Raymond | dee0849 | 2015-04-02 10:43:13 -0700 | [diff] [blame] | 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 | * http://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 | package org.apache.commons.math.stat.descriptive.moment; |
| 18 | |
| 19 | import java.io.Serializable; |
| 20 | |
| 21 | import org.apache.commons.math.stat.descriptive.AbstractStorelessUnivariateStatistic; |
| 22 | import org.apache.commons.math.util.FastMath; |
| 23 | |
| 24 | /** |
| 25 | * Computes the sample standard deviation. The standard deviation |
| 26 | * is the positive square root of the variance. This implementation wraps a |
| 27 | * {@link Variance} instance. The <code>isBiasCorrected</code> property of the |
| 28 | * wrapped Variance instance is exposed, so that this class can be used to |
| 29 | * compute both the "sample standard deviation" (the square root of the |
| 30 | * bias-corrected "sample variance") or the "population standard deviation" |
| 31 | * (the square root of the non-bias-corrected "population variance"). See |
| 32 | * {@link Variance} for more information. |
| 33 | * <p> |
| 34 | * <strong>Note that this implementation is not synchronized.</strong> If |
| 35 | * multiple threads access an instance of this class concurrently, and at least |
| 36 | * one of the threads invokes the <code>increment()</code> or |
| 37 | * <code>clear()</code> method, it must be synchronized externally.</p> |
| 38 | * |
| 39 | * @version $Revision: 1006299 $ $Date: 2010-10-10 16:47:17 +0200 (dim. 10 oct. 2010) $ |
| 40 | */ |
| 41 | public class StandardDeviation extends AbstractStorelessUnivariateStatistic |
| 42 | implements Serializable { |
| 43 | |
| 44 | /** Serializable version identifier */ |
| 45 | private static final long serialVersionUID = 5728716329662425188L; |
| 46 | |
| 47 | /** Wrapped Variance instance */ |
| 48 | private Variance variance = null; |
| 49 | |
| 50 | /** |
| 51 | * Constructs a StandardDeviation. Sets the underlying {@link Variance} |
| 52 | * instance's <code>isBiasCorrected</code> property to true. |
| 53 | */ |
| 54 | public StandardDeviation() { |
| 55 | variance = new Variance(); |
| 56 | } |
| 57 | |
| 58 | /** |
| 59 | * Constructs a StandardDeviation from an external second moment. |
| 60 | * |
| 61 | * @param m2 the external moment |
| 62 | */ |
| 63 | public StandardDeviation(final SecondMoment m2) { |
| 64 | variance = new Variance(m2); |
| 65 | } |
| 66 | |
| 67 | /** |
| 68 | * Copy constructor, creates a new {@code StandardDeviation} identical |
| 69 | * to the {@code original} |
| 70 | * |
| 71 | * @param original the {@code StandardDeviation} instance to copy |
| 72 | */ |
| 73 | public StandardDeviation(StandardDeviation original) { |
| 74 | copy(original, this); |
| 75 | } |
| 76 | |
| 77 | /** |
| 78 | * Contructs a StandardDeviation with the specified value for the |
| 79 | * <code>isBiasCorrected</code> property. If this property is set to |
| 80 | * <code>true</code>, the {@link Variance} used in computing results will |
| 81 | * use the bias-corrected, or "sample" formula. See {@link Variance} for |
| 82 | * details. |
| 83 | * |
| 84 | * @param isBiasCorrected whether or not the variance computation will use |
| 85 | * the bias-corrected formula |
| 86 | */ |
| 87 | public StandardDeviation(boolean isBiasCorrected) { |
| 88 | variance = new Variance(isBiasCorrected); |
| 89 | } |
| 90 | |
| 91 | /** |
| 92 | * Contructs a StandardDeviation with the specified value for the |
