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[MATH-851] Fix formatting, code style, improve loops. 

git-svn-id: https://svn.apache.org/repos/asf/commons/proper/math/trunk@1489104 13f79535-47bb-0310-9956-ffa450edef68
This commit is contained in:
Thomas Neidhart 2013-06-03 19:00:31 +00:00
parent bd445c9b14
commit d302ce0a95
1 changed files with 17 additions and 16 deletions
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33
src/main/java/org/apache/commons/math3/util/MathArrays.java
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@ -1356,43 +1356,44 @@ public class MathArrays {
/** /**
* Calculates the convolution between two sequences. * Calculates the convolution between two sequences.
* <p> * <p>
* The solution is obtained via straightforward computation of the convolution sum (and not via FFT; for longer sequences, * The solution is obtained via straightforward computation of the convolution sum (and not via FFT;
* the performance of this method might be inferior to an FFT-based implementation). * for longer sequences, the performance of this method might be inferior to an FFT-based implementation).
* *
* @param x the first sequence (double array of length {@code N}); the sequence is assumed to be zero elsewhere * @param x the first sequence (double array of length {@code N});
* (i.e. {x[i]}=0 for i<0 and i>={@code N}). Typically, this sequence will represent an input signal to a system. * the sequence is assumed to be zero elsewhere (i.e. {x[i]}=0 for i<0 and i>={@code N}).
* @param h the second sequence (double array of length {@code M}); the sequence is assumed to be zero elsewhere * Typically, this sequence will represent an input signal to a system.
* (i.e. {h[i]}=0 for i<0 and i>={@code M}). Typically, this sequence will represent the impulse response of the system. * @param h the second sequence (double array of length {@code M});
* the sequence is assumed to be zero elsewhere (i.e. {h[i]}=0 for i<0 and i>={@code M}).
* Typically, this sequence will represent the impulse response of the system.
* @return the convolution of {@code x} and {@code h} (double array of length {@code N} + {@code M} -1) * @return the convolution of {@code x} and {@code h} (double array of length {@code N} + {@code M} -1)
* @throws NullArgumentException if either {@code x} or {@code h} is null * @throws NullArgumentException if either {@code x} or {@code h} is null
* @throws NoDataException if either {@code x} or {@code h} is empty * @throws NoDataException if either {@code x} or {@code h} is empty
* *
* @see <a href="http://en.wikipedia.org/wiki/Convolution">Convolution (Wikipedia)</a> * @see <a href="http://en.wikipedia.org/wiki/Convolution">Convolution (Wikipedia)</a>
* @since 4.0 * @since 3.3
*/ */
public static double[] convolve(double[] x, double[] h) throws NullArgumentException, NoDataException { public static double[] convolve(double[] x, double[] h) throws NullArgumentException, NoDataException {
MathUtils.checkNotNull(x); MathUtils.checkNotNull(x);
MathUtils.checkNotNull(h); MathUtils.checkNotNull(h);
final int N = x.length; final int lenX = x.length;
final int M = h.length; final int lenH = h.length;
if (N == 0 || M == 0) { if (lenX == 0 || lenH == 0) {
throw new NoDataException(); throw new NoDataException();
} }
// initialize the output array // initialize the output array
final int totalLength = N + M - 1; final int totalLength = lenX + lenH - 1;
final double[] y = new double[totalLength]; final double[] y = new double[totalLength];
// straightforward implementation of the convolution sum // straightforward implementation of the convolution sum
for (int n = 0; n < totalLength; n++) { for (int n = 0; n < totalLength; n++) {
double yn = 0; double yn = 0;
for (int k = 0; k < M; k++) { int k = FastMath.max(0, n + 1 - lenX);
final int j = n - k; int j = n - k;
if ((j > -1) && (j < N) ) { while (k < lenH && j >= 0) {
yn = yn + x[j] * h[k]; yn += x[j--] * h[k++];
}
} }
y[n] = yn; y[n] = yn;
} }