Debian Science Project
Summary
Numerical computation
paquets pour le calcul numérique de Debian Science

Ce métapaquet installe les paquets de Debian Science concernant le calcul numérique. Les paquets fournissent un système de calcul et visualisation orienté matrice pour le calcul scientifique et l’analyse de données. Ces paquets sont similaires aux systèmes commerciaux tels que Matlab et 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
outil pour calculer des maillages solides triangulés − exécutable
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Actuellement, même s'il peut écrire des fichiers STL, VRML, OFF et DXF, ADMesh ne lit que les fichiers au format STL qui sont utilisés pour le prototypage rapide. Admesh peut entre autres : remplir les trous dans le réseau en ajoutant des facettes, réparer les faces en connectant les facettes environnantes, réparer les directions normales (c’est-à-dire, les facettes doivent être orientées dans le sens contraire des aiguilles d'une montre), enlever les faces dégénérées (c’est-à-dire, les faces avec au moins deux sommets égaux).

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Algotutor
programme d'observation des étapes intermédiaires d'un algorithme
Maintainer: Georges Khaznadar
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Le programme interactif algotutor permet d'observer les étapes intermédiaires d'algorithmes (« animation d'algorithme »). Le programme s'adresse aux étudiants en informatique et à quiconque veut étudier des algorithmes ou des structures de données. Des fichiers de données au format texte (en fait des hachages Perl anonymes, mais peu importe) sont fournis à algotutor qui exécute un algorithme prédéfini. La séquence d'exécution de l’algorithme peut alors être parcourue pas à pas, en avant ou en arrière, à différents niveaux de détail.

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Calculix-ccx
programme d'éléments finis structurels en trois dimensions
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CalculiX est une application d'analyse d'éléments finis libre qui utilise un format d'entrée similaire à celui d'Abaqus. Il a un solveur implicite et explicite, un préprocesseur et un postprocesseur (CGX). Ce paquet fournit le solveur CalculiX CrunchiX (cxx).

Calculix-cgx
pré et postprocesseur tridimensionnel pour les modèles à éléments finis
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CalculiX GraphiX (cgx) est un pré et postprocesseur tridimensionnel pour les éléments finis. Des modèles à éléments finis de CalculiX CrunchiX peuvent être compilés, calculés et post-traités. Le pré et postprocesseur est un outil 3D interactif utilisant l'API openGL.

En plus des fichiers de résultats de CalculiX CrunchiX, les résultats d'OpenFoam, Duns (2D et 3D), Isaac (2D et 3D) et Nastran (f06) peuvent être lus. Pour prétraiter le format natif Netgen, STEP et STL peuvent être importés.

Coinor-cbc
solveur de programmes en variables mixtes par branch-and-cut COIN-OR
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Cbc (Coin-or branch and cut) est un solveur de programmes en variables mixtes libre écrit en C++. Il peut être utilisé en tant que bibliothèque appelable ou comme un exécutable autonome.

Ce paquet fournit l'exécutable cbc.

Coinor-clp
solveur de programmation linéaire COIN-OR
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Clp (« COIN-OR linear programming ») est un solveur de programmation linéaire libre écrit en C++. Il est principalement prévu pour être utilisé en tant que bibliothèque, mais un exécutable basique et autonome est également disponible. Clp est conçu pour trouver les solutions de problèmes mathématiques d'optimisation linéaire contraints.

Ce paquet fournit l'exécutable clp.

Coinor-symphony
solveur COIN-OR pour les programmes linéaires en nombres mixtes
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SYMPHONY est un solveur libre et générique de programmes linéaires en nombres mixtes (MILP – «⋅Mixed-Integer Linear Programs⋅»), une bibliothèque et un cadriciel pour implémenter des solveurs personnalisés. SYMPHONY a un certain nombre de capacités évoluées, telles que la possibilité de résoudre des MILP multiobjectifs, la possibilité d'utiliser un démarrage à chaud de sa procédure de résolution et la capacité d'effectuer des analyses de sensibilité basiques.

SYMPHONY fait partie de l'initiative COIN-OR (« Computational Infrastructure for Operations Research »).

