development/numpy-legacy: Fix README.

Signed-off-by: B. Watson <yalhcru@gmail.com>

Signed-off-by: Willy Sudiarto Raharjo <willysr@slackbuilds.org>

1 files changed, 16 insertions, 15 deletions

diff --git a/development/numpy-legacy/README b/development/numpy-legacy/README
index 0d3993e366b3..582c0ae5442f 100644
--- a/development/numpy-legacy/README
+++ b/development/numpy-legacy/README
@@ -2,34 +2,35 @@ NumPy is a general-purpose array-processing package designed to
 efficiently manipulate large multi-dimensional arrays of arbitrary
 records without sacrificing too much speed for small multi-dimensional
 arrays.  NumPy is built on the Numeric code base and adds features
-introduced by numarray as well as an extended C-API and the ability to
-create arrays of arbitrary type which also makes NumPy suitable for
+introduced by numarray as well as an extended C-API and the ability
+to create arrays of arbitrary type which also makes NumPy suitable for
 interfacing with general-purpose data-base applications.
 
 There are also basic facilities for discrete fourier transform, basic
 linear algebra and random number generation.
 
-If you need to build numpy for debugging, set DEBUG=y. If you use software
-which is having problems with numpy's new relaxed strides checking, set
-NPY_RSC=0.
+If you need to build numpy for debugging, set DEBUG=y. If you use
+software which is having problems with numpy's new relaxed strides
+checking, set NPY_RSC=0.
 
-It is highly recommended to install libraries implementing BLAS and LAPACK
-before installing numpy. You may choose between:
+It is highly recommended to install libraries implementing BLAS and
+LAPACK before installing numpy. You may choose between:
    a) BLAS and LAPACK (reference but unoptimized and thus slow)
    b) OpenBLAS (optimized, provides LAPACK too)
    c) ATLAS and LAPACK (optimized), good to read README.ATLAS
 All these are available on SlackBuilds.org.
 
-If you want to use the UMFPACK library instead of SuperLU to solve unsymmetric
-sparse linear systems, then run this Slackbuild with NO_UMFPACK set to "no"
-and then install scikit-umfpack on top of scipy. In this context, UMFPACK is an
-optional dependency for numpy. Nevertheless, note that presently scikit-umfpack
-is not available on SlackBuilds.org while its dependencies are.
+If you want to use the UMFPACK library instead of SuperLU to solve
+unsymmetric sparse linear systems, then run this Slackbuild with
+NO_UMFPACK set to "no" and then install scikit-umfpack on top of
+scipy. In this context, UMFPACK is an optional dependency for
+numpy. Nevertheless, note that presently scikit-umfpack is not
+available on SlackBuilds.org while its dependencies are.
 
 NOTE: If you use this SlackBuild, numpy will run with the python version
-      provided by Slackware Linux, which is presently 2.7.xx. If you'd like to
-      use python 3.x then you have to install numpy with the numpy-legacy3
-      SlackBuild.
+      provided by Slackware Linux, which is presently 2.7.xx. If you'd
+      like to use python 3.x then you have to install numpy with the
+      numpy-legacy3 SlackBuild.
 
 IMPORTANT: This version, 1.8.2, is the latest to include the oldnumeric
            and numarray compatibility modules. Starting with version