/*
    * Copyright (C) 2017 Alberto Irurueta Carro (alberto@irurueta.com)
    *
    * 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 com.irurueta.geometry.estimators;
  
  import com.irurueta.algebra.Matrix;
  import com.irurueta.geometry.EuclideanTransformation2D;
  import com.irurueta.geometry.Point2D;
  import com.irurueta.geometry.refiners.EuclideanTransformation2DRefiner;
  import com.irurueta.numerical.robust.InliersData;
  import com.irurueta.numerical.robust.RobustEstimatorException;
  import com.irurueta.numerical.robust.RobustEstimatorMethod;
  
  import java.util.List;
  
  /**
   * This is an abstract class to robustly find the best Euclidean transformation
   * for collections of matching 2D points.
   * Implementations of this class should be able to detect and discard outliers
   * in order to find the best solution.
   */
  @SuppressWarnings("DuplicatedCode")
  public abstract class EuclideanTransformation2DRobustEstimator {
  
      /**
       * Minimum number of matched points required to estimate an Euclidean 2D
       * transformation.
       */
      public static final int MINIMUM_SIZE = EuclideanTransformation2DEstimator.MINIMUM_SIZE;
  
      /**
       * For some point configurations a solution can be found with only 2 points.
       */
      public static final int WEAK_MINIMUM_SIZE = EuclideanTransformation2DEstimator.WEAK_MINIMUM_SIZE;
  
      /**
       * Default amount of progress variation before notifying a change in
       * estimation progress. By default, this is set to 5%.
       */
      public static final float DEFAULT_PROGRESS_DELTA = 0.05f;
  
      /**
       * Minimum allowed value for progress delta.
       */
      public static final float MIN_PROGRESS_DELTA = 0.0f;
  
      /**
       * Maximum allowed value for progress delta.
       */
      public static final float MAX_PROGRESS_DELTA = 1.0f;
  
      /**
       * Constant defining default confidence of the estimated result, which is
       * 99%. This means that with a probability of 99% estimation will be
       * accurate because chosen sub-samples will be inliers.
       */
      public static final double DEFAULT_CONFIDENCE = 0.99;
  
      /**
       * Default maximum allowed number of iterations.
       */
      public static final int DEFAULT_MAX_ITERATIONS = 5000;
  
      /**
       * Minimum allowed confidence value.
       */
      public static final double MIN_CONFIDENCE = 0.0;
  
      /**
       * Maximum allowed confidence value.
       */
      public static final double MAX_CONFIDENCE = 1.0;
  
      /**
       * Minimum allowed number of iterations.
       */
      public static final int MIN_ITERATIONS = 1;
  
      /**
       * Indicates that is refined by default using Levenberg-Marquardt
       * fitting algorithm over found inliers.
       */
      public static final boolean DEFAULT_REFINE_RESULT = true;
  
      /**
       * Indicates that covariance is not kept by default after refining result.
       */
     public static final boolean DEFAULT_KEEP_COVARIANCE = false;
 
     /**
      * Default robust estimator method when none is provided.
      */
     public static final RobustEstimatorMethod DEFAULT_ROBUST_METHOD = RobustEstimatorMethod.PROMEDS;
 
     /**
      * Listener to be notified of events such as when estimation starts, ends
      * or its progress significantly changes.
      */
     protected EuclideanTransformation2DRobustEstimatorListener listener;
 
     /**
      * Indicates if this estimator is locked because an estimation is being
      * computed.
      */
     protected boolean locked;
 
     /**
      * Amount of progress variation before notifying a progress change during
      * estimation.
      */
     protected float progressDelta;
 
     /**
      * Amount of confidence expressed as a value between 0.0 and 1.0 (which is
      * equivalent to 100%). The amount of confidence indicates the probability
      * that the estimated result is correct. Usually this value will be close
      * to 1.0, but not exactly 1.0.
      */
     protected double confidence;
 
     /**
      * Maximum allowed number of iterations. When the maximum number of
      * iterations is exceeded, result will not be available, however an
      * approximate result will be available for retrieval.
      */
     protected int maxIterations;
 
     /**
      * Data related to inliers found after estimation.
      */
     protected InliersData inliersData;
 
     /**
      * Indicates whether result must be refined using Levenberg-Marquardt
      * fitting algorithm over found inliers.
      * If true, inliers will be computed and kept in any implementation
      * regardless of the settings.
      */
     protected boolean refineResult;
 
     /**
      * Indicates whether covariance must be kept after refining result.
      * This setting is only taken into account if result is refined.
      */
     private boolean keepCovariance;
 
     /**
      * Estimated covariance of estimated 2D Euclidean transformation.
      * This is only available when result has been refined and covariance is
      * kept.
      */
     private Matrix covariance;
 
     /**
      * List of points to be used to estimate an Euclidean 2D transformation.
      * Each point in the list of input points must be matched with the
      * corresponding point in the list of output points located at the same
      * position. Hence, both input points and output points must have the same
      * size, and their size must be greater or equal than MINIMUM_SIZE.
      */
     protected List<Point2D> inputPoints;
 
     /**
      * List of points to be used to estimate an Euclidean 2D transformation.
      * Each point in the lis tof output points must be matched with the
      * corresponding point in the list of input points located at the same
      * position. Hence, both input points and output points must have the same
      * size, and their size must be greater or equal than MINIMUM_SIZE.
      */
     protected List<Point2D> outputPoints;
 
     /**
      * Indicates whether estimation can start with only 2 points or not.
      * True allows 2 points, false requires 3.
      */
     private boolean weakMinimumSizeAllowed;
 
 
     /**
      * Constructor.
      */
     protected EuclideanTransformation2DRobustEstimator() {
         progressDelta = DEFAULT_PROGRESS_DELTA;
         confidence = DEFAULT_CONFIDENCE;
         maxIterations = DEFAULT_MAX_ITERATIONS;
         refineResult = DEFAULT_REFINE_RESULT;
         keepCovariance = DEFAULT_KEEP_COVARIANCE;
     }
 
     /**
      * Constructor.
      *
      * @param listener listener to be notified of events such as when estimation
      *                 starts, ends or its progress significantly changes.
      */
     protected EuclideanTransformation2DRobustEstimator(
             final EuclideanTransformation2DRobustEstimatorListener listener) {
         this();
         this.listener = listener;
     }
 
     /**
      * Constructor with lists of points to be used to estimate an Euclidean 2D
      * transformation.
      * Points in the list located at the same position are considered to be
      * matched. Hence, both lists must have the same size, and their size must
      * be greater or equal than MINIMUM_SIZE.
      *
      * @param inputPoints  list of input points to be used to estimate an
      *                     Euclidean 2D transformation.
      * @param outputPoints list of output points to be used to estimate an
      *                     Euclidean 2D transformation.
      * @throws IllegalArgumentException if provided lists of points don't have
      *                                  the same size or their size is smaller than MINIMUM_SIZE.
      */
     protected EuclideanTransformation2DRobustEstimator(
             final List<Point2D> inputPoints, final List<Point2D> outputPoints) {
         this();
         internalSetPoints(inputPoints, outputPoints);
     }
 
     /**
      * Constructor with listener and lists of points to be used to estimate an
      * Euclidean 2D transformation.
      * Points in the list located at the same position are considered to be
      * matched. Hence, both lists must have the same size, and their size must
      * be greater or equal than MINIMUM_SIZE.
      *
      * @param listener     listener to be notified of events such as when estimation
      *                     starts, ends or its progress significantly changes.
      * @param inputPoints  list of input points to be used to estimate an
      *                     Euclidean 2D transformation.
      * @param outputPoints list of output points to be used to estimate an
      *                     Euclidean 2D transformation.
      * @throws IllegalArgumentException if provided lists of points don't have
      *                                  the same size or their size is smaller than MINIMUM_SIZE.
      */
     protected EuclideanTransformation2DRobustEstimator(
             final EuclideanTransformation2DRobustEstimatorListener listener, final List<Point2D> inputPoints,
             final List<Point2D> outputPoints) {
         this(listener);
         internalSetPoints(inputPoints, outputPoints);
     }
 