Ce paquet fournit l'exécutable symphony.

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
Environnement mathématique (globalement compatible Matlab)
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Freemat est un environnement gratuit pour l'ingénierie rapide, le prototypage scientifique et le traitement de données. Il est similaire aux systèmes commerciaux tels que MATLAB de Mathworks et IDL de Research Systems mais est Open Source. Freemat est disponible sous la licence GPL.

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Gnudatalanguage
compilateur incrémental libre compatible avec IDL
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GNU Data Language (GDL) est un compilateur incrémental libre compatible avec IDL (Interactive Data Language). Sa syntaxe est entièrement compatible avec IDL 7.1. IDL est une marque déposée d’ITT Visual Information Solutions. À partir de IDL 8.0, les éléments de langage suivants sont pris en charge :

 — boucle FOREACH ;
 — indices de tableau négatifs ;
 — ramasse-miettes pour les pointeurs et objets ;
 — méthodes d’appel sur des objets en utilisant « . » (par exemple,
   `object.aMemberProcedure,arg1`).

Le système d’entrée et sortie de fichiers est complètement implémenté. La prise en charge de l’interface graphique (composants graphiques) est officiellement fournie, mais pas encore finie.

Ce paquet fournit le frontal de l’interpréteur en ligne de commande.

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.

Ipython3
Enhanced interactive Python 3 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 3.

The package is enhanced by the following packages: isympy3 python3-matplotlib
Julia
langage de programmation haute-performance pour le calcul technique
Maintainer: Debian Julia Team (Mo Zhou)
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Julia est un langage de programmation haute-performance de haut-niveau pour le calcul technique avec une syntaxe familière aux utilisateurs d'autres environnements de calcul technique. Il fournit un compilateur sophistiqué, une exécution distribuée parallèle, une précision numérique et une vaste bibliothèque de fonctions mathématiques. La bibliothèque, écrite en Julia pour l'essentiel, intègre aussi des bibliothèques⋅C et Fortran, matures et optimales, pour l'algèbre linéaire, la génération de nombres aléatoires, les transformations de Fourier rapides et le traitement de chaînes. Les programmes de Julia sont organisés autour de la définition de fonctions et leur surcharge pour différentes combinaisons de types d'argument (qui peuvent également être définis par l'utilisateur).

Ce paquet fournit une installation complète de Julia (compilateur JIT, bibliothèque standard, interface utilisateur en mode texte).

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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
Bibliothèques et en-têtes de développement ADOLC
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Le système ADOLC calcule automatiquement les dérivées exactes d'une fonction C/C++. Il utilise la surcharge C++ pour enregistrer les opérations arithmétiques et les utilise plus tard de différentes manières pour calculer les valeurs demandées.

Ce paquet contient les bibliothèques, les fichiers d'en-têtes et le manuel d'utilisation.

Libarrayfire-unified-dev
fichiers de développement pour ArrayFire — dorsal unifié
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ArrayFire est une bibliothèque logicielle haute performance pour le calcul parallèle avec une API simple d'utilisation. Son ensemble de fonctions basées sur des tableaux simplifie la programmation parallèle.

Les nombreux dorsaux d'ArrayFire (CUDA, OpenCL et CPU natif) la rendent indépendante des plateformes et extrêmement portable.

Quelques lignes de code dans ArrayFire peuvent remplacer des douzaines de lignes de code de calcul parallèle, épargnant un temps précieux et baissant les coûts de développement.

Ce paquet fournit les fichiers de développement pour le dorsal unifié de la bibliothèque ArrayFire.

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
minimiseur de moindres carrés non linéaire — fichiers de développement
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Ceres Solver est une bibliothèque libre en C++ pour modéliser et résoudre des problèmes d'optimisation de grande taille et complexes. Il s'agit d'une bibliothèque riche en fonctionnalités, mûre et performante qui est utilisée en production par Google depuis 2010.

Ceres Solver peut résoudre deux types de problèmes :

 — les problèmes de moindres carrés non linéaires avec contraintes de
   bornes ;
 — les problèmes d'optimisation génériques sans contrainte.

