/*
    * 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.geometry.estimators;
  
  import com.irurueta.geometry.CoordinatesType;
  import com.irurueta.geometry.PinholeCamera;
  import com.irurueta.geometry.Point2D;
  import com.irurueta.geometry.Point3D;
  import com.irurueta.numerical.robust.RANSACRobustEstimator;
  import com.irurueta.numerical.robust.RANSACRobustEstimatorListener;
  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;
  
  /**
   * Finds the best pinhole camera for provided collections of matched 2D/3D
   * points using RANSAC algorithm.
   */
  @SuppressWarnings("DuplicatedCode")
  public class RANSACDLTPointCorrespondencePinholeCameraRobustEstimator extends
          DLTPointCorrespondencePinholeCameraRobustEstimator {
  
      /**
       * Constant defining default threshold to determine whether points are
       * inliers or not.
       * By default, 1.0 is considered a good value for cases where measures are
       * done on pixels, since typically the minimum resolution is 1 pixel.
       */
      public static final double DEFAULT_THRESHOLD = 1.0;
  
      /**
       * Minimum value that can be set as threshold.
       * Threshold must be strictly greater than 0.0.
       */
      public static final double MIN_THRESHOLD = 0.0;
  
      /**
       * Indicates that by default inliers will only be computed but not kept.
       */
      public static final boolean DEFAULT_COMPUTE_AND_KEEP_INLIERS = false;
  
      /**
       * Indicates that by default residuals will only be computed but not kept.
       */
      public static final boolean DEFAULT_COMPUTE_AND_KEEP_RESIDUALS = false;
  
      /**
       * Threshold to determine whether points are inliers or not when testing
       * possible estimation solutions.
       * The threshold refers to the amount of error (i.e. distance) a possible
       * solution has on a matched pair of points.
       */
      private double threshold;
  
      /**
       * Indicates whether inliers must be computed and kept.
       */
      private boolean computeAndKeepInliers;
  
      /**
       * Indicates whether residuals must be computed and kept.
       */
      private boolean computeAndKeepResiduals;
  
      /**
       * Constructor.
       */
      public RANSACDLTPointCorrespondencePinholeCameraRobustEstimator() {
          super();
          threshold = DEFAULT_THRESHOLD;
          computeAndKeepInliers = DEFAULT_COMPUTE_AND_KEEP_INLIERS;
          computeAndKeepResiduals = DEFAULT_COMPUTE_AND_KEEP_RESIDUALS;
      }
  
      /**
       * Constructor with lists of points to be used to estimate a pinhole camera.
       * 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 MIN_NUMBER_OF_POINT_CORRESPONDENCES.
       *
       * @param points3D list of 3D points used to estimate a pinhole camera.
       * @param points2D list of corresponding projected 2D points used to
       *                 estimate a pinhole camera.
      * @throws IllegalArgumentException if provided lists of points don't have
      *                                  the same size or their size is smaller than required minimum size
      *                                  (6 correspondences).
      */
     public RANSACDLTPointCorrespondencePinholeCameraRobustEstimator(
             final List<Point3D> points3D, final List<Point2D> points2D) {
         super(points3D, points2D);
         threshold = DEFAULT_THRESHOLD;
         computeAndKeepInliers = DEFAULT_COMPUTE_AND_KEEP_INLIERS;
         computeAndKeepResiduals = DEFAULT_COMPUTE_AND_KEEP_RESIDUALS;
     }
 
     /**
      * Constructor.
      *
      * @param listener listener to be notified of events such as when estimation
      *                 starts, ends or its progress significantly changes.
      */
     public RANSACDLTPointCorrespondencePinholeCameraRobustEstimator(
             final PinholeCameraRobustEstimatorListener listener) {
         super(listener);
         threshold = DEFAULT_THRESHOLD;
         computeAndKeepInliers = DEFAULT_COMPUTE_AND_KEEP_INLIERS;
         computeAndKeepResiduals = DEFAULT_COMPUTE_AND_KEEP_RESIDUALS;
     }
 
     /**
      * Constructor with listener and lists of points to be used ot estimate a
      * pinhole camera.
      * 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 MIN_NUMBER_OF_POINT_CORRESPONDENCES.
      *
      * @param listener listener to be notified of events such as when estimation
      *                 starts, ends or its progress significantly changes.
      * @param points3D list of 3D points used to estimate a pinhole camera.
      * @param points2D list of corresponding projected 2D points used to
      *                 estimate a pinhole camera.
      * @throws IllegalArgumentException if provided lists of points don't have
      *                                  the same size or their size is smaller than required minimum size
      *                                  (6 correspondences).
      */
     public RANSACDLTPointCorrespondencePinholeCameraRobustEstimator(
             final PinholeCameraRobustEstimatorListener listener,
             final List<Point3D> points3D, final List<Point2D> points2D) {
         super(listener, points3D, points2D);
         threshold = DEFAULT_THRESHOLD;
         computeAndKeepInliers = DEFAULT_COMPUTE_AND_KEEP_INLIERS;
         computeAndKeepResiduals = DEFAULT_COMPUTE_AND_KEEP_RESIDUALS;
     }
 
