| /* |
| * Licensed to the Apache Software Foundation (ASF) under one or more |
| * contributor license agreements. See the NOTICE file distributed with |
| * this work for additional information regarding copyright ownership. |
| * The ASF licenses this file to You under the Apache License, Version 2.0 |
| * (the "License"); you may not use this file except in compliance with |
| * the License. You may obtain a copy of the License at |
| * |
| * http://www.apache.org/licenses/LICENSE-2.0 |
| * |
| * Unless required by applicable law or agreed to in writing, software |
| * distributed under the License is distributed on an "AS IS" BASIS, |
| * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. |
| * See the License for the specific language governing permissions and |
| * limitations under the License. |
| */ |
| package org.apache.commons.math3.transform; |
| |
| import java.io.Serializable; |
| import java.lang.reflect.Array; |
| |
| import org.apache.commons.math3.analysis.FunctionUtils; |
| import org.apache.commons.math3.analysis.UnivariateFunction; |
| import org.apache.commons.math3.complex.Complex; |
| import org.apache.commons.math3.exception.DimensionMismatchException; |
| import org.apache.commons.math3.exception.MathIllegalArgumentException; |
| import org.apache.commons.math3.exception.MathIllegalStateException; |
| import org.apache.commons.math3.exception.util.LocalizedFormats; |
| import org.apache.commons.math3.util.ArithmeticUtils; |
| import org.apache.commons.math3.util.FastMath; |
| import org.apache.commons.math3.util.MathArrays; |
| |
| /** |
| * Implements the Fast Fourier Transform for transformation of one-dimensional |
| * real or complex data sets. For reference, see <em>Applied Numerical Linear |
| * Algebra</em>, ISBN 0898713897, chapter 6. |
| * <p> |
| * There are several variants of the discrete Fourier transform, with various |
| * normalization conventions, which are specified by the parameter |
| * {@link DftNormalization}. |
| * <p> |
| * The current implementation of the discrete Fourier transform as a fast |
| * Fourier transform requires the length of the data set to be a power of 2. |
| * This greatly simplifies and speeds up the code. Users can pad the data with |
| * zeros to meet this requirement. There are other flavors of FFT, for |
| * reference, see S. Winograd, |
| * <i>On computing the discrete Fourier transform</i>, Mathematics of |
| * Computation, 32 (1978), 175 - 199. |
| * |
| * @see DftNormalization |
| * @since 1.2 |
| */ |
| public class FastFourierTransformer implements Serializable { |
| |
| /** Serializable version identifier. */ |
| static final long serialVersionUID = 20120210L; |
| |
| /** |
| * {@code W_SUB_N_R[i]} is the real part of |
| * {@code exp(- 2 * i * pi / n)}: |
| * {@code W_SUB_N_R[i] = cos(2 * pi/ n)}, where {@code n = 2^i}. |
| */ |
| private static final double[] W_SUB_N_R = |
| { 0x1.0p0, -0x1.0p0, 0x1.1a62633145c07p-54, 0x1.6a09e667f3bcdp-1 |
| , 0x1.d906bcf328d46p-1, 0x1.f6297cff75cbp-1, 0x1.fd88da3d12526p-1, 0x1.ff621e3796d7ep-1 |
| , 0x1.ffd886084cd0dp-1, 0x1.fff62169b92dbp-1, 0x1.fffd8858e8a92p-1, 0x1.ffff621621d02p-1 |
| , 0x1.ffffd88586ee6p-1, 0x1.fffff62161a34p-1, 0x1.fffffd8858675p-1, 0x1.ffffff621619cp-1 |
| , 0x1.ffffffd885867p-1, 0x1.fffffff62161ap-1, 0x1.fffffffd88586p-1, 0x1.ffffffff62162p-1 |
| , 0x1.ffffffffd8858p-1, 0x1.fffffffff6216p-1, 0x1.fffffffffd886p-1, 0x1.ffffffffff621p-1 |