     /**
      * Constructor.
      *
      * @param weakMinimumSizeAllowed true allows 2 points, false requires 3.
      */
     protected EuclideanTransformation2DRobustEstimator(final boolean weakMinimumSizeAllowed) {
         this();
         this.weakMinimumSizeAllowed = weakMinimumSizeAllowed;
     }
 
     /**
      * Constructor.
      *
      * @param listener               listener to be notified of events such as when estimation
      *                               starts, ends or its progress significantly changes.
      * @param weakMinimumSizeAllowed true allows 2 points, false requires 3.
      */
     protected EuclideanTransformation2DRobustEstimator(
             final EuclideanTransformation2DRobustEstimatorListener listener, final boolean weakMinimumSizeAllowed) {
         this();
         this.listener = listener;
         this.weakMinimumSizeAllowed = weakMinimumSizeAllowed;
     }
 
     /**
      * Constructor with lists of points to be used to estimate an Euclidean 2D
      * transformation.
      * Points in the list located at the same position are considered to be
      * matched. Hence, both lists must have the same size, and their size must
      * be greater or equal than MINIMUM_SIZE.
      *
      * @param inputPoints            list of input points to be used to estimate an
      *                               Euclidean 2D transformation.
      * @param outputPoints           list of output points to be used to estimate an
      *                               Euclidean 2D transformation.
      * @param weakMinimumSizeAllowed true allows 2 points, false requires 3.
      * @throws IllegalArgumentException if provided lists of points don't have
      *                                  the same size or their size is smaller than MINIMUM_SIZE.
      */
     protected EuclideanTransformation2DRobustEstimator(
             final List<Point2D> inputPoints, final List<Point2D> outputPoints, final boolean weakMinimumSizeAllowed) {
         this();
         this.weakMinimumSizeAllowed = weakMinimumSizeAllowed;
         internalSetPoints(inputPoints, outputPoints);
     }
 
     /**
      * Constructor with listener and lists of points to be used to estimate an
      * Euclidean 2D transformation.
      * Points in the list located at the same position are considered to be
      * matched. Hence, both lists must have the same size, and their size must
      * be greater or equal than MINIMUM_SIZE.
      *
      * @param listener               listener to be notified of events such as when estimation
      *                               starts, ends or its progress significantly changes.
      * @param inputPoints            list of input points to be used to estimate an
      *                               Euclidean 2D transformation.
      * @param outputPoints           list of output points to be used to estimate an
      *                               Euclidean 2D transformation.
      * @param weakMinimumSizeAllowed true allows 2 points, false requires 3.
      * @throws IllegalArgumentException if provided lists of points don't have
      *                                  the same size or their size is smaller than MINIMUM_SIZE.
      */
     protected EuclideanTransformation2DRobustEstimator(
             final EuclideanTransformation2DRobustEstimatorListener listener, final List<Point2D> inputPoints,
             final List<Point2D> outputPoints, final boolean weakMinimumSizeAllowed) {
         this(listener);
         this.weakMinimumSizeAllowed = weakMinimumSizeAllowed;
         internalSetPoints(inputPoints, outputPoints);
     }
 
     /**
      * Returns list of input points to be used to estimate an Euclidean 2D
      * transformation.
      * Each point in the list of input points must be matched with the
      * corresponding point in the list of output points located at the same
      * position. Hence, both input points and output points must have the same
      * size, and their size must be greater or equal than MINIMUM_SIZE.
      *
      * @return list of input points to be used to estimate an Euclidean 2D
      * transformation.
      */
     public List<Point2D> getInputPoints() {
         return inputPoints;
     }
 
     /**
      * Returns list of output points to be used to estimate an Euclidean 2D
      * transformation.
      * Each point in the list of output points must be matched with the
      * corresponding point in the list of input points located at the same
      * position. Hence, both input points and output points must have the same
      * size, and their size must be greater or equal than MINIMUM_SIZE.
      *
      * @return list of output points to be used to estimate an Euclidean 2D
      * transformation.
      */
     public List<Point2D> getOutputPoints() {
         return outputPoints;
     }
 
     /**
      * Sets list of points to be used to estimate an Euclidean 2D
      * transformation.
      * Points in the list located at the same position are considered to be
      * matched. Hence, both lists must have the same size, and their size must
      * be greater or equal than MINIMUM_SIZE.
      *
      * @param inputPoints  list of input points to be used to estimate an
      *                     Euclidean 2D transformation.
      * @param outputPoints list of output points to be used to estimate an
      *                     Euclidean 2D transformation.
      * @throws IllegalArgumentException if provided lists of points don't have
      *                                  the same size or their size is smaller than MINIMUM_SIZE.
      * @throws LockedException          if estimator is locked because a computation is
      *                                  already in progress.
      */
     public void setPoints(final List<Point2D> inputPoints, final List<Point2D> outputPoints) throws LockedException {
         if (isLocked()) {
             throw new LockedException();
         }
         internalSetPoints(inputPoints, outputPoints);
     }
 
     /**
      * Indicates if estimator is ready to start the Euclidean 2D transformation
      * estimation.
      * This is true when input data (i.e. lists of matched points) are provided
      * and a minimum of MINIMUM_SIZE points are available.
      *
      * @return true if estimator is ready, false otherwise.
      */
     public boolean isReady() {
         return inputPoints != null && outputPoints != null && inputPoints.size() == outputPoints.size()
                 && inputPoints.size() >= getMinimumPoints();
     }
 
     /**
      * Returns quality scores corresponding to each pair of matched points.
      * The larger the score value the better the quality of the matching.
      * This implementation always returns null.
      * Subclasses using quality scores must implement proper behaviour.
      *
      * @return quality scores corresponding to each pair of matched points.
      */
     public double[] getQualityScores() {
         return null;
     }
 
     /**
      * Sets quality scores corresponding to each pair of matched points.
      * The larger the score value the better the quality of the matching.
      * This implementation makes no action.
      * Subclasses using quality scores must implement proper behaviour.
      *
      * @param qualityScores quality scores corresponding to each pair of matched
      *                      points.
      * @throws LockedException          if robust estimator is locked because an
      *                                  estimation is already in progress.
      * @throws IllegalArgumentException if provided quality scores length is
      *                                  smaller than MINIMUM_SIZE (i.e. 3 samples).
      */
     public void setQualityScores(final double[] qualityScores) throws LockedException {
     }
 
     /**
      * Returns reference to listener to be notified of events such as when
      * estimation starts, ends or its progress significantly changes.
      *
      * @return listener to be notified of events.
      */
     public EuclideanTransformation2DRobustEstimatorListener getListener() {
         return listener;
     }
 
     /**
      * Sets listener to be notified of events such as when estimation starts,
      * ends or its progress significantly changes.
      *
      * @param listener listener to be notified of events.
      * @throws LockedException if robust estimator is locked.
      */
     public void setListener(final EuclideanTransformation2DRobustEstimatorListener listener) throws LockedException {
         if (isLocked()) {
             throw new LockedException();
         }
         this.listener = listener;
     }
 
     /**
      * Indicates whether listener has been provided and is available for
      * retrieval.
      *
      * @return true if available, false otherwise.
      */
     public boolean isListenerAvailable() {
         return listener != null;
     }
 
