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 */
017package org.apache.commons.math3.transform;
018
019import java.io.Serializable;
020
021import org.apache.commons.math3.analysis.FunctionUtils;
022import org.apache.commons.math3.analysis.UnivariateFunction;
023import org.apache.commons.math3.exception.MathIllegalArgumentException;
024import org.apache.commons.math3.exception.util.LocalizedFormats;
025import org.apache.commons.math3.util.ArithmeticUtils;
026
027/**
028 * Implements the <a href="http://www.archive.chipcenter.com/dsp/DSP000517F1.html">Fast Hadamard Transform</a> (FHT).
029 * Transformation of an input vector x to the output vector y.
030 * <p>
031 * In addition to transformation of real vectors, the Hadamard transform can
032 * transform integer vectors into integer vectors. However, this integer transform
033 * cannot be inverted directly. Due to a scaling factor it may lead to rational results.
034 * As an example, the inverse transform of integer vector (0, 1, 0, 1) is rational
035 * vector (1/2, -1/2, 0, 0).
036 *
037 * @version $Id: FastHadamardTransformer.java 1385310 2012-09-16 16:32:10Z tn $
038 * @since 2.0
039 */
040public class FastHadamardTransformer implements RealTransformer, Serializable {
041
042    /** Serializable version identifier. */
043    static final long serialVersionUID = 20120211L;
044
045    /**
046     * {@inheritDoc}
047     *
048     * @throws MathIllegalArgumentException if the length of the data array is
049     * not a power of two
050     */
051    public double[] transform(final double[] f, final TransformType type) {
052        if (type == TransformType.FORWARD) {
053            return fht(f);
054        }
055        return TransformUtils.scaleArray(fht(f), 1.0 / f.length);
056    }
057
058    /**
059     * {@inheritDoc}
060     *
061     * @throws org.apache.commons.math3.exception.NonMonotonicSequenceException
062     *   if the lower bound is greater than, or equal to the upper bound
063     * @throws org.apache.commons.math3.exception.NotStrictlyPositiveException
064     *   if the number of sample points is negative
065     * @throws MathIllegalArgumentException if the number of sample points is not a power of two
066     */
067    public double[] transform(final UnivariateFunction f,
068        final double min, final double max, final int n,
069        final TransformType type) {
070
071        return transform(FunctionUtils.sample(f, min, max, n), type);
072    }
073
074    /**
075     * Returns the forward transform of the specified integer data set.The
076     * integer transform cannot be inverted directly, due to a scaling factor
077     * which may lead to double results.
078     *
079     * @param f the integer data array to be transformed (signal)
080     * @return the integer transformed array (spectrum)
081     * @throws MathIllegalArgumentException if the length of the data array is not a power of two
082     */
083    public int[] transform(final int[] f) {
084        return fht(f);
085    }
086
087    /**
088     * The FHT (Fast Hadamard Transformation) which uses only subtraction and
089     * addition. Requires {@code N * log2(N) = n * 2^n} additions.
090     *
091     * <h3>Short Table of manual calculation for N=8</h3>
092     * <ol>
093     * <li><b>x</b> is the input vector to be transformed,</li>
094     * <li><b>y</b> is the output vector (Fast Hadamard transform of <b>x</b>),</li>
095     * <li>a and b are helper rows.</li>
096     * </ol>
097     * <table align="center" border="1" cellpadding="3">
098     * <tbody align="center">
099     * <tr>
100     *     <th>x</th>
101     *     <th>a</th>
102     *     <th>b</th>
