This package contains a set of routines for computing the LDL' factorization of sparse, symmetric matrices. Its focus lies on concise code.

CyLP is a Python interface to COIN-OR’s Linear and mixed-integer program solvers (CLP, CBC, and CGL). CyLP’s unique feature is that you can use it to alter the solution process of the solvers from within Python. For example, you may define cut generators, branch-and-bound strategies, and primal/dual Simplex pivot rules completely in Python.

SLEPc is a software library for the solution of large sparse eigenproblems on parallel computers. It can be used for the solution of linear eigenvalue problems formulated in either standard or generalized form, as well as other related problems such as the singular value decomposition. The emphasis of the software is on methods and techniques appropriate for problems in which the associated matrices are sparse, for example, those arising after the discretization of partial differential equations.

IT++ is a C++ library of mathematical, signal processing and communication classes and functions. Its main use is in simulation of communication systems and for performing research in the area of communications. The kernel of the library consists of generic vector and matrix classes, and a set of accompanying routines. Such a kernel makes IT++ similar to MATLAB, GNU Octave or SciPy.

DUNE, the Distributed and Unified Numerics Environment is a modular toolbox for solving partial differential equations (PDEs) with grid-based methods.

This is the iterative solver template library which provides generic sparse matrix/vector classes and a variety of solvers based on these classes. A special feature is the use of templates to exploit the recursive block structure of finite element matrices at compile time. Available solvers include Krylov methods, (block-) incomplete decompositions and aggregation-based algebraic multigrid.

The Parma Polyhedra Library (PPL) provides numerical abstractions especially targeted at applications in the field of analysis and verification of complex systems. These abstractions include convex polyhedra, defined as the intersection of a finite number of (open or closed) halfspaces, each described by a linear inequality (strict or non-strict) with rational coefficients; some special classes of polyhedra shapes that offer interesting complexity/precision tradeoffs; and grids which represent regularly spaced points that satisfy a set of linear congruence relations. The library also supports finite powersets and products of (any kind of) polyhedra and grids, a mixed integer linear programming problem solver using an exact-arithmetic version of the simplex algorithm, a parametric integer programming solver, and primitives for termination analysis via the automatic synthesis of linear ranking functions.

MUMPS (MUltifrontal Massively Parallel sparse direct Solver) solves a sparse system of linear equations A x = b using Gaussian elimination.

Openspecfun provides AMOS and Faddeeva. AMOS (from Netlib) is a portable package for Bessel Functions of a Complex Argument and Nonnegative Order; it contains subroutines for computing Bessel functions and Airy functions. Faddeeva allows computing the various error functions of arbitrary complex arguments (Faddeeva function, error function, complementary error function, scaled complementary error function, imaginary error function, and Dawson function); given these, one can also easily compute Voigt functions, Fresnel integrals, and similar related functions as well.

This package provides a C++ implementation of the Louvain community detection algorithm.

PETSc, the Portable, Extensible Toolkit for Scientific Computation, is a suite of data structures and routines for the scalable (parallel) solution of scientific applications modeled by partial differential equations. It employs the MPI standard for all message-passing communication. petsc4py provides Python bindings to almost all functions of PETSc.

ALUGrid is an adaptive, loadbalancing, unstructured implementation of the DUNE grid interface supporting either simplices or cubes.

This library implements the math.h functions in fixed point (16.16) format.

CHOLMOD is a set of routines for factorizing sparse symmetrix positive definite matrices, updating/downdating sparse Cholesky factorizations and other related operations.

This package provides a Mathics3 frontend for Jupyter Notebook and Marimo.

This package provides the C library of RBio. It can be used for reading and writing sparse matrices in the Rutherford/Boeing format.

DUNE, the Distributed and Unified Numerics Environment is a modular toolbox for solving partial differential equations (PDEs) with grid-based methods. It supports the easy implementation of methods like Finite Elements (FE), Finite Volumes (FV), and also Finite Differences (FD).

This package contains the DUNE UG grid classes.

hmat-oss is hierarchical matrix library written in C++ with a C API. It contains a LU and LLt solver, and a few other things.

LinAsm is collection of very fast and SIMD optimized assembly written libraries for x86-64.

It implements many common and widely used algorithms for array manipulations: searching, sorting, arithmetic and vector operations, unit conversions; fast mathematical and statistic functions; numbers and time converting algorithms; finite impulse response (FIR) digital filters; spectrum analysis algorithms, Fast Hartley transformation; CPU cache friendly functions and extremely fast abstract data types (ADT) such as hash tables b-trees, and much more.

More than 1500 numerical integration schemes for line segments, circles, disks, triangles, quadrilaterals, spheres, balls, tetrahedra, hexahedra, wedges, pyramids, n-spheres, n-balls, n-cubes, n-simplices, and the 1D/2D/3D/nD spaces with weight functions exp(-r) and exp(-r2) for fast integration of real-, complex-, and vector-valued functions.

HDF5 is a suite that makes possible the management of extremely large and complex data collections.

Py-BOBYQA is a flexible package for solving bound-constrained general objective minimization, without requiring derivatives of the objective. At its core, it is a Python implementation of the BOBYQA algorithm by Powell,but Py-BOBYQA has extra features improving its performance on some problems. Py-BOBYQA is particularly useful when evaluations of the objective function are expensive and/or noisy.

PnetCDF is a high-performance parallel I/O library for accessing Unidata's NetCDF, files in classic formats, specifically the formats of CDF-1, 2, and 5.

This package provides the Blis BLAS-like linear algebra library, as a self-contained C-extension for Python.

SCOTCH is a set of programs and libraries which implement the static mapping and sparse matrix reordering algorithms developed within the SCOTCH project. Its purpose is to apply graph theory, with a divide and conquer approach, to scientific computing problems such as graph and mesh partitioning, static mapping, and sparse matrix ordering, in application domains ranging from structural mechanics to operating systems or bio-chemistry.