[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
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@ -1356,43 +1356,44 @@ public class MathArrays {
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/**
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* Calculates the convolution between two sequences.
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* <p>
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* The solution is obtained via straightforward computation of the convolution sum (and not via FFT; for longer sequences,
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* the performance of this method might be inferior to an FFT-based implementation).
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* The solution is obtained via straightforward computation of the convolution sum (and not via FFT;
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* for longer sequences, the performance of this method might be inferior to an FFT-based implementation).
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*
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* @param x the first sequence (double array of length {@code N}); the sequence is assumed to be zero elsewhere
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* (i.e. {x[i]}=0 for i<0 and i>={@code N}). Typically, this sequence will represent an input signal to a system.
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* @param h the second sequence (double array of length {@code M}); the sequence is assumed to be zero elsewhere
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* (i.e. {h[i]}=0 for i<0 and i>={@code M}). Typically, this sequence will represent the impulse response of the system.
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* @param x the first sequence (double array of length {@code N});
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* the sequence is assumed to be zero elsewhere (i.e. {x[i]}=0 for i<0 and i>={@code N}).
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* Typically, this sequence will represent an input signal to a system.
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* @param h the second sequence (double array of length {@code M});
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* the sequence is assumed to be zero elsewhere (i.e. {h[i]}=0 for i<0 and i>={@code M}).
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* Typically, this sequence will represent the impulse response of the system.
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* @return the convolution of {@code x} and {@code h} (double array of length {@code N} + {@code M} -1)
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* @throws NullArgumentException if either {@code x} or {@code h} is null
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* @throws NoDataException if either {@code x} or {@code h} is empty
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*
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* @see <a href="http://en.wikipedia.org/wiki/Convolution">Convolution (Wikipedia)</a>
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* @since 4.0
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* @since 3.3
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*/
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public static double[] convolve(double[] x, double[] h) throws NullArgumentException, NoDataException {
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MathUtils.checkNotNull(x);
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MathUtils.checkNotNull(h);
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final int N = x.length;
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final int M = h.length;
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final int lenX = x.length;
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final int lenH = h.length;
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if (N == 0 || M == 0) {
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if (lenX == 0 || lenH == 0) {
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throw new NoDataException();
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}
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// initialize the output array
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final int totalLength = N + M - 1;
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final int totalLength = lenX + lenH - 1;
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final double[] y = new double[totalLength];
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// straightforward implementation of the convolution sum
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for (int n = 0; n < totalLength; n++) {
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double yn = 0;
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for (int k = 0; k < M; k++) {
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final int j = n - k;
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if ((j > -1) && (j < N) ) {
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yn = yn + x[j] * h[k];
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}
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int k = FastMath.max(0, n + 1 - lenX);
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int j = n - k;
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while (k < lenH && j >= 0) {
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yn += x[j--] * h[k++];
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}
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y[n] = yn;
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}
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