Ce paquet fournit les en-têtes de développement.

Libclblas-dev
fichiers de développement pour clBLAS
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Cette bibliothèque fournit une implémentation des niveaux 1, 2 et 3 des sous-programmes d'algèbre linéaire de base en utilisant OpenCL et optimisée pour les GPU AMD.

Ce paquet fournit les fichiers de développement.

Libclfft-dev
fichiers de développement pour clFFT
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La bibliothèque clFFT est une implémentation OpenCL libre de transformations rapides de Fourier (FFT) discrètes, qui :

 – fournit une plate-forme rapide et précise pour calculer les FFT
   discrètes ;
 – fonctionne sur des dorsaux CPU ou GPU ;
 – prend en charge des transformations internes (« in-place ») et externes
   (« out-of-place ») ;
 – prend en charge des transformations en 1D, 2D et 3D avec une taille de
   lot pouvant être supérieure à 1 ;
 – prend en charge les formats planaire (composants réels et complexes
   dans des tableaux différents) et entremêlé (composants réels et
   complexes en paires contiguës en mémoire) ;
 – prend en charge les longueurs de dimensions pouvant être toute
   combinaison de puissances de 2, 3 et 5 ;
 – prend en charge les formats à virgule flottante en simple et double
   précision.

Ce paquet fournit les fichiers de développement.

Libclsparse-dev
fichiers de développement pour clSPARSE
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clSPARSE fournit les opérations fondamentales sur des structures creuses pour OpenCL, dont :

 – multiplication de matrice creuse et vecteur dense (SpM-dV) ;
 – multiplication de matrice creuse et matrice dense (SpM-dM) ;
 – solveur de gradient conjugué itératif (CG) ;
 – solveur stabilisé de gradient biconjugué itératif (BiCGStab) ;
 – conversion du format dense vers le format CSR (et inversement) ;
 – conversion du format COO vers le format CSR (et inversement):;
 – fonctions de lecture de fichiers « matrix market » au format COO ou CSR.

Ce paquet fournit les fichiers de développement.

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
bibliothèque de polyèdres Parma –⋅développement
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La bibliothèque de polyèdre Parma (« Parma Polyhedra Library » ou PPL) est une bibliothèque C++ de manipulation de polyèdres convexes (pas forcément fermés) et autres abstractions numériques. Les applications de polyèdres convexes peuvent être l'analyse de programme, la compilation optimisée, l'optimisation entière et combinatoire et l'édition de données statistiques. La bibliothèque est simple d'utilisation (il suffit d'écrire ce qu'on souhaite, par exemple « x + 2y + 5z <= 7 »), totalement dynamique (la mémoire virtuelle disponible étant la seule limite aux dimensions de ce qui est analysé), écrite en C++ standard, exempte d'exceptions, plutôt efficace et largement documentée.

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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.

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

GraphBLAS graph algorithms via sparse matrix operations on semirings

Mongoose graph partitioning library that can quickly compute edge cuts

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
langage GNU Octave pour calculs numériques
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Octave est un langage de haut niveau (presque entièrement compatible avec Matlab®), d'abord destiné aux calculs numériques. Il fournit une interface pratique en ligne de commande, pour résoudre de façon numérique les problèmes linéaires et non linéaires.

Octave peut être étendu à l’aide de fichiers C++.

The package is enhanced by the following packages: liboctave-dev octave-doc 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)
Registry entries: SciCrunch 
Pdl
langage de données Perl : extensions de Perl pour le calcul numérique
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PDL (Perl Data Language — « langage de données Perl ») donne au Perl standard la possibilité de stocker d'une manière COMPACTE et de manipuler RAPIDEMENT des grands tableaux de données à N dimensions qui sont les bases du calcul scientifique. L'idée est de faire de Perl un langage de calcul numérique, libre, orienté sur les tableaux de la même manière que les paquets commerciaux comme IDL et MatLab. Il est possible d'écrire des expressions en Perl simples pour manipuler des tableaux numériques complets en une fois. Par exemple, en utilisant PDL, la variable de Perl $a peut contenir une image 1024x1024 en virgule flottante, en ne prenant que 4 Mo de mémoire et des expressions comme $a=sqrt($a)+2 manipulent l'image en quelques secondes.

