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57dbc1b @rkern Fleshed-out site.cfg example.
rkern authored
1 # This file provides configuration information about non-Python dependencies for
2 # numpy.distutils-using packages. Create a file like this called "site.cfg" next
3 # to your package's setup.py file and fill in the appropriate sections. Not all
4 # packages will use all sections so you should leave out sections that your
5 # package does not use.
6
7 # The format of the file is that of the standard library's ConfigParser module.
8 #
9 # http://www.python.org/doc/current/lib/module-ConfigParser.html
10 #
11 # Each section defines settings that apply to one particular dependency. Some of
12 # the settings are general and apply to nearly any section and are defined here.
13 # Settings specific to a particular section will be defined near their section.
14 #
15 # libraries
16 # Comma-separated list of library names to add to compile the extension
17 # with. Note that these should be just the names, not the filenames. For
18 # example, the file "libfoo.so" would become simply "foo".
19 # libraries = lapack,f77blas,cblas,atlas
20 #
21 # library_dirs
22 # List of directories to add to the library search path when compiling
23 # extensions with this dependency. Use the character given by os.pathsep
24 # to separate the items in the list. On UN*X-type systems (Linux, FreeBSD,
25 # OS X):
26 # library_dirs = /usr/lib:/usr/local/lib
27 # On Windows:
28 # library_dirs = c:\mingw\lib,c:\atlas\lib
29 #
30 # include_dirs
31 # List of directories to add to the header file earch path.
32 # include_dirs = /usr/include:/usr/local/include
33 #
34 # src_dirs
35 # List of directories that contain extracted source code for the
36 # dependency. For some dependencies, numpy.distutils will be able to build
37 # them from source if binaries cannot be found. The FORTRAN BLAS and
38 # LAPACK libraries are one example. However, most dependencies are more
39 # complicated and require actual installation that you need to do
40 # yourself.
41 # src_dirs = /home/rkern/src/BLAS_SRC:/home/rkern/src/LAPACK_SRC
42 #
43 # search_static_first
44 # Boolean (one of (0, false, no, off) for False or (1, true, yes, on) for
45 # True) to tell numpy.distutils to prefer static libraries (.a) over
46 # shared libraries (.so). It is turned off by default.
47 # search_static_first = false
48
49 # Defaults
50 # ========
51 # The settings given here will apply to all other sections if not overridden.
52 # This is a good place to add general library and include directories like
53 # /usr/local/{lib,include}
54 #
55 #[DEFAULT]
56 #library_dirs = /usr/local/lib
57 #include_dirs = /usr/local/include
58
59 # Optimized BLAS and LAPACK
60 # -------------------------
61 # Use the blas_opt and lapack_opt sections to give any settings that are
62 # required to link against your chosen BLAS and LAPACK, including the regular
63 # FORTRAN reference BLAS and also ATLAS. Some other sections still exist for
64 # linking against certain optimized libraries (e.g. [atlas], [lapack_atlas]),
65 # however, they are now deprecated and should not be used.
66 #
67 # These are typical configurations for ATLAS (assuming that the library and
68 # include directories have already been set in [DEFAULT]; the include directory
69 # is important for the BLAS C interface):
70 #
71 #[blas_opt]
72 #libraries = f77blas, cblas, atlas
73 #
74 #[lapack_opt]
75 #libraries = lapack, f77blas, cblas, atlas
76 #
77 # If your ATLAS was compiled with pthreads, the names of the libraries might be
78 # different:
79 #
80 #[blas_opt]
81 #libraries = ptf77blas, ptcblas, atlas
82 #
83 #[lapack_opt]
84 #libraries = lapack, ptf77blas, ptcblas, atlas
85
86 # UMFPACK
87 # -------
88 # The UMFPACK library is used to factor large sparse matrices. It, in turn,
89 # depends on the AMD library for reordering the matrices for better performance.
90 # Note that the AMD library has nothing to do with AMD (Advanced Micro Devices),
91 # the CPU company.
92 #
93 # http://www.cise.ufl.edu/research/sparse/umfpack/
94 # http://www.cise.ufl.edu/research/sparse/amd/
95 #
96 #[amd]
97 #amd_libs = amd
98 #
99 #[umfpack]
100 #umfpack_libs = umfpack
101
102 # FFT libraries
103 # -------------
104 # There are two FFT libraries that we can configure here: FFTW (2 and 3) and djbfft.
105 #
106 # http://fftw.org/
107 # http://cr.yp.to/djbfft.html
108 #
109 # Given only this section, numpy.distutils will try to figure out which version
110 # of FFTW you are using.
111 #[fftw]
112 #libraries = fftw3
113 #
114 # For djbfft, numpy.distutils will look for either djbfft.a or libdjbfft.a .
115 #[djbfft]
116 #include_dirs = /usr/local/djbfft/include
117 #library_dirs = /usr/local/djbfft/lib
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