/*
    * Copyright (C) 2015 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.ar.sfm;
  
  import com.irurueta.geometry.PinholeCamera;
  import com.irurueta.geometry.Point2D;
  import com.irurueta.geometry.Point3D;
  import com.irurueta.geometry.estimators.LockedException;
  import com.irurueta.geometry.estimators.NotReadyException;
  import com.irurueta.numerical.robust.RobustEstimatorException;
  import com.irurueta.numerical.robust.RobustEstimatorMethod;
  
  import java.util.List;
  
  /**
   * Abstract class for algorithms to robustly triangulate 3D points from matched
   * 2D points and their corresponding cameras on several views.
   * Robust estimators can be used to estimate a more precise triangulation when
   * there are more than 2 views where points have been matched.
   */
  public abstract class RobustSinglePoint3DTriangulator {
  
      /**
       * Default robust estimator method when none is provided.
       */
      public static final RobustEstimatorMethod DEFAULT_ROBUST_METHOD = RobustEstimatorMethod.PROMEDS;
  
      /**
       * 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 chose 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;
  
      /**
       * Minimum required number of views to triangulate 3D points.
       */
      public static final int MIN_REQUIRED_VIEWS = 2;
  
      /**
       * Indicates whether by default a solution to an homogeneous system of
       * equations should be found.
       */
      public static final boolean DEFAULT_USE_HOMOGENEOUS_SOLUTION = true;
  
      /**
       * Matched 2D points. Each point in the list is assumed to be projected by
       * the corresponding camera in the list.
       */
      protected List<Point2D> points2D;
 
     /**
      * List of cameras associated to the matched 2D point on the same position
      * as the camera on the list.
      */
     protected List<PinholeCamera> cameras;
 
     /**
      * Listener to be notified of events such as when estimation starts, ends or
      * its progress significantly changes.
      */
     protected RobustSinglePoint3DTriangulatorListener listener;
 
     /**
      * Indicates whether a solution to an homogeneous system of equations should
      * be found. Typically, this should be true, since even points and cameras
      * at infinity can be used. If points are close and geometry is
      * well-defined, false can be used to solve an inhomogeneous system of equations
      * and obtain a slightly better accuracy.
      */
     protected boolean useHomogeneousSolution;
 
     /**
      * Indicates if this estimator is locked because an estimation is being
      * computed.
      */
     protected volatile 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;
 
     /**
      * Constructor.
      */
     protected RobustSinglePoint3DTriangulator() {
         useHomogeneousSolution = DEFAULT_USE_HOMOGENEOUS_SOLUTION;
         progressDelta = DEFAULT_PROGRESS_DELTA;
         confidence = DEFAULT_CONFIDENCE;
         maxIterations = DEFAULT_MAX_ITERATIONS;
     }
 
     /**
      * Constructor.
      *
      * @param listener listener to be notified of events such as when estimation
      *                 starts, ends or its progress significantly changes.
      */
     protected RobustSinglePoint3DTriangulator(
             final RobustSinglePoint3DTriangulatorListener listener) {
         this();
         this.listener = listener;
     }
 
     /**
      * Constructor.
      *
      * @param points  Matched 2D points. Each point in the list is assumed to be
      *                projected by the corresponding camera in the list.
      * @param cameras List of cameras associated to the matched 2D point on the
      *                same position as the camera on the list.
      * @throws IllegalArgumentException if provided lists don't have the same
      *                                  length or their length is less than 2 views, which is the minimum
      *                                  required to compute triangulation.
      */
     protected RobustSinglePoint3DTriangulator(final List<Point2D> points, final List<PinholeCamera> cameras) {
         this();
         internalSetPointsAndCameras(points, cameras);
     }
 
