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1   /*
2    * Copyright (C) 2015 Alberto Irurueta Carro (alberto@irurueta.com)
3    *
4    * Licensed under the Apache License, Version 2.0 (the "License");
5    * you may not use this file except in compliance with the License.
6    * You may obtain a copy of the License at
7    *
8    *         http://www.apache.org/licenses/LICENSE-2.0
9    *
10   * Unless required by applicable law or agreed to in writing, software
11   * distributed under the License is distributed on an "AS IS" BASIS,
12   * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
13   * See the License for the specific language governing permissions and
14   * limitations under the License.
15   */
16  package com.irurueta.geometry.estimators;
17  
18  import com.irurueta.geometry.Circle;
19  import com.irurueta.geometry.Point2D;
20  import com.irurueta.numerical.robust.RobustEstimatorException;
21  import com.irurueta.numerical.robust.RobustEstimatorMethod;
22  
23  import java.util.List;
24  
25  /**
26   * This is an abstract class for algorithms to robustly find the best circle
27   * that fits in a collection of 2D points.
28   * Implementations of this class should be able to detect and discard outliers
29   * in order to find the best solution.
30   */
31  @SuppressWarnings("DuplicatedCode")
32  public abstract class CircleRobustEstimator {
33      /**
34       * Minimum number of 2D points required to estimate a circle.
35       */
36      public static final int MINIMUM_SIZE = 3;
37  
38      /**
39       * Default amount of progress variation before notifying a change in
40       * estimation progress. By default, this is set to 5%.
41       */
42      public static final float DEFAULT_PROGRESS_DELTA = 0.05f;
43  
44      /**
45       * Minimum allowed value for progress delta.
46       */
47      public static final float MIN_PROGRESS_DELTA = 0.0f;
48  
49      /**
50       * Maximum allowed value for progress delta.
51       */
52      public static final float MAX_PROGRESS_DELTA = 1.0f;
53  
54      /**
55       * Constant defining default confidence of the estimated result, which is
56       * 99%. This means that with a probability of 99% estimation will be
57       * accurate because chosen sub-samples will be inliers.
58       */
59      public static final double DEFAULT_CONFIDENCE = 0.99;
60  
61      /**
62       * Default maximum allowed number of iterations.
63       */
64      public static final int DEFAULT_MAX_ITERATIONS = 5000;
65  
66      /**
67       * Minimum allowed confidence value.
68       */
69      public static final double MIN_CONFIDENCE = 0.0;
70  
71      /**
72       * Maximum allowed confidence value.
73       */
74      public static final double MAX_CONFIDENCE = 1.0;
75  
76      /**
77       * Minimum allowed number of iterations.
78       */
79      public static final int MIN_ITERATIONS = 1;
80  
81      /**
82       * Default robust estimator method when none is provided.
83       */
84      public static final RobustEstimatorMethod DEFAULT_ROBUST_METHOD = RobustEstimatorMethod.PROMEDS;
85  
86      /**
87       * Listener to be notified of events such as when estimation starts, ends
88       * or its progress significantly changes.
89       */
90      protected CircleRobustEstimatorListener listener;
91  
92      /**
93       * Indicates if this estimator is locked because an estimation is being
94       * computed.
95       */
96      protected volatile boolean locked;
97  
98      /**
99       * Amount of progress variation before notifying a progress change during
100      * estimation.
101      */
102     protected float progressDelta;
103 
104     /**
105      * Amount of confidence expressed as a value between 0.0 and 1.0 (which is
106      * equivalent to 100%). The amount of confidence indicates the probability
107      * that the estimated result is correct. Usually this value will be close
108      * to 1.0, but not exactly 1.0.
109      */
110     protected double confidence;
111 
112     /**
113      * Maximum allowed number of iterations. When the maximum number of
114      * iterations is exceeded, result will not be available, however an
115      * approximate result will be available for retrieval.
116      */
117     protected int maxIterations;
118 
119     /**
120      * List of points to be used to estimate a circle. Provided list must have
121      * a size greater or equal than MINIMUM_SIZE.
