CGLAB is a Scilab interface to the CGAL library (Computational Geometry Algorithms Library) for efficient and reliable geometric algorithms.

It can be used in various areas needing geometric computation, such as geographic information systems, computer aided design, molecular biology, medical imaging, computer graphics, and robotics.

**Download on ATOMS:
**https://atoms.scilab.org/toolboxes/cglab

# Functional domains

Delaunay triangulations

Delaunay triangulations

A **Delaunay triangulation** for a set **P** of points in a plane is a triangulationDT(**P**) such that no point in **P** is inside the circumcircle of any triangle in DT(**P**). Delaunay triangulations maximize the minimum angle of all the angles of the triangles in the triangulation; they tend to avoid skinny triangles. The triangulation is named after Boris Delaunay for his work on this topic from 1934.

https://en.wikipedia.org/wiki/Delaunay_triangulation

Voronoi diagrams

Voronoi diagrams

In mathematics, a **Voronoi diagram** is a partitioning of a plane into regions based on distance to points in a specific subset of the plane. That set of points (called seeds, sites, or generators) is specified beforehand, and for each seed there is a corresponding region consisting of all points closer to that seed than to any other. These regions are called Voronoi cells. The Voronoi diagram of a set of points is dual to its Delaunay triangulation.

https://en.wikipedia.org/wiki/Voronoi_diagram

**Interpolation**

**Interpolation** is a method of constructing new data points within the range of a discrete set of known data points.

In engineering and science, one often has a number of data points, obtained by sampling or experimentation, which represent the values of a function for a limited number of values of the independent variable. It is often required to **interpolate** (i.e. estimate) the value of that function for an intermediate value of the independent variable. This may be achieved by curve fitting or regression analysis.

https://en.wikipedia.org/wiki/Interpolation

Convex Hull

Convex Hull

The **convex hull** or **convex envelope** of a set *X* of points in the Euclidean plane or Euclidean space is the smallest convex set that contains *X*. For instance, when *X* is a bounded subset of the plane, the convex hull may be visualized as the shape enclosed by a rubber band stretched around *X*.

The convex hull of the red set is the blue and red convex set.

https://en.wikipedia.org/wiki/Convex_hull

**Mesh generation**

**Mesh generation** is the practice of generating a polygonal or polyhedral mesh that approximates a geometric domain. The term “**grid generation**” is often used interchangeably. Typical uses are for rendering to a computer screen or for physical simulation such as finite element analysis or computational fluid dynamics. The input model form can vary greatly but common sources are CAD, NURBS, B-rep, STL (file format) or a point cloud. The field is highly interdisciplinary, with contributions found in mathematics, computer science, and engineering.

Three-dimensional meshes created for finite element analysis need to consist of tetrahedra, pyramids, prisms or hexahedra. Those used for the finite volume method can consist of arbitrary polyhedra. Those used for finite difference methods usually need to consist of piecewise structured arrays of hexahedra known as multi-block structured meshes. A mesh is otherwise a discretization of a domain existing in one, two or three dimensions.

https://en.wikipedia.org/wiki/Mesh_generation

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