| Classes in this File | Line Coverage | Branch Coverage | Complexity | |||||||
| StandardDeviation |
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| 1.0;1 |
| 1 | /* |
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| 2 | * Copyright 2003-2004 The Apache Software Foundation. |
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| 3 | * |
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| 4 | * Licensed under the Apache License, Version 2.0 (the "License"); |
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| 5 | * you may not use this file except in compliance with the License. |
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| 6 | * You may obtain a copy of the License at |
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| 7 | * |
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| 8 | * http://www.apache.org/licenses/LICENSE-2.0 |
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| 9 | * |
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| 10 | * Unless required by applicable law or agreed to in writing, software |
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| 11 | * distributed under the License is distributed on an "AS IS" BASIS, |
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| 12 | * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. |
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| 13 | * See the License for the specific language governing permissions and |
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| 14 | * limitations under the License. |
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| 15 | */ |
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| 16 | package org.apache.commons.math.stat.descriptive.moment; |
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| 17 | ||
| 18 | import java.io.Serializable; |
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| 19 | ||
| 20 | import org.apache.commons.math.stat.descriptive.AbstractStorelessUnivariateStatistic; |
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| 21 | ||
| 22 | /** |
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| 23 | * Computes the sample standard deviation. The standard deviation |
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| 24 | * is the positive square root of the variance. This implementation wraps a |
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| 25 | * {@link Variance} instance. The <code>isBiasCorrected</code> property of the |
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| 26 | * wrapped Variance instance is exposed, so that this class can be used to |
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| 27 | * compute both the "sample standard deviation" (the square root of the |
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| 28 | * bias-corrected "sample variance") or the "population standard deviation" |
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| 29 | * (the square root of the non-bias-corrected "population variance"). See |
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| 30 | * {@link Variance} for more information. |
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| 31 | * <p> |
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| 32 | * <strong>Note that this implementation is not synchronized.</strong> If |
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| 33 | * multiple threads access an instance of this class concurrently, and at least |
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| 34 | * one of the threads invokes the <code>increment()</code> or |
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| 35 | * <code>clear()</code> method, it must be synchronized externally. |
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| 36 | * |
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| 37 | * @version $Revision$ $Date: 2005-02-26 05:11:52 -0800 (Sat, 26 Feb 2005) $ |
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| 38 | */ |
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| 39 | public class StandardDeviation extends AbstractStorelessUnivariateStatistic |
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| 40 | implements Serializable { |
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| 41 | ||
| 42 | /** Serializable version identifier */ |
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| 43 | static final long serialVersionUID = 5728716329662425188L; |
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| 44 | ||
| 45 | /** Wrapped Variance instance */ |
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| 46 | 24 | private Variance variance = null; |
| 47 | ||
| 48 | /** |
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| 49 | * Constructs a StandardDeviation. Sets the underlying {@link Variance} |
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| 50 | * instance's <code>isBiasCorrected</code> property to true. |
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| 51 | */ |
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| 52 | 20 | public StandardDeviation() { |
| 53 | 20 | variance = new Variance(); |
| 54 | 20 | } |
| 55 | ||
| 56 | /** |
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| 57 | * Constructs a StandardDeviation from an external second moment. |
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| 58 | * |
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| 59 | * @param m2 the external moment |
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| 60 | */ |
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| 61 | 0 | public StandardDeviation(final SecondMoment m2) { |
| 62 | 0 | variance = new Variance(m2); |
| 63 | 0 | } |
| 64 | ||
| 65 | /** |
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| 66 | * Contructs a StandardDeviation with the specified value for the |
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| 67 | * <code>isBiasCorrected</code> property. If this property is set to |
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| 68 | * <code>true</code>, the {@link Variance} used in computing results will |
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| 69 | * use the bias-corrected, or "sample" formula. See {@link Variance} for |
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| 70 | * details. |
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| 71 | * |
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| 72 | * @param isBiasCorrected whether or not the variance computation will use |
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| 73 | * the bias-corrected formula |
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| 74 | */ |
