[SciPy-dev] [Numpy-discussion] New 0.4.2 beta release of scipy core

Arnd Baecker arnd.baecker at web.de
Thu Oct 13 08:24:06 CDT 2005

On Wed, 12 Oct 2005, Travis Oliphant wrote:

> I made another beta release of scipy core last night.   There are
> windows binaries for Python 2.4 and Python 2.3.   If you are already a
> user of scipy, the new __init__ file installed for newcore will break
> your current installation of scipy (but the problem with linalg,
> fftpack, and stats is no longer there).
> There have been many improvements:
> - bug fixes (including 64-bit fixes)
> - threading support fixes
> - optimizations
> - more random numbers (thanks Robert Kern).
> - more distutils fixes (thanks Pearu Peterson).
> More tests are welcome.    We are moving towards a release (but still
> need to get Masked Arrays working and all of scipy to build on top of
> the new scipy core before a full release).

Alright, on the Opteron with its 64 Bit all problems are gone.

A few observations:

- I installed it separately from the normal python (and old scipy)
  installation by
    `python setup.py install --prefix=$DESTDIR`

  This time I used gcc 3.4.4 and the installed packages end up in

  With gcc version 4.0.2 20050826 (prerelease) (SUSE Linux)
  they ended up in

  This is not a problem for me, but it might be worth knowing.

- _configtest.c: Several times one gets:

  gcc options: '-pthread -fno-strict-aliasing -DNDEBUG -g -O3 -Wall
  -Wstrict-prototypes -fPIC'
  compile options: '-Iscipy/base/src -I/scr/python/include/python2.4 -c'
  gcc: _configtest.c
  _configtest.c:3: warning: function declaration isn't a prototype
  _configtest.c: In function `main':
  _configtest.c:4: warning: statement with no effect
  _configtest.c:5: warning: control reaches end of non-void function
  gcc -pthread _configtest.o -lm -o _configtest

- scipy/corelib/mtrand/mtrand.c:
  Several warnings of the type:

  In function `__pyx_f_6mtrand_cont0_array':
  scipy/corelib/mtrand/mtrand.c:221: warning: assignment from incompatible
  pointer type

  (should I post the full list?)

- I can either use a non-optimized LAPACK or
  an optimized LAPACK (via atlas).

  Question: is there a python way to figure out which one is used by

  (Imagine the situation that I am dumped on a machine, installed
  by someone else, and to my surprise I find scipy installed,
  and now would like to know if it uses the fast libraries,
  like ATLAS, fftw, ... ?)
  ((scipy_distutils can only tell me which libraries
  are available at the time of running it, right?))

- Installing the new scipy on top of scipy_core works as well.

  However, it seems that none of the unit tests
  (e.g. for special)
  get copied to the installation directory

  They are there in the source directory,
  but not in the build directory and neither in the installation

OK, so much for now,


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