| # This file provides configuration information about non-Python dependencies for |
| # numpy.distutils-using packages. Create a file like this called "site.cfg" next |
| # to your package's setup.py file and fill in the appropriate sections. Not all |
| # packages will use all sections so you should leave out sections that your |
| # package does not use. |
| |
| # To assist automatic installation like pip, the user's home directory |
| # will also be checked for the file ~/.numpy-site.cfg . |
| |
| # The format of the file is that of the standard library's ConfigParser module. |
| # No interpolation is allowed; the RawConfigParser class is being used to load it. |
| # |
| # https://docs.python.org/library/configparser.html |
| # |
| # Each section defines settings that apply to one particular dependency. Some of |
| # the settings are general and apply to nearly any section and are defined here. |
| # Settings specific to a particular section will be defined near their section. |
| # |
| # libraries |
| # Comma-separated list of library names to add to compile the extension |
| # with. Note that these should be just the names, not the filenames. For |
| # example, the file "libfoo.so" would become simply "foo". |
| # libraries = lapack,f77blas,cblas,atlas |
| # This setting is available for *all* sections. |
| # |
| # library_dirs |
| # List of directories to add to the library search path when compiling |
| # extensions with this dependency. Use the character given by os.pathsep |
| # to separate the items in the list. Note that this character is known to |
| # vary on some unix-like systems; if a colon does not work, try a comma. |
| # This also applies to include_dirs. |
| # On UN*X-type systems (OS X, most BSD and Linux systems): |
| # library_dirs = /usr/lib:/usr/local/lib |
| # On Windows: |
| # library_dirs = c:\mingw\lib,c:\atlas\lib |
| # On some BSD and Linux systems: |
| # library_dirs = /usr/lib,/usr/local/lib |
| # |
| # include_dirs |
| # List of directories to add to the header file search path. |
| # include_dirs = /usr/include:/usr/local/include |
| # |
| # search_static_first |
| # Boolean (one of (0, false, no, off) for False or (1, true, yes, on) for |
| # True) to tell numpy.distutils to prefer static libraries (.a) over |
| # shared libraries (.so). It is turned off by default. |
| # search_static_first = false |
| # |
| # runtime_library_dirs/rpath |
| # List of directories that contains the libraries that should be |
| # used at runtime, thereby disregarding the LD_LIBRARY_PATH variable. |
| # See 'library_dirs' for formatting on different platforms. |
| # runtime_library_dirs = /opt/blas/lib:/opt/lapack/lib |
| # or equivalently |
| # rpath = /opt/blas/lib:/opt/lapack/lib |
| # |
| # extra_compile_args |
| # Add additional arguments to the compilation of sources. |
| # Split into arguments in a platform-appropriate way. |
| # Provide a single line with all complete flags. |
| # extra_compile_args = -g -ftree-vectorize |
| # |
| # extra_link_args |
| # Add additional arguments when libraries/executables |
| # are linked. |
| # Split into arguments in a platform-appropriate way. |
| # Provide a single line with all complete flags. |
| # extra_link_args = -lgfortran |
| # |
| |
| # Defaults |
| # ======== |
| # The settings here will apply to all sections as general defaults |
| # This is a good place to add general library and include directories like |
| # /usr/local/{lib,include} |
| # These settings apply when they are not overridden in the sections below. |
| # Note that the standard paths (e.g. `/usr/lib`) are not searched if you |
