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CrocoPat
'CrocoPat' is a tool for querying and manipulating relations. It is easy to use because of its simple query and manipulation language based on predicate calculus and its simple file format for relations. It is efficient because it internally represents relations as binary decision diagrams, a data structure that is well-known as a compact representation of large relations. CrocoPat is general, because it manipulates not only graphs (i.e. binary relations), but n-ary relations.
Ctioga2
ctioga2 is a plotting program in the spirit of gnuplot. It can be used either directly on command-line or writing command files (or a mix of both). It produces publication-quality PDF files. It is based on the Tioga plotting library.
Cuba
The Cuba library offers a choice of four independent routines for multidimensional numerical integration: Vegas, Suave, Divonne, and Cuhre. They work by very different methods, first three are Monte Carlo based. All four have a C/C++, Fortran interface and can integrate vector integrands. Their invocation is very similar, so it is easy to substitute one method by another for cross-checking. For further safeguarding, the output is supplemented by a chi-square probability which quantifies the reliability of the error estimate.
DUNE-Common
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). DUNE is free software licensed under the GPL (version 2) with a so called "runtime exception" (see license). This licence is similar to the one under which the libstdc++ libraries are distributed. Thus it is possible to use DUNE even in proprietary software. The underlying idea of DUNE is to create slim interfaces allowing an efficient use of legacy and/or new libraries. Modern C++ programming techniques enable very different implementations of the same concept (i.e. grids, solvers, ...) using a common interface at a very low overhead. Thus DUNE ensures efficiency in scientific computations and supports high-performance computing applications. DUNE is based on the following main principles:
  • Separation of data structures and algorithms by abstract interfaces.- This provides more functionality with less code and also ensures maintainability and extendability of the framework.
  • Efficient implementation of these interfaces using generic programming techniques.
  • Static polymorphism allows the compiler to do more optimizations, in particular function inlining, which in turn allows the interface to have very small functions (implemented by one or few machine instructions) without a severe performance penalty. In essence the algorithms are parametrized with a particular data structure and the interface is removed at compile time. Thus the resulting code is as efficient as if it would have been written for the special case.
  • Reuse of existing finite element packages with a large body of functionality.- In particular the finite element codes UG, ALBERTA, and ALUGrid have been adapted to the DUNE framework. Thus, parallel and adaptive meshes with multiple element types and refinement rules are available. All these packages can be linked together in one executable.
  • The framework consists of a number of modules which are downloadable as separate packages. The current core modules are:
  • dune-common- contains the basic classes used by all DUNE-modules. It provides some infrastructural classes for debugging and exception handling as well as a library to handle dense matrices and vectors.
  • dune-grid- is the most mature module. It defines nonconforming, hierarchically nested, multi-element-type, parallel grids in arbitrary space dimensions. Graphical output with several packages is available, e.g. file output to IBM data explorer and VTK (parallel XML format for unstructured grids). The graphics package Grape has been integrated in interactive mode.
  • dune-istl (Iterative Solver Template Library)- provides generic sparse matrix/vector classes and a variety of solvers based on these classes. A special feature is the use of templates to exploit the recursive block structure of finite element matrices at compile time. Available solvers include Krylov methods, (block-) incomplete decompositions and aggregation-based algebraic multigrid.
DUNE-Grid
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). DUNE is free software licensed under the GPL (version 2) with a so called "runtime exception" (see license). This licence is similar to the one under which the libstdc++ libraries are distributed. Thus it is possible to use DUNE even in proprietary software. The underlying idea of DUNE is to create slim interfaces allowing an efficient use of legacy and/or new libraries. Modern C++ programming techniques enable very different implementations of the same concept (i.e. grids, solvers, ...) using a common interface at a very low overhead. Thus DUNE ensures efficiency in scientific computations and supports high-performance computing applications. DUNE is based on the following main principles:
  • Separation of data structures and algorithms by abstract interfaces.- This provides more functionality with less code and also ensures maintainability and extendability of the framework.