Un interpréteur de commandes interactif simple (perldl) est fourni pour une utilisation en ligne de commande ainsi qu'un module (PDL) pour l'utilisation dans les scripts en Perl.

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Psurface
piecewise linear bijections between triangulated surfaces -- utilities
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Psurface is a C++ library that handles piecewise linear bijections between triangulated surfaces. These surfaces can be of arbitrary shape and need not even be manifolds.

This package contains several utilities for working with psurface.

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-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-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 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
système de traçage basé sur Python dans un style similaire à celui Matlab –⋅Python⋅3
Maintainer: Sandro Tosi
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Matplotlib est une bibliothèque de traçage en Python pur conçue pour apporter à Python des capacités de traçage d'une qualité adaptée à la publication, avec une syntaxe familière aux utilisateurs de Matlab. L'accès à toutes les commandes de traçage, dans l'interface pylab, est possible soit à travers une interface fonctionnelle familière aux utilisateurs de Matlab, soit à travers une interface orientée objet familière à ceux de Python.

Ce paquet fournit la version Python⋅3 de matplotlib.

Python3-numpy
gestion rapide des tableaux avec le langage Python 3
Maintainer: Sandro Tosi
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NumPy (Numerical Python) fournit un puissant objet de tableau à n dimensions, des fonctions sophistiquées (dispersion), des outils pour intégrer du code Fortran et C/C++, des outils pratiques pour l'algèbre linéaire, la transformation de Fourier et la génération de nombres aléatoires.

Il remplace les modules python-numeric et python-numarray qui sont maintenant obsolètes et ne devraient être utilisés que pour d'anciens logiciels.

Ce paquet fournit NumPy pour Python.3.

The package is enhanced by the following packages: python3-shapely
Python3-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.

Python3-scipy
outils scientifiques pour Python 3
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SciPy complète le module NumPy populaire (paquet python-numpy), rassemblant une grande variété de modules de haut niveau technique dans un seul paquet.

SciPy est un ensemble d’outils scientifiques et numériques pour Python. Il prend en charge, entre autres, les fonctions spéciales, la résolution d’intégrales et d’équations différentielles ordinaires, l’optimisation par gradient, des algorithmes génétiques, des outils de programmation parallèle, un compilateur expression-vers-C++ pour une exécution rapide.

Python3-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-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 package for managing hierarchical datasets and designed to efficiently cope with extremely large amounts of data.

It is built on top of the HDF5 library and the NumPy package. It features an object-oriented interface that, combined with C extensions for the performance-critical parts of the code (generated using Cython), makes it a fast, yet extremely easy to use tool for interactively save and retrieve very large amounts of data. One important feature of PyTables is that it optimizes memory and disk resources so that they take much less space (between a factor 3 to 5, and more if the data is compressible) than other solutions, like for example, relational or object oriented databases.

  • 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 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.

Theano development is ending: consider using Caffe or Torch instead.

Please cite: Theano Development Team: Theano: A Python framework for fast computation of mathematical expressions (eprint) (2016)
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
système de calcul statistique et de graphique GNU R
Maintainer: Dirk Eddelbuettel
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R est un système de calcul statistique et de graphiques. Il est composé d'un langage ainsi que d'un environnement d'exécution avec des graphiques, un débogueur, un accès à certaines fonctions système et la possibilité d'exécuter des programmes stockés dans des fichiers de script.

La conception de R a été fortement influencée par deux langages existants : le S de Becker, Chambers et Wilks et le Scheme de Sussman. Le langage obtenu est très proche en apparence du S, alors que l'implémentation sous-jacente et la sémantique dérivent du Scheme.