| 93 | * <code>isBiasCorrected</code> property and the supplied external moment. |
| 94 | * If <code>isBiasCorrected</code> is set to <code>true</code>, the |
| 95 | * {@link Variance} used in computing results will use the bias-corrected, |
| 96 | * or "sample" formula. See {@link Variance} for details. |
| 97 | * |
| 98 | * @param isBiasCorrected whether or not the variance computation will use |
| 99 | * the bias-corrected formula |
| 100 | * @param m2 the external moment |
| 101 | */ |
| 102 | public StandardDeviation(boolean isBiasCorrected, SecondMoment m2) { |
| 103 | variance = new Variance(isBiasCorrected, m2); |
| 104 | } |
| 105 | |
| 106 | /** |
| 107 | * {@inheritDoc} |
| 108 | */ |
| 109 | @Override |
| 110 | public void increment(final double d) { |
| 111 | variance.increment(d); |
| 112 | } |
| 113 | |
| 114 | /** |
| 115 | * {@inheritDoc} |
| 116 | */ |
| 117 | public long getN() { |
| 118 | return variance.getN(); |
| 119 | } |
| 120 | |
| 121 | /** |
| 122 | * {@inheritDoc} |
| 123 | */ |
| 124 | @Override |
| 125 | public double getResult() { |
| 126 | return FastMath.sqrt(variance.getResult()); |
| 127 | } |
| 128 | |
| 129 | /** |
| 130 | * {@inheritDoc} |
| 131 | */ |
| 132 | @Override |
| 133 | public void clear() { |
| 134 | variance.clear(); |
| 135 | } |
| 136 | |
| 137 | /** |
| 138 | * Returns the Standard Deviation of the entries in the input array, or |
| 139 | * <code>Double.NaN</code> if the array is empty. |
| 140 | * <p> |
| 141 | * Returns 0 for a single-value (i.e. length = 1) sample.</p> |
| 142 | * <p> |
| 143 | * Throws <code>IllegalArgumentException</code> if the array is null.</p> |
| 144 | * <p> |
| 145 | * Does not change the internal state of the statistic.</p> |
| 146 | * |
| 147 | * @param values the input array |
| 148 | * @return the standard deviation of the values or Double.NaN if length = 0 |
| 149 | * @throws IllegalArgumentException if the array is null |
| 150 | */ |
| 151 | @Override |
| 152 | public double evaluate(final double[] values) { |
| 153 | return FastMath.sqrt(variance.evaluate(values)); |
| 154 | } |
| 155 | |
| 156 | /** |
| 157 | * Returns the Standard Deviation of the entries in the specified portion of |
| 158 | * the input array, or <code>Double.NaN</code> if the designated subarray |
| 159 | * is empty. |
| 160 | * <p> |
| 161 | * Returns 0 for a single-value (i.e. length = 1) sample. </p> |
| 162 | * <p> |
| 163 | * Throws <code>IllegalArgumentException</code> if the array is null.</p> |
| 164 | * <p> |
| 165 | * Does not change the internal state of the statistic.</p> |
| 166 | * |
| 167 | * @param values the input array |
| 168 | * @param begin index of the first array element to include |
| 169 | * @param length the number of elements to include |
| 170 | * @return the standard deviation of the values or Double.NaN if length = 0 |
| 171 | * @throws IllegalArgumentException if the array is null or the array index |
| 172 | * parameters are not valid |
| 173 | */ |
| 174 | @Override |
| 175 | public double evaluate(final double[] values, final int begin, final int length) { |
| 176 | return FastMath.sqrt(variance.evaluate(values, begin, length)); |
| 177 | } |
| 178 | |
| 179 | /** |
| 180 | * Returns the Standard Deviation of the entries in the specified portion of |
| 181 | * the input array, using the precomputed mean value. Returns |
| 182 | * <code>Double.NaN</code> if the designated subarray is empty. |
| 183 | * <p> |
| 184 | * Returns 0 for a single-value (i.e. length = 1) sample.</p> |
| 185 | * <p> |
