1 /*
2 * Licensed to the Apache Software Foundation (ASF) under one or more
3 * contributor license agreements. See the NOTICE file distributed with
4 * this work for additional information regarding copyright ownership.
5 * The ASF licenses this file to You under the Apache License, Version 2.0
6 * (the "License"); you may not use this file except in compliance with
7 * the License. You may obtain a copy of the License at
8 *
9 * https://www.apache.org/licenses/LICENSE-2.0
10 *
11 * Unless required by applicable law or agreed to in writing, software
12 * distributed under the License is distributed on an "AS IS" BASIS,
13 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
14 * See the License for the specific language governing permissions and
15 * limitations under the License.
16 */
17
18 /*
19 * This is not the original file distributed by the Apache Software Foundation
20 * It has been modified by the Hipparchus project
21 */
22 package org.hipparchus.stat.descriptive;
23
24 import java.io.Serializable;
25
26 import org.hipparchus.util.FastMath;
27 import org.hipparchus.util.MathUtils;
28 import org.hipparchus.util.Precision;
29
30 /**
31 * Value object representing the results of a univariate
32 * statistical summary.
33 */
34 public class StatisticalSummaryValues
35 implements Serializable, StatisticalSummary {
36
37 /** Serialization id */
38 private static final long serialVersionUID = 20160406L;
39
40 /** The sample mean */
41 private final double mean;
42
43 /** The sample variance */
44 private final double variance;
45
46 /** The number of observations in the sample */
47 private final long n;
48
49 /** The maximum value */
50 private final double max;
51
52 /** The minimum value */
53 private final double min;
54
55 /** The sum of the sample values */
56 private final double sum;
57
58 /**
59 * Constructor.
60 *
61 * @param mean the sample mean
62 * @param variance the sample variance
63 * @param n the number of observations in the sample
64 * @param max the maximum value
65 * @param min the minimum value
66 * @param sum the sum of the values
67 */
68 public StatisticalSummaryValues(double mean, double variance, long n,
69 double max, double min, double sum) {
70 super();
71 this.mean = mean;
72 this.variance = variance;
73 this.n = n;
74 this.max = max;
75 this.min = min;
76 this.sum = sum;
77 }
78
79 /**
80 * @return Returns the max.
81 */
82 @Override
83 public double getMax() {
84 return max;
85 }
86
87 /**
88 * @return Returns the mean.
89 */
90 @Override
91 public double getMean() {
92 return mean;
93 }
94
95 /**
96 * @return Returns the min.
97 */
98 @Override
99 public double getMin() {
100 return min;
101 }
102
103 /**
104 * @return Returns the number of values.
105 */
106 @Override
107 public long getN() {
108 return n;
109 }
110
111 /**
112 * @return Returns the sum.
113 */
114 @Override
115 public double getSum() {
116 return sum;
117 }
118
119 /**
120 * @return Returns the standard deviation
121 */
122 @Override
123 public double getStandardDeviation() {
124 return FastMath.sqrt(variance);
125 }
126
127 /**
128 * @return Returns the variance.
129 */
130 @Override
131 public double getVariance() {
132 return variance;
133 }
134
135 /**
136 * Returns true iff <code>object</code> is a
137 * <code>StatisticalSummary</code> instance and all
138 * statistics have the same values as this.
139 *
140 * @param object the object to test equality against.
141 * @return true if object equals this
142 */
143 @Override
144 public boolean equals(Object object) {
145 if (object == this) {
146 return true;
147 }
148 if (!(object instanceof StatisticalSummaryValues)) {
149 return false;
150 }
151 StatisticalSummary other = (StatisticalSummary) object;
152 return Precision.equalsIncludingNaN(other.getMax(), getMax()) &&
153 Precision.equalsIncludingNaN(other.getMean(), getMean()) &&
154 Precision.equalsIncludingNaN(other.getMin(), getMin()) &&
155 Precision.equalsIncludingNaN(other.getN(), getN()) &&
156 Precision.equalsIncludingNaN(other.getSum(), getSum()) &&
157 Precision.equalsIncludingNaN(other.getVariance(), getVariance());
158 }
159
160 /**
161 * Returns hash code based on values of statistics
162 *
163 * @return hash code
164 */
165 @Override
166 public int hashCode() {
167 int result = 31 + MathUtils.hash(getMax());
168 result = result * 31 + MathUtils.hash(getMean());
169 result = result * 31 + MathUtils.hash(getMin());
170 result = result * 31 + MathUtils.hash(getN());
171 result = result * 31 + MathUtils.hash(getSum());
172 result = result * 31 + MathUtils.hash(getVariance());
173 return result;
174 }
175
176 /**
177 * Generates a text report displaying values of statistics.
178 * Each statistic is displayed on a separate line.
179 *
180 * @return String with line feeds displaying statistics
181 */
182 @Override
183 public String toString() {
184 StringBuilder outBuffer = new StringBuilder(200); // the size is just a wild guess
185 String endl = "\n";
186 outBuffer.append("StatisticalSummaryValues:").append(endl).
187 append("n: ").append(getN()).append(endl).
188 append("min: ").append(getMin()).append(endl).
189 append("max: ").append(getMax()).append(endl).
190 append("mean: ").append(getMean()).append(endl).
191 append("std dev: ").append(getStandardDeviation()).append(endl).
192 append("variance: ").append(getVariance()).append(endl).
193 append("sum: ").append(getSum()).append(endl);
194 return outBuffer.toString();
195 }
196
197 }