122      */
123     protected List<Point2D> points;
124 
125     /**
126      * Constructor.
127      */
128     protected CircleRobustEstimator() {
129         progressDelta = DEFAULT_PROGRESS_DELTA;
130         confidence = DEFAULT_CONFIDENCE;
131         maxIterations = DEFAULT_MAX_ITERATIONS;
132     }
133 
134     /**
135      * Constructor.
136      *
137      * @param listener listener to be notified of events such as when estimation
138      *                 starts, ends or its progress significantly changes.
139      */
140     protected CircleRobustEstimator(final CircleRobustEstimatorListener listener) {
141         this.listener = listener;
142         progressDelta = DEFAULT_PROGRESS_DELTA;
143         confidence = DEFAULT_CONFIDENCE;
144         maxIterations = DEFAULT_MAX_ITERATIONS;
145     }
146 
147     /**
148      * Constructor with points.
149      *
150      * @param points 2D points to estimate a circle.
151      * @throws IllegalArgumentException if provided list of points don't have
152      *                                  a size greater or equal than MINIMUM_SIZE.
153      */
154     protected CircleRobustEstimator(final List<Point2D> points) {
155         progressDelta = DEFAULT_PROGRESS_DELTA;
156         confidence = DEFAULT_CONFIDENCE;
157         maxIterations = DEFAULT_MAX_ITERATIONS;
158         internalSetPoints(points);
159     }
160 
161     /**
162      * Constructor.
163      *
164      * @param points   2D points to estimate a circle.
165      * @param listener listener to be notified of events such as when estimation
166      *                 starts, ends or its progress significantly changes.
167      * @throws IllegalArgumentException if provided list of points don't have
168      *                                  a size greater or equal than MINIMUM_SIZE.
169      */
170     protected CircleRobustEstimator(final CircleRobustEstimatorListener listener, final List<Point2D> points) {
171         this.listener = listener;
172         progressDelta = DEFAULT_PROGRESS_DELTA;
173         confidence = DEFAULT_CONFIDENCE;
174         maxIterations = DEFAULT_MAX_ITERATIONS;
175         internalSetPoints(points);
176     }
177 
178 
179     /**
180      * Returns reference to listener to be notified of events such as when
181      * estimation starts, ends or its progress significantly changes.
182      *
183      * @return listener to be notified of events.
184      */
185     public CircleRobustEstimatorListener getListener() {
186         return listener;
187     }
188 
189     /**
190      * Sets listener to be notified of events such as when estimation starts,
191      * ends or its progress significantly changes.
192      *
193      * @param listener listener to be notified of events.
194      * @throws LockedException if robust estimator is locked.
195      */
196     public void setListener(final CircleRobustEstimatorListener listener) throws LockedException {
197         if (isLocked()) {
198             throw new LockedException();
199         }
200         this.listener = listener;
201     }
202 
203     /**
204      * Indicates whether listener has been provided and is available for
205      * retrieval.
206      *
207      * @return true if available, false otherwise.
208      */
209     public boolean isListenerAvailable() {
210         return listener != null;
211     }
212 
213     /**
214      * Indicates if this instance is locked because estimation is being computed
215      *
216      * @return true if locked, false otherwise.
217      */
218     public boolean isLocked() {
219         return locked;
220     }
221 
222     /**
223      * Returns amount of progress variation before notifying a progress change
224      * during estimation.
225      *
226      * @return amount of progress variation before notifying a progress change
227      * during estimation.
228      */
229     public float getProgressDelta() {
230         return progressDelta;
231     }
232 
233     /**
234      * Sets amount of progress variation before notifying a progress change
235      * during estimation.
236      *
237      * @param progressDelta amount of progress variation before notifying a
238      *                      progress change during estimation.
239      * @throws IllegalArgumentException if progress delta is less than zero or
240      *                                  greater than 1.
241      * @throws LockedException          if this estimator is locked because an estimation
242      *                                  is being computed.