103     *     <th>y</th>
104     * </tr>
105     * <tr>
106     *     <th>x<sub>0</sub></th>
107     *     <td>a<sub>0</sub> = x<sub>0</sub> + x<sub>1</sub></td>
108     *     <td>b<sub>0</sub> = a<sub>0</sub> + a<sub>1</sub></td>
109     *     <td>y<sub>0</sub> = b<sub>0</sub >+ b<sub>1</sub></td>
110     * </tr>
111     * <tr>
112     *     <th>x<sub>1</sub></th>
113     *     <td>a<sub>1</sub> = x<sub>2</sub> + x<sub>3</sub></td>
114     *     <td>b<sub>0</sub> = a<sub>2</sub> + a<sub>3</sub></td>
115     *     <td>y<sub>0</sub> = b<sub>2</sub> + b<sub>3</sub></td>
116     * </tr>
117     * <tr>
118     *     <th>x<sub>2</sub></th>
119     *     <td>a<sub>2</sub> = x<sub>4</sub> + x<sub>5</sub></td>
120     *     <td>b<sub>0</sub> = a<sub>4</sub> + a<sub>5</sub></td>
121     *     <td>y<sub>0</sub> = b<sub>4</sub> + b<sub>5</sub></td>
122     * </tr>
123     * <tr>
124     *     <th>x<sub>3</sub></th>
125     *     <td>a<sub>3</sub> = x<sub>6</sub> + x<sub>7</sub></td>
126     *     <td>b<sub>0</sub> = a<sub>6</sub> + a<sub>7</sub></td>
127     *     <td>y<sub>0</sub> = b<sub>6</sub> + b<sub>7</sub></td>
128     * </tr>
129     * <tr>
130     *     <th>x<sub>4</sub></th>
131     *     <td>a<sub>0</sub> = x<sub>0</sub> - x<sub>1</sub></td>
132     *     <td>b<sub>0</sub> = a<sub>0</sub> - a<sub>1</sub></td>
133     *     <td>y<sub>0</sub> = b<sub>0</sub> - b<sub>1</sub></td>
134     * </tr>
135     * <tr>
136     *     <th>x<sub>5</sub></th>
137     *     <td>a<sub>1</sub> = x<sub>2</sub> - x<sub>3</sub></td>
138     *     <td>b<sub>0</sub> = a<sub>2</sub> - a<sub>3</sub></td>
139     *     <td>y<sub>0</sub> = b<sub>2</sub> - b<sub>3</sub></td>
140     * </tr>
141     * <tr>
142     *     <th>x<sub>6</sub></th>
143     *     <td>a<sub>2</sub> = x<sub>4</sub> - x<sub>5</sub></td>
144     *     <td>b<sub>0</sub> = a<sub>4</sub> - a<sub>5</sub></td>
145     *     <td>y<sub>0</sub> = b<sub>4</sub> - b<sub>5</sub></td>
146     * </tr>
147     * <tr>
148     *     <th>x<sub>7</sub></th>
149     *     <td>a<sub>3</sub> = x<sub>6</sub> - x<sub>7</sub></td>
150     *     <td>b<sub>0</sub> = a<sub>6</sub> - a<sub>7</sub></td>
151     *     <td>y<sub>0</sub> = b<sub>6</sub> - b<sub>7</sub></td>
152     * </tr>
153     * </tbody>
154     * </table>
155     *
156     * <h3>How it works</h3>
157     * <ol>
158     * <li>Construct a matrix with {@code N} rows and {@code n + 1} columns,
159     * {@code hadm[n+1][N]}.<br/>
160     * <em>(If I use [x][y] it always means [row-offset][column-offset] of a
161     * Matrix with n rows and m columns. Its entries go from M[0][0]
162     * to M[n][N])</em></li>
163     * <li>Place the input vector {@code x[N]} in the first column of the
164     * matrix {@code hadm}.</li>
165     * <li>The entries of the submatrix {@code D_top} are calculated as follows
166     *     <ul>
167     *         <li>{@code D_top} goes from entry {@code [0][1]} to
168     *         {@code [N / 2 - 1][n + 1]},</li>
169     *         <li>the columns of {@code D_top} are the pairwise mutually
170     *         exclusive sums of the previous column.</li>
171     *     </ul>
172     * </li>
173     * <li>The entries of the submatrix {@code D_bottom} are calculated as
174     * follows
175     *     <ul>
176     *         <li>{@code D_bottom} goes from entry {@code [N / 2][1]} to
177     *         {@code [N][n + 1]},</li>
178     *         <li>the columns of {@code D_bottom} are the pairwise differences
179     *         of the previous column.</li>
180     *     </ul>
181     * </li>
182     * <li>The consputation of {@code D_top} and {@code D_bottom} are best
183     * understood with the above example (for {@code N = 8}).
