/*
    * Licensed to the Apache Software Foundation (ASF) under one or more
    * contributor license agreements.  See the NOTICE file distributed with
    * this work for additional information regarding copyright ownership.
    * The ASF licenses this file to You 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
    *
    *      https://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.
   */
  
  /*
   * This is not the original file distributed by the Apache Software Foundation
   * It has been modified by the Hipparchus project
   */
  package org.hipparchus.stat.descriptive.rank;
  
  import java.io.IOException;
  import java.io.ObjectInputStream;
  import java.io.Serializable;
  import java.text.DecimalFormat;
  import java.util.ArrayList;
  import java.util.Arrays;
  import java.util.Collection;
  import java.util.Collections;
  import java.util.List;
  
  import org.hipparchus.analysis.UnivariateFunction;
  import org.hipparchus.analysis.interpolation.LinearInterpolator;
  import org.hipparchus.analysis.interpolation.NevilleInterpolator;
  import org.hipparchus.analysis.interpolation.UnivariateInterpolator;
  import org.hipparchus.exception.LocalizedCoreFormats;
  import org.hipparchus.exception.MathIllegalArgumentException;
  import org.hipparchus.stat.descriptive.AbstractStorelessUnivariateStatistic;
  import org.hipparchus.stat.descriptive.StorelessUnivariateStatistic;
  import org.hipparchus.util.MathArrays;
  import org.hipparchus.util.MathUtils;
  import org.hipparchus.util.Precision;
  
  /**
   * A {@link StorelessUnivariateStatistic} estimating percentiles using the
   * <a href=http://www.cs.wustl.edu/~jain/papers/ftp/psqr.pdf>P<SUP>2</SUP></a>
   * Algorithm as explained by <a href=http://www.cse.wustl.edu/~jain/>Raj
   * Jain</a> and Imrich Chlamtac in
   * <a href=http://www.cse.wustl.edu/~jain/papers/psqr.htm>P<SUP>2</SUP> Algorithm
   * for Dynamic Calculation of Quantiles and Histogram Without Storing
   * Observations</a>.
   * <p>
   * Note: This implementation is not synchronized and produces an approximate
   * result. For small samples, where data can be stored and processed in memory,
   * {@link Percentile} should be used.
   */
  public class PSquarePercentile extends AbstractStorelessUnivariateStatistic
      implements StorelessUnivariateStatistic, Serializable {
  
      /** The maximum array size used for psquare algorithm */
      private static final int PSQUARE_CONSTANT = 5;
  
      /**
       * A Default quantile needed in case if user prefers to use default no
       * argument constructor.
       */
      private static final double DEFAULT_QUANTILE_DESIRED = 50d;
  
      /** Serial ID */
      private static final long serialVersionUID = 20150412L;
  
      /** A decimal formatter for print convenience */
      private static final DecimalFormat DECIMAL_FORMAT = new DecimalFormat("00.00");
  
      /**
       * Initial list of 5 numbers corresponding to 5 markers. <b>NOTE:</b>watch
       * out for the add methods that are overloaded
       */
      private final List<Double> initialFive = new FixedCapacityList<>(PSQUARE_CONSTANT);
  
      /**
       * The quantile needed should be in range of 0-1. The constructor
       * {@link #PSquarePercentile(double)} ensures that passed in percentile is
       * divided by 100.
       */
      private final double quantile;
  
      /**
       * lastObservation is the last observation value/input sample. No need to
       * serialize.
       */
      private transient double lastObservation;
  
      /**
       * Markers is the marker collection object which comes to effect
       * only after 5 values are inserted
       */
     private PSquareMarkers markers;
 
     /**
      * Computed p value (i,e percentile value of data set hither to received)
      */
     private double pValue = Double.NaN;
 
     /**
      * Counter to count the values/observations accepted into this data set
      */
     private long countOfObservations;
 
     /**
      * Constructs a PSquarePercentile with the specific percentile value.
      * @param p the percentile
      * @throws MathIllegalArgumentException  if p is not greater than 0 and less
      * than or equal to 100
      */
     public PSquarePercentile(final double p) {
         if (p > 100 || p < 0) {
             throw new MathIllegalArgumentException(LocalizedCoreFormats.OUT_OF_RANGE,
                                                    p, 0, 100);
         }
         this.quantile = p / 100d;// always set it within (0,1]
     }
 
