BayesOpt / doxygen / install.dox

/*! \page install Installing BayesOpt
\tableofcontents

The core of BayesOpt uses standard C/C++ code (C++98) so it can be
compiled from many C++ compilers (gcc, clang, MSVC...). The library
also include wrappers for Python, Matlab and Octave interfaces which requires
extra dependencies or compilation steps. Note that the
Python or Matlab/Octave interfaces are not included by default.

\section unixinst Installing in Linux/MacOS:

The compilation is very similar in any *nix system. Following these
instructions, the library will be compiled using the default
configuration. You can modify that easily as explained in 
\ref confinst

\subsection getDepend Getting dependencies:

The easiest way to compile this library is using the cross platform
and cross compiler tool <a href="http://www.cmake.org/">CMake</a>.

This code uses Boost libraries for matrix operations (uBlas), random
number generation, math functions and smart pointers. Being only
include files, Boost does not require any speciall install. Boost can
be found in many Linux and MacOS repositories. It can also be
downloaded from http://www.boost.org.

Both Python development files (Python.h) and Numpy are needed if you
want the Python interface. The library has been tested with Python 2.6
and 2.7. The interface relies on Numpy arrays.

Finally, if you want the Matlab interface, just make sure your C++
compiler is compatible with your Matlab version.

\subsubsection cinlinux Linux:
For Ubuntu/Debian, the minimum dependencies (C/C++) can be optained by running:
\verbatim
>> sudo apt-get install libboost-dev cmake cmake-curses-gui g++
\endverbatim

If you want the Python interface:
\verbatim
>> sudo apt-get install python-dev python-numpy
\endverbatim

If you want the Octave interface (note that the \a octave package does not include all the necessary files):
\verbatim
>> sudo apt-get install octave-headers
\endverbatim

And for all dependencies:
\verbatim
>> sudo apt-get install libboost-dev python-dev python-numpy cmake cmake-curses-gui g++ cython octave-headers
\endverbatim

\subsubsection cinmac MacOS:
This section assumes \b macports is installed. Similar packages can be
found in \b fink or \b homebrew. For the minimal install, run:
\verbatim
>> sudo port install boost gcc47 cmake
\endverbatim

If you want the Python interface:
\verbatim
>> sudo port install python27 py27-numpy
\endverbatim

If you want the Octave interface:
\verbatim
>> sudo port install octave
\endverbatim

Again, for all dependencies:
\verbatim
>> sudo port install boost python27 py27-numpy gcc47 cmake py27-cython octave
\endverbatim


\subsection compile Compile the library:
In order to compile the source code in a *nix system, run this from a
terminal.
\verbatim
>> cmake . 
>> make
>> sudo make install
\endverbatim

\b Important: If you use \b ccmake instead of \b cmake you will access a graphical
interface to select features such as the include the Python and Matlab interfaces,
debug/release mode or if you want to use shared libraries or not. More details about how
to configure it can be found in \ref confinst

\subsubsection docbuild Building the documentation

If you have doxygen installed on your computer, you can compile the
documentation right after compiling the code by running.
\verbatim
>> make doc
\endverbatim
Thid documentation will appear in the "doc" subdirectory.



\subsection instpython Python interface:

Both Python development files (Python.h) and Numpy are needed if you
want the python interface. The library has been tested with Python 2.6
and 2.7. The interface relies on Numpy arrays. If we want to select
the option to compile the Python interface we can just run:
\verbatim
>> cmake -DBAYESOPT_PYTHON_INTERFACE=ON . 
\endverbatim
or 
\verbatim
>> ccmake . 
\endverbatim
and select the corresponding option.

\b Important: Python requires a special module with shared access and nonstandard
name. Thus, it will build a separate module called "bayesopt.so". This module can be
accessible from Python provided that it is in the PYTHONPATH or sys.path. It cannot be
linked to any executable or other libraries. Use libbayesopt.* instead.

\subsection instmatlab MATLAB/Octave interface:

Make sure the library is compiled with the MATLAB_COMPATIBLE option
using ccmake. Undex Mac OS they must be shared. Also, configure 
Matlab/Octave to compile mex files. For example, in Matlab you can run
to check the supported compilers:
\verbatim
>> mex -setup
\endverbatim

Run the corresponding script compile_matlab.m or compile_octave.m,
which can be found in the \em /matlab/ directory.

If bayesopt or nlopt are compiled as \b shared libraries, then, at run
time, MATLAB/Octave also needs to access to the libraries. For
example, LD_LIBRARY_PATH must include the folder where the libraries
are. If the install path is the default, you can execute the
exportlocalpath.sh script before calling MATLAB.

