Open Source Algorithms

Technical analysis library with indicators like ADX, MACD, RSI, Stochastic, TRIX... includes also candlestick pattern recognition. Useful for trading application developpers using either Excel, .NET, Mono, Java, Perl or C/C++.

CRC RevEng is a portable, arbitrary-precision CRC calculator and algorithm finder. It calculates CRCs using any of the 113 preset algorithms, or a user-specified algorithm to any width. It calculates reversed CRCs to give the bit pattern that produces a desired forward CRC. CRC RevEng also reverse-engineers any CRC algorithm from sufficient correctly formatted message-CRC pairs and optional known parameters. It comprises powerful input interpretation options. Compliant with Ross Williams' Rocksoft(tm) model of parametrised CRC algorithms.

JDIFF is a program that outputs the differences between two binary files, either in binary format or in human readable format (detailed or summarized) and then allows to reconstruct the second file from the first one and the diff-file.

LinAsm is collection of very fast and SIMD optimized assembly written libraries for x86-64 Linux. It implements many common and widely used algorithms for array manipulations: searching, sorting, arithmetic and vector operations, unit conversions; fast mathematical and statistic functions; numbers and time converting algorithms; finite impulse response (FIR) digital filters; spectrum analysis algorithms, Fast Hartley transformation; CPU cache friendly functions and extremely fast abstract data types (ADT) such as hash tables b-trees, and much more. LinAsm libraries are written on FASM assembly language. They are stable and have appropriate benchmarks for many units. All libraries are well documented and grouped by their functionality. To get more information about this library, please visit the official web site: http://linasm.sourceforge.net

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

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.

DRAMMS is a software package designed for 2D-to-2D and 3D-to-3D deformable medical image registration tasks. Released by Section of Biomedical Image Analysis (SBIA) at the University of Pennsylvania. Some typical applications of DRAMMS include, -- Cross-subject registration of the same organ (can be brain, breast, cardiac, etc); -- Mono- and Multi-modality registration (MRI, CT, histology); -- Longitudinal registration (pediatric brain growth, cancer development, mouse brain development, etc); -- Registration under missing correspondences (e.g., vascular lesions, tumors, histological cuts). DRAMMS runs in command line in UNIX/Mac OS, It accepts Nifti/ANALYZE/MetaImage image formats. It is fully-automatic --- takes two input images, and generates a registered image and (optionally) the deformation field. More information (installation, tutorial, manual, demonstration, FAQ, etc) can be found at http://www.rad.upenn.edu/sbia/software/dramms/ .

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.

The package implements a variety of tools for categorization of multivariate data such as boosted decision trees, bagging and random forest, bump hunting (PRIM), a multi-class learner and others.

A univariate and multivariate analysis UI. This project is no longer under development. Please use as you wish.

Progressive Function Point Analysis Book Released: Print Copy: http://www.amazon.com/Progressive-Function-Point-Analysis-Estimation/dp/1502354160 EBook: http://www.amazon.com/dp/B00NH0MMAG Please support this project and its future releases ! Managers provide the architect/teams with project requirements. The architect/team returns detailed task list with estimated man hours per task making life easier for Project Managers with less guesstimates and proper business/technical process flows to justify estimates. Better Accountability: All work is accounted for in greater detail, ensuring payment. Task Bound: Every task identified and defined in a user story with well-planned set of functions Time Bound: Every task and user story has a pre-defined time limit for monitoring. Working Blueprint: Base design for development defined in Process steps. Team Involvement: Teams work together in counting process and thereby gain better insight into the project.

iGesture is a Java-based gesture recognition framework providing access to multiple gesture recognition algorithms and different input devices. The iGesture Workbench supports the definition and evaluation of customised gesture sets and algorithms.

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.

This project has moved to github at http://lmwtree.devries.ninja.

The Arbitrarily-Decomposed MPI FFT library is a C subroutine library for the computation of the multidimensional Fast Fourier Transform (FFT) of a distributed grid using the Message-Passing Interface (MPI).

Balie - BAseLine Information Extraction (in Java) This project is not maintained anymore.

Barracuda is a circuit board analyzer that analyze PCB and make sure the new boards doesn't contain errors Barracuda has now his first release, The error detection works fine, but it require to much calibration to get good pictures.

Cluster Analysis Wrapped Feature Subset Selection (CAWFSS) is a collection of feature subset selection algorithms which use various cluster analysis algorithms as wrappers.

Continuous wavelet transform library

Software to build database of all best solution of all configurations of Cube21/Square1 Silver edition puzzle cube. Also 3D UI is provided.

FORce based Cluster Editing (FORCE) is a Java software heuristically solving the graph cluster editing problem on weighted edges using BLAST E-values. It further provides a training mode for heuristic parameter estimation.

This is a method for identifying graphs using MD5 hashing. It can be used for graph equality comparisons and to facilitate graph isomorphism testing. The graphs can be labeled or unlabeled.

Genetic Programming (tree structure) predictor within Weka data mining software for both continuous and classification problems.

C++, Matlab and Python library for Hidden-state Conditional Random Fields. Implements 3 algorithms: LDCRF, HCRF and CRF. For Windows and Linux, 32- and 64-bits. Optimized for multi-threading. Works with sparse or dense input features.

This is a framework used to decompose hierarchical graphs, i.e.,graphs which were created from or contain a hierarchy of modules. Each module is reused several times in the hierarchy. This may be useful to reverse-engineer human constructs like electronic equipment, manufactured machines, or bureaucratic hierarchies; but also to decompose natural constructs like gene-relation or protein-relation nets.