184     * <li>The output vector {@code y} is now in the last column of
185     * {@code hadm}.</li>
186     * <li><em>Algorithm from <a href="http://www.archive.chipcenter.com/dsp/DSP000517F1.html">chipcenter</a>.</em></li>
187     * </ol>
188     * <h3>Visually</h3>
189     * <table border="1" align="center" cellpadding="3">
190     * <tbody align="center">
191     * <tr>
192     *     <td></td><th>0</th><th>1</th><th>2</th><th>3</th>
193     *     <th>&hellip;</th>
194     *     <th>n + 1</th>
195     * </tr>
196     * <tr>
197     *     <th>0</th>
198     *     <td>x<sub>0</sub></td>
199     *     <td colspan="5" rowspan="5" align="center" valign="middle">
200     *         &uarr;<br/>
201     *         &larr; D<sub>top</sub> &rarr;<br/>
202     *         &darr;
203     *     </td>
204     * </tr>
205     * <tr><th>1</th><td>x<sub>1</sub></td></tr>
206     * <tr><th>2</th><td>x<sub>2</sub></td></tr>
207     * <tr><th>&hellip;</th><td>&hellip;</td></tr>
208     * <tr><th>N / 2 - 1</th><td>x<sub>N/2-1</sub></td></tr>
209     * <tr>
210     *     <th>N / 2</th>
211     *     <td>x<sub>N/2</sub></td>
212     *     <td colspan="5" rowspan="5" align="center" valign="middle">
213     *         &uarr;<br/>
214     *         &larr; D<sub>bottom</sub> &rarr;<br/>
215     *         &darr;
216     *     </td>
217     * </tr>
218     * <tr><th>N / 2 + 1</th><td>x<sub>N/2+1</sub></td></tr>
219     * <tr><th>N / 2 + 2</th><td>x<sub>N/2+2</sub></td></tr>
220     * <tr><th>&hellip;</th><td>&hellip;</td></tr>
221     * <tr><th>N</th><td>x<sub>N</sub></td></tr>
222     * </tbody>
223     * </table>
224     *
225     * @param x the real data array to be transformed
226     * @return the real transformed array, {@code y}
227     * @throws MathIllegalArgumentException if the length of the data array is not a power of two
228     */
229    protected double[] fht(double[] x) throws MathIllegalArgumentException {
230
231        final int n     = x.length;
232        final int halfN = n / 2;
233
234        if (!ArithmeticUtils.isPowerOfTwo(n)) {
235            throw new MathIllegalArgumentException(
236                    LocalizedFormats.NOT_POWER_OF_TWO,
237                    Integer.valueOf(n));
238        }
239
240        /*
241         * Instead of creating a matrix with p+1 columns and n rows, we use two
242         * one dimension arrays which we are used in an alternating way.
243         */
244        double[] yPrevious = new double[n];
245        double[] yCurrent  = x.clone();
246
247        // iterate from left to right (column)
248        for (int j = 1; j < n; j <<= 1) {
249
250            // switch columns
251            final double[] yTmp = yCurrent;
252            yCurrent  = yPrevious;
253            yPrevious = yTmp;
254
255            // iterate from top to bottom (row)
256            for (int i = 0; i < halfN; ++i) {
257                // Dtop: the top part works with addition
258                final int twoI = 2 * i;
259                yCurrent[i] = yPrevious[twoI] + yPrevious[twoI + 1];
260            }
261            for (int i = halfN; i < n; ++i) {
262                // Dbottom: the bottom part works with subtraction
263                final int twoI = 2 * i;
264                yCurrent[i] = yPrevious[twoI - n] - yPrevious[twoI - n + 1];
265            }
266        }
267
268        return yCurrent;
269
270    }
271
272    /**
273     * Returns the forward transform of the specified integer data set. The FHT
274     * (Fast Hadamard Transform) uses only subtraction and addition.
275     *
276     * @param x the integer data array to be transformed
277     * @return the integer transformed array, {@code y}
278     * @throws MathIllegalArgumentException if the length of the data array is not a power of two
279     */
280    protected int[] fht(int[] x) throws MathIllegalArgumentException {
281
282        final int n     = x.length;
283        final int halfN = n / 2;
284
285        if (!ArithmeticUtils.isPowerOfTwo(n)) {
286            throw new MathIllegalArgumentException(
287                    LocalizedFormats.NOT_POWER_OF_TWO,
288                    Integer.valueOf(n));
289        }
290
291        /*
292         * Instead of creating a matrix with p+1 columns and n rows, we use two
293         * one dimension arrays which we are used in an alternating way.
294         */
295        int[] yPrevious = new int[n];
296        int[] yCurrent  = x.clone();
297
298        // iterate from left to right (column)
299        for (int j = 1; j < n; j <<= 1) {
300
301            // switch columns
302            final int[] yTmp = yCurrent;
303            yCurrent  = yPrevious;
304            yPrevious = yTmp;
305
306            // iterate from top to bottom (row)
307            for (int i = 0; i < halfN; ++i) {
308                // Dtop: the top part works with addition
309                final int twoI = 2 * i;
310                yCurrent[i] = yPrevious[twoI] + yPrevious[twoI + 1];
311            }
312            for (int i = halfN; i < n; ++i) {
313                // Dbottom: the bottom part works with subtraction
314                final int twoI = 2 * i;
315                yCurrent[i] = yPrevious[twoI - n] - yPrevious[twoI - n + 1];
316            }
317        }
318
319        // return the last computed output vector y
320        return yCurrent;
321
322    }
323
324}