote: > > jeremito wrote: > >> If I understand correctly, the LAPACK package has some standard > >> matrices included with it for testing. Does the linalg portion of > >> numpy also have access to these matrices/arrays? > > > > No. > > To clarify, these are routi

Re: [Numpy-discussion] Matrices for testing

Robert Kern wrote: > jeremito wrote: >> If I understand correctly, the LAPACK package has some standard >> matrices included with it for testing. Does the linalg portion of >> numpy also have access to these matrices/arrays? > > No. To clarify, these are routines provided with the LAPACK sourc

Re: [Numpy-discussion] Matrices for testing

jeremito wrote: > If I understand correctly, the LAPACK package has some standard > matrices included with it for testing. Does the linalg portion of > numpy also have access to these matrices/arrays? No. -- Robert Kern "I have come to believe that the whole world is an enigma, a harmless en

[Numpy-discussion] Matrices for testing

If I understand correctly, the LAPACK package has some standard matrices included with it for testing. Does the linalg portion of numpy also have access to these matrices/arrays? Thanks, Jeremy - Using Tomcat but need to d

Re: [Numpy-discussion] lexsort in numpy crashing on strings

Thanks Robert.  Will do.On 10/25/06, Robert Kern <[EMAIL PROTECTED]> wrote: Tom Denniston wrote:> Hi, I've been using the lexsort and it is really nice.  Much simpler and> faster than the implementation I had before.   The only problem is it> seems  to crash on strings.> > Do I just need to upgrade

[Numpy-discussion] Still a ticket 112 "check_longfloat_repr" issue on OSX

OS X 10.4, PPC In [5]: import numpy as N In [6]: N.__version__ Out[6]: '1.0.1.dev3399' In [7]: print N.longfloat(0).itemsize 16 In [8]: a = N.exp(N.array([1000],dtype=N.longfloat)) In [9]: print str(a) [inf] In [10]: print str(a[0]) inf In [11]: print a.itemsize 16 ---

Re: [Numpy-discussion] f2py g3 question

Pearu, Fantastic, I will try this out. Thanks for your work on this. Brian On 10/25/06, [EMAIL PROTECTED] <[EMAIL PROTECTED]> wrote: > > On Wed, 25 Oct 2006, Brian Granger wrote: > > > HI, > > > > I have noticed that Pearu has been doing lots of work on f2py g3. I > > have heard that this will

Re: [Numpy-discussion] f2py g3 question

On Wed, 25 Oct 2006, Brian Granger wrote: > HI, > > I have noticed that Pearu has been doing lots of work on f2py g3. I > have heard that this will have support for derived types. What is the > status of this work? Is is ready for public use? Are the derived > types implemented? Thanks! At

Re: [Numpy-discussion] lexsort in numpy crashing on strings

Tom Denniston wrote: > Hi, I've been using the lexsort and it is really nice. Much simpler and > faster than the implementation I had before. The only problem is it > seems to crash on strings. > > Do I just need to upgrade numpy or is it a current bug? Upgrade numpy. I believe this bug has

[Numpy-discussion] lexsort in numpy crashing on strings

Hi, I've been using the lexsort and it is really nice.  Much simpler and faster than the implementation I had before.   The only problem is it seems  to crash on strings.Do I just need to upgrade numpy or is it a current bug?    In [2]: import numpy    nu    In [3]: numpy.array(['a', 'b', 'c'])  

[Numpy-discussion] f2py g3 question

HI, I have noticed that Pearu has been doing lots of work on f2py g3. I have heard that this will have support for derived types. What is the status of this work? Is is ready for public use? Are the derived types implemented? Thanks! Brian ---

Re: [Numpy-discussion] PyDX - announcement

On Oct 22, 2006, at 17:38 , Simon Burton wrote: > > Apologies if this is too off-topic for these lists, but > I hope some people here find this interesting! It looks very nifty. Interval arithmetic for rigourous bounds is something that should be used more often, I think. You should add it to t

Re: [Numpy-discussion] Cross compilation

On Oct 22, 2006, at 22:05 , Jeremy R. Fishman wrote: > Hi, I was wondering if anyone can give me some advice on how to go > about cross-compiling NumPy. I have been searching around and > can't find any support in distutils for cross compilation. Is > there some way I can still compile Num

