| /* |
| * 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.math.stat.descriptive.moment; |
| |
| import java.io.Serializable; |
| |
| import org.apache.commons.math.stat.descriptive.AbstractStorelessUnivariateStatistic; |
| import org.apache.commons.math.util.FastMath; |
| |
| /** |
| * Computes the sample standard deviation. The standard deviation |
| * is the positive square root of the variance. This implementation wraps a |
| * {@link Variance} instance. The <code>isBiasCorrected</code> property of the |
| * wrapped Variance instance is exposed, so that this class can be used to |
| * compute both the "sample standard deviation" (the square root of the |
| * bias-corrected "sample variance") or the "population standard deviation" |
| * (the square root of the non-bias-corrected "population variance"). See |
| * {@link Variance} for more information. |
| * <p> |
| * <strong>Note that this implementation is not synchronized.</strong> If |
| * multiple threads access an instance of this class concurrently, and at least |
| * one of the threads invokes the <code>increment()</code> or |
| * <code>clear()</code> method, it must be synchronized externally.</p> |
| * |
| * @version $Revision: 1006299 $ $Date: 2010-10-10 16:47:17 +0200 (dim. 10 oct. 2010) $ |
| */ |
| public class StandardDeviation extends AbstractStorelessUnivariateStatistic |
| implements Serializable { |
| |
| /** Serializable version identifier */ |
| private static final long serialVersionUID = 5728716329662425188L; |
| |
| /** Wrapped Variance instance */ |
| private Variance variance = null; |
| |
| /** |
| * Constructs a StandardDeviation. Sets the underlying {@link Variance} |
| * instance's <code>isBiasCorrected</code> property to true. |
| */ |
| public StandardDeviation() { |
| variance = new Variance(); |
| } |
| |
| /** |
| * Constructs a StandardDeviation from an external second moment. |
| * |
| * @param m2 the external moment |
| */ |
| public StandardDeviation(final SecondMoment m2) { |
| variance = new Variance(m2); |
| } |
| |
| /** |
| * Copy constructor, creates a new {@code StandardDeviation} identical |
| * to the {@code original} |
| * |
| * @param original the {@code StandardDeviation} instance to copy |
| */ |
| public StandardDeviation(StandardDeviation original) { |
| copy(original, this); |
| } |
| |
| /** |
| * Contructs a StandardDeviation with the specified value for the |
| * <code>isBiasCorrected</code> property. If this property is set to |
| * <code>true</code>, the {@link Variance} used in computing results will |
| * use the bias-corrected, or "sample" formula. See {@link Variance} for |
| * details. |
| * |
| * @param isBiasCorrected whether or not the variance computation will use |
| * the bias-corrected formula |
| */ |
| public StandardDeviation(boolean isBiasCorrected) { |
| variance = new Variance(isBiasCorrected); |
| } |
| |
| /** |
| * Contructs a StandardDeviation with the specified value for the |
| * <code>isBiasCorrected</code> property and the supplied external moment. |
| * If <code>isBiasCorrected</code> is set to <code>true</code>, the |
| * {@link Variance} used in computing results will use the bias-corrected, |
| * or "sample" formula. See {@link Variance} for details. |
| * |
| * @param isBiasCorrected whether or not the variance computation will use |
| * the bias-corrected formula |
| * @param m2 the external moment |
| */ |
| public StandardDeviation(boolean isBiasCorrected, SecondMoment m2) { |
| variance = new Variance(isBiasCorrected, m2); |
| } |
| |
| /** |
| * {@inheritDoc} |
| */ |
| @Override |
| public void increment(final double d) { |
| variance.increment(d); |
| } |
| |
| /** |
| * {@inheritDoc} |
| */ |
| public long getN() { |
| return variance.getN(); |
| } |
| |
| /** |
| * {@inheritDoc} |
| */ |
| @Override |
| public double getResult() { |
| return FastMath.sqrt(variance.getResult()); |
| } |
| |
| /** |
| * {@inheritDoc} |
| */ |
| @Override |
| public void clear() { |
| variance.clear(); |
| } |
| |
| /** |
| * Returns the Standard Deviation of the entries in the input array, or |
| * <code>Double.NaN</code> if the array is empty. |
| * <p> |
| * Returns 0 for a single-value (i.e. length = 1) sample.</p> |
| * <p> |
| * Throws <code>IllegalArgumentException</code> if the array is null.</p> |
| * <p> |
| * Does not change the internal state of the statistic.</p> |
| * |
| * @param values the input array |
| * @return the standard deviation of the values or Double.NaN if length = 0 |