     /**
      * Default constructor that assumes a {@link #DEFAULT_QUANTILE_DESIRED
      * default quantile} needed.
      */
     PSquarePercentile() {
         this(DEFAULT_QUANTILE_DESIRED);
     }
 
     /**
      * Copy constructor, creates a new {@code PSquarePercentile} identical
      * to the {@code original}.
      *
      * @param original the {@code PSquarePercentile} instance to copy
      * @throws org.hipparchus.exception.NullArgumentException if original is null
      */
     public PSquarePercentile(PSquarePercentile original) {
         super();
 
         this.quantile = original.quantile;
 
         if (original.markers != null) {
             this.markers = original.markers.copySelf();
         }
 
         this.countOfObservations = original.countOfObservations;
         this.pValue = original.pValue;
         this.initialFive.addAll(original.initialFive);
     }
 
     /** {@inheritDoc} */
     @Override
     public int hashCode() {
         double result = getResult();
         result = Double.isNaN(result) ? 37 : result;
         final double markersHash = markers == null ? 0 : markers.hashCode();
         final double[] toHash = {result, quantile, markersHash, countOfObservations};
         return Arrays.hashCode(toHash);
     }
 
     /**
      * Returns true iff {@code o} is a {@code PSquarePercentile} returning the
      * same values as this for {@code getResult()} and {@code getN()} and also
      * having equal markers
      *
      * @param o object to compare
      * @return true if {@code o} is a {@code PSquarePercentile} with
      * equivalent internal state
      */
     @Override
     public boolean equals(Object o) {
         boolean result = false;
         if (this == o) {
             result = true;
         } else if (o instanceof PSquarePercentile) {
             PSquarePercentile that = (PSquarePercentile) o;
             boolean isNotNull = markers != null && that.markers != null;
             boolean isNull = markers == null && that.markers == null;
             result = isNotNull ? markers.equals(that.markers) : isNull;
             // markers as in the case of first
             // five observations
             result = result && getN() == that.getN();
         }
         return result;
     }
 
     /**
      * {@inheritDoc}The internal state updated due to the new value in this
      * context is basically of the marker positions and computation of the
      * approximate quantile.
      *
      * @param observation the observation currently being added.
      */
     @Override
     public void increment(final double observation) {
         // Increment counter
         countOfObservations++;
 
         // Store last observation
         this.lastObservation = observation;
 
         // 0. Use Brute force for <5
         if (markers == null) {
             if (initialFive.add(observation)) {
                 Collections.sort(initialFive);
                 pValue = initialFive.get((int) (quantile * (initialFive.size() - 1)));
                 return;
             }
             // 1. Initialize once after 5th observation
             markers = newMarkers(initialFive, quantile);
         }
         // 2. process a Data Point and return pValue
         pValue = markers.processDataPoint(observation);
     }
 
     /**
      * Returns a string containing the last observation, the current estimate
      * of the quantile and all markers.
      *
      * @return string representation of state data
      */
     @Override
     public String toString() {
         synchronized (this) {
             synchronized (DECIMAL_FORMAT) {
                 if (markers == null) {
                     return String.format("obs=%s pValue=%s",
                                          DECIMAL_FORMAT.format(lastObservation),
                                          DECIMAL_FORMAT.format(pValue));
                 } else {
                     return String.format("obs=%s markers=%s",
                                          DECIMAL_FORMAT.format(lastObservation), markers.toString());
                 }
             }
         }
    }
 
     /** {@inheritDoc} */
     @Override
     public long getN() {
         return countOfObservations;
     }
 
     /** {@inheritDoc} */
     @Override
     public PSquarePercentile copy() {
         return new PSquarePercentile(this);
     }
 
     /**
      * Returns the quantile estimated by this statistic in the range [0.0-1.0]
      *
      * @return quantile estimated by {@link #getResult()}
      */
     public double quantile() {
         return quantile;
     }
 