Le cœur de R est un langage de calcul interprété qui permet les branchements et les boucles ainsi que la programmation modulaire en utilisant des fonctions. La plupart des fonctions visibles par les utilisateurs sont écrites en R. Il est possible d'utiliser des procédures écrites en C, C++ ou FORTRAN pour plus d'efficacité, et la plupart des fonctions internes de R le font. La distribution R contient des fonctionnalités pour un large panel de procédures statistiques et de calculs mathématiques appliqués sous-jacents. Elle contient également un grand nombre de fonctions qui fournissent un environnement graphique flexible pour créer différents types de présentations des données.

De plus, plusieurs milliers de « paquets » d’extension sont disponibles à partir de CRAN (Comprehensive R Archive Network), aussi que sous forme de paquets Debian appelés « r-cran- ».

Ce paquet est un meta-paquet pour faciliter la transition de la configuration du paquet pre-1.5.0 avec le paquet principal r-base. Une fois installé, ce paquet peut être supprimé en toute sécurité, apt-get continuera à mettre à jour automatiquement ses composants dans les futures mises à jour. Fournir ce paquet est un moyen donné aux utilisateurs de n'installer que r-base-core s'ils le souhaitent.

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
paquet logiciel scientifique pour le calcul numérique
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Scilab est paquet logiciel scientifique basé sur le calcul matriciel. Scilab fournit en interne des centaines de fonctions mathématiques, des structures puissantes (incluant les polynômes, les fonctions rationnelles, les systèmes linéaires, les listes…), ainsi qu’un certain nombre de boîtes à outils spécifiques au contrôle, traitement de signal…

Ce paquet fournit aussi Xcos, un éditeur graphique pour concevoir des modèles de système dynamique hybride. Ces modèles peuvent être conçus, chargés, enregistrés, compilés ou simulés. Solution stable et efficiente pour les besoins industriels et académiques, Xcos fournit des fonctions pour la modélisation de système mécanique (automobile, aéronautique…), de circuit hydraulique (modélisation de barrage, canalisation…), etc. Des fonctions Modelica sont aussi fournies.

Pour une version minimale de scilab, le paquet « scilab-cli » est à installer.

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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-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
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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 3.

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
outil graphique pour éditer ou parcourir des fichiers PyTables et HDF5
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ViTables est un composant de la famille PyTables. C’est un outil graphique pour parcourir et éditer les fichiers aux formats PyTables ou HDF5.

Les possibilités de ViTables comprennent la navigation aisée dans la hiérarchie de données, l’affichage des données réelles et des métadonnées associées, une navigation simple, quoique puissante, de données multi-dimensionnelles, et bien plus.

Une des plus grandes forces de ViTables est son aptitude à afficher de très grandes tables. Celles avec un milliard de lignes (et au-delà) sont parcourues de manière étonnamment rapide et avec des besoins en mémoire très faibles. Aussi, si on a besoin de parcourir de très grandes tables, sans hésitation, ViTables est la solution.

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Yade
plateforme pour la modélisation d'élément discret
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Encore un autre moteur dynamique (YADE).

Environnement de travail open-source extensible pour les modèles numériques discrets, concentrés sur la méthode d'élément discret. Las parties de calcul sont écrites en C++ en utilisant un modèle d'objet flexible, permettant la mise en œuvre indépendante de nouveaux algorithmes et interfaces. Python est utilisé pour la construction rapide et concise de scène, de contrôle de simulation, de post-traitement et de débogage.

Ce paquet fournit une version de yade optimisant la vitesse.

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.),. The Yade Project, 2nd ed. (2015)
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Yorick
langage interprété et graphiques scientifiques
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Yorick est un langage de programmation interprété pour :

  • les simulations scientifiques et les calculs ;
  • le post-traitement ou le guidage de grands codes de simulation ;
  • les graphiques scientifiques interactifs ;
  • la lecture, l'écriture et la traduction de grands fichiers de nombres.

Le langage fournit une syntaxe compacte pour plusieurs opérations habituelles sur les tableaux et donc travaille rapidement et efficacement sur de grands tableaux de nombres. Le code yorick ressemble superficiellement à du C mais les variables de yorick ne sont jamais explicitement déclarées et elles ont un champ dynamique similaire aux dialectes Lisp. Le langage yorick est conçu pour être saisi interactivement au clavier, ainsi que pour être stocké dans des fichiers pour une utilisation ultérieure.