| , 0x1.ffffffffffd88p-1, 0x1.fffffffffff62p-1, 0x1.fffffffffffd9p-1, 0x1.ffffffffffff6p-1 |
| , 0x1.ffffffffffffep-1, 0x1.fffffffffffffp-1, 0x1.0p0, 0x1.0p0 |
| , 0x1.0p0, 0x1.0p0, 0x1.0p0, 0x1.0p0 |
| , 0x1.0p0, 0x1.0p0, 0x1.0p0, 0x1.0p0 |
| , 0x1.0p0, 0x1.0p0, 0x1.0p0, 0x1.0p0 |
| , 0x1.0p0, 0x1.0p0, 0x1.0p0, 0x1.0p0 |
| , 0x1.0p0, 0x1.0p0, 0x1.0p0, 0x1.0p0 |
| , 0x1.0p0, 0x1.0p0, 0x1.0p0, 0x1.0p0 |
| , 0x1.0p0, 0x1.0p0, 0x1.0p0, 0x1.0p0 |
| , 0x1.0p0, 0x1.0p0, 0x1.0p0 }; |
| |
| /** |
| * {@code W_SUB_N_I[i]} is the imaginary part of |
| * {@code exp(- 2 * i * pi / n)}: |
| * {@code W_SUB_N_I[i] = -sin(2 * pi/ n)}, where {@code n = 2^i}. |
| */ |
| private static final double[] W_SUB_N_I = |
| { 0x1.1a62633145c07p-52, -0x1.1a62633145c07p-53, -0x1.0p0, -0x1.6a09e667f3bccp-1 |
| , -0x1.87de2a6aea963p-2, -0x1.8f8b83c69a60ap-3, -0x1.917a6bc29b42cp-4, -0x1.91f65f10dd814p-5 |
| , -0x1.92155f7a3667ep-6, -0x1.921d1fcdec784p-7, -0x1.921f0fe670071p-8, -0x1.921f8becca4bap-9 |
| , -0x1.921faaee6472dp-10, -0x1.921fb2aecb36p-11, -0x1.921fb49ee4ea6p-12, -0x1.921fb51aeb57bp-13 |
| , -0x1.921fb539ecf31p-14, -0x1.921fb541ad59ep-15, -0x1.921fb5439d73ap-16, -0x1.921fb544197ap-17 |
| , -0x1.921fb544387bap-18, -0x1.921fb544403c1p-19, -0x1.921fb544422c2p-20, -0x1.921fb54442a83p-21 |
| , -0x1.921fb54442c73p-22, -0x1.921fb54442cefp-23, -0x1.921fb54442d0ep-24, -0x1.921fb54442d15p-25 |
| , -0x1.921fb54442d17p-26, -0x1.921fb54442d18p-27, -0x1.921fb54442d18p-28, -0x1.921fb54442d18p-29 |
| , -0x1.921fb54442d18p-30, -0x1.921fb54442d18p-31, -0x1.921fb54442d18p-32, -0x1.921fb54442d18p-33 |
| , -0x1.921fb54442d18p-34, -0x1.921fb54442d18p-35, -0x1.921fb54442d18p-36, -0x1.921fb54442d18p-37 |
| , -0x1.921fb54442d18p-38, -0x1.921fb54442d18p-39, -0x1.921fb54442d18p-40, -0x1.921fb54442d18p-41 |
| , -0x1.921fb54442d18p-42, -0x1.921fb54442d18p-43, -0x1.921fb54442d18p-44, -0x1.921fb54442d18p-45 |
| , -0x1.921fb54442d18p-46, -0x1.921fb54442d18p-47, -0x1.921fb54442d18p-48, -0x1.921fb54442d18p-49 |
| , -0x1.921fb54442d18p-50, -0x1.921fb54442d18p-51, -0x1.921fb54442d18p-52, -0x1.921fb54442d18p-53 |
| , -0x1.921fb54442d18p-54, -0x1.921fb54442d18p-55, -0x1.921fb54442d18p-56, -0x1.921fb54442d18p-57 |
| , -0x1.921fb54442d18p-58, -0x1.921fb54442d18p-59, -0x1.921fb54442d18p-60 }; |
| |
| /** The type of DFT to be performed. */ |
| private final DftNormalization normalization; |
| |
| /** |
| * Creates a new instance of this class, with various normalization |
| * conventions. |
| * |
| * @param normalization the type of normalization to be applied to the |
| * transformed data |
| */ |
| public FastFourierTransformer(final DftNormalization normalization) { |
| this.normalization = normalization; |
| } |
| |
| /** |
| * Performs identical index bit reversal shuffles on two arrays of identical |
| * size. Each element in the array is swapped with another element based on |
| * the bit-reversal of the index. For example, in an array with length 16, |
| * item at binary index 0011 (decimal 3) would be swapped with the item at |
| * binary index 1100 (decimal 12). |
| * |
| * @param a the first array to be shuffled |
| * @param b the second array to be shuffled |
| */ |
| private static void bitReversalShuffle2(double[] a, double[] b) { |
| final int n = a.length; |
| assert b.length == n; |
| final int halfOfN = n >> 1; |
| |
| int j = 0; |
| for (int i = 0; i < n; i++) { |
| if (i < j) { |
| // swap indices i & j |
| double temp = a[i]; |