     /**
      * {@inheritDoc}. This basically clears all the markers, the
      * initialFive list and sets countOfObservations to 0.
      */
     @Override
     public void clear() {
         markers = null;
         initialFive.clear();
         countOfObservations = 0L;
         pValue = Double.NaN;
     }
 
     /**
      * {@inheritDoc}
      */
     @Override
     public double getResult() {
         if (Double.compare(quantile, 1d) == 0) {
             pValue = maximum();
         } else if (Double.compare(quantile, 0d) == 0) {
             pValue = minimum();
         }
         return pValue;
     }
 
     /** Get quantile estimated by this statistic.
      * @return the quantile estimated by this statistic
      */
     public double getQuantile() {
         return quantile;
     }
 
     /** Get maximum in the data set added to this statistic.
      * @return maximum in the data set added to this statistic
      */
     private double maximum() {
         double val = Double.NaN;
         if (markers != null) {
             val = markers.height(PSQUARE_CONSTANT);
         } else if (!initialFive.isEmpty()) {
             val = initialFive.get(initialFive.size() - 1);
         }
         return val;
     }
 
     /** Get minimum in the data set added to this statistic.
      * @return minimum in the data set added to this statistic
      */
     private double minimum() {
         double val = Double.NaN;
         if (markers != null) {
             val = markers.height(1);
         } else if (!initialFive.isEmpty()) {
             val = initialFive.get(0);
         }
         return val;
     }
 
     /**
      * Markers is an encapsulation of the five markers/buckets as indicated in
      * the original works.
      */
     private static class Markers implements PSquareMarkers, Serializable {
         /**
          * Serial version id
          */
         private static final long serialVersionUID = 1L;
 
         /** Low marker index */
         private static final int LOW = 2;
 
         /** High marker index */
         private static final int HIGH = 4;
 
         /**
          * Array of 5+1 Markers (The first marker is dummy just so we
          * can match the rest of indexes [1-5] indicated in the original works
          * which follows unit based index)
          */
         private final Marker[] markerArray;
 
         /**
          * Constructor
          *
          * @param theMarkerArray marker array to be used, a reference to the array will be stored
          */
         private Markers(final Marker[] theMarkerArray) { // NOPMD - storing a reference to the array is intentional and documented here
             MathUtils.checkNotNull(theMarkerArray);
             markerArray = theMarkerArray;
             for (int i = 1; i < PSQUARE_CONSTANT; i++) {
                 markerArray[i].previous(markerArray[i - 1])
                         .next(markerArray[i + 1]).index(i);
             }
             markerArray[0].previous(markerArray[0])
                           .next(markerArray[1])
                           .index(0);
             markerArray[5].previous(markerArray[4])
                           .next(markerArray[5])
                           .index(5);
         }
 
         /**
          * Constructor
          *
          * @param initialFive elements required to build Marker
          * @param p quantile required to be computed
          */
         private Markers(final List<Double> initialFive, final double p) {
             this(createMarkerArray(initialFive, p));
         }
 
         /**
          * Creates a marker array using initial five elements and a quantile
          *
          * @param initialFive list of initial five elements
          * @param p the pth quantile
          * @return Marker array
          */
         private static Marker[] createMarkerArray(
                 final List<Double> initialFive, final double p) {
             final int countObserved =
                     initialFive == null ? -1 : initialFive.size();
             if (countObserved < PSQUARE_CONSTANT) {
                 throw new MathIllegalArgumentException(
                         LocalizedCoreFormats.INSUFFICIENT_OBSERVED_POINTS_IN_SAMPLE,
                         countObserved, PSQUARE_CONSTANT);
             }
             Collections.sort(initialFive);
             return new Marker[] {
                     new Marker(),// Null Marker
                     new Marker(initialFive.get(0), 1, 0, 1),
                     new Marker(initialFive.get(1), 1 + 2 * p, p / 2, 2),
                     new Marker(initialFive.get(2), 1 + 4 * p, p, 3),
                     new Marker(initialFive.get(3), 3 + 2 * p, (1 + p) / 2, 4),
                     new Marker(initialFive.get(4), 5, 1, 5) };
         }
 