     /**
      * Returns threshold to determine whether points are inliers or not when
      * testing possible estimation solutions.
      * The threshold refers to the amount of error (i.e. Euclidean distance) a
      * possible solution has on projected 2D points.
      *
      * @return threshold to determine whether points are inliers or not when
      * testing possible estimation solutions.
      */
     public double getThreshold() {
         return threshold;
     }
 
     /**
      * Sets threshold to determine whether points are inliers or not when
      * testing possible estimation solutions.
      * The threshold refers to the amount of error (i.e. Euclidean distance) a
      * possible solution has on projected 2D points.
      *
      * @param threshold threshold to be set.
      * @throws IllegalArgumentException if provided value is equal or less than
      *                                  zero.
      * @throws LockedException          if robust estimator is locked because an
      *                                  estimation is already in progress.
      */
     public void setThreshold(final double threshold) throws LockedException {
         if (isLocked()) {
             throw new LockedException();
         }
         if (threshold <= MIN_THRESHOLD) {
             throw new IllegalArgumentException();
         }
         this.threshold = threshold;
     }
 
     /**
      * Indicates whether inliers must be computed and kept.
      *
      * @return true if inliers must be computed and kept, false if inliers
      * only need to be computed but not kept.
      */
     public boolean isComputeAndKeepInliersEnabled() {
         return computeAndKeepInliers;
     }
 
     /**
      * Specifies whether inliers must be computed and kept.
      *
      * @param computeAndKeepInliers true if inliers must be computed and kept,
      *                              false if inliers only need to be computed but not kept.
      * @throws LockedException if estimator is locked.
      */
     public void setComputeAndKeepInliersEnabled(final boolean computeAndKeepInliers) throws LockedException {
         if (isLocked()) {
             throw new LockedException();
         }
         this.computeAndKeepInliers = computeAndKeepInliers;
     }
 
     /**
      * Indicates whether residuals must be computed and kept.
      *
      * @return true if residuals must be computed and kept, false if residuals
      * only need to be computed but not kept.
      */
     public boolean isComputeAndKeepResidualsEnabled() {
         return computeAndKeepResiduals;
     }
 
     /**
      * Specifies whether residuals must be computed and kept.
      *
      * @param computeAndKeepResiduals true if residuals must be computed and
      *                                kept, false if residuals only need to be computed but not kept.
      * @throws LockedException if estimator is locked.
      */
     public void setComputeAndKeepResidualsEnabled(final boolean computeAndKeepResiduals) throws LockedException {
         if (isLocked()) {
             throw new LockedException();
         }
         this.computeAndKeepResiduals = computeAndKeepResiduals;
     }
 
     /**
      * Estimates a pinhole camera using a robust estimator and
      * the best set of matched 2D/3D point correspondences found using the
      * robust estimator.
      *
      * @return a pinhole camera.
      * @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).
      */
     @Override
     public PinholeCamera estimate() throws LockedException, NotReadyException, RobustEstimatorException {
         if (isLocked()) {
             throw new LockedException();
         }
         if (!isReady()) {
             throw new NotReadyException();
         }
 
         // pinhole camera estimator using DLT (Direct Linear Transform) algorithm
         final var nonRobustEstimator = new DLTPointCorrespondencePinholeCameraEstimator();
 
         nonRobustEstimator.setLMSESolutionAllowed(false);
         nonRobustEstimator.setPointCorrespondencesNormalized(normalizeSubsetPointCorrespondences);
 
         // suggestions
         nonRobustEstimator.setSuggestSkewnessValueEnabled(isSuggestSkewnessValueEnabled());
         nonRobustEstimator.setSuggestedSkewnessValue(getSuggestedSkewnessValue());
         nonRobustEstimator.setSuggestHorizontalFocalLengthEnabled(isSuggestHorizontalFocalLengthEnabled());
         nonRobustEstimator.setSuggestedHorizontalFocalLengthValue(getSuggestedHorizontalFocalLengthValue());
         nonRobustEstimator.setSuggestVerticalFocalLengthEnabled(isSuggestVerticalFocalLengthEnabled());
         nonRobustEstimator.setSuggestedVerticalFocalLengthValue(getSuggestedVerticalFocalLengthValue());
         nonRobustEstimator.setSuggestAspectRatioEnabled(isSuggestAspectRatioEnabled());
         nonRobustEstimator.setSuggestedAspectRatioValue(getSuggestedAspectRatioValue());
         nonRobustEstimator.setSuggestPrincipalPointEnabled(isSuggestPrincipalPointEnabled());
         nonRobustEstimator.setSuggestedPrincipalPointValue(getSuggestedPrincipalPointValue());
         nonRobustEstimator.setSuggestRotationEnabled(isSuggestRotationEnabled());
         nonRobustEstimator.setSuggestedRotationValue(getSuggestedRotationValue());
         nonRobustEstimator.setSuggestCenterEnabled(isSuggestCenterEnabled());
         nonRobustEstimator.setSuggestedCenterValue(getSuggestedCenterValue());
 
         final var innerEstimator = new RANSACRobustEstimator<>(new RANSACRobustEstimatorListener<PinholeCamera>() {
 
