/*
    * 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.CoordinatesType;
  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.LMedSRobustEstimator;
  import com.irurueta.numerical.robust.LMedSRobustEstimatorListener;
  import com.irurueta.numerical.robust.RobustEstimator;
  import com.irurueta.numerical.robust.RobustEstimatorException;
  import com.irurueta.numerical.robust.RobustEstimatorMethod;
  
  import java.util.ArrayList;
  import java.util.List;
  
  /**
   * Robustly triangulates 3D points from matched 2D points and their
   * corresponding cameras on several views using LMedS algorithm.
   */
  public class LMedSRobustSinglePoint3DTriangulator extends RobustSinglePoint3DTriangulator {
  
      /**
       * Default value to be used for stop threshold. Stop threshold can be used
       * to keep the algorithm iterating in case that best estimated threshold
       * using median of residuals is not small enough. Once a solution is found
       * that generates a threshold below this value, the algorithm will stop.
       * The stop threshold can be used to prevent the LMedS algorithm iterating
       * too many times in cases where samples have a very similar accuracy.
       * For instance, in cases where proportion of outliers is very small (close
       * to 0%), and samples are very accurate (i.e. 1e-6), the algorithm would
       * iterate for a long time trying to find the best solution when indeed
       * there is no need to do that if a reasonable threshold has already been
       * reached.
       * Because of this behaviour the stop threshold can be set to a value much
       * lower than the one typically used in RANSAC, and yet the algorithm could
       * still produce even smaller thresholds in estimated results.
       */
      public static final double DEFAULT_STOP_THRESHOLD = 1e-3;
  
      /**
       * Minimum allowed stop threshold value.
       */
      public static final double MIN_STOP_THRESHOLD = 0.0;
  
      /**
       * Threshold to be used to keep the algorithm iterating in case that best
       * estimated threshold using median of residuals is not small enough. Once
       * a solution is found that generates a threshold below this value, the
       * algorithm will stop.
       * The stop threshold can be used to prevent the LMedS algorithm iterating
       * too many times in cases where samples have a very similar accuracy.
       * For instance, in cases where proportion of outliers is very small (close
       * to 0%), and samples are very accurate (i.e. 1e-6), the algorithm would
       * iterate for a long time trying to find the best solution when indeed
       * there is no need to do that if a reasonable threshold has already been
       * reached.
       * Because of this behaviour the stop threshold can be set to a value much
       * lower than the one typically used in RANSAC, and yet the algorithm could
       * still produce even smaller thresholds in estimated results.
       */
      private double stopThreshold;
  
      /**
       * Constructor.
       */
      public LMedSRobustSinglePoint3DTriangulator() {
          super();
          stopThreshold = DEFAULT_STOP_THRESHOLD;
      }
  
      /**
       * Constructor.
       *
       * @param listener listener to be notified of events such as when estimation
       *                 starts, ends or its progress significantly changes.
       */
      public LMedSRobustSinglePoint3DTriangulator(final RobustSinglePoint3DTriangulatorListener listener) {
          super(listener);
          stopThreshold = DEFAULT_STOP_THRESHOLD;
      }
  
      /**
      * 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.
      */
     public LMedSRobustSinglePoint3DTriangulator(final List<Point2D> points, final List<PinholeCamera> cameras) {
         super(points, cameras);
         stopThreshold = DEFAULT_STOP_THRESHOLD;
     }
 
     /**
      * 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.
      */
     public LMedSRobustSinglePoint3DTriangulator(final List<Point2D> points,
                                                 final List<PinholeCamera> cameras,
                                                 final RobustSinglePoint3DTriangulatorListener listener) {
         super(points, cameras, listener);
         stopThreshold = DEFAULT_STOP_THRESHOLD;
     }
 
     /**
      * Returns threshold to be used to keep the algorithm iterating in case that
      * best estimated threshold using median of residuals is not small enough.
      * Once a solution is found that generates a threshold below this value, the
      * algorithm will stop.
      * The stop threshold can be used to prevent the LMedS algorithm iterating
      * too many times in cases where samples have a very similar accuracy.
      * For instance, in cases where proportion of outliers is very small (close
      * to 0%), and samples are very accurate (i.e. 1e-6), the algorithm would
      * iterate for a long time trying to find the best solution when indeed
      * there is no need to do that if a reasonable threshold has already been
      * reached.
      * Because of this behaviour the stop threshold can be set to a value much
      * lower than the one typically used in RANSAC, and yet the algorithm could
      * still produce even smaller thresholds in estimated results.
      *
      * @return stop threshold to stop the algorithm prematurely when a certain
      * accuracy has been reached.
      */
     public double getStopThreshold() {
         return stopThreshold;
     }
 