| a[i] = a[j]; |
| a[j] = temp; |
| |
| temp = b[i]; |
| b[i] = b[j]; |
| b[j] = temp; |
| } |
| |
| int k = halfOfN; |
| while (k <= j && k > 0) { |
| j -= k; |
| k >>= 1; |
| } |
| j += k; |
| } |
| } |
| |
| /** |
| * Applies the proper normalization to the specified transformed data. |
| * |
| * @param dataRI the unscaled transformed data |
| * @param normalization the normalization to be applied |
| * @param type the type of transform (forward, inverse) which resulted in the specified data |
| */ |
| private static void normalizeTransformedData(final double[][] dataRI, |
| final DftNormalization normalization, final TransformType type) { |
| |
| final double[] dataR = dataRI[0]; |
| final double[] dataI = dataRI[1]; |
| final int n = dataR.length; |
| assert dataI.length == n; |
| |
| switch (normalization) { |
| case STANDARD: |
| if (type == TransformType.INVERSE) { |
| final double scaleFactor = 1.0 / ((double) n); |
| for (int i = 0; i < n; i++) { |
| dataR[i] *= scaleFactor; |
| dataI[i] *= scaleFactor; |
| } |
| } |
| break; |
| case UNITARY: |
| final double scaleFactor = 1.0 / FastMath.sqrt(n); |
| for (int i = 0; i < n; i++) { |
| dataR[i] *= scaleFactor; |
| dataI[i] *= scaleFactor; |
| } |
| break; |
| default: |
| /* |
| * This should never occur in normal conditions. However this |
| * clause has been added as a safeguard if other types of |
| * normalizations are ever implemented, and the corresponding |
| * test is forgotten in the present switch. |
| */ |
| throw new MathIllegalStateException(); |
| } |
| } |
| |
| /** |
| * Computes the standard transform of the specified complex data. The |
| * computation is done in place. The input data is laid out as follows |
| * <ul> |
| * <li>{@code dataRI[0][i]} is the real part of the {@code i}-th data point,</li> |
| * <li>{@code dataRI[1][i]} is the imaginary part of the {@code i}-th data point.</li> |
| * </ul> |
| * |
| * @param dataRI the two dimensional array of real and imaginary parts of the data |
| * @param normalization the normalization to be applied to the transformed data |
| * @param type the type of transform (forward, inverse) to be performed |
| * @throws DimensionMismatchException if the number of rows of the specified |
| * array is not two, or the array is not rectangular |
| * @throws MathIllegalArgumentException if the number of data points is not |
| * a power of two |
| */ |
| public static void transformInPlace(final double[][] dataRI, |
| final DftNormalization normalization, final TransformType type) { |
| |
| if (dataRI.length != 2) { |
| throw new DimensionMismatchException(dataRI.length, 2); |
| } |
| final double[] dataR = dataRI[0]; |
| final double[] dataI = dataRI[1]; |
| if (dataR.length != dataI.length) { |
| throw new DimensionMismatchException(dataI.length, dataR.length); |
| } |
| |
| final int n = dataR.length; |
| if (!ArithmeticUtils.isPowerOfTwo(n)) { |
| throw new MathIllegalArgumentException( |
| LocalizedFormats.NOT_POWER_OF_TWO_CONSIDER_PADDING, |
| Integer.valueOf(n)); |
| } |
| |
| if (n == 1) { |
| return; |
| } else if (n == 2) { |
| final double srcR0 = dataR[0]; |
| final double srcI0 = dataI[0]; |
| final double srcR1 = dataR[1]; |
| final double srcI1 = dataI[1]; |
| |
| // X_0 = x_0 + x_1 |
| dataR[0] = srcR0 + srcR1; |
| dataI[0] = srcI0 + srcI1; |
| // X_1 = x_0 - x_1 |
| dataR[1] = srcR0 - srcR1; |
| dataI[1] = srcI0 - srcI1; |
| |
