org.jtransforms.fft.DoubleFFT_2D Maven / Gradle / Ivy
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* JTransforms
* Copyright (c) 2007 onward, Piotr Wendykier
* All rights reserved.
*
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*
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package org.jtransforms.fft;
import java.util.concurrent.Future;
import org.jtransforms.utils.ConcurrencyUtils;
import pl.edu.icm.jlargearrays.DoubleLargeArray;
/**
* Computes 2D Discrete Fourier Transform (DFT) of complex and real, double
* precision data. The sizes of both dimensions can be arbitrary numbers. This
* is a parallel implementation of split-radix and mixed-radix algorithms
* optimized for SMP systems.
*
* Part of the code is derived from General Purpose FFT Package written by Takuya Ooura
* (http://www.kurims.kyoto-u.ac.jp/~ooura/fft.html)
*
* @author Piotr Wendykier ([email protected])
*/
public class DoubleFFT_2D
{
private int rows;
private int columns;
private long rowsl;
private long columnsl;
private DoubleFFT_1D fftColumns, fftRows;
private boolean isPowerOfTwo = false;
private boolean useThreads = false;
/**
* Creates new instance of DoubleFFT_2D.
*
* @param rows
* number of rows
* @param columns
* number of columns
*/
public DoubleFFT_2D(long rows, long columns)
{
if (rows <= 1 || columns <= 1) {
throw new IllegalArgumentException("rows and columns must be greater than 1");
}
this.rows = (int) rows;
this.columns = (int) columns;
this.rowsl = rows;
this.columnsl = columns;
if (rows * columns >= ConcurrencyUtils.getThreadsBeginN_2D()) {
this.useThreads = true;
}
if (ConcurrencyUtils.isPowerOf2(rows) && ConcurrencyUtils.isPowerOf2(columns)) {
isPowerOfTwo = true;
}
long largeArraysBenginN = ConcurrencyUtils.getLargeArraysBeginN();
if (rows * columns > (1 << 28)) {
ConcurrencyUtils.setLargeArraysBeginN(Math.min(rows, columns));
}
fftRows = new DoubleFFT_1D(rows);
if (rows == columns) {
fftColumns = fftRows;
}
else {
fftColumns = new DoubleFFT_1D(columns);
}
ConcurrencyUtils.setLargeArraysBeginN(largeArraysBenginN);
}
/**
* Computes 2D forward DFT of complex data leaving the result in
* a. The data is stored in 1D array in row-major order.
* Complex number is stored as two double values in sequence: the real and
* imaginary part, i.e. the input array must be of size rows*2*columns. The
* physical layout of the input data has to be as follows:
*
*
* a[k1*2*columns+2*k2] = Re[k1][k2],
* a[k1*2*columns+2*k2+1] = Im[k1][k2], 0<=k1<rows, 0<=k2<columns,
*
*
* @param a
* data to transform
*/
public void complexForward(final double[] a)
{
int nthreads = ConcurrencyUtils.getNumberOfThreads();
if (isPowerOfTwo) {
columns = 2 * columns;
if ((nthreads > 1) && useThreads) {
xdft2d0_subth1(0, -1, a, true);
cdft2d_subth(-1, a, true);
} else {
for (int r = 0; r < rows; r++) {
fftColumns.complexForward(a, r * columns);
}
cdft2d_sub(-1, a, true);
}
columns = columns / 2;
} else {
final int rowStride = 2 * columns;
if ((nthreads > 1) && useThreads && (rows >= nthreads) && (columns >= nthreads)) {
Future[] futures = new Future[nthreads];
int p = rows / nthreads;
for (int l = 0; l < nthreads; l++) {
final int firstRow = l * p;
final int lastRow = (l == (nthreads - 1)) ? rows : firstRow + p;
futures[l] = ConcurrencyUtils.submit(new Runnable()
{
public void run()
{
for (int r = firstRow; r < lastRow; r++) {
fftColumns.complexForward(a, r * rowStride);
}
}
});
}
ConcurrencyUtils.waitForCompletion(futures);
p = columns / nthreads;
for (int l = 0; l < nthreads; l++) {
final int firstColumn = l * p;
final int lastColumn = (l == (nthreads - 1)) ? columns : firstColumn + p;
futures[l] = ConcurrencyUtils.submit(new Runnable()
{
public void run()
{
double[] temp = new double[2 * rows];
for (int c = firstColumn; c < lastColumn; c++) {
int idx0 = 2 * c;
for (int r = 0; r < rows; r++) {
int idx1 = 2 * r;
int idx2 = r * rowStride + idx0;
temp[idx1] = a[idx2];
temp[idx1 + 1] = a[idx2 + 1];
}
fftRows.complexForward(temp);
for (int r = 0; r < rows; r++) {
int idx1 = 2 * r;
int idx2 = r * rowStride + idx0;
a[idx2] = temp[idx1];
a[idx2 + 1] = temp[idx1 + 1];
}
}
}
});
}
ConcurrencyUtils.waitForCompletion(futures);
} else {
for (int r = 0; r < rows; r++) {
fftColumns.complexForward(a, r * rowStride);
}
double[] temp = new double[2 * rows];
for (int c = 0; c < columns; c++) {
int idx0 = 2 * c;
for (int r = 0; r < rows; r++) {
int idx1 = 2 * r;
int idx2 = r * rowStride + idx0;
temp[idx1] = a[idx2];
temp[idx1 + 1] = a[idx2 + 1];
}
fftRows.complexForward(temp);
for (int r = 0; r < rows; r++) {
int idx1 = 2 * r;
int idx2 = r * rowStride + idx0;
a[idx2] = temp[idx1];
a[idx2 + 1] = temp[idx1 + 1];
}
}
}
}
}
/**
* Computes 2D forward DFT of complex data leaving the result in
* a. The data is stored in 1D array in row-major order.
* Complex number is stored as two double values in sequence: the real and
* imaginary part, i.e. the input array must be of size rows*2*columns. The
* physical layout of the input data has to be as follows:
*
*
* a[k1*2*columns+2*k2] = Re[k1][k2],
* a[k1*2*columns+2*k2+1] = Im[k1][k2], 0<=k1<rows, 0<=k2<columns,
*
*
* @param a
* data to transform
*/
public void complexForward(final DoubleLargeArray a)
{
int nthreads = ConcurrencyUtils.getNumberOfThreads();
if (isPowerOfTwo) {
columnsl = 2 * columnsl;
if ((nthreads > 1) && useThreads) {
xdft2d0_subth1(0, -1, a, true);
cdft2d_subth(-1, a, true);
} else {
for (int r = 0; r < rowsl; r++) {
fftColumns.complexForward(a, r * columnsl);
}
cdft2d_sub(-1, a, true);
}
columnsl = columnsl / 2;
} else {
final long rowStride = 2 * columnsl;
if ((nthreads > 1) && useThreads && (rowsl >= nthreads) && (columnsl >= nthreads)) {
Future[] futures = new Future[nthreads];
long p = rowsl / nthreads;
for (int l = 0; l < nthreads; l++) {
final long firstRow = l * p;
final long lastRow = (l == (nthreads - 1)) ? rowsl : firstRow + p;
futures[l] = ConcurrencyUtils.submit(new Runnable()
{
public void run()
{
for (long r = firstRow; r < lastRow; r++) {
fftColumns.complexForward(a, r * rowStride);
}
}
});
}
ConcurrencyUtils.waitForCompletion(futures);
p = columnsl / nthreads;
for (int l = 0; l < nthreads; l++) {
final long firstColumn = l * p;
final long lastColumn = (l == (nthreads - 1)) ? columnsl : firstColumn + p;
futures[l] = ConcurrencyUtils.submit(new Runnable()
{
public void run()
{
DoubleLargeArray temp = new DoubleLargeArray(2 * rowsl, false);
for (long c = firstColumn; c < lastColumn; c++) {
long idx0 = 2 * c;
for (long r = 0; r < rowsl; r++) {
long idx1 = 2 * r;
long idx2 = r * rowStride + idx0;
temp.setDouble(idx1, a.getDouble(idx2));
temp.setDouble(idx1 + 1, a.getDouble(idx2 + 1));
}
fftRows.complexForward(temp);
for (long r = 0; r < rowsl; r++) {
long idx1 = 2 * r;
long idx2 = r * rowStride + idx0;
a.setDouble(idx2, temp.getDouble(idx1));
a.setDouble(idx2 + 1, temp.getDouble(idx1 + 1));
}
}
}
});
}
ConcurrencyUtils.waitForCompletion(futures);
} else {
for (long r = 0; r < rowsl; r++) {
fftColumns.complexForward(a, r * rowStride);
}
DoubleLargeArray temp = new DoubleLargeArray(2 * rowsl, false);
for (long c = 0; c < columnsl; c++) {
long idx0 = 2 * c;
for (long r = 0; r < rowsl; r++) {
long idx1 = 2 * r;
long idx2 = r * rowStride + idx0;
temp.setDouble(idx1, a.getDouble(idx2));
temp.setDouble(idx1 + 1, a.getDouble(idx2 + 1));
}
fftRows.complexForward(temp);
for (long r = 0; r < rowsl; r++) {
long idx1 = 2 * r;
long idx2 = r * rowStride + idx0;
a.setDouble(idx2, temp.getDouble(idx1));
a.setDouble(idx2 + 1, temp.getDouble(idx1 + 1));
}
}
}
}
}
/**
* Computes 2D forward DFT of complex data leaving the result in
* a. The data is stored in 2D array. Complex data is
* represented by 2 double values in sequence: the real and imaginary part,
* i.e. the input array must be of size rows by 2*columns. The physical
* layout of the input data has to be as follows:
*
*
* a[k1][2*k2] = Re[k1][k2],
* a[k1][2*k2+1] = Im[k1][k2], 0<=k1<rows, 0<=k2<columns,
*
*
* @param a
* data to transform
*/
public void complexForward(final double[][] a)
{
int nthreads = ConcurrencyUtils.getNumberOfThreads();
if (isPowerOfTwo) {
columns = 2 * columns;
if ((nthreads > 1) && useThreads) {
xdft2d0_subth1(0, -1, a, true);
cdft2d_subth(-1, a, true);
} else {
for (int r = 0; r < rows; r++) {
fftColumns.complexForward(a[r]);
}
cdft2d_sub(-1, a, true);
}
columns = columns / 2;
} else {
if ((nthreads > 1) && useThreads && (rows >= nthreads) && (columns >= nthreads)) {
Future[] futures = new Future[nthreads];
int p = rows / nthreads;
for (int l = 0; l < nthreads; l++) {
final int firstRow = l * p;
final int lastRow = (l == (nthreads - 1)) ? rows : firstRow + p;
futures[l] = ConcurrencyUtils.submit(new Runnable()
{
public void run()
{
for (int r = firstRow; r < lastRow; r++) {
fftColumns.complexForward(a[r]);
}
}
});
}
ConcurrencyUtils.waitForCompletion(futures);
p = columns / nthreads;
for (int l = 0; l < nthreads; l++) {
final int firstColumn = l * p;
final int lastColumn = (l == (nthreads - 1)) ? columns : firstColumn + p;
futures[l] = ConcurrencyUtils.submit(new Runnable()
{
public void run()
{
double[] temp = new double[2 * rows];
for (int c = firstColumn; c < lastColumn; c++) {
int idx1 = 2 * c;
for (int r = 0; r < rows; r++) {
int idx2 = 2 * r;
temp[idx2] = a[r][idx1];
temp[idx2 + 1] = a[r][idx1 + 1];
}
fftRows.complexForward(temp);
for (int r = 0; r < rows; r++) {
int idx2 = 2 * r;
a[r][idx1] = temp[idx2];
a[r][idx1 + 1] = temp[idx2 + 1];
}
}
}
});
}
ConcurrencyUtils.waitForCompletion(futures);
} else {
for (int r = 0; r < rows; r++) {
fftColumns.complexForward(a[r]);
}
double[] temp = new double[2 * rows];
for (int c = 0; c < columns; c++) {
int idx1 = 2 * c;
for (int r = 0; r < rows; r++) {
int idx2 = 2 * r;
temp[idx2] = a[r][idx1];
temp[idx2 + 1] = a[r][idx1 + 1];
}
fftRows.complexForward(temp);
for (int r = 0; r < rows; r++) {
int idx2 = 2 * r;
a[r][idx1] = temp[idx2];
a[r][idx1 + 1] = temp[idx2 + 1];
}
}
}
}
}
/**
* Computes 2D inverse DFT of complex data leaving the result in
* a. The data is stored in 1D array in row-major order.
