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/*
* 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;
/**
* An algorithm that can be applied to a non-linear least squares problem.
*
* @since 3.3
*/
public interface LeastSquaresOptimizer {
/**
* Solve the non-linear least squares problem.
*
*
* @param leastSquaresProblem the problem definition, including model function and
* convergence criteria.
* @return The optimum.
*/
Optimum optimize(LeastSquaresProblem leastSquaresProblem);
/**
* The optimum found by the optimizer. This object contains the point, its value, and
* some metadata.
*/
//TODO Solution?
interface Optimum extends LeastSquaresProblem.Evaluation {
/**
* Get the number of times the model was evaluated in order to produce this
* optimum.
*
* @return the number of model (objective) function evaluations
*/
int getEvaluations();
/**
* Get the number of times the algorithm iterated in order to produce this
* optimum. In general least squares it is common to have one {@link
* #getEvaluations() evaluation} per iterations.
*
* @return the number of iterations
*/
int getIterations();
}
}
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