namespace Lemma{

/**
    \page   Tutorial

   A basic tutorial outlining the goals of Lemma, how to acquire and use it, and how to extend it 
   for your own purposes. 

   - \subpage Intro - Introduction to the project
   - \subpage Compiling - how to compile the library
   - \subpage Memory - our implementation of garbage collection, and what it means to you
   - \subpage Minimal - compiling your first minimal Lemma application
   - \subpage EmSources - Electromagnetic sources
    
  \page   Intro
  <div class="lemmamainmenu">  
    \b   Intro      
  | \ref Compiling "Compiling"
  | \ref Memory    "Memory management"
  | \ref Minimal   "Minimal programme"  
  | \ref EmSources "EM Sources"
  </div>

Some basic information about Lemma to get you started. If you are familiar with
C++ and API's you can skip this page.

\section C Why C++?
We get this a lot as most EM software seems to be written in fortran or Matlab. We
begin by discussing why we didn't choose certain languages/platforms.

\subsection  Fortran Why not fortran?
We have  lots of reasons for choosing C++ over fortran, some of them better than others.
- We know it better, and we like it better. Too many hours debugging old 
  FORTRAN subroutines has left us jaded.
- Easy integration with existing libraries. For example Lemma has built in 
support for VTK, an extremely powerful visualization package. We also include 
MATLAB file IO readers and an XML parser. Providing fortran wrappers for all 
of this would be a huge undertaking.
- Flexibility. Lemma is NOT a program, its an API that lets you build 
 applications that fit your needs. This approach is a natural fit for object oriented
 programming and C++ is a much more natural choice for an OO project. 
- Infinitely better interface. We leverage the Eigen 
   <http://eigen.tuxfamily.org>  linear algebra package
  to deliver expressive, fast code. Their benchmarks are right in line with 
  fast BLAS and LAPACK implimentations. If you honestly feel that 
\code
DGEMM ( TRANSA, TRANSB, M, N, K, ALPHA, A, LDA, B, LDB, BETA, C, LDC )
\endcode  
 is superior to
\code
  C = A*B.transpose(); 
\endcode 
 you are living in denial. Check the benchmarks if you are still skeptical. 
- We know fortran 2003 has come a long way, but hey, so has C++. Give it a 
chance.

\subsection Matlab Ok, so why not MATLAB?
First its closed source, second most large MATLAB programs suffer severe 
performance issues. Third, support for object-oriented programming is a joke. 
Finally, its also expensive and we don't think the graphics are all
that great.

\subsection Python How about Python?
We like Python. While large 100% native Python applications are often very slow, it is easy to wrap fast C++ and Fortran routines around a Python interface. 
We actually plan on doing this in the future, and it is likely that at some 
point this may be the most common way to use Lemma. Lots of great visualization
solutions exist in Python (including VTK) and it is a great programming environment. The hard
part is that Eigen relies heavily on Expression templates that cannot be 
trivially wrapped into a python interface. So any python interface would have 
to be carefully constructed. We would welcome help in this department.
In the mean-time our API is elegant and easy to use.

\section API An API? What's that?
Lemma is not a program. It's an API, or an Application Programming Interface.
This offers a lot of advantages over traditional programs. 
- First, its flexible. Its easy to put together components to do exactly what 
  you want and nothing more. 
- Second, its extendible. If we have a class that does almost what you want, you
  can just extend a class. 
- Third, it limits the amount of file IO you might need to do.
- Four, there are lots of other good reasons too. Just give it a try. 
*/

/** @} */
}