         /**
          * {@inheritDoc}
          */
         @Override
         public int hashCode() {
             return Arrays.deepHashCode(markerArray);
         }
 
         /**
          * {@inheritDoc}.This equals method basically checks for marker array to
          * be deep equals.
          *
          * @param o is the other object
          * @return true if the object compares with this object are equivalent
          */
         @Override
         public boolean equals(Object o) {
             boolean result = false;
             if (this == o) {
                 result = true;
             } else if (o instanceof Markers) {
                 Markers that = (Markers) o;
                 result = Arrays.deepEquals(markerArray, that.markerArray);
             }
             return result;
         }
 
         /**
          * Process a data point
          *
          * @param inputDataPoint is the data point passed
          * @return computed percentile
          */
         @Override
         public double processDataPoint(final double inputDataPoint) {
 
             // 1. Find cell and update minima and maxima
             final int kthCell = findCellAndUpdateMinMax(inputDataPoint);
 
             // 2. Increment positions
             incrementPositions(1, kthCell + 1, 5);
 
             // 2a. Update desired position with increments
             updateDesiredPositions();
 
             // 3. Adjust heights of m[2-4] if necessary
             adjustHeightsOfMarkers();
 
             // 4. Return percentile
             return getPercentileValue();
         }
 
         /**
          * Returns the percentile computed thus far.
          *
          * @return height of mid point marker
          */
         @Override
         public double getPercentileValue() {
             return height(3);
         }
 
         /**
          * Finds the cell where the input observation / value fits.
          *
          * @param observation the input value to be checked for
          * @return kth cell (of the markers ranging from 1-5) where observed
          *         sample fits
          */
         private int findCellAndUpdateMinMax(final double observation) {
             if (observation < height(1)) {
                 markerArray[1].markerHeight = observation;
                 return 1;
             } else if (observation < height(2)) {
                 return 1;
             } else if (observation < height(3)) {
                 return 2;
             } else if (observation < height(4)) {
                 return 3;
             } else if (observation <= height(5)) {
                 return 4;
             } else {
                 markerArray[5].markerHeight = observation;
                 return 4;
             }
         }
 
         /**
          * Adjust marker heights by setting quantile estimates to middle markers.
          */
         private void adjustHeightsOfMarkers() {
             for (int i = LOW; i <= HIGH; i++) {
                 estimate(i);
             }
         }
 
         /**
          * {@inheritDoc}
          */
         @Override
         public double estimate(final int index) {
             MathUtils.checkRangeInclusive(index, LOW, HIGH);
             return markerArray[index].estimate();
         }
 
         /**
          * Increment positions by d. Refer to algorithm paper for the
          * definition of d.
          *
          * @param d The increment value for the position
          * @param startIndex start index of the marker array
          * @param endIndex end index of the marker array
          */
         private void incrementPositions(final int d, final int startIndex,
                 final int endIndex) {
             for (int i = startIndex; i <= endIndex; i++) {
                 markerArray[i].incrementPosition(d);
             }
         }
 
         /**
          * Desired positions incremented by bucket width. The bucket width is
          * basically the desired increments.
          */
         private void updateDesiredPositions() {
             for (int i = 1; i < markerArray.length; i++) {
                 markerArray[i].updateDesiredPosition();
             }
         }
 
         /**
          * Sets previous and next markers after default read is done.
          *
          * @param anInputStream the input stream to be deserialized
          * @throws ClassNotFoundException thrown when a desired class not found
          * @throws IOException thrown due to any io errors
          */
         private void readObject(ObjectInputStream anInputStream)
                 throws ClassNotFoundException, IOException {
             // always perform the default de-serialization first
             anInputStream.defaultReadObject();
             // Build links
             for (int i = 1; i < PSQUARE_CONSTANT; i++) {
                 markerArray[i].previous(markerArray[i - 1]).next(markerArray[i + 1]).index(i);
             }
             markerArray[0].previous(markerArray[0]).next(markerArray[1]).index(0);
             markerArray[5].previous(markerArray[4]).next(markerArray[5]).index(5);
         }
 
