Debian Science Project
Summary
Numerical computation
Debian Science Numerical Computation packages

This metapackage will install Debian Science packages useful for numerical computation. The packages provide an array oriented calculation and visualisation system for scientific computing and data analysis. These packages are similar to commercial systems such as Matlab and IDL.

Description

For a better overview of the project's availability as a Debian package, each head row has a color code according to this scheme:

If you discover a project which looks like a good candidate for Debian Science to you, or if you have prepared an unofficial Debian package, please do not hesitate to send a description of that project to the Debian Science mailing list

Links to other tasks

Debian Science Numerical computation packages

Official Debian packages with high relevance

Admesh
Tool for processing triangulated solid meshes. Binary
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Currently, ADMesh only reads the STL file format that is used for rapid prototyping applications, although it can write STL, VRML, OFF, and DXF files. Some features of admesh are: Fill holes in the mesh by adding facets. Repair facets by connecting nearby facets. Repair normal directions (i.e. facets should be CCW) Remove degenerate facets (i.e. facets with 2 or more vertices equal)

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Algotutor
program for observing the intermediate steps of algorithm
Maintainer: Georges Khaznadar
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algotutor is an interactive program for observing the intermediate steps of algorithms ("algorithm animation"). The target audience is computer science students and/or anyone who studies algorithms and/or data structures. One can create data files in plain text format (actually perl anonymous hashes, but one need not care) and let algotutor runs through some predefined algorithm. Then one can step backward and forward through the execution sequence of the algorithm at different levels of details.

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Calculix-ccx
Three-Dimensional Structural Finite Element Program
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CalculiX is a free and open source finite element analysis application that uses a similar input format to Abaqus. It has an implicit and explicit solver and a pre and post processor (CGX). This package contains the solver CalculiX CrunchiX (cxx).

Calculix-cgx
Calculix cgx is a 3-dimensional pre- and post-processor for fem
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CalculiX GraphiX (cgx) is a 3-dimensional pre- and post-processor for finite elemnts. CalculiX CrunchiX Finite Element Models can be build, calculated and post-processed. The pre- and post-processor is an interactive 3D-tool using the openGL API.

In addition to the Calculix CrunchiX results files (frd) results from OpenFoam, Duns (2D and 3D), Isaac (2D and 3D) and Nastran (f06) can be read. For preprocessing Netgen nativ format, STEP and STL can be imported.

Coinor-cbc
Coin-or branch-and-cut mixed integer programming solver
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Cbc (Coin-or branch and cut) is an open-source mixed integer programming solver written in C++. It can be used as a callable library or as a stand-alone executable.

This package contains cbc executable.

Coinor-clp
Coin-or linear programming solver
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Clp (Coin-or linear programming) is an open-source linear programming solver written in C++. It is primarily meant to be used as a callable library, but a basic, stand-alone executable version is also available. It is designed to find solutions of constrained linear mathematical optimization problems.

This package contains the clp executable.

Coinor-symphony
COIN-OR solver for mixed-integer linear programs
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SYMPHONY is an open-source generic mixed-integer linear programs (MILP) solver, callable library, and extensible framework for implementing customized solvers SYMPHONY has a number of advanced capabilities, including the ability to solve multi-objective MILPs, the ability to warm start its solution procedure, and the ability to perform basic sensitivity analyses.

SYMPHONY is part of the larger COIN-OR initiative (Computational Infrastructure for Operations Research).

This package contains the symphony executable.

Esys-particle
Software for particle-based numerical modelling. MPI version.
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ESyS-Particle is Open Source software for particle-based numerical modelling. The software implements the Discrete Element Method (DEM), a widely used technique for modelling processes involving large deformations, granular flow and/or fragmentation. ESyS-Particle is designed for execution on parallel supercomputers, clusters or multi-core PCs running a Linux-based operating system. The C++ simulation engine implements spatial domain decomposition via the Message Passing Interface (MPI). A Python wrapper API provides flexibility in the design of numerical models, specification of modelling parameters and contact logic, and analysis of simulation data. ESyS-Particle has been utilised to simulate earthquake nucleation, comminution in shear cells, silo flow, rock fragmentation, and fault gouge evolution, to name but a few applications.

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Freemat
mathematics framework (mostly matlab compatible)
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FreeMat is a free environment for rapid engineering and scientific prototyping and data processing. It is similar to commercial systems such as MATLAB from Mathworks, and IDL from Research Systems, but is Open Source. FreeMat is available under the GPL license.

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Gnudatalanguage
Free IDL compatible incremental compiler
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GNU Data Language (GDL) is a free IDL (Interactive Data Language) compatible incremental compiler. It has full syntax compatibility with IDL 7.1. IDL is a registered trademark of ITT Visual Information Solutions. From IDL 8.0, the following language elements are supported:

  • FOREACH loop
  • negative array indices
  • garbage collection pointers and objects
  • call methods on an object using "." (e. g. object.aMemberProcedure,arg1)

The file input output system is fully implemented. GUI support (widgets) is officially provided, but it's not complete yet.

This package contains the main commandline and interpreter frontend.

Please cite: A. Coulais, M. Schellens, J. Gales, S. Arabas, M. Boquien, P. Chanial, P. Messmer, D. Fillmore, O. Poplawski, S. Maret, G. Marchal, N. Galmiche and T. Mermet: Status of GDL - GNU Data Language. (eprint) Astronomical Data Analysis Software and Systems XIX 434:187 (2010)
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Iep
transitional dummy package for IEP
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Pyzo is a cross-platform Python IDE focused on interactivity and introspection, which makes it very suitable for scientific computing. Its practical design is aimed at simplicity and efficiency.

It consists of two main components, the editor and the shell, and uses a set of pluggable tools to help the programmer in various ways. Some example tools are source structure, project manager, interactive help, workspace...

Pyzo is written in (pure) Python 3 and uses the Qt GUI toolkit. Binaries are provided for all major operating system. After installing Pyzo, it can be used to execute code on any Python version available on your system (Python 2.4 - 3.x, including Pypy).

This is a transitional dummy package enabling the upgrade from IEP to Pyzo. It can safely be removed.

Ipython
Enhanced interactive Python 2 shell
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IPython can be used as a replacement for the standard Python shell, or it can be used as a complete working environment for scientific computing (like Matlab or Mathematica) when paired with the standard Python scientific and numerical tools. It supports dynamic object introspections, numbered input/output prompts, a macro system, session logging, session restoring, complete system shell access, verbose and colored traceback reports, auto-parentheses, auto-quoting, and is embeddable in other Python programs.

This package contains the actual terminal shell for Python 2.

The package is enhanced by the following packages: powerline python-matplotlib
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Julia
high-performance programming language for technical computing
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Julia is a high-level, high-performance dynamic programming language for technical computing, with syntax that is familiar to users of other technical computing environments. It provides a sophisticated compiler, distributed parallel execution, numerical accuracy, and an extensive mathematical function library. The library, mostly written in Julia itself, also integrates mature, best-of-breed C and Fortran libraries for linear algebra, random number generation, FFTs, and string processing. Julia programs are organized around defining functions, and overloading them for different combinations of argument types (which can also be user-defined).

This package provides a complete Julia installation (JIT compiler, standard library, text-based user interface).

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Lammps
Molecular Dynamics Simulator
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LAMMPS is a classical molecular dynamics code, and an acronym for Large-scale Atomic/Molecular Massively Parallel Simulator.