243      */
244     public void setProgressDelta(final float progressDelta) throws LockedException {
245         if (isLocked()) {
246             throw new LockedException();
247         }
248         if (progressDelta < MIN_PROGRESS_DELTA || progressDelta > MAX_PROGRESS_DELTA) {
249             throw new IllegalArgumentException();
250         }
251         this.progressDelta = progressDelta;
252     }
253 
254     /**
255      * Returns amount of confidence expressed as a value between 0.0 and 1.0
256      * (which is equivalent to 100%). The amount of confidence indicates the
257      * probability that the estimated result is correct. Usually this value will
258      * be close to 1.0, but not exactly 1.0.
259      *
260      * @return amount of confidence as a value between 0.0 and 1.0.
261      */
262     public double getConfidence() {
263         return confidence;
264     }
265 
266     /**
267      * Sets amount of confidence expressed as a value between 0.0 and 1.0 (which
268      * is equivalent to 100%). The amount of confidence indicates the
269      * probability that the estimated result is correct. Usually this value will
270      * be close to 1.0, but not exactly 1.0.
271      *
272      * @param confidence confidence to be set as a value between 0.0 and 1.0.
273      * @throws IllegalArgumentException if provided value is not between 0.0 and
274      *                                  1.0.
275      * @throws LockedException          if this estimator is locked because an estimator
276      *                                  is being computed.
277      */
278     public void setConfidence(final double confidence) throws LockedException {
279         if (isLocked()) {
280             throw new LockedException();
281         }
282         if (confidence < MIN_CONFIDENCE || confidence > MAX_CONFIDENCE) {
283             throw new IllegalArgumentException();
284         }
285         this.confidence = confidence;
286     }
287 
288     /**
289      * Returns maximum allowed number of iterations. If maximum allowed number
290      * of iterations is achieved without converging to a result when calling
291      * estimate(), a RobustEstimatorException will be raised.
292      *
293      * @return maximum allowed number of iterations.
294      */
295     public int getMaxIterations() {
296         return maxIterations;
297     }
298 
299     /**
300      * Sets maximum allowed number of iterations. When the maximum number of
301      * iterations is exceeded, result will not be available, however an
302      * approximate result will be available for retrieval.
303      *
304      * @param maxIterations maximum allowed number of iterations to be set.
305      * @throws IllegalArgumentException if provided value is less than 1.
306      * @throws LockedException          if this estimator is locked because an estimation
307      *                                  is being computed.
308      */
309     public void setMaxIterations(final int maxIterations) throws LockedException {
310         if (isLocked()) {
311             throw new LockedException();
312         }
313         if (maxIterations < MIN_ITERATIONS) {
314             throw new IllegalArgumentException();
315         }
316         this.maxIterations = maxIterations;
317     }
318 
319     /**
320      * Returns list of points to be used to estimate a circle.
321      * Provided list must have a size greater or equal than MINIMUM_SIZE.
322      *
323      * @return list of points to be used to estimate a circle.
324      */
325     public List<Point2D> getPoints() {
326         return points;
327     }
328 
329     /**
330      * Sets list of points to be used to estimate a circle.
331      * Provided list must have a size greater or equal than MINIMUM_SIZE.
332      *
333      * @param points list of points to be used to estimate a circle.
334      * @throws IllegalArgumentException if provided list of points don't have
335      *                                  a size greater or equal than MINIMUM_SIZE.
336      * @throws LockedException          if estimator is locked because a computation is
337      *                                  already in progress.
338      */
339     public void setPoints(final List<Point2D> points) throws LockedException {
340         if (isLocked()) {
341             throw new LockedException();
342         }
343         internalSetPoints(points);
344     }
345 
346     /**
347      * Indicates if estimator is ready to start the circle estimation.
348      * This is true when a minimum if MINIMUM_SIZE points are available.
349      *
350      * @return true if estimator is ready, false otherwise.