         /**
          * Return marker height given index
          *
          * @param markerIndex index of marker within (1,6)
          * @return marker height
          */
         @Override
         public double height(final int markerIndex) {
             MathUtils.checkRangeInclusive(markerIndex, 1, markerArray.length - 1);
             return markerArray[markerIndex].markerHeight;
         }
 
         /** {@inheritDoc} */
         @Override
         public Markers copySelf() {
             return new Markers(new Marker[] {
                 new Marker(),
                 markerArray[1].copySelf(),
                 markerArray[2].copySelf(),
                 markerArray[3].copySelf(),
                 markerArray[4].copySelf(),
                 markerArray[5].copySelf()
             });
 
         }
 
         /**
          * Returns string representation of the Marker array.
          *
          * @return Markers as a string
          */
         @Override
         public String toString() {
             return String.format("m1=[%s],m2=[%s],m3=[%s],m4=[%s],m5=[%s]",
                     markerArray[1].toString(), markerArray[2].toString(),
                     markerArray[3].toString(), markerArray[4].toString(),
                     markerArray[5].toString());
         }
 
     }
 
     /**
      * The class modeling the attributes of the marker of the P-square algorithm
      */
     private static class Marker implements Serializable {
 
         /**
          * Serial Version ID
          */
         private static final long serialVersionUID = -3575879478288538431L;
 
         /**
          * The marker index which is just a serial number for the marker in the
          * marker array of 5+1.
          */
         private int index;
 
         /**
          * The integral marker position. Refer to the variable n in the original
          * works.
          */
         private double intMarkerPosition;
 
         /**
          * Desired marker position. Refer to the variable n' in the original
          * works.
          */
         private double desiredMarkerPosition;
 
         /**
          * Marker height or the quantile. Refer to the variable q in the
          * original works.
          */
         private double markerHeight;
 
         /**
          * Desired marker increment. Refer to the variable dn' in the original
          * works.
          */
         private double desiredMarkerIncrement;
 
         /**
          * Next and previous markers for easy linked navigation in loops. this
          * is not serialized as they can be rebuilt during deserialization.
          */
         private transient Marker next;
 
         /**
          * The previous marker links
          */
         private transient Marker previous;
 
         /**
          * Nonlinear interpolator
          */
         private final UnivariateInterpolator nonLinear = new NevilleInterpolator();
 
         /**
          * Linear interpolator which is not serializable
          */
         private transient UnivariateInterpolator linear = new LinearInterpolator();
 
         /**
          * Default constructor
          */
         private Marker() {
             this.next = this.previous = this;
         }
 
         /**
          * Constructor of the marker with parameters
          *
          * @param heightOfMarker represent the quantile value
          * @param makerPositionDesired represent the desired marker position
          * @param markerPositionIncrement represent increments for position
          * @param markerPositionNumber represent the position number of marker
          */
         private Marker(double heightOfMarker, double makerPositionDesired,
                 double markerPositionIncrement, double markerPositionNumber) {
             this();
             this.markerHeight = heightOfMarker;
             this.desiredMarkerPosition = makerPositionDesired;
             this.desiredMarkerIncrement = markerPositionIncrement;
             this.intMarkerPosition = markerPositionNumber;
         }
 
         /**
          * Sets the previous marker.
          *
          * @param previousMarker the previous marker to the current marker in
          *            the array of markers
          * @return this instance
          */
         private Marker previous(final Marker previousMarker) {
             MathUtils.checkNotNull(previousMarker);
             this.previous = previousMarker;
             return this;
         }
 
         /**
          * Sets the next marker.
          *
          * @param nextMarker the next marker to the current marker in the array
          *            of markers
          * @return this instance
          */
         private Marker next(final Marker nextMarker) {
             MathUtils.checkNotNull(nextMarker);
             this.next = nextMarker;
             return this;
         }
 
         /**
          * Sets the index of the marker.
          *
          * @param indexOfMarker the array index of the marker in marker array
          * @return this instance
          */
         private Marker index(final int indexOfMarker) {
             this.index = indexOfMarker;
             return this;
         }
 
         /**
          * Update desired Position with increment.
          */
         private void updateDesiredPosition() {
             desiredMarkerPosition += desiredMarkerIncrement;
         }
 