* Complex number is stored as two double values in sequence: the real and
* imaginary part, i.e. the input array must be of size rows*2*columns. The
* physical layout of the input data has to be as follows:
*
*
* a[k1*2*columns+2*k2] = Re[k1][k2],
* a[k1*2*columns+2*k2+1] = Im[k1][k2], 0<=k1<rows, 0<=k2<columns,
*
*
* @param a
* data to transform
* @param scale
* if true then scaling is performed
*
*/
public void complexInverse(final double[] a, final boolean scale)
{
int nthreads = ConcurrencyUtils.getNumberOfThreads();
if (isPowerOfTwo) {
columns = 2 * columns;
if ((nthreads > 1) && useThreads) {
xdft2d0_subth1(0, 1, a, scale);
cdft2d_subth(1, a, scale);
} else {
for (int r = 0; r < rows; r++) {
fftColumns.complexInverse(a, r * columns, scale);
}
cdft2d_sub(1, a, scale);
}
columns = columns / 2;
} else {
final int rowspan = 2 * columns;
if ((nthreads > 1) && useThreads && (rows >= nthreads) && (columns >= nthreads)) {
Future[] futures = new Future[nthreads];
int p = rows / nthreads;
for (int l = 0; l < nthreads; l++) {
final int firstRow = l * p;
final int lastRow = (l == (nthreads - 1)) ? rows : firstRow + p;
futures[l] = ConcurrencyUtils.submit(new Runnable()
{
public void run()
{
for (int r = firstRow; r < lastRow; r++) {
fftColumns.complexInverse(a, r * rowspan, scale);
}
}
});
}
ConcurrencyUtils.waitForCompletion(futures);
p = columns / nthreads;
for (int l = 0; l < nthreads; l++) {
final int firstColumn = l * p;
final int lastColumn = (l == (nthreads - 1)) ? columns : firstColumn + p;
futures[l] = ConcurrencyUtils.submit(new Runnable()
{
public void run()
{
double[] temp = new double[2 * rows];
for (int c = firstColumn; c < lastColumn; c++) {
int idx1 = 2 * c;
for (int r = 0; r < rows; r++) {
int idx2 = 2 * r;
int idx3 = r * rowspan + idx1;
temp[idx2] = a[idx3];
temp[idx2 + 1] = a[idx3 + 1];
}
fftRows.complexInverse(temp, scale);
for (int r = 0; r < rows; r++) {
int idx2 = 2 * r;
int idx3 = r * rowspan + idx1;
a[idx3] = temp[idx2];
a[idx3 + 1] = temp[idx2 + 1];
}
}
}
});
}
ConcurrencyUtils.waitForCompletion(futures);
} else {
for (int r = 0; r < rows; r++) {
fftColumns.complexInverse(a, r * rowspan, scale);
}
double[] temp = new double[2 * rows];
for (int c = 0; c < columns; c++) {
int idx1 = 2 * c;
for (int r = 0; r < rows; r++) {
int idx2 = 2 * r;
int idx3 = r * rowspan + idx1;
temp[idx2] = a[idx3];
temp[idx2 + 1] = a[idx3 + 1];
}
fftRows.complexInverse(temp, scale);
for (int r = 0; r < rows; r++) {
int idx2 = 2 * r;
int idx3 = r * rowspan + idx1;
a[idx3] = temp[idx2];
a[idx3 + 1] = temp[idx2 + 1];
}
}
}
}
}
/**
* Computes 2D inverse DFT of complex data leaving the result in
* a. The data is stored in 1D array in row-major order.
* Complex number is stored as two double values in sequence: the real and
* imaginary part, i.e. the input array must be of size rows*2*columns. The
* physical layout of the input data has to be as follows:
*
*
* a[k1*2*columns+2*k2] = Re[k1][k2],
* a[k1*2*columns+2*k2+1] = Im[k1][k2], 0<=k1<rows, 0<=k2<columns,
*
*
* @param a
* data to transform
* @param scale
* if true then scaling is performed
*
*/
public void complexInverse(final DoubleLargeArray a, final boolean scale)
{
int nthreads = ConcurrencyUtils.getNumberOfThreads();
if (isPowerOfTwo) {
columnsl = 2 * columnsl;
if ((nthreads > 1) && useThreads) {
xdft2d0_subth1(0, 1, a, scale);
cdft2d_subth(1, a, scale);
} else {
for (long r = 0; r < rowsl; r++) {
fftColumns.complexInverse(a, r * columnsl, scale);
}
cdft2d_sub(1, a, scale);
}
columnsl = columnsl / 2;
} else {
final long rowspan = 2 * columnsl;
if ((nthreads > 1) && useThreads && (rowsl >= nthreads) && (columnsl >= nthreads)) {
Future[] futures = new Future[nthreads];
long p = rowsl / nthreads;
for (int l = 0; l < nthreads; l++) {
final long firstRow = l * p;
final long lastRow = (l == (nthreads - 1)) ? rowsl : firstRow + p;
futures[l] = ConcurrencyUtils.submit(new Runnable()
{
public void run()
{
for (long r = firstRow; r < lastRow; r++) {
fftColumns.complexInverse(a, r * rowspan, scale);
}
}
});
}
ConcurrencyUtils.waitForCompletion(futures);
p = columnsl / nthreads;
for (int l = 0; l < nthreads; l++) {
final long firstColumn = l * p;
final long lastColumn = (l == (nthreads - 1)) ? columnsl : firstColumn + p;
futures[l] = ConcurrencyUtils.submit(new Runnable()
{
public void run()
{
DoubleLargeArray temp = new DoubleLargeArray(2 * rowsl, false);
for (long c = firstColumn; c < lastColumn; c++) {
long idx1 = 2 * c;
for (long r = 0; r < rowsl; r++) {
long idx2 = 2 * r;
long idx3 = r * rowspan + idx1;
temp.setDouble(idx2, a.getDouble(idx3));
temp.setDouble(idx2 + 1, a.getDouble(idx3 + 1));
}
fftRows.complexInverse(temp, scale);
for (long r = 0; r < rowsl; r++) {
long idx2 = 2 * r;
long idx3 = r * rowspan + idx1;
a.setDouble(idx3, temp.getDouble(idx2));
a.setDouble(idx3 + 1, temp.getDouble(idx2 + 1));
}
}
}
});
}
ConcurrencyUtils.waitForCompletion(futures);
} else {
for (long r = 0; r < rowsl; r++) {
fftColumns.complexInverse(a, r * rowspan, scale);
}
DoubleLargeArray temp = new DoubleLargeArray(2 * rowsl, false);
for (long c = 0; c < columnsl; c++) {
long idx1 = 2 * c;
for (long r = 0; r < rowsl; r++) {
long idx2 = 2 * r;
long idx3 = r * rowspan + idx1;
temp.setDouble(idx2, a.getDouble(idx3));
temp.setDouble(idx2 + 1, a.getDouble(idx3 + 1));
}
fftRows.complexInverse(temp, scale);
for (long r = 0; r < rowsl; r++) {
long idx2 = 2 * r;
long idx3 = r * rowspan + idx1;
a.setDouble(idx3, temp.getDouble(idx2));
a.setDouble(idx3 + 1, temp.getDouble(idx2 + 1));
}
}
}
}
}
/**
* Computes 2D inverse DFT of complex data leaving the result in
* a. The data is stored in 2D array. Complex data is
* represented by 2 double values in sequence: the real and imaginary part,
* i.e. the input array must be of size rows by 2*columns. The physical
* layout of the input data has to be as follows:
*
*
* a[k1][2*k2] = Re[k1][k2],
* a[k1][2*k2+1] = Im[k1][k2], 0<=k1<rows, 0<=k2<columns,
*
*
* @param a
* data to transform
* @param scale
* if true then scaling is performed
*
*/
public void complexInverse(final double[][] a, final boolean scale)
{
int nthreads = ConcurrencyUtils.getNumberOfThreads();
if (isPowerOfTwo) {
columns = 2 * columns;
if ((nthreads > 1) && useThreads) {
xdft2d0_subth1(0, 1, a, scale);
cdft2d_subth(1, a, scale);
} else {
for (int r = 0; r < rows; r++) {
fftColumns.complexInverse(a[r], scale);
}
cdft2d_sub(1, a, scale);
}
columns = columns / 2;
} else {
if ((nthreads > 1) && useThreads && (rows >= nthreads) && (columns >= nthreads)) {
Future[] futures = new Future[nthreads];
int p = rows / nthreads;
for (int l = 0; l < nthreads; l++) {
final int firstRow = l * p;
final int lastRow = (l == (nthreads - 1)) ? rows : firstRow + p;
futures[l] = ConcurrencyUtils.submit(new Runnable()
{
public void run()
{
for (int r = firstRow; r < lastRow; r++) {
fftColumns.complexInverse(a[r], scale);
}
}
});
}
ConcurrencyUtils.waitForCompletion(futures);
p = columns / nthreads;
for (int l = 0; l < nthreads; l++) {
final int firstColumn = l * p;
final int lastColumn = (l == (nthreads - 1)) ? columns : firstColumn + p;
futures[l] = ConcurrencyUtils.submit(new Runnable()
{
public void run()
{
double[] temp = new double[2 * rows];
for (int c = firstColumn; c < lastColumn; c++) {
int idx1 = 2 * c;
for (int r = 0; r < rows; r++) {
int idx2 = 2 * r;
temp[idx2] = a[r][idx1];
temp[idx2 + 1] = a[r][idx1 + 1];
}
fftRows.complexInverse(temp, scale);
for (int r = 0; r < rows; r++) {
int idx2 = 2 * r;
a[r][idx1] = temp[idx2];
a[r][idx1 + 1] = temp[idx2 + 1];
}
}
}
});
}
ConcurrencyUtils.waitForCompletion(futures);
} else {
for (int r = 0; r < rows; r++) {
fftColumns.complexInverse(a[r], scale);
}
double[] temp = new double[2 * rows];
for (int c = 0; c < columns; c++) {
int idx1 = 2 * c;
for (int r = 0; r < rows; r++) {
int idx2 = 2 * r;
temp[idx2] = a[r][idx1];
temp[idx2 + 1] = a[r][idx1 + 1];
}
fftRows.complexInverse(temp, scale);
for (int r = 0; r < rows; r++) {
int idx2 = 2 * r;
a[r][idx1] = temp[idx2];
a[r][idx1 + 1] = temp[idx2 + 1];
}
}
}
}
}
/**
* Computes 2D forward DFT of real data leaving the result in a
* . This method only works when the sizes of both dimensions are
* power-of-two numbers. The physical layout of the output data is as
* follows:
*
*
* a[k1*columns+2*k2] = Re[k1][k2] = Re[rows-k1][columns-k2],
* a[k1*columns+2*k2+1] = Im[k1][k2] = -Im[rows-k1][columns-k2],
* 0<k1<rows, 0<k2<columns/2,
* a[2*k2] = Re[0][k2] = Re[0][columns-k2],
* a[2*k2+1] = Im[0][k2] = -Im[0][columns-k2],
* 0<k2<columns/2,
* a[k1*columns] = Re[k1][0] = Re[rows-k1][0],
* a[k1*columns+1] = Im[k1][0] = -Im[rows-k1][0],
* a[(rows-k1)*columns+1] = Re[k1][columns/2] = Re[rows-k1][columns/2],
* a[(rows-k1)*columns] = -Im[k1][columns/2] = Im[rows-k1][columns/2],
* 0<k1<rows/2,
* a[0] = Re[0][0],
* a[1] = Re[0][columns/2],
* a[(rows/2)*columns] = Re[rows/2][0],
* a[(rows/2)*columns+1] = Re[rows/2][columns/2]
*
*
* This method computes only half of the elements of the real transform. The
* other half satisfies the symmetry condition. If you want the full real
* forward transform, use realForwardFull. To get back the
* original data, use realInverse on the output of this method.
*
* @param a
* data to transform
*/
public void realForward(double[] a)
{
if (isPowerOfTwo == false) {
throw new IllegalArgumentException("rows and columns must be power of two numbers");
} else {
int nthreads = ConcurrencyUtils.getNumberOfThreads();
if ((nthreads > 1) && useThreads) {
xdft2d0_subth1(1, 1, a, true);
cdft2d_subth(-1, a, true);
rdft2d_sub(1, a);
} else {
for (int r = 0; r < rows; r++) {
fftColumns.realForward(a, r * columns);
}
cdft2d_sub(-1, a, true);
rdft2d_sub(1, a);
}
}
}
/**
* Computes 2D forward DFT of real data leaving the result in a
* . This method only works when the sizes of both dimensions are
* power-of-two numbers. The physical layout of the output data is as
* follows:
*
*
* a[k1*columns+2*k2] = Re[k1][k2] = Re[rows-k1][columns-k2],
* a[k1*columns+2*k2+1] = Im[k1][k2] = -Im[rows-k1][columns-k2],
* 0<k1<rows, 0<k2<columns/2,
* a[2*k2] = Re[0][k2] = Re[0][columns-k2],
* a[2*k2+1] = Im[0][k2] = -Im[0][columns-k2],
* 0<k2<columns/2,
* a[k1*columns] = Re[k1][0] = Re[rows-k1][0],
* a[k1*columns+1] = Im[k1][0] = -Im[rows-k1][0],
* a[(rows-k1)*columns+1] = Re[k1][columns/2] = Re[rows-k1][columns/2],
* a[(rows-k1)*columns] = -Im[k1][columns/2] = Im[rows-k1][columns/2],
* 0<k1<rows/2,
* a[0] = Re[0][0],
* a[1] = Re[0][columns/2],
* a[(rows/2)*columns] = Re[rows/2][0],
* a[(rows/2)*columns+1] = Re[rows/2][columns/2]
*
*
* This method computes only half of the elements of the real transform. The
* other half satisfies the symmetry condition. If you want the full real
* forward transform, use realForwardFull. To get back the
* original data, use realInverse on the output of this method.
