jsci.maths.matrices

Package jsci.maths.matrices

Matrix and Vector classes.

See: Description

Package jsci.maths.matrices Description

Matrix and Vector classes.

The matrix and vector classes support three different numeric types. These are integer (for speed), double (for accuracy) and complex.

The square matrix classes introduce the following methods:

  • LU decomposition (luDecompose)

    Decomposes a matrix M into a lower triangular matrix L and an upper triangular matrix U, such that M=LU.

  • Cholesky decomposition (choleskyDecompose)

    Similar to LU decomposition but with the addition property that U=LT. The matrix must be symmetric and positive definite for this to work correctly.

  • Singular value decomposition (singularValueDecompose)

    Decomposes a matrix M into an orthogonal matrix U, a diagonal matrix S and an orthogonal matrix V, such that M=USVT.

  • Inverse (inverse)

    Computes the inverse of a matrix using LU decomposition (M-1=U-1L-1).

Where ever possible, the abstract matrix/vector API should be used in preference to a particular matrix/vector implementation API.That is, use code like AbstractDoubleVector vec = new DoubleVector(dim);.This philosophy is similar to that of the Java Collections Framework.

SCaVis 1.7 © jWork.org