  • Efficient implementation of these interfaces using generic programming techniques.
  • Static polymorphism allows the compiler to do more optimizations, in particular function inlining, which in turn allows the interface to have very small functions (implemented by one or few machine instructions) without a severe performance penalty. In essence the algorithms are parametrized with a particular data structure and the interface is removed at compile time. Thus the resulting code is as efficient as if it would have been written for the special case.
  • Reuse of existing finite element packages with a large body of functionality.- In particular the finite element codes UG, ALBERTA, and ALUGrid have been adapted to the DUNE framework. Thus, parallel and adaptive meshes with multiple element types and refinement rules are available. All these packages can be linked together in one executable.
  • The framework consists of a number of modules which are downloadable as separate packages. The current core modules are:
  • dune-common- contains the basic classes used by all DUNE-modules. It provides some infrastructural classes for debugging and exception handling as well as a library to handle dense matrices and vectors.
  • dune-grid- is the most mature module. It defines nonconforming, hierarchically nested, multi-element-type, parallel grids in arbitrary space dimensions. Graphical output with several packages is available, e.g. file output to IBM data explorer and VTK (parallel XML format for unstructured grids). The graphics package Grape has been integrated in interactive mode.
  • dune-istl (Iterative Solver Template Library)- provides generic sparse matrix/vector classes and a variety of solvers based on these classes. A special feature is the use of templates to exploit the recursive block structure of finite element matrices at compile time. Available solvers include Krylov methods, (block-) incomplete decompositions and aggregation-based algebraic multigrid.
DUNE-Grid How To
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). DUNE is free software licensed under the GPL (version 2) with a so called "runtime exception" (see license). This licence is similar to the one under which the libstdc++ libraries are distributed. Thus it is possible to use DUNE even in proprietary software. The underlying idea of DUNE is to create slim interfaces allowing an efficient use of legacy and/or new libraries. Modern C++ programming techniques enable very different implementations of the same concept (i.e. grids, solvers, ...) using a common interface at a very low overhead. Thus DUNE ensures efficiency in scientific computations and supports high-performance computing applications. DUNE is based on the following main principles:
  • Separation of data structures and algorithms by abstract interfaces.- This provides more functionality with less code and also ensures maintainability and extendability of the framework.
  • Efficient implementation of these interfaces using generic programming techniques.
  • Static polymorphism allows the compiler to do more optimizations, in particular function inlining, which in turn allows the interface to have very small functions (implemented by one or few machine instructions) without a severe performance penalty. In essence the algorithms are parametrized with a particular data structure and the interface is removed at compile time. Thus the resulting code is as efficient as if it would have been written for the special case.
  • Reuse of existing finite element packages with a large body of functionality.- In particular the finite element codes UG, ALBERTA, and ALUGrid have been adapted to the DUNE framework. Thus, parallel and adaptive meshes with multiple element types and refinement rules are available. All these packages can be linked together in one executable.
  • The framework consists of a number of modules which are downloadable as separate packages. The current core modules are:
  • dune-common- contains the basic classes used by all DUNE-modules. It provides some infrastructural classes for debugging and exception handling as well as a library to handle dense matrices and vectors.
  • dune-grid- is the most mature module. It defines nonconforming, hierarchically nested, multi-element-type, parallel grids in arbitrary space dimensions. Graphical output with several packages is available, e.g. file output to IBM data explorer and VTK (parallel XML format for unstructured grids). The graphics package Grape has been integrated in interactive mode.
  • dune-istl (Iterative Solver Template Library)- provides generic sparse matrix/vector classes and a variety of solvers based on these classes. A special feature is the use of templates to exploit the recursive block structure of finite element matrices at compile time. Available solvers include Krylov methods, (block-) incomplete decompositions and aggregation-based algebraic multigrid.
