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157 lines
6.2 KiB
INI
157 lines
6.2 KiB
INI
# This file provides configuration information about non-Python dependencies for
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# numpy.distutils-using packages. Create a file like this called "site.cfg" next
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# to your package's setup.py file and fill in the appropriate sections. Not all
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# packages will use all sections so you should leave out sections that your
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# package does not use.
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# To assist automatic installation like easy_install, the user's home directory
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# will also be checked for the file ~/.numpy-site.cfg .
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# The format of the file is that of the standard library's ConfigParser module.
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#
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# http://www.python.org/doc/current/lib/module-ConfigParser.html
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#
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# Each section defines settings that apply to one particular dependency. Some of
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# the settings are general and apply to nearly any section and are defined here.
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# Settings specific to a particular section will be defined near their section.
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#
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# libraries
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# Comma-separated list of library names to add to compile the extension
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# with. Note that these should be just the names, not the filenames. For
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# example, the file "libfoo.so" would become simply "foo".
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# libraries = lapack,f77blas,cblas,atlas
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#
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# library_dirs
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# List of directories to add to the library search path when compiling
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# extensions with this dependency. Use the character given by os.pathsep
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# to separate the items in the list. Note that this character is known to
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# vary on some unix-like systems; if a colon does not work, try a comma.
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# This also applies to include_dirs and src_dirs (see below).
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# On UN*X-type systems (OS X, most BSD and Linux systems):
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# library_dirs = /usr/lib:/usr/local/lib
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# On Windows:
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# library_dirs = c:\mingw\lib,c:\atlas\lib
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# On some BSD and Linux systems:
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# library_dirs = /usr/lib,/usr/local/lib
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#
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# include_dirs
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# List of directories to add to the header file earch path.
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# include_dirs = /usr/include:/usr/local/include
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#
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# src_dirs
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# List of directories that contain extracted source code for the
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# dependency. For some dependencies, numpy.distutils will be able to build
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# them from source if binaries cannot be found. The FORTRAN BLAS and
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# LAPACK libraries are one example. However, most dependencies are more
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# complicated and require actual installation that you need to do
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# yourself.
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# src_dirs = /home/rkern/src/BLAS_SRC:/home/rkern/src/LAPACK_SRC
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#
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# search_static_first
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# Boolean (one of (0, false, no, off) for False or (1, true, yes, on) for
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# True) to tell numpy.distutils to prefer static libraries (.a) over
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# shared libraries (.so). It is turned off by default.
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# search_static_first = false
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# Defaults
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# ========
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# The settings given here will apply to all other sections if not overridden.
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# This is a good place to add general library and include directories like
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# /usr/local/{lib,include}
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#
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#[DEFAULT]
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#library_dirs = /usr/local/lib
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#include_dirs = /usr/local/include
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# Atlas
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# -----
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# Atlas is an open source optimized implementation of the BLAS and Lapack
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# routines. Numpy will try to build against Atlas by default when available in
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# the system library dirs. To build numpy against a custom installation of
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# Atlas you can add an explicit section such as the following. Here we assume
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# that Atlas was configured with ``prefix=/opt/atlas``.
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#
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# [atlas]
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# library_dirs = /opt/atlas/lib
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# include_dirs = /opt/atlas/include
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# OpenBLAS
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# --------
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# OpenBLAS is another open source optimized implementation of BLAS and Lapack
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# and can be seen as an alternative to Atlas. To build numpy against OpenBLAS
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# instead of Atlas, use this section instead of the above, adjusting as needed
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# for your configuration (in the following example we installed OpenBLAS with
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# ``make install PREFIX=/opt/OpenBLAS``.
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#
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# **Warning**: OpenBLAS, by default, is built in multithreaded mode. Due to the
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# way Python's multiprocessing is implemented, a multithreaded OpenBLAS can
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# cause programs using both to hang as soon as a worker process is forked on
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# POSIX systems (Linux, Mac).
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# This is fixed in Openblas 0.2.9 for the pthread build, the OpenMP build using
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# GNU openmp is as of gcc-4.9 not fixed yet.
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# Python 3.4 will introduce a new feature in multiprocessing, called the
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# "forkserver", which solves this problem. For older versions, make sure
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# OpenBLAS is built using pthreads or use Python threads instead of
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# multiprocessing.
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# (This problem does not exist with multithreaded ATLAS.)
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#
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# http://docs.python.org/3.4/library/multiprocessing.html#contexts-and-start-methods
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# https://github.com/xianyi/OpenBLAS/issues/294
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#
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[openblas]
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libraries = openblas
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library_dirs = /usr/lib
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include_dirs = /usr/include
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# MKL
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#----
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# MKL is Intel's very optimized yet proprietary implementation of BLAS and
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# Lapack.
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# For recent (9.0.21, for example) mkl, you need to change the names of the
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# lapack library. Assuming you installed the mkl in /opt, for a 32 bits cpu:
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# [mkl]
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# library_dirs = /opt/intel/mkl/9.1.023/lib/32/
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# lapack_libs = mkl_lapack
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#
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# For 10.*, on 32 bits machines:
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# [mkl]
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# library_dirs = /opt/intel/mkl/10.0.1.014/lib/32/
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# lapack_libs = mkl_lapack
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# mkl_libs = mkl, guide
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# UMFPACK
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# -------
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# The UMFPACK library is used in scikits.umfpack to factor large sparse matrices.
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# It, in turn, depends on the AMD library for reordering the matrices for
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# better performance. Note that the AMD library has nothing to do with AMD
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# (Advanced Micro Devices), the CPU company.
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#
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# UMFPACK is not needed for numpy or scipy.
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#
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# http://www.cise.ufl.edu/research/sparse/umfpack/
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# http://www.cise.ufl.edu/research/sparse/amd/
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# http://scikits.appspot.com/umfpack
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#
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#[amd]
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#amd_libs = amd
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#
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#[umfpack]
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#umfpack_libs = umfpack
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# FFT libraries
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# -------------
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# There are two FFT libraries that we can configure here: FFTW (2 and 3) and djbfft.
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# Note that these libraries are not needed for numpy or scipy.
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#
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# http://fftw.org/
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# http://cr.yp.to/djbfft.html
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#
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# Given only this section, numpy.distutils will try to figure out which version
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# of FFTW you are using.
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#[fftw]
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#libraries = fftw3
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#
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# For djbfft, numpy.distutils will look for either djbfft.a or libdjbfft.a .
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#[djbfft]
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#include_dirs = /usr/local/djbfft/include
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#library_dirs = /usr/local/djbfft/lib
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