Debian Science Numerical Computation packages

비록 ADMesh가 STL, VRML, OFF, 그리고 DXF 파일로 쓸 수 있지만, 현재까지, ADMesh는 오직 고속가공 어플리케이션에 사용되는 STL 파일 형식만을 읽을 수 있 습니다. admesh의 몇몇 특징은 다음과 같습니다: 면을 추가함으로 mesh의 공백을 채웁니다. 근접한 면에 연결함으로 면을 회복함니다. 일반 방향을 회복합니다 (예. 면은 CCW로 되어야 합니다) 변질된 면을 제거합니다 (예. 둘 또는 그 이상 의 대등한 정점을 가지는 면)

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.

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 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.

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.

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.

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 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.

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.

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.

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 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.

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).

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

SLEEF stands for SIMD Library for Evaluating Elementary Functions. It implements vectorized versions of all C99 real floating point math functions. It can utilize SIMD instructions of modern processors. SLEEF is designed to fully utilize SIMD computation by reducing the use of conditional branches and scatter/gather memory access.

The library contains subroutines for all C99 real FP math functions in double precision and single precision. SLEEF also includes subroutines for discrete Fourier transform(DFT).

This package ships development files.

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

ParU unsymmetric multifrontal multithreaded sparse LU factorization

RBio read/write sparse matrices in Rutherford/Boeing format

SPQR sparse QR factorization

Mongoose graph partitioning library that can quickly compute edge cuts

SPEX solves sparse linear systems in exact arithmetic

SuiteSparse_config configuration routines for all the above packages.

This package contains the static libraries and header files.

This package contains all development files necessary to build applications using SUNDIALS (SUite of Nonlinear and DIfferential/ALgebraic equation Solvers). All examples and documentation links live in this package as well.

TooN is a C++ numerics library which is designed to operate efficiently on large numbers of small matrices, and provides easy access to a number of algorithms including matrix decompositions and optimizations.

TooN is type generic and works well with a variety of numeric types including double, float and automatic differentiation types.

It is designed to integrate very will with the libCVD computer vision library and GVars3 configuration library.

TooN is a C++ numerics library which is designed to operate efficiently on large numbers of small matrices, and provides easy access to a number of algorithms including matrix decompositions and optimizations.

TooN is type generic and works well with a variety of numeric types including double, float and automatic differentiation types.

It is designed to integrate very will with the libCVD computer vision library and GVars3 configuration library.

TaG is the TooN Algorithm Library, it contains a mixed bag of algorithms including estimation, 3D geoometry and standard library enhancements.

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.

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 is a (mostly MATLAB® 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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

This package installs NumPy for Python 3.

A Python interface to the C++ Parma Polyhedra Library (PPL), which allows computations with polyhedra and grids, like mixed integer linear programming.

This package installs the library for Python 3.

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.

PySwarms is an extensible research toolkit for particle swarm optimization (PSO) in Python.

It is intended for swarm intelligence researchers, practitioners, and students who prefer a high-level declarative interface for implementing PSO in their problems. PySwarms enables basic optimization with PSO and interaction with swarm optimizations.

Features:

• High-level module for Particle Swarm Optimization
• Built-in objective functions to test optimization algorithms
• Plotting environment for cost histories and particle movement
• Hyperparameter search tools to optimize swarm behaviour

This package contains the Python 3.x version of PySwarms.

Implements band-limited sinc interpolation method for sampling rate conversion.

rioxarray is an extension to the xarray package that

• supports multidimensional datasets such as netCDF
• stores the CRS as a WKT, which is the recommended format
• loads in the CRS, transform, and nodata metadata in standard CF & GDAL locations
• supports masking and scaling data with the masked and mask_and_scale kwargs
• adds the coordinate axis CF metadata
• loads in raster metadata into the attributes

This package provides the Python 3 library

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.

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.

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.

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.

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.

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 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 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.

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.

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.

Scilab은 매트릭스 기반의 과학 소프트웨어 패키지입니다. Scilab은 수백의 내장 수학 함수, 다양한 데이타 구조(다항식, 유리수, 선형 시스템, 배열, 등등...)를 포함하며 그리고 제어, 신호 처리, 등등을 위한 다수의 특정 툴박스가 부속합니다.

이 패키지는 또한 하이브리드 동적 시스템 모델을 설계할 수 있는 그래픽 편집기 인, Xcos를 제공합니다. 모델을 설계, 로드, 저장, 컴파일 및 시뮬레이트 할 수 있습니다. 기업과 학교의 요구에 대한 안정적이고 효과적인 솔루션, Xcos는 기계 시스템(자동차, 항공기..), 유압 회로(댐, 파이프 모델링...), 제어 시스템등의 모델링 기능을 제공합니다.

Scilab의 최소 사양을 원한다면, "scilab-cli" 패키지를 설치하십시요.

SDPB is an open-source, arbitrary-precision, parallelized semidefinite program solver, designed for the conformal bootstrap. SDPB significantly outperforms less specialized solvers and should enable many new computations.

