Hi, What version of MSVC are you using ?
If you really want to have an optimized version, don't use mingw (gcc is not up to date). Matthieu 2007/7/13, [EMAIL PROTECTED] < [EMAIL PROTECTED]>:
Hi, I am keen to evaluate numpy as an alternative to MATLAB for my PhD work and possible wider use within the department. To make a fairer comparison I wanted to build it with optimised ATLAS/LAPACK etc. hence building from source. I am running into some problems though. I am using Windows XP SP2, with latest Cygwin and I'm trying to follow the instructions on the wiki. Firstly, is what I'm trying possible? On the Installing Scipy/Windows page it says MinGW gcc and g77 are best supported, but also says to build against binary Python download you need to use MSVC. From http://boodebr.org/main/python/build-windows-extensions it seems building extensions with gcc is fine (and I built PyCrypto successfully as a test). So can I do what I am trying to do (build numpy/scipy on windows using cygwin without MSVC installed) against the downloaded Python distribution? If not, I can't find any resources about building Python from source on Windows using Cygwin, so it seems like I would be completely stuck. The next problem is that although I filled in the site.cfg file as documented (below), the setup.py script doesn't seem to pick it up and doesn't look in any of the specified directories. I can get around this by putting ATLAS/LAPACK libs in C:\, but obviously this isn't very satisfactory. Also is the entry for fftw correct? I couldn't find any information about this on the wiki. ------ [blas_opt] libraries = f77blas, cblas, atlas library_dirs = C:\cygwin\home\mqbxfri2\ATLAS\atlas_win32\lib include_dirs = C:\cygwin\home\mqbxfri2\ATLAS\atlas_win32\include # [lapack_opt] libraries = lapack, f77blas, cblas, atlas library_dirs = C:\cygwin\home\mqbxfri2\ATLAS\atlas_win32\lib include_dirs = C:\cygwin\home\mqbxfri2\ATLAS\atlas_win32\include [fftw] libraries = fftw3-3 library_dirs = "C:\fftw" ----- Following this there seem to be some more problems with the setup. "python setup.py build --compiler=mingw32" fails with: File "C:\cygwin\home\mqbxfri2\numpy_trunk\numpy\distutils\fcompiler\__init__.py", line 731, in _find_existing_fcompiler c.customize(dist) AttributeError: 'NoneType' object has no attribute 'customize' c is the result of the new_fcompiler function. "python setup.py config_fc --help-fcompiler" failes with: File "c:\Python25\lib\distutils\msvccompiler.py", line 270, in initialize "version of the compiler, but it isn't installed." % self.__product) distutils.errors.DistutilsPlatformError: Python was built with Visual Studio version 7.1, and extensions need to be built with the same version of the compiler, but it isn't installed. Although as I mentioned I can successfully build extensions with gcc. Reading through the help I saw that there is a "none" fcompiler type, so using that I get a bit further: "python setup.py build --compiler=mingw32 --fcompiler=none" run initially with build directory removed gives the same NoneType error, but then running it again the build appears to start. I then run into bug #220 http://projects.scipy.org/scipy/numpy/ticket/220: numpy\core\src\multiarraymodule.c: In function `initmultiarray': numpy\core\src\multiarraymodule.c:7563: error: `NPY_ALLOW_THREADS' undeclared (first use in this function) numpy\core\src\multiarraymodule.c:7563: error: (Each undeclared identifier is reported only once numpy\core\src\multiarraymodule.c:7563: error: for each function it appears in.) I would really appreciate any help to get this working. I understand building numpy doesn't require a fortran compiler, but scipy does. I am hoping to build scipy as well, so presumably the config system needs to recognise the cygwin g77 compiler for that to work? During the config I also see the following message: don't know how to compile Fortran code on platform 'nt' with 'gnu' compiler. Supported compilers are: absoft Does this mean it isn't possible to build scipy on Windows with Cygwin compilers? If I am eventually successful I would be happy to update the wiki with some more detailed instructions based on my experiences. Finally, I can't find any discussion of the relevant merits of ATLAS vs MKL, other than the different licensing. Is it expected that MKL performs better? Which is recommended? Thanks very much, Robin _______________________________________________ Numpy-discussion mailing list Numpy-discussion@scipy.org http://projects.scipy.org/mailman/listinfo/numpy-discussion
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