DOC: link and cleanup docstrings in site.cfg.example

1 files changed, 20 insertions, 22 deletions

diff --git a/site.cfg.example b/site.cfg.example
index cff076381..236c26e6a 100644
--- a/site.cfg.example
+++ b/site.cfg.example
@@ -40,7 +40,7 @@
 #       List of directories to add to the header file search path.
 #           include_dirs = /usr/include:/usr/local/include
 #
-#   src_dirs 
+#   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
@@ -56,7 +56,7 @@
 #           search_static_first = false
 #
 #   runtime_library_dirs/rpath
-#       List of directories that contains the libraries that should be 
+#       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
@@ -79,14 +79,12 @@
 
 # Defaults
 # ========
-# The settings given here will apply to all other sections if not overridden.
+# 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}
-#
-#[ALL]
+#[DEFAULT]
 #library_dirs = /usr/local/lib
 #include_dirs = /usr/local/include
-#
 
 # ATLAS
 # -----
@@ -108,7 +106,7 @@
 # for your configuration (in the following example we installed OpenBLAS with
 # ``make install PREFIX=/opt/OpenBLAS``.
 # OpenBLAS is generically installed as a shared library, to force the OpenBLAS
-# library linked to also be used at runtime you can utilize the 
+# library linked to also be used at runtime you can utilize the
 # runtime_library_dirs variable.
 #
 # **Warning**: OpenBLAS, by default, is built in multithreaded mode. Due to the
@@ -215,26 +213,26 @@
 # runtime_library_dirs = /home/username/flame/lib
 
 # MKL
-#---- 
-# Intel MKL is Intel's very optimized yet proprietary implementation of BLAS and 
+#----
+# 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] 
+# 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 
+# include_dirs = /opt/intel/compilers_and_libraries_2018/linux/mkl/include
 # libraries = mkl_rt
-# 
-# For 32 bit code at Linux: 
+#
+# 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 
+# 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] 
+#
+# 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
@@ -249,7 +247,7 @@
 
 # UMFPACK
 # -------
-# The UMFPACK library is used in scikits.umfpack to factor large sparse matrices. 
+# 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.
@@ -279,7 +277,7 @@
 #[fftw]
 #libraries = fftw3
 #
-# For djbfft, numpy.distutils will look for either djbfft.a or libdjbfft.a . 
+# 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