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| 75 | 2 | public StandardDeviation(boolean isBiasCorrected) { |
| 76 | 2 | variance = new Variance(isBiasCorrected); |
| 77 | 2 | } |
| 78 | ||
| 79 | /** |
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| 80 | * Contructs a StandardDeviation with the specified value for the |
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| 81 | * <code>isBiasCorrected</code> property and the supplied external moment. |
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| 82 | * If <code>isBiasCorrected</code> is set to <code>true</code>, the |
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| 83 | * {@link Variance} used in computing results will use the bias-corrected, |
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| 84 | * or "sample" formula. See {@link Variance} for details. |
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| 85 | * |
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| 86 | * @param isBiasCorrected whether or not the variance computation will use |
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| 87 | * the bias-corrected formula |
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| 88 | * @param m2 the external moment |
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| 89 | */ |
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| 90 | 2 | public StandardDeviation(boolean isBiasCorrected, SecondMoment m2) { |
| 91 | 2 | variance = new Variance(isBiasCorrected, m2); |
| 92 | 2 | } |
| 93 | ||
| 94 | /** |
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| 95 | * @see org.apache.commons.math.stat.descriptive.StorelessUnivariateStatistic#increment(double) |
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| 96 | */ |
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| 97 | public void increment(final double d) { |
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| 98 | 196 | variance.increment(d); |
| 99 | 196 | } |
| 100 | ||
| 101 | /** |
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| 102 | * @see org.apache.commons.math.stat.descriptive.StorelessUnivariateStatistic#getN() |
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| 103 | */ |
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| 104 | public long getN() { |
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| 105 | 58 | return variance.getN(); |
| 106 | } |
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| 107 | ||
| 108 | /** |
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| 109 | * @see org.apache.commons.math.stat.descriptive.StorelessUnivariateStatistic#getResult() |
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| 110 | */ |
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| 111 | public double getResult() { |
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| 112 | 100 | return Math.sqrt(variance.getResult()); |
| 113 | } |
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| 114 | ||
| 115 | /** |
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| 116 | * @see org.apache.commons.math.stat.descriptive.StorelessUnivariateStatistic#clear() |
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| 117 | */ |
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| 118 | public void clear() { |
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| 119 | 22 | variance.clear(); |
| 120 | 22 | } |
| 121 | ||
| 122 | /** |
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| 123 | * Returns the Standard Deviation of the entries in the input array, or |
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| 124 | * <code>Double.NaN</code> if the array is empty. |
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| 125 | * <p> |
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| 126 | * Returns 0 for a single-value (i.e. length = 1) sample. |
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| 127 | * <p> |
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| 128 | * Throws <code>IllegalArgumentException</code> if the array is null. |
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| 129 | * <p> |
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| 130 | * Does not change the internal state of the statistic. |
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| 131 | * |
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| 132 | * @param values the input array |
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| 133 | * @return the standard deviation of the values or Double.NaN if length = 0 |
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| 134 | * @throws IllegalArgumentException if the array is null |
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| 135 | */ |
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| 136 | public double evaluate(final double[] values) { |
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| 137 | 18 | return Math.sqrt(variance.evaluate(values)); |
| 138 | } |
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| 139 | ||
| 140 | /** |
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| 141 | * Returns the Standard Deviation of the entries in the specified portion of |
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| 142 | * the input array, or <code>Double.NaN</code> if the designated subarray |
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| 143 | * is empty. |
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| 144 | * <p> |
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| 145 | * Returns 0 for a single-value (i.e. length = 1) sample. |
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| 146 | * <p> |
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| 147 | * Throws <code>IllegalArgumentException</code> if the array is null. |
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| 148 | * <p> |
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| 149 | * Does not change the internal state of the statistic. |
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| 150 | * |
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| 151 | * @param values the input array |
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| 152 | * @param begin index of the first array element to include |
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| 153 | * @param length the number of elements to include |
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| 154 | * @return the standard deviation of the values or Double.NaN if length = 0 |
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| 155 | * @throws IllegalArgumentException if the array is null or the array index |
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| 156 | * parameters are not valid |