         /**
          * Increment Position by d.
          *
          * @param d a delta value to increment
          */
         private void incrementPosition(final int d) {
             intMarkerPosition += d;
         }
 
         /**
          * Difference between desired and actual position
          *
          * @return difference between desired and actual position
          */
         private double difference() {
             return desiredMarkerPosition - intMarkerPosition;
         }
 
         /**
          * Estimate the quantile for the current marker.
          *
          * @return estimated quantile
          */
         private double estimate() {
             final double di = difference();
             final boolean isNextHigher =
                     next.intMarkerPosition - intMarkerPosition > 1;
             final boolean isPreviousLower =
                     previous.intMarkerPosition - intMarkerPosition < -1;
 
             if (di >= 1 && isNextHigher || di <= -1 && isPreviousLower) {
                 final int d = di >= 0 ? 1 : -1;
                 final double[] xval = { previous.intMarkerPosition, intMarkerPosition, next.intMarkerPosition };
                 final double[] yval = { previous.markerHeight, markerHeight, next.markerHeight };
                 final double xD = intMarkerPosition + d;
 
                 UnivariateFunction univariateFunction =
                         nonLinear.interpolate(xval, yval);
                 markerHeight = univariateFunction.value(xD);
 
                 // If parabolic estimate is bad then turn linear
                 if (isEstimateBad(yval, markerHeight)) {
                     int delta = xD - xval[1] > 0 ? 1 : -1;
                     final double[] xBad = { xval[1], xval[1 + delta] };
                     final double[] yBad = { yval[1], yval[1 + delta] };
                     MathArrays.sortInPlace(xBad, yBad);// since d can be +/- 1
                     univariateFunction = linear.interpolate(xBad, yBad);
                     markerHeight = univariateFunction.value(xD);
                 }
                 incrementPosition(d);
             }
             return markerHeight;
         }
 
         /**
          * Check if parabolic/nonlinear estimate is bad by checking if the
          * ordinate found is beyond the y[0] and y[2].
          *
          * @param y the array to get the bounds
          * @param yD the estimate
          * @return true if yD is a bad estimate
          */
         private boolean isEstimateBad(final double[] y, final double yD) {
             return yD <= y[0] || yD >= y[2];
         }
 
         /**
          * {@inheritDoc}<i>This equals method checks for marker attributes and
          * as well checks if navigation pointers (next and previous) are the same
          * between this and passed in object</i>
          *
          * @param o Other object
          * @return true if this equals passed in other object o
          */
         @Override
         public boolean equals(Object o) {
             boolean result = false;
             if (this == o) {
                 result = true;
             } else if (o instanceof Marker) {
                 Marker that = (Marker) o;
 
                 result = Double.compare(markerHeight, that.markerHeight) == 0;
                 result =
                         result &&
                                 Double.compare(intMarkerPosition,
                                         that.intMarkerPosition) == 0;
                 result =
                         result &&
                                 Double.compare(desiredMarkerPosition,
                                         that.desiredMarkerPosition) == 0;
                 result =
                         result &&
                                 Double.compare(desiredMarkerIncrement,
                                         that.desiredMarkerIncrement) == 0;
 
                 result = result && next.index == that.next.index;
                 result = result && previous.index == that.previous.index;
             }
             return result;
         }
 
         /** {@inheritDoc} */
         @Override
         public int hashCode() {
             return Arrays.hashCode(new double[] {markerHeight, intMarkerPosition,
                 desiredMarkerIncrement, desiredMarkerPosition, previous.index, next.index});
         }
 
         /**
          * Read Object to deserialize.
          *
          * @param anInstream Stream Object data
          * @throws IOException thrown for IO Errors
          * @throws ClassNotFoundException thrown for class not being found
          */
         private void readObject(ObjectInputStream anInstream)
                 throws ClassNotFoundException, IOException {
             anInstream.defaultReadObject();
             previous=next=this;
             linear = new LinearInterpolator();
         }
 
