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Java example source code file (AbstractEvaluation.java)

This example Java source code file (AbstractEvaluation.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.

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Java - Java tags/keywords

abstractevaluation, arrayrealvector, decompositionsolver, qrdecomposition, realmatrix, realvector

The AbstractEvaluation.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,
 * See the License for the specific language governing permissions and
 * limitations under the License.
package org.apache.commons.math3.fitting.leastsquares;

import org.apache.commons.math3.fitting.leastsquares.LeastSquaresProblem.Evaluation;
import org.apache.commons.math3.linear.ArrayRealVector;
import org.apache.commons.math3.linear.DecompositionSolver;
import org.apache.commons.math3.linear.QRDecomposition;
import org.apache.commons.math3.linear.RealMatrix;
import org.apache.commons.math3.linear.RealVector;
import org.apache.commons.math3.util.FastMath;

 * An implementation of {@link Evaluation} that is designed for extension. All of the
 * methods implemented here use the methods that are left unimplemented.
 * <p/>
 * TODO cache results?
 * @since 3.3
public abstract class AbstractEvaluation implements Evaluation {

    /** number of observations */
    private final int observationSize;

     * Constructor.
     * @param observationSize the number of observation. Needed for {@link
     *                        #getRMS()}.
    AbstractEvaluation(final int observationSize) {
        this.observationSize = observationSize;

    /** {@inheritDoc} */
    public RealMatrix getCovariances(double threshold) {
        // Set up the Jacobian.
        final RealMatrix j = this.getJacobian();

        // Compute transpose(J)J.
        final RealMatrix jTj = j.transpose().multiply(j);

        // Compute the covariances matrix.
        final DecompositionSolver solver
                = new QRDecomposition(jTj, threshold).getSolver();
        return solver.getInverse();

    /** {@inheritDoc} */
    public RealVector getSigma(double covarianceSingularityThreshold) {
        final RealMatrix cov = this.getCovariances(covarianceSingularityThreshold);
        final int nC = cov.getColumnDimension();
        final RealVector sig = new ArrayRealVector(nC);
        for (int i = 0; i < nC; ++i) {
            sig.setEntry(i, FastMath.sqrt(cov.getEntry(i,i)));
        return sig;

    /** {@inheritDoc} */
    public double getRMS() {
        final double cost = this.getCost();
        return FastMath.sqrt(cost * cost / this.observationSize);

    /** {@inheritDoc} */
    public double getCost() {
        final ArrayRealVector r = new ArrayRealVector(this.getResiduals());
        return FastMath.sqrt(r.dotProduct(r));


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