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CGAL 5.0.3 - Manual
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CGAL 5.0.3 - Manual
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In order to build a program using CGAL, you need a C++ compiler supporting C++14 or later. CGAL 5.0.3 is supported (continuously tested) for the following compilers/operating systems:
| Operating System | Compiler |
|---|---|
| Linux | Gnu g++ 6.3 or laterhttp://gcc.gnu.org/ |
Clang http://clang.llvm.org/ compiler version 8.0.0 | |
| MS Windows | Gnu g++ 6.3 or laterhttp://gcc.gnu.org/ |
MS Visual C++ 14.0, 15.9, 16.0 (Visual Studio 2015, 2017, and 2019)https://visualstudio.microsoft.com/ | |
| MacOS X | Gnu g++ 6.3 or laterhttp://gcc.gnu.org/ |
Apple Clang compiler versions 7.0.2 and 10.0.1 |
Older versions of the above listed compilers might work, but no guarantee is provided.
Version 3.1 or later
In order to configure and build the CGAL examples, demos, or libraries, you need CMake, a cross-platform "makefile generator".
This manual explains only the features of CMake which are needed in order to build CGAL. Please refer to the CMake documentation for further details.
The focus of CGAL is on geometry, and we rely on other highly specialized libraries and software for non-geometric issues, for instance for numeric solvers or visualization. We first list software that is essential to most of CGAL, and must therefore be found during the configuration of CGAL. The page Summary of CGAL's Configuration Variables lists CMake and environment variables which can be used to specify the location of third-party software during configuration.
CGAL heavily uses the STL, and in particular adopted many of its design ideas. You can find online documentation for the STL at various web sites, for instance, https://en.cppreference.com, or https://msdn.microsoft.com.
The STL comes with the compiler, and as such no installation is required.
Version 1.58 or later
The Boost libraries are a set of portable C++ source libraries. Most of Boost libraries are header-only, but a few of them need to be compiled or installed as binaries.
CGAL only requires the headers of the Boost libraries, but some demos and examples depend on the binary library Boost.Program_options. As an exception and because of a bug in the GCC compiler about the C++ 11 keyword thread_local, the CGAL_Core library always requires the binary library Boost.Thread if the GCC compiler version 9.0 or earlier is used.
In case the Boost libraries are not installed on your system already, you can obtain them from https://www.boost.org/. For Visual C++ you can download precompiled libraries from https://sourceforge.net/projects/boost/files/boost-binaries/.
As there is no canonical directory for where to find Boost on Windows, we recommend that you define the environment variable BOOST_ROOT and set it to where you have installed Boost, e.g., C:\boost\boost_1_69_0.
GMP Version 4.2 or later, MPFR Version 2.2.1 or later
The components libCGAL, libCGAL_Core, and libCGAL_Qt5 require Gmp and Mpfr which are libraries for multi precision integers and rational numbers, and for multi precision floating point numbers.
CGAL combines floating point arithmetic with exact arithmetic in order to be efficient and reliable. CGAL has a built-in number type for that, but Gmp and Mpfr provide a faster solution, and we recommend to use them.
These libraries can be obtained from https://gmplib.org/ and https://www.mpfr.org/. Since Visual C++ is not properly supported by the Gmp and Mpfr projects, we provide precompiled versions of Gmp and Mpfr, which can be downloaded with the installer CGAL-5.0.3-Setup.exe.
Optional 3rd party software can be used by CGAL for various reasons: certain optional libraries might be required to build examples and demos shipped with CGAL or to build your own project using CGAL; another reason is to speed up basic tasks where specialized libraries can be faster than the default version shipped with CGAL. The page Summary of CGAL's Configuration Variables lists CMake and environment variables which can be used to specify the location of third-party software during configuration.
Version 5.9.0 or later
Qt is a cross-platform application and UI framework.
The component libCGAL_Qt5 is essential to run the CGAL demos and basic viewers. It requires Qt5 installed on your system. In case Qt is not yet installed on your system, you can download it from https://www.qt-project.org/.
The exhaustive list of Qt5 components used in demos is: Core, Gui, Help, OpenGL, Script, ScriptTools, Svg, Widgets, qcollectiongenerator (with sqlite driver plugin), and Xml.
Version 3.1 or later
Eigen is a C++ template library for linear algebra. Eigen supports all matrix sizes, various matrix decomposition methods and sparse linear solvers.
In CGAL, Eigen is used in many packages such as Poisson Surface Reconstruction or Estimation of Local Differential Properties of Point-Sampled Surfaces, providing sparse linear solvers and singular value decompositions. A package dependency over Eigen is marked on the Package Overview page.
The Eigen web site is http://eigen.tuxfamily.org.