         /** Copy this instance.
          * @return copy of the instance
          */
         public Marker copySelf() {
             return new Marker(markerHeight, desiredMarkerPosition, desiredMarkerIncrement, intMarkerPosition);
         }
 
         /**
          * {@inheritDoc}
          */
         @Override
         public String toString() {
             return String.format(
                     "index=%.0f,n=%.0f,np=%.2f,q=%.2f,dn=%.2f,prev=%d,next=%d",
                     (double) index, Precision.round(intMarkerPosition, 0),
                     Precision.round(desiredMarkerPosition, 2),
                     Precision.round(markerHeight, 2),
                     Precision.round(desiredMarkerIncrement, 2), previous.index,
                     next.index);
         }
     }
 
     /**
      * A simple fixed capacity list that has an upper bound to growth.
      * Once its capacity is reached, {@code add} is a no-op, returning
      * {@code false}.
      *
      * @param <E> type of the elements
      */
     private static class FixedCapacityList<E> extends ArrayList<E> implements Serializable {
 
         /**
          * Serialization Version Id
          */
         private static final long serialVersionUID = 2283952083075725479L;
         /**
          * Capacity of the list
          */
         private final int capacity;
 
         /**
          * This constructor constructs the list with given capacity and as well
          * as stores the capacity
          *
          * @param fixedCapacity the capacity to be fixed for this list
          */
         FixedCapacityList(final int fixedCapacity) {
             super(fixedCapacity);
             this.capacity = fixedCapacity;
         }
 
         /**
          * {@inheritDoc} In addition it checks if the {@link #size()} returns a
          * size that is within capacity and if true it adds; otherwise the list
          * contents are unchanged and {@code false} is returned.
          *
          * @return true if addition is successful and false otherwise
          */
         @Override
         public boolean add(final E e) {
             return size() < capacity && super.add(e);
         }
 
         /**
          * {@inheritDoc} In addition it checks if the sum of Collection size and
          * this instance's {@link #size()} returns a value that is within
          * capacity and if true it adds the collection; otherwise the list
          * contents are unchanged and {@code false} is returned.
          *
          * @return true if addition is successful and false otherwise
          */
         @Override
         public boolean addAll(Collection<? extends E> collection) {
             boolean isCollectionLess =
                     collection != null &&
                             collection.size() + size() <= capacity;
             return isCollectionLess && super.addAll(collection);
         }
 
         /** {@inheritDoc} */
         @Override
         public boolean equals(final Object other) {
             return super.equals(other) && capacity == ((FixedCapacityList<?>) other).capacity;
         }
 
         /** {@inheritDoc} */
         @Override
         public int hashCode() {
             return super.hashCode() + capacity;
         }
 
     }
 
     /**
      * A creation method to build Markers
      *
      * @param initialFive list of initial five elements
      * @param p the quantile desired
      * @return an instance of PSquareMarkers
      */
     public static PSquareMarkers newMarkers(final List<Double> initialFive, final double p) {
         return new Markers(initialFive, p);
     }
 
     /**
      * An interface that encapsulates abstractions of the
      * P-square algorithm markers as is explained in the original works. This
      * interface is exposed with protected access to help in testability.
      */
     protected interface PSquareMarkers {
         /**
          * Returns Percentile value computed thus far.
          *
          * @return percentile
          */
         double getPercentileValue();
 
         /**
          * A deep copy function to clone the current instance.
          *
          * @return deep copy of this instance
          */
         PSquareMarkers copySelf();
 
         /**
          * Returns the marker height (or percentile) of a given marker index.
          *
          * @param markerIndex is the index of marker in the marker array
          * @return percentile value of the marker index passed
          * @throws MathIllegalArgumentException in case the index is not within [1-5]
          */
         double height(int markerIndex);
 
         /**
          * Process a data point by moving the marker heights based on estimator.
          *
          * @param inputDataPoint is the data point passed
          * @return computed percentile
          */
         double processDataPoint(double inputDataPoint);
 
         /**
          * An Estimate of the percentile value of a given Marker
          *
          * @param index the marker's index in the array of markers
          * @return percentile estimate
          * @throws MathIllegalArgumentException in case if index is not within [1-5]
          */
         double estimate(int index);
     }
 }