     /**
      * Indicates whether estimation can start with only 2 points or not.
      *
      * @return true allows 2 points, false requires 3.
      */
     public boolean isWeakMinimumSizeAllowed() {
         return weakMinimumSizeAllowed;
     }
 
     /**
      * Specifies whether estimation can start with only 2 points or not.
      *
      * @param weakMinimumSizeAllowed true allows 2 points, false requires 3.
      * @throws LockedException if estimator is locked.
      */
     public void setWeakMinimumSizeAllowed(final boolean weakMinimumSizeAllowed) throws LockedException {
         if (isLocked()) {
             throw new LockedException();
         }
         this.weakMinimumSizeAllowed = weakMinimumSizeAllowed;
     }
 
     /**
      * Required minimum number of point correspondences to start the estimation.
      * Can be either 2 or 3.
      *
      * @return minimum number of point correspondences.
      */
     public int getMinimumPoints() {
         return weakMinimumSizeAllowed ? WEAK_MINIMUM_SIZE : MINIMUM_SIZE;
     }
 
     /**
      * Indicates if this instance is locked because estimation is being
      * computed.
      *
      * @return true if locked, false otherwise.
      */
     public boolean isLocked() {
         return locked;
     }
 
     /**
      * Returns amount of progress variation before notifying a progress change
      * during estimation.
      *
      * @return amount of progress variation before notifying a progress change
      * during estimation.
      */
     public float getProgressDelta() {
         return progressDelta;
     }
 
     /**
      * Sets amount of progress variation before notifying a progress change
      * during estimation.
      *
      * @param progressDelta amount of progress variation before notifying a
      *                      progress change during estimation.
      * @throws IllegalArgumentException if progress delta is less than zero or
      *                                  greater than 1.
      * @throws LockedException          if this estimator is locked because an estimation
      *                                  is being computed.
      */
     public void setProgressDelta(final float progressDelta) throws LockedException {
         if (isLocked()) {
             throw new LockedException();
         }
         if (progressDelta < MIN_PROGRESS_DELTA || progressDelta > MAX_PROGRESS_DELTA) {
             throw new IllegalArgumentException();
         }
         this.progressDelta = progressDelta;
     }
 
     /**
      * Returns amount of confidence expressed as a value between 0.0 and 1.0
      * (which is equivalent to 100%). The amount of confidence indicates the
      * probability that the estimated result is correct. Usually this value will
      * be close to 1.0, but not exactly 1.0.
      *
      * @return amount of confidence as a value between 0.0 and 1.0.
      */
     public double getConfidence() {
         return confidence;
     }
 
     /**
      * Sets amount of confidence expressed as a value between 0.0 and 1.0 (which
      * is equivalent to 100%). The amount of confidence indicates the
      * probability that the estimated result is correct. Usually this value will
      * be close to 1.0, but not exactly 1.0.
      *
      * @param confidence confidence to be set as a value between 0.0 and 1.0.
      * @throws IllegalArgumentException if provided value is not between 0.0 and
      *                                  1.0.
      * @throws LockedException          if this estimator is locked because an estimator
      *                                  is being computed.
      */
     public void setConfidence(final double confidence) throws LockedException {
         if (isLocked()) {
             throw new LockedException();
         }
         if (confidence < MIN_CONFIDENCE || confidence > MAX_CONFIDENCE) {
             throw new IllegalArgumentException();
         }
         this.confidence = confidence;
     }
 
     /**
      * Returns maximum allowed number of iterations. If maximum allowed number
      * of iterations is achieved without converging to a result when calling
      * estimate(), a RobustEstimatorException will be raised.
      *
      * @return maximum allowed number of iterations.
      */
     public int getMaxIterations() {
         return maxIterations;
     }
 
     /**
      * Sets maximum allowed number of iterations. When the maximum number of
      * iterations is exceeded, result will not be available, however an
      * approximate result will be available for retrieval.
      *
      * @param maxIterations maximum allowed number of iterations to be set.
      * @throws IllegalArgumentException if provided value is less than 1.
      * @throws LockedException          if this estimator is locked because an estimation
      *                                  is being computed.
      */
     public void setMaxIterations(final int maxIterations) throws LockedException {
         if (isLocked()) {
             throw new LockedException();
         }
         if (maxIterations < MIN_ITERATIONS) {
             throw new IllegalArgumentException();
         }
         this.maxIterations = maxIterations;
     }
 
     /**
      * Gets data related to inliers found after estimation.
      *
      * @return data related to inliers found after estimation.
      */
     public InliersData getInliersData() {
         return inliersData;
     }
 
     /**
      * Indicates whether result must be refined using Levenberg-Marquardt
      * fitting algorithm over found inliers.
      * If ture, inliers will be computed and kept in any implementation
      * regardless of the settings.
      *
      * @return true to refine result, false to simply use result found by
      * robust estimator without further refining.
      */
     public boolean isResultRefined() {
         return refineResult;
     }
 
     /**
      * Specifies whether result must be refined using Levenberg-Marquardt
      * fitting algorithm over found inliers.
      *
      * @param refineResult true to refine result, false to simply use result
      *                     found by robust estimator without further refining.
      * @throws LockedException if estimator is locked.
      */
     public void setResultRefined(final boolean refineResult) throws LockedException {
         if (isLocked()) {
             throw new LockedException();
         }
         this.refineResult = refineResult;
     }
 
     /**
      * Indicates whether covariance must be kept after refining result.
      * This setting is only taken into account if result is refined.
      *
      * @return true if covariance must be kept after refining result, false
      * otherwise.
      */
     public boolean isCovarianceKept() {
         return keepCovariance;
     }
 
     /**
      * Specifies whether covariance must be kept after refining result.
      * This setting is only taken into account if result is refined.
      *
      * @param keepCovariance true if covariance must be kept after refining
      *                       result, false otherwise.
      * @throws LockedException if estimator is locked.
      */
     public void setCovarianceKept(final boolean keepCovariance) throws LockedException {
         if (isLocked()) {
             throw new LockedException();
         }
         this.keepCovariance = keepCovariance;
     }
 
     /**
      * Gets estimated covariance of estimated 3D point if available.
      * This is only available when result has been refined and covariance is
      * kept.
      *
      * @return estimated covariance or null.
      */
     public Matrix getCovariance() {
         return covariance;
     }
 
     /**
      * Estimates an Euclidean 2D transformation using a robust estimator and the
      * best set of matched 2D point correspondences found using the robust
      * estimator.
      *
      * @return an Euclidean 2D transformation.
      * @throws LockedException          if robust estimator is locked because an
      *                                  estimation is already in progress.
      * @throws NotReadyException        if provided input data is not enough to start
      *                                  the estimation.
      * @throws RobustEstimatorException if estimation fails for any reason
      *                                  (i.e. numerical instability, no solution available, etc).
      */
     public abstract EuclideanTransformation2D estimate() throws LockedException, NotReadyException,
             RobustEstimatorException;
 
     /**
      * Returns method being used for robust estimation.
      *
      * @return method being used for robust estimation.
      */
     public abstract RobustEstimatorMethod getMethod();
 
     /**
      * Creates an Euclidean 2D transformation estimator based on 2D point
      * correspondences and using provided robust estimator method.
      *
      * @param method method of a robust estimator algorithm to estimate the
      *               best Euclidean 2D transformation.
      * @return an instance of Euclidean 2D transformation estimator.
      */
     public static EuclideanTransformation2DRobustEstimator create(final RobustEstimatorMethod method) {
         return switch (method) {
             case LMEDS -> new LMedSEuclideanTransformation2DRobustEstimator();
             case MSAC -> new MSACEuclideanTransformation2DRobustEstimator();
             case PROSAC -> new PROSACEuclideanTransformation2DRobustEstimator();
             case PROMEDS -> new PROMedSEuclideanTransformation2DRobustEstimator();
             default -> new RANSACEuclideanTransformation2DRobustEstimator();
         };
     }
 