LAMMPS has potentials for soft materials (biomolecules, polymers) and solid-state materials (metals, semiconductors) and coarse-grained or mesoscopic systems. It can be used to model atoms or, more generically, as a parallel particle simulator at the atomic, meso, or continuum scale.

LAMMPS runs on single processors or in parallel using message-passing techniques and a spatial-decomposition of the simulation domain. The code is designed to be easy to modify or extend with new functionality.

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Libadolc-dev
ADOLC development libs and headers
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The ADOLC system automatically calculates exact derivatives of a C/C++ function. It uses C++ overloading to record arithmetic operations, which it plays back later in various ways to calculate the requested values.

This package contains the development library, header files, and user's manual.

Libarrayfire-unified-dev
Development files for ArrayFire (unified backend)
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ArrayFire is a high performance software library for parallel computing with an easy-to-use API. Its array based function set makes parallel programming simple.

ArrayFire's multiple backends (CUDA, OpenCL and native CPU) make it platform independent and highly portable.

A few lines of code in ArrayFire can replace dozens of lines of parallel computing code, saving you valuable time and lowering development costs.

This package provides the development files for the unified backend of the ArrayFire library.

Please cite: P. Yalamanchili, U. Arshad, Z. Mohammed, P. Garigipati, P. Entschev, B. Kloppenborg, J. Malcolm and J. Melonakos: ArrayFire - A high performance software library for parallel computing with an easy-to-use API (2015)
Libceres-dev
nonlinear least squares minimizer (development files)
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Ceres Solver is an open source C++ library for modeling and solving large, complicated optimization problems. It is a feature rich, mature and performant library which has been used in production at Google since 2010.

Ceres Solver can solve two kinds of problems.

  • Non-linear Least Squares problems with bounds constraints.
  • General unconstrained optimization problems.

This package contains the development header files.

Libclblas-dev
development files for clBLAS
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This library provides an implementation of the Basic Linear Algebra Subprograms levels 1, 2 and 3, using OpenCL and optimized for AMD GPU hardware.

This package provides the development files.

Libclfft-dev
development files for clFFT
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The clFFT library is an open source OpenCL library implementation of discrete Fast Fourier Transforms, which:

  • Provides a fast and accurate platform for calculating discrete FFTs.
  • Works on CPU or GPU backends.
  • Supports in-place or out-of-place transforms.
  • Supports 1D, 2D, and 3D transforms with a batch size that can be greater than 1.
  • Supports planar (real and complex components in separate arrays) and interleaved (real and complex components as a pair contiguous in memory) formats.
  • Supports dimension lengths that can be any mix of powers of 2, 3, and 5.
  • Supports single and double precision floating point formats.

This package provides the development files.

Libclsparse-dev
development files for clSPARSE
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clSPARSE provides fundamental sparse operations for OpenCL, including:

  • Sparse Matrix - dense Vector multiply (SpM-dV)
  • Sparse Matrix - dense Matrix multiply (SpM-dM)
  • Iterative conjugate gradient solver (CG)
  • Iterative biconjugate gradient stabilized solver (BiCGStab)
  • Dense to CSR conversions (& converse)
  • COO to CSR conversions (& converse)
  • Functions to read matrix market files in COO or CSR format

This package provides the development files.

Libcolpack-dev
Specialized graph vertex coloring library, development files
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ColPack is a package comprising of implementation of algorithms for specialized vertex coloring problems that arise in sparse derivative computation. It is written in an object-oriented fashion heavily using the Standard Template Library (STL). It is designed to be simple, modular, extenable and efficient. Its primary application has been for use in automatic differentiation.

This package contains the development library, header files, and documentation.

Libdune-grid-dev
toolbox for solving PDEs -- grid interface (development files)
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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 development files for the grid interface.

Libopengm-dev
C++ template library for discrete factor graph models
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OpenGM is a C++ template library for discrete factor graph models and distributive operations on these models.

It includes state-of-the-art optimization and inference algorithms beyond message passing. OpenGM handles large models efficiently, is modular and extendible. The graphical model data structure, inference algorithms and different encodings of functions inter-operate through well-defined interfaces. The binary OpenGM file format is based on the HDF5 standard and incorporates user extensions automatically.

This package contains the development headers for the OpenGM library.

Please cite: B. Andres, T. Beier and J.H. Kappes: OpenGM: A C++ Library for Discrete Graphical Models. (eprint) CoRR abs/1206.0111 (2012)
Libppl-dev
Parma Polyhedra Library (development)
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The Parma Polyhedra Library (PPL) is a C++ library for the manipulation of (not necessarily closed) convex polyhedra and other numerical abstractions. The applications of convex polyhedra include program analysis, optimized compilation, integer and combinatorial optimization and statistical data-editing. The Parma Polyhedra Library is user friendly (you write `x + 2y + 5z <= 7' when you mean it), fully dynamic (available virtual memory is the only limitation to the dimension of anything), written in standard C++, exception-safe, rather efficient and thoroughly documented.

This package provides the header files and static libraries for the C and C++ interfaces.

Libqsopt-ex-dev
Exact linear programming solver -- development files
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QSopt-ex is an implementation of a simplex-based algorithm that returns exact rational solutions, taking advantage of the speed of floating-point calculations and attempting to minimize the operations performed in rational arithmetic.

This package contains the header files and static library.

Please cite: David L Applegate, William Cook, Sanjeeb Dash and Daniel G Espinoza: Exact solutions to linear programming problems. Operations Research Letters 35(6):693-699 (2007)
Librsb-dev
recursive sparse blocks matrix computations library (development)
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This is a library for sparse matrix computations featuring the Recursive Sparse Blocks (RSB) matrix format. This format allows cache efficient and multi-threaded (that is, shared memory parallel) operations on large sparse matrices. It provides the most common operations necessary to iterative solvers, like matrix-vector multiplication, triangular solution, rows/columns scaling, diagonal extraction / setting, blocks extraction, norm computation, formats conversion. The RSB format is especially well suited for symmetric and transposed multiplication variants.

This package contains the static libraries for development with librsb, including examples and the rsbench utility.

Please cite: Michele Martone, Marcin Paprzycki and Salvatore Filippone: An Improved Sparse Matrix-Vector Multiply Based on Recursive Sparse Blocks Layout. :606-613 (2012)
Libsuitesparse-dev
libraries for sparse matrices computations (development files)
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Suitesparse is a collection of libraries for computations involving sparse matrices. This package includes the following libraries:

AMD approximate minimum degree ordering

CAMD symmetric approximate minimum degree

BTF permutation to block triangular form (beta)

COLAMD column approximate minimum degree ordering

CCOLAMD constrained column approximate minimum degree ordering

CHOLMOD sparse Cholesky factorization

CXSparse a concise sparse matrix package

KLU sparse LU factorization, primarily for circuit simulation

LDL a simple LDL' factorization

UMFPACK sparse LU factorization

RBio read/write sparse matrices in Rutherford/Boeing format

SPQR sparse QR factorization

SuiteSparse_config configuration routines for all the above packages.

This package contains the static libraries and header files.

Liggghts
Open Source DEM Particle Simulation Software.
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LIGGGHTS stands for LAMMPS improved for general granular and granular heat transfer simulations.

