Java matrix libraries

The interface for COLT gives you a generic OP: assign(matrix, function), which you can use to add or subtract matrices and vectors.

As the javadocs for assign() says:

Assigns the result of a function to each cell; x[row,col] =function(x[row,col],y[row,col]).

So by using using an addition function as function - you can add matrices.


Try Apache Commons Math library. org.apache.commons.math3.linear package contains the functions that you want. Home page


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).

Tags:

Java

Matrix

Colt