Ce paquet inclut un environnement de développement basé sur emacs, que vous pouvez lancer en saisissant M-x yorick dans emacs.

De nombreux modules et greffons sont disponibles pour Yorick (paquets yorick-*). Le méta-paquet yorick-full dépend de la majorité d'entre-eux.

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Official Debian packages with lower relevance

Calculix-ccx-doc
programme d'éléments finis structurels en trois dimensions – fichiers de documentation
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CalculiX est une application d'analyse d'éléments finis libre qui utilise un format d'entrée similaire à celui d'Abaqus. Il a un solveur implicite et explicite, un préprocesseur et un postprocesseur (CGX).

Ce paquet fournit la documentation au format HTML pour CalculiX CrunchiX.

Calculix-ccx-test
programme d'éléments finis structurels en trois dimensions – fichiers de documentation
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CalculiX est une application d'analyse d'éléments finis libre qui utilise un format d'entrée similaire à celui d'Abaqus. Il a un solveur implicite et explicite, un préprocesseur et un postprocesseur (CGX).

Ce paquet fournit les fichiers d'exemple pour CalculiX CrunchiX.

Calculix-cgx-examples
fichiers d'exemple pour CalculiX GraphiX
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CalculiX GraphiX (cgx) est un pré et postprocesseur tridimensionnel pour les éléments finis. Des modèles à éléments finis de CalculiX CrunchiX peuvent être compilés, calculés et post-traités. Le pré et postprocesseur est un outil 3D interactif utilisant l'API openGL.

En plus des fichiers de résultats de CalculiX CrunchiX, les résultats d'OpenFoam, Duns (2D et 3D), Isaac (2D et 3D) et Nastran (f06) peuvent être lus. Pour prétraiter le format natif Netgen, STEP et STL peuvent être importés.

Ce paquet fournit les exemples.

Ceres-solver-doc
documentation pour ceres-solver
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Ceres Solver est une bibliothèque libre en C++ pour modéliser et résoudre des problèmes d'optimisation de grande taille et complexes. Il s'agit d'une bibliothèque riche en fonctionnalités, mûre et performante qui est utilisée en production chez Google depuis 2010.

Ceres Solver peut résoudre deux types de problèmes :

 — les problèmes de moindres carrés non linéaires avec contraintes de
   bornes ;
 — les problèmes d'optimisation génériques sans contrainte.

Ce paquet fournit la documentation disponible sur http://ceres-solver.org/ et les exemples fournis avec la distribution.

Coinor-libcoinmp-dev
API C simple pour les solveurs Clp et Cbc de COIN-OR – fichiers de développement
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L'optimiseur Coin-MP est un solveur libre faisant partie du projet COIN-OR qui est une initiative pour stimuler le développement de logiciels libres pour la communauté de recherche opérationnelle.

CoinMP est une bibliothèque API en C prenant en charge la plupart des fonctions des projets CLP (Coin LP), CBC (Coin Branch-and-Cut) et CGL (Cut Generation Library).

Ce paquet fournit les fichiers nécessaires pour construire des applications utilisant libCoinMP.

Evolver-nox
Surface Evolver, modélisation de surfaces – sans gestion d’X
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Surface Evolver est un programme interactif pour la modélisation de la surface d’un liquide, façonnée par différentes forces et tensions.

Ce paquet fournit des variantes d’evolver construites suivant des formats différents de virgule flottante (double, long double, quadruple), mais sans prise en charge d’X.

The package is enhanced by the following packages: evolver-doc
Evolver-ogl
Surface Evolver, modélisation de surfaces – avec affichage OpenGL
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Surface Evolver est un programme interactif pour la modélisation de la surface d’un liquide, façonnée par différentes forces et tensions.

Ce paquet fournit des variantes d’evolver construites suivant des formats différents de virgule flottante (double, long double, quadruple), et avec un affichage utilisant OpenGL/GLUT.