LAMMPS is a classical molecular dynamics simulator. It is widely used in the field of Molecular Dynamics. Thanks to physical and algorithmic analogies, LAMMPS is a very good platform for DEM simulations. LAMMPS offers a GRANULAR package to perform these kind of simulations. LIGGGHTS aims to improve those capability with the goal to apply it to industrial applications. Development version.

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Metis
Serial Graph Partitioning and Fill-reducing Matrix Ordering. Binaries
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METIS is a set of serial programs for partitioning graphs, partitioning finite element meshes, and producing fill reducing orderings for sparse matrices. The algorithms implemented in METIS are based on the multilevel recursive-bisection, multilevel k-way, and multi-constraint partitioning schemes. The package contains some binaries for graph analyzing.

Octave
GNU Octave language for numerical computations
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Octave is a (mostly Matlab (R) compatible) high-level language, primarily intended for numerical computations. It provides a convenient command-line interface for solving linear and nonlinear problems numerically.

Octave can be dynamically extended with user-supplied C++ files.

The package is enhanced by the following packages: texmacs
Please cite: John W. Eaton, David Bateman, Søren Hauberg and Rik Wehbring: GNU Octave version 4.2.0 manual: a high-level interactive language for numerical computations. (2016)
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Pdl
perl data language: Perl extensions for numerics
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PDL gives standard perl the ability to COMPACTLY store and SPEEDILY manipulate the large N-dimensional data arrays which are the bread and butter of scientific computing. The idea is to turn perl in to a free, array-oriented, numerical language in the same sense as commercial packages like IDL and MatLab. One can write simple perl expressions to manipulate entire numerical arrays all at once. For example, using PDL the perl variable $a can hold a 1024x1024 floating point image, it only takes 4Mb of memory to store it and expressions like $a=sqrt($a)+2 would manipulate the whole image in a few seconds.

A simple interactive shell (perldl) is provided for command line use together with a module (PDL) for use in perl scripts.

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Python-csa
Connection-Set Algebra (CSA) implemented in Python
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The CSA library provides elementary connection-sets and operators for combining them. It also provides an iteration interface to such connection-sets enabling efficient iteration over existing connections with a small memory footprint also for very large networks. The CSA can be used as a component of neuronal network simulators or other tools.

Python-demgengeo
DEMGenGeo is a library for creating geometry files
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DEMGenGeo is a library for creating geometry files used by ESyS-Particle. It provides a convenient method for creating arbitrary geometries of simple spherical particles and indivisible particle clusters. An LSMGenGeo script written in Python specifies the geometry that will be written to a text file and the format that this file takes. The geometry file can then be read by an ESyS-Particle script

Python-escript
Escript/Finley finite elements Python2 system (with OpenMP)
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Escript is a programming tool for implementing mathematical models in Python using the finite element method (FEM). Because users do not access the data structures it is very easy to use and scripts can run on desktop computers as well as highly parallel supercomputer without changes. Application areas for escript include earth mantle convection, geophysical inversion, earthquakes, porous media flow, reactive transport, plate subduction, erosion, and tsunamis.

Scripts can be executed in parallel (on varying numbers of threads or nodes) without any special modifications.

Escript now includes the esys.downunder module for 3D inversion of geophysical data sets. The current version supports gravity, magnetic and joint inversion.

This package contains the commands and libraries for Python2 with OpenMP threading.

Python-gts
Python wrapper for the GNU Triangulated Surface library (GTS)
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PyGTS is a Python package used to construct, manipulate, and perform computations on 3D triangulated surfaces. It is a hand-crafted and pythonic binding for the GNU Triangulated Surface (GTS) Library.

Python-pysph
open source framework for Smoothed Particle Hydrodynamics
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It is implemented in Python and the performance critical parts are implemented in Cython.

PySPH is implemented in a way that allows a user to specify the entire SPH simulation in pure Python. High-performance code is generated from this high-level Python code, compiled on the fly and executed. PySPH also features optional automatic parallelization using mpi4py and Zoltan.

Python-scitools
Python library for scientific computing
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SciTools is a Python package containing lots of useful tools for scientific computing in Python. The package is built on top of other widely used packages such as NumPy, SciPy, ScientificPython, Gnuplot, etc.

SciTools also comes with a plotting interface called Easyviz, which is a unified interface to various packages for scientific visualization and plotting. Both curve plots and more advanced 2D/3D visualization of scalar and vector fields are supported. The Easyviz interface was designed with three ideas in mind: 1) a simple, Matlab-like syntax; 2) a unified interface to lots of visualization engines (backends): Gnuplot, Matplotlib, Grace, Veusz, Pmw.Blt.Graph, PyX, Matlab, VTK, VisIt, OpenDX; and 3) a minimalistic interface which offers only basic control of plots: curves, linestyles, legends, title, axis extent and names. More fine-tuning of plots can be done by adding backend-specific commands.

Python-sfepy
Simple Finite Elements in Python
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SfePy is a software for solving systems of coupled partial differential equations (PDEs) by the finite element method in 1D, 2D and 3D. It can be viewed both as black-box PDE solver, and as a Python package which can be used for building custom applications. The word “simple” means that complex FEM problems can be coded very easily and rapidly.

Python3-arrayfire
ArrayFire bindings for Python 3
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ArrayFire is a high performance library for parallel computing with an easy-to-use API. It enables users to write scientific computing code that is portable across CUDA, OpenCL and CPU devices. This project provides Python bindings for the ArrayFire library.

This package provides the bindings for Python 3.

Python3-bitstring
Python module for manipulation of binary data (Python 3)
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Bitstring is a pure Python module designed to help make the creation and analysis of binary data as simple and natural as possible.

Bitstrings can be constructed from integers (big and little endian), hex, octal, binary, strings or files. They can be sliced, joined, reversed, inserted into, overwritten, etc. with simple functions or slice notation. They can also be read from, searched and replaced, and navigated in, similar to a file or stream.

This package provides the Python 3 version of the module.

Python3-deap
Distributed Evolutionary Algorithms in Python3
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DEAP is a novel evolutionary computation framework for rapid prototyping and testing of ideas. It seeks to make algorithms explicit and data structures transparent. It works in perfect harmony with parallelisation mechanism such as multiprocessing and SCOOP.

This package contains the modules for Python3.

Python3-guiqwt
efficient 2D data-plotting library - Python 3
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The guiqwt Python library provides efficient 2D data-plotting features (curve/image visualization and related tools) for signal/image processing application development and interactive computing. It's based on the scientific modules NumPy and SciPy, and the PyQwt plotting widgets for PyQt4 graphical user interfaces.

This is the Python 3 version of the package.

Python3-lmfit
Least-Squares Minimization with Constraints (Python 3)
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The lmfit Python package provides a simple, flexible interface to non-linear optimization or curve fitting problems. The package extends the optimization capabilities of scipy.optimize by replacing floating pointing values for the variables to be optimized with Parameter objects. These Parameters can be fixed or varied, have upper and/or lower bounds placed on its value, or written as an algebraic expression of other Parameters.

The principal advantage of using Parameters instead of simple variables is that the objective function does not have to be rewritten to reflect every change of what is varied in the fit, or what relationships or constraints are placed on the Parameters. This means a scientific programmer can write a general model that encapsulates the phenomenon to be optimized, and then allow user of that model to change what is varied and fixed, what range of values is acceptable for Parameters, and what constraints are placed on the model. The ease with which the model can be changed also allows one to easily test the significance of certain Parameters in a fitting model.

