Open Source Mac Algorithms - Page 3

The Safe C Library provides bound checking memory and string functions per ISO/IEC TR24731. These functions are alternative functions to the existing standard C library that promote safer, more secure programming. The ISO/IEC Programming languages — C spec, C11, now includes the bounded APIs in Appendix K, "Bounds-checking interfaces". This latest upload supports building static library, a shared library and a linux kernel module.

La librería Arduino para Java es una compilación de métodos que permite comunicar aplicaciones en Java con Arduino

Structorizer is a little tool which you can use to create Nassi-Schneiderman Diagrams (NSD). Stuctorizer is written in Java and free for any use. The code has been moved to Github: https://github.com/fesch/Structorizer.Desktop

Analysis software for MRS/NMR data. Allows processing and fitting to be performed in a fully automatic workflow.

JAG3D is no longer developed at source-forge, and has moved to GitHub. Please visit https://github.com/applied-geodesy/jag3d or https://software.applied-geodesy.org to get the latest version.

jpaul is a Java implementation of several algorithms widely used in program analysis. It emphasizes flexibility and ease-of-use and is independent of any specific compiler infrastructure project. BSD Licence.

Carnaval est un logiciel destiné au calcul de masques et d'ensoleillement. La version actuelle permet de calculer les trajectoires solaires et les masques de terrain liés au relief (modèle issu des données SRTM). Les développements ont été repris par Sober Software. Merci de visiter ce site pour télécharger la dernière version et accéder aux nouvelles fonctionalités : www.sober-software.com

MultiBoost is a C++ implementation of the multi-class AdaBoost algorithm. AdaBoost is a powerful meta-learning algorithm commonly used in machine learning. The code is well documented and easy to extend, especially for adding new weak learners.

psimpl - generic n-dimensional polyline simplification. psimpl is a lightweight C++ library that is generic, easy to use, and supports multiple simplification algorithms, including Douglas-Peucker.

BigAl is a free open source and platform independent software for calculating really BIG numbers. It supports not only standard arithmetic, but also exact period determination, predefined factorials, fibonacci with seeds, factorization, nth root, etc

See the new project page: https://nojhan.github.io/paradiseo/ (Archived project page: http://eodev.sourceforge.net/)

Sinalgo is a simulation framework for testing and validating network algorithms. It allows for quick prototyping and verification in freely customizable network settings. It is mainly suited for packet-oriented wireless networks.

This collection of Python3 modules provides a large range of implemented decision aiding algorithms useful in the field of outranking digraphs based Multiple Criteria Decision Aid (MCDA), especially best choice, linear ranking and absolute or relative rating algorithms with multiple incommensurable criteria. Technical documentation and tutorials are available under the following link: https://digraph3.readthedocs.io/en/latest/ The tutorials introduce the main objects like digraphs, outranking digraphs and performance tableaux. There is also a tutorial provided on undirected graphs. Some tutorials are problem oriented and show how to compute the winner of an election, how to build a best choice recommendation, or how to linearly rank or rate with multiple incommensurable performance criteria. Other tutorials concern more specifically operational aspects of computing maximal independent sets (MISs) and kernels in graphs and digraphs.

TSPSG is intended to generate and solve Travelling Salesman Problem (TSP) tasks. It uses Branch and Bound method for solving. An input is a number of cities and a matrix of city-to-city travel prices. The matrix can be populated with random values in a given range (useful for generating tasks). The result is an optimal route, its price, step-by-step matrices of solving and solving graph. The task can be saved in internal binary format and opened later. The result can be printed or saved as PDF, HTML, or ODF. TSPSG may be useful for teachers to generate test tasks or just for regular users to solve TSPs. Also, it may be used as an example of using Branch and Bound method to solve a particular task.

TimeFinder automatically optimizes schedules (timetables) for universities and high schools. It makes manual timetabling for the timetabler easier via a Java GUI. Export+import is supported via xml and text formats. http://timefinder.sourceforge.net/

SimMetrics is a Similarity Metric Library, e.g. from edit distance's (Levenshtein, Gotoh, Jaro etc) to other metrics, (e.g Soundex, Chapman). Work provided by UK Sheffield University funded by (AKT) an IRC sponsored by EPSRC, grant number GR/N15764/01.

CoRoPa stands for Computational Rough Paths. The aim of CoRoPa is to provide a software framework for various ideas related to Rough Path Theory, including rough differential equations and the digital description of serial data streams.

An OpenGL GUI for the inspection and segmentation of 3D surface meshes

NeoBio is a Java class library of Computational Biology Algorithms. The current version consists mainly of pairwise sequence alignment algorithms such as the classical dynamic programming methods of Needleman-Wunsch and Smith-Waterman.

Sudoku Maker is a generator for Sudoku number puzzles. It uses a genetic algorithm internally, so it can serve as an introduction to genetic algorithms. The generated Sudokus are usually very hard to solve -- good for getting rid of a Sudoku addiction.

This is a commandline-terminal sokoban solver written in Ada. It is "generic" in the sense that it contains no domain specific strategies. It also provides a demonstration of the incredible power of the Hungarian Algorithm. The proper command to extract the archive and maintain the directory structure is "7z x filename".

JGAP is a Genetic Algorithms and Genetic Programming package written in Java. It is designed to require minimum effort to use, but is also designed to be highly modular. JGAP features grid functionality and a lot of examples. Many unit tests included. Legal notice/Impressum: Klaus Meffert An der Struth 25 D-65510 Idstein sourceforge <at> klausmeffert.de

The Modular toolkit for Data Processing (MDP) is a Python data processing framework. From the user's perspective, MDP is a collection of supervised and unsupervised learning algorithms and other data processing units that can be combined into data processing sequences and more complex feed-forward network architectures. From the scientific developer's perspective, MDP is a modular framework, which can easily be expanded. The implementation of new algorithms is easy and intuitive. The new implemented units are then automatically integrated with the rest of the library. The base of available algorithms is steadily increasing and includes signal processing methods (Principal Component Analysis, Independent Component Analysis, Slow Feature Analysis), manifold learning methods ([Hessian] Locally Linear Embedding), several classifiers, probabilistic methods (Factor Analysis, RBM), data pre-processing methods, and many others.

FRODO is a Java platform to solve Distributed Constraint Satisfaction Problems (DisCSPs) and Optimization Problems (DCOPs). It provides implementations for a variety of algorithms, including DPOP (and its variants), ADOPT, SynchBB, DSA...

* Fast GPU linear algebra library (matrix maths) for the C++ language, aiming towards a good balance between speed and ease of use * Provides high-level syntax and functionality deliberately similar to Matlab * Provides an API that is aiming to be compatible with Armadillo for easy transition between CPU and GPU linear algebra code * Useful for algorithm development directly in C++, or quick conversion of research code into production environments * Distributed under the permissive Apache 2.0 license, useful for both open-source and proprietary (closed-source) software * Can be used for machine learning, pattern recognition, computer vision, signal processing, bioinformatics, statistics, finance, etc * Downloads: http://coot.sourceforge.io/download.html * Documentation: http://coot.sourceforge.io/docs.html * Bug reports: http://coot.sourceforge.io/faq.html * Git repo: https://gitlab.com/conradsnicta/bandicoot-code