     /**
      * Creates an Euclidean 2D transformation estimator based on 2D point
      * correspondences and using provided estimator method.
      *
      * @param inputPoints  list of input points to be used to estimate an
      *                     Euclidean 2D transformation.
      * @param outputPoints list of output points to be used to estimate an
      *                     Euclidean 2D transformation.
      * @param method       method of a robust estimator algorithm to estimate the best
      *                     Euclidean 2D transformation.
      * @return an instance of Euclidean 2D transformation estimator.
      * @throws IllegalArgumentException if provided lists of points don't have
      *                                  the same size or their size is smaller than MINIMUM_SIZE.
      */
     public static EuclideanTransformation2DRobustEstimator create(
             final List<Point2D> inputPoints, final List<Point2D> outputPoints, final RobustEstimatorMethod method) {
         return switch (method) {
             case LMEDS -> new LMedSEuclideanTransformation2DRobustEstimator(inputPoints, outputPoints);
             case MSAC -> new MSACEuclideanTransformation2DRobustEstimator(inputPoints, outputPoints);
             case PROSAC -> new PROSACEuclideanTransformation2DRobustEstimator(inputPoints, outputPoints);
             case PROMEDS -> new PROMedSEuclideanTransformation2DRobustEstimator(inputPoints, outputPoints);
             default -> new RANSACEuclideanTransformation2DRobustEstimator(inputPoints, outputPoints);
         };
     }
 
     /**
      * Creates an Euclidean 2D transformation estimator based on 2D point
      * correspondences and using provided robust estimator method.
      *
      * @param listener listener to be notified of events such as when estimation
      *                 starts, ends or its progress significantly changes.
      * @param method   method of a robust estimator algorithm to estimate the best
      *                 Euclidean 2D transformation.
      * @return an instance of Euclidean 2D transformation estimator.
      */
     public static EuclideanTransformation2DRobustEstimator create(
             final EuclideanTransformation2DRobustEstimatorListener listener, final RobustEstimatorMethod method) {
         return switch (method) {
             case LMEDS -> new LMedSEuclideanTransformation2DRobustEstimator(listener);
             case MSAC -> new MSACEuclideanTransformation2DRobustEstimator(listener);
             case PROSAC -> new PROSACEuclideanTransformation2DRobustEstimator(listener);
             case PROMEDS -> new PROMedSEuclideanTransformation2DRobustEstimator(listener);
             default -> new RANSACEuclideanTransformation2DRobustEstimator(listener);
         };
     }
 
     /**
      * Creates an Euclidean 2D transformation estimator based on 2D point
      * correspondences and using provided robust estimator method.
      *
      * @param listener     listener to be notified of events such as when estimation
      *                     starts, ends or its progress significantly changes.
      * @param inputPoints  list of input points to be used to estimate an
      *                     Euclidean 2D transformation.
      * @param outputPoints list of output points to be used to estimate an
      *                     Euclidean 2D transformation.
      * @param method       method of a robust estimator algorithm to estimate the best
      *                     Euclidean 2D transformation.
      * @return an instance of Euclidean 2D transformation estimator.
      * @throws IllegalArgumentException if provided lists of points don't have
      *                                  the same size or their size is smaller than MINIMUM_SIZE.
      */
     public static EuclideanTransformation2DRobustEstimator create(
             final EuclideanTransformation2DRobustEstimatorListener listener, final List<Point2D> inputPoints,
             final List<Point2D> outputPoints, final RobustEstimatorMethod method) {
         return switch (method) {
             case LMEDS -> new LMedSEuclideanTransformation2DRobustEstimator(listener, inputPoints, outputPoints);
             case MSAC -> new MSACEuclideanTransformation2DRobustEstimator(listener, inputPoints, outputPoints);
             case PROSAC -> new PROSACEuclideanTransformation2DRobustEstimator(listener, inputPoints, outputPoints);
             case PROMEDS -> new PROMedSEuclideanTransformation2DRobustEstimator(listener, inputPoints, outputPoints);
             default -> new RANSACEuclideanTransformation2DRobustEstimator(listener, inputPoints, outputPoints);
         };
     }
 
     /**
      * Creates an Euclidean 2D transformation estimator based on 2D point
      * correspondences and using provided robust estimator method.
      *
      * @param qualityScores quality scores corresponding to each pair of matched
      *                      points.
      * @param method        method of a robust estimator algorithm to estimate the best
      *                      Euclidean 2D transformation.
      * @return an instance of Euclidean 2D transformation estimator.
      * @throws IllegalArgumentException if provided quality scores length is
      *                                  smaller than MINIMUM_SIZE (i.e. 3 matched points).
      */
     public static EuclideanTransformation2DRobustEstimator create(
             final double[] qualityScores, final RobustEstimatorMethod method) {
         return switch (method) {
             case LMEDS -> new LMedSEuclideanTransformation2DRobustEstimator();
             case MSAC -> new MSACEuclideanTransformation2DRobustEstimator();
             case PROSAC -> new PROSACEuclideanTransformation2DRobustEstimator(qualityScores);
             case PROMEDS -> new PROMedSEuclideanTransformation2DRobustEstimator(qualityScores);
             default -> new RANSACEuclideanTransformation2DRobustEstimator();
         };
     }
 
     /**
      * Creates an Euclidean 2D transformation estimator based on 2D point
      * correspondences and using provided robust estimator method.
      *
      * @param inputPoints   list of input points to be used to estimate an
      *                      Euclidean 2D transformation.
      * @param outputPoints  list of output points to be used to estimate an
      *                      Euclidean 2D transformation.
      * @param qualityScores quality scores corresponding to each pair of matched
      *                      points.
      * @param method        method of a robust estimator algorithm to estimate the best
      *                      Euclidean 2D transformation.
      * @return an instance of Euclidean 2D transformation estimator.
      * @throws IllegalArgumentException if provided lists of points or scores
      *                                  don't have the same size or their size is smaller than MINIMUM_SIZE.
      */
     public static EuclideanTransformation2DRobustEstimator create(
             final List<Point2D> inputPoints, final List<Point2D> outputPoints, final double[] qualityScores,
             final RobustEstimatorMethod method) {
         return switch (method) {
             case LMEDS -> new LMedSEuclideanTransformation2DRobustEstimator(inputPoints, outputPoints);
             case MSAC -> new MSACEuclideanTransformation2DRobustEstimator(inputPoints, outputPoints);
             case PROSAC -> new PROSACEuclideanTransformation2DRobustEstimator(inputPoints, outputPoints, qualityScores);
             case PROMEDS -> new PROMedSEuclideanTransformation2DRobustEstimator(
                     inputPoints, outputPoints, qualityScores);
             default -> new RANSACEuclideanTransformation2DRobustEstimator(inputPoints, outputPoints);
         };
     }
 
