Java matrix libraries

Question

I was wondering whether any of the well-known matrix libraries for Java, such as Colt or EJML, actually provide similar functionality as MatLab? For instance, I can\'t seem

Answer 1

Some Java libraries for linear algebra are:

• Apache Commons Math: http://commons.apache.org/proper/commons-math/
• jeigen - a wrapper for eigen - https://github.com/hughperkins/jeigen (includes complex and rarely found feature like matrix exponential and matrix logarithm)
• jblas http://mikiobraun.github.io/jblas/ (also features more complex functions like matrix exponential, also very fast).
• Colt http://acs.lbl.gov/software/colt/
• JAMA http://math.nist.gov/javanumerics/jama/
• UJMP - http://sourceforge.net/projects/ujmp/

EDIT maybe we can extend this list whenever one comes across and you know - the world keeps moving:

• ojAlgo - http://ojalgo.org/ has promising benchmarks
• Efficient Java Matrix Library (EJML) - http://ejml.org
• ParallelColt - https://sites.google.com/site/piotrwendykier/software/parallelcolt
• la4j - http://la4j.org/
• MTJ - https://github.com/fommil/matrix-toolkits-java
• nd4j - https://nd4j.org/ lets you choose underlying native implementations like cuda or openBlas

Note: Personally: I use Apache Commons Math and Colt in my own project (http://www.finmath.net). While commons math is actively developed, I found that Colt is still faster in some tasks (like Eigenvalue decomposition). For that reason I use some kind of wrapper which allows me to quickly switch the underlying library (I only need a few things like solving systems of equations and Eigenvalue decomposition).