     /**
      * Constructor.
      *
      * @param points   Matched 2D points. Each point in the list is assumed to be
      *                 projected by the corresponding camera in the list.
      * @param cameras  List of cameras associated to the matched 2D point on the
      *                 same position as the camera on the list.
      * @param listener listener to be notified of events such as when estimation
      *                 starts, ends or its progress significantly changes.
      * @throws IllegalArgumentException if provided lists don't have the same
      *                                  length or their length is less than 2 views, which is the minimum
      *                                  required to compute triangulation.
      */
     protected RobustSinglePoint3DTriangulator(final List<Point2D> points,
                                               final List<PinholeCamera> cameras,
                                               final RobustSinglePoint3DTriangulatorListener listener) {
         this(points, cameras);
         this.listener = listener;
     }
 
     /**
      * 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 RobustSinglePoint3DTriangulatorListener 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 RobustSinglePoint3DTriangulatorListener 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 a solution to an homogeneous system of equations should
      * be found. Typically, this should be true, since even points and cameras
      * at infinity can be used. If points are close and geometry is
      * well-defined, false can be used to solve an inhomogeneous system of equations
      * and obtain a slightly better accuracy.
      *
      * @return true if an homogeneous solution must be found (default value),
      * false otherwise.
      */
     public boolean isUseHomogeneousSolution() {
         return useHomogeneousSolution;
     }
 
     /**
      * Sets boolean indicating whether a solution to an homogeneous system of
      * equations should be found. Typically, this should be true, since even
      * points and cameras at infinity can be used. If points are close and
      * geometry is well-defined, false can be used to solve an inhomogeneous
      * system of equations and obtain a slightly better accuracy.
      *
      * @param useHomogeneousSolution true if an homogeneous solution will be
      *                               found, false if an inhomogeneous solution will be found instead.
      * @throws LockedException if this instance is locked.
      */
     public void setUseHomogeneousSolution(final boolean useHomogeneousSolution) throws LockedException {
         if (isLocked()) {
             throw new LockedException();
         }
         this.useHomogeneousSolution = useHomogeneousSolution;
     }
 
     /**
      * Indicates if this instance is locked because triangulation 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;
     }
 
     /**
      * Sets list of matched 2D points for each view and their corresponding
      * cameras used to project them.
      *
      * @param points2D list of matched 2D points on each view. Each point in the
      *                 list is assumed to be projected by the corresponding camera in the list.
      * @param cameras  cameras for each view where 2D points are represented.
      * @throws LockedException          if this instance is locked.
      * @throws IllegalArgumentException if provided lists don't have the same
      *                                  length or their length is less than 2 views, which is the minimum
      *                                  required to compute triangulation.
      */
     public void setPointsAndCameras(final List<Point2D> points2D, final List<PinholeCamera> cameras)
             throws LockedException {
         if (isLocked()) {
             throw new LockedException();
         }
         internalSetPointsAndCameras(points2D, cameras);
     }
 
     /**
      * Returns list of matched 2D points on each view. Each point in the list is
      * assumed to be projected by the corresponding camera.
      *
      * @return list of matched 2D points on each view.
      */
     public List<Point2D> getPoints2D() {
         return points2D;
     }
 
     /**
      * Returns cameras for each view where 2D points are represented.
      *
      * @return cameras for each view where 2D points are represented.
      */
     public List<PinholeCamera> getCameras() {
         return cameras;
     }
 
     /**
      * Returns quality scores corresponding to each view.
      * The larger the score value the better the quality of the view measure.
      * This implementation always returns null.
      * Subclasses using quality scores must implement proper behaviour.
      *
      * @return quality scores corresponding to each view.
      */
     public double[] getQualityScores() {
         return null;
     }
 
     /**
      * Sets quality scores corresponding to each view.
      * The larger the score value the better the quality of the view sample.
      * This implementation makes no action.
      * Subclasses using quality scores must implement proper behaviour.
      *
      * @param qualityScores quality scores corresponding to each view.
      * @throws LockedException          if robust estimator is locked because an
      *                                  estimation is already in progress.
      * @throws IllegalArgumentException if provided quality scores length is
      *                                  smaller than MIN_REQUIRED_VIEWS (i.e. 2 views).
      */
     public void setQualityScores(final double[] qualityScores) throws LockedException {
     }
 