| normalizeTransformedData(dataRI, normalization, type); |
| return; |
| } |
| |
| bitReversalShuffle2(dataR, dataI); |
| |
| // Do 4-term DFT. |
| if (type == TransformType.INVERSE) { |
| for (int i0 = 0; i0 < n; i0 += 4) { |
| final int i1 = i0 + 1; |
| final int i2 = i0 + 2; |
| final int i3 = i0 + 3; |
| |
| final double srcR0 = dataR[i0]; |
| final double srcI0 = dataI[i0]; |
| final double srcR1 = dataR[i2]; |
| final double srcI1 = dataI[i2]; |
| final double srcR2 = dataR[i1]; |
| final double srcI2 = dataI[i1]; |
| final double srcR3 = dataR[i3]; |
| final double srcI3 = dataI[i3]; |
| |
| // 4-term DFT |
| // X_0 = x_0 + x_1 + x_2 + x_3 |
| dataR[i0] = srcR0 + srcR1 + srcR2 + srcR3; |
| dataI[i0] = srcI0 + srcI1 + srcI2 + srcI3; |
| // X_1 = x_0 - x_2 + j * (x_3 - x_1) |
| dataR[i1] = srcR0 - srcR2 + (srcI3 - srcI1); |
| dataI[i1] = srcI0 - srcI2 + (srcR1 - srcR3); |
| // X_2 = x_0 - x_1 + x_2 - x_3 |
| dataR[i2] = srcR0 - srcR1 + srcR2 - srcR3; |
| dataI[i2] = srcI0 - srcI1 + srcI2 - srcI3; |
| // X_3 = x_0 - x_2 + j * (x_1 - x_3) |
| dataR[i3] = srcR0 - srcR2 + (srcI1 - srcI3); |
| dataI[i3] = srcI0 - srcI2 + (srcR3 - srcR1); |
| } |
| } else { |
| for (int i0 = 0; i0 < n; i0 += 4) { |
| final int i1 = i0 + 1; |
| final int i2 = i0 + 2; |
| final int i3 = i0 + 3; |
| |
| final double srcR0 = dataR[i0]; |
| final double srcI0 = dataI[i0]; |
| final double srcR1 = dataR[i2]; |
| final double srcI1 = dataI[i2]; |
| final double srcR2 = dataR[i1]; |
| final double srcI2 = dataI[i1]; |
| final double srcR3 = dataR[i3]; |
| final double srcI3 = dataI[i3]; |
| |
| // 4-term DFT |
| // X_0 = x_0 + x_1 + x_2 + x_3 |
| dataR[i0] = srcR0 + srcR1 + srcR2 + srcR3; |
| dataI[i0] = srcI0 + srcI1 + srcI2 + srcI3; |
| // X_1 = x_0 - x_2 + j * (x_3 - x_1) |
| dataR[i1] = srcR0 - srcR2 + (srcI1 - srcI3); |
| dataI[i1] = srcI0 - srcI2 + (srcR3 - srcR1); |
| // X_2 = x_0 - x_1 + x_2 - x_3 |
| dataR[i2] = srcR0 - srcR1 + srcR2 - srcR3; |
| dataI[i2] = srcI0 - srcI1 + srcI2 - srcI3; |
| // X_3 = x_0 - x_2 + j * (x_1 - x_3) |
| dataR[i3] = srcR0 - srcR2 + (srcI3 - srcI1); |
| dataI[i3] = srcI0 - srcI2 + (srcR1 - srcR3); |
| } |
| } |
| |
| int lastN0 = 4; |
| int lastLogN0 = 2; |
| while (lastN0 < n) { |
| int n0 = lastN0 << 1; |
| int logN0 = lastLogN0 + 1; |
| double wSubN0R = W_SUB_N_R[logN0]; |
| double wSubN0I = W_SUB_N_I[logN0]; |
| if (type == TransformType.INVERSE) { |
| wSubN0I = -wSubN0I; |
| } |
| |
| // Combine even/odd transforms of size lastN0 into a transform of size N0 (lastN0 * 2). |
| for (int destEvenStartIndex = 0; destEvenStartIndex < n; destEvenStartIndex += n0) { |
| int destOddStartIndex = destEvenStartIndex + lastN0; |
| |
| double wSubN0ToRR = 1; |
| double wSubN0ToRI = 0; |
| |
| for (int r = 0; r < lastN0; r++) { |
| double grR = dataR[destEvenStartIndex + r]; |
| double grI = dataI[destEvenStartIndex + r]; |
| double hrR = dataR[destOddStartIndex + r]; |
| double hrI = dataI[destOddStartIndex + r]; |
| |
| // dest[destEvenStartIndex + r] = Gr + WsubN0ToR * Hr |
| dataR[destEvenStartIndex + r] = grR + wSubN0ToRR * hrR - wSubN0ToRI * hrI; |
| dataI[destEvenStartIndex + r] = grI + wSubN0ToRR * hrI + wSubN0ToRI * hrR; |
| // dest[destOddStartIndex + r] = Gr - WsubN0ToR * Hr |
| dataR[destOddStartIndex + r] = grR - (wSubN0ToRR * hrR - wSubN0ToRI * hrI); |
| dataI[destOddStartIndex + r] = grI - (wSubN0ToRR * hrI + wSubN0ToRI * hrR); |
| |
| // WsubN0ToR *= WsubN0R |