*
* @param a
* data to transform
*/
public void realForward(DoubleLargeArray a)
{
if (isPowerOfTwo == false) {
throw new IllegalArgumentException("rows and columns must be power of two numbers");
} else {
int nthreads = ConcurrencyUtils.getNumberOfThreads();
if ((nthreads > 1) && useThreads) {
xdft2d0_subth1(1, 1, a, true);
cdft2d_subth(-1, a, true);
rdft2d_sub(1, a);
} else {
for (long r = 0; r < rowsl; r++) {
fftColumns.realForward(a, r * columnsl);
}
cdft2d_sub(-1, a, true);
rdft2d_sub(1, a);
}
}
}
/**
* Computes 2D forward DFT of real data leaving the result in a
* . This method only works when the sizes of both dimensions are
* power-of-two numbers. The physical layout of the output data is as
* follows:
*
*
* a[k1][2*k2] = Re[k1][k2] = Re[rows-k1][columns-k2],
* a[k1][2*k2+1] = Im[k1][k2] = -Im[rows-k1][columns-k2],
* 0<k1<rows, 0<k2<columns/2,
* a[0][2*k2] = Re[0][k2] = Re[0][columns-k2],
* a[0][2*k2+1] = Im[0][k2] = -Im[0][columns-k2],
* 0<k2<columns/2,
* a[k1][0] = Re[k1][0] = Re[rows-k1][0],
* a[k1][1] = Im[k1][0] = -Im[rows-k1][0],
* a[rows-k1][1] = Re[k1][columns/2] = Re[rows-k1][columns/2],
* a[rows-k1][0] = -Im[k1][columns/2] = Im[rows-k1][columns/2],
* 0<k1<rows/2,
* a[0][0] = Re[0][0],
* a[0][1] = Re[0][columns/2],
* a[rows/2][0] = Re[rows/2][0],
* a[rows/2][1] = Re[rows/2][columns/2]
*
*
* This method computes only half of the elements of the real transform. The
* other half satisfies the symmetry condition. If you want the full real
* forward transform, use realForwardFull. To get back the
* original data, use realInverse on the output of this method.
*
* @param a
* data to transform
*/
public void realForward(double[][] a)
{
if (isPowerOfTwo == false) {
throw new IllegalArgumentException("rows and columns must be power of two numbers");
} else {
int nthreads = ConcurrencyUtils.getNumberOfThreads();
if ((nthreads > 1) && useThreads) {
xdft2d0_subth1(1, 1, a, true);
cdft2d_subth(-1, a, true);
rdft2d_sub(1, a);
} else {
for (int r = 0; r < rows; r++) {
fftColumns.realForward(a[r]);
}
cdft2d_sub(-1, a, true);
rdft2d_sub(1, a);
}
}
}
/**
* Computes 2D forward DFT of real data leaving the result in a
* . This method computes full real forward transform, i.e. you will get the
* same result as from complexForward called with all imaginary
* part equal 0. Because the result is stored in a, the input
* array must be of size rows*2*columns, with only the first rows*columns
* elements filled with real data. To get back the original data, use
* complexInverse on the output of this method.
*
* @param a
* data to transform
*/
public void realForwardFull(double[] a)
{
if (isPowerOfTwo) {
int nthreads = ConcurrencyUtils.getNumberOfThreads();
if ((nthreads > 1) && useThreads) {
xdft2d0_subth1(1, 1, a, true);
cdft2d_subth(-1, a, true);
rdft2d_sub(1, a);
} else {
for (int r = 0; r < rows; r++) {
fftColumns.realForward(a, r * columns);
}
cdft2d_sub(-1, a, true);
rdft2d_sub(1, a);
}
fillSymmetric(a);
} else {
mixedRadixRealForwardFull(a);
}
}
/**
* Computes 2D forward DFT of real data leaving the result in a
* . This method computes full real forward transform, i.e. you will get the
* same result as from complexForward called with all imaginary
* part equal 0. Because the result is stored in a, the input
* array must be of size rows*2*columns, with only the first rows*columns
* elements filled with real data. To get back the original data, use
* complexInverse on the output of this method.
*
* @param a
* data to transform
*/
public void realForwardFull(DoubleLargeArray a)
{
if (isPowerOfTwo) {
int nthreads = ConcurrencyUtils.getNumberOfThreads();
if ((nthreads > 1) && useThreads) {
xdft2d0_subth1(1, 1, a, true);
cdft2d_subth(-1, a, true);
rdft2d_sub(1, a);
} else {
for (long r = 0; r < rowsl; r++) {
fftColumns.realForward(a, r * columnsl);
}
cdft2d_sub(-1, a, true);
rdft2d_sub(1, a);
}
fillSymmetric(a);
} else {
mixedRadixRealForwardFull(a);
}
}
/**
* Computes 2D forward DFT of real data leaving the result in a
* . This method computes full real forward transform, i.e. you will get the
* same result as from complexForward called with all imaginary
* part equal 0. Because the result is stored in a, the input
* array must be of size rows by 2*columns, with only the first rows by
* columns elements filled with real data. To get back the original data,
* use complexInverse on the output of this method.
*
* @param a
* data to transform
*/
public void realForwardFull(double[][] a)
{
if (isPowerOfTwo) {
int nthreads = ConcurrencyUtils.getNumberOfThreads();
if ((nthreads > 1) && useThreads) {
xdft2d0_subth1(1, 1, a, true);
cdft2d_subth(-1, a, true);
rdft2d_sub(1, a);
} else {
for (int r = 0; r < rows; r++) {
fftColumns.realForward(a[r]);
}
cdft2d_sub(-1, a, true);
rdft2d_sub(1, a);
}
fillSymmetric(a);
} else {
mixedRadixRealForwardFull(a);
}
}
/**
* Computes 2D inverse DFT of real data leaving the result in a
* . This method only works when the sizes of both dimensions are
* power-of-two numbers. The physical layout of the input data has to be as
* follows:
*
*
* a[k1*columns+2*k2] = Re[k1][k2] = Re[rows-k1][columns-k2],
* a[k1*columns+2*k2+1] = Im[k1][k2] = -Im[rows-k1][columns-k2],
* 0<k1<rows, 0<k2<columns/2,
* a[2*k2] = Re[0][k2] = Re[0][columns-k2],
* a[2*k2+1] = Im[0][k2] = -Im[0][columns-k2],
* 0<k2<columns/2,
* a[k1*columns] = Re[k1][0] = Re[rows-k1][0],
* a[k1*columns+1] = Im[k1][0] = -Im[rows-k1][0],
* a[(rows-k1)*columns+1] = Re[k1][columns/2] = Re[rows-k1][columns/2],
* a[(rows-k1)*columns] = -Im[k1][columns/2] = Im[rows-k1][columns/2],
* 0<k1<rows/2,
* a[0] = Re[0][0],
* a[1] = Re[0][columns/2],
* a[(rows/2)*columns] = Re[rows/2][0],
* a[(rows/2)*columns+1] = Re[rows/2][columns/2]
*
*
* This method computes only half of the elements of the real transform. The
* other half satisfies the symmetry condition. If you want the full real
* inverse transform, use realInverseFull.
*
* @param a
* data to transform
*
* @param scale
* if true then scaling is performed
*/
public void realInverse(double[] a, boolean scale)
{
if (isPowerOfTwo == false) {
throw new IllegalArgumentException("rows and columns must be power of two numbers");
} else {
int nthreads = ConcurrencyUtils.getNumberOfThreads();
if ((nthreads > 1) && useThreads) {
rdft2d_sub(-1, a);
cdft2d_subth(1, a, scale);
xdft2d0_subth1(1, -1, a, scale);
} else {
rdft2d_sub(-1, a);
cdft2d_sub(1, a, scale);
for (int r = 0; r < rows; r++) {
fftColumns.realInverse(a, r * columns, scale);
}
}
}
}
/**
* Computes 2D inverse DFT of real data leaving the result in a
* . This method only works when the sizes of both dimensions are
* power-of-two numbers. The physical layout of the input data has to be as
* follows:
*
*
* a[k1*columns+2*k2] = Re[k1][k2] = Re[rows-k1][columns-k2],
* a[k1*columns+2*k2+1] = Im[k1][k2] = -Im[rows-k1][columns-k2],
* 0<k1<rows, 0<k2<columns/2,
* a[2*k2] = Re[0][k2] = Re[0][columns-k2],
* a[2*k2+1] = Im[0][k2] = -Im[0][columns-k2],
* 0<k2<columns/2,
* a[k1*columns] = Re[k1][0] = Re[rows-k1][0],
* a[k1*columns+1] = Im[k1][0] = -Im[rows-k1][0],
* a[(rows-k1)*columns+1] = Re[k1][columns/2] = Re[rows-k1][columns/2],
* a[(rows-k1)*columns] = -Im[k1][columns/2] = Im[rows-k1][columns/2],
* 0<k1<rows/2,
* a[0] = Re[0][0],
* a[1] = Re[0][columns/2],
* a[(rows/2)*columns] = Re[rows/2][0],
* a[(rows/2)*columns+1] = Re[rows/2][columns/2]
*
*
* This method computes only half of the elements of the real transform. The
* other half satisfies the symmetry condition. If you want the full real
* inverse transform, use realInverseFull.
*
* @param a
* data to transform
*
* @param scale
* if true then scaling is performed
*/
public void realInverse(DoubleLargeArray a, boolean scale)
{
if (isPowerOfTwo == false) {
throw new IllegalArgumentException("rows and columns must be power of two numbers");
} else {
int nthreads = ConcurrencyUtils.getNumberOfThreads();
if ((nthreads > 1) && useThreads) {
rdft2d_sub(-1, a);
cdft2d_subth(1, a, scale);
xdft2d0_subth1(1, -1, a, scale);
} else {
rdft2d_sub(-1, a);
cdft2d_sub(1, a, scale);
for (long r = 0; r < rowsl; r++) {
fftColumns.realInverse(a, r * columnsl, scale);
}
}
}
}
/**
* Computes 2D inverse DFT of real data leaving the result in a
* . This method only works when the sizes of both dimensions are
* power-of-two numbers. The physical layout of the input data has to be as
* follows:
*
*
* a[k1][2*k2] = Re[k1][k2] = Re[rows-k1][columns-k2],
* a[k1][2*k2+1] = Im[k1][k2] = -Im[rows-k1][columns-k2],
* 0<k1<rows, 0<k2<columns/2,
* a[0][2*k2] = Re[0][k2] = Re[0][columns-k2],
* a[0][2*k2+1] = Im[0][k2] = -Im[0][columns-k2],
* 0<k2<columns/2,
* a[k1][0] = Re[k1][0] = Re[rows-k1][0],
* a[k1][1] = Im[k1][0] = -Im[rows-k1][0],
* a[rows-k1][1] = Re[k1][columns/2] = Re[rows-k1][columns/2],
* a[rows-k1][0] = -Im[k1][columns/2] = Im[rows-k1][columns/2],
* 0<k1<rows/2,
* a[0][0] = Re[0][0],
* a[0][1] = Re[0][columns/2],
* a[rows/2][0] = Re[rows/2][0],
* a[rows/2][1] = Re[rows/2][columns/2]
*
*
* This method computes only half of the elements of the real transform. The
* other half satisfies the symmetry condition. If you want the full real
* inverse transform, use realInverseFull.
*
* @param a
* data to transform
*
* @param scale
* if true then scaling is performed
*/
public void realInverse(double[][] a, boolean scale)
{
if (isPowerOfTwo == false) {
throw new IllegalArgumentException("rows and columns must be power of two numbers");
} else {
int nthreads = ConcurrencyUtils.getNumberOfThreads();
if ((nthreads > 1) && useThreads) {
rdft2d_sub(-1, a);
cdft2d_subth(1, a, scale);
xdft2d0_subth1(1, -1, a, scale);
} else {
rdft2d_sub(-1, a);
cdft2d_sub(1, a, scale);
for (int r = 0; r < rows; r++) {
fftColumns.realInverse(a[r], scale);
}
}
}
}
/**
* Computes 2D inverse DFT of real data leaving the result in a
* . This method computes full real inverse transform, i.e. you will get the
* same result as from complexInverse called with all imaginary
* part equal 0. Because the result is stored in a, the input
* array must be of size rows*2*columns, with only the first rows*columns
* elements filled with real data.
*
* @param a
* data to transform
*
* @param scale
* if true then scaling is performed
*/
public void realInverseFull(double[] a, boolean scale)
{
if (isPowerOfTwo) {
int nthreads = ConcurrencyUtils.getNumberOfThreads();
if ((nthreads > 1) && useThreads) {
xdft2d0_subth2(1, -1, a, scale);
cdft2d_subth(1, a, scale);
rdft2d_sub(1, a);
} else {
for (int r = 0; r < rows; r++) {
fftColumns.realInverse2(a, r * columns, scale);
}
cdft2d_sub(1, a, scale);
rdft2d_sub(1, a);
}
fillSymmetric(a);
} else {
mixedRadixRealInverseFull(a, scale);
}
}
/**
* Computes 2D inverse DFT of real data leaving the result in a
* . This method computes full real inverse transform, i.e. you will get the
* same result as from complexInverse called with all imaginary
* part equal 0. Because the result is stored in a, the input
* array must be of size rows*2*columns, with only the first rows*columns
* elements filled with real data.
*
* @param a
* data to transform
*
* @param scale
* if true then scaling is performed
*/
public void realInverseFull(DoubleLargeArray a, boolean scale)
{
if (isPowerOfTwo) {
int nthreads = ConcurrencyUtils.getNumberOfThreads();
if ((nthreads > 1) && useThreads) {
xdft2d0_subth2(1, -1, a, scale);
cdft2d_subth(1, a, scale);
rdft2d_sub(1, a);
} else {
for (long r = 0; r < rowsl; r++) {
fftColumns.realInverse2(a, r * columnsl, scale);
}
cdft2d_sub(1, a, scale);
rdft2d_sub(1, a);
}
fillSymmetric(a);
} else {
mixedRadixRealInverseFull(a, scale);
}
}
/**
* Computes 2D inverse DFT of real data leaving the result in a
* . This method computes full real inverse transform, i.e. you will get the
* same result as from complexInverse called with all imaginary
* part equal 0. Because the result is stored in a, the input
* array must be of size rows by 2*columns, with only the first rows by
* columns elements filled with real data.
