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With inspiration from other libraries
/*
* 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.fitting.leastsquares;
import org.apache.commons.math3.fitting.leastsquares.LeastSquaresOptimizer.Optimum;
import org.apache.commons.math3.fitting.leastsquares.LeastSquaresProblem.Evaluation;
import org.apache.commons.math3.linear.RealMatrix;
import org.apache.commons.math3.linear.RealVector;
/**
* A pedantic implementation of {@link Optimum}.
*
* @since 3.3
*/
class OptimumImpl implements Optimum {
/** abscissa and ordinate */
private final Evaluation value;
/** number of evaluations to compute this optimum */
private final int evaluations;
/** number of iterations to compute this optimum */
private final int iterations;
/**
* Construct an optimum from an evaluation and the values of the counters.
*
* @param value the function value
* @param evaluations number of times the function was evaluated
* @param iterations number of iterations of the algorithm
*/
OptimumImpl(final Evaluation value, final int evaluations, final int iterations) {
this.value = value;
this.evaluations = evaluations;
this.iterations = iterations;
}
/* auto-generated implementations */
/** {@inheritDoc} */
public int getEvaluations() {
return evaluations;
}
/** {@inheritDoc} */
public int getIterations() {
return iterations;
}
/** {@inheritDoc} */
public RealMatrix getCovariances(double threshold) {
return value.getCovariances(threshold);
}
/** {@inheritDoc} */
public RealVector getSigma(double covarianceSingularityThreshold) {
return value.getSigma(covarianceSingularityThreshold);
}
/** {@inheritDoc} */
public double getRMS() {
return value.getRMS();
}
/** {@inheritDoc} */
public RealMatrix getJacobian() {
return value.getJacobian();
}
/** {@inheritDoc} */
public double getCost() {
return value.getCost();
}
/** {@inheritDoc} */
public RealVector getResiduals() {
return value.getResiduals();
}
/** {@inheritDoc} */
public RealVector getPoint() {
return value.getPoint();
}
}