     /**
      * Sets threshold to be used to keep the algorithm iterating in case that
      * best estimated threshold using median of residuals is not small enough.
      * Once a solution is found that generates a threshold below this value, the
      * algorithm will stop.
      * The stop threshold can be used to prevent the LMedS algorithm iterating
      * too many times in cases where samples have a very similar accuracy.
      * For instance, in cases where proportion of outliers is very small (close
      * to 0%), and samples are very accurate (i.e. 1e-6), the algorithm would
      * iterate for a long time trying to find the best solution when indeed
      * there is no need to do that if a reasonable threshold has already been
      * reached.
      * Because of this behaviour the stop threshold can be set to a value much
      * lower than the one typically used in RANSAC, and yet the algorithm could
      * still produce even smaller thresholds in estimated results.
      *
      * @param stopThreshold stop threshold to stop the algorithm prematurely
      *                      when a certain accuracy has been reached.
      * @throws IllegalArgumentException if provided value is zero or negative.
      * @throws LockedException          if robust estimator is locked because an
      *                                  estimation is already in progress.
      */
     public void setStopThreshold(final double stopThreshold) throws LockedException {
         if (isLocked()) {
             throw new LockedException();
         }
         if (stopThreshold <= MIN_STOP_THRESHOLD) {
             throw new IllegalArgumentException();
         }
 
         this.stopThreshold = stopThreshold;
     }
 
     /**
      * 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).
      */
     @SuppressWarnings("DuplicatedCode")
     @Override
     public Point3D triangulate() throws LockedException, NotReadyException, RobustEstimatorException {
         if (isLocked()) {
             throw new LockedException();
         }
         if (!isReady()) {
             throw new NotReadyException();
         }
 
         final var innerEstimator = new LMedSRobustEstimator<Point3D>(new LMedSRobustEstimatorListener<>() {
 
             // point to be reused when computing residuals
             private final Point2D testPoint = Point2D.create(CoordinatesType.HOMOGENEOUS_COORDINATES);
 
             // non-robust 3D point triangulator
             private final SinglePoint3DTriangulator triangulator = SinglePoint3DTriangulator.create(
                     useHomogeneousSolution ? Point3DTriangulatorType.LMSE_HOMOGENEOUS_TRIANGULATOR
                             : Point3DTriangulatorType.LMSE_INHOMOGENEOUS_TRIANGULATOR);
 
             // subset of 2D points
             private final List<Point2D> subsetPoints = new ArrayList<>();
 
             // subst of cameras
             private final List<PinholeCamera> subsetCameras = new ArrayList<>();
 
             @Override
             public int getTotalSamples() {
                 return points2D.size();
             }
 
             @Override
             public int getSubsetSize() {
                 return MIN_REQUIRED_VIEWS;
             }
 
             @Override
             public void estimatePreliminarSolutions(final int[] samplesIndices, final List<Point3D> solutions) {
                 subsetPoints.clear();
                 subsetPoints.add(points2D.get(samplesIndices[0]));
                 subsetPoints.add(points2D.get(samplesIndices[1]));
 
                 subsetCameras.clear();
                 subsetCameras.add(cameras.get(samplesIndices[0]));
                 subsetCameras.add(cameras.get(samplesIndices[1]));
 
                 try {
                     triangulator.setPointsAndCameras(subsetPoints, subsetCameras);
                     final var triangulated = triangulator.triangulate();
                     solutions.add(triangulated);
                 } catch (final Exception e) {
                     // if anything fails, no solution is added
                 }
             }
 
             @Override
             public double computeResidual(final Point3D currentEstimation, final int i) {
                 final var point2D = points2D.get(i);
                 final var camera = cameras.get(i);
 
                 // project estimated point with camera
                 camera.project(currentEstimation, testPoint);
 
                 // return distance of projected point respect to the original one
                 // as a residual
                 return testPoint.distanceTo(point2D);
             }
 
             @Override
             public boolean isReady() {
                 return LMedSRobustSinglePoint3DTriangulator.this.isReady();
             }
 
             @Override
             public void onEstimateStart(final RobustEstimator<Point3D> estimator) {
                 if (listener != null) {
                     listener.onTriangulateStart(LMedSRobustSinglePoint3DTriangulator.this);
                 }
             }
 
             @Override
             public void onEstimateEnd(final RobustEstimator<Point3D> estimator) {
                 if (listener != null) {
                     listener.onTriangulateEnd(LMedSRobustSinglePoint3DTriangulator.this);
                 }
             }
 
             @Override
             public void onEstimateNextIteration(final RobustEstimator<Point3D> estimator, final int iteration) {
                 if (listener != null) {
                     listener.onTriangulateNextIteration(
                             LMedSRobustSinglePoint3DTriangulator.this, iteration);
                 }
             }
 
             @Override
             public void onEstimateProgressChange(final RobustEstimator<Point3D> estimator, final float progress) {
                 if (listener != null) {
                     listener.onTriangulateProgressChange(
                             LMedSRobustSinglePoint3DTriangulator.this, progress);
                 }
             }
         });
 
         try {
             locked = true;
             innerEstimator.setConfidence(confidence);
             innerEstimator.setMaxIterations(maxIterations);
             innerEstimator.setProgressDelta(progressDelta);
             innerEstimator.setStopThreshold(stopThreshold);
             return innerEstimator.estimate();
         } catch (final com.irurueta.numerical.LockedException e) {
             throw new LockedException(e);
         } catch (final com.irurueta.numerical.NotReadyException e) {
             throw new NotReadyException(e);
         } finally {
             locked = false;
         }
     }
 
     /**
      * Returns method being used for robust estimation.
      *
      * @return method being used for robust estimation.
      */
     @Override
     public RobustEstimatorMethod getMethod() {
         return RobustEstimatorMethod.LMEDS;
     }
 }