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Java example source code file (StandardDeviation.java)

This example Java source code file (StandardDeviation.java) is included in the alvinalexander.com "Java Source Code Warehouse" project. The intent of this project is to help you "Learn Java by Example" TM.

Learn more about this Java project at its project page.

Java - Java tags/keywords

abstractstorelessunivariatestatistic, mathillegalargumentexception, nullargumentexception, override, secondmoment, serializable, standarddeviation, variance

The StandardDeviation.java Java example source code

/*
 * 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.math3.stat.descriptive.moment;

import java.io.Serializable;

import org.apache.commons.math3.exception.MathIllegalArgumentException;
import org.apache.commons.math3.exception.NullArgumentException;
import org.apache.commons.math3.stat.descriptive.AbstractStorelessUnivariateStatistic;
import org.apache.commons.math3.util.FastMath;
import org.apache.commons.math3.util.MathUtils;

/**
 * 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 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. If
 * multiple threads access an instance of this class concurrently, and at least
 * one of the threads invokes the <code>increment() or
 * <code>clear() method, it must be synchronized externally.

* */ 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 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 * @throws NullArgumentException if original is null */ public StandardDeviation(StandardDeviation original) throws NullArgumentException { copy(original, this); } /** * Contructs a StandardDeviation with the specified value for the * <code>isBiasCorrected property. If this property is set to * <code>true, 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 property and the supplied external moment. * If <code>isBiasCorrected is set to true, 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 if the array is empty. * <p> * Returns 0 for a single-value (i.e. length = 1) sample.</p> * <p> * Throws <code>MathIllegalArgumentException if the array is null.

* <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 MathIllegalArgumentException if the array is null */ @Override public double evaluate(final double[] values) throws MathIllegalArgumentException { 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 if the designated subarray * is empty. * <p> * Returns 0 for a single-value (i.e. length = 1) sample. </p> * <p> * Throws <code>MathIllegalArgumentException if the array is null.

* <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 MathIllegalArgumentException 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) throws MathIllegalArgumentException { 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 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 if the array is null.

* <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 MathIllegalArgumentException 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) throws MathIllegalArgumentException { 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 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>MathIllegalArgumentException if the array is null.

* <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 MathIllegalArgumentException if the array is null */ public double evaluate(final double[] values, final double mean) throws MathIllegalArgumentException { 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(); // No try-catch or advertised exception because args are guaranteed non-null copy(this, result); return result; } /** * Copies source to dest. * <p>Neither source nor dest can be null.

* * @param source StandardDeviation to copy * @param dest StandardDeviation to copy to * @throws NullArgumentException if either source or dest is null */ public static void copy(StandardDeviation source, StandardDeviation dest) throws NullArgumentException { MathUtils.checkNotNull(source); MathUtils.checkNotNull(dest); dest.setData(source.getDataRef()); dest.variance = source.variance.copy(); } }

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