| 186 | * The formula used assumes that the supplied mean value is the arithmetic |
| 187 | * mean of the sample data, not a known population parameter. This method |
| 188 | * is supplied only to save computation when the mean has already been |
| 189 | * computed.</p> |
| 190 | * <p> |
| 191 | * Throws <code>IllegalArgumentException</code> if the array is null.</p> |
| 192 | * <p> |
| 193 | * Does not change the internal state of the statistic.</p> |
| 194 | * |
| 195 | * @param values the input array |
| 196 | * @param mean the precomputed mean value |
| 197 | * @param begin index of the first array element to include |
| 198 | * @param length the number of elements to include |
| 199 | * @return the standard deviation of the values or Double.NaN if length = 0 |
| 200 | * @throws IllegalArgumentException if the array is null or the array index |
| 201 | * parameters are not valid |
| 202 | */ |
| 203 | public double evaluate(final double[] values, final double mean, |
| 204 | final int begin, final int length) { |
| 205 | return FastMath.sqrt(variance.evaluate(values, mean, begin, length)); |
| 206 | } |
| 207 | |
| 208 | /** |
| 209 | * Returns the Standard Deviation of the entries in the input array, using |
| 210 | * the precomputed mean value. Returns |
| 211 | * <code>Double.NaN</code> if the designated subarray is empty. |
| 212 | * <p> |
| 213 | * Returns 0 for a single-value (i.e. length = 1) sample.</p> |
| 214 | * <p> |
| 215 | * The formula used assumes that the supplied mean value is the arithmetic |
| 216 | * mean of the sample data, not a known population parameter. This method |
| 217 | * is supplied only to save computation when the mean has already been |
| 218 | * computed.</p> |
| 219 | * <p> |
| 220 | * Throws <code>IllegalArgumentException</code> if the array is null.</p> |
| 221 | * <p> |
| 222 | * Does not change the internal state of the statistic.</p> |
| 223 | * |
| 224 | * @param values the input array |
| 225 | * @param mean the precomputed mean value |
| 226 | * @return the standard deviation of the values or Double.NaN if length = 0 |
| 227 | * @throws IllegalArgumentException if the array is null |
| 228 | */ |
| 229 | public double evaluate(final double[] values, final double mean) { |
| 230 | return FastMath.sqrt(variance.evaluate(values, mean)); |
| 231 | } |
| 232 | |
| 233 | /** |
| 234 | * @return Returns the isBiasCorrected. |
| 235 | */ |
| 236 | public boolean isBiasCorrected() { |
| 237 | return variance.isBiasCorrected(); |
| 238 | } |
| 239 | |
| 240 | /** |
| 241 | * @param isBiasCorrected The isBiasCorrected to set. |
| 242 | */ |
| 243 | public void setBiasCorrected(boolean isBiasCorrected) { |
| 244 | variance.setBiasCorrected(isBiasCorrected); |
| 245 | } |
| 246 | |
| 247 | /** |
| 248 | * {@inheritDoc} |
| 249 | */ |
| 250 | @Override |
| 251 | public StandardDeviation copy() { |
| 252 | StandardDeviation result = new StandardDeviation(); |
| 253 | copy(this, result); |
| 254 | return result; |
| 255 | } |
| 256 | |
| 257 | |
| 258 | /** |
| 259 | * Copies source to dest. |
| 260 | * <p>Neither source nor dest can be null.</p> |
| 261 | * |
| 262 | * @param source StandardDeviation to copy |
| 263 | * @param dest StandardDeviation to copy to |
| 264 | * @throws NullPointerException if either source or dest is null |
| 265 | */ |
| 266 | public static void copy(StandardDeviation source, StandardDeviation dest) { |
| 267 | dest.setData(source.getDataRef()); |
| 268 | dest.variance = source.variance.copy(); |
| 269 | } |
| 270 | |
| 271 | } |