The lmfit package allows a choice of several optimization methods available from scipy.optimize. The default, and by far best tested optimization method used is the Levenberg-Marquardt algorithm from from MINPACK-1 as implemented in scipy.optimize.leastsq. This method is by far the most tested and best support method in lmfit, and much of this document assumes this algorithm is used unless explicitly stated. An important point for many scientific analysis is that this is only method that automatically estimates uncertainties and correlations between fitted variables from the covariance matrix calculated during the fit.

A few other optimization routines are also supported, including Nelder-Mead simplex downhill, Powell's method, COBYLA, Sequential Least Squares methods as implemented in scipy.optimize.fmin, and several others from scipy.optimize. In their native form, some of these methods setting allow upper or lower bounds on parameter variables, or adding constraints on fitted variables. By using Parameter objects, lmfit allows bounds and constraints for all of these methods, and makes it easy to swap between methods without hanging the objective function or set of Parameters.

Finally, because the approach derived from MINPACK-1 usin the covariance matrix to determine uncertainties is sometimes questioned (and sometimes rightly so), lmfit supports methods to do a brute force search of the confidence intervals and correlations for sets of parameters.

This is the Python 3 version of the package.

Python3-matplotlib
Python based plotting system in a style similar to Matlab (Python 3)
Maintainer: Sandro Tosi
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Matplotlib is a pure Python plotting library designed to bring publication quality plotting to Python with a syntax familiar to Matlab users. All of the plotting commands in the pylab interface can be accessed either via a functional interface familiar to Matlab users or an object oriented interface familiar to Python users.

This package contains the Python 3 version of matplotlib.

Python3-numpy
Fast array facility to the Python 3 language
Maintainer: Sandro Tosi
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Numpy contains a powerful N-dimensional array object, sophisticated (broadcasting) functions, tools for integrating C/C++ and Fortran code, and useful linear algebra, Fourier transform, and random number capabilities.

Numpy replaces the python-numeric and python-numarray modules which are now deprecated and shouldn't be used except to support older software.

This package contains Numpy for Python 3.

The package is enhanced by the following packages: python3-shapely
Python3-pydap
implementation of the Data Access Protocol in Python
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Pydap is an implementation of the Opendap/DODS protocol, written from scratch. You can use Pydap to access scientific data on the internet without having to download it; instead, you work with special array and iterable objects that download data on-the-fly as necessary, saving bandwidth and time. The module also comes with a robust-but-lightweight Opendap server, implemented as a WSGI application.

This package provides the modules for Python 3.

Python3-scipy
scientific tools for Python 3
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SciPy supplements the popular NumPy module (python-numpy package), gathering a variety of high level science and engineering modules together as a single package.

SciPy is a set of Open Source scientific and numeric tools for Python. It currently supports special functions, integration, ordinary differential equation (ODE) solvers, gradient optimization, genetic algorithms, parallel programming tools, an expression-to-C++ compiler for fast execution, and others.

This package provides the Python 3 version.

Python3-sparse
multidimensional sparse arrays for Python
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This package implements sparse multidimensional arrays on top of NumPy and scipy.sparse. It generalizes the scipy.sparse.coo_matrix layout but extends beyond just rows and columns to an arbitrary number of dimensions. The original motivation is for machine learning algorithms, but it is intended for somewhat general use.

It supports:

  • NumPy ufuncs (where zeros are preserved)
  • Arithmetic with scalars (where zeros are preserved)
  • Reductions (sum, max)
  • Reshape
  • Transpose
  • Tensordot
  • Slicing with integers, lists, and slices (with no step value)
  • Concatenation and stacking
  • Addition with other sparse arrays of the same shape

This package provides the modules for Python 3.

Python3-tables
hierarchical database for Python3 based on HDF5
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PyTables is a hierarchical database package designed to efficiently manage very large amounts of data. PyTables is built on top of the HDF5 library and the NumPy package. It features an object-oriented interface that, combined with natural naming and C-code generated from Pyrex sources, makes it a fast, yet extremely easy to use tool for interactively save and retrieve large amounts of data.

  • Compound types (records) can be used entirely from Python (i.e. it is not necessary to use C for taking advantage of them).
  • The tables are both enlargeable and compressible.
  • I/O is buffered, so you can get very fast I/O, specially with large tables.
  • Very easy to select data through the use of iterators over the rows in tables. Extended slicing is supported as well.
  • It supports the complete set of NumPy, Numeric and numarray objects.

This is the Python 3 version of the package.

Python3-theano
CPU/GPU math expression compiler for Python 3
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Theano is a Python library that allows one to define and evaluate mathematical expressions involving multi-dimensional arrays efficiently. It provides a high-level Numpy like expression language for functional description of calculation, rearranges expressions for speed and stability, and generates native machine instructions for fast calculation. Optionally, highly accelerated computations could be carried out on graphics cards processors.

This package contains Theano for Python 3.

Python3-woo
Discrete dynamic compuations, esp. granular mechanics (python 3)
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Extesible and portable framework primarily for mechanics granular materials. Computation parts are written in c++ parallelized using OpenMP, fully accessible and modifiable from python (ipython console or scripts). Arbitrarily complex scene can be scripted. Qt-based user interface is provided, featuring flexible OpenGL display, inspection of all objects and runtime modification. Parametric preprocessors can be written in pure python, and batch system can be used to drive parametric studies. New material models and particle shapes can be added (in c++) without modifying existing classes.

Woo is an evolution of the Yade package (http://www.launchpad.net/yade), aiming at more flexibility, extensibility, tighter integration with python and user-friendliness.

This version is built with OpenMP enabled, and targets Python 3.x.

Python3-xarray
N-D labeled arrays and datasets in Python 3
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xarray (formerly xray) is an open source project and Python package that aims to bring the labeled data power of pandas to the physical sciences, by providing N-dimensional variants of the core pandas data structures.

It provides a pandas-like and pandas-compatible toolkit for analytics on multi-dimensional arrays, rather than the tabular data for which pandas excels.

This package provides the Python 3 library

Pyzo
interactive editor for scientific Python
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Pyzo is a cross-platform Python IDE focused on interactivity and introspection, which makes it very suitable for scientific computing. Its practical design is aimed at simplicity and efficiency.

It consists of two main components, the editor and the shell, and uses a set of pluggable tools to help the programmer in various ways. Some example tools are source structure, project manager, interactive help, workspace...

Pyzo is written in (pure) Python 3 and uses the Qt GUI toolkit. Binaries are provided for all major operating system. After installing Pyzo, it can be used to execute code on any Python version available on your system (Python 2.4 - 3.x, including Pypy).

This package provides the Pyzo IDE.

Qsopt-ex
Exact linear programming solver
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QSopt-ex is an implementation of a simplex-based algorithm that returns exact rational solutions, taking advantage of the speed of floating-point calculations and attempting to minimize the operations performed in rational arithmetic.

This package contains the command-line utilities.

Please cite: David L Applegate, William Cook, Sanjeeb Dash and Daniel G Espinoza: Exact solutions to linear programming problems. Operations Research Letters 35(6):693-699 (2007)
R-base
GNU R statistical computation and graphics system
Maintainer: Dirk Eddelbuettel
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R is a system for statistical computation and graphics. It consists of a language plus a run-time environment with graphics, a debugger, access to certain system functions, and the ability to run programs stored in script files.