             // point to be reused when computing residuals
             private final Point2D testPoint = Point2D.create(CoordinatesType.HOMOGENEOUS_COORDINATES);
 
             // 3D points for a subset of samples
             private final List<Point3D> subset3D = new ArrayList<>();
 
             // 2D points for a subset of samples
             private final List<Point2D> subset2D = new ArrayList<>();
 
             @Override
             public double getThreshold() {
                 return threshold;
             }
 
             @Override
             public int getTotalSamples() {
                 return points3D.size();
             }
 
             @Override
             public int getSubsetSize() {
                 return PointCorrespondencePinholeCameraRobustEstimator.MIN_NUMBER_OF_POINT_CORRESPONDENCES;
             }
 
             @Override
             public void estimatePreliminarSolutions(final int[] samplesIndices, final List<PinholeCamera> solutions) {
                 subset3D.clear();
                 subset3D.add(points3D.get(samplesIndices[0]));
                 subset3D.add(points3D.get(samplesIndices[1]));
                 subset3D.add(points3D.get(samplesIndices[2]));
                 subset3D.add(points3D.get(samplesIndices[3]));
                 subset3D.add(points3D.get(samplesIndices[4]));
                 subset3D.add(points3D.get(samplesIndices[5]));
 
                 subset2D.clear();
                 subset2D.add(points2D.get(samplesIndices[0]));
                 subset2D.add(points2D.get(samplesIndices[1]));
                 subset2D.add(points2D.get(samplesIndices[2]));
                 subset2D.add(points2D.get(samplesIndices[3]));
                 subset2D.add(points2D.get(samplesIndices[4]));
                 subset2D.add(points2D.get(samplesIndices[5]));
 
                 try {
                     nonRobustEstimator.setLists(subset3D, subset2D);
 
                     final var cam = nonRobustEstimator.estimate();
                     solutions.add(cam);
                 } catch (final Exception e) {
                     // if points configuration is degenerate, no solution is added
                 }
             }
 
             @Override
             public double computeResidual(final PinholeCamera currentEstimation, final int i) {
                 // pick i-th points
                 final var point3D = points3D.get(i);
                 final var point2D = points2D.get(i);
 
                 // project point3D into test point
                 currentEstimation.project(point3D, testPoint);
 
                 // compare test point and 2D point
                 return testPoint.distanceTo(point2D);
             }
 
             @Override
             public boolean isReady() {
                 return RANSACDLTPointCorrespondencePinholeCameraRobustEstimator.this.isReady();
             }
 
             @Override
             public void onEstimateStart(final RobustEstimator<PinholeCamera> estimator) {
                 if (listener != null) {
                     listener.onEstimateStart(RANSACDLTPointCorrespondencePinholeCameraRobustEstimator.this);
                 }
             }
 
             @Override
             public void onEstimateEnd(final RobustEstimator<PinholeCamera> estimator) {
                 if (listener != null) {
                     listener.onEstimateEnd(RANSACDLTPointCorrespondencePinholeCameraRobustEstimator.this);
                 }
             }
 
             @Override
             public void onEstimateNextIteration(final RobustEstimator<PinholeCamera> estimator, final int iteration) {
                 if (listener != null) {
                     listener.onEstimateNextIteration(
                             RANSACDLTPointCorrespondencePinholeCameraRobustEstimator.this, iteration);
                 }
             }
 
             @Override
             public void onEstimateProgressChange(final RobustEstimator<PinholeCamera> estimator, final float progress) {
                 if (listener != null) {
                     listener.onEstimateProgressChange(
                             RANSACDLTPointCorrespondencePinholeCameraRobustEstimator.this, progress);
                 }
             }
         });
 
         try {
             locked = true;
             inliersData = null;
             innerEstimator.setComputeAndKeepInliersEnabled(computeAndKeepInliers || refineResult);
             innerEstimator.setComputeAndKeepResidualsEnabled(computeAndKeepResiduals || refineResult);
             innerEstimator.setConfidence(confidence);
             innerEstimator.setMaxIterations(maxIterations);
             innerEstimator.setProgressDelta(progressDelta);
             final var result = innerEstimator.estimate();
             inliersData = innerEstimator.getInliersData();
             return attemptRefine(result, nonRobustEstimator.getMaxSuggestionWeight());
         } 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.RANSAC;
     }
 
     /**
      * 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.
      */
     @Override
     protected double getRefinementStandardDeviation() {
         return threshold;
     }
 }