namespace Lemma{
/**
\page Compiling
\ref Intro "Intro"
| \b Compiling
| \ref Memory "Memory management"
| \ref Minimal "Minimal programme"
| \ref EmSources "EM Sources"
Compiling Lemma is fairly straightforward. The biggest hurdle is possibly installing
the prerequisites, but on many platforms this is easy.
\section Table Table of contents
- \ref Prerequisites
- \ref OptionalPrerequisites
- \ref Downloading
- \ref Configuring
- \ref Building
\section OptionalPrerequisites Optional Prerequisites
- VTK - The Visualization ToolKit is a powerful data visualization framework. This is
an optional dependency, but some functionality will be missing without it. Any
version after 6.0 is fine. VTK is available under a BSD license from
Again--on Linux-- most package managers offer VTK. Compiling from source is not
terribly difficult, but requires installing CMake as well.
\note Some Lemma modules may impose additional (optional or mandatory) prerequisites, see the
module documentation.
\section Prerequisites Prerequisites
Lemma uses CMake to manage the build process (https://cmake.org). CMake is free software
that is easy to install on about any operating system.
\subsection Dependencies
Hard dependencies are
The only dependencies are the Eigen linear algebra Library v3, a
C++ compiler and scons.
The following compilers are fully supported and tested: gnu, mingw,
and intelc. Several routines are parallelised for shared memory platforms
using OpenMP. Any of the above compilers is able to be used with OpenMP.
Microsoft's Visual C++ compiler will likely be supported for stable
releases, but is not actively tested.
Eigen extensively uses template
meta programming, the Borland compiler has been shown to be subpar at
optimizing this type of code and will likely never be supported actively.
A new compiler clang, is being developed and may prove to be promising as
well, but current C++ support is lacking. If you are using a different
compiler, please share your experiences with us.
The Visualization ToolKit (VTK) is used for visualisation throughout Lemma.
It is not an explicit dependency, but without it, you will not be able to
get any graphical output.
Eigen is freely available under the LGPL at
. The necessary components of Eigen will
be included in stable releases of Lemma.
Scons is a make replacement built on top of Python, and is also free.
- Eigen3 - Eigen is a header-only linear algebra template library. It is made
available under the Gnu Lesser Public License. It is available at
. Please note that Lemma uses Version 3 of the Library.
\section Downloading Acquiring the source
Lemma is currently available from svn checkout only. Note that while Lemma is still in Beta only
developers have access to the source code. Contact us if you would like to contribute.
\code
svn co https://svn.lemmasoftware.org/lemma/trunk Lemma
\endcode
\section Configuring Configuring
There is very little configuring to do. In the main Lemma directory you will find a file
called 'Examplesettings.py listed below'
\include Examplesettings.py
Configure this to your machine, and copy to a file named
\code
settings.py
\endcode
If you have more questions about a parameter you can type
\code
scons -h
\endcode
For more information. After configuring, copy Examplesettings.py to a file called settings.py.
\section Building
To build the libraries simply type:
\code
scons -j2
\endcode
To build the libraries and unit tests. The -j2 arguments tell scons how many threads compilation
should occur on (parallel build). We recommend one per processor. Note, this only affects
the speed of the build, not whether or not Lemma will have OpenMP support.
\section Installing
To install the library simply type:
\code
scons install
\endcode
To install to INSTALLDIR. Note depending on your machine, you may need sudo privileges to do this.
Also, if you let INSTALLDIR=./lib this step will fail as those libraries are already located in Lemma/lib.
Note that on a Mac, this step is crucial.
*/
/** @} */
}