The design of R has been heavily influenced by two existing languages: Becker, Chambers & Wilks' S and Sussman's Scheme. Whereas the resulting language is very similar in appearance to S, the underlying implementation and semantics are derived from Scheme.

The core of R is an interpreted computer language which allows branching and looping as well as modular programming using functions. Most of the user-visible functions in R are written in R. It is possible for the user to interface to procedures written in the C, C++, or FORTRAN languages for efficiency, and many of R's core functions do so. The R distribution contains functionality for a large number of statistical procedures and underlying applied math computations. There is also a large set of functions which provide a flexible graphical environment for creating various kinds of data presentations.

Additionally, several thousand extension "packages" are available from CRAN, the Comprehensive R Archive Network, many also as Debian packages, named 'r-cran-'.

This package is a metapackage which eases the transition from the pre-1.5.0 package setup with its larger r-base package. Once installed, it can be safely removed and apt-get will automatically upgrade its components during future upgrades. Providing this package gives a way to users to then only install r-base-core if they so desire.

The package is enhanced by the following packages: texmacs
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R-cran-nleqslv
GNU R package for solving systems of nonlinear equations
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This R package solves a system of nonlinear equations using a Broyden or a Newton method with a choice of global strategies such as line search and trust region. There are options for using a numerical or user supplied Jacobian, for specifying a banded numerical Jacobian and for allowing a singular or ill-conditioned Jacobian.

Scilab
Scientific software package for numerical computations
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Scilab is a matrix-based scientific software package. Scilab contains hundreds of built-in mathematical functions, rich data structures (including polynomials, rationals, linear systems, lists, etc...) and comes with a number of specific toolboxes for control, signal processing, ...

This package also provides Xcos, a graphical editor to design hybrid dynamical systems models. Models can be designed, loaded, saved, compiled and simulated. Stable and efficient solution for industrial and academics needs, Xcos provides functionalities for modeling of mechanical systems (automotive, aeronautics...), hydraulic circuits (dam, pipe modeling...), control systems, etc. Modelica capabilities are also provided.

For a minimum version of scilab, install package "scilab-cli".

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Scilab-ann
Scilab module for artificial neural networks
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This module implements artificial neural networks capabilities into the Scilab language. Current features are:

  • Only layered feedforward networks are supported directly at the moment (for others use the "hooks" provided)
  • Unlimited number of layers
  • Unlimited number of neurons per each layer separately
  • User defined activation function (defaults to logistic)
  • User defined error function (defaults to SSE)
  • Algorithms implemented so far:
  • standard (vanilla) with or without bias, on-line or batch
  • momentum with or without bias, on-line or batch
  • SuperSAB with or without bias, on-line or batch
  • Conjugate gradients
  • Jacobian computation
  • Computation of result of multiplication between "vector" and Hessian
  • Some helper functions provided
Scilab-plotlib
"Matlab-like" Plotting library for Scilab
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This toolbox is providing plotting capabilities in the Scilab language. Plotlib functions matches the one from Matlab and therefor is dedicated to users switching from Matlab to Scilab.

Scilab-scimax
Symbolic computations for Scilab based on Maxima
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This toolbox is providing symbolic capabilities with the Scilab languages.

It is based on Maxima which is a fully symbolic computation program. It is full featured doing symbolic manipulation of polynomials, matrices, rational functions, integration, Todd-coxeter methods for finite group analysis, graphing, multiple precision floating point computation.

Spyder
Python IDE for scientists (Python 2)
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Spyder (previously known as Pydee) is a free open-source Python development environment providing MATLAB-like features in a simple and light-weighted software

This package provides the application for Python 2.

Toulbar2
Exact combinatorial optimization for Graphical Models
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Toulbar2 is an exact discrete optimization tool for Graphical Models such as Cost Function Networks, Markov Random Fields, Weighted Constraint Satisfaction Problems and Bayesian Nets.

Vitables
graphical tool to browse and edit PyTables and HDF5 files
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ViTables is a component of the PyTables family. It is a graphical tool for browsing and editing files in both PyTables and HDF5 formats.

ViTables capabilities include easy navigation through the data hierarchy, displaying of real data and its associated metadata, a simple, yet powerful, browsing of multidimensional data and much more.

One of the greatest strengths of ViTables is its ability to display very large tables. Tables with one thousand millions of rows (and beyond) are navigated stunningly fast and with very low memory requirements. So, if you ever need to browse very large tables, don't hesitate, ViTables is your choice.

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Xtensor-dev
multi-dimensional arrays with broadcasting and lazy computing
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xtensor is a C++ library meant for numerical analysis with multi-dimensional array expressions.

xtensor provides:

  • an extensible expression system enabling lazy broadcasting.
  • an API following the idioms of the C++ standard library.
  • tools to manipulate array expressions and build upon xtensor.

Containers of xtensor are inspired by NumPy, the Python array programming library. In fact, xtensor can be used to process numpy data structures inplace using Python's buffer protocol. For more details on the numpy bindings, check out the xtensor-python project.

This package provides the header-only library.

Xtensor-python-dev
Python bindings for the xtensor library
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xtensor is a C++ library for multi-dimensional arrays enabling numpy-style broadcasting and lazy computing.

xtensor-python enables inplace use of numpy arrays in C++ with all the benefits from xtensor:

  • C++ universal function and broadcasting
  • STL - compliant APIs.
  • A broad coverage of numpy APIs (see the numpy to xtensor cheat sheet).

The Python bindings for xtensor are based on the pybind11 C++ library, which enables seemless interoperability between C++ and Python.

This package provides the header-only library.

Yade
Platform for discrete element modeling
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Yet Another Dynamic Engine.

Extensible open-source framework for discrete numerical models, focused on Discrete Element Method. The computation parts are written in c++ using flexible object model, allowing independent implementation of new algorithms and interfaces. Python is used for rapid and concise scene construction, simulation control, postprocessing and debugging.

This package contains speed-optimized build of yade.

Please cite: V.ŠMilauer, E. Catalano, B. Chareyre, S. Dorofeenko, J. Duriez, A. Gladky, J. Kozicki, C. Modenese, L. Scholtès, L. Sibille, J. Stránský and K. Thoeni: Yade Documentation (V. Šmilauer, ed.), (eprint) The Yade Project, 1st ed. (2010)
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Yorick
interpreted language and scientific graphics
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Yorick is an interpreted programming language for:

  • scientific simulations or calculations
  • postprocessing or steering large simulation codes
  • interactive scientific graphics
  • reading, writing, and translating large files of numbers

The language features a compact syntax for many common array operations, so it processes large arrays of numbers very quickly and efficiently. Superficially, yorick code resembles C code, but yorick variables are never explicitly declared and have a dynamic scoping similar to many Lisp dialects. The yorick language is designed to be typed interactively at a keyboard, as well as stored in files for later use.

This package includes an emacs-based development environment, which you can launch by typing M-x yorick in emacs.

Many add-on packages and plug-ins are available for Yorick (the package names begin with "yorick-"). You may want to install the yorick-full metapackage which depends on the vast majority of them.

Screenshots of package yorick

Official Debian packages with lower relevance

Calculix-ccx-doc
Three-Dimensional Structural Finite Element Program (documentation files)
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CalculiX is a free and open source finite element analysis application that uses a similar input format to Abaqus. It has an implicit and explicit solver and a pre and post processor (CGX).