*
* @param a
* data to transform
*
* @param scale
* if true then scaling is performed
*/
public void realInverseFull(double[][] a, boolean scale)
{
if (isPowerOfTwo) {
int nthreads = ConcurrencyUtils.getNumberOfThreads();
if ((nthreads > 1) && useThreads) {
xdft2d0_subth2(1, -1, a, scale);
cdft2d_subth(1, a, scale);
rdft2d_sub(1, a);
} else {
for (int r = 0; r < rows; r++) {
fftColumns.realInverse2(a[r], 0, scale);
}
cdft2d_sub(1, a, scale);
rdft2d_sub(1, a);
}
fillSymmetric(a);
} else {
mixedRadixRealInverseFull(a, scale);
}
}
private void mixedRadixRealForwardFull(final double[][] a)
{
final int n2d2 = columns / 2 + 1;
final double[][] temp = new double[n2d2][2 * rows];
int nthreads = ConcurrencyUtils.getNumberOfThreads();
if ((nthreads > 1) && useThreads && (rows >= nthreads) && (n2d2 - 2 >= nthreads)) {
Future[] futures = new Future[nthreads];
int p = rows / nthreads;
for (int l = 0; l < nthreads; l++) {
final int firstRow = l * p;
final int lastRow = (l == (nthreads - 1)) ? rows : firstRow + p;
futures[l] = ConcurrencyUtils.submit(new Runnable()
{
public void run()
{
for (int i = firstRow; i < lastRow; i++) {
fftColumns.realForward(a[i]);
}
}
});
}
ConcurrencyUtils.waitForCompletion(futures);
for (int r = 0; r < rows; r++) {
temp[0][r] = a[r][0]; //first column is always real
}
fftRows.realForwardFull(temp[0]);
p = (n2d2 - 2) / nthreads;
for (int l = 0; l < nthreads; l++) {
final int firstColumn = 1 + l * p;
final int lastColumn = (l == (nthreads - 1)) ? n2d2 - 1 : firstColumn + p;
futures[l] = ConcurrencyUtils.submit(new Runnable()
{
public void run()
{
for (int c = firstColumn; c < lastColumn; c++) {
int idx2 = 2 * c;
for (int r = 0; r < rows; r++) {
int idx1 = 2 * r;
temp[c][idx1] = a[r][idx2];
temp[c][idx1 + 1] = a[r][idx2 + 1];
}
fftRows.complexForward(temp[c]);
}
}
});
}
ConcurrencyUtils.waitForCompletion(futures);
if ((columns % 2) == 0) {
for (int r = 0; r < rows; r++) {
temp[n2d2 - 1][r] = a[r][1];
//imaginary part = 0;
}
fftRows.realForwardFull(temp[n2d2 - 1]);
} else {
for (int r = 0; r < rows; r++) {
int idx1 = 2 * r;
int idx2 = n2d2 - 1;
temp[idx2][idx1] = a[r][2 * idx2];
temp[idx2][idx1 + 1] = a[r][1];
}
fftRows.complexForward(temp[n2d2 - 1]);
}
p = rows / nthreads;
for (int l = 0; l < nthreads; l++) {
final int firstRow = l * p;
final int lastRow = (l == (nthreads - 1)) ? rows : firstRow + p;
futures[l] = ConcurrencyUtils.submit(new Runnable()
{
public void run()
{
for (int r = firstRow; r < lastRow; r++) {
int idx1 = 2 * r;
for (int c = 0; c < n2d2; c++) {
int idx2 = 2 * c;
a[r][idx2] = temp[c][idx1];
a[r][idx2 + 1] = temp[c][idx1 + 1];
}
}
}
});
}
ConcurrencyUtils.waitForCompletion(futures);
for (int l = 0; l < nthreads; l++) {
final int firstRow = 1 + l * p;
final int lastRow = (l == (nthreads - 1)) ? rows : firstRow + p;
futures[l] = ConcurrencyUtils.submit(new Runnable()
{
public void run()
{
for (int r = firstRow; r < lastRow; r++) {
int idx3 = rows - r;
for (int c = n2d2; c < columns; c++) {
int idx1 = 2 * c;
int idx2 = 2 * (columns - c);
a[0][idx1] = a[0][idx2];
a[0][idx1 + 1] = -a[0][idx2 + 1];
a[r][idx1] = a[idx3][idx2];
a[r][idx1 + 1] = -a[idx3][idx2 + 1];
}
}
}
});
}
ConcurrencyUtils.waitForCompletion(futures);
} else {
for (int r = 0; r < rows; r++) {
fftColumns.realForward(a[r]);
}
for (int r = 0; r < rows; r++) {
temp[0][r] = a[r][0]; //first column is always real
}
fftRows.realForwardFull(temp[0]);
for (int c = 1; c < n2d2 - 1; c++) {
int idx2 = 2 * c;
for (int r = 0; r < rows; r++) {
int idx1 = 2 * r;
temp[c][idx1] = a[r][idx2];
temp[c][idx1 + 1] = a[r][idx2 + 1];
}
fftRows.complexForward(temp[c]);
}
if ((columns % 2) == 0) {
for (int r = 0; r < rows; r++) {
temp[n2d2 - 1][r] = a[r][1];
//imaginary part = 0;
}
fftRows.realForwardFull(temp[n2d2 - 1]);
} else {
for (int r = 0; r < rows; r++) {
int idx1 = 2 * r;
int idx2 = n2d2 - 1;
temp[idx2][idx1] = a[r][2 * idx2];
temp[idx2][idx1 + 1] = a[r][1];
}
fftRows.complexForward(temp[n2d2 - 1]);
}
for (int r = 0; r < rows; r++) {
int idx1 = 2 * r;
for (int c = 0; c < n2d2; c++) {
int idx2 = 2 * c;
a[r][idx2] = temp[c][idx1];
a[r][idx2 + 1] = temp[c][idx1 + 1];
}
}
//fill symmetric
for (int r = 1; r < rows; r++) {
int idx3 = rows - r;
for (int c = n2d2; c < columns; c++) {
int idx1 = 2 * c;
int idx2 = 2 * (columns - c);
a[0][idx1] = a[0][idx2];
a[0][idx1 + 1] = -a[0][idx2 + 1];
a[r][idx1] = a[idx3][idx2];
a[r][idx1 + 1] = -a[idx3][idx2 + 1];
}
}
}
}
private void mixedRadixRealForwardFull(final double[] a)
{
final int rowStride = 2 * columns;
final int n2d2 = columns / 2 + 1;
final double[][] temp = new double[n2d2][2 * rows];
int nthreads = ConcurrencyUtils.getNumberOfThreads();
if ((nthreads > 1) && useThreads && (rows >= nthreads) && (n2d2 - 2 >= nthreads)) {
Future[] futures = new Future[nthreads];
int p = rows / nthreads;
for (int l = 0; l < nthreads; l++) {
final int firstRow = l * p;
final int lastRow = (l == (nthreads - 1)) ? rows : firstRow + p;
futures[l] = ConcurrencyUtils.submit(new Runnable()
{
public void run()
{
for (int i = firstRow; i < lastRow; i++) {
fftColumns.realForward(a, i * columns);
}
}
});
}
ConcurrencyUtils.waitForCompletion(futures);
for (int r = 0; r < rows; r++) {
temp[0][r] = a[r * columns]; //first column is always real
}
fftRows.realForwardFull(temp[0]);
p = (n2d2 - 2) / nthreads;
for (int l = 0; l < nthreads; l++) {
final int firstColumn = 1 + l * p;
final int lastColumn = (l == (nthreads - 1)) ? n2d2 - 1 : firstColumn + p;
futures[l] = ConcurrencyUtils.submit(new Runnable()
{
public void run()
{
for (int c = firstColumn; c < lastColumn; c++) {
int idx0 = 2 * c;
for (int r = 0; r < rows; r++) {
int idx1 = 2 * r;
int idx2 = r * columns + idx0;
temp[c][idx1] = a[idx2];
temp[c][idx1 + 1] = a[idx2 + 1];
}
fftRows.complexForward(temp[c]);
}
}
});
}
ConcurrencyUtils.waitForCompletion(futures);
if ((columns % 2) == 0) {
for (int r = 0; r < rows; r++) {
temp[n2d2 - 1][r] = a[r * columns + 1];
//imaginary part = 0;
}
fftRows.realForwardFull(temp[n2d2 - 1]);
} else {
for (int r = 0; r < rows; r++) {
int idx1 = 2 * r;
int idx2 = r * columns;
int idx3 = n2d2 - 1;
temp[idx3][idx1] = a[idx2 + 2 * idx3];
temp[idx3][idx1 + 1] = a[idx2 + 1];
}
fftRows.complexForward(temp[n2d2 - 1]);
}
p = rows / nthreads;
for (int l = 0; l < nthreads; l++) {
final int firstRow = l * p;
final int lastRow = (l == (nthreads - 1)) ? rows : firstRow + p;
futures[l] = ConcurrencyUtils.submit(new Runnable()
{
public void run()
{
for (int r = firstRow; r < lastRow; r++) {
int idx1 = 2 * r;
for (int c = 0; c < n2d2; c++) {
int idx0 = 2 * c;
int idx2 = r * rowStride + idx0;
a[idx2] = temp[c][idx1];
a[idx2 + 1] = temp[c][idx1 + 1];
}
}
}
});
}
ConcurrencyUtils.waitForCompletion(futures);
for (int l = 0; l < nthreads; l++) {
final int firstRow = 1 + l * p;
final int lastRow = (l == (nthreads - 1)) ? rows : firstRow + p;
futures[l] = ConcurrencyUtils.submit(new Runnable()
{
public void run()
{
for (int r = firstRow; r < lastRow; r++) {
int idx5 = r * rowStride;
int idx6 = (rows - r + 1) * rowStride;
for (int c = n2d2; c < columns; c++) {
int idx1 = 2 * c;
int idx2 = 2 * (columns - c);
a[idx1] = a[idx2];
a[idx1 + 1] = -a[idx2 + 1];
int idx3 = idx5 + idx1;
int idx4 = idx6 - idx1;
a[idx3] = a[idx4];
a[idx3 + 1] = -a[idx4 + 1];
}
}
}
});
}
ConcurrencyUtils.waitForCompletion(futures);
} else {
for (int r = 0; r < rows; r++) {
fftColumns.realForward(a, r * columns);
}
for (int r = 0; r < rows; r++) {
temp[0][r] = a[r * columns]; //first column is always real
}
fftRows.realForwardFull(temp[0]);
for (int c = 1; c < n2d2 - 1; c++) {
int idx0 = 2 * c;
for (int r = 0; r < rows; r++) {
int idx1 = 2 * r;
int idx2 = r * columns + idx0;
temp[c][idx1] = a[idx2];
temp[c][idx1 + 1] = a[idx2 + 1];
}
fftRows.complexForward(temp[c]);
}
if ((columns % 2) == 0) {
for (int r = 0; r < rows; r++) {
temp[n2d2 - 1][r] = a[r * columns + 1];
//imaginary part = 0;
}
fftRows.realForwardFull(temp[n2d2 - 1]);
} else {
for (int r = 0; r < rows; r++) {
int idx1 = 2 * r;
int idx2 = r * columns;
int idx3 = n2d2 - 1;
temp[idx3][idx1] = a[idx2 + 2 * idx3];
temp[idx3][idx1 + 1] = a[idx2 + 1];
}
fftRows.complexForward(temp[n2d2 - 1]);
}
for (int r = 0; r < rows; r++) {
int idx1 = 2 * r;
for (int c = 0; c < n2d2; c++) {
int idx0 = 2 * c;
int idx2 = r * rowStride + idx0;
a[idx2] = temp[c][idx1];
a[idx2 + 1] = temp[c][idx1 + 1];
}
}
//fill symmetric
for (int r = 1; r < rows; r++) {
int idx5 = r * rowStride;
int idx6 = (rows - r + 1) * rowStride;
for (int c = n2d2; c < columns; c++) {
int idx1 = 2 * c;
int idx2 = 2 * (columns - c);
a[idx1] = a[idx2];
a[idx1 + 1] = -a[idx2 + 1];
int idx3 = idx5 + idx1;
int idx4 = idx6 - idx1;
a[idx3] = a[idx4];
a[idx3 + 1] = -a[idx4 + 1];
}
}
}
}
private void mixedRadixRealForwardFull(final DoubleLargeArray a)
{
final long rowStride = 2 * columnsl;
final long n2d2 = columnsl / 2 + 1;
final DoubleLargeArray temp = new DoubleLargeArray(n2d2 * 2 * rowsl, false);
final long temp_stride = 2 * rowsl;
int nthreads = ConcurrencyUtils.getNumberOfThreads();
if ((nthreads > 1) && useThreads && (rowsl >= nthreads) && (n2d2 - 2 >= nthreads)) {
Future[] futures = new Future[nthreads];
long p = rowsl / nthreads;
for (int l = 0; l < nthreads; l++) {
final long firstRow = l * p;
final long lastRow = (l == (nthreads - 1)) ? rowsl : firstRow + p;
futures[l] = ConcurrencyUtils.submit(new Runnable()
{
public void run()
{
for (long i = firstRow; i < lastRow; i++) {
fftColumns.realForward(a, i * columnsl);
}
}
});
}
ConcurrencyUtils.waitForCompletion(futures);
for (long r = 0; r < rowsl; r++) {
