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===================================================================
RCS file: /ftp/cvs/cvsroot/pkgsrc/math/eigen3/DESCR,v
rcsdiff: /ftp/cvs/cvsroot/pkgsrc/math/eigen3/DESCR,v: warning: Unknown phrases like `commitid ...;' are present.
retrieving revision 1.2
retrieving revision 1.3
diff -u -p -r1.2 -r1.3
--- pkgsrc/math/eigen3/DESCR	2013/04/07 20:49:37	1.2
+++ pkgsrc/math/eigen3/DESCR	2013/04/08 18:29:41	1.3
@@ -21,4 +21,11 @@ related algorithms. It is:
   o With fixed-size objects, dynamic memory allocation is avoided, and the
     loops are unrolled when that makes sense.
   o For large matrices, special attention is paid to cache-friendliness.
-...and more!
+* Elegant. The API is extremely clean and expressive, thanks to expression
+  templates. Implementing an algorithm on top of Eigen feels like just copying
+  pseudocode. You can use complex expressions and still rely on Eigen to
+  produce optimized code: there is no need for you to manually decompose
+  expressions into small steps.
+* Compiler-friendy. Eigen has very reasonable compilation times at least with
+  GCC, compared to other C++ libraries based on expression templates and heavy
+  metaprogramming. Eigen is also standard C++ and supports various compilers.