Download JAR files tagged by algebra with all dependencies

Redberry is an open source computer algebra system designed for tensor manipulation. It implements basic computer algebra system routines as well as complex tools for real computations in physics. This module contains the implementation of special routines needed in real physical problems. It contains tools for such problems like Feynman graphs and one-loop counterterms calculation etc.

The chart-fx charting library is an extension in the spirit of Oracle's XYChart and performance/time-proven JDataViewer charting functionalities. Emphasis was put on plotting performance for both large number of data points and real-time displays, as well as scientific accuracies leading to error bar/surface plots, and other scientific plotting features (parameter measurements, fitting, multiple axes, zoom, ...). The library also contains a small set of math routines that can operate directly on the DataSet primitive for fitting, computing spectra, linear algebra, FIR/IIR filtering, and other functionalities common to signal processing.

The chart-fx charting library is an extension in the spirit of Oracle's XYChart and performance/time-proven JDataViewer charting functionalities. Emphasis was put on plotting performance for both large number of data points and real-time displays, as well as scientific accuracies leading to error bar/surface plots, and other scientific plotting features (parameter measurements, fitting, multiple axes, zoom, ...). The library also contains a small set of math routines that can operate directly on the DataSet primitive for fitting, computing spectra, linear algebra, FIR/IIR filtering, and other functionalities common to signal processing.

The Universal Java Matrix Package (UJMP) is an open source library for dense and sparse matrix computations and linear algebra in Java. In addition to the basic operations like matrix multiplication, matrix inverse or decomposition methods, it also supports visualization, JDBC import/export and many other useful functions such as mean, correlation, standard deviation, mutual information, or the replacement of missing values. It's a swiss army knife for data processing in Java, tailored to machine learning applications.

JSci is a set of open source Java packages. The aim is to encapsulate scientific methods/principles in the most natural way possible. As such they should greatly aid the development of scientific based software. It offers: abstract math interfaces, linear algebra (support for various matrix and vector types), statistics (including probability distributions), wavelets, newtonian mechanics, chart/graph components (AWT and Swing), MathML DOM implementation, ... Note: some packages, like javax.comm, for the astro and instruments package aren't listed as dependencies (not available).

The Java Algebra System (JAS) is an object oriented, type safe and multi-threaded approach to computer algebra. JAS provides a well designed software library using generic types for algebraic computations implemented in the Java programming language using the JVM runtime infrastructure. The library can be used as any other Java software package or it can be used interactively or interpreted through a jython (Java Python) or jruby (Java Ruby) front end, there is also an Android App based on Ruboto (jruby for Android). The focus of JAS is at the moment on commutative, solvable and non-commutative polynomials, power series, Groebner bases, factorization, real and complex roots and applications. By the use of Java as implementation language JAS is 64-bit and multi-core CPU ready and can make use of mutiple CPUs where available. JAS can run on a wide variety of devices ranging from Android to compute clusters (using MPJ a Java Message Passing Interface (MPI) or OpenMPI).

PATRIUS is a core space dynamics Java library that enables to quickly develop high level algorithms such as orbit extrapolator. PATRIUS contains several sub-libraries that work together and cover low level classes (i.e.: such as matrix, vectors, orbits parameters) as well as high level classes and interfaces (i.e.: numerical propagators, attitude laws, manoeuvers sequences). All the main domains of space dynamics are available: Analysis, algebra and geometry core library (quaternions, derivable functions, integrators …) Core objects for space dynamics (dates, orbits, frames...) Orbit propagation: analytical, semi-analytical and numerical propagators, a full set of force models Maneuvers: impulsive or continuous thrust, sequences Attitude: extensible set of attitude laws, sequences and guidance framework Events: event detection (orbital, sensor events, etc.) and post-processing (chronograms) Spacecraft: characteristics of mass, geometry (drag force), sensors field of view, etc.

This module contains a more general approach to construct AlignmentAlgorithms by relying on the theoretical concept of Algebraic Dynamic Programming (ADP) as developed by Giegerich et al. ADP defines four ingredients for an alignment algorithm: 1.) A signature that defines the permitted alignment operations. Operations are just function templates with an associated arity, meaning the number of arguments it takes from the left sequence and from the right sequence. In the TCSAlignmentToolbox we have a fixed signature with the following operations: REPLACEMENT(1, 1), DELETION(1, 0), INSERTION(0, 1), SKIPDELETION(1, 0) and SKIPINSERTION(0, 1) 2.) A regular tree grammar that produces alignments, that is: sequences of operations, in a restricted fashion. 3.) An algebra that can translate such trees to a cost. In the TCSAlignmentToolbox this is a Comparator. 4.) A choice function, in case of the TCSAlignmentToolbox: the strict minimum or the soft minimum. An alignment algorithm in the TCSAlignmentToolbox sense of the word then is the combination of choice function and grammar. While we provide hardcoded versions of these combinations in the main package, the adp package allows you to create your own grammars. You can combine them with a choice function by instantiating one of the Algorithm classes provided in this package with a grammar of your choice. For example: AlignmentAlgorithm algo = new SoftADPScoreAlgorithm(my_grammar, comparator); creates an alignment algorithm that implicitly produces all possible alignments your grammar can construct with the given input, translates them to a cost using the algebra/comparator you provided and applies the soft minimum to return the score. This all gets efficient by dynamic programming. Note that there is runtime overhead when using this method in comparison with the hardcoded algorithms. But for complicated grammars this is a much easier way to go. For more information on the theory, please refer to my master's thesis: "Adaptive Affine Sequence Alignment using Algebraic Dynamic Programming"