/*
    * Copyright (C) 2016 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.calibration.estimators;
  
  import com.irurueta.ar.calibration.DualAbsoluteQuadric;
  import com.irurueta.geometry.PinholeCamera;
  import com.irurueta.geometry.estimators.LockedException;
  import com.irurueta.geometry.estimators.NotReadyException;
  import com.irurueta.numerical.robust.PROMedSRobustEstimator;
  import com.irurueta.numerical.robust.PROMedSRobustEstimatorListener;
  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 dual absolute quadric (DAQ) for provided collection of
   * cameras using PROMedS algorithm.
   */
  public class PROMedSDualAbsoluteQuadricRobustEstimator extends DualAbsoluteQuadricRobustEstimator {
  
      /**
       * 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.
       * Threshold is defined by the equations used to estimate the DAQ depending
       * on the required settings (zero skewness, principal point at origin, and
       * known aspect ratio).
       */
      public static final double DEFAULT_STOP_THRESHOLD = 1e-6;
  
      /**
       * Minimum value that can be set as stop threshold.
       * Threshold must be strictly greater than 0.0.
       */
      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 PROMedS algorithm iterating
       * too many times in cases where samples have a very similar accuracy.
       * For instance, in cases where proportion of inliers 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;
  
      /**
       * Quality scores corresponding to each provided camera.
       * The larger the score value the better the quality of the sample.
       */
      private double[] qualityScores;
  
      /**
       * Constructor.
       */
      public PROMedSDualAbsoluteQuadricRobustEstimator() {
          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 PROMedSDualAbsoluteQuadricRobustEstimator(final DualAbsoluteQuadricRobustEstimatorListener listener) {
          super(listener);
          stopThreshold = DEFAULT_STOP_THRESHOLD;
      }
  
      /**
       * Constructor.
       *
      * @param cameras list of cameras used to estimate the dual absolute quadric
      *                (DAC), which can be used to obtain pinhole camera intrinsic parameters.
      * @throws IllegalArgumentException if not enough cameras are provided for
      *                                  default settings. Hence, at least 2 cameras must be provided.
      */
     public PROMedSDualAbsoluteQuadricRobustEstimator(final List<PinholeCamera> cameras) {
         super(cameras);
         stopThreshold = DEFAULT_STOP_THRESHOLD;
     }
 
     /**
      * Constructor.
      *
      * @param cameras  list of cameras used to estimate the dual absolute quadric
      *                 (DAQ), which can be used to obtain pinhole camera intrinsic parameters.
      * @param listener listener to be notified of events such as when estimation
      *                 starts, ends or estimation progress changes.
      * @throws IllegalArgumentException if not enough cameras are provided for
      *                                  default settings. Hence, at least 2 cameras must be provided.
      */
     public PROMedSDualAbsoluteQuadricRobustEstimator(
             final List<PinholeCamera> cameras, final DualAbsoluteQuadricRobustEstimatorListener listener) {
         super(cameras, listener);
         stopThreshold = DEFAULT_STOP_THRESHOLD;
     }
 
     /**
      * Constructor.
      *
      * @param qualityScores quality scores corresponding to each provided
      *                      camera.
      * @throws IllegalArgumentException if provided quality scores length is
      *                                  smaller than required number of homographies for default
      *                                  settings (i.e. 2 cameras).
      */
     public PROMedSDualAbsoluteQuadricRobustEstimator(final double[] qualityScores) {
         this();
         internalSetQualityScores(qualityScores);
     }
 
     /**
      * Constructor.
      *
      * @param qualityScores quality scores corresponding to each provided
      *                      camera.
      * @param listener      listener to be notified of events such as when estimation
      *                      starts, ends or its progress significantly changes.
      * @throws IllegalArgumentException if provided quality scores length is
      *                                  smaller than required number of cameras for default settings (i.e.
      *                                  2 cameras).
      */
     public PROMedSDualAbsoluteQuadricRobustEstimator(
             final double[] qualityScores, final DualAbsoluteQuadricRobustEstimatorListener listener) {
         this(listener);
         internalSetQualityScores(qualityScores);
     }
 
     /**
      * Constructor.
      *
      * @param cameras       list of cameras used to estimate the dual absolute quadric
      *                      (DAQ), which can be used to obtain pinhole camera intrinsic parameters.
      * @param qualityScores quality scores corresponding to each provided
      *                      camera.
      * @throws IllegalArgumentException if not enough cameras are provided for
      *                                  default settings (i.e. 2 cameras) or quality scores and cameras
      *                                  don't have the same size.
      */
     public PROMedSDualAbsoluteQuadricRobustEstimator(final List<PinholeCamera> cameras, final double[] qualityScores) {
         this(cameras);
         internalSetQualityScores(qualityScores);
     }
 
     /**
      * Constructor.
      *
      * @param cameras       list of cameras used to estimate the dual absolute quadric
      *                      (DAQ), which can be used to obtain pinhole camera intrinsic parameters.
      * @param qualityScores quality scores corresponding to each provided
      *                      camera.
      * @param listener      listener to be notified of events such as when estimation
      *                      starts, ends or estimation progress changes.
      * @throws IllegalArgumentException if not enough cameras are provided for
      *                                  default settings (i.e. 2 cameras) or quality scores and cameras
      *                                  don't have the same size.
      */
     public PROMedSDualAbsoluteQuadricRobustEstimator(
             final List<PinholeCamera> cameras, final double[] qualityScores,
             final DualAbsoluteQuadricRobustEstimatorListener listener) {
         this(cameras, listener);
         internalSetQualityScores(qualityScores);
     }
 
