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math/qhull-2012.1 (Score: 0.10508093)
Qhull computes convex hulls, Delaunay triangulations, and halfspaces
Qhull computes convex hulls, Delaunay triangulations, halfspace intersections about a point, Voronoi diagrams, furthest-site Delaunay triangulations, and furthest-site Voronoi diagrams. It runs in 2-d, 3-d, 4-d, and higher dimensions. It implements the Quickhull algorithm for computing the convex hull. Qhull handles roundoff errors from floating point arithmetic. It computes volumes, surface areas, and approximations to the convex hull.
math/qhull-1.0 (Score: 0.10508093)
Qhull computes convex hulls, Delaunay triangulations, and halfspaces
Qhull computes convex hulls, Delaunay triangulations, halfspace intersections about a point, Voronoi diagrams, furthest-site Delaunay triangulations, and furthest-site Voronoi diagrams. It runs in 2-d, 3-d, 4-d, and higher dimensions. It implements the Quickhull algorithm for computing the convex hull. Qhull handles roundoff errors from floating point arithmetic. It computes volumes, surface areas, and approximations to the convex hull.
math/cdecimal-2.3 (Score: 0.10508093)
Fast drop-in replacement for the Decimal module
The cdecimal is a fast drop-in replacement for the decimal module in Python's standard library. Both modules provide complete implementations of the General Decimal Arithmetic Specification. Typical performance gains are between 30x for I/O heavy benchmarks and 80x for numerical programs. In a database benchmark, cdecimal exhibits a speedup of 12x over decimal.py. decimal cdecimal speedup pi 42.75s 0.58s 74x telco 172.19s 5.68s 30x psycopg 3.57s 0.29s 12x All Python versions from 2.5 up to 3.2 are supported. For the few remaining differences, read the cdecimal documentation. cdecimal has been included in Python-3.3.
math/fastcluster-1.1.20 (Score: 0.10508093)
Python functions for hierarchical clustering
Fastcluster provides Python functions for hierarchical clustering. It generates hierarchical clusters from distance matrices or from vector data. Part of this module is intended to replace the functions linkage, single, complete, average, weighted, centroid, median, ward in the module scipy.cluster.hierarchy with the same functionality but much faster algorithms. Moreover, the function 'linkage_vector' provides memory-efficient clustering for vector data. The interface is very similar to MATLAB's Statistics Toolbox API to make code easier to port from MATLAB to Python/Numpy. The core implementation of this library is in C++ for efficiency.
math/ffc-1.2.0 (Score: 0.10508093)
C++ code generator for multilinear forms
FFC works as a compiler for multilinear forms by generating code (C++) for the evaluation of a multilinear form given in mathematical notation.
math/reed-solomon-4.0 (Score: 0.10508093)
Reed-Solomon CODEC library
This is a port of Phil Karn's Reed-Solomon CODEC library. This package may be useful to programmers working on data communications software.
math/fiat-1.1.0 (Score: 0.10508093)
FInite element Automatic Tabulator
The FInite element Automatic Tabulator FIAT supports generation of arbitrary order instances of the Lagrange elements on lines, triangles, and tetrahedra.
math/RcppArmadillo-0.7.400.2.0 (Score: 0.10508093)
Rcpp integration for Armadillo templated linear algebra library
RcppArmadillo provides an interface from R to and from Armadillo by utilising the Rcpp R/C++ interface library.
math/gato-1.2.2 (Score: 0.10508093)
Python-based toolbox to visualise algorithms on graphs
Paraphrasing the website: Gato - the Graph Animation Toolbox - is software [toolkit] which visualizes algorithms on graphs. - Graphs are mathematical objects consisting of vertices, and edges connecting pairs of vertices. - Algorithms might find a shortest path - the fastest route - or a minimal spanning tree or solve one of other interesting problems on graphs: maximal-flow, weighted and non-weighted matching and min-cost flow. - Visualisation means linking cause - the statements of an algorithm - immediately to an effect - changes to the graph the algorithm has as its input - by terms of blinking, changing colors and other visual effects.
math/cgal-4.8.1 (Score: 0.10508093)
Computational geometry library
CGAL is a collaborative effort of several sites in Europe and Israel. The goal is to make the most important of the solutions and methods developed in computational geometry available to users in industry and academia in a C++ library. The goal is to provide easy access to useful, reliable geometric algorithms. The CGAL library contains: * the Kernel with geometric primitives such as points, vectors, lines, predicates for testing things such as relative positions of points, and operations such as intersections and distance calculation. * the Basic Library which is a collection of standard data structures and geometric algorithms, such as convex hull in 2D/3D, (Delaunay) triangulation in 2D/3D, planar map, polyhedron, smallest enclosing circle, and multidimensional query structures. * the Support Library which offers interfaces to other packages, e.g., for visualisation, and I/O, and other support facilities.