| double nextWsubN0ToRR = wSubN0ToRR * wSubN0R - wSubN0ToRI * wSubN0I; |
| double nextWsubN0ToRI = wSubN0ToRR * wSubN0I + wSubN0ToRI * wSubN0R; |
| wSubN0ToRR = nextWsubN0ToRR; |
| wSubN0ToRI = nextWsubN0ToRI; |
| } |
| } |
| |
| lastN0 = n0; |
| lastLogN0 = logN0; |
| } |
| |
| normalizeTransformedData(dataRI, normalization, type); |
| } |
| |
| /** |
| * Returns the (forward, inverse) transform of the specified real data set. |
| * |
| * @param f the real data array to be transformed |
| * @param type the type of transform (forward, inverse) to be performed |
| * @return the complex transformed array |
| * @throws MathIllegalArgumentException if the length of the data array is not a power of two |
| */ |
| public Complex[] transform(final double[] f, final TransformType type) { |
| final double[][] dataRI = new double[][] { |
| MathArrays.copyOf(f, f.length), new double[f.length] |
| }; |
| |
| transformInPlace(dataRI, normalization, type); |
| |
| return TransformUtils.createComplexArray(dataRI); |
| } |
| |
| /** |
| * Returns the (forward, inverse) transform of the specified real function, |
| * sampled on the specified interval. |
| * |
| * @param f the function to be sampled and transformed |
| * @param min the (inclusive) lower bound for the interval |
| * @param max the (exclusive) upper bound for the interval |
| * @param n the number of sample points |
| * @param type the type of transform (forward, inverse) to be performed |
| * @return the complex transformed array |
| * @throws org.apache.commons.math3.exception.NumberIsTooLargeException |
| * if the lower bound is greater than, or equal to the upper bound |
| * @throws org.apache.commons.math3.exception.NotStrictlyPositiveException |
| * if the number of sample points {@code n} is negative |
| * @throws MathIllegalArgumentException if the number of sample points |
| * {@code n} is not a power of two |
| */ |
| public Complex[] transform(final UnivariateFunction f, |
| final double min, final double max, final int n, |
| final TransformType type) { |
| |
| final double[] data = FunctionUtils.sample(f, min, max, n); |
| return transform(data, type); |
| } |
| |
| /** |
| * Returns the (forward, inverse) transform of the specified complex data set. |
| * |
| * @param f the complex data array to be transformed |
| * @param type the type of transform (forward, inverse) to be performed |
| * @return the complex transformed array |
| * @throws MathIllegalArgumentException if the length of the data array is not a power of two |
| */ |
| public Complex[] transform(final Complex[] f, final TransformType type) { |
| final double[][] dataRI = TransformUtils.createRealImaginaryArray(f); |
| |
| transformInPlace(dataRI, normalization, type); |
| |
| return TransformUtils.createComplexArray(dataRI); |
| } |
| |
| /** |
| * Performs a multi-dimensional Fourier transform on a given array. Use |
| * {@link #transform(Complex[], TransformType)} in a row-column |
| * implementation in any number of dimensions with |
| * O(N×log(N)) complexity with |
| * N = n<sub>1</sub> × n<sub>2</sub> ×n<sub>3</sub> × ... |
| * × n<sub>d</sub>, where n<sub>k</sub> is the number of elements in |
| * dimension k, and d is the total number of dimensions. |
| * |
| * @param mdca Multi-Dimensional Complex Array, i.e. {@code Complex[][][][]} |
| * @param type the type of transform (forward, inverse) to be performed |
| * @return transform of {@code mdca} as a Multi-Dimensional Complex Array, i.e. {@code Complex[][][][]} |