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| 157 | */ |
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| 158 | public double evaluate(final double[] values, final int begin, final int length) { |
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| 159 | 0 | return Math.sqrt(variance.evaluate(values, begin, length)); |
| 160 | } |
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| 161 | ||
| 162 | /** |
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| 163 | * Returns the Standard Deviation of the entries in the specified portion of |
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| 164 | * the input array, using the precomputed mean value. Returns |
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| 165 | * <code>Double.NaN</code> if the designated subarray is empty. |
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| 166 | * <p> |
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| 167 | * Returns 0 for a single-value (i.e. length = 1) sample. |
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| 168 | * <p> |
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| 169 | * The formula used assumes that the supplied mean value is the arithmetic |
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| 170 | * mean of the sample data, not a known population parameter. This method |
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| 171 | * is supplied only to save computation when the mean has already been |
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| 172 | * computed. |
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| 173 | * <p> |
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| 174 | * Throws <code>IllegalArgumentException</code> if the array is null. |
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| 175 | * <p> |
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| 176 | * Does not change the internal state of the statistic. |
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| 177 | * |
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| 178 | * @param values the input array |
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| 179 | * @param mean the precomputed mean value |
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| 180 | * @param begin index of the first array element to include |
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| 181 | * @param length the number of elements to include |
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| 182 | * @return the standard deviation of the values or Double.NaN if length = 0 |
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| 183 | * @throws IllegalArgumentException if the array is null or the array index |
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| 184 | * parameters are not valid |
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| 185 | */ |
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| 186 | public double evaluate(final double[] values, final double mean, |
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| 187 | final int begin, final int length) { |
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| 188 | 0 | return Math.sqrt(variance.evaluate(values, mean, begin, length)); |
| 189 | } |
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| 190 | ||
| 191 | /** |
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| 192 | * Returns the Standard Deviation of the entries in the input array, using |
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| 193 | * the precomputed mean value. Returns |
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| 194 | * <code>Double.NaN</code> if the designated subarray is empty. |
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| 195 | * <p> |
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| 196 | * Returns 0 for a single-value (i.e. length = 1) sample. |
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| 197 | * <p> |
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| 198 | * The formula used assumes that the supplied mean value is the arithmetic |
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| 199 | * mean of the sample data, not a known population parameter. This method |
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| 200 | * is supplied only to save computation when the mean has already been |
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| 201 | * computed. |
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| 202 | * <p> |
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| 203 | * Throws <code>IllegalArgumentException</code> if the array is null. |
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| 204 | * <p> |
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| 205 | * Does not change the internal state of the statistic. |
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| 206 | * |
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| 207 | * @param values the input array |
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| 208 | * @param mean the precomputed mean value |
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| 209 | * @return the standard deviation of the values or Double.NaN if length = 0 |
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| 210 | * @throws IllegalArgumentException if the array is null |
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| 211 | */ |
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| 212 | public double evaluate(final double[] values, final double mean) { |
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| 213 | 0 | return Math.sqrt(variance.evaluate(values, mean)); |
| 214 | } |
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| 215 | ||
| 216 | /** |
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| 217 | * @return Returns the isBiasCorrected. |
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| 218 | */ |
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| 219 | public boolean isBiasCorrected() { |
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| 220 | 0 | return variance.isBiasCorrected(); |
| 221 | } |
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| 222 | ||
| 223 | /** |
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| 224 | * @param isBiasCorrected The isBiasCorrected to set. |
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| 225 | */ |
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| 226 | public void setBiasCorrected(boolean isBiasCorrected) { |
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| 227 | 2 | variance.setBiasCorrected(isBiasCorrected); |
| 228 | 2 | } |
| 229 | } |