001    /*
002     * Licensed to the Apache Software Foundation (ASF) under one or more
003     * contributor license agreements.  See the NOTICE file distributed with
004     * this work for additional information regarding copyright ownership.
005     * The ASF licenses this file to You under the Apache License, Version 2.0
006     * (the "License"); you may not use this file except in compliance with
007     * the License.  You may obtain a copy of the License at
008     *
009     *      http://www.apache.org/licenses/LICENSE-2.0
010     *
011     * Unless required by applicable law or agreed to in writing, software
012     * distributed under the License is distributed on an "AS IS" BASIS,
013     * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
014     * See the License for the specific language governing permissions and
015     * limitations under the License.
016     */
017    
018    package org.apache.commons.math.optimization.fitting;
019    
020    import java.io.Serializable;
021    
022    import org.apache.commons.math.exception.DimensionMismatchException;
023    import org.apache.commons.math.exception.util.LocalizedFormats;
024    import org.apache.commons.math.exception.ZeroException;
025    import org.apache.commons.math.exception.NullArgumentException;
026    import org.apache.commons.math.optimization.fitting.ParametricRealFunction;
027    
028    /**
029     * A Gaussian function.  Specifically:
030     * <p>
031     * <tt>f(x) = a + b*exp(-((x - c)^2 / (2*d^2)))</tt>
032     * <p>
033     * The parameters have the following meaning:
034     * <ul>
035     * <li><tt>a</tt> is a constant offset that shifts <tt>f(x)</tt> up or down
036     * <li><tt>b</tt> is the height of the peak
037     * <li><tt>c</tt> is the position of the center of the peak
038     * <li><tt>d</tt> is related to the FWHM by <tt>FWHM = 2*sqrt(2*ln(2))*d</tt>
039     * </ul>
040     * Notation key:
041     * <ul>
042     * <li><tt>x^n</tt>: <tt>x</tt> raised to the power of <tt>n</tt>
043     * <li><tt>exp(x)</tt>: <i>e</i><tt>^x</tt>
044     * <li><tt>sqrt(x)</tt>: the square root of <tt>x</tt>
045     * <li><tt>ln(x)</tt>: the natural logarithm of <tt>x</tt>
046     * </ul>
047     * References:
048     * <ul>
049     * <li><a href="http://en.wikipedia.org/wiki/Gaussian_function">Wikipedia:
050     *   Gaussian function</a>
051     * </ul>
052     *
053     * @since 2.2
054     * @version $Revision: 1037327 $ $Date: 2010-11-20 21:57:37 +0100 (sam. 20 nov. 2010) $
055     */
056    public class ParametricGaussianFunction implements ParametricRealFunction, Serializable {
057    
058        /** Serializable version Id. */
059        private static final long serialVersionUID = -3875578602503903233L;
060    
061        /**
062         * Constructs an instance.
063         */
064        public ParametricGaussianFunction() {
065        }
066    
067        /**
068         * Computes value of function <tt>f(x)</tt> for the specified <tt>x</tt> and
069         * parameters <tt>a</tt>, <tt>b</tt>, <tt>c</tt>, and <tt>d</tt>.
070         *
071         * @param x <tt>x</tt> value
072         * @param parameters values of <tt>a</tt>, <tt>b</tt>, <tt>c</tt>, and
073         *        <tt>d</tt>
074         *
075         * @return value of <tt>f(x)</tt> evaluated at <tt>x</tt> with the specified
076         *         parameters
077         *
078         * @throws IllegalArgumentException if <code>parameters</code> is invalid as
079         *         determined by {@link #validateParameters(double[])}
080         * @throws ZeroException if <code>parameters</code> values are
081         *         invalid as determined by {@link #validateParameters(double[])}
082         */
083        public double value(double x, double[] parameters) throws ZeroException {
084            validateParameters(parameters);
085            final double a = parameters[0];
086            final double b = parameters[1];
087            final double c = parameters[2];
088            final double d = parameters[3];
089            final double xMc = x - c;
090            return a + b * Math.exp(-xMc * xMc / (2.0 * (d * d)));
091        }
092    
093        /**
094         * Computes the gradient vector for a four variable version of the function
095         * where the parameters, <tt>a</tt>, <tt>b</tt>, <tt>c</tt>, and <tt>d</tt>,
096         * are considered the variables, not <tt>x</tt>.  That is, instead of
097         * computing the gradient vector for the function <tt>f(x)</tt> (which would
098         * just be the derivative of <tt>f(x)</tt> with respect to <tt>x</tt> since
099         * it's a one-dimensional function), computes the gradient vector for the
100         * function <tt>f(a, b, c, d) = a + b*exp(-((x - c)^2 / (2*d^2)))</tt>
101         * treating the specified <tt>x</tt> as a constant.
102         * <p>
103         * The components of the computed gradient vector are the partial
104         * derivatives of <tt>f(a, b, c, d)</tt> with respect to each variable.
105         * That is, the partial derivative of <tt>f(a, b, c, d)</tt> with respect to
106         * <tt>a</tt>, the partial derivative of <tt>f(a, b, c, d)</tt> with respect
107         * to <tt>b</tt>, the partial derivative of <tt>f(a, b, c, d)</tt> with
108         * respect to <tt>c</tt>, and the partial derivative of <tt>f(a, b, c,
109         * d)</tt> with respect to <tt>d</tt>.
110         *
111         * @param x <tt>x</tt> value to be used as constant in <tt>f(a, b, c,
112         *        d)</tt>
113         * @param parameters values of <tt>a</tt>, <tt>b</tt>, <tt>c</tt>, and
114         *        <tt>d</tt> for computation of gradient vector of <tt>f(a, b, c,
115         *        d)</tt>
116         *
117         * @return gradient vector of <tt>f(a, b, c, d)</tt>
118         *
119         * @throws IllegalArgumentException if <code>parameters</code> is invalid as
120         *         determined by {@link #validateParameters(double[])}
121         * @throws ZeroException if <code>parameters</code> values are
122         *         invalid as determined by {@link #validateParameters(double[])}
123         */
124        public double[] gradient(double x, double[] parameters) throws ZeroException {
125    
126            validateParameters(parameters);
127            final double b = parameters[1];
128            final double c = parameters[2];
129            final double d = parameters[3];
130    
131            final double xMc  = x - c;
132            final double d2   = d * d;
133            final double exp  = Math.exp(-xMc * xMc / (2 * d2));
134            final double f    = b * exp * xMc / d2;
135    
136            return new double[] { 1.0, exp, f, f * xMc / d };
137    
138        }
139    
140        /**
141         * Validates parameters to ensure they are appropriate for the evaluation of
142         * the <code>value</code> and <code>gradient</code> methods.
143         *
144         * @param parameters values of <tt>a</tt>, <tt>b</tt>, <tt>c</tt>, and
145         *        <tt>d</tt>
146         *
147         * @throws IllegalArgumentException if <code>parameters</code> is
148         *         <code>null</code> or if <code>parameters</code> does not have
149         *         length == 4
150         * @throws ZeroException if <code>parameters[3]</code>
151         *         (<tt>d</tt>) is 0
152         */
153        private void validateParameters(double[] parameters) throws ZeroException {
154            if (parameters == null) {
155                throw new NullArgumentException(LocalizedFormats.INPUT_ARRAY);
156            }
157            if (parameters.length != 4) {
158                throw new DimensionMismatchException(4, parameters.length);
159            }
160            if (parameters[3] == 0.0) {
161                throw new ZeroException();
162            }
163        }
164    
165    }