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DDogleg Numerics is a high performance Java library for non-linear optimization, robust model fitting, polynomial root finding, sorting, and more.

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/*
 * Copyright (c) 2012-2016, Peter Abeles. All Rights Reserved.
 *
 * This file is part of DDogleg (http://ddogleg.org).
 *
 * Licensed 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.ddogleg.fitting.modelset;

import java.util.List;


/**
 * 

* Given a set of points and it finds a set of model parameters which fit the data robustly. Some of the points are * assumed to be noise and are pruned. The set of points which fit the found parameters and their index in the * input list are returned. *

* * @param Type of model being fitted. * @param Type of data point being fitted. * * @author Peter Abeles */ public interface ModelMatcher { /** * Finds a set of points from the provided list that are a good fit for the internal model and * computes the fit parameters for the model. * * @param dataSet Set of points (with noise) that are to be fit. * @return true if it successfully found a solution or false if not. */ public boolean process(List dataSet ); /** * Model for the match set * * @return model. */ public Model getModelParameters(); /** * A set of points which match the provided parameters. * * @return List of points in the match set. */ public List getMatchSet(); /** * For an item in the match set, return the index of the item in the original input set. * * @param matchIndex Index of an element in the match set. * @return Index of the same element in the original input list. */ public int getInputIndex( int matchIndex ); /** * Returns the metric used to evaluate the quality of fit. Meaning is implementation specific. Larger * or smaller values could be preferred depending on implementation.. * * @return Quality of fit to matched set of points */ public double getFitQuality(); /** * This is the minimum number of observations which can be input and produce a valid model. * * @return Minimum number of sample points */ public int getMinimumSize(); /** * Returns a class for the input point object */ Class getPointType(); /** * Returns a class for the input point object */ Class getModelType(); }




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