/**
    * 
    */
   package org.opentrafficsim.water.statistics;
   
   import java.io.Serializable;
   
   import org.apache.poi.ss.usermodel.CellStyle;
   import org.apache.poi.ss.usermodel.DataFormat;
  import org.apache.poi.ss.usermodel.Row;
  import org.apache.poi.ss.usermodel.Sheet;
  
  import com.thoughtworks.xstream.annotations.XStreamAlias;
  import com.thoughtworks.xstream.annotations.XStreamOmitField;
  
  import nl.tudelft.simulation.jstats.distributions.DistNormal;
  import nl.tudelft.simulation.jstats.statistics.Tally;
  import nl.tudelft.simulation.jstats.streams.MersenneTwister;
  
  /**
   * <br>
   * Copyright (c) 2011-2013 TU Delft, Faculty of TBM, Systems and Simulation <br>
   * This software is licensed without restrictions to Nederlandse Organisatie voor Toegepast Natuurwetenschappelijk
   * Onderzoek TNO (TNO), Erasmus University Rotterdam, Delft University of Technology, Panteia B.V., Stichting Projecten
   * Binnenvaart, Ab Ovo Nederland B.V., Modality Software Solutions B.V., and Rijkswaterstaat - Dienst Water, Verkeer en
   * Leefomgeving, including the right to sub-license sources and derived products to third parties. <br>
   * 
   * @version Mar 24, 2013 <br>
   * @author <a href="http://tudelft.nl/averbraeck">Alexander Verbraeck </a>
   */
  @XStreamAlias("tally")
  public class XTally implements Serializable
  {
      /** */
      @XStreamOmitField
      private static final long serialVersionUID = 1L;
  
      /** sum refers to the sum of the tally */
      protected double sum = Double.NaN;
  
      /** min refers to the min of the tally */
      protected double min = Double.NaN;
  
      /** maxrefers to the max of the tally */
      protected double max = Double.NaN;
  
      /** varianceSum refers to the varianceSum of the tally */
      protected double varianceSum = Double.NaN;
  
      /** n refers to the number of measurements */
      protected long n = Long.MIN_VALUE;
  
      /** description refers to the description of this tally */
      protected String description;
  
      /** the confidenceDistribution */
      @XStreamOmitField
      private DistNormal confidenceDistribution = new DistNormal(new MersenneTwister());
  
      /** the semaphore */
      @XStreamOmitField
      protected Object semaphore = new Object();
  
      /** LEFT_SIDE_CONFIDENCE refers to the left side confidence */
      @XStreamOmitField
      public static final short LEFT_SIDE_CONFIDENCE = -1;
  
      /** BOTH_SIDE_CONFIDENCE refers to both sides of the confidence */
      @XStreamOmitField
      public static final short BOTH_SIDE_CONFIDENCE = 0;
  
      /** RIGTH_SIDE_CONFIDENCE refers to the right side confidence */
      @XStreamOmitField
      public static final short RIGTH_SIDE_CONFIDENCE = 1;
  
      /**
       * @param description description of the statistic
       */
      public XTally(String description)
      {
          super();
          this.description = description;
      }
  
      /**
       * Returns the sampleMean of all oberservations since the initialization
       * 
       * @return double the sampleMean
       */
      public double getSampleMean()
      {
          if (this.n > 0)
              return this.sum / this.n;
          else
              return Double.NaN;
      }
  
      /**
       * returns the confidence interval on either side of the mean
      * 
      * @param alpha Alpha is the significance level used to compute the confidence level. The confidence level equals
      *            100*(1 - alpha)%, or in other words, an alpha of 0.05 indicates a 95 percent confidence level.
      * @return double[] the confidence interval of this tally
      */
     public double[] getConfidenceInterval(final double alpha)
     {
         return this.getConfidenceInterval(alpha, Tally.BOTH_SIDE_CONFIDENCE);
     }
 
