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    package org.apache.commons.math3.special;
018    
019    import org.apache.commons.math3.util.FastMath;
020    
021    /**
022     * This is a utility class that provides computation methods related to the
023     * error functions.
024     *
025     * @version $Id: Erf.java 1456905 2013-03-15 11:37:35Z luc $
026     */
027    public class Erf {
028    
029        /**
030         * The number {@code X_CRIT} is used by {@link #erf(double, double)} internally.
031         * This number solves {@code erf(x)=0.5} within 1ulp.
032         * More precisely, the current implementations of
033         * {@link #erf(double)} and {@link #erfc(double)} satisfy:<br/>
034         * {@code erf(X_CRIT) < 0.5},<br/>
035         * {@code erf(Math.nextUp(X_CRIT) > 0.5},<br/>
036         * {@code erfc(X_CRIT) = 0.5}, and<br/>
037         * {@code erfc(Math.nextUp(X_CRIT) < 0.5}
038         */
039        private static final double X_CRIT = 0.4769362762044697;
040    
041        /**
042         * Default constructor.  Prohibit instantiation.
043         */
044        private Erf() {}
045    
046        /**
047         * Returns the error function.
048         *
049         * <p>erf(x) = 2/&radic;&pi; <sub>0</sub>&int;<sup>x</sup> e<sup>-t<sup>2</sup></sup>dt </p>
050         *
051         * <p>This implementation computes erf(x) using the
052         * {@link Gamma#regularizedGammaP(double, double, double, int) regularized gamma function},
053         * following <a href="http://mathworld.wolfram.com/Erf.html"> Erf</a>, equation (3)</p>
054         *
055         * <p>The value returned is always between -1 and 1 (inclusive).
056         * If {@code abs(x) > 40}, then {@code erf(x)} is indistinguishable from
057         * either 1 or -1 as a double, so the appropriate extreme value is returned.
058         * </p>
059         *
060         * @param x the value.
061         * @return the error function erf(x)
062         * @throws org.apache.commons.math3.exception.MaxCountExceededException
063         * if the algorithm fails to converge.
064         * @see Gamma#regularizedGammaP(double, double, double, int)
065         */
066        public static double erf(double x) {
067            if (FastMath.abs(x) > 40) {
068                return x > 0 ? 1 : -1;
069            }
070            final double ret = Gamma.regularizedGammaP(0.5, x * x, 1.0e-15, 10000);
071            return x < 0 ? -ret : ret;
072        }
073    
074        /**
075         * Returns the complementary error function.
076         *
077         * <p>erfc(x) = 2/&radic;&pi; <sub>x</sub>&int;<sup>&infin;</sup> e<sup>-t<sup>2</sup></sup>dt
078         * <br/>
079         *    = 1 - {@link #erf(double) erf(x)} </p>
080         *
081         * <p>This implementation computes erfc(x) using the
082         * {@link Gamma#regularizedGammaQ(double, double, double, int) regularized gamma function},
083         * following <a href="http://mathworld.wolfram.com/Erf.html"> Erf</a>, equation (3).</p>
084         *
085         * <p>The value returned is always between 0 and 2 (inclusive).
086         * If {@code abs(x) > 40}, then {@code erf(x)} is indistinguishable from
087         * either 0 or 2 as a double, so the appropriate extreme value is returned.
088         * </p>
089         *
090         * @param x the value
091         * @return the complementary error function erfc(x)
092         * @throws org.apache.commons.math3.exception.MaxCountExceededException
093         * if the algorithm fails to converge.
094         * @see Gamma#regularizedGammaQ(double, double, double, int)
095         * @since 2.2
096         */
097        public static double erfc(double x) {
098            if (FastMath.abs(x) > 40) {
099                return x > 0 ? 0 : 2;
100            }
101            final double ret = Gamma.regularizedGammaQ(0.5, x * x, 1.0e-15, 10000);
102            return x < 0 ? 2 - ret : ret;
103        }
104    
105        /**
106         * Returns the difference between erf(x1) and erf(x2).
107         *
108         * The implementation uses either erf(double) or erfc(double)
109         * depending on which provides the most precise result.
110         *
111         * @param x1 the first value
112         * @param x2 the second value
113         * @return erf(x2) - erf(x1)
114         */
115        public static double erf(double x1, double x2) {
116            if(x1 > x2) {
117                return -erf(x2, x1);
118            }
119    
120            return
121            x1 < -X_CRIT ?
122                x2 < 0.0 ?
123                    erfc(-x2) - erfc(-x1) :
124                    erf(x2) - erf(x1) :
125                x2 > X_CRIT && x1 > 0.0 ?
126                    erfc(x1) - erfc(x2) :
127                    erf(x2) - erf(x1);
128        }
129    
130        /**
131         * Returns the inverse erf.
132         * <p>
133         * This implementation is described in the paper:
134         * <a href="http://people.maths.ox.ac.uk/gilesm/files/gems_erfinv.pdf">Approximating
135         * the erfinv function</a> by Mike Giles, Oxford-Man Institute of Quantitative Finance,
136         * which was published in GPU Computing Gems, volume 2, 2010.