For more information, see "A Semidefinite Program Solver for the Conformal Bootstrap" at http://arxiv.org/abs/1502.02033.

Spyder is a powerful interactive development environment for Python providing many features and facilities, including advanced editing facilities (including tooltips and completion facilities), issue highlighting, interactive testing, debugging and introspection facilities, an embedded console (IPython) supporting graphics and much more.

This package provides the application.

There is one plugin currently available in Debian: spyder-unittest, in the package python3-spyder-unittest.

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 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.

xtensor is a C++ library meant for numerical analysis with multi-dimensional array expressions.

This is a dummy package transitioning to libxtensor-dev.

Yet Another Dynamic Engine.

이산 요소 방법에 초점을 맞춘 이산 수치 모델용 확장 가능한 오픈 소스 프레임워크. 계산 부분은 유연한 객체 모델을 사용해서 C++로 작성되었고 따라서 새로운 알고리즘과 인터페이스를 독립적으로 구현할 수 있습니다. Python은 빠르고 간결한 장면 구성, 시뮬레이션 제어, 후 처리 및 디버깅에 사용됩니다.

이 패키지는 속도에 최적화된 yade 빌드를 포함합니다.

Yorick은 다음을 위한 인터프리티드 프로그래밍 언어입니다:

• 과학 시뮬레이션 또는 계산
• 후처리 또는 운영에 대한 많은 시뮬레이션 코드
• 대화형 과학 그래픽
• 대량 파일의 읽기, 쓰기, 그리고 번역

Yorick은 많은 일발적 배열 작업에 대한 간편한 구문을 제공하며, 그래서 Yorick은 거대한 배열을 매우 빠르고 효과적으로 처리합니다. 피상적으로, yorick 코드는 C 코드와 비슷합니다, 그러나 yorick은 절대로 변수를 명시적으로 선언하지 않으며 많은 Lisp 변종과 유사하게 동적 범위를 갖습니다. Yorick 언어는 키보드에서 대화형으로 입력받을 뿐만 아니라, 나중에 사용하기 위해 파일로 저장하도록 설계되었습니다.

이 패키지는 이맥스 기반에 개발환경을 포함합니다. 그래서 당신은 이맥스내에서 M-x yorick 명령으로 yorick를 시작할 수 있습니다.

많은 추가 패키지와 플러그인은 Yorick을 사용할 수 있습니다 (패키지 이름은 "yorick-"으로 시작). 사용자는 Yorick 패키지의 대부분과 의존성 관계인 yorick-full 메타패키지를 설치할 수도 있습니다.

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 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 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 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.

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.

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 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.

High Performance Computing (HPC) Challenge 벤치마크는 HPC 클러스터에 대한 CPU, 메모리, 네트워크 성능을 계산하는 7개의 테스트를 실행합니다. 무엇보다도, Top500 랭킹 (http://www.top500.org/)에서 사용하는 High-Performance LINPACK (HPL) 벤치마크가 포함되어 있습니다.

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.

A lightweight C++ library of numerical optimization methods for nonlinear functions, including L-BFGS-B for TensorFlow

This is a simple C package for adaptive multidimensional integration (cubature) of vector-valued integrands over hypercubes. Of course, it can handle scalar integrands as the special case where f is a one-dimensional vector: the dimensionalities of f and x are independent. The integrand can be evaluated for an array of points at once to enable easy parallelization.

This package contains the development files.

LBFGS++ is a header-only C++ library that implements the Limited-memory BFGS algorithm (L-BFGS) for unconstrained minimization problems, and a modified version of the L-BFGS-B algorithm for box-constrained ones.

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 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.

The STochastic OPTimization library (StOpt) aims at providing tools in C++ for solving some stochastic optimization problems encountered in finance or in the industry. Different methods are available:

• dynamic programming methods based on Monte Carlo with regressions (global, local, kernel and sparse regressors), for underlying states following some uncontrolled Stochastic Differential Equations;
• dynamic programming with a representation of uncertainties with a tree: transition problems are here solved by some discretizations of the commands, resolution of LP with cut representation of the Bellman values;
• Semi-Lagrangian methods for Hamilton Jacobi Bellman general equations for underlying states following some controlled Stochastic Differential Equations;
• Stochastic Dual Dynamic Programming methods to deal with stochastic stock management problems in high dimension. Uncertainties can be given by Monte Carlo and can be represented by a state with a finite number of values (tree);
• Some branching nesting methods to solve very high dimensional non linear PDEs and some appearing in HJB problems. Besides some methods are provided to solve by Monte Carlo some problems where the underlying stochastic state is controlled. For each method, a framework is provided to optimize the problem and then simulate it out of the sample using the optimal commands previously computed. Parallelization methods based on OpenMP and MPI are provided in this framework permitting to solve high dimensional problems on clusters. The library should be flexible enough to be used at different levels depending on the user's willingness.

This package contains the headers and the static libraries (libstopt-mpi which allows for multithreading, and libstopt which does not).