| * @throws IllegalArgumentException if any dimension is not a power of two |
| * @deprecated see MATH-736 |
| */ |
| @Deprecated |
| public Object mdfft(Object mdca, TransformType type) { |
| MultiDimensionalComplexMatrix mdcm = (MultiDimensionalComplexMatrix) |
| new MultiDimensionalComplexMatrix(mdca).clone(); |
| int[] dimensionSize = mdcm.getDimensionSizes(); |
| //cycle through each dimension |
| for (int i = 0; i < dimensionSize.length; i++) { |
| mdfft(mdcm, type, i, new int[0]); |
| } |
| return mdcm.getArray(); |
| } |
| |
| /** |
| * Performs one dimension of a multi-dimensional Fourier transform. |
| * |
| * @param mdcm input matrix |
| * @param type the type of transform (forward, inverse) to be performed |
| * @param d index of the dimension to process |
| * @param subVector recursion subvector |
| * @throws IllegalArgumentException if any dimension is not a power of two |
| * @deprecated see MATH-736 |
| */ |
| @Deprecated |
| private void mdfft(MultiDimensionalComplexMatrix mdcm, |
| TransformType type, int d, int[] subVector) { |
| |
| int[] dimensionSize = mdcm.getDimensionSizes(); |
| //if done |
| if (subVector.length == dimensionSize.length) { |
| Complex[] temp = new Complex[dimensionSize[d]]; |
| for (int i = 0; i < dimensionSize[d]; i++) { |
| //fft along dimension d |
| subVector[d] = i; |
| temp[i] = mdcm.get(subVector); |
| } |
| |
| temp = transform(temp, type); |
| |
| for (int i = 0; i < dimensionSize[d]; i++) { |
| subVector[d] = i; |
| mdcm.set(temp[i], subVector); |
| } |
| } else { |
| int[] vector = new int[subVector.length + 1]; |
| System.arraycopy(subVector, 0, vector, 0, subVector.length); |
| if (subVector.length == d) { |
| //value is not important once the recursion is done. |
| //then an fft will be applied along the dimension d. |
| vector[d] = 0; |
| mdfft(mdcm, type, d, vector); |
| } else { |
| for (int i = 0; i < dimensionSize[subVector.length]; i++) { |
| vector[subVector.length] = i; |
| //further split along the next dimension |
| mdfft(mdcm, type, d, vector); |
| } |
| } |
| } |
| } |
| |
| /** |
| * Complex matrix implementation. Not designed for synchronized access may |
| * eventually be replaced by jsr-83 of the java community process |
| * http://jcp.org/en/jsr/detail?id=83 |
| * may require additional exception throws for other basic requirements. |
| * |
| * @deprecated see MATH-736 |
| */ |
| @Deprecated |
| private static class MultiDimensionalComplexMatrix |
| implements Cloneable { |
| |
| /** Size in all dimensions. */ |
| protected int[] dimensionSize; |
| |
| /** Storage array. */ |
| protected Object multiDimensionalComplexArray; |
| |
| /** |
| * Simple constructor. |
| * |
| * @param multiDimensionalComplexArray array containing the matrix |
| * elements |
| */ |
| public MultiDimensionalComplexMatrix( |
| Object multiDimensionalComplexArray) { |
| |
| this.multiDimensionalComplexArray = multiDimensionalComplexArray; |
| |
| // count dimensions |
| int numOfDimensions = 0; |
| for (Object lastDimension = multiDimensionalComplexArray; |
| lastDimension instanceof Object[];) { |
| final Object[] array = (Object[]) lastDimension; |
| numOfDimensions++; |
| lastDimension = array[0]; |
| } |
| |
| // allocate array with exact count |
| dimensionSize = new int[numOfDimensions]; |
| |
| // fill array |
| numOfDimensions = 0; |
| for (Object lastDimension = multiDimensionalComplexArray; |
