/*
    * Copyright (C) 2018 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.navigation.indoor.radiosource;
  
  import com.irurueta.geometry.Point3D;
  import com.irurueta.navigation.LockedException;
  import com.irurueta.navigation.NotReadyException;
  import com.irurueta.navigation.indoor.RadioSource;
  import com.irurueta.navigation.indoor.RangingReadingLocated;
  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.List;
  
  /**
   * Robustly estimated 3D position of a radio source (e.g. Wi-Fi
   * access point or bluetooth beacon), by discarding outliers using LMedS
   * algorithm.
   *
   * @param <S> a {@link RadioSource} type.
   */
  public class LMedSRobustRangingRadioSourceEstimator3D<S extends RadioSource> extends
          RobustRangingRadioSourceEstimator3D<S> {
  
      /**
       * Default value to be used for stop threshold. Stop threshold can be used to
       * avoid keeping the algorithm unnecessarily 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-4;
  
      /**
       * 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 = DEFAULT_STOP_THRESHOLD;
  
      /**
       * Constructor.
       */
      public LMedSRobustRangingRadioSourceEstimator3D() {
          super();
      }
  
      /**
       * Constructor.
       * Sets radio signal ranging readings belonging to the same radio source.
       *
       * @param readings radio signal ranging readings belonging to the same
       *                 radio source.
       * @throws IllegalArgumentException if readings are not valid.
       */
      public LMedSRobustRangingRadioSourceEstimator3D(final List<? extends RangingReadingLocated<S, Point3D>> readings) {
          super(readings);
     }
 
     /**
      * Constructor.
      *
      * @param listener listener in charge of attending events raised by this instance.
      */
     public LMedSRobustRangingRadioSourceEstimator3D(
             final RobustRangingRadioSourceEstimatorListener<S, Point3D> listener) {
         super(listener);
     }
 
     /**
      * Constructor.
      * Sets radio signal readings belonging to the same radio source.
      *
      * @param readings radio signal readings belonging to the same radio source.
      * @param listener listener in charge of attending events raised by this instance.
      * @throws IllegalArgumentException if readings are not valid.
      */
     public LMedSRobustRangingRadioSourceEstimator3D(
             final List<? extends RangingReadingLocated<S, Point3D>> readings,
             final RobustRangingRadioSourceEstimatorListener<S, Point3D> listener) {
         super(readings, listener);
     }
 
     /**
      * Constructor.
      *
      * @param initialPosition initial position to start the estimation or radio
      *                        source position.
      */
     public LMedSRobustRangingRadioSourceEstimator3D(final Point3D initialPosition) {
         super(initialPosition);
     }
 
     /**
      * Constructor.
      * <p>
      * Sets radio signal readings belonging to the same radio source.
      *
      * @param readings        radio signal readings belonging to the same radio source.
      * @param initialPosition initial position to start the estimation of radio
      *                        source position.
      * @throws IllegalArgumentException if readings are not valid.
      */
     public LMedSRobustRangingRadioSourceEstimator3D(
             final List<? extends RangingReadingLocated<S, Point3D>> readings, final Point3D initialPosition) {
         super(readings, initialPosition);
     }
 
     /**
      * Constructor.
      *
      * @param initialPosition initial position to start the estimation of radio
      *                        source position.
      * @param listener        listener in charge of attending events raised by this instance.
      */
     public LMedSRobustRangingRadioSourceEstimator3D(
             final Point3D initialPosition, final RobustRangingRadioSourceEstimatorListener<S, Point3D> listener) {
         super(initialPosition, listener);
     }
 
     /**
      * Constructor.
      * Sets radio signal ranging readings belonging to the same radio source.
      *
      * @param readings        radio signal ranging readings belonging to the same radio source.
      * @param initialPosition initial position to start the estimation of radio source
      *                        position.
      * @param listener        listener in charge of attending events raised by this instance.
      * @throws IllegalArgumentException if readings are not valid.
      */
     public LMedSRobustRangingRadioSourceEstimator3D(
             final List<? extends RangingReadingLocated<S, Point3D>> readings, final Point3D initialPosition,
             final RobustRangingRadioSourceEstimatorListener<S, Point3D> listener) {
         super(readings, initialPosition, listener);
     }
 
     /**
      * 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 to iterate
      * 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 to iterate
      * 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 this solver is locked.
      */
     public void setStopThreshold(final double stopThreshold) throws LockedException {
         if (isLocked()) {
             throw new LockedException();
         }
         if (stopThreshold <= MIN_STOP_THRESHOLD) {
             throw new IllegalArgumentException();
         }
 
         this.stopThreshold = stopThreshold;
     }
 
     /**
      * Robustly estimates position for a radio source.
      *
      * @throws LockedException          if instance is busy during estimation.
      * @throws NotReadyException        if estimator is not ready.
      * @throws RobustEstimatorException if estimation fails for any reason
      *                                  (i.e. numerical instability, no solution available, etc).
      */
     @SuppressWarnings("DuplicatedCode")
     @Override
     public void estimate() throws LockedException, NotReadyException,
             RobustEstimatorException {
         if (isLocked()) {
             throw new LockedException();
         }
         if (!isReady()) {
             throw new NotReadyException();
         }
 
         final var innerEstimator = new LMedSRobustEstimator<>(new LMedSRobustEstimatorListener<Solution<Point3D>>() {
             @Override
             public int getTotalSamples() {
                 return readings.size();
             }
 
             @Override
             public int getSubsetSize() {
                 return Math.max(preliminarySubsetSize, getMinReadings());
             }
 
             @Override
             public void estimatePreliminarSolutions(
                     final int[] sampleIndices, final List<Solution<Point3D>> solutions) {
                 solvePreliminarySolutions(sampleIndices, solutions);
             }
 
             @Override
             public double computeResidual(final Solution<Point3D> currentEstimation, final int i) {
                 return residual(currentEstimation, i);
             }
 
             @Override
             public boolean isReady() {
                 return LMedSRobustRangingRadioSourceEstimator3D.this.isReady();
             }
 
             @Override
             public void onEstimateStart(final RobustEstimator<Solution<Point3D>> estimator) {
                 // no action needed
             }
 
             @Override
             public void onEstimateEnd(final RobustEstimator<Solution<Point3D>> estimator) {
                 // no action needed
             }
 
             @Override
             public void onEstimateNextIteration(
                     final RobustEstimator<Solution<Point3D>> estimator, final int iteration) {
                 if (listener != null) {
                     listener.onEstimateNextIteration(
                             LMedSRobustRangingRadioSourceEstimator3D.this, iteration);
                 }
             }
 
             @Override
             public void onEstimateProgressChange(
                     final RobustEstimator<Solution<Point3D>> estimator, final float progress) {
                 if (listener != null) {
                     listener.onEstimateProgressChange(LMedSRobustRangingRadioSourceEstimator3D.this, progress);
                 }
             }
         });
 
         try {
             locked = true;
 
             if (listener != null) {
                 listener.onEstimateStart(this);
             }
 
             inliersData = null;
             innerEstimator.setConfidence(confidence);
             innerEstimator.setMaxIterations(maxIterations);
             innerEstimator.setProgressDelta(progressDelta);
             final var result = innerEstimator.estimate();
             inliersData = innerEstimator.getInliersData();
             attemptRefine(result);
 
             if (listener != null) {
                 listener.onEstimateEnd(this);
             }
 
         } 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;
     }
 }