temp.setDouble(r, a.getDouble(r * columnsl)); //first column is always real
}
fftRows.realForwardFull(temp);
p = (n2d2 - 2) / nthreads;
for (int l = 0; l < nthreads; l++) {
final long firstColumn = 1 + l * p;
final long lastColumn = (l == (nthreads - 1)) ? n2d2 - 1 : firstColumn + p;
futures[l] = ConcurrencyUtils.submit(new Runnable()
{
public void run()
{
for (long c = firstColumn; c < lastColumn; c++) {
long idx0 = 2 * c;
for (long r = 0; r < rowsl; r++) {
long idx1 = 2 * r;
long idx2 = r * columnsl + idx0;
temp.setDouble(c * temp_stride + idx1, a.getDouble(idx2));
temp.setDouble(c * temp_stride + idx1 + 1, a.getDouble(idx2 + 1));
}
fftRows.complexForward(temp, c * temp_stride);
}
}
});
}
ConcurrencyUtils.waitForCompletion(futures);
if ((columnsl % 2) == 0) {
for (long r = 0; r < rowsl; r++) {
temp.setDouble((n2d2 - 1) * temp_stride + r, a.getDouble(r * columnsl + 1));
//imaginary part = 0;
}
fftRows.realForwardFull(temp, (n2d2 - 1) * temp_stride);
} else {
for (long r = 0; r < rowsl; r++) {
long idx1 = 2 * r;
long idx2 = r * columnsl;
long idx3 = n2d2 - 1;
temp.setDouble(idx3 * temp_stride + idx1, a.getDouble(idx2 + 2 * idx3));
temp.setDouble(idx3 * temp_stride + idx1 + 1, a.getDouble(idx2 + 1));
}
fftRows.complexForward(temp, (n2d2 - 1) * temp_stride);
}
p = rowsl / nthreads;
for (int l = 0; l < nthreads; l++) {
final long firstRow = l * p;
final long lastRow = (l == (nthreads - 1)) ? rowsl : firstRow + p;
futures[l] = ConcurrencyUtils.submit(new Runnable()
{
public void run()
{
for (long r = firstRow; r < lastRow; r++) {
long idx1 = 2 * r;
for (long c = 0; c < n2d2; c++) {
long idx0 = 2 * c;
long idx2 = r * rowStride + idx0;
a.setDouble(idx2, temp.getDouble(c * temp_stride + idx1));
a.setDouble(idx2 + 1, temp.getDouble(c * temp_stride + idx1 + 1));
}
}
}
});
}
ConcurrencyUtils.waitForCompletion(futures);
for (int l = 0; l < nthreads; l++) {
final long firstRow = 1 + l * p;
final long lastRow = (l == (nthreads - 1)) ? rowsl : firstRow + p;
futures[l] = ConcurrencyUtils.submit(new Runnable()
{
public void run()
{
for (long r = firstRow; r < lastRow; r++) {
long idx5 = r * rowStride;
long idx6 = (rowsl - r + 1) * rowStride;
for (long c = n2d2; c < columnsl; c++) {
long idx1 = 2 * c;
long idx2 = 2 * (columnsl - c);
a.setDouble(idx1, a.getDouble(idx2));
a.setDouble(idx1 + 1, -a.getDouble(idx2 + 1));
long idx3 = idx5 + idx1;
long idx4 = idx6 - idx1;
a.setDouble(idx3, a.getDouble(idx4));
a.setDouble(idx3 + 1, -a.getDouble(idx4 + 1));
}
}
}
});
}
ConcurrencyUtils.waitForCompletion(futures);
} else {
for (long r = 0; r < rowsl; r++) {
fftColumns.realForward(a, r * columnsl);
}
for (long r = 0; r < rowsl; r++) {
temp.setDouble(r, a.getDouble(r * columnsl)); //first column is always real
}
fftRows.realForwardFull(temp);
for (long c = 1; c < n2d2 - 1; c++) {
long idx0 = 2 * c;
for (long r = 0; r < rowsl; r++) {
long idx1 = 2 * r;
long idx2 = r * columnsl + idx0;
temp.setDouble(c * temp_stride + idx1, a.getDouble(idx2));
temp.setDouble(c * temp_stride + idx1 + 1, a.getDouble(idx2 + 1));
}
fftRows.complexForward(temp, c * temp_stride);
}
if ((columnsl % 2) == 0) {
for (long r = 0; r < rowsl; r++) {
temp.setDouble((n2d2 - 1) * temp_stride + r, a.getDouble(r * columnsl + 1));
//imaginary part = 0;
}
fftRows.realForwardFull(temp, (n2d2 - 1) * temp_stride);
} else {
for (long r = 0; r < rowsl; r++) {
long idx1 = 2 * r;
long idx2 = r * columnsl;
long idx3 = n2d2 - 1;
temp.setDouble(idx3 * temp_stride + idx1, a.getDouble(idx2 + 2 * idx3));
temp.setDouble(idx3 * temp_stride + idx1 + 1, a.getDouble(idx2 + 1));
}
fftRows.complexForward(temp, (n2d2 - 1) * temp_stride);
}
for (long r = 0; r < rowsl; r++) {
long idx1 = 2 * r;
for (long c = 0; c < n2d2; c++) {
long idx0 = 2 * c;
long idx2 = r * rowStride + idx0;
a.setDouble(idx2, temp.getDouble(c * temp_stride + idx1));
a.setDouble(idx2 + 1, temp.getDouble(c * temp_stride + idx1 + 1));
}
}
//fill symmetric
for (long r = 1; r < rowsl; r++) {
long idx5 = r * rowStride;
long idx6 = (rowsl - r + 1) * rowStride;
for (long c = n2d2; c < columnsl; c++) {
long idx1 = 2 * c;
long idx2 = 2 * (columnsl - c);
a.setDouble(idx1, a.getDouble(idx2));
a.setDouble(idx1 + 1, -a.getDouble(idx2 + 1));
long idx3 = idx5 + idx1;
long idx4 = idx6 - idx1;
a.setDouble(idx3, a.getDouble(idx4));
a.setDouble(idx3 + 1, -a.getDouble(idx4 + 1));
}
}
}
}
private void mixedRadixRealInverseFull(final double[][] a, final boolean scale)
{
final int n2d2 = columns / 2 + 1;
final double[][] temp = new double[n2d2][2 * rows];
int nthreads = ConcurrencyUtils.getNumberOfThreads();
if ((nthreads > 1) && useThreads && (rows >= nthreads) && (n2d2 - 2 >= nthreads)) {
Future[] futures = new Future[nthreads];
int p = rows / nthreads;
for (int l = 0; l < nthreads; l++) {
final int firstRow = l * p;
final int lastRow = (l == (nthreads - 1)) ? rows : firstRow + p;
futures[l] = ConcurrencyUtils.submit(new Runnable()
{
public void run()
{
for (int i = firstRow; i < lastRow; i++) {
fftColumns.realInverse2(a[i], 0, scale);
}
}
});
}
ConcurrencyUtils.waitForCompletion(futures);
for (int r = 0; r < rows; r++) {
temp[0][r] = a[r][0]; //first column is always real
}
fftRows.realInverseFull(temp[0], scale);
p = (n2d2 - 2) / nthreads;
for (int l = 0; l < nthreads; l++) {
final int firstColumn = 1 + l * p;
final int lastColumn = (l == (nthreads - 1)) ? n2d2 - 1 : firstColumn + p;
futures[l] = ConcurrencyUtils.submit(new Runnable()
{
public void run()
{
for (int c = firstColumn; c < lastColumn; c++) {
int idx2 = 2 * c;
for (int r = 0; r < rows; r++) {
int idx1 = 2 * r;
temp[c][idx1] = a[r][idx2];
temp[c][idx1 + 1] = a[r][idx2 + 1];
}
fftRows.complexInverse(temp[c], scale);
}
}
});
}
ConcurrencyUtils.waitForCompletion(futures);
if ((columns % 2) == 0) {
for (int r = 0; r < rows; r++) {
temp[n2d2 - 1][r] = a[r][1];
//imaginary part = 0;
}
fftRows.realInverseFull(temp[n2d2 - 1], scale);
} else {
for (int r = 0; r < rows; r++) {
int idx1 = 2 * r;
int idx2 = n2d2 - 1;
temp[idx2][idx1] = a[r][2 * idx2];
temp[idx2][idx1 + 1] = a[r][1];
}
fftRows.complexInverse(temp[n2d2 - 1], scale);
}
p = rows / nthreads;
for (int l = 0; l < nthreads; l++) {
final int firstRow = l * p;
final int lastRow = (l == (nthreads - 1)) ? rows : firstRow + p;
futures[l] = ConcurrencyUtils.submit(new Runnable()
{
public void run()
{
for (int r = firstRow; r < lastRow; r++) {
int idx1 = 2 * r;
for (int c = 0; c < n2d2; c++) {
int idx2 = 2 * c;
a[r][idx2] = temp[c][idx1];
a[r][idx2 + 1] = temp[c][idx1 + 1];
}
}
}
});
}
ConcurrencyUtils.waitForCompletion(futures);
for (int l = 0; l < nthreads; l++) {
final int firstRow = 1 + l * p;
final int lastRow = (l == (nthreads - 1)) ? rows : firstRow + p;
futures[l] = ConcurrencyUtils.submit(new Runnable()
{
public void run()
{
for (int r = firstRow; r < lastRow; r++) {
int idx3 = rows - r;
for (int c = n2d2; c < columns; c++) {
int idx1 = 2 * c;
int idx2 = 2 * (columns - c);
a[0][idx1] = a[0][idx2];
a[0][idx1 + 1] = -a[0][idx2 + 1];
a[r][idx1] = a[idx3][idx2];
a[r][idx1 + 1] = -a[idx3][idx2 + 1];
}
}
}
});
}
ConcurrencyUtils.waitForCompletion(futures);
} else {
for (int r = 0; r < rows; r++) {
fftColumns.realInverse2(a[r], 0, scale);
}
for (int r = 0; r < rows; r++) {
temp[0][r] = a[r][0]; //first column is always real
}
fftRows.realInverseFull(temp[0], scale);
for (int c = 1; c < n2d2 - 1; c++) {
int idx2 = 2 * c;
for (int r = 0; r < rows; r++) {
int idx1 = 2 * r;
temp[c][idx1] = a[r][idx2];
temp[c][idx1 + 1] = a[r][idx2 + 1];
}
fftRows.complexInverse(temp[c], scale);
}
if ((columns % 2) == 0) {
for (int r = 0; r < rows; r++) {
temp[n2d2 - 1][r] = a[r][1];
//imaginary part = 0;
}
fftRows.realInverseFull(temp[n2d2 - 1], scale);
} else {
for (int r = 0; r < rows; r++) {
int idx1 = 2 * r;
int idx2 = n2d2 - 1;
temp[idx2][idx1] = a[r][2 * idx2];
temp[idx2][idx1 + 1] = a[r][1];
}
fftRows.complexInverse(temp[n2d2 - 1], scale);
}
for (int r = 0; r < rows; r++) {
int idx1 = 2 * r;
for (int c = 0; c < n2d2; c++) {
int idx2 = 2 * c;
a[r][idx2] = temp[c][idx1];
a[r][idx2 + 1] = temp[c][idx1 + 1];
}
}
//fill symmetric
for (int r = 1; r < rows; r++) {
int idx3 = rows - r;
for (int c = n2d2; c < columns; c++) {
int idx1 = 2 * c;
int idx2 = 2 * (columns - c);
a[0][idx1] = a[0][idx2];
a[0][idx1 + 1] = -a[0][idx2 + 1];
a[r][idx1] = a[idx3][idx2];
a[r][idx1 + 1] = -a[idx3][idx2 + 1];
}
}
}
}
private void mixedRadixRealInverseFull(final double[] a, final boolean scale)
{
final int rowStride = 2 * columns;
final int n2d2 = columns / 2 + 1;
final double[][] temp = new double[n2d2][2 * rows];
int nthreads = ConcurrencyUtils.getNumberOfThreads();
if ((nthreads > 1) && useThreads && (rows >= nthreads) && (n2d2 - 2 >= nthreads)) {
Future[] futures = new Future[nthreads];
int p = rows / nthreads;
for (int l = 0; l < nthreads; l++) {
final int firstRow = l * p;
final int lastRow = (l == (nthreads - 1)) ? rows : firstRow + p;
futures[l] = ConcurrencyUtils.submit(new Runnable()
{
public void run()
{
for (int i = firstRow; i < lastRow; i++) {
fftColumns.realInverse2(a, i * columns, scale);
}
}
});
}
ConcurrencyUtils.waitForCompletion(futures);
for (int r = 0; r < rows; r++) {
temp[0][r] = a[r * columns]; //first column is always real
}
fftRows.realInverseFull(temp[0], scale);
p = (n2d2 - 2) / nthreads;
for (int l = 0; l < nthreads; l++) {
final int firstColumn = 1 + l * p;
final int lastColumn = (l == (nthreads - 1)) ? n2d2 - 1 : firstColumn + p;
futures[l] = ConcurrencyUtils.submit(new Runnable()
{
public void run()
{
for (int c = firstColumn; c < lastColumn; c++) {
int idx0 = 2 * c;
for (int r = 0; r < rows; r++) {
int idx1 = 2 * r;