     /**
      * returns the confidence interval based of the mean
      * 
      * @param alpha Alpha is the significance level used to compute the confidence level. The confidence level equals
      *            100*(1 - alpha)%, or in other words, an alpha of 0.05 indicates a 95 percent confidence level.
      * @param side the side of the confidence interval with respect to the mean
      * @return double[] the confidence interval of this tally
      */
     public double[] getConfidenceInterval(final double alpha, final short side)
     {
         if (!(side == LEFT_SIDE_CONFIDENCE || side == BOTH_SIDE_CONFIDENCE || side == RIGTH_SIDE_CONFIDENCE))
         {
             throw new IllegalArgumentException("side of confidence level is not defined");
         }
         if (alpha < 0 || alpha > 1)
         {
             throw new IllegalArgumentException("1 >= confidenceLevel >= 0");
         }
         synchronized (this.semaphore)
         {
             if (Double.isNaN(this.getSampleMean()) || Double.isNaN(this.getStdDev()))
             {
                 return null;
             }
             double level = 1 - alpha;
             if (side == Tally.BOTH_SIDE_CONFIDENCE)
             {
                 level = 1 - alpha / 2.0;
             }
             double z = this.confidenceDistribution.getInverseCumulativeProbability(level);
             double confidence = z * Math.sqrt(this.getSampleVariance() / this.n);
             double[] result = {this.getSampleMean() - confidence, this.getSampleMean() + confidence};
             if (side == Tally.LEFT_SIDE_CONFIDENCE)
             {
                 result[1] = this.getSampleMean();
             }
             if (side == Tally.RIGTH_SIDE_CONFIDENCE)
             {
                 result[0] = this.getSampleMean();
             }
             result[0] = Math.max(result[0], this.min);
             result[1] = Math.min(result[1], this.max);
             return result;
         }
     }
 
     /**
      * returns the description of this tally
      * 
      * @return Sting description
      */
     public String getDescription()
     {
         return this.description;
     }
 
     /**
      * Returns the max.
      * 
      * @return double
      */
     public double getMax()
     {
         return this.max;
     }
 
     /**
      * Returns the min.
      * 
      * @return double
      */
     public double getMin()
     {
         return this.min;
     }
 
     /**
      * Returns the number of observations
      * 
      * @return long n
      */
     public long getN()
     {
         return this.n;
     }
 
     /**
      * Returns the current tally standard deviation
      * 
      * @return double the standard deviation
      */
     public double getStdDev()
     {
         synchronized (this.semaphore)
         {
             if (this.n > 1)
             {
                 return Math.sqrt(this.varianceSum / (1.0 * this.n - 1.0));
             }
             return Double.NaN;
         }
     }
 
     /**
      * returns the sum of the values of the observations
      * 
      * @return double sum
      */
     public double getSum()
     {
         return this.sum;
     }
 
     /**
      * Returns the current tally variance
      * 
      * @return double samplevariance
      */
     public double getSampleVariance()
     {
         synchronized (this.semaphore)
         {
             if (this.n > 1)
             {
                 return this.varianceSum / (1.0 * this.n - 1.0);
             }
             return Double.NaN;
         }
     }
 
     /**
      * initializes the Tally. This methods sets the max, min, n, sum and variance values to their initial values.
      */
     public void initialize()
     {
         synchronized (this.semaphore)
         {
             this.max = -Double.MAX_VALUE;
             this.min = Double.MAX_VALUE;
             this.n = 0;
             this.sum = 0.0;
             this.varianceSum = 0.0;
         }
     }
 
     /**
      * is this tally initialized?
      * 
      * @return true whenever this.initialize is invoked.
      */
     public boolean isInitialized()
     {
         return !Double.isNaN(this.max);
     }
 
     /**
      * tally
      * 
      * @param value the value
      */
     public void tally(final double value)
     {
         if (!Double.isNaN(value))
         {
             synchronized (this.semaphore)
             {
                 this.varianceSum += value * value;
                 this.sum += value;
                 this.n += 1;
                 if (value < this.min)
                     this.min = value;
                 if (value > this.max)
                     this.max = value;
             }
         }
     }
 
     /**
      * Write statistics to an excel spreadsheet, starting on row "startRow"
      * 
      * @param sheet the excel sheet to write to 
      * @param startRow the first row of writing
      * @return first free row after writing
      */
     public int writeToExcel(final Sheet sheet, final int startRow)
     {
         DataFormat format = sheet.getWorkbook().createDataFormat();
         CellStyle style = sheet.getWorkbook().createCellStyle();
         style.setDataFormat(format.getFormat("0.00"));
 
         int rownr = startRow;
         Row row = sheet.createRow(rownr);
 
         row.createCell(1).setCellValue(description);
         row.createCell(2).setCellValue("tally [n, gem, stdev, min, max]");
         row.createCell(3).setCellValue(getN());
         if (getN() > 0)
         {
             row.createCell(4).setCellValue(getSampleMean());
             row.getCell(4).setCellStyle(style);
             if (getN() > 1 && !Double.isNaN(getStdDev()))
             {
                 row.createCell(5).setCellValue(getStdDev());
                 row.getCell(5).setCellStyle(style);
             }
             row.createCell(6).setCellValue(getMin());
             row.getCell(6).setCellStyle(style);
             row.createCell(7).setCellValue(getMax());
             row.getCell(7).setCellStyle(style);
         }
 
         return rownr + 1;
     }
 
     /**
      * @see java.lang.Object#toString()
      */
     @Override
     public String toString()
     {
         return this.description;
     }
 
 }