351      */
352     public boolean isReady() {
353         return points != null && points.size() >= MINIMUM_SIZE;
354     }
355 
356     /**
357      * Returns quality scores corresponding to each point.
358      * The larger the score value the better the quality of the point measure.
359      * This implementation always returns null.
360      * Subclasses using quality scores must implement proper behaviour.
361      *
362      * @return quality scores corresponding to each point.
363      */
364     public double[] getQualityScores() {
365         return null;
366     }
367 
368     /**
369      * Sets quality scores corresponding to each point.
370      * The larger the score value the better the quality of the point sample.
371      * This implementation makes no action.
372      * Subclasses using quality scores must implement proper behaviour.
373      *
374      * @param qualityScores quality scores corresponding to each sampled point.
375      * @throws LockedException          if robust estimator is locked because an
376      *                                  estimation is already in progress.
377      * @throws IllegalArgumentException if provided quality scores length is
378      *                                  smaller than MINIMUM_SIZE (i.e. 3 samples).
379      */
380     public void setQualityScores(final double[] qualityScores) throws LockedException {
381     }
382 
383     /**
384      * Creates a circle robust estimator based on 2D point samples and using
385      * provided robust estimator method.
386      *
387      * @param method method of a robust estimator algorithm to estimate best
388      *               circle.
389      * @return an instance of a circle robust estimator.
390      */
391     public static CircleRobustEstimator create(final RobustEstimatorMethod method) {
392         return switch (method) {
393             case LMEDS -> new LMedSCircleRobustEstimator();
394             case MSAC -> new MSACCircleRobustEstimator();
395             case PROSAC -> new PROSACCircleRobustEstimator();
396             case PROMEDS -> new PROMedSCircleRobustEstimator();
397             default -> new RANSACCircleRobustEstimator();
398         };
399     }
400 
401     /**
402      * Creates a circle robust estimator based on 2D point samples and using
403      * provided points and robust estimator method.
404      *
405      * @param points 2D points to estimate a circle.
406      * @param method method of a robust estimator algorithm to estimate best
407      *               circle.
408      * @return an instance of a circle robust estimator.
409      * @throws IllegalArgumentException if provided list of points don't have a
410      *                                  size greater or equal than MINIMUM_SIZE.
411      */
412     public static CircleRobustEstimator create(
413             final List<Point2D> points, final RobustEstimatorMethod method) {
414         return switch (method) {
415             case LMEDS -> new LMedSCircleRobustEstimator(points);
416             case MSAC -> new MSACCircleRobustEstimator(points);
417             case PROSAC -> new PROSACCircleRobustEstimator(points);
418             case PROMEDS -> new PROMedSCircleRobustEstimator(points);
419             default -> new RANSACCircleRobustEstimator(points);
420         };
421     }
422 
423     /**
424      * Creates a circle robust estimator based on 2D point samples and using
425      * provided listener.
426      *
427      * @param listener listener to be notified of events such as when estimation
428      *                 starts, ends or its progress significantly changes.
429      * @param method   method of a robust estimator algorithm to estimate best
430      *                 circle.
431      * @return an instance of a circle robust estimator.
432      */
433     public static CircleRobustEstimator create(
434             final CircleRobustEstimatorListener listener,
435             final RobustEstimatorMethod method) {
436         return switch (method) {
437             case LMEDS -> new LMedSCircleRobustEstimator(listener);
438             case MSAC -> new MSACCircleRobustEstimator(listener);
439             case PROSAC -> new PROSACCircleRobustEstimator(listener);
440             case PROMEDS -> new PROMedSCircleRobustEstimator(listener);
441             default -> new RANSACCircleRobustEstimator(listener);
442         };
443     }
444 
445     /**
446      * Creates a circle robust estimator based on 2D point samples and using
447      * provided listener and points.
448      *
449      * @param listener listener to be notified of events such as when estimation
450      *                 starts, ends or its progress significantly changes.
451      * @param points   2D points to estimate a circle.
452      * @param method   method of a robust estimator algorithm to estimate best
453      *                 circle.