int idx2 = r * columns + idx0;
temp[c][idx1] = a[idx2];
temp[c][idx1 + 1] = a[idx2 + 1];
}
fftRows.complexInverse(temp[c], scale);
}
}
});
}
ConcurrencyUtils.waitForCompletion(futures);
if ((columns % 2) == 0) {
for (int r = 0; r < rows; r++) {
temp[n2d2 - 1][r] = a[r * columns + 1];
//imaginary part = 0;
}
fftRows.realInverseFull(temp[n2d2 - 1], scale);
} else {
for (int r = 0; r < rows; r++) {
int idx1 = 2 * r;
int idx2 = r * columns;
int idx3 = n2d2 - 1;
temp[idx3][idx1] = a[idx2 + 2 * idx3];
temp[idx3][idx1 + 1] = a[idx2 + 1];
}
fftRows.complexInverse(temp[n2d2 - 1], scale);
}
p = rows / nthreads;
for (int l = 0; l < nthreads; l++) {
final int firstRow = l * p;
final int lastRow = (l == (nthreads - 1)) ? rows : firstRow + p;
futures[l] = ConcurrencyUtils.submit(new Runnable()
{
public void run()
{
for (int r = firstRow; r < lastRow; r++) {
int idx1 = 2 * r;
for (int c = 0; c < n2d2; c++) {
int idx0 = 2 * c;
int idx2 = r * rowStride + idx0;
a[idx2] = temp[c][idx1];
a[idx2 + 1] = temp[c][idx1 + 1];
}
}
}
});
}
ConcurrencyUtils.waitForCompletion(futures);
for (int l = 0; l < nthreads; l++) {
final int firstRow = 1 + l * p;
final int lastRow = (l == (nthreads - 1)) ? rows : firstRow + p;
futures[l] = ConcurrencyUtils.submit(new Runnable()
{
public void run()
{
for (int r = firstRow; r < lastRow; r++) {
int idx5 = r * rowStride;
int idx6 = (rows - r + 1) * rowStride;
for (int c = n2d2; c < columns; c++) {
int idx1 = 2 * c;
int idx2 = 2 * (columns - c);
a[idx1] = a[idx2];
a[idx1 + 1] = -a[idx2 + 1];
int idx3 = idx5 + idx1;
int idx4 = idx6 - idx1;
a[idx3] = a[idx4];
a[idx3 + 1] = -a[idx4 + 1];
}
}
}
});
}
ConcurrencyUtils.waitForCompletion(futures);
} else {
for (int r = 0; r < rows; r++) {
fftColumns.realInverse2(a, r * columns, scale);
}
for (int r = 0; r < rows; r++) {
temp[0][r] = a[r * columns]; //first column is always real
}
fftRows.realInverseFull(temp[0], scale);
for (int c = 1; c < n2d2 - 1; c++) {
int idx0 = 2 * c;
for (int r = 0; r < rows; r++) {
int idx1 = 2 * r;
int idx2 = r * columns + idx0;
temp[c][idx1] = a[idx2];
temp[c][idx1 + 1] = a[idx2 + 1];
}
fftRows.complexInverse(temp[c], scale);
}
if ((columns % 2) == 0) {
for (int r = 0; r < rows; r++) {
temp[n2d2 - 1][r] = a[r * columns + 1];
//imaginary part = 0;
}
fftRows.realInverseFull(temp[n2d2 - 1], scale);
} else {
for (int r = 0; r < rows; r++) {
int idx1 = 2 * r;
int idx2 = r * columns;
int idx3 = n2d2 - 1;
temp[idx3][idx1] = a[idx2 + 2 * idx3];
temp[idx3][idx1 + 1] = a[idx2 + 1];
}
fftRows.complexInverse(temp[n2d2 - 1], scale);
}
for (int r = 0; r < rows; r++) {
int idx1 = 2 * r;
for (int c = 0; c < n2d2; c++) {
int idx0 = 2 * c;
int idx2 = r * rowStride + idx0;
a[idx2] = temp[c][idx1];
a[idx2 + 1] = temp[c][idx1 + 1];
}
}
//fill symmetric
for (int r = 1; r < rows; r++) {
int idx5 = r * rowStride;
int idx6 = (rows - r + 1) * rowStride;
for (int c = n2d2; c < columns; c++) {
int idx1 = 2 * c;
int idx2 = 2 * (columns - c);
a[idx1] = a[idx2];
a[idx1 + 1] = -a[idx2 + 1];
int idx3 = idx5 + idx1;
int idx4 = idx6 - idx1;
a[idx3] = a[idx4];
a[idx3 + 1] = -a[idx4 + 1];
}
}
}
}
private void mixedRadixRealInverseFull(final DoubleLargeArray a, final boolean scale)
{
final long rowStride = 2 * columnsl;
final long n2d2 = columnsl / 2 + 1;
final DoubleLargeArray temp = new DoubleLargeArray(n2d2 * 2 * rowsl, false);
final long temp_stride = 2 * rowsl;
int nthreads = ConcurrencyUtils.getNumberOfThreads();
if ((nthreads > 1) && useThreads && (rowsl >= nthreads) && (n2d2 - 2 >= nthreads)) {
Future[] futures = new Future[nthreads];
long p = rowsl / nthreads;
for (int l = 0; l < nthreads; l++) {
final long firstRow = l * p;
final long lastRow = (l == (nthreads - 1)) ? rowsl : firstRow + p;
futures[l] = ConcurrencyUtils.submit(new Runnable()
{
public void run()
{
for (long i = firstRow; i < lastRow; i++) {
fftColumns.realInverse2(a, i * columnsl, scale);
}
}
});
}
ConcurrencyUtils.waitForCompletion(futures);
for (long r = 0; r < rowsl; r++) {
temp.setDouble(r, a.getDouble(r * columnsl)); //first column is always real
}
fftRows.realInverseFull(temp, scale);
p = (n2d2 - 2) / nthreads;
for (int l = 0; l < nthreads; l++) {
final long firstColumn = 1 + l * p;
final long lastColumn = (l == (nthreads - 1)) ? n2d2 - 1 : firstColumn + p;
futures[l] = ConcurrencyUtils.submit(new Runnable()
{
public void run()
{
for (long c = firstColumn; c < lastColumn; c++) {
long idx0 = 2 * c;
for (long r = 0; r < rowsl; r++) {
long idx1 = 2 * r;
long idx2 = r * columnsl + idx0;
temp.setDouble(c * temp_stride + idx1, a.getDouble(idx2));
temp.setDouble(c * temp_stride + idx1 + 1, a.getDouble(idx2 + 1));
}
fftRows.complexInverse(temp, c * temp_stride, scale);
}
}
});
}
ConcurrencyUtils.waitForCompletion(futures);
if ((columnsl % 2) == 0) {
for (long r = 0; r < rowsl; r++) {
temp.setDouble((n2d2 - 1) * temp_stride + r, a.getDouble(r * columnsl + 1));
//imaginary part = 0;
}
fftRows.realInverseFull(temp, (n2d2 - 1) * temp_stride, scale);
} else {
for (long r = 0; r < rowsl; r++) {
long idx1 = 2 * r;
long idx2 = r * columnsl;
long idx3 = n2d2 - 1;
temp.setDouble(idx3 * temp_stride + idx1, a.getDouble(idx2 + 2 * idx3));
temp.setDouble(idx3 * temp_stride + idx1 + 1, a.getDouble(idx2 + 1));
}
fftRows.complexInverse(temp, (n2d2 - 1) * temp_stride, scale);
}
p = rowsl / nthreads;
for (int l = 0; l < nthreads; l++) {
final long firstRow = l * p;
final long lastRow = (l == (nthreads - 1)) ? rowsl : firstRow + p;
futures[l] = ConcurrencyUtils.submit(new Runnable()
{
public void run()
{
for (long r = firstRow; r < lastRow; r++) {
long idx1 = 2 * r;
for (long c = 0; c < n2d2; c++) {
long idx0 = 2 * c;
long idx2 = r * rowStride + idx0;
a.setDouble(idx2, temp.getDouble(c * temp_stride + idx1));
a.setDouble(idx2 + 1, temp.getDouble(c * temp_stride + idx1 + 1));
}
}
}
});
}
ConcurrencyUtils.waitForCompletion(futures);
for (int l = 0; l < nthreads; l++) {
final long firstRow = 1 + l * p;
final long lastRow = (l == (nthreads - 1)) ? rowsl : firstRow + p;
futures[l] = ConcurrencyUtils.submit(new Runnable()
{
public void run()
{
for (long r = firstRow; r < lastRow; r++) {
long idx5 = r * rowStride;
long idx6 = (rowsl - r + 1) * rowStride;
for (long c = n2d2; c < columnsl; c++) {
long idx1 = 2 * c;
long idx2 = 2 * (columnsl - c);
a.setDouble(idx1, a.getDouble(idx2));
a.setDouble(idx1 + 1, -a.getDouble(idx2 + 1));
long idx3 = idx5 + idx1;
long idx4 = idx6 - idx1;
a.setDouble(idx3, a.getDouble(idx4));
a.setDouble(idx3 + 1, -a.getDouble(idx4 + 1));
}
}
}
});
}
ConcurrencyUtils.waitForCompletion(futures);
} else {
for (long r = 0; r < rowsl; r++) {
fftColumns.realInverse2(a, r * columnsl, scale);
}
for (long r = 0; r < rowsl; r++) {
temp.setDouble(r, a.getDouble(r * columnsl)); //first column is always real
}
fftRows.realInverseFull(temp, scale);
for (long c = 1; c < n2d2 - 1; c++) {
long idx0 = 2 * c;
for (long r = 0; r < rowsl; r++) {
long idx1 = 2 * r;
long idx2 = r * columnsl + idx0;
temp.setDouble(c * temp_stride + idx1, a.getDouble(idx2));
temp.setDouble(c * temp_stride + idx1 + 1, a.getDouble(idx2 + 1));
}
fftRows.complexInverse(temp, c * temp_stride, scale);
}
if ((columnsl % 2) == 0) {
for (long r = 0; r < rowsl; r++) {
temp.setDouble((n2d2 - 1) * temp_stride + r, a.getDouble(r * columnsl + 1));
//imaginary part = 0;
}
fftRows.realInverseFull(temp, (n2d2 - 1) * temp_stride, scale);
} else {
for (long r = 0; r < rowsl; r++) {
long idx1 = 2 * r;
long idx2 = r * columnsl;
long idx3 = n2d2 - 1;
temp.setDouble(idx3 * temp_stride + idx1, a.getDouble(idx2 + 2 * idx3));
temp.setDouble(idx3 * temp_stride + idx1 + 1, a.getDouble(idx2 + 1));
}
fftRows.complexInverse(temp, (n2d2 - 1) * temp_stride, scale);
}
for (long r = 0; r < rowsl; r++) {
long idx1 = 2 * r;
for (long c = 0; c < n2d2; c++) {
long idx0 = 2 * c;
long idx2 = r * rowStride + idx0;
a.setDouble(idx2, temp.getDouble(c * temp_stride + idx1));
a.setDouble(idx2 + 1, temp.getDouble(c * temp_stride + idx1 + 1));
}
}
//fill symmetric
for (long r = 1; r < rowsl; r++) {
long idx5 = r * rowStride;
long idx6 = (rowsl - r + 1) * rowStride;
for (long c = n2d2; c < columnsl; c++) {
long idx1 = 2 * c;
long idx2 = 2 * (columnsl - c);
a.setDouble(idx1, a.getDouble(idx2));
a.setDouble(idx1 + 1, -a.getDouble(idx2 + 1));
long idx3 = idx5 + idx1;
long idx4 = idx6 - idx1;
a.setDouble(idx3, a.getDouble(idx4));
a.setDouble(idx3 + 1, -a.getDouble(idx4 + 1));
}
}
}
}
private void rdft2d_sub(int isgn, double[] a)
{
int n1h, j;
double xi;
int idx1, idx2;
n1h = rows >> 1;
if (isgn < 0) {
for (int i = 1; i < n1h; i++) {
j = rows - i;
idx1 = i * columns;
idx2 = j * columns;
xi = a[idx1] - a[idx2];
a[idx1] += a[idx2];
a[idx2] = xi;
xi = a[idx2 + 1] - a[idx1 + 1];
a[idx1 + 1] += a[idx2 + 1];
a[idx2 + 1] = xi;
}
} else {
for (int i = 1; i < n1h; i++) {
j = rows - i;
idx1 = i * columns;
idx2 = j * columns;
a[idx2] = 0.5f * (a[idx1] - a[idx2]);
a[idx1] -= a[idx2];
a[idx2 + 1] = 0.5f * (a[idx1 + 1] + a[idx2 + 1]);
a[idx1 + 1] -= a[idx2 + 1];
}
}
}
private void rdft2d_sub(int isgn, DoubleLargeArray a)
{
long n1h, j;
double xi;
long idx1, idx2;
n1h = rowsl >> 1;
if (isgn < 0) {
for (long i = 1; i < n1h; i++) {
j = rowsl - i;
idx1 = i * columnsl;
idx2 = j * columnsl;
xi = a.getDouble(idx1) - a.getDouble(idx2);
a.setDouble(idx1, a.getDouble(idx1) + a.getDouble(idx2));
a.setDouble(idx2, xi);
xi = a.getDouble(idx2 + 1) - a.getDouble(idx1 + 1);
a.setDouble(idx1 + 1, a.getDouble(idx1 + 1) + a.getDouble(idx2 + 1));
a.setDouble(idx2 + 1, xi);
}
} else {
for (long i = 1; i < n1h; i++) {
j = rowsl - i;
idx1 = i * columnsl;
idx2 = j * columnsl;