     /**
      * Creates an Euclidean 2D transformation estimator based on 2D point
      * correspondences and using provided robust estimator method.
      *
      * @param listener      listener to be notified of events such as when estimation
      *                      starts, ends or its progress significantly changes.
      * @param qualityScores quality scores corresponding to each pair of matched
      *                      points.
      * @param method        method of a robust estimator algorithm to estimate the best
      *                      Euclidean 2D transformation.
      * @return an instance of Euclidean 2D transformation estimator.
      * @throws IllegalArgumentException if provided quality scores don't have
      *                                  the required minimum size.
      */
     public static EuclideanTransformation2DRobustEstimator create(
             final EuclideanTransformation2DRobustEstimatorListener listener, final double[] qualityScores,
             final RobustEstimatorMethod method) {
         return switch (method) {
             case LMEDS -> new LMedSEuclideanTransformation2DRobustEstimator(listener);
             case MSAC -> new MSACEuclideanTransformation2DRobustEstimator(listener);
             case PROSAC -> new PROSACEuclideanTransformation2DRobustEstimator(listener, qualityScores);
             case PROMEDS -> new PROMedSEuclideanTransformation2DRobustEstimator(listener, qualityScores);
             default -> new RANSACEuclideanTransformation2DRobustEstimator(listener);
         };
     }
 
     /**
      * Creates an Euclidean 2D transformation estimator based on 2D point
      * correspondences and using provided robust estimator method.
      *
      * @param listener      listener to be notified of events such as when estimation
      *                      starts, ends or its progress significantly changes.
      * @param inputPoints   list of input points to be used to estimate an
      *                      Euclidean 2D transformation.
      * @param outputPoints  list of output points to be used to estimate an
      *                      Euclidean 2D transformation.
      * @param qualityScores quality scores corresponding to each pair of matched
      *                      points.
      * @param method        method of a robust estimator algorithm to estimate the best
      *                      Euclidean 2D transformation.
      * @return an instance of Euclidean 2D transformation estimator.
      * @throws IllegalArgumentException if provided lists of points don't have
      *                                  the same size of their size is smaller than MINIMUM_SIZE.
      */
     public static EuclideanTransformation2DRobustEstimator create(
             final EuclideanTransformation2DRobustEstimatorListener listener, final List<Point2D> inputPoints,
             final List<Point2D> outputPoints, final double[] qualityScores, final RobustEstimatorMethod method) {
         return switch (method) {
             case LMEDS -> new LMedSEuclideanTransformation2DRobustEstimator(listener, inputPoints, outputPoints);
             case MSAC -> new MSACEuclideanTransformation2DRobustEstimator(listener, inputPoints, outputPoints);
             case PROSAC -> new PROSACEuclideanTransformation2DRobustEstimator(
                     listener, inputPoints, outputPoints, qualityScores);
             case PROMEDS -> new PROMedSEuclideanTransformation2DRobustEstimator(
                     listener, inputPoints, outputPoints, qualityScores);
             default -> new RANSACEuclideanTransformation2DRobustEstimator(listener, inputPoints, outputPoints);
         };
     }
 
     /**
      * Creates an Euclidean 2D transformation estimator based on 2D point
      * correspondences and using provided robust estimator method.
      *
      * @param weakMinimumSizeAllowed true allows 2 points, false requires 3.
      * @param method                 method of a robust estimator algorithm to estimate
      *                               the best Euclidean 2D transformation.
      * @return an instance of Euclidean 2D transformation estimator.
      */
     public static EuclideanTransformation2DRobustEstimator create(
             final boolean weakMinimumSizeAllowed, final RobustEstimatorMethod method) {
         return switch (method) {
             case LMEDS -> new LMedSEuclideanTransformation2DRobustEstimator(weakMinimumSizeAllowed);
             case MSAC -> new MSACEuclideanTransformation2DRobustEstimator(weakMinimumSizeAllowed);
             case PROSAC -> new PROSACEuclideanTransformation2DRobustEstimator(weakMinimumSizeAllowed);
             case PROMEDS -> new PROMedSEuclideanTransformation2DRobustEstimator(weakMinimumSizeAllowed);
             default -> new RANSACEuclideanTransformation2DRobustEstimator(weakMinimumSizeAllowed);
         };
     }
 
     /**
      * Creates an Euclidean 2D transformation estimator based on 2D point
      * correspondences and using provided estimator method.
      *
      * @param inputPoints            list of input points to be used to estimate an
      *                               Euclidean 2D transformation.
      * @param outputPoints           list of output points to be used to estimate an
      *                               Euclidean 2D transformation.
      * @param weakMinimumSizeAllowed true allows 2 points, false requires 3.
      * @param method                 method of a robust estimator algorithm to estimate the best
      *                               Euclidean 2D transformation.
      * @return an instance of Euclidean 2D transformation estimator.
      * @throws IllegalArgumentException if provided lists of points don't have
      *                                  the same size or their size is smaller than MINIMUM_SIZE.
      */
     public static EuclideanTransformation2DRobustEstimator create(
             final List<Point2D> inputPoints, final List<Point2D> outputPoints, final boolean weakMinimumSizeAllowed,
             final RobustEstimatorMethod method) {
         return switch (method) {
             case LMEDS -> new LMedSEuclideanTransformation2DRobustEstimator(
                     inputPoints, outputPoints, weakMinimumSizeAllowed);
             case MSAC -> new MSACEuclideanTransformation2DRobustEstimator(
                     inputPoints, outputPoints, weakMinimumSizeAllowed);
             case PROSAC -> new PROSACEuclideanTransformation2DRobustEstimator(
                     inputPoints, outputPoints, weakMinimumSizeAllowed);
             case PROMEDS -> new PROMedSEuclideanTransformation2DRobustEstimator(
                     inputPoints, outputPoints, weakMinimumSizeAllowed);
             default -> new RANSACEuclideanTransformation2DRobustEstimator(
                     inputPoints, outputPoints, weakMinimumSizeAllowed);
         };
     }
 
     /**
      * Creates an Euclidean 2D transformation estimator based on 2D point
      * correspondences and using provided robust estimator method.
      *
      * @param listener               listener to be notified of events such as when estimation
      *                               starts, ends or its progress significantly changes.
      * @param weakMinimumSizeAllowed true allows 2 points, false requires 3.
      * @param method                 method of a robust estimator algorithm to estimate the best
      *                               Euclidean 2D transformation.
      * @return an instance of Euclidean 2D transformation estimator.
      */
     public static EuclideanTransformation2DRobustEstimator create(
             final EuclideanTransformation2DRobustEstimatorListener listener, final boolean weakMinimumSizeAllowed,
             final RobustEstimatorMethod method) {
         return switch (method) {
             case LMEDS -> new LMedSEuclideanTransformation2DRobustEstimator(listener, weakMinimumSizeAllowed);
             case MSAC -> new MSACEuclideanTransformation2DRobustEstimator(listener, weakMinimumSizeAllowed);
             case PROSAC -> new PROSACEuclideanTransformation2DRobustEstimator(listener, weakMinimumSizeAllowed);
             case PROMEDS -> new PROMedSEuclideanTransformation2DRobustEstimator(listener, weakMinimumSizeAllowed);
             default -> new RANSACEuclideanTransformation2DRobustEstimator(listener, weakMinimumSizeAllowed);
         };
     }
 