454      * @return an instance of a circle robust estimator.
455      * @throws IllegalArgumentException if provided list of points don't have a
456      *                                  size greater or equal than MINIMUM_SIZE.
457      */
458     public static CircleRobustEstimator create(
459             final CircleRobustEstimatorListener listener, final List<Point2D> points,
460             final RobustEstimatorMethod method) {
461         return switch (method) {
462             case LMEDS -> new LMedSCircleRobustEstimator(listener, points);
463             case MSAC -> new MSACCircleRobustEstimator(listener, points);
464             case PROSAC -> new PROSACCircleRobustEstimator(listener, points);
465             case PROMEDS -> new PROMedSCircleRobustEstimator(listener, points);
466             default -> new RANSACCircleRobustEstimator(listener, points);
467         };
468     }
469 
470     /**
471      * Creates a circle robust estimator based on 2D point samples and using
472      * provided robust estimator method.
473      *
474      * @param qualityScores quality scores corresponding to each provided point.
475      * @param method        method of a robust estimator algorithm to estimate best
476      *                      circle.
477      * @return an instance of a circle robust estimator.
478      * @throws IllegalArgumentException if provided quality scores length is
479      *                                  smaller than MINIMUM_SIZE (i.e. 3 points).
480      */
481     public static CircleRobustEstimator create(
482             final double[] qualityScores, final RobustEstimatorMethod method) {
483         return switch (method) {
484             case LMEDS -> new LMedSCircleRobustEstimator();
485             case MSAC -> new MSACCircleRobustEstimator();
486             case PROSAC -> new PROSACCircleRobustEstimator(qualityScores);
487             case PROMEDS -> new PROMedSCircleRobustEstimator(qualityScores);
488             default -> new RANSACCircleRobustEstimator();
489         };
490     }
491 
492     /**
493      * Creates a circle robust estimator based on 2D point samples and using
494      * provided points and robust estimator method.
495      *
496      * @param points        2D points to estimate a circle.
497      * @param qualityScores quality scores corresponding to each provided point.
498      * @param method        method of a robust estimator algorithm to estimate best
499      *                      circle.
500      * @return an instance of a circle robust estimator.
501      * @throws IllegalArgumentException if provided list of points don't have
502      *                                  the same size as the list of provided quality scores, or it their size
503      *                                  is not greater or equal than MINIMUM_SIZE.
504      */
505     public static CircleRobustEstimator create(
506             final List<Point2D> points, final double[] qualityScores, final RobustEstimatorMethod method) {
507         return switch (method) {
508             case LMEDS -> new LMedSCircleRobustEstimator(points);
509             case MSAC -> new MSACCircleRobustEstimator(points);
510             case PROSAC -> new PROSACCircleRobustEstimator(points, qualityScores);
511             case PROMEDS -> new PROMedSCircleRobustEstimator(points, qualityScores);
512             default -> new RANSACCircleRobustEstimator(points);
513         };
514     }
515 
516     /**
517      * Creates a circle robust estimator based on 2D point samples and using
518      * provided listener.
519      *
520      * @param listener      listener to be notified of events such as when estimation
521      *                      starts, ends or its progress significantly changes.
522      * @param qualityScores quality scores corresponding to each provided point.
523      * @param method        method of a robust estimator algorithm to estimate best
524      *                      circle.
525      * @return an instance of a circle robust estimator.
526      * @throws IllegalArgumentException if provided quality scores length is
527      *                                  smaller than MINIMUM_SIZE (i.e. 3 points).
528      */
529     public static CircleRobustEstimator create(
530             final CircleRobustEstimatorListener listener, final double[] qualityScores,
531             final RobustEstimatorMethod method) {
532         return switch (method) {
533             case LMEDS -> new LMedSCircleRobustEstimator(listener);
534             case MSAC -> new MSACCircleRobustEstimator(listener);
535             case PROSAC -> new PROSACCircleRobustEstimator(listener, qualityScores);
536             case PROMEDS -> new PROMedSCircleRobustEstimator(listener, qualityScores);
537             default -> new RANSACCircleRobustEstimator(listener);
538         };
539     }
540 
541     /**
542      * Creates a circle robust estimator based on 2D point samples and using
543      * provided listener and points.