This package contains the documentation in html format for CalculiX CrunchiX

Calculix-ccx-test
Three-Dimensional Structural Finite Element Program (documentation files)
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CalculiX is a free and open source finite element analysis application that uses a similar input format to Abaqus. It has an implicit and explicit solver and a pre and post processor (CGX).

This package contains example files for CalculiX CrunchiX.

Calculix-cgx-examples
Example files for Calculix GraphiX
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CalculiX GraphiX (cgx) is a 3-dimensional pre- and post-processor for finite elemnts. CalculiX CrunchiX Finite Element Models can be build, calculated and post-processed. The pre- and post-processor is an interactive 3D-tool using the openGL API.

In addition to the Calculix CrunchiX results files (frd) results from OpenFoam, Duns (2D and 3D), Isaac (2D and 3D) and Nastran (f06) can be read. For preprocessing Netgen nativ format, STEP and STL can be imported.

This package contains the examples.

Ceres-solver-doc
documentation for ceres-solver
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Ceres Solver is an open source C++ library for modeling and solving large, complicated optimization problems. It is a feature rich, mature and performant library which has been used in production at Google since 2010.

Ceres Solver can solve two kinds of problems.

  • Non-linear Least Squares problems with bounds constraints.
  • General unconstrained optimization problems.

This package contains the documentation found on http://ceres-solver.org/ and the examples that were included with the release.

Coinor-libcoinmp-dev
Simple C API for COIN-OR Solvers Clp and Cbc -- development
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The Coin-MP optimizer is an open source solver, it is part of the COIN-OR project which is an initiative to spur the development of open-source software for the operations research community.

CoinMP is a C-API library that supports most of the functionality of CLP (Coin LP), CBC (Coin Branch-and-Cut), and CGL (Cut Generation Library) projects.

This package contains the files needed to build applications using libCoinMP.

Evolver-nox
Surface Evolver - with no X support
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The Surface Evolver is an interactive program for the modelling of liquid surfaces shaped by various forces and constraints.

This package provides evolver variants built with different floating point formats (double, long double, quadruple) but with no X support.

The package is enhanced by the following packages: evolver-doc
Evolver-ogl
Surface Evolver - with OpenGL display
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The Surface Evolver is an interactive program for the modelling of liquid surfaces shaped by various forces and constraints.

This package provides evolver variants built with different floating point formats (double, long double, quadruple) and with an OpenGL/GLUT display.

The package is enhanced by the following packages: evolver-doc
Hpcc
HPC Challenge benchmark
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The High Performance Computing (HPC) Challenge benchmark runs a suite of 7 tests that measure the performance of CPU, memory and network for HPC clusters. Amongst others, it includes the High-Performance LINPACK (HPL) benchmark, used by the Top500 ranking (http://www.top500.org/).

Libcneartree-dev
Library and headers for solving the Nearest Neighbor Problem
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Neartree is an API and a library for finding nearest neighbors among points in spaces of arbitrary dimensions. This package provides a C++ template, TNear.h, and C library and header files for compiling programs using Neartree.

The library uses the Nearest Neighbor algorithm after Kalantari and McDonald, (IEEE Transactions on Software Engineering, v. SE-9, pp. 631-634,1983) modified to use recursion instead of a double-linked tree and simplified so that it does less checking for things like is the distance to the right less than the distance to the left; it was found that these checks make little to no difference.

Libquantum-dev
library for the simulation of a quantum computer (development files)
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libquantum is a C library for the simulation of a quantum computer. Based on the principles of quantum mechanics, it provides an implementation of a quantum register. Basic operations for register manipulation such as the Hadamard gate or the Controlled-NOT gate are available through an easy-to-use interface. Measurements can be performed on either single qubits or the whole quantum register.

Features:

  • Simulation of arbitrary quantum algorithms is possible
  • High perfomance and low memory consumption
  • Decoherence support for realistic quantum computation
  • Interface for quantum error correction (QEC)
  • Supports the density operator formalism
  • Implementations of Shor's factoring algorithm and Grover's search algorithm are included

This package contains the header files and static libraries which are needed to develop applications based on libquantum.

Libscirenderer-java
Java rendering library based on JOGL
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This Java API allows 2-D or 3-D plotting from simple 2-D graph to complex scenes.

While this library has been developed in the context of Scilab, it can be used in any context.

Libsundials-serial-dev
SUNDIALS development files
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The family of solvers referred to as SUNDIALS (SUit of Nonlinear and DIfferential/ALgebraic equation Solvers) consists of solvers CVODE (for ODE systems), CVODES (ODE with sensitivity analysis capabilities), IDA (for differential-algebraic systems), and KINSOL (for nonlinear algebraic systems).

This package contains files necessary for development applications using SUNDIALS in C and, in case of FCVODE and FKINSOL, Fortran. It also contains various example programs distributed by the upstream authors.

Python-arrayfire
ArrayFire bindings for Python 2
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ArrayFire is a high performance library for parallel computing with an easy-to-use API. It enables users to write scientific computing code that is portable across CUDA, OpenCL and CPU devices. This project provides Python bindings for the ArrayFire library.

This package provides the bindings for Python 2.

Python-bitstring
Python module for manipulation of binary data (Python 2)
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Bitstring is a pure Python module designed to help make the creation and analysis of binary data as simple and natural as possible.

Bitstrings can be constructed from integers (big and little endian), hex, octal, binary, strings or files. They can be sliced, joined, reversed, inserted into, overwritten, etc. with simple functions or slice notation. They can also be read from, searched and replaced, and navigated in, similar to a file or stream.

This package provides the Python 2 version of the module.

Python-deap
Distributed Evolutionary Algorithms in Python
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DEAP is a novel evolutionary computation framework for rapid prototyping and testing of ideas. It seeks to make algorithms explicit and data structures transparent. It works in perfect harmony with parallelisation mechanism such as multiprocessing and SCOOP.

This package contains the modules for Python.

Python-escript-mpi
Escript/Finley finite elements Python2 system (OpenMP + MPI)
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Escript is a programming tool for implementing mathematical models in Python using the finite element method (FEM). Because users do not access the data structures it is very easy to use and scripts can run on desktop computers as well as highly parallel supercomputer without changes. Application areas for escript include earth mantle convection, geophysical inversion, earthquakes, porous media flow, reactive transport, plate subduction, erosion, and tsunamis.

Scripts can be executed in parallel (on varying numbers of threads or nodes) without any special modifications.

Escript now includes the esys.downunder module for 3D inversion of geophysical data sets. The current version supports gravity, magnetic and joint inversion.

This package contains the commands and libraries for Python2 with both OpenMP threading and MPI multiprocess support.

Python-guiqwt
efficient 2D data-plotting library - Python 2
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The guiqwt Python library provides efficient 2D data-plotting features (curve/image visualization and related tools) for signal/image processing application development and interactive computing. It's based on the scientific modules NumPy and SciPy, and the PyQwt plotting widgets for PyQt4 graphical user interfaces.

This is the Python 2 version of the package.

Python-lmfit
Least-Squares Minimization with Constraints (Python 2)
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The lmfit Python package provides a simple, flexible interface to non-linear optimization or curve fitting problems. The package extends the optimization capabilities of scipy.optimize by replacing floating pointing values for the variables to be optimized with Parameter objects. These Parameters can be fixed or varied, have upper and/or lower bounds placed on its value, or written as an algebraic expression of other Parameters.

