001 /*
002 * Licensed to the Apache Software Foundation (ASF) under one or more
003 * contributor license agreements. See the NOTICE file distributed with
004 * this work for additional information regarding copyright ownership.
005 * The ASF licenses this file to You under the Apache License, Version 2.0
006 * (the "License"); you may not use this file except in compliance with
007 * the License. You may obtain a copy of the License at
008 *
009 * http://www.apache.org/licenses/LICENSE-2.0
010 *
011 * Unless required by applicable law or agreed to in writing, software
012 * distributed under the License is distributed on an "AS IS" BASIS,
013 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
014 * See the License for the specific language governing permissions and
015 * limitations under the License.
016 */
017 package org.apache.commons.math.stat.descriptive;
018
019 import java.io.Serializable;
020
021 import org.apache.commons.math.util.FastMath;
022 import org.apache.commons.math.util.MathUtils;
023
024 /**
025 * Value object representing the results of a univariate statistical summary.
026 *
027 * @version $Revision: 1054186 $ $Date: 2011-01-01 03:28:46 +0100 (sam. 01 janv. 2011) $
028 */
029 public class StatisticalSummaryValues implements Serializable,
030 StatisticalSummary {
031
032 /** Serialization id */
033 private static final long serialVersionUID = -5108854841843722536L;
034
035 /** The sample mean */
036 private final double mean;
037
038 /** The sample variance */
039 private final double variance;
040
041 /** The number of observations in the sample */
042 private final long n;
043
044 /** The maximum value */
045 private final double max;
046
047 /** The minimum value */
048 private final double min;
049
050 /** The sum of the sample values */
051 private final double sum;
052
053 /**
054 * Constructor
055 *
056 * @param mean the sample mean
057 * @param variance the sample variance
058 * @param n the number of observations in the sample
059 * @param max the maximum value
060 * @param min the minimum value
061 * @param sum the sum of the values
062 */
063 public StatisticalSummaryValues(double mean, double variance, long n,
064 double max, double min, double sum) {
065 super();
066 this.mean = mean;
067 this.variance = variance;
068 this.n = n;
069 this.max = max;
070 this.min = min;
071 this.sum = sum;
072 }
073
074 /**
075 * @return Returns the max.
076 */
077 public double getMax() {
078 return max;
079 }
080
081 /**
082 * @return Returns the mean.
083 */
084 public double getMean() {
085 return mean;
086 }
087
088 /**
089 * @return Returns the min.
090 */
091 public double getMin() {
092 return min;
093 }
094
095 /**
096 * @return Returns the number of values.
097 */
098 public long getN() {
099 return n;
100 }
101
102 /**
103 * @return Returns the sum.
104 */
105 public double getSum() {
106 return sum;
107 }
108
109 /**
110 * @return Returns the standard deviation
111 */
112 public double getStandardDeviation() {
113 return FastMath.sqrt(variance);
114 }
115
116 /**
117 * @return Returns the variance.
118 */
119 public double getVariance() {
120 return variance;
121 }
122
123 /**
124 * Returns true iff <code>object</code> is a
125 * <code>StatisticalSummaryValues</code> instance and all statistics have
126 * the same values as this.
127 *
128 * @param object the object to test equality against.
129 * @return true if object equals this
130 */
131 @Override
132 public boolean equals(Object object) {
133 if (object == this ) {
134 return true;
135 }
136 if (object instanceof StatisticalSummaryValues == false) {
137 return false;
138 }
139 StatisticalSummaryValues stat = (StatisticalSummaryValues) object;
140 return MathUtils.equalsIncludingNaN(stat.getMax(), getMax()) &&
141 MathUtils.equalsIncludingNaN(stat.getMean(), getMean()) &&
142 MathUtils.equalsIncludingNaN(stat.getMin(), getMin()) &&
143 MathUtils.equalsIncludingNaN(stat.getN(), getN()) &&
144 MathUtils.equalsIncludingNaN(stat.getSum(), getSum()) &&
145 MathUtils.equalsIncludingNaN(stat.getVariance(), getVariance());
146 }
147
148 /**
149 * Returns hash code based on values of statistics
150 *
151 * @return hash code
152 */
153 @Override
154 public int hashCode() {
155 int result = 31 + MathUtils.hash(getMax());
156 result = result * 31 + MathUtils.hash(getMean());
157 result = result * 31 + MathUtils.hash(getMin());
158 result = result * 31 + MathUtils.hash(getN());
159 result = result * 31 + MathUtils.hash(getSum());
160 result = result * 31 + MathUtils.hash(getVariance());
161 return result;
162 }
163
164 /**
165 * Generates a text report displaying values of statistics.
166 * Each statistic is displayed on a separate line.
167 *
168 * @return String with line feeds displaying statistics
169 */
170 @Override
171 public String toString() {
172 StringBuilder outBuffer = new StringBuilder();
173 String endl = "\n";
174 outBuffer.append("StatisticalSummaryValues:").append(endl);
175 outBuffer.append("n: ").append(getN()).append(endl);
176 outBuffer.append("min: ").append(getMin()).append(endl);
177 outBuffer.append("max: ").append(getMax()).append(endl);
178 outBuffer.append("mean: ").append(getMean()).append(endl);
179 outBuffer.append("std dev: ").append(getStandardDeviation())
180 .append(endl);
181 outBuffer.append("variance: ").append(getVariance()).append(endl);
182 outBuffer.append("sum: ").append(getSum()).append(endl);
183 return outBuffer.toString();
184 }
185
186 }