 
     /**
      * Indicates whether this instance is ready to start the triangulation.
      * An instance is ready when both lists of 2D points and cameras are
      * provided, both lists have the same length and at least data for 2 views
      * is provided.
      *
      * @return true if this instance is ready, false otherwise.
      */
     public boolean isReady() {
         return SinglePoint3DTriangulator.areValidPointsAndCameras(points2D, cameras);
     }
 
     /**
      * Triangulates provided matched 2D points being projected by each
      * corresponding camera into a single 3D point.
      * At least 2 matched 2D points and their corresponding 2 cameras are
      * required to compute triangulation. If more views are provided, an
      * averaged solution can be found.
      *
      * @return computed triangulated 3D point.
      * @throws LockedException          if this instance is locked.
      * @throws NotReadyException        if lists of points and cameras don't have the
      *                                  same length or less than 2 views are provided.
      * @throws RobustEstimatorException if estimation fails for any reason
      *                                  (i.e. numerical instability, no solution available, etc).
      */
     public abstract Point3D triangulate() throws LockedException, NotReadyException, RobustEstimatorException;
 
     /**
      * Returns method being used for robust estimation.
      *
      * @return method being used for robust estimation.
      */
     public abstract RobustEstimatorMethod getMethod();
 
     /**
      * Creates a robust single 3D point triangulator using provided robust
      * method.
      *
      * @param method method of a robust estimator algorithm to estimate the best
      *               triangulation.
      * @return an instance of a robust single 3D point triangulator.
      */
     public static RobustSinglePoint3DTriangulator create(final RobustEstimatorMethod method) {
         return switch (method) {
             case RANSAC -> new RANSACRobustSinglePoint3DTriangulator();
             case LMEDS -> new LMedSRobustSinglePoint3DTriangulator();
             case MSAC -> new MSACRobustSinglePoint3DTriangulator();
             case PROSAC -> new PROSACRobustSinglePoint3DTriangulator();
             default -> new PROMedSRobustSinglePoint3DTriangulator();
         };
     }
 
     /**
      * Creates a robust single 3D point triangulator using provided points,
      * cameras and robust method.
      *
      * @param points  matched 2D points. Each point in the list is assumed to
      *                be projected by the corresponding camera in the list.
      * @param cameras list of cameras associated to the matched 2D point on the
      *                same position as the camera on the list.
      * @param method  method of a robust estimator algorithm to estimate the best
      *                triangulation.
      * @return an instance of a robust single 3D point triangulator.
      * @throws IllegalArgumentException if provided lists don't have the same
      *                                  length or their length is less than 2 views, which is the minimum
      *                                  required to compute triangulation.
      */
     public static RobustSinglePoint3DTriangulator create(
             final List<Point2D> points, final List<PinholeCamera> cameras, final RobustEstimatorMethod method) {
         return switch (method) {
             case RANSAC -> new RANSACRobustSinglePoint3DTriangulator(points, cameras);
             case LMEDS -> new LMedSRobustSinglePoint3DTriangulator(points, cameras);
             case MSAC -> new MSACRobustSinglePoint3DTriangulator(points, cameras);
             case PROSAC -> new PROSACRobustSinglePoint3DTriangulator(points, cameras);
             default -> new PROMedSRobustSinglePoint3DTriangulator(points, cameras);
         };
     }
 