The package is enhanced by the following packages: evolver-doc
Hpcc
mesureur de performance HPC Challenge
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Le mesureur de performance HPC Challenge (High Performance Computing – Informatique de haute performance) exécute une suite de sept tests pour les CPU, la mémoire et le réseau pour des grappes HPC. Entre autres, il fournit le mesureur HPL (High-Performance LINPACK), utilisé par le classement Top500 (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.

Libpsurface-dev
piecewise linear bijections between triangulated surfaces -- development files
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Psurface is a C++ library that handles piecewise linear bijections between triangulated surfaces. These surfaces can be of arbitrary shape and need not even be manifolds.

There are two main uses for psurface. When doing adaptive finite element simulations on grids with parametrized boundaries, psurface can store the parametrization. Boundary parametrizations are practically mappings from the coarse grid boundary to the actual boundary, and if that actual boundary is a triangulated surface then psurface can handle it. This is implemented, for example, in the dune-grid module of Dune.

Secondly, when doing domain decomposition methods with nonconforming interfaces, you need to relate the two interface grids to each other. Psurface can do this for you, even if your interfaces do not match geometrically. Such is the case, e.g., in contact problems. This second functionality is also available for 1d surfaces in 2d space.

The easiest way to use psurface for domain decomposition is to get the dune-grid-glue module and use it to drive psurface.

This package contains the development files.

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 performance 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.

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-agatedbf
support for dbf files in agate
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Agate-dbf adds read support for dbf files to agate. It uses a monkey patching pattern to add read methods for dbf files to all agate.Table instances after import of the corresponding agatedbf module.

This package provides the modules for Python 3.

Python3-agateexcel
support for Excel files in agate
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Agate-excel adds read support for Excel files (xls and xlsx) to agate. It uses a monkey patching pattern to add read methods for xls and xlsx files to all agate.Table instances after import of the corresponding agateexcel module.

This package provides the modules for Python 3.

Python3-agatesql
support for SQL read/write in agate
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Agate-sql adds read/write support for SQL to agate. It uses a monkey patching pattern to add read and write methods for SQL to all agate.Table instances after import of the corresponding agatesql module.

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-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-numcodecs
buffer compression and transformation codecs for Python
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Numcodecs is a Python package providing buffer compression and transformation codecs for use in data storage and communication applications. These include:

  • Compression codecs, e.g., Zlib, BZ2, LZMA and Blosc.
  • Pre-compression filters, e.g., Delta, Quantize, FixedScaleOffset, PackBits, Categorize.
  • Integrity checks, e.g., CRC32, Adler32.

All codecs implement the same API, allowing codecs to be organized into pipelines in a variety of ways.

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-reports
plugin to render scientific reports within the Spyder IDE
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Spyder-reports is a plugin for the Spyder IDE which renders scientific reports written in Markdown. The preview is displayed on a separate pannel and uses pandoc and Pweave in the backend to perform the conversion from Markdown to HTML.

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.

Python3-zarr
chunked, compressed, N-dimensional arrays for Python
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Zarr is a Python package providing an implementation of compressed, chunked, N-dimensional arrays, designed for use in parallel computing. Some highlights:

  • Create N-dimensional arrays with any NumPy dtype.
  • Chunk arrays along any dimension.
  • Compress chunks using the fast Blosc meta-compressor or alternatively using zlib, BZ2 or LZMA.
  • Store arrays in memory, on disk, inside a Zip file, on S3, ...
  • Read an array concurrently from multiple threads or processes.
  • Write to an array concurrently from multiple threads or processes.
  • Organize arrays into hierarchies via groups.
  • Use filters to preprocess data and improve compression.
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.

Please cite: Theano Development Team: Theano: A Python framework for fast computation of mathematical expressions (eprint) (2016)

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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.

Libgismo-dev
Geometry plus simulatiom modules development files
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G+Smo (Geometry + Simulation Modules, pronounced "gismo") is a new open-source C++ library that brings together mathematical tools for geometric design and numerical simulation. This package contains inlude headers, cmake configuration files and other development utils.

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.

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.

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