     /**
      * Creates an Euclidean 2D transformation estimator based on 2D point
      * correspondences and using provided robust estimator method.
      *
      * @param listener               listener to be notified of events such as when estimation
      *                               starts, ends or its progress significantly changes.
      * @param inputPoints            list of input points to be used to estimate an
      *                               Euclidean 2D transformation.
      * @param outputPoints           list of output points to be used to estimate an
      *                               Euclidean 2D transformation.
      * @param weakMinimumSizeAllowed true allows 2 points, false requires 3.
      * @param method                 method of a robust estimator algorithm to estimate the best
      *                               Euclidean 2D transformation.
      * @return an instance of Euclidean 2D transformation estimator.
      * @throws IllegalArgumentException if provided lists of points don't have
      *                                  the same size or their size is smaller than MINIMUM_SIZE.
      */
     public static EuclideanTransformation2DRobustEstimator create(
             final EuclideanTransformation2DRobustEstimatorListener listener, final List<Point2D> inputPoints,
             final List<Point2D> outputPoints, final boolean weakMinimumSizeAllowed,
             final RobustEstimatorMethod method) {
         return switch (method) {
             case LMEDS -> new LMedSEuclideanTransformation2DRobustEstimator(
                     listener, inputPoints, outputPoints, weakMinimumSizeAllowed);
             case MSAC -> new MSACEuclideanTransformation2DRobustEstimator(
                     listener, inputPoints, outputPoints, weakMinimumSizeAllowed);
             case PROSAC -> new PROSACEuclideanTransformation2DRobustEstimator(
                     listener, inputPoints, outputPoints, weakMinimumSizeAllowed);
             case PROMEDS -> new PROMedSEuclideanTransformation2DRobustEstimator(
                     listener, inputPoints, outputPoints, weakMinimumSizeAllowed);
             default -> new RANSACEuclideanTransformation2DRobustEstimator(
                     listener, inputPoints, outputPoints, weakMinimumSizeAllowed);
         };
     }
 
     /**
      * Creates an Euclidean 2D transformation estimator based on 2D point
      * correspondences and using provided robust estimator method.
      *
      * @param qualityScores          quality scores corresponding to each pair of matched
      *                               points.
      * @param weakMinimumSizeAllowed true allows 2 points, false requires 3.
      * @param method                 method of a robust estimator algorithm to estimate the best
      *                               Euclidean 2D transformation.
      * @return an instance of Euclidean 2D transformation estimator.
      * @throws IllegalArgumentException if provided quality scores length is
      *                                  smaller than MINIMUM_SIZE (i.e. 3 matched points).
      */
     public static EuclideanTransformation2DRobustEstimator create(
             final double[] qualityScores, final boolean weakMinimumSizeAllowed, final RobustEstimatorMethod method) {
         return switch (method) {
             case LMEDS -> new LMedSEuclideanTransformation2DRobustEstimator(weakMinimumSizeAllowed);
             case MSAC -> new MSACEuclideanTransformation2DRobustEstimator(weakMinimumSizeAllowed);
             case PROSAC -> new PROSACEuclideanTransformation2DRobustEstimator(qualityScores, weakMinimumSizeAllowed);
             case PROMEDS -> new PROMedSEuclideanTransformation2DRobustEstimator(qualityScores, weakMinimumSizeAllowed);
             default -> new RANSACEuclideanTransformation2DRobustEstimator(weakMinimumSizeAllowed);
         };
     }
 
     /**
      * Creates an Euclidean 2D transformation estimator based on 2D point
      * correspondences and using provided robust estimator method.
      *
      * @param inputPoints            list of input points to be used to estimate an
      *                               Euclidean 2D transformation.
      * @param outputPoints           list of output points to be used to estimate an
      *                               Euclidean 2D transformation.
      * @param qualityScores          quality scores corresponding to each pair of matched
      *                               points.
      * @param weakMinimumSizeAllowed true allows 2 points, false requires 3.
      * @param method                 method of a robust estimator algorithm to estimate the best
      *                               Euclidean 2D transformation.
      * @return an instance of Euclidean 2D transformation estimator.
      * @throws IllegalArgumentException if provided lists of points or scores
      *                                  don't have the same size or their size is smaller than MINIMUM_SIZE.
      */
     public static EuclideanTransformation2DRobustEstimator create(
             final List<Point2D> inputPoints, final List<Point2D> outputPoints, final double[] qualityScores,
             final boolean weakMinimumSizeAllowed, final RobustEstimatorMethod method) {
         return switch (method) {
             case LMEDS -> new LMedSEuclideanTransformation2DRobustEstimator(
                     inputPoints, outputPoints, weakMinimumSizeAllowed);
             case MSAC -> new MSACEuclideanTransformation2DRobustEstimator(
                     inputPoints, outputPoints, weakMinimumSizeAllowed);
             case PROSAC -> new PROSACEuclideanTransformation2DRobustEstimator(
                     inputPoints, outputPoints, qualityScores, weakMinimumSizeAllowed);
             case PROMEDS -> new PROMedSEuclideanTransformation2DRobustEstimator(
                     inputPoints, outputPoints, qualityScores, weakMinimumSizeAllowed);
             default -> new RANSACEuclideanTransformation2DRobustEstimator(
                     inputPoints, outputPoints, weakMinimumSizeAllowed);
         };
     }
 
     /**
      * Creates an Euclidean 2D transformation estimator based on 2D point
      * correspondences and using provided robust estimator method.
      *
      * @param listener               listener to be notified of events such as when estimation
      *                               starts, ends or its progress significantly changes.
      * @param qualityScores          quality scores corresponding to each pair of matched
      *                               points.
      * @param weakMinimumSizeAllowed true allows 2 points, false requires 3.
      * @param method                 method of a robust estimator algorithm to estimate the best
      *                               Euclidean 2D transformation.
      * @return an instance of Euclidean 2D transformation estimator.
      * @throws IllegalArgumentException if provided quality scores don't have
      *                                  the required minimum size.
      */
     public static EuclideanTransformation2DRobustEstimator create(
             final EuclideanTransformation2DRobustEstimatorListener listener, final double[] qualityScores,
             final boolean weakMinimumSizeAllowed, final RobustEstimatorMethod method) {
         return switch (method) {
             case LMEDS -> new LMedSEuclideanTransformation2DRobustEstimator(listener, weakMinimumSizeAllowed);
             case MSAC -> new MSACEuclideanTransformation2DRobustEstimator(listener, weakMinimumSizeAllowed);
             case PROSAC -> new PROSACEuclideanTransformation2DRobustEstimator(
                     listener, qualityScores, weakMinimumSizeAllowed);
             case PROMEDS -> new PROMedSEuclideanTransformation2DRobustEstimator(
                     listener, qualityScores, weakMinimumSizeAllowed);
             default -> new RANSACEuclideanTransformation2DRobustEstimator(listener, weakMinimumSizeAllowed);
         };
     }
 
     /**
      * Creates an Euclidean 2D transformation estimator based on 2D point
      * correspondences and using provided robust estimator method.
      *
      * @param listener               listener to be notified of events such as when estimation
      *                               starts, ends or its progress significantly changes.
      * @param inputPoints            list of input points to be used to estimate an
      *                               Euclidean 2D transformation.
      * @param outputPoints           list of output points to be used to estimate an
      *                               Euclidean 2D transformation.
      * @param qualityScores          quality scores corresponding to each pair of matched
      *                               points.
      * @param weakMinimumSizeAllowed true allows 2 points, false requires 3.
      * @param method                 method of a robust estimator algorithm to estimate the best
      *                               Euclidean 2D transformation.
      * @return an instance of Euclidean 2D transformation estimator.
      * @throws IllegalArgumentException if provided lists of points don't have
      *                                  the same size of their size is smaller than MINIMUM_SIZE.
      */
     public static EuclideanTransformation2DRobustEstimator create(
             final EuclideanTransformation2DRobustEstimatorListener listener, final List<Point2D> inputPoints,
             final List<Point2D> outputPoints, final double[] qualityScores, final boolean weakMinimumSizeAllowed,
             final RobustEstimatorMethod method) {
         return switch (method) {
             case LMEDS -> new LMedSEuclideanTransformation2DRobustEstimator(
                     listener, inputPoints, outputPoints, weakMinimumSizeAllowed);
             case MSAC -> new MSACEuclideanTransformation2DRobustEstimator(
                     listener, inputPoints, outputPoints, weakMinimumSizeAllowed);
             case PROSAC -> new PROSACEuclideanTransformation2DRobustEstimator(
                     listener, inputPoints, outputPoints, qualityScores, weakMinimumSizeAllowed);
             case PROMEDS -> new PROMedSEuclideanTransformation2DRobustEstimator(
                     listener, inputPoints, outputPoints, qualityScores, weakMinimumSizeAllowed);
             default -> new RANSACEuclideanTransformation2DRobustEstimator(
                     listener, inputPoints, outputPoints, weakMinimumSizeAllowed);
         };
     }
 
