lemma_mirror/Documentation/dox/tutorial.dox

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>

\section C Why C++?
We get this a lot as most EM software seems to be written in Fortran or Matlab. 
C++ has developed into a fast powerful language appropriate for scientific computing. 
The language is undeniably complex and can be intimidating (lots of bad C++ code is out there).
However, it is also possible to generate high performance, intuitive, flexible software using 
C++. In Lemma we take advantage of several recent changes to the language such that our public 
interface is simple to use, does not require manual memory management, and lets scientists focus on 
the problem at hand. The biggest hurdle for newcomers is often getting used to the object oriented 
approach we have taken. Rather than provide programs performing specific tasks Lemma exposes a 
flexible application programming interface (API) which can be though of as building blocks used 
to construct programs or projects.   

\subsection Design Our design philosophy 
Software should be flexible, intuitive, and simple. Many times, less is more and offering 
Note that simple is not necessarily synonymous with easy, although we do strive to make Lemma 
as easy to use as possible without sacrificing our other goals.    

\subsubsection 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, but is missing 
  something, you can just extend a class. 
- Third, it limits the amount of file IO you might need to do. We deviate from the Unix philosophy 
  of piping text streams between small applications, mainly because doing so is difficult on some 
  operating systems (I'm looking at you Windows), as well as cumbersome when used in graphical 
  user interfaces.
- Four, it enforces a consistent design and feel across the project. Once becoming familiar with 
  how Lemma objects are constructed, it becomes simple to use new building blocks. Think of the 
  objects as Lego's, since they are all constructed to work together, you can build anything. If 
  instead you have a mix of Lego, Lincoln Logs, and Tinker Toys you will be more more limited 
  in how you can use the pieces together.  

\subsection  Fortran Why not Fortran?
We have  lots of reasons for choosing C++ over Fortran, some of them better than others.
- We know C++ better, and we like it better. Too many hours debugging old 
  FORTRAN 77 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, an XML parser, and YAML class serialization. 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 (OO)
 programming and C++ is a much more natural choice for an OO project. 
 In spite of advances in the language, Fortran is still more geared towards procedural 
 programming paradigms (for better or worse). 
- 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 implementations. 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 out the benchmarks if you are still sceptical
http://eigen.tuxfamily.org/index.php?title=Benchmark 
- We know Fortran has come a long way since FORTRAN 77, but hey, so has C++. Give it a 
chance.

\subsection MATLAB Why not MATLAB?
MATLAB is a closed source environment that is severely restrictive. The Lemma license is pro-business, 
we are happy if Lemma is used in commercial code and programs. MATLAB code is expensive and difficult to 
distribute in binary form. Also, the object oriented aspects of the MATLAB language feel a bit bolted on, and 
cumbersome to use.  We prefer to avoid MATLAB for these reasons. 

\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 a 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.
*/

/** @} */
}