The principal advantage of using Parameters instead of simple variables is that the objective function does not have to be rewritten to reflect every change of what is varied in the fit, or what relationships or constraints are placed on the Parameters. This means a scientific programmer can write a general model that encapsulates the phenomenon to be optimized, and then allow user of that model to change what is varied and fixed, what range of values is acceptable for Parameters, and what constraints are placed on the model. The ease with which the model can be changed also allows one to easily test the significance of certain Parameters in a fitting model.

The lmfit package allows a choice of several optimization methods available from scipy.optimize. The default, and by far best tested optimization method used is the Levenberg-Marquardt algorithm from from MINPACK-1 as implemented in scipy.optimize.leastsq. This method is by far the most tested and best support method in lmfit, and much of this document assumes this algorithm is used unless explicitly stated. An important point for many scientific analysis is that this is only method that automatically estimates uncertainties and correlations between fitted variables from the covariance matrix calculated during the fit.

A few other optimization routines are also supported, including Nelder-Mead simplex downhill, Powell's method, COBYLA, Sequential Least Squares methods as implemented in scipy.optimize.fmin, and several others from scipy.optimize. In their native form, some of these methods setting allow upper or lower bounds on parameter variables, or adding constraints on fitted variables. By using Parameter objects, lmfit allows bounds and constraints for all of these methods, and makes it easy to swap between methods without hanging the objective function or set of Parameters.

Finally, because the approach derived from MINPACK-1 usin the covariance matrix to determine uncertainties is sometimes questioned (and sometimes rightly so), lmfit supports methods to do a brute force search of the confidence intervals and correlations for sets of parameters.

This is the Python 2 version of the package.

Python-matplotlib
Python based plotting system in a style similar to Matlab
Maintainer: Sandro Tosi
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Matplotlib is a pure Python plotting library designed to bring publication quality plotting to Python with a syntax familiar to Matlab users. All of the plotting commands in the pylab interface can be accessed either via a functional interface familiar to Matlab users or an object oriented interface familiar to Python users.

Python-numpy
Numerical Python adds a fast array facility to the Python language
Maintainer: Sandro Tosi
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Numpy contains a powerful N-dimensional array object, sophisticated (broadcasting) functions, tools for integrating C/C++ and Fortran code, and useful linear algebra, Fourier transform, and random number capabilities.

Numpy replaces the python-numeric and python-numarray modules which are now deprecated and shouldn't be used except to support older software.

The package is enhanced by the following packages: python-shapely
Python-scipy
scientific tools for Python
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SciPy supplements the popular NumPy module (python-numpy package), gathering a variety of high level science and engineering modules together as a single package.

SciPy is a set of Open Source scientific and numeric tools for Python. It currently supports special functions, integration, ordinary differential equation (ODE) solvers, gradient optimization, genetic algorithms, parallel programming tools, an expression-to-C++ compiler for fast execution, and others.

Python-sciscipy
Python binding of Scilab
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Sciscipy provides a Python API to map Scilab features. Three main methods are available:

  • sciscipy.eval(sci_cmd)
  • sciscipy.read(sci_var_name)
  • sciscipy.write(sci_var_name, py_var_name)

Also, to increase the level of enjoyment, a python module called scilab is also provided. This package contains a class 'Scilab' that can be used to issue any valid scilab function.

Python-sparse
Sparse linear algebra extension for Python
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This provides a set of sparse matrix types for Python, with modules which implement:

  • Iterative methods for solving linear systems of equations
  • A set of standard preconditioners
  • An interface to a direct solver for sparse linear systems of equations
  • The JDSYM eigensolver

All of these modules are implemented as C extension modules based on standard sparse and dense matrix libraries (UMFPACK/AMD, SuperLU, BLAS/LAPACK) for maximum performance and robustness.

Python-tables
hierarchical database for Python based on HDF5
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PyTables is a hierarchical database package designed to efficiently manage very large amounts of data. PyTables is built on top of the HDF5 library and the NumPy package. It features an object-oriented interface that, combined with natural naming and C-code generated from Pyrex sources, makes it a fast, yet extremely easy to use tool for interactively save and retrieve large amounts of data.

  • Compound types (records) can be used entirely from Python (i.e. it is not necessary to use C for taking advantage of them).
  • The tables are both enlargeable and compressible.
  • I/O is buffered, so you can get very fast I/O, specially with large tables.
  • Very easy to select data through the use of iterators over the rows in tables. Extended slicing is supported as well.
  • It supports the complete set of NumPy, Numeric and numarray objects.

This is the Python 2 version of the package.

Python-theano
CPU/GPU math expression compiler for Python
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Theano is a Python library that allows one to define and evaluate mathematical expressions involving multi-dimensional arrays efficiently. It provides a high-level Numpy like expression language for functional description of calculation, rearranges expressions for speed and stability, and generates native machine instructions for fast calculation. Optionally, highly accelerated computations could be carried out on graphics cards processors.

This package contains Theano for Python 2.

Python-woo
Discrete dynamic computations, esp. granular mechanics (python 2)
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Extesible and portable framework primarily for mechanics granular materials. Computation parts are written in c++ parallelized using OpenMP, fully accessible and modifiable from python (ipython console or scripts). Arbitrarily complex scene can be scripted. Qt-based user interface is provided, featuring flexible OpenGL display, inspection of all objects and runtime modification. Parametric preprocessors can be written in pure python, and batch system can be used to drive parametric studies. New material models and particle shapes can be added (in c++) without modifying existing classes.

Woo is an evolution of the Yade package (http://www.launchpad.net/yade), aiming at more flexibility, extensibility, tighter integration with python and user-friendliness.

This version is built with OpenMP enabled, and targets Python 2.x

Python3-agate
data analysis library optimized for human readability
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Agate is a Python data analysis library that is optimized for humans instead of machines. It is an alternative to numpy and pandas that solves real-world problems with readable code.

Why agate?

  • A readable and user-friendly API.
  • A complete set of SQL-like operations.
  • Unicode support everywhere.
  • Decimal precision everywhere.
  • Exhaustive user documentation.
  • Pluggable extensions that add SQL integration, Excel support, and more.
  • Designed with iPython, Jupyter and atom/hydrogen in mind.
  • Pure Python. No C dependencies to compile.
  • Exhaustive test coverage.
  • MIT licensed and free for all purposes.
  • Zealously zen.
  • Made with love.

This package provides the modules for Python 3.

Python3-bcolz
high performant compressed data container based on NumPy (Python 3)
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bcolz provides columnar, chunked data containers that can be compressed in-memory and on-disk. Column storage allows for efficiently querying tables, as well as for cheap column addition and removal. It is based on NumPy, and uses it as the standard data container to communicate with bcolz objects, but it also comes with support for import/export facilities to/from HDF5/PyTables tables and Pandas dataframes.

This package contains the modules for Python 3.

Python3-dbfread
read DBF Files with Python
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DBF is a file format used by databases such dBase, Visual FoxPro, and FoxBase+. This library reads DBF files and returns the data as native Python data types for further processing. It is primarily intended for batch jobs and one-off scripts.

This package provides the modules for Python 3.

Python3-escript
Escript/Finley finite elements Python3 system (with OpenMP)
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Escript is a programming tool for implementing mathematical models in Python using the finite element method (FEM). Because users do not access the data structures it is very easy to use and scripts can run on desktop computers as well as highly parallel supercomputer without changes. Application areas for escript include earth mantle convection, geophysical inversion, earthquakes, porous media flow, reactive transport, plate subduction, erosion, and tsunamis.