     /**
      * Creates a robust single 3D point triangulator using provided points,
      * cameras and robust method.
      *
      * @param points        matched 2D points. Each point in the list is assumed to
      *                      be projected by the corresponding camera in the list.
      * @param cameras       list of cameras associated to the matched 2D point on the
      *                      same position as the camera on the list.
      * @param qualityScores quality scores corresponding to each point.
      * @param method        method of a robust estimator algorithm to estimate the best
      *                      triangulation.
      * @return an instance of a robust single 3D point triangulator.
      * @throws IllegalArgumentException if provided lists or quality scores
      *                                  don't have the same length or their length is less than 2 views,
      *                                  which is the minimum required to compute triangulation.
      */
     public static RobustSinglePoint3DTriangulator create(
             final List<Point2D> points, final List<PinholeCamera> cameras, final double[] qualityScores,
             final RobustEstimatorMethod method) {
         return switch (method) {
             case RANSAC -> new RANSACRobustSinglePoint3DTriangulator(points, cameras);
             case LMEDS -> new LMedSRobustSinglePoint3DTriangulator(points, cameras);
             case MSAC -> new MSACRobustSinglePoint3DTriangulator(points, cameras);
             case PROSAC -> new PROSACRobustSinglePoint3DTriangulator(points, cameras, qualityScores);
             default -> new PROMedSRobustSinglePoint3DTriangulator(points, cameras, qualityScores);
         };
     }
 
     /**
      * Creates a robust single 3D point triangulator using default robust
      * method.
      *
      * @return an instance of a robust single 3D point triangulator.
      */
     public static RobustSinglePoint3DTriangulator create() {
         return create(DEFAULT_ROBUST_METHOD);
     }
 
     /**
      * Creates a robust single 3D point triangulator using provided points,
      * cameras and default robust method.
      *
      * @param points  matched 2D points. Each point in the list is assumed to
      *                be projected by the corresponding camera in the list.
      * @param cameras list of cameras associated to the matched 2D point on the
      *                same position as the camera on the list.
      * @return an instance of a robust single 3D point triangulator.
      * @throws IllegalArgumentException if provided lists don't have the same
      *                                  length or their length is less than 2 views, which is the minimum
      *                                  required to compute triangulation.
      */
     public static RobustSinglePoint3DTriangulator create(
             final List<Point2D> points, final List<PinholeCamera> cameras) {
         return create(points, cameras, DEFAULT_ROBUST_METHOD);
     }
 
     /**
      * Creates a robust single 3D point triangulator using provided points,
      * cameras and default robust method.
      *
      * @param points        matched 2D points. Each point in the list is assumed to
      *                      be projected by the corresponding camera in the list.
      * @param cameras       list of cameras associated to the matched 2D point on the
      *                      same position as the camera on the list.
      * @param qualityScores quality scores corresponding to each point.
      * @return an instance of a robust single 3D point triangulator.
      * @throws IllegalArgumentException if provided lists or quality scores
      *                                  don't have the same length or their length is less than 2 views,
      *                                  which is the minimum required to compute triangulation.
      */
     public static RobustSinglePoint3DTriangulator create(
             final List<Point2D> points, final List<PinholeCamera> cameras, final double[] qualityScores) {
         return create(points, cameras, qualityScores, DEFAULT_ROBUST_METHOD);
     }
 
     /**
      * Internal method to sets list of matched 2D points for each view and their
      * corresponding cameras used to project them.
      * This method does not check whether instance is locked.
      *
      * @param points2D list of matched 2D points on each view. Each point in the
      *                 list is assumed to be projected by the corresponding camera in the list.
      * @param cameras  cameras for each view where 2D points are represented.
      * @throws IllegalArgumentException if provided lists don't have the same
      *                                  length or their length is less than 2 views, which is the minimum
      *                                  required to compute triangulation.
      */
     private void internalSetPointsAndCameras(
             final List<Point2D> points2D, final List<PinholeCamera> cameras) {
 
         if (!SinglePoint3DTriangulator.areValidPointsAndCameras(points2D, cameras)) {
             throw new IllegalArgumentException();
         }
 
         this.points2D = points2D;
         this.cameras = cameras;
     }
 }