[Numpy-discussion] LAPACK warning on FC2

FYI, I got the following warning building numpy-1.0 from sources on a FC2 box, using distribution provided blas and lapack rpm's. $ rpm -q blas blas-3.0-24.1 $ rpm -q lapack lapack-3.0-24.1 $ python setup.py build > build.log Running from numpy source directory. /u/dalcinl/Build/Python/numpy-1.0

Re: [Numpy-discussion] indexing with arrays of indexes and +=

[snip]Vincent, I may be wrong, but it looks like you could use a weighted histogramdd (see other thread where I sent a patch to do so).You run it once to find the number of sample in each bin, then again with weights=value, normed=False to find the total weight in each bin, then you can divide each

[Numpy-discussion] numpy.distutils Intel Visual Fortran detection

Hello all I'm trying to get SciPy compiling with MSVC and the Intel Visual Fortran compiler, version 9.1. I'm running into problems with the version detection code failing. The current version_cmd in intel.py is: 'version_cmd' : [fc_exe, "-FI -V -c %(fname)s.f -o %(fname)s.o" \

Re: [Numpy-discussion] A way to compute a 2d histogram

Nicolas, thanks for the bug report, I fooled around with argument passing and should have checked every case. You'll find the histogram function that deals with weights on the numpy trac ticket 189,I'm waiting for some hints as to where the histogram function should reside (numpy.histogram, numpy.

[Numpy-discussion] classgrect

Fricke include tom Petty Jayhawks Gary Louris himself of Byrds mr ed. Fricke include tom Petty Jayhawks Gary Louris himself of Byrds mr ed. Messages this a dictfiltc elcido cc such directory Error make in utils or problem crypt routine libc operating linkers in tendto strict boneheaded than

Re: [Numpy-discussion] A way to compute a 2d histogram

Hi, it would be great if you could add the weight option in the 1D histogram too. Nicolas David Huard a écrit : > Xavier, > Here is the patch against svn. Please report any bug. I haven't had > the time to test it extensively, something that should be done before > commiting the patch to

Re: [Numpy-discussion] A way to compute a 2d histogram

Hi, there is a problem when using this patch of numpy.histogram2d. I've tried: a=pylab.rand(10) numpy.histogram2d(a,a) and there is an exception (exceptions.AttributeError) in numpy.histogramdd function called by numpy.histogram2d. But numpy.histogram2d(a,a,bins=[10,10]) works. So I'v

Re: [Numpy-discussion] vectorize pitfall

On 25/10/06, Travis Oliphant <[EMAIL PROTECTED]> wrote: > It takes old "type-codes" as one big string so you say > > vectorize(f,otypes='d') > > This should be modernized to handle a list of dtype objects. > > I've fixed vectorize in SVN. Thanks! A. M. Archibald

Re: [Numpy-discussion] vectorize pitfall

A. M. Archibald wrote: > Hi, > > Vectorize is a very handy function, but it has at least one pitfall: > > def f(x): > if 1.3 return sqrt(x) > else: > return 0 > > Now vectorize(f)(2)=1.41421356237 but vectorize(f)(array([1,2]))=array([0,1]). > > The problem is that, when giv

Re: [Numpy-discussion] can this be made faster?

Andreas Eisele wrote: > Recently, there were several requests and discussions on this list about > how to > increment an array a in cells pointed to from a second integer array b > (optionally by > values from a third array c), such as: > > >> Yes, that'd be >> a[b] += c >> >> On 10/8

[Numpy-discussion] vectorize pitfall

Hi, Vectorize is a very handy function, but it has at least one pitfall: def f(x): if 1.3http://sel.as-us.falkag.net/sel?cmd=lnk&kid=120709&bid=263057&dat=121642 ___ Numpy-discussion mailing list Numpy-discussion@lists.sourceforge.net https://lists.

Re: [Numpy-discussion] can this be made faster?

Recently, there were several requests and discussions on this list about how to increment an array a in cells pointed to from a second integer array b (optionally by values from a third array c), such as: > Yes, that'd be > a[b] += c > > On 10/8/06, Daniel Mahler <[EMAIL PROTECTED]> wro

Re: [Numpy-discussion] indexing with arrays of indexes and +=

David Huard wrote: > 2006/10/24, Vincent Schut <[EMAIL PROTECTED] > >: > > It is clear to me that the numpy += operator in combination with > the use > of arrays of indexes, as is explained in the Tentative Numpy Tutorial > ( > > http://www.scipy.org/