DUNE-ISTL
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). DUNE is free software licensed under the GPL (version 2) with a so called "runtime exception" (see license). This licence is similar to the one under which the libstdc++ libraries are distributed. Thus it is possible to use DUNE even in proprietary software. The underlying idea of DUNE is to create slim interfaces allowing an efficient use of legacy and/or new libraries. Modern C++ programming techniques enable very different implementations of the same concept (i.e. grids, solvers, ...) using a common interface at a very low overhead. Thus DUNE ensures efficiency in scientific computations and supports high-performance computing applications. DUNE is based on the following main principles:
  • Separation of data structures and algorithms by abstract interfaces.- This provides more functionality with less code and also ensures maintainability and extendability of the framework.
  • Efficient implementation of these interfaces using generic programming techniques.
  • Static polymorphism allows the compiler to do more optimizations, in particular function inlining, which in turn allows the interface to have very small functions (implemented by one or few machine instructions) without a severe performance penalty. In essence the algorithms are parametrized with a particular data structure and the interface is removed at compile time. Thus the resulting code is as efficient as if it would have been written for the special case.
  • Reuse of existing finite element packages with a large body of functionality.- In particular the finite element codes UG, ALBERTA, and ALUGrid have been adapted to the DUNE framework. Thus, parallel and adaptive meshes with multiple element types and refinement rules are available. All these packages can be linked together in one executable.
  • The framework consists of a number of modules which are downloadable as separate packages. The current core modules are:
  • dune-common- contains the basic classes used by all DUNE-modules. It provides some infrastructural classes for debugging and exception handling as well as a library to handle dense matrices and vectors.
  • dune-grid- is the most mature module. It defines nonconforming, hierarchically nested, multi-element-type, parallel grids in arbitrary space dimensions. Graphical output with several packages is available, e.g. file output to IBM data explorer and VTK (parallel XML format for unstructured grids). The graphics package Grape has been integrated in interactive mode.
  • dune-istl (Iterative Solver Template Library)- provides generic sparse matrix/vector classes and a variety of solvers based on these classes. A special feature is the use of templates to exploit the recursive block structure of finite element matrices at compile time. Available solvers include Krylov methods, (block-) incomplete decompositions and aggregation-based algebraic multigrid.
Dap Heckert gnu.tiny.png
Dap is a small statistics and graphics package, based on C, that provides core methods of data management, analysis, and graphics commonly used in statistical consulting practice. Anyone familiar with basic C syntax can learn Dap quickly and easily from the manual and the examples in it. Advanced features of C are not necessary, although they are available. As of Version 3.0, Dap can read SBS programs, thereby freeing the user from having to learn any C at all to run straightforward analyses. The manual contains a brief introduction to the C syntax needed for C-style programming for Dap. Because Dap processes files one line at a time, rather than reading entire files into memory, it can be, and has been, used on data sets that have very many lines and/or very many variables.
Data Frame
In the R language, a dataframe object is a way to group tabular data. The functions in this package allow the manipulation of data in a similar way in Octave. Dataframe objects in Octave can be created in a variety of ways (from other objects or from tabular data in a file) and then can be accessed either as matrix or by column name. This Octave add-on package is part of the Octave-Forge project.
DataCaptureTool
This is a candidate for deletion: All links broken. Software not on archive.org. Email to maintainer broken. poppy-one (talk) 02:37, 28 July 2018 (EDT) DataCapture was born out of frustration, and after much procrastination. Every time I had to get numerical values of a graph from a journal or a conference paper, I had to painstakingly approximate data points from the graph as best I could. Every time the points would come out inaccurate and a rather poor reproduction of the actual data. I wanted to write a program that would automate this task, and do a much better job at that. But then, that was three years ago. Finally its done. Its not the best thing that I have created, but certainly, one of the most useful. Its written in TCl/Tk and is a very small and uncomplicated aplication. Something that you can easily incorporate into your own applications easily.


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