 
     /**
      * Creates an Euclidean 2D transformation estimator based on 2D point
      * correspondences and using default robust estimator method.
      *
      * @return an instance of Euclidean 2D transformation estimator.
      */
     public static EuclideanTransformation2DRobustEstimator create() {
         return create(DEFAULT_ROBUST_METHOD);
     }
 
     /**
      * Creates an Euclidean 2D transformation estimator based on 2D point
      * correspondences and using default robust estimator method.
      *
      * @param inputPoints  list of input points to be used to estimate an
      *                     Euclidean 2D transformation.
      * @param outputPoints list of output points to be used to estimate an
      *                     Euclidean 2D transformation.
      * @return an instance of Euclidean 2D transformation estimator.
      * @throws IllegalArgumentException if provided lists of points don't have
      *                                  the same size of their size is smaller than MINIMUM_SIZE.
      */
     public static EuclideanTransformation2DRobustEstimator create(
             final List<Point2D> inputPoints, final List<Point2D> outputPoints) {
         return create(inputPoints, outputPoints, DEFAULT_ROBUST_METHOD);
     }
 
     /**
      * Creates an Euclidean 2D transformation estimator based on 2D point
      * correspondences and using default robust estimator method.
      *
      * @param listener listener to be notified of events such as when estimation
      *                 starts, ends or its progress significantly changes.
      * @return an instance of Euclidean 2D transformation estimator.
      */
     public static EuclideanTransformation2DRobustEstimator create(
             final EuclideanTransformation2DRobustEstimatorListener listener) {
         return create(listener, DEFAULT_ROBUST_METHOD);
     }
 
     /**
      * Creates an Euclidean 2D transformation estimator based on 2D point
      * correspondences and using default robust estimator method.
      *
      * @param listener     listener to be notified of events such as when estimation
      *                     starts, ends or its progress significantly changes.
      * @param inputPoints  list of input points to be used to estimate an
      *                     Euclidean 2D transformation.
      * @param outputPoints list of output points to be used to estimate an
      *                     Euclidean 2D transformation.
      * @return an instance of Euclidean 2D transformation estimator.
      * @throws IllegalArgumentException if provided lists of points don't have
      *                                  the same size or their size is smaller than MINIMUM_SIZE.
      */
     public static EuclideanTransformation2DRobustEstimator create(
             final EuclideanTransformation2DRobustEstimatorListener listener, final List<Point2D> inputPoints,
             final List<Point2D> outputPoints) {
         return create(listener, inputPoints, outputPoints, DEFAULT_ROBUST_METHOD);
     }
 
     /**
      * Creates an Euclidean 2D transformation estimator based on 2D point
      * correspondences and using default robust estimator method.
      *
      * @param qualityScores quality scores corresponding to each pair of matched
      *                      points.
      * @return an instance of Euclidean 2D transformation estimator.
      */
     public static EuclideanTransformation2DRobustEstimator create(final double[] qualityScores) {
         return create(qualityScores, DEFAULT_ROBUST_METHOD);
     }
 
     /**
      * Creates an Euclidean 2D transformation estimator based on 2D point
      * correspondences and using default robust estimator method.
      *
      * @param inputPoints   list of input points to be used to estimate an
      *                      Euclidean 2D transformation.
      * @param outputPoints  list of output points ot be used to estimate an
      *                      Euclidean 2D transformation.
      * @param qualityScores quality scores corresponding to each pair of points.
      * @return an instance of Euclidean 2D transformation estimator.
      * @throws IllegalArgumentException if provided lists of points don't have
      *                                  the same size or their size is smaller than MINIMUM_SIZE.
      */
     public static EuclideanTransformation2DRobustEstimator create(
             final List<Point2D> inputPoints, final List<Point2D> outputPoints, final double[] qualityScores) {
         return create(inputPoints, outputPoints, qualityScores, DEFAULT_ROBUST_METHOD);
     }
 
     /**
      * Creates an Euclidean 2D transformation estimator based on 2D point
      * correspondences and using default robust estimator method.
      *
      * @param listener      listener to be notified of events such as when estimation
      *                      starts, ends or its progress significantly changes.
      * @param qualityScores quality scores corresponding to each pair of matched
      *                      points.
      * @return an instance of Euclidean 2D transformation estimator.
      */
     public static EuclideanTransformation2DRobustEstimator create(
             final EuclideanTransformation2DRobustEstimatorListener listener, final double[] qualityScores) {
         return create(listener, qualityScores, DEFAULT_ROBUST_METHOD);
     }
 
     /**
      * Creates an Euclidean 2D transformation estimator based on 2D point
      * correspondences and using default robust estimator method.
      *
      * @param listener      listener to be notified of events such as when estimation
      *                      starts, ends or its progress significantly changes.
      * @param inputPoints   list of input points to be used to estimate an
      *                      Euclidean 2D transformation.
      * @param outputPoints  list of output points ot be used to estimate an
      *                      Euclidean 2D transformation.
      * @param qualityScores quality scores corresponding to each pair of matched
      *                      points.
      * @return an instance of Euclidean 2D transformation estimator.
      * @throws IllegalArgumentException if provided lists of points don't have
      *                                  the same size or their size is smaller than MINIMUM_SIZE.
      */
     public static EuclideanTransformation2DRobustEstimator create(
             final EuclideanTransformation2DRobustEstimatorListener listener, final List<Point2D> inputPoints,
             final List<Point2D> outputPoints, final double[] qualityScores) {
         return create(listener, inputPoints, outputPoints, qualityScores, DEFAULT_ROBUST_METHOD);
     }
 
     /**
      * Creates an Euclidean 2D transformation estimator based on 2D point
      * correspondences and using default robust estimator method.
      *
      * @param weakMinimumSizeAllowed true allows 2 points, false requires 3.
      * @return an instance of Euclidean 2D transformation estimator.
      */
     public static EuclideanTransformation2DRobustEstimator create(final boolean weakMinimumSizeAllowed) {
         return create(weakMinimumSizeAllowed, DEFAULT_ROBUST_METHOD);
     }
 
     /**
      * Creates an Euclidean 2D transformation estimator based on 2D point
      * correspondences and using default robust estimator method.
      *
      * @param inputPoints            list of input points to be used to estimate an
      *                               Euclidean 2D transformation.
      * @param outputPoints           list of output points to be used to estimate an
      *                               Euclidean 2D transformation.
      * @param weakMinimumSizeAllowed true allows 2 points, false requires 3.
      * @return an instance of Euclidean 2D transformation estimator.
      * @throws IllegalArgumentException if provided lists of points don't have
      *                                  the same size of their size is smaller than MINIMUM_SIZE.
      */
     public static EuclideanTransformation2DRobustEstimator create(
             final List<Point2D> inputPoints, final List<Point2D> outputPoints, final boolean weakMinimumSizeAllowed) {
         return create(inputPoints, outputPoints, weakMinimumSizeAllowed, DEFAULT_ROBUST_METHOD);
     }
 
