Project details for Universal Java Matrix Package

Screenshot Universal Java Matrix Package 0.3.0

by arndt - July 31, 2015, 14:23:14 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ]

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The Universal Java Matrix Package (UJMP) is an open source Java library which provides sparse and dense matrix classes, as well as a large number of calculations for linear algebra like matrix multiplication or matrix inverse. Operations such as mean, correlation, standard deviation, replacement of missing values or the calculation of mutual information are supported also.

The Universal Java Matrix Package provides various visualization methods, import and export filters for a large number of file formats, and the possibility to link to tables in JDBC databases. Multi-dimensional matrices as well as generic matrices with a specified object type are supported and very large matrices with up to 2^63 rows and columns can be handled even when they do not fit into memory.

A central concept of UJMP is the separation of interfaces, abstract classes and their implementations, which makes it very easy to exchange the underlying data storage. Thus, a matrix in our framework can be an array of values in main memory, a file on disk or a table in an SQL database. In fact, the actual storage implementation becomes secondary and UJMP can even integrate other matrix libraries such as JAMA or Colt, making UJMP’s visualization and import and export filters available to these libraries.

On the other hand, UJMP can also decide to redirect calculations to other matrix libraries, depending on matrix size and computer hardware. UJMP uses multiple threads for calculations, which results in much better performance compared to JAMA or Colt on modern hardware.

UJMP also includes interfaces to Matlab, Octave and R, which makes it easy to perform calculations not available in Java.

While some parts of UJMP are pretty stable by now, a lot of development is still going on in other parts. Developers are welcome to contribute!

Changes to previous version:

Updated to version 0.3.0

BibTeX Entry: Download
Corresponding Paper BibTeX Entry: Download
Supported Operating Systems: Platform Independent
Data Formats: Ascii, Binary, Matlab, Java Arrays, Lucene, Txt, Wav
Tags: Large Scale, Matlab, Octave, Matrix Library, High Dimensional Data, Parallel, Algorithms, Pca, Missing Data, Lapack, Linear Algebra, Matrix, Matrix Factorization, Large Datasets, Java, Icml2010
Archive: download here

Other available revisons

Version Changelog Date

Updated to version 0.3.0

July 31, 2015, 14:23:14

Meta data updated.

February 9, 2010, 15:55:23


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