diff options
Diffstat (limited to 'src/qhull/Announce.txt')
-rw-r--r-- | src/qhull/Announce.txt | 47 |
1 files changed, 47 insertions, 0 deletions
diff --git a/src/qhull/Announce.txt b/src/qhull/Announce.txt new file mode 100644 index 000000000..635cff1af --- /dev/null +++ b/src/qhull/Announce.txt @@ -0,0 +1,47 @@ + + Qhull 2015.2 2016/01/18 + + http://www.qhull.org + git@github.com:qhull/qhull.git + http://www.geomview.org + +Qhull computes convex hulls, Delaunay triangulations, Voronoi diagrams, +furthest-site Voronoi diagrams, and halfspace intersections about a point. +It runs in 2-d, 3-d, 4-d, or higher. It implements the Quickhull algorithm +for computing convex hulls. Qhull handles round-off errors from floating +point arithmetic. It can approximate a convex hull. + +The program includes options for hull volume, facet area, partial hulls, +input transformations, randomization, tracing, multiple output formats, and +execution statistics. The program can be called from within your application. +You can view the results in 2-d, 3-d and 4-d with Geomview. + +To download Qhull: + http://www.qhull.org/download + git@github.com:qhull/qhull.git + +Download qhull-96.ps for: + + Barber, C. B., D.P. Dobkin, and H.T. Huhdanpaa, "The + Quickhull Algorithm for Convex Hulls," ACM Trans. on + Mathematical Software, 22(4):469-483, Dec. 1996. + http://www.acm.org/pubs/citations/journals/toms/1996-22-4/p469-barber/ + http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.117.405 + +Abstract: + +The convex hull of a set of points is the smallest convex set that contains +the points. This article presents a practical convex hull algorithm that +combines the two-dimensional Quickhull Algorithm with the general dimension +Beneath-Beyond Algorithm. It is similar to the randomized, incremental +algorithms for convex hull and Delaunay triangulation. We provide empirical +evidence that the algorithm runs faster when the input contains non-extreme +points, and that it uses less memory. + +Computational geometry algorithms have traditionally assumed that input sets +are well behaved. When an algorithm is implemented with floating point +arithmetic, this assumption can lead to serious errors. We briefly describe +a solution to this problem when computing the convex hull in two, three, or +four dimensions. The output is a set of "thick" facets that contain all +possible exact convex hulls of the input. A variation is effective in five +or more dimensions. |