a.setDouble(idx2, 0.5f * (a.getDouble(idx1) - a.getDouble(idx2)));
a.setDouble(idx1, a.getDouble(idx1) - a.getDouble(idx2));
a.setDouble(idx2 + 1, 0.5f * (a.getDouble(idx1 + 1) + a.getDouble(idx2 + 1)));
a.setDouble(idx1 + 1, a.getDouble(idx1 + 1) - a.getDouble(idx2 + 1));
}
}
}
private void rdft2d_sub(int isgn, double[][] a)
{
int n1h, j;
double xi;
n1h = rows >> 1;
if (isgn < 0) {
for (int i = 1; i < n1h; i++) {
j = rows - i;
xi = a[i][0] - a[j][0];
a[i][0] += a[j][0];
a[j][0] = xi;
xi = a[j][1] - a[i][1];
a[i][1] += a[j][1];
a[j][1] = xi;
}
} else {
for (int i = 1; i < n1h; i++) {
j = rows - i;
a[j][0] = 0.5f * (a[i][0] - a[j][0]);
a[i][0] -= a[j][0];
a[j][1] = 0.5f * (a[i][1] + a[j][1]);
a[i][1] -= a[j][1];
}
}
}
private void cdft2d_sub(int isgn, double[] a, boolean scale)
{
int idx1, idx2, idx3, idx4, idx5;
int nt = 8 * rows;
if (columns == 4) {
nt >>= 1;
} else if (columns < 4) {
nt >>= 2;
}
double[] t = new double[nt];
if (isgn == -1) {
if (columns > 4) {
for (int c = 0; c < columns; c += 8) {
for (int r = 0; r < rows; r++) {
idx1 = r * columns + c;
idx2 = 2 * r;
idx3 = 2 * rows + 2 * r;
idx4 = idx3 + 2 * rows;
idx5 = idx4 + 2 * rows;
t[idx2] = a[idx1];
t[idx2 + 1] = a[idx1 + 1];
t[idx3] = a[idx1 + 2];
t[idx3 + 1] = a[idx1 + 3];
t[idx4] = a[idx1 + 4];
t[idx4 + 1] = a[idx1 + 5];
t[idx5] = a[idx1 + 6];
t[idx5 + 1] = a[idx1 + 7];
}
fftRows.complexForward(t, 0);
fftRows.complexForward(t, 2 * rows);
fftRows.complexForward(t, 4 * rows);
fftRows.complexForward(t, 6 * rows);
for (int r = 0; r < rows; r++) {
idx1 = r * columns + c;
idx2 = 2 * r;
idx3 = 2 * rows + 2 * r;
idx4 = idx3 + 2 * rows;
idx5 = idx4 + 2 * rows;
a[idx1] = t[idx2];
a[idx1 + 1] = t[idx2 + 1];
a[idx1 + 2] = t[idx3];
a[idx1 + 3] = t[idx3 + 1];
a[idx1 + 4] = t[idx4];
a[idx1 + 5] = t[idx4 + 1];
a[idx1 + 6] = t[idx5];
a[idx1 + 7] = t[idx5 + 1];
}
}
} else if (columns == 4) {
for (int r = 0; r < rows; r++) {
idx1 = r * columns;
idx2 = 2 * r;
idx3 = 2 * rows + 2 * r;
t[idx2] = a[idx1];
t[idx2 + 1] = a[idx1 + 1];
t[idx3] = a[idx1 + 2];
t[idx3 + 1] = a[idx1 + 3];
}
fftRows.complexForward(t, 0);
fftRows.complexForward(t, 2 * rows);
for (int r = 0; r < rows; r++) {
idx1 = r * columns;
idx2 = 2 * r;
idx3 = 2 * rows + 2 * r;
a[idx1] = t[idx2];
a[idx1 + 1] = t[idx2 + 1];
a[idx1 + 2] = t[idx3];
a[idx1 + 3] = t[idx3 + 1];
}
} else if (columns == 2) {
for (int r = 0; r < rows; r++) {
idx1 = r * columns;
idx2 = 2 * r;
t[idx2] = a[idx1];
t[idx2 + 1] = a[idx1 + 1];
}
fftRows.complexForward(t, 0);
for (int r = 0; r < rows; r++) {
idx1 = r * columns;
idx2 = 2 * r;
a[idx1] = t[idx2];
a[idx1 + 1] = t[idx2 + 1];
}
}
} else {
if (columns > 4) {
for (int c = 0; c < columns; c += 8) {
for (int r = 0; r < rows; r++) {
idx1 = r * columns + c;
idx2 = 2 * r;
idx3 = 2 * rows + 2 * r;
idx4 = idx3 + 2 * rows;
idx5 = idx4 + 2 * rows;
t[idx2] = a[idx1];
t[idx2 + 1] = a[idx1 + 1];
t[idx3] = a[idx1 + 2];
t[idx3 + 1] = a[idx1 + 3];
t[idx4] = a[idx1 + 4];
t[idx4 + 1] = a[idx1 + 5];
t[idx5] = a[idx1 + 6];
t[idx5 + 1] = a[idx1 + 7];
}
fftRows.complexInverse(t, 0, scale);
fftRows.complexInverse(t, 2 * rows, scale);
fftRows.complexInverse(t, 4 * rows, scale);
fftRows.complexInverse(t, 6 * rows, scale);
for (int r = 0; r < rows; r++) {
idx1 = r * columns + c;
idx2 = 2 * r;
idx3 = 2 * rows + 2 * r;
idx4 = idx3 + 2 * rows;
idx5 = idx4 + 2 * rows;
a[idx1] = t[idx2];
a[idx1 + 1] = t[idx2 + 1];
a[idx1 + 2] = t[idx3];
a[idx1 + 3] = t[idx3 + 1];
a[idx1 + 4] = t[idx4];
a[idx1 + 5] = t[idx4 + 1];
a[idx1 + 6] = t[idx5];
a[idx1 + 7] = t[idx5 + 1];
}
}
} else if (columns == 4) {
for (int r = 0; r < rows; r++) {
idx1 = r * columns;
idx2 = 2 * r;
idx3 = 2 * rows + 2 * r;
t[idx2] = a[idx1];
t[idx2 + 1] = a[idx1 + 1];
t[idx3] = a[idx1 + 2];
t[idx3 + 1] = a[idx1 + 3];
}
fftRows.complexInverse(t, 0, scale);
fftRows.complexInverse(t, 2 * rows, scale);
for (int r = 0; r < rows; r++) {
idx1 = r * columns;
idx2 = 2 * r;
idx3 = 2 * rows + 2 * r;
a[idx1] = t[idx2];
a[idx1 + 1] = t[idx2 + 1];
a[idx1 + 2] = t[idx3];
a[idx1 + 3] = t[idx3 + 1];
}
} else if (columns == 2) {
for (int r = 0; r < rows; r++) {
idx1 = r * columns;
idx2 = 2 * r;
t[idx2] = a[idx1];
t[idx2 + 1] = a[idx1 + 1];
}
fftRows.complexInverse(t, 0, scale);
for (int r = 0; r < rows; r++) {
idx1 = r * columns;
idx2 = 2 * r;
a[idx1] = t[idx2];
a[idx1 + 1] = t[idx2 + 1];
}
}
}
}
private void cdft2d_sub(int isgn, DoubleLargeArray a, boolean scale)
{
long idx1, idx2, idx3, idx4, idx5;
long nt = 8 * rowsl;
if (columnsl == 4) {
nt >>= 1;
} else if (columnsl < 4) {
nt >>= 2;
}
DoubleLargeArray t = new DoubleLargeArray(nt, false);
if (isgn == -1) {
if (columnsl > 4) {
for (long c = 0; c < columnsl; c += 8) {
for (long r = 0; r < rowsl; r++) {
idx1 = r * columnsl + c;
idx2 = 2 * r;
idx3 = 2 * rowsl + 2 * r;
idx4 = idx3 + 2 * rowsl;
idx5 = idx4 + 2 * rowsl;
t.setDouble(idx2, a.getDouble(idx1));
t.setDouble(idx2 + 1, a.getDouble(idx1 + 1));
t.setDouble(idx3, a.getDouble(idx1 + 2));
t.setDouble(idx3 + 1, a.getDouble(idx1 + 3));
t.setDouble(idx4, a.getDouble(idx1 + 4));
t.setDouble(idx4 + 1, a.getDouble(idx1 + 5));
t.setDouble(idx5, a.getDouble(idx1 + 6));
t.setDouble(idx5 + 1, a.getDouble(idx1 + 7));
}
fftRows.complexForward(t, 0);
fftRows.complexForward(t, 2 * rowsl);
fftRows.complexForward(t, 4 * rowsl);
fftRows.complexForward(t, 6 * rowsl);
for (long r = 0; r < rowsl; r++) {
idx1 = r * columnsl + c;
idx2 = 2 * r;
idx3 = 2 * rowsl + 2 * r;
idx4 = idx3 + 2 * rowsl;
idx5 = idx4 + 2 * rowsl;
a.setDouble(idx1, t.getDouble(idx2));
a.setDouble(idx1 + 1, t.getDouble(idx2 + 1));
a.setDouble(idx1 + 2, t.getDouble(idx3));
a.setDouble(idx1 + 3, t.getDouble(idx3 + 1));
a.setDouble(idx1 + 4, t.getDouble(idx4));
a.setDouble(idx1 + 5, t.getDouble(idx4 + 1));
a.setDouble(idx1 + 6, t.getDouble(idx5));
a.setDouble(idx1 + 7, t.getDouble(idx5 + 1));
}
}
} else if (columnsl == 4) {
for (long r = 0; r < rowsl; r++) {
idx1 = r * columnsl;
idx2 = 2 * r;
idx3 = 2 * rowsl + 2 * r;
t.setDouble(idx2, a.getDouble(idx1));
t.setDouble(idx2 + 1, a.getDouble(idx1 + 1));
t.setDouble(idx3, a.getDouble(idx1 + 2));
t.setDouble(idx3 + 1, a.getDouble(idx1 + 3));
}
fftRows.complexForward(t, 0);
fftRows.complexForward(t, 2 * rowsl);
for (long r = 0; r < rowsl; r++) {
idx1 = r * columnsl;
idx2 = 2 * r;
idx3 = 2 * rowsl + 2 * r;
a.setDouble(idx1, t.getDouble(idx2));
a.setDouble(idx1 + 1, t.getDouble(idx2 + 1));
a.setDouble(idx1 + 2, t.getDouble(idx3));
a.setDouble(idx1 + 3, t.getDouble(idx3 + 1));
}
} else if (columnsl == 2) {
for (long r = 0; r < rowsl; r++) {
idx1 = r * columnsl;
idx2 = 2 * r;
t.setDouble(idx2, a.getDouble(idx1));
t.setDouble(idx2 + 1, a.getDouble(idx1 + 1));
}
fftRows.complexForward(t, 0);
for (long r = 0; r < rowsl; r++) {
idx1 = r * columnsl;
idx2 = 2 * r;
a.setDouble(idx1, t.getDouble(idx2));
a.setDouble(idx1 + 1, t.getDouble(idx2 + 1));
}
}
} else {
if (columnsl > 4) {
for (long c = 0; c < columnsl; c += 8) {
for (long r = 0; r < rowsl; r++) {
idx1 = r * columnsl + c;
idx2 = 2 * r;
idx3 = 2 * rowsl + 2 * r;
idx4 = idx3 + 2 * rowsl;
idx5 = idx4 + 2 * rowsl;
t.setDouble(idx2, a.getDouble(idx1));
t.setDouble(idx2 + 1, a.getDouble(idx1 + 1));
t.setDouble(idx3, a.getDouble(idx1 + 2));
t.setDouble(idx3 + 1, a.getDouble(idx1 + 3));
t.setDouble(idx4, a.getDouble(idx1 + 4));
t.setDouble(idx4 + 1, a.getDouble(idx1 + 5));
t.setDouble(idx5, a.getDouble(idx1 + 6));
t.setDouble(idx5 + 1, a.getDouble(idx1 + 7));
}
fftRows.complexInverse(t, 0, scale);
fftRows.complexInverse(t, 2 * rowsl, scale);
fftRows.complexInverse(t, 4 * rowsl, scale);
fftRows.complexInverse(t, 6 * rowsl, scale);
for (long r = 0; r < rowsl; r++) {
idx1 = r * columnsl + c;
idx2 = 2 * r;
idx3 = 2 * rowsl + 2 * r;
idx4 = idx3 + 2 * rowsl;
idx5 = idx4 + 2 * rowsl;
a.setDouble(idx1, t.getDouble(idx2));
a.setDouble(idx1 + 1, t.getDouble(idx2 + 1));
a.setDouble(idx1 + 2, t.getDouble(idx3));
a.setDouble(idx1 + 3, t.getDouble(idx3 + 1));
a.setDouble(idx1 + 4, t.getDouble(idx4));
a.setDouble(idx1 + 5, t.getDouble(idx4 + 1));
a.setDouble(idx1 + 6, t.getDouble(idx5));
a.setDouble(idx1 + 7, t.getDouble(idx5 + 1));
}
}
} else if (columnsl == 4) {
for (long r = 0; r < rowsl; r++) {
idx1 = r * columnsl;
idx2 = 2 * r;
idx3 = 2 * rowsl + 2 * r;
t.setDouble(idx2, a.getDouble(idx1));
t.setDouble(idx2 + 1, a.getDouble(idx1 + 1));
t.setDouble(idx3, a.getDouble(idx1 + 2));
t.setDouble(idx3 + 1, a.getDouble(idx1 + 3));
}
fftRows.complexInverse(t, 0, scale);
fftRows.complexInverse(t, 2 * rowsl, scale);
for (long r = 0; r < rowsl; r++) {
idx1 = r * columnsl;
idx2 = 2 * r;
idx3 = 2 * rowsl + 2 * r;
a.setDouble(idx1, t.getDouble(idx2));
a.setDouble(idx1 + 1, t.getDouble(idx2 + 1));
a.setDouble(idx1 + 2, t.getDouble(idx3));
a.setDouble(idx1 + 3, t.getDouble(idx3 + 1));
}
} else if (columnsl == 2) {
for (long r = 0; r < rowsl; r++) {
idx1 = r * columnsl;
idx2 = 2 * r;
t.setDouble(idx2, a.getDouble(idx1));
t.setDouble(idx2 + 1, a.getDouble(idx1 + 1));
}
fftRows.complexInverse(t, 0, scale);
for (long r = 0; r < rowsl; r++) {
idx1 = r * columnsl;
idx2 = 2 * r;
a.setDouble(idx1, t.getDouble(idx2));
a.setDouble(idx1 + 1, t.getDouble(idx2 + 1));
}
}
}
}
private void cdft2d_sub(int isgn, double[][] a, boolean scale)
{
int idx2, idx3, idx4, idx5;
int nt = 8 * rows;
if (columns == 4) {
nt >>= 1;
} else if (columns < 4) {
nt >>= 2;
}
double[] t = new double[nt];
if (isgn == -1) {
if (columns > 4) {
for (int c = 0; c < columns; c += 8) {
for (int r = 0; r < rows; r++) {
idx2 = 2 * r;
idx3 = 2 * rows + 2 * r;
idx4 = idx3 + 2 * rows;
idx5 = idx4 + 2 * rows;
t[idx2] = a[r][c];
t[idx2 + 1] = a[r][c + 1];
