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Java example source code file (JacobiPreconditioner.java)

This example Java source code file (JacobiPreconditioner.java) is included in the alvinalexander.com "Java Source Code Warehouse" project. The intent of this project is to help you "Learn Java by Example" TM.

Learn more about this Java project at its project page.

Java - Java tags/keywords

abstractrealmatrix, arrayrealvector, jacobipreconditioner, nonsquareoperatorexception, override, reallinearoperator, realvector, sqrt

The JacobiPreconditioner.java Java example source code

/*
 * Licensed to the Apache Software Foundation (ASF) under one or more
 * contributor license agreements.  See the NOTICE file distributed with
 * this work for additional information regarding copyright ownership.
 * The ASF licenses this file to You under the Apache License, Version 2.0
 * (the "License"); you may not use this file except in compliance with
 * the License.  You may obtain a copy of the License at
 *
 *      http://www.apache.org/licenses/LICENSE-2.0
 *
 * Unless required by applicable law or agreed to in writing, software
 * distributed under the License is distributed on an "AS IS" BASIS,
 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 * See the License for the specific language governing permissions and
 * limitations under the License.
 */
package org.apache.commons.math3.linear;

import org.apache.commons.math3.analysis.function.Sqrt;
import org.apache.commons.math3.util.MathArrays;

/**
 * This class implements the standard Jacobi (diagonal) preconditioner. For a
 * matrix A<sub>ij, this preconditioner is
 * M = diag(1 / A<sub>11, 1 / A22, …).
 *
 * @since 3.0
 */
public class JacobiPreconditioner extends RealLinearOperator {

    /** The diagonal coefficients of the preconditioner. */
    private final ArrayRealVector diag;

    /**
     * Creates a new instance of this class.
     *
     * @param diag the diagonal coefficients of the linear operator to be
     * preconditioned
     * @param deep {@code true} if a deep copy of the above array should be
     * performed
     */
    public JacobiPreconditioner(final double[] diag, final boolean deep) {
        this.diag = new ArrayRealVector(diag, deep);
    }

    /**
     * Creates a new instance of this class. This method extracts the diagonal
     * coefficients of the specified linear operator. If {@code a} does not
     * extend {@link AbstractRealMatrix}, then the coefficients of the
     * underlying matrix are not accessible, coefficient extraction is made by
     * matrix-vector products with the basis vectors (and might therefore take
     * some time). With matrices, direct entry access is carried out.
     *
     * @param a the linear operator for which the preconditioner should be built
     * @return the diagonal preconditioner made of the inverse of the diagonal
     * coefficients of the specified linear operator
     * @throws NonSquareOperatorException if {@code a} is not square
     */
    public static JacobiPreconditioner create(final RealLinearOperator a)
        throws NonSquareOperatorException {
        final int n = a.getColumnDimension();
        if (a.getRowDimension() != n) {
            throw new NonSquareOperatorException(a.getRowDimension(), n);
        }
        final double[] diag = new double[n];
        if (a instanceof AbstractRealMatrix) {
            final AbstractRealMatrix m = (AbstractRealMatrix) a;
            for (int i = 0; i < n; i++) {
                diag[i] = m.getEntry(i, i);
            }
        } else {
            final ArrayRealVector x = new ArrayRealVector(n);
            for (int i = 0; i < n; i++) {
                x.set(0.);
                x.setEntry(i, 1.);
                diag[i] = a.operate(x).getEntry(i);
            }
        }
        return new JacobiPreconditioner(diag, false);
    }

    /** {@inheritDoc} */
    @Override
    public int getColumnDimension() {
        return diag.getDimension();
    }

    /** {@inheritDoc} */
    @Override
    public int getRowDimension() {
        return diag.getDimension();
    }

    /** {@inheritDoc} */
    @Override
    public RealVector operate(final RealVector x) {
        // Dimension check is carried out by ebeDivide
        return new ArrayRealVector(MathArrays.ebeDivide(x.toArray(),
                                                        diag.toArray()),
                                   false);
    }

    /**
     * Returns the square root of {@code this} diagonal operator. More
     * precisely, this method returns
     * P = diag(1 / √A<sub>11, 1 / √A22, …).
     *
     * @return the square root of {@code this} preconditioner
     * @since 3.1
     */
    public RealLinearOperator sqrt() {
        final RealVector sqrtDiag = diag.map(new Sqrt());
        return new RealLinearOperator() {
            /** {@inheritDoc} */
            @Override
            public RealVector operate(final RealVector x) {
                return new ArrayRealVector(MathArrays.ebeDivide(x.toArray(),
                                                                sqrtDiag.toArray()),
                                           false);
            }

            /** {@inheritDoc} */
            @Override
            public int getRowDimension() {
                return sqrtDiag.getDimension();
            }

            /** {@inheritDoc} */
            @Override
            public int getColumnDimension() {
                return sqrtDiag.getDimension();
            }
        };
    }
}

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