public class EigenValueDecomposition
extends Object
Constructor and Description |
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EigenValueDecomposition() |
Modifier and Type | Method and Description |
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static scala.Tuple2<breeze.linalg.DenseVector<Object>,breeze.linalg.DenseMatrix<Object>> |
symmetricEigs(scala.Function1<breeze.linalg.DenseVector<Object>,breeze.linalg.DenseVector<Object>> mul,
int n,
int k,
double tol,
int maxIterations)
Compute the leading k eigenvalues and eigenvectors on a symmetric square matrix using ARPACK.
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public static scala.Tuple2<breeze.linalg.DenseVector<Object>,breeze.linalg.DenseMatrix<Object>> symmetricEigs(scala.Function1<breeze.linalg.DenseVector<Object>,breeze.linalg.DenseVector<Object>> mul, int n, int k, double tol, int maxIterations)
n*(4*k+4)
doubles.
mul
- a function that multiplies the symmetric matrix with a DenseVector.n
- dimension of the square matrix (maximum Int.MaxValue).k
- number of leading eigenvalues required, where k must be positive and less than n.tol
- tolerance of the eigs computation.maxIterations
- the maximum number of Arnoldi update iterations.