| # override these settings, unless they are explicitly included. |
| # The ``:`` is os.pathsep, which is ``;`` on windows |
| #[DEFAULT] |
| #library_dirs = /usr/local/lib64:/usr/local/lib:/usr/lib64:/usr/lib |
| #include_dirs = /usr/local/include:/usr/include |
| |
| |
| # ATLAS |
| # ----- |
| # ATLAS is an open source optimized implementation of the BLAS and LAPACK |
| # routines. NumPy will try to build against ATLAS when available in |
| # the system library dirs (and OpenBLAS, MKL and BLIS are not installed). To |
| # build NumPy against a custom installation of ATLAS you can add an explicit |
| # section such as the following. Here we assume that ATLAS was configured with |
| # ``prefix=/opt/atlas``. |
| # |
| # [atlas] |
| # library_dirs = /opt/atlas/lib |
| # include_dirs = /opt/atlas/include |
| |
| # OpenBLAS |
| # -------- |
| # OpenBLAS is an open source optimized implementation of BLAS and LAPACK |
| # and is the default choice for NumPy itself (CI, wheels). OpenBLAS will be |
| # selected above ATLAS and Netlib BLAS/LAPACK. OpenBLAS is generically |
| # installed as a shared library, to force the OpenBLAS library linked to also |
| # be used at runtime you can utilize the runtime_library_dirs variable. |
| # |
| # [openblas] |
| # libraries = openblas |
| # library_dirs = /opt/OpenBLAS/lib |
| # include_dirs = /opt/OpenBLAS/include |
| # runtime_library_dirs = /opt/OpenBLAS/lib |
| |
| # OpenBLAS (64-bit with suffix) |
| # ----------------------------- |
| # OpenBLAS can be compiled with 64-bit integer size and symbol suffix '64_' |
| # (INTERFACE64=1 SYMBOLSUFFIX=64_). OpenBLAS built with this setting are also |
| # provided by some Linux distributions (e.g. Fedora's 64-bit openblas packages). |
| # This is an emerging "standard" for 64-bit BLAS/LAPACK, avoiding symbol clashes |
| # with 32-bit BLAS/LAPACK. |
| # |
| # To build Numpy with such 64-bit BLAS/LAPACK, set environment |
| # variables NPY_USE_BLAS_ILP64=1, NPY_BLAS_ILP64_ORDER=openblas64_, |
| # NPY_LAPACK_ILP64_ORDER=openblas64_ at build time. |
| # |
| # See: |
| # https://github.com/xianyi/OpenBLAS/issues/646 |
| # |
| # [openblas64_] |
| # libraries = openblas64_ |
| # library_dirs = /opt/OpenBLAS/lib |
| # include_dirs = /opt/OpenBLAS/include |
| # runtime_library_dirs = /opt/OpenBLAS/lib |
| |
| # OpenBLAS (64-bit ILP64) |
| # ----------------------- |
| # It is possible to also use OpenBLAS compiled with 64-bit integer |
| # size (ILP64) but no symbol name changes. To do that, set the |
| # environment variables NPY_USE_BLAS_ILP64=1, |
| # NPY_BLAS_ILP64_ORDER=openblas_ilp64, |
| # NPY_LAPACK_ILP64_ORDER=openblas_ilp64 at build time. |
| # |
| # Note that mixing both 64-bit and 32-bit BLAS without symbol suffixes |
| # in the same application may cause problems due to symbol name |
| # clashes, especially with embedded Python interpreters. |
| # |
| # The name of the library file may vary on different systems, so you |
| # may need to check your specific OpenBLAS installation and |
| # uncomment and e.g. set ``libraries = openblas`` below. |
| # |
| # [openblas_ilp64] |
| # libraries = openblas64 |
| # library_dirs = /opt/OpenBLAS/lib |
| # include_dirs = /opt/OpenBLAS/include |
| # runtime_library_dirs = /opt/OpenBLAS/lib |
| # symbol_prefix = |
| # symbol_suffix = |
| |
| # BLIS |
| # ---- |
| # BLIS (https://github.com/flame/blis) also provides a BLAS interface. It's a |
| # relatively new library, its performance in some cases seems to match that of |
| # MKL and OpenBLAS, but it hasn't been benchmarked with NumPy or SciPy yet. |
| # |
