/*
    * 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
    *
    *      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 org.apache.commons.math4.legacy.stat.descriptive;
  
  import org.apache.commons.math4.core.jdkmath.JdkMath;
  import org.apache.commons.numbers.core.Precision;
  
  /**
   *  Value object representing the results of a univariate statistical summary.
   *
   */
  public class StatisticalSummaryValues
      implements StatisticalSummary {
      /** The sample mean. */
      private final double mean;
  
      /** The sample variance. */
      private final double variance;
  
      /** The number of observations in the sample. */
      private final long n;
  
      /** The maximum value. */
      private final double max;
  
      /** The minimum value. */
      private final double min;
  
      /** The sum of the sample values. */
      private final double sum;
  
      /**
        * Constructor.
        *
        * @param mean  the sample mean
        * @param variance  the sample variance
        * @param n  the number of observations in the sample
        * @param max  the maximum value
        * @param min  the minimum value
        * @param sum  the sum of the values
       */
      public StatisticalSummaryValues(double mean, double variance, long n,
          double max, double min, double sum) {
          super();
          this.mean = mean;
          this.variance = variance;
          this.n = n;
          this.max = max;
          this.min = min;
          this.sum = sum;
      }
  
      /**
       * @return Returns the max.
       */
      @Override
      public double getMax() {
          return max;
      }
  
      /**
       * @return Returns the mean.
       */
      @Override
      public double getMean() {
          return mean;
      }
  
      /**
       * @return Returns the min.
       */
      @Override
      public double getMin() {
          return min;
      }
  
      /**
       * @return Returns the number of values.
       */
      @Override
      public long getN() {
          return n;
      }
  
      /**
      * @return Returns the sum.
      */
     @Override
     public double getSum() {
         return sum;
     }
 
     /**
      * @return Returns the standard deviation
      */
     @Override
     public double getStandardDeviation() {
         return JdkMath.sqrt(variance);
     }
 
     /**
      * @return Returns the variance.
      */
     @Override
     public double getVariance() {
         return variance;
     }
 
     /**
      * Returns true iff <code>object</code> is a
      * <code>StatisticalSummaryValues</code> instance and all statistics have
      *  the same values as this.
      *
      * @param object the object to test equality against.
      * @return true if object equals this
      */
     @Override
     public boolean equals(Object object) {
         if (object == this ) {
             return true;
         }
         if (!(object instanceof StatisticalSummaryValues)) {
             return false;
         }
         StatisticalSummaryValues stat = (StatisticalSummaryValues) object;
         return Precision.equalsIncludingNaN(stat.getMax(),      getMax())  &&
                Precision.equalsIncludingNaN(stat.getMean(),     getMean()) &&
                Precision.equalsIncludingNaN(stat.getMin(),      getMin())  &&
                Precision.equalsIncludingNaN(stat.getN(),        getN())    &&
                Precision.equalsIncludingNaN(stat.getSum(),      getSum())  &&
                Precision.equalsIncludingNaN(stat.getVariance(), getVariance());
     }
 
     /**
      * Returns hash code based on values of statistics.
      *
      * @return hash code
      */
     @Override
     public int hashCode() {
         int result = 31 + Double.hashCode(getMax());
         result = result * 31 + Double.hashCode(getMean());
         result = result * 31 + Double.hashCode(getMin());
         result = result * 31 + Double.hashCode(getN());
         result = result * 31 + Double.hashCode(getSum());
         result = result * 31 + Double.hashCode(getVariance());
         return result;
     }
 
     /**
      * Generates a text report displaying values of statistics.
      * Each statistic is displayed on a separate line.
      *
      * @return String with line feeds displaying statistics
      */
     @Override
     public String toString() {
         StringBuffer outBuffer = new StringBuffer();
         String endl = "\n";
         outBuffer.append("StatisticalSummaryValues:").append(endl);
         outBuffer.append("n: ").append(getN()).append(endl);
         outBuffer.append("min: ").append(getMin()).append(endl);
         outBuffer.append("max: ").append(getMax()).append(endl);
         outBuffer.append("mean: ").append(getMean()).append(endl);
         outBuffer.append("std dev: ").append(getStandardDeviation())
             .append(endl);
         outBuffer.append("variance: ").append(getVariance()).append(endl);
         outBuffer.append("sum: ").append(getSum()).append(endl);
         return outBuffer.toString();
     }
 }