| * @throws IllegalArgumentException if the array is null |
| */ |
| @Override |
| public double evaluate(final double[] values) { |
| return FastMath.sqrt(variance.evaluate(values)); |
| } |
| |
| /** |
| * Returns the Standard Deviation of the entries in the specified portion of |
| * the input array, or <code>Double.NaN</code> if the designated subarray |
| * is empty. |
| * <p> |
| * Returns 0 for a single-value (i.e. length = 1) sample. </p> |
| * <p> |
| * Throws <code>IllegalArgumentException</code> if the array is null.</p> |
| * <p> |
| * Does not change the internal state of the statistic.</p> |
| * |
| * @param values the input array |
| * @param begin index of the first array element to include |
| * @param length the number of elements to include |
| * @return the standard deviation of the values or Double.NaN if length = 0 |
| * @throws IllegalArgumentException if the array is null or the array index |
| * parameters are not valid |
| */ |
| @Override |
| public double evaluate(final double[] values, final int begin, final int length) { |
| return FastMath.sqrt(variance.evaluate(values, begin, length)); |
| } |
| |
| /** |
| * Returns the Standard Deviation of the entries in the specified portion of |
| * the input array, using the precomputed mean value. Returns |
| * <code>Double.NaN</code> if the designated subarray is empty. |
| * <p> |
| * Returns 0 for a single-value (i.e. length = 1) sample.</p> |
| * <p> |
| * The formula used assumes that the supplied mean value is the arithmetic |
| * mean of the sample data, not a known population parameter. This method |
| * is supplied only to save computation when the mean has already been |
| * computed.</p> |
| * <p> |
| * Throws <code>IllegalArgumentException</code> if the array is null.</p> |
| * <p> |
| * Does not change the internal state of the statistic.</p> |
| * |
| * @param values the input array |
| * @param mean the precomputed mean value |
| * @param begin index of the first array element to include |
| * @param length the number of elements to include |
| * @return the standard deviation of the values or Double.NaN if length = 0 |
| * @throws IllegalArgumentException if the array is null or the array index |
| * parameters are not valid |
| */ |
| public double evaluate(final double[] values, final double mean, |
| final int begin, final int length) { |
| return FastMath.sqrt(variance.evaluate(values, mean, begin, length)); |
| } |
| |
| /** |
| * Returns the Standard Deviation of the entries in the input array, using |
| * the precomputed mean value. Returns |
| * <code>Double.NaN</code> if the designated subarray is empty. |
| * <p> |
| * Returns 0 for a single-value (i.e. length = 1) sample.</p> |
| * <p> |
| * The formula used assumes that the supplied mean value is the arithmetic |
| * mean of the sample data, not a known population parameter. This method |
| * is supplied only to save computation when the mean has already been |
| * computed.</p> |
| * <p> |
| * Throws <code>IllegalArgumentException</code> if the array is null.</p> |
| * <p> |
| * Does not change the internal state of the statistic.</p> |
| * |
| * @param values the input array |
| * @param mean the precomputed mean value |
| * @return the standard deviation of the values or Double.NaN if length = 0 |
| * @throws IllegalArgumentException if the array is null |
| */ |
| public double evaluate(final double[] values, final double mean) { |
| return FastMath.sqrt(variance.evaluate(values, mean)); |
| } |
| |
| /** |
| * @return Returns the isBiasCorrected. |
| */ |
| public boolean isBiasCorrected() { |
| return variance.isBiasCorrected(); |
| } |
| |
| /** |
| * @param isBiasCorrected The isBiasCorrected to set. |
| */ |
| public void setBiasCorrected(boolean isBiasCorrected) { |
| variance.setBiasCorrected(isBiasCorrected); |
| } |
| |
| /** |
| * {@inheritDoc} |
| */ |
| @Override |
| public StandardDeviation copy() { |
| StandardDeviation result = new StandardDeviation(); |
| copy(this, result); |
| return result; |
| } |
| |
| |
| /** |
| * Copies source to dest. |
| * <p>Neither source nor dest can be null.</p> |
| * |
| * @param source StandardDeviation to copy |
| * @param dest StandardDeviation to copy to |
| * @throws NullPointerException if either source or dest is null |
| */ |
| public static void copy(StandardDeviation source, StandardDeviation dest) { |
| dest.setData(source.getDataRef()); |
| dest.variance = source.variance.copy(); |
| } |
| |
| } |