     /**
      * 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 PROMedS 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 PROMedS 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;
     }
 
     /**
      * Returns quality scores corresponding to each provided camera.
      * The larger the score value the better the quality of the sampled
      * camera.
      *
      * @return quality scores corresponding to each camera.
      */
     @Override
     public double[] getQualityScores() {
         return qualityScores;
     }
 
     /**
      * Sets quality scores corresponding to each provided camera.
      * The larger the score value the better the quality of the sampled
      * camera.
      *
      * @param qualityScores quality scores corresponding to each camera.
      * @throws LockedException          if robust estimator is locked because an
      *                                  estimation is already in progress.
      * @throws IllegalArgumentException if provided quality scores length is
      *                                  smaller than minimum required number of cameras (i.e. 2 cameras).
      */
     @Override
     public void setQualityScores(final double[] qualityScores) throws LockedException {
         if (isLocked()) {
             throw new LockedException();
         }
         internalSetQualityScores(qualityScores);
     }
 
     /**
      * Indicates if estimator is ready to start the DAQ estimation.
      * This is true when input data (i.e. cameras) is provided and list contains
      * at least the minimum number of required cameras, and also quality scores
      * are provided.
      *
      * @return true if estimator is ready, false otherwise.
      */
     @Override
     public boolean isReady() {
         return super.isReady() && qualityScores != null && qualityScores.length == cameras.size();
     }
 
     /**
      * Estimates the Dual Absolute Quadric using provided cameras.
      *
      * @return estimated Dual Absolute Quadric (DAQ).
      * @throws LockedException          if robust estimator is locked.
      * @throws NotReadyException        if no valid input data has already been
      *                                  provided.
      * @throws RobustEstimatorException if estimation fails for any reason
      *                                  (i.e. numerical instability, no solution available, etc).
      */
     @SuppressWarnings("DuplicatedCode")
     @Override
     public DualAbsoluteQuadric estimate() throws LockedException, NotReadyException, RobustEstimatorException {
         if (isLocked()) {
             throw new LockedException();
         }
         if (!isReady()) {
             throw new NotReadyException();
         }
 
         final var innerEstimator = new PROMedSRobustEstimator<DualAbsoluteQuadric>(new PROMedSRobustEstimatorListener<>() {
 
             // subset of cameras picked on each iteration
             private final List<PinholeCamera> subsetCameras = new ArrayList<>();
 
             @Override
             public double getThreshold() {
                 return stopThreshold;
             }
 
             @Override
             public int getTotalSamples() {
                 return cameras.size();
             }
 
             @Override
             public int getSubsetSize() {
                 return daqEstimator.getMinNumberOfRequiredCameras();
             }
 
             @Override
             public void estimatePreliminarSolutions(
                     final int[] samplesIndices, final List<DualAbsoluteQuadric> solutions) {
                 subsetCameras.clear();
                 for (final var samplesIndex : samplesIndices) {
                     subsetCameras.add(cameras.get(samplesIndex));
                 }
 
                 try {
                     daqEstimator.setLMSESolutionAllowed(false);
                     daqEstimator.setCameras(subsetCameras);
 
                     final var daq = daqEstimator.estimate();
                     solutions.add(daq);
                 } catch (final Exception e) {
                     // if anything fails, no solution is added
                 }
             }
 
             @Override
             public double computeResidual(final DualAbsoluteQuadric currentEstimation, final int i) {
                 return residual(currentEstimation, cameras.get(i));
             }
 
             @Override
             public boolean isReady() {
                 return PROMedSDualAbsoluteQuadricRobustEstimator.this.isReady();
             }
 
             @Override
             public void onEstimateStart(final RobustEstimator<DualAbsoluteQuadric> estimator) {
                 if (listener != null) {
                     listener.onEstimateStart(PROMedSDualAbsoluteQuadricRobustEstimator.this);
                 }
             }
 
             @Override
             public void onEstimateEnd(final RobustEstimator<DualAbsoluteQuadric> estimator) {
                 if (listener != null) {
                     listener.onEstimateEnd(PROMedSDualAbsoluteQuadricRobustEstimator.this);
                 }
             }
 
             @Override
             public void onEstimateNextIteration(
                     final RobustEstimator<DualAbsoluteQuadric> estimator, final int iteration) {
                 if (listener != null) {
                     listener.onEstimateNextIteration(PROMedSDualAbsoluteQuadricRobustEstimator.this,
                             iteration);
                 }
             }
 
             @Override
             public void onEstimateProgressChange(
                     final RobustEstimator<DualAbsoluteQuadric> estimator, final float progress) {
                 if (listener != null) {
                     listener.onEstimateProgressChange(PROMedSDualAbsoluteQuadricRobustEstimator.this,
                             progress);
                 }
             }
 
             @Override
             public double[] getQualityScores() {
                 return qualityScores;
             }
         });
 
         try {
             locked = true;
             innerEstimator.setConfidence(confidence);
             innerEstimator.setMaxIterations(maxIterations);
             innerEstimator.setProgressDelta(progressDelta);
             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.PROMEDS;
     }
 
     /**
      * Sets quality scores corresponding to each camera.
      * This method is used internally and does not check whether instance is
      * locked or not.
      *
      * @param qualityScores quality scores to be set.
      * @throws IllegalArgumentException if provided quality scores length is
      *                                  smaller than the minimum number of required homographies for
      *                                  current settings.
      */
     private void internalSetQualityScores(final double[] qualityScores) {
         if (qualityScores.length < daqEstimator.getMinNumberOfRequiredCameras()) {
             throw new IllegalArgumentException();
         }
 
         this.qualityScores = qualityScores;
     }
 }