EVOLUTION-MANAGER

Edit File: site.cfg.example

# 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 easy_install, 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. # # http://www.python.org/doc/current/lib/module-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 # # 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 and src_dirs (see below). # 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 earch path. # include_dirs = /usr/include:/usr/local/include # # src_dirs # List of directories that contain extracted source code for the # dependency. For some dependencies, numpy.distutils will be able to build # them from source if binaries cannot be found. The FORTRAN BLAS and # LAPACK libraries are one example. However, most dependencies are more # complicated and require actual installation that you need to do # yourself. # src_dirs = /home/rkern/src/BLAS_SRC:/home/rkern/src/LAPACK_SRC # # 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 # Defaults # ======== # The settings given here will apply to all other sections if not overridden. # This is a good place to add general library and include directories like # /usr/local/{lib,include} # #[DEFAULT] #library_dirs = /usr/local/lib #include_dirs = /usr/local/include # Optimized BLAS and LAPACK # ------------------------- # Use the blas_opt and lapack_opt sections to give any settings that are # required to link against your chosen BLAS and LAPACK, including the regular # FORTRAN reference BLAS and also ATLAS. Some other sections still exist for # linking against certain optimized libraries (e.g. [atlas], [lapack_atlas]), # however, they are now deprecated and should not be used. # # These are typical configurations for ATLAS (assuming that the library and # include directories have already been set in [DEFAULT]; the include directory # is important for the BLAS C interface): # #[blas_opt] #libraries = f77blas, cblas, atlas # #[lapack_opt] #libraries = lapack, f77blas, cblas, atlas # # If your ATLAS was compiled with pthreads, the names of the libraries might be # different: # #[blas_opt] #libraries = ptf77blas, ptcblas, atlas # #[lapack_opt] #libraries = lapack, ptf77blas, ptcblas, atlas # 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 needed for numpy or scipy. # # http://www.cise.ufl.edu/research/sparse/umfpack/ # http://www.cise.ufl.edu/research/sparse/amd/ # http://scikits.appspot.com/umfpack # #[amd] #amd_libs = amd # #[umfpack] #umfpack_libs = 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 needed for numpy or scipy. # # http://fftw.org/ # http://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 # MKL #---- # For recent (9.0.21, for example) mkl, you need to change the names of the # lapack library. Assuming you installed the mkl in /opt, for a 32 bits cpu: # [mkl] # library_dirs = /opt/intel/mkl/9.1.023/lib/32/ # lapack_libs = mkl_lapack # # For 10.*, on 32 bits machines: # [mkl] # library_dirs = /opt/intel/mkl/10.0.1.014/lib/32/ # lapack_libs = mkl_lapack # mkl_libs = mkl, guide