137         * The source code is available <a href="http://gpucomputing.net/?q=node/1828">here</a>.
138         * </p>
139         * @param x the value
140         * @return t such that x = erf(t)
141         * @since 3.2
142         */
143        public static double erfInv(final double x) {
144    
145            // beware that the logarithm argument must be
146            // commputed as (1.0 - x) * (1.0 + x),
147            // it must NOT be simplified as 1.0 - x * x as this
148            // would induce rounding errors near the boundaries +/-1
149            double w = - FastMath.log((1.0 - x) * (1.0 + x));
150            double p;
151    
152            if (w < 6.25) {
153                w = w - 3.125;
154                p =  -3.6444120640178196996e-21;
155                p =   -1.685059138182016589e-19 + p * w;
156                p =   1.2858480715256400167e-18 + p * w;
157                p =    1.115787767802518096e-17 + p * w;
158                p =   -1.333171662854620906e-16 + p * w;
159                p =   2.0972767875968561637e-17 + p * w;
160                p =   6.6376381343583238325e-15 + p * w;
161                p =  -4.0545662729752068639e-14 + p * w;
162                p =  -8.1519341976054721522e-14 + p * w;
163                p =   2.6335093153082322977e-12 + p * w;
164                p =  -1.2975133253453532498e-11 + p * w;
165                p =  -5.4154120542946279317e-11 + p * w;
166                p =    1.051212273321532285e-09 + p * w;
167                p =  -4.1126339803469836976e-09 + p * w;
168                p =  -2.9070369957882005086e-08 + p * w;
169                p =   4.2347877827932403518e-07 + p * w;
170                p =  -1.3654692000834678645e-06 + p * w;
171                p =  -1.3882523362786468719e-05 + p * w;
172                p =    0.0001867342080340571352 + p * w;
173                p =  -0.00074070253416626697512 + p * w;
174                p =   -0.0060336708714301490533 + p * w;
175                p =      0.24015818242558961693 + p * w;
176                p =       1.6536545626831027356 + p * w;
177            } else if (w < 16.0) {
178                w = FastMath.sqrt(w) - 3.25;
179                p =   2.2137376921775787049e-09;
180                p =   9.0756561938885390979e-08 + p * w;
181                p =  -2.7517406297064545428e-07 + p * w;
182                p =   1.8239629214389227755e-08 + p * w;
183                p =   1.5027403968909827627e-06 + p * w;
184                p =   -4.013867526981545969e-06 + p * w;
185                p =   2.9234449089955446044e-06 + p * w;
186                p =   1.2475304481671778723e-05 + p * w;
187                p =  -4.7318229009055733981e-05 + p * w;
188                p =   6.8284851459573175448e-05 + p * w;
189                p =   2.4031110387097893999e-05 + p * w;
190                p =   -0.0003550375203628474796 + p * w;
191                p =   0.00095328937973738049703 + p * w;
192                p =   -0.0016882755560235047313 + p * w;
193                p =    0.0024914420961078508066 + p * w;
194                p =   -0.0037512085075692412107 + p * w;
195                p =     0.005370914553590063617 + p * w;
196                p =       1.0052589676941592334 + p * w;
197                p =       3.0838856104922207635 + p * w;
198            } else if (!Double.isInfinite(w)) {
199                w = FastMath.sqrt(w) - 5.0;
200                p =  -2.7109920616438573243e-11;
201                p =  -2.5556418169965252055e-10 + p * w;
202                p =   1.5076572693500548083e-09 + p * w;
203                p =  -3.7894654401267369937e-09 + p * w;
204                p =   7.6157012080783393804e-09 + p * w;
205                p =  -1.4960026627149240478e-08 + p * w;
206                p =   2.9147953450901080826e-08 + p * w;
207                p =  -6.7711997758452339498e-08 + p * w;
208                p =   2.2900482228026654717e-07 + p * w;
209                p =  -9.9298272942317002539e-07 + p * w;
210                p =   4.5260625972231537039e-06 + p * w;
211                p =  -1.9681778105531670567e-05 + p * w;
212                p =   7.5995277030017761139e-05 + p * w;
213                p =  -0.00021503011930044477347 + p * w;
214                p =  -0.00013871931833623122026 + p * w;
215                p =       1.0103004648645343977 + p * w;
216                p =       4.8499064014085844221 + p * w;
217            } else {
218                // this branch does not appears in the original code, it
219                // was added because the previous branch does not handle
220                // x = +/-1 correctly. In this case, w is positive infinity
221                // and as the first coefficient (-2.71e-11) is negative.
222                // Once the first multiplication is done, p becomes negative
223                // infinity and remains so throughout the polynomial evaluation.
224                // So the branch above incorrectly returns negative infinity
225                // instead of the correct positive infinity.
226                p = Double.POSITIVE_INFINITY;
227            }
228    
229            return p * x;
230    
231        }
232    
233        /**
234         * Returns the inverse erfc.
235         * @param x the value
236         * @return t such that x = erfc(t)
237         * @since 3.2
238         */
239        public static double erfcInv(final double x) {
240            return erfInv(1 - x);
241        }
242    
243    }
244