     /**
      * Creates an Euclidean 2D transformation estimator based on 2D point
      * correspondences and using default robust estimator method.
      *
      * @param listener               listener to be notified of events such as when estimation
      *                               starts, ends or its progress significantly changes.
      * @param weakMinimumSizeAllowed true allows 2 points, false requires 3.
      * @return an instance of Euclidean 2D transformation estimator.
      */
     public static EuclideanTransformation2DRobustEstimator create(
             final EuclideanTransformation2DRobustEstimatorListener listener, final boolean weakMinimumSizeAllowed) {
         return create(listener, weakMinimumSizeAllowed, DEFAULT_ROBUST_METHOD);
     }
 
     /**
      * Creates an Euclidean 2D transformation estimator based on 2D point
      * correspondences and using default robust estimator method.
      *
      * @param listener               listener to be notified of events such as when estimation
      *                               starts, ends or its progress significantly changes.
      * @param inputPoints            list of input points to be used to estimate an
      *                               Euclidean 2D transformation.
      * @param outputPoints           list of output points to be used to estimate an
      *                               Euclidean 2D transformation.
      * @param weakMinimumSizeAllowed true allows 2 points, false requires 3.
      * @return an instance of Euclidean 2D transformation estimator.
      * @throws IllegalArgumentException if provided lists of points don't have
      *                                  the same size or their size is smaller than MINIMUM_SIZE.
      */
     public static EuclideanTransformation2DRobustEstimator create(
             final EuclideanTransformation2DRobustEstimatorListener listener, final List<Point2D> inputPoints,
             final List<Point2D> outputPoints, final boolean weakMinimumSizeAllowed) {
         return create(listener, inputPoints, outputPoints, weakMinimumSizeAllowed, DEFAULT_ROBUST_METHOD);
     }
 
     /**
      * Creates an Euclidean 2D transformation estimator based on 2D point
      * correspondences and using default robust estimator method.
      *
      * @param qualityScores          quality scores corresponding to each pair of matched
      *                               points.
      * @param weakMinimumSizeAllowed true allows 2 points, false requires 3.
      * @return an instance of Euclidean 2D transformation estimator.
      */
     public static EuclideanTransformation2DRobustEstimator create(
             final double[] qualityScores, final boolean weakMinimumSizeAllowed) {
         return create(qualityScores, weakMinimumSizeAllowed, DEFAULT_ROBUST_METHOD);
     }
 
     /**
      * Creates an Euclidean 2D transformation estimator based on 2D point
      * correspondences and using default robust estimator method.
      *
      * @param inputPoints            list of input points to be used to estimate an
      *                               Euclidean 2D transformation.
      * @param outputPoints           list of output points ot be used to estimate an
      *                               Euclidean 2D transformation.
      * @param qualityScores          quality scores corresponding to each pair of points.
      * @param weakMinimumSizeAllowed true allows 2 points, false requires 3.
      * @return an instance of Euclidean 2D transformation estimator.
      * @throws IllegalArgumentException if provided lists of points don't have
      *                                  the same size or their size is smaller than MINIMUM_SIZE.
      */
     public static EuclideanTransformation2DRobustEstimator create(
             final List<Point2D> inputPoints, final List<Point2D> outputPoints, final double[] qualityScores,
             final boolean weakMinimumSizeAllowed) {
         return create(inputPoints, outputPoints, qualityScores, weakMinimumSizeAllowed, DEFAULT_ROBUST_METHOD);
     }
 
     /**
      * Creates an Euclidean 2D transformation estimator based on 2D point
      * correspondences and using default robust estimator method.
      *
      * @param listener               listener to be notified of events such as when estimation
      *                               starts, ends or its progress significantly changes.
      * @param qualityScores          quality scores corresponding to each pair of matched
      *                               points.
      * @param weakMinimumSizeAllowed true allows 2 points, false requires 3.
      * @return an instance of Euclidean 2D transformation estimator.
      */
     public static EuclideanTransformation2DRobustEstimator create(
             final EuclideanTransformation2DRobustEstimatorListener listener, final double[] qualityScores,
             final boolean weakMinimumSizeAllowed) {
         return create(listener, qualityScores, weakMinimumSizeAllowed, DEFAULT_ROBUST_METHOD);
     }
 
     /**
      * Creates an Euclidean 2D transformation estimator based on 2D point
      * correspondences and using default robust estimator method.
      *
      * @param listener               listener to be notified of events such as when estimation
      *                               starts, ends or its progress significantly changes.
      * @param inputPoints            list of input points to be used to estimate an
      *                               Euclidean 2D transformation.
      * @param outputPoints           list of output points ot be used to estimate an
      *                               Euclidean 2D transformation.
      * @param qualityScores          quality scores corresponding to each pair of matched
      *                               points.
      * @param weakMinimumSizeAllowed true allows 2 points, false requires 3.
      * @return an instance of Euclidean 2D transformation estimator.
      * @throws IllegalArgumentException if provided lists of points don't have
      *                                  the same size or their size is smaller than MINIMUM_SIZE.
      */
     public static EuclideanTransformation2DRobustEstimator create(
             final EuclideanTransformation2DRobustEstimatorListener listener, final List<Point2D> inputPoints,
             final List<Point2D> outputPoints, final double[] qualityScores, final boolean weakMinimumSizeAllowed) {
         return create(listener, inputPoints, outputPoints, qualityScores, weakMinimumSizeAllowed,
                 DEFAULT_ROBUST_METHOD);
     }
 
 
     /**
      * Internal method to set lists of points to be used to estimate an
      * Euclidean 2D transformation.
      * This method does not check whether estimator is locked or not.
      *
      * @param inputPoints  list of input points to be used to estimate an
      *                     Euclidean 2D transformation.
      * @param outputPoints list of output points to be used to estimate an
      *                     Euclidean 2D transformation.
      * @throws IllegalArgumentException if provided lists of points don't have
      *                                  the same size or their size is smaller than MINIMUM_SIZE.
      */
     private void internalSetPoints(final List<Point2D> inputPoints, final List<Point2D> outputPoints) {
         if (inputPoints.size() < getMinimumPoints()) {
             throw new IllegalArgumentException();
         }
         if (inputPoints.size() != outputPoints.size()) {
             throw new IllegalArgumentException();
         }
         this.inputPoints = inputPoints;
         this.outputPoints = outputPoints;
     }
 
     /**
      * Attempts to refine provided solution if refinement is requested.
      * This method returns a refined solution of the same provided solution
      * if refinement is not requested or has failed.
      * If refinement is enabled, and it is requested to keep covariance, this
      * method will also keep covariance of refined transformation.
      *
      * @param transformation transformation estimated by a robust estimator
      *                       without refinement.
      * @return solution after refinement (if requested) or the provided
      * non-refined solution if not requested or refinement failed.
      */
     protected EuclideanTransformation2D attemptRefine(final EuclideanTransformation2D transformation) {
         if (refineResult) {
             final var refiner = new EuclideanTransformation2DRefiner(transformation, keepCovariance, getInliersData(),
                     inputPoints, outputPoints, getRefinementStandardDeviation());
 
             try {
                 final var result = new EuclideanTransformation2D();
                 final var improved = refiner.refine(result);
 
                 if (keepCovariance) {
                     // keep covariance
                     covariance = refiner.getCovariance();
                 }
 
                 return improved ? result : transformation;
             } catch (final Exception e) {
                 // refinement failed, so we return input value
                 return transformation;
             }
         } else {
             return transformation;
         }
     }
 
     /**
      * Gets standard deviation used for Levenberg-Marquardt fitting during
      * refinement.
      * Returned value gives an indication of how much variance each residual
      * has.
      * Typically, this value is related to the threshold used on each robust
      * estimation, since residuals of found inliers are within the range of
      * such threshold.
      *
      * @return standard deviation used for refinement.
      */
     protected abstract double getRefinementStandardDeviation();
 }