544      *
545      * @param listener      listener to be notified of events such as when estimation
546      *                      starts, ends or its progress significantly changes.
547      * @param points        2D points to estimate a circle.
548      * @param qualityScores quality scores corresponding to each provided point.
549      * @param method        method of a robust estimator algorithm to estimate best
550      *                      circle.
551      * @return an instance of a circle robust estimator.
552      * @throws IllegalArgumentException if provided list of points don't have
553      *                                  the same size as the list of provided quality scores, or it their size
554      *                                  is not greater or equal than MINIMUM_SIZE.
555      */
556     public static CircleRobustEstimator create(
557             final CircleRobustEstimatorListener listener, final List<Point2D> points,
558             final double[] qualityScores, final RobustEstimatorMethod method) {
559         return switch (method) {
560             case LMEDS -> new LMedSCircleRobustEstimator(listener, points);
561             case MSAC -> new MSACCircleRobustEstimator(listener, points);
562             case PROSAC -> new PROSACCircleRobustEstimator(listener, points,
563                     qualityScores);
564             case PROMEDS -> new PROMedSCircleRobustEstimator(listener, points,
565                     qualityScores);
566             default -> new RANSACCircleRobustEstimator(listener, points);
567         };
568     }
569 
570     /**
571      * Creates a circle robust estimator based on 2D point samples and using
572      * default robust estimator method.
573      *
574      * @return an instance of a circle robust estimator.
575      */
576     public static CircleRobustEstimator create() {
577         return create(DEFAULT_ROBUST_METHOD);
578     }
579 
580     /**
581      * Creates a circle robust estimator based on 2D point samples and using
582      * provided points and default robust estimator method.
583      *
584      * @param points 2D points to estimate a circle.
585      * @return an instance of a circle robust estimator.
586      * @throws IllegalArgumentException if provided list of points don't have a
587      *                                  size greater or equal than MINIMUM_SIZE.
588      */
589     public static CircleRobustEstimator create(final List<Point2D> points) {
590         return create(points, DEFAULT_ROBUST_METHOD);
591     }
592 
593     /**
594      * Creates a circle robust estimator based on 2D point samples and using
595      * provided listener and default robust estimator method.
596      *
597      * @param listener listener to be notified of events such as when estimation
598      *                 starts, ends or its progress significantly changes.
599      * @return an instance of a circle robust estimator.
600      */
601     public static CircleRobustEstimator create(final CircleRobustEstimatorListener listener) {
602         return create(listener, DEFAULT_ROBUST_METHOD);
603     }
604 
605     /**
606      * Creates a circle robust estimator based on 2D point samples and using
607      * provided listener and points and default robust estimator method.
608      *
609      * @param listener listener to be notified of events such as when estimation
610      *                 starts, ends or its progress significantly changes.
611      * @param points   2D points to estimate a circle.
612      * @return an instance of a circle robust estimator.
613      * @throws IllegalArgumentException if provided list of points don't have a
614      *                                  size greater or equal than MINIMUM_SIZE.
615      */
616     public static CircleRobustEstimator create(final CircleRobustEstimatorListener listener,
617                                                final List<Point2D> points) {
618         return create(listener, points, DEFAULT_ROBUST_METHOD);
619     }
620 
621     /**
622      * Creates a circle robust estimator based on 2D point samples and using
623      * default robust estimator method.
624      *
625      * @param qualityScores quality scores corresponding to each provided point
626      * @return an instance of a circle robust estimator.
627      * @throws IllegalArgumentException if provided quality scores length is
628      *                                  smaller than MINIMUM_SIZE (i.e. 3 points).