t[idx3] = a[r][c + 2];
t[idx3 + 1] = a[r][c + 3];
t[idx4] = a[r][c + 4];
t[idx4 + 1] = a[r][c + 5];
t[idx5] = a[r][c + 6];
t[idx5 + 1] = a[r][c + 7];
}
fftRows.complexForward(t, 0);
fftRows.complexForward(t, 2 * rows);
fftRows.complexForward(t, 4 * rows);
fftRows.complexForward(t, 6 * rows);
for (int r = 0; r < rows; r++) {
idx2 = 2 * r;
idx3 = 2 * rows + 2 * r;
idx4 = idx3 + 2 * rows;
idx5 = idx4 + 2 * rows;
a[r][c] = t[idx2];
a[r][c + 1] = t[idx2 + 1];
a[r][c + 2] = t[idx3];
a[r][c + 3] = t[idx3 + 1];
a[r][c + 4] = t[idx4];
a[r][c + 5] = t[idx4 + 1];
a[r][c + 6] = t[idx5];
a[r][c + 7] = t[idx5 + 1];
}
}
} else if (columns == 4) {
for (int r = 0; r < rows; r++) {
idx2 = 2 * r;
idx3 = 2 * rows + 2 * r;
t[idx2] = a[r][0];
t[idx2 + 1] = a[r][1];
t[idx3] = a[r][2];
t[idx3 + 1] = a[r][3];
}
fftRows.complexForward(t, 0);
fftRows.complexForward(t, 2 * rows);
for (int r = 0; r < rows; r++) {
idx2 = 2 * r;
idx3 = 2 * rows + 2 * r;
a[r][0] = t[idx2];
a[r][1] = t[idx2 + 1];
a[r][2] = t[idx3];
a[r][3] = t[idx3 + 1];
}
} else if (columns == 2) {
for (int r = 0; r < rows; r++) {
idx2 = 2 * r;
t[idx2] = a[r][0];
t[idx2 + 1] = a[r][1];
}
fftRows.complexForward(t, 0);
for (int r = 0; r < rows; r++) {
idx2 = 2 * r;
a[r][0] = t[idx2];
a[r][1] = t[idx2 + 1];
}
}
} else {
if (columns > 4) {
for (int c = 0; c < columns; c += 8) {
for (int r = 0; r < rows; r++) {
idx2 = 2 * r;
idx3 = 2 * rows + 2 * r;
idx4 = idx3 + 2 * rows;
idx5 = idx4 + 2 * rows;
t[idx2] = a[r][c];
t[idx2 + 1] = a[r][c + 1];
t[idx3] = a[r][c + 2];
t[idx3 + 1] = a[r][c + 3];
t[idx4] = a[r][c + 4];
t[idx4 + 1] = a[r][c + 5];
t[idx5] = a[r][c + 6];
t[idx5 + 1] = a[r][c + 7];
}
fftRows.complexInverse(t, 0, scale);
fftRows.complexInverse(t, 2 * rows, scale);
fftRows.complexInverse(t, 4 * rows, scale);
fftRows.complexInverse(t, 6 * rows, scale);
for (int r = 0; r < rows; r++) {
idx2 = 2 * r;
idx3 = 2 * rows + 2 * r;
idx4 = idx3 + 2 * rows;
idx5 = idx4 + 2 * rows;
a[r][c] = t[idx2];
a[r][c + 1] = t[idx2 + 1];
a[r][c + 2] = t[idx3];
a[r][c + 3] = t[idx3 + 1];
a[r][c + 4] = t[idx4];
a[r][c + 5] = t[idx4 + 1];
a[r][c + 6] = t[idx5];
a[r][c + 7] = t[idx5 + 1];
}
}
} else if (columns == 4) {
for (int r = 0; r < rows; r++) {
idx2 = 2 * r;
idx3 = 2 * rows + 2 * r;
t[idx2] = a[r][0];
t[idx2 + 1] = a[r][1];
t[idx3] = a[r][2];
t[idx3 + 1] = a[r][3];
}
fftRows.complexInverse(t, 0, scale);
fftRows.complexInverse(t, 2 * rows, scale);
for (int r = 0; r < rows; r++) {
idx2 = 2 * r;
idx3 = 2 * rows + 2 * r;
a[r][0] = t[idx2];
a[r][1] = t[idx2 + 1];
a[r][2] = t[idx3];
a[r][3] = t[idx3 + 1];
}
} else if (columns == 2) {
for (int r = 0; r < rows; r++) {
idx2 = 2 * r;
t[idx2] = a[r][0];
t[idx2 + 1] = a[r][1];
}
fftRows.complexInverse(t, 0, scale);
for (int r = 0; r < rows; r++) {
idx2 = 2 * r;
a[r][0] = t[idx2];
a[r][1] = t[idx2 + 1];
}
}
}
}
private void xdft2d0_subth1(final int icr, final int isgn, final double[] a, final boolean scale)
{
final int nthreads = ConcurrencyUtils.getNumberOfThreads() > rows ? rows : ConcurrencyUtils.getNumberOfThreads();
Future[] futures = new Future[nthreads];
for (int i = 0; i < nthreads; i++) {
final int n0 = i;
futures[i] = ConcurrencyUtils.submit(new Runnable()
{
public void run()
{
if (icr == 0) {
if (isgn == -1) {
for (int r = n0; r < rows; r += nthreads) {
fftColumns.complexForward(a, r * columns);
}
} else {
for (int r = n0; r < rows; r += nthreads) {
fftColumns.complexInverse(a, r * columns, scale);
}
}
} else {
if (isgn == 1) {
for (int r = n0; r < rows; r += nthreads) {
fftColumns.realForward(a, r * columns);
}
} else {
for (int r = n0; r < rows; r += nthreads) {
fftColumns.realInverse(a, r * columns, scale);
}
}
}
}
});
}
ConcurrencyUtils.waitForCompletion(futures);
}
private void xdft2d0_subth1(final long icr, final int isgn, final DoubleLargeArray a, final boolean scale)
{
final int nthreads = (int) (ConcurrencyUtils.getNumberOfThreads() > rowsl ? rowsl : ConcurrencyUtils.getNumberOfThreads());
Future[] futures = new Future[nthreads];
for (int i = 0; i < nthreads; i++) {
final int n0 = i;
futures[i] = ConcurrencyUtils.submit(new Runnable()
{
public void run()
{
if (icr == 0) {
if (isgn == -1) {
for (long r = n0; r < rowsl; r += nthreads) {
fftColumns.complexForward(a, r * columnsl);
}
} else {
for (long r = n0; r < rowsl; r += nthreads) {
fftColumns.complexInverse(a, r * columnsl, scale);
}
}
} else {
if (isgn == 1) {
for (long r = n0; r < rowsl; r += nthreads) {
fftColumns.realForward(a, r * columnsl);
}
} else {
for (long r = n0; r < rowsl; r += nthreads) {
fftColumns.realInverse(a, r * columnsl, scale);
}
}
}
}
});
}
ConcurrencyUtils.waitForCompletion(futures);
}
private void xdft2d0_subth2(final int icr, final int isgn, final double[] a, final boolean scale)
{
final int nthreads = ConcurrencyUtils.getNumberOfThreads() > rows ? rows : ConcurrencyUtils.getNumberOfThreads();
Future[] futures = new Future[nthreads];
for (int i = 0; i < nthreads; i++) {
final int n0 = i;
futures[i] = ConcurrencyUtils.submit(new Runnable()
{
public void run()
{
if (icr == 0) {
if (isgn == -1) {
for (int r = n0; r < rows; r += nthreads) {
fftColumns.complexForward(a, r * columns);
}
} else {
for (int r = n0; r < rows; r += nthreads) {
fftColumns.complexInverse(a, r * columns, scale);
}
}
} else {
if (isgn == 1) {
for (int r = n0; r < rows; r += nthreads) {
fftColumns.realForward(a, r * columns);
}
} else {
for (int r = n0; r < rows; r += nthreads) {
fftColumns.realInverse2(a, r * columns, scale);
}
}
}
}
});
}
ConcurrencyUtils.waitForCompletion(futures);
}
private void xdft2d0_subth2(final long icr, final int isgn, final DoubleLargeArray a, final boolean scale)
{
final int nthreads = ConcurrencyUtils.getNumberOfThreads() > rows ? rows : ConcurrencyUtils.getNumberOfThreads();
Future[] futures = new Future[nthreads];
for (int i = 0; i < nthreads; i++) {
final long n0 = i;
futures[i] = ConcurrencyUtils.submit(new Runnable()
{
public void run()
{
if (icr == 0) {
if (isgn == -1) {
for (long r = n0; r < rowsl; r += nthreads) {
fftColumns.complexForward(a, r * columnsl);
}
} else {
for (long r = n0; r < rowsl; r += nthreads) {
fftColumns.complexInverse(a, r * columnsl, scale);
}
}
} else {
if (isgn == 1) {
for (long r = n0; r < rowsl; r += nthreads) {
fftColumns.realForward(a, r * columnsl);
}
} else {
for (long r = n0; r < rowsl; r += nthreads) {
fftColumns.realInverse2(a, r * columnsl, scale);
}
}
}
}
});
}
ConcurrencyUtils.waitForCompletion(futures);
}
private void xdft2d0_subth1(final int icr, final int isgn, final double[][] a, final boolean scale)
{
final int nthreads = ConcurrencyUtils.getNumberOfThreads() > rows ? rows : ConcurrencyUtils.getNumberOfThreads();
Future[] futures = new Future[nthreads];
for (int i = 0; i < nthreads; i++) {
final int n0 = i;
futures[i] = ConcurrencyUtils.submit(new Runnable()
{
public void run()
{
if (icr == 0) {
if (isgn == -1) {
for (int r = n0; r < rows; r += nthreads) {
fftColumns.complexForward(a[r]);
}
} else {
for (int r = n0; r < rows; r += nthreads) {
fftColumns.complexInverse(a[r], scale);
}
}
} else {
if (isgn == 1) {
for (int r = n0; r < rows; r += nthreads) {
fftColumns.realForward(a[r]);
}
} else {
for (int r = n0; r < rows; r += nthreads) {
fftColumns.realInverse(a[r], scale);
}
}
}
}
});
}
ConcurrencyUtils.waitForCompletion(futures);
}
private void xdft2d0_subth2(final int icr, final int isgn, final double[][] a, final boolean scale)
{
final int nthreads = ConcurrencyUtils.getNumberOfThreads() > rows ? rows : ConcurrencyUtils.getNumberOfThreads();
Future[] futures = new Future[nthreads];
for (int i = 0; i < nthreads; i++) {
final int n0 = i;
futures[i] = ConcurrencyUtils.submit(new Runnable()
{
public void run()
{
if (icr == 0) {
if (isgn == -1) {
for (int r = n0; r < rows; r += nthreads) {
fftColumns.complexForward(a[r]);
}
} else {
for (int r = n0; r < rows; r += nthreads) {
fftColumns.complexInverse(a[r], scale);
}
}
} else {
if (isgn == 1) {
for (int r = n0; r < rows; r += nthreads) {
fftColumns.realForward(a[r]);
}
} else {
for (int r = n0; r < rows; r += nthreads) {
fftColumns.realInverse2(a[r], 0, scale);
}
}
}
}
});
}
ConcurrencyUtils.waitForCompletion(futures);
}
private void cdft2d_subth(final int isgn, final double[] a, final boolean scale)
{
int nthread = Math.min(columns / 2, ConcurrencyUtils.getNumberOfThreads());
int nt = 8 * rows;
if (columns == 4) {
nt >>= 1;
} else if (columns < 4) {
nt >>= 2;
}
final int ntf = nt;
Future[] futures = new Future[nthread];
final int nthreads = nthread;
for (int i = 0; i < nthread; i++) {
final int n0 = i;
futures[i] = ConcurrencyUtils.submit(new Runnable()
{
public void run()
{
int idx1, idx2, idx3, idx4, idx5;
double[] t = new double[ntf];
if (isgn == -1) {
if (columns > 4 * nthreads) {
for (int c = 8 * n0; c < columns; c += 8 * nthreads) {
for (int r = 0; r < rows; r++) {
idx1 = r * columns + c;
idx2 = 2 * r;
idx3 = 2 * rows + 2 * r;
idx4 = idx3 + 2 * rows;
idx5 = idx4 + 2 * rows;
t[idx2] = a[idx1];
t[idx2 + 1] = a[idx1 + 1];
t[idx3] = a[idx1 + 2];
t[idx3 + 1] = a[idx1 + 3];
t[idx4] = a[idx1 + 4];
t[idx4 + 1] = a[idx1 + 5];
t[idx5] = a[idx1 + 6];
t[idx5 + 1] = a[idx1 + 7];
}
fftRows.complexForward(t, 0);
fftRows.complexForward(t, 2 * rows);
fftRows.complexForward(t, 4 * rows);
fftRows.complexForward(t, 6 * rows);
for (int r = 0; r < rows; r++) {
idx1 = r * columns + c;
idx2 = 2 * r;
idx3 = 2 * rows + 2 * r;
idx4 = idx3 + 2 * rows;
idx5 = idx4 + 2 * rows;
a[idx1] = t[idx2];
a[idx1 + 1] = t[idx2 + 1];
a[idx1 + 2] = t[idx3];
a[idx1 + 3] = t[idx3 + 1];
a[idx1 + 4] = t[idx4];
a[idx1 + 5] = t[idx4 + 1];
a[idx