Scripts can be executed in parallel (on varying numbers of threads or nodes) without any special modifications.

Escript now includes the esys.downunder module for 3D inversion of geophysical data sets. The current version supports gravity, magnetic and joint inversion.

This package contains the commands and libraries for Python3 with OpenMP threading and MPI multiprocess support.

Python3-escript-mpi
Escript/Finley finite elements Python3 system (OpenMP + MPI)
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Escript is a programming tool for implementing mathematical models in Python using the finite element method (FEM). Because users do not access the data structures it is very easy to use and scripts can run on desktop computers as well as highly parallel supercomputer without changes. Application areas for escript include earth mantle convection, geophysical inversion, earthquakes, porous media flow, reactive transport, plate subduction, erosion, and tsunamis.

Scripts can be executed in parallel (on varying numbers of threads or nodes) without any special modifications.

Escript now includes the esys.downunder module for 3D inversion of geophysical data sets. The current version supports gravity, magnetic and joint inversion.

This package contains the commands and libraries for Python3 with both OpenMP threading and MPI multiprocess support.

Python3-leather
charting library for Python
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Leather is the Python charting library for those who need charts now and don’t care if they’re perfect.

Why leather?

  • A readable and user-friendly API.
  • Optimized for exploratory charting.
  • Produces scale-independent SVG charts.
  • Completely type-agnostic. Chart your data, whatever it is.
  • Designed with iPython, Jupyter and atom/hydrogen in mind.
  • Pure Python. No C dependencies to compile.
  • MIT licensed and free for all purposes.
  • Zealously zen.
  • Made with love.

This package provides the modules for Python 3.

Python3-spyder-line-profiler
line profiling plugin for the Spyder IDE
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This is a plugin for the Spyder IDE that integrates the Python line profiler.

Add a @profile decorator to the functions that you wish to profile then press Shift+F10 (line profiler default) to run the profiler on the current script, or go to Run > Profile line by line.

The results will be shown in a dockwidget, grouped by function. Lines with a stronger color take more time to run.

Python3-spyder-memory-profiler
memory profiling plugin for the Spyder IDE
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This is a plugin for the Spyder IDE that integrates the Python memory profiler. It allows you to see the memory usage in every line.

Add a @profile decorator to the functions that you wish to profile then press Ctrl+Shift+F10 to run the profiler on the current script, or go to Run > Profile memory line by line.

The results will be shown in a dockwidget, grouped by function. Lines with a stronger color have the largest increments in memory usage.

Python3-spyder-unittest
plugin to run tests within the Spyder IDE
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This is a plugin for the Spyder IDE that integrates popular unit test frameworks. It allows you to run tests and view the results.

The plugin adds an item Run unit tests to the Run menu in Spyder. Click on this to run the unit tests. After you specify the testing framework and the directory under which the tests are stored, the tests are run. The Unit testing window pane (displayed at the top of this file) will pop up with the results.

Scilab-jims
Binds Java from the Scilab engine
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JIMS is an effort to allow Scilab programs full access to Java class libraries. This is achieved by interfacing at the native level in both Virtual Machines.

From Scilab, JIMS allows the capability to load and manage Java objects from the Scilab interpreter.

Thanks to this module, Scilab can access to complex and advanced Java objects with Scilab classical data types.

Theano-doc
CPU/GPU math expression compiler for Python (docs)
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Theano is a Python library that allows one to define and evaluate mathematical expressions involving multi-dimensional arrays efficiently. It provides a high-level Numpy like expression language for functional description of calculation, rearranges expressions for speed and stability, and generates native machine instructions for fast calculation. Optionally, highly accelerated computations could be carried out on graphics cards processors.

This package contains the documentation for Theano.

Debian packages in contrib or non-free

Libsuitesparse-metis-dev
collection of libraries for computations for sparse matrices
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Suitesparse is a collection of libraries for computations involving sparse matrices. libsuitesparse-metis-dev is a replacement for libsuitesparse-dev compiled with libmetis support. The package includes the following libraries:

AMD approximate minimum degree ordering

CAMD symmetric approximate minimum degree

BTF permutation to block triangular form (beta)

COLAMD column approximate minimum degree ordering

CCOLAMD constrained column approximate minimum degree ordering

CHOLMOD sparse Cholesky factorization

CSparse a concise sparse matrix package

CXSparse CSparse extended: complex matrix, int and long int support

KLU sparse LU factorization, primarily for circuit simulation

LDL a simple LDL' factorization

UMFPACK sparse LU factorization

UFconfig configuration file for all the above packages.

This package contains the static libraries and header files.

Matlab-support
distro integration for local MATLAB installations
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This package does not provide MATLAB. Instead, it configures an existing MATLAB installation to integrate more comfortably in a Debian installation.

Currently it provides /usr/bin/matlab through the alternatives system, offers to work around incompatibilities between the libraries bundled with MATLAB and system libraries, and provides a helper utility meant to be used by other packages to compile MEX extensions.

Install this if you would like your MATLAB installation to behave more like an ordinary Debian package. Other packages may depend on this one if they install MATLAB code, for example in order to compile MEX extensions.

Metis-edf
Family of Multilevel Partitioning Algorithms
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METIS: A Family of Multilevel Partitioning Algorithms

This is a collection of serial and parallel programs & libraries that can be used to partitioning unstructured graphs, finite element meshes, and hypergraphs, both on serial as well as on parallel computers.

Adaptation of METIS for Code_Aster purpose

Packaging has started and developers might try the packaging code in VCS

Libcblas-dev
Basic Linear Algebra Subroutines 3, static library
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This package is a binary incompatible upgrade to the blas-dev package. Several minor changes to the C interface have been incorporated.

BLAS (Basic Linear Algebra Subroutines) is a set of efficient routines for most of the basic vector and matrix operations. They are widely used as the basis for other high quality linear algebra software, for example lapack and linpack. This implementation is the Fortran 77 reference implementation found at netlib.

This implementation of the library belongs to the CLAPACK distribution.

This package contains a static version of the library.

Scilab-metanet
Scilab graphs and networks computations module.
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A number of algorithms solving classical graph problems and minimal cost flow network are provided in this module. This extension is fully integrated in the Scilab environment and provides display and interaction on graphs.

Scilab-sivp
Scilab Image and Video Processing toolbox
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SIVP intends to do image and video processing tasks. SIVP is meant to be a useful, efficient, and free image and video processing toolbox for Scilab. Its goals include tasks such as filtering, blurring, edge detection, thresholding, histogram manipulation, segmentation, mathematical morphology, and color image processing.

This package also provides some functions on video processing.

Scilab-swt
Scilab Wavelet and signal processing toolbox
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Wavelet is a powerful signal processing tool developed and developing in the last two decades. Scilab Wavelet Toolbox is a free software package to enable you using wavelet analysis tools freely in Scilab on most OSes including GNU/Linux, BSD and Windows. Scilab Wavelet Toolbox is designed to work with any Scilab Image Processing Toolbox like SIP or SIVP for displaying 2-D results.

What Scilab Wavelet Toolbox supposed to do:

  • Discrete Fast Wavelet Transform, daubechies wavelets
  • 1-D single level signal decomposition and reconstruction
  • 1-D multi-level signal decomposition and reconstruction
  • 2-D single level image decomposition and reconstruction
  • 2-D multi-level image decomposition and reconstruction
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