| # Notes on compiling BLIS itself: |
| # - the CBLAS interface (needed by NumPy) isn't built by default; define |
| # BLIS_ENABLE_CBLAS to build it. |
| # - ``./configure auto`` doesn't support 32-bit builds, see gh-7294 for |
| # details. |
| # Notes on compiling NumPy against BLIS: |
| # - ``include_dirs`` below should be the directory where the BLIS cblas.h |
| # header is installed. |
| # |
| # [blis] |
| # libraries = blis |
| # library_dirs = /home/username/blis/lib |
| # include_dirs = /home/username/blis/include/blis |
| # runtime_library_dirs = /home/username/blis/lib |
| |
| # libFLAME |
| # -------- |
| # libFLAME (https://www.cs.utexas.edu/~flame/web/libFLAME.html) provides a |
| # LAPACK interface. It's a relatively new library, its performance in some |
| # cases seems to match that of MKL and OpenBLAS. |
| # It hasn't been benchmarked with NumPy or SciPy yet. |
| # |
| # Notes on compiling libFLAME itself: |
| # - the LAPACK interface (needed by NumPy) isn't built by default; please |
| # configure with ``./configure --enable-lapack2flame``. |
| # |
| # [flame] |
| # libraries = flame |
| # library_dirs = /home/username/flame/lib |
| # runtime_library_dirs = /home/username/flame/lib |
| |
| # MKL |
| #---- |
| # Intel MKL is Intel's very optimized yet proprietary implementation of BLAS and |
| # LAPACK. Find the latest info on building NumPy with Intel MKL in this article: |
| # https://software.intel.com/en-us/articles/numpyscipy-with-intel-mkl |
| # Assuming you installed the mkl in /opt/intel/compilers_and_libraries_2018/linux/mkl, |
| # for 64 bits code at Linux: |
| # [mkl] |
| # library_dirs = /opt/intel/compilers_and_libraries_2018/linux/mkl/lib/intel64 |
| # include_dirs = /opt/intel/compilers_and_libraries_2018/linux/mkl/include |
| # libraries = mkl_rt |
| # |
| # For 32 bit code at Linux: |
| # [mkl] |
| # library_dirs = /opt/intel/compilers_and_libraries_2018/linux/mkl/lib/ia32 |
| # include_dirs = /opt/intel/compilers_and_libraries_2018/linux/mkl/include |
| # libraries = mkl_rt |
| # |
| # On win-64, the following options compiles NumPy with the MKL library |
| # dynamically linked. |
| # [mkl] |
| # include_dirs = C:\Program Files (x86)\IntelSWTools\compilers_and_libraries_2018\windows\mkl\include |
| # library_dirs = C:\Program Files (x86)\IntelSWTools\compilers_and_libraries_2018\windows\mkl\lib\intel64 |
| # libraries = mkl_rt |
| |
| # UMFPACK |
| # ------- |
| # The UMFPACK library is used in scikits.umfpack to factor large sparse matrices. |
| # It, in turn, depends on the AMD library for reordering the matrices for |
| # better performance. Note that the AMD library has nothing to do with AMD |
| # (Advanced Micro Devices), the CPU company. |
| # |
| # UMFPACK is not used by NumPy. |
| # |
| # https://www.cise.ufl.edu/research/sparse/umfpack/ |
| # https://www.cise.ufl.edu/research/sparse/amd/ |
| # https://scikit-umfpack.github.io/scikit-umfpack/ |
| # |
| #[amd] |
| #libraries = amd |
| # |
| #[umfpack] |
| #libraries = umfpack |
| |
| # FFT libraries |
| # ------------- |
| # There are two FFT libraries that we can configure here: FFTW (2 and 3) and djbfft. |
| # Note that these libraries are not used by NumPy or SciPy. |
| # |
| # http://fftw.org/ |
| # https://cr.yp.to/djbfft.html |
| # |
| # Given only this section, numpy.distutils will try to figure out which version |
| # of FFTW you are using. |
| #[fftw] |
| #libraries = fftw3 |
| # |
| # For djbfft, numpy.distutils will look for either djbfft.a or libdjbfft.a . |
| #[djbfft] |
| #include_dirs = /usr/local/djbfft/include |
| #library_dirs = /usr/local/djbfft/lib |