Version 6.2 or later
LEDA is a library of efficient data structures and algorithms. Like Core, LEDA offers a real number data type.
In CGAL this library is optional, and its number types can be used as an alternative to Gmp, Mpfr, and Core.
Free and commercial editions of LEDA are available from https://www.algorithmic-solutions.com.
Version 1.4 or later
Mpfi provides arbitrary precision interval arithmetic with intervals represented using Mpfr reliable floating-point numbers. It is based on the libraries Gmp and Mpfr. In the setting of CGAL, this library is optional: it is used by some models of the Algebraic Kernel.
Mpfi can be downloaded from https://mpfi.gforge.inria.fr/.
Rs (Real Solutions) is devoted to the study of the real roots of polynomial systems with a finite number of complex roots (including univariate polynomials). In CGAL, Rs is used by one model of the Algebraic Kernel.
Rs is freely distributable for non-commercial use. You can download it from http://vegas.loria.fr/rs/. Actually, the Rs package also includes Rs3, the successor of Rs, which is used in conjunction with it.
The libraries Rs and Rs3 need Mpfi, which can be downloaded from https://mpfi.gforge.inria.fr/.
Version 5.1 or later
Ntl provides data structures and algorithms for signed, arbitrary length integers, and for vectors, matrices, and polynomials over the integers and over finite fields. The optional library Ntl is used by CGAL to speed up operations of the Polynomial package, such as GCDs. It is recommended to install Ntl with support from Gmp.
Ntl can be downloaded from https://www.shoup.net/ntl/.
The Esbtl (Easy Structural Biology Template Library) is a library that allows the handling of Pdb data.
In CGAL, the Esbtl is used in an example of the 3D Skin Surface Meshing package.
It can be downloaded from http://esbtl.sourceforge.net/.
Tbb (Threading Building Blocks) is a library developed by Intel Corporation for writing software programs that take advantage of multi-core processors.
In CGAL, Tbb is used by the packages that offer parallel code.
The Tbb web site is https://www.threadingbuildingblocks.org.
LASlib is a C++ library for handling LIDAR data sets stored in the LAS format (or the compressed LAZ format).
In CGAL, LASlib is used to provide input and output functions in the Point Set Processing package.
The LASlib web site is https://rapidlasso.com/lastools/. LASlib is usually distributed along with LAStools: for simplicity, CGAL provides a fork with a CMake based install procedure.
OpenCV (Open Computer Vision) is a library designed for computer vision, computer graphics and machine learning.
In CGAL, OpenCV is used by the Classification package.
The OpenCV web site is https://opencv.org/.
TensorFlow is a library designed for machine learning and deep learning.
In CGAL, the C++ API of TensorFlow is used by the Classification package for neural network. The C++ API can be compiled using CMake: it is distributed as part of the official package and is located in tensorflow/contrib/cmake. Be sure to enable and compile the following targets:
tensorflow_BUILD_ALL_KERNELStensorflow_BUILD_PYTHON_BINDINGStensorflow_BUILD_SHARED_LIB.The TensorFlow web site is https://www.tensorflow.org/.
Version 5.1 or later
METIS is a library developed by the Karypis Lab and designed to partition graphs and produce fill-reducing matrix orderings.
CGAL offers wrappers around some of the methods of the METIS library to allow the partitioning of graphs that are models of the concepts of the Boost Graph Library, and, by extension, of surface meshes (see Section Graph Partitioning of the package CGAL and the Boost Graph Library).
More information is available on the METIS library at http://glaros.dtc.umn.edu/gkhome/metis/metis/overview.
zlib is a data compression library, and is essential for the component libCGAL_ImageIO.
In CGAL, this library is used in the examples of the 3D Surface Mesh Generation package.
If it is not already on your system, for instance, on Windows, you can download it from https://www.zlib.net/.
Ceres is an open source C++ library for modeling and solving large, complicated optimization problems.
In CGAL, Ceres is used by the Polygon Mesh Processing Reference package for mesh smoothing, which requires solving complex non-linear least squares problems.
Visit the official website of the library at ceres-solver.org for more information.
GLPK (GNU Linear Programming Kit) is a library for solving linear programming (LP), mixed integer programming (MIP), and other related problems.
In CGAL, GLPK provides an optional linear integer program solver in the Polygonal Surface Reconstruction package.
The GLPK web site is https://www.gnu.org/software/glpk/.
SCIP (Solving Constraint Integer Programs) is currently one of the fastest open source solvers for mixed integer programming (MIP) and mixed integer nonlinear programming (MINLP).
In CGAL, SCIP provides an optional linear integer program solver in the Polygonal Surface Reconstruction package.
The SCIP web site is http://scip.zib.de/.
1.8.13