629      */
630     public static CircleRobustEstimator create(final double[] qualityScores) {
631         return create(qualityScores, DEFAULT_ROBUST_METHOD);
632     }
633 
634     /**
635      * Creates a circle robust estimator based on 2D point samples and using
636      * provided points and default estimator method.
637      *
638      * @param points        2D points to estimate a circle.
639      * @param qualityScores quality scores corresponding to each provided point
640      * @return an instance of a circle robust estimator.
641      * @throws IllegalArgumentException if provided list of points don't have
642      *                                  the same size as the list of provided quality scores, or if their size
643      *                                  is not greater or equal than MINIMUM_SIZE.
644      */
645     public static CircleRobustEstimator create(
646             final List<Point2D> points, final double[] qualityScores) {
647         return create(points, qualityScores, DEFAULT_ROBUST_METHOD);
648     }
649 
650     /**
651      * Creates a circle robust estimator based on 2D point samples and using
652      * provided listener and default estimator method.
653      *
654      * @param listener      listener to be notified of events such as when estimation
655      *                      starts, ends or its progress significantly changes.
656      * @param qualityScores quality scores corresponding to each provided point
657      * @return an instance of a circle robust estimator.
658      * @throws IllegalArgumentException if provided quality scores length is
659      *                                  smaller than MINIMUM_SIZE (i.e. 3 points).
660      */
661     public static CircleRobustEstimator create(
662             final CircleRobustEstimatorListener listener, final double[] qualityScores) {
663         return create(listener, qualityScores, DEFAULT_ROBUST_METHOD);
664     }
665 
666     /**
667      * Creates a circle robust estimator based on 2D point samples and using
668      * provided listener and points and default estimator method.
669      *
670      * @param listener      listener to be notified of events such as when estimation
671      *                      starts, ends or its progress significantly changes.
672      * @param points        2D points to estimate a circle.
673      * @param qualityScores quality scores corresponding to each provided point
674      * @return an instance of a circle robust estimator.
675      * @throws IllegalArgumentException if provided list of points don't have
676      *                                  the same size as the list of provided quality scores, or if their size
677      *                                  is not greater or equal than MINIMUM_SIZE.
678      */
679     public static CircleRobustEstimator create(
680             final CircleRobustEstimatorListener listener, final List<Point2D> points, final double[] qualityScores) {
681         return create(listener, points, qualityScores, DEFAULT_ROBUST_METHOD);
682     }
683 
684     /**
685      * Estimates a circle using a robust estimator and the best set of 2D points
686      * that fit into the locus of the estimated circle found using the robust
687      * estimator.
688      *
689      * @return a circle.
690      * @throws LockedException          if robust estimator is locked because an
691      *                                  estimation is already in progress.
692      * @throws NotReadyException        if provided input data is not enough to start
693      *                                  the estimation.
694      * @throws RobustEstimatorException if estimation fails for any reason
695      *                                  (i.e. numerical instability, no solution available, etc).
696      */
697     public abstract Circle estimate() throws LockedException, NotReadyException, RobustEstimatorException;
698 
699     /**
700      * Returns method being used for robust estimation.
701      *
702      * @return method being used for robust estimation.
703      */
704     public abstract RobustEstimatorMethod getMethod();
705 
706     /**
707      * Internal method to set lists of points to be used to estimate a circle.
708      * This method does not check whether estimator is locked or not.
709      *
710      * @param points list of points to be used to estimate a circle.
711      * @throws IllegalArgumentException if provided list of points doesn't have
712      *                                  a size greater or equal than MINIMUM_SIZE.
713      */
714     private void internalSetPoints(final List<Point2D> points) {
715         if (points.size() < MINIMUM_SIZE) {
716             throw new IllegalArgumentException();
717         }
718         this.points = points;
719     }
720 
721     /**
722      * Computes the residual between a circle and a point.
723      *
724      * @param c     a circle.
725      * @param point a 2D point.
726      * @return residual.
727      */
728     protected double residual(final Circle c, final Point2D point) {
729         point.normalize();
730 
731         return c.getDistance(point);
732     }
733 }