On MacOS there are known issues both in Matlab and Octave about the compiler linking with
the worng std++ library for different reasons. See:
\li http://www.mathworks.com/matlabcentral/newsreader/view_thread/291752
\li https://mailman.cae.wisc.edu/pipermail/octave-maintainers/2012-January/026341.html

<HR>

\section cinwin Windows and other systems:
Install this components:
\li CMake: http://www.cmake.org

CMake for Windows provides a nice GUI where you can select your
favorite C++ compiler (MinGW, Visual Studio, etc.). It will
automatically create the necesary configuration files for the compiler
(makefile, solution, etc.).

\li Boost: http://www.boost.org

Since Boost they are pure template libraries, they do not require
compilation. Just make sure the headers are on the include path. You
can also add an entry named BOOST_ROOT in CMake with the corresponding
path to the library.

\li MinGW(optional): http://www.mingw.org

If you do not have a C++ compiler, we recomend MinGW+MSYS. Then, you
just need to compile from the command line with:
\verbatim
>> mingw32-make
\endverbatim

The most important options/variables are explained in \ref confinst.

\subsection instmatlabwin MATLAB/Octave interface:

Make sure the library is compiled with the MATLAB_COMPATIBLE option
and configure Matlab/Octave to compile mex files. For example, in
Matlab you can run to check the supported compilers:
\verbatim
>> mex -setup
\endverbatim

Run the corresponding script compile_matlab.m or compile_octave.m,
which can be found in the \em /matlab/ directory. 

If bayesopt or nlopt are compiled as \b shared libraries, then, at run
time, MATLAB/Octave also needs to access to the libraries. You can
modify the PATH variable or copy the dll files in the same bolder as
the generated mexfile.

\b Important: It is strongly recommended to compile bayesopt with
exactly the same compiler that was select for mex files. For a list of
the supported compilers for your Matlab version, you can check the
online docs at mathworks. 

\subsubsection matlabmingw MATLAB and MinGW

Unfortunately, MinGW has never been suported by Matlab. Thus I have
also included a Makefile to generate the mex files outside Matlab. You
might need to change the \c MATLABROOT path with the root folder of
your Matlab install and copy the dlls. Then, run \c mingw32-make. Note
that \c mingw32-make only supports 32 bits libraries, so you need a 32
bit version of Matlab. There is a fork of MinGW with 64 bit support
under development, but it has not been tested here.

\subsection instpythonwin Python interface:

The Python interface has not been tested in \b Windows because getting
the correct dependencies is highly involved. You might need to
download and install:
\li Python (binary and \b sources): http://www.python.org
\li Numpy: http://new.scipy.org/download.html 

Also, read this article about how to link everything:
http://docs.python.org/2/extending/windows.html#building-on-windows


<HR>

\section confinst Configure the compilation/install

CMake allows to configure the compilation using some variables (see
for example how to compile the Python module in Linux). These
variables can be set in Linux/MacOS from the command line with the -D
flag:
\verbatim
>> cmake -DVARIABLE=VALUE .
\endverbatim
For example
\verbatim
>> cmake -DCMAKE_BUILD_TYPE=Debug .
\endverbatim

If you use ccmake in Linux/MacOS or CMake for Windows, you can access
to a list of all the variables and their values. Just modify the value
of the desired variable.

\subsection instshared Compile as shared libraries

We can select if we want BayesOpt and NLOPT compiled as shared libraries
\verbatim
BAYESOPT_BUILD_SHARED=ON 
NLOPT_BUILD_SHARED=ON
\endverbatim
In this case, we also need to force rebuild NLOPT (by default it is
not compiled if it is found in the system).

\subsection instpath Install the library in a different path

CMake allows to select the install path before compilation
compilation. You just need to change the CMAKE_INSTALL_PREFIX
variable.
\verbatim
CMAKE_INSTALL_PREFIX=/your/desired/path
\endverbatim


\subsection mininst Minimal installation (fast compilation)

Sobol sequences can be used to for the initial design (see \ref
initpar). In many cases, the performance is similar to latin hypercube
sampling, however including the Sobol components increases
considerably the library size and the compilation time. Thus, it can
be removed from compilation:
\verbatim
BAYESOPT_BUILD_SOBOL=OFF
\endverbatim
Similarly, we can avoid to compile the example files and demos:
\verbatim
BAYESOPT_BUILD_EXAMPLES=OFF
\endverbatim


 */
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