| lastDimension instanceof Object[];) { |
| final Object[] array = (Object[]) lastDimension; |
| dimensionSize[numOfDimensions++] = array.length; |
| lastDimension = array[0]; |
| } |
| |
| } |
| |
| /** |
| * Get a matrix element. |
| * |
| * @param vector indices of the element |
| * @return matrix element |
| * @exception DimensionMismatchException if dimensions do not match |
| */ |
| public Complex get(int... vector) |
| throws DimensionMismatchException { |
| |
| if (vector == null) { |
| if (dimensionSize.length > 0) { |
| throw new DimensionMismatchException( |
| 0, |
| dimensionSize.length); |
| } |
| return null; |
| } |
| if (vector.length != dimensionSize.length) { |
| throw new DimensionMismatchException( |
| vector.length, |
| dimensionSize.length); |
| } |
| |
| Object lastDimension = multiDimensionalComplexArray; |
| |
| for (int i = 0; i < dimensionSize.length; i++) { |
| lastDimension = ((Object[]) lastDimension)[vector[i]]; |
| } |
| return (Complex) lastDimension; |
| } |
| |
| /** |
| * Set a matrix element. |
| * |
| * @param magnitude magnitude of the element |
| * @param vector indices of the element |
| * @return the previous value |
| * @exception DimensionMismatchException if dimensions do not match |
| */ |
| public Complex set(Complex magnitude, int... vector) |
| throws DimensionMismatchException { |
| |
| if (vector == null) { |
| if (dimensionSize.length > 0) { |
| throw new DimensionMismatchException( |
| 0, |
| dimensionSize.length); |
| } |
| return null; |
| } |
| if (vector.length != dimensionSize.length) { |
| throw new DimensionMismatchException( |
| vector.length, |
| dimensionSize.length); |
| } |
| |
| Object[] lastDimension = (Object[]) multiDimensionalComplexArray; |
| for (int i = 0; i < dimensionSize.length - 1; i++) { |
| lastDimension = (Object[]) lastDimension[vector[i]]; |
| } |
| |
| Complex lastValue = (Complex) lastDimension[vector[dimensionSize.length - 1]]; |
| lastDimension[vector[dimensionSize.length - 1]] = magnitude; |
| |
| return lastValue; |
| } |
| |
| /** |
| * Get the size in all dimensions. |
| * |
| * @return size in all dimensions |
| */ |
| public int[] getDimensionSizes() { |
| return dimensionSize.clone(); |
| } |
| |
| /** |
| * Get the underlying storage array. |
| * |
| * @return underlying storage array |
| */ |
| public Object getArray() { |
| return multiDimensionalComplexArray; |
| } |
| |
| /** {@inheritDoc} */ |
| @Override |
| public Object clone() { |
| MultiDimensionalComplexMatrix mdcm = |
| new MultiDimensionalComplexMatrix(Array.newInstance( |
| Complex.class, dimensionSize)); |
| clone(mdcm); |
| return mdcm; |
| } |
| |
| /** |
| * Copy contents of current array into mdcm. |
| * |
| * @param mdcm array where to copy data |
| */ |
| private void clone(MultiDimensionalComplexMatrix mdcm) { |
| |
| int[] vector = new int[dimensionSize.length]; |
| int size = 1; |
| for (int i = 0; i < dimensionSize.length; i++) { |
| size *= dimensionSize[i]; |
| } |
| int[][] vectorList = new int[size][dimensionSize.length]; |
| for (int[] nextVector : vectorList) { |
| System.arraycopy(vector, 0, nextVector, 0, |
| dimensionSize.length); |
| for (int i = 0; i < dimensionSize.length; i++) { |
| vector[i]++; |
| if (vector[i] < dimensionSize[i]) { |
| break; |
| } else { |
| vector[i] = 0; |
| } |
| } |
| } |
| |
| for (int[] nextVector : vectorList) { |
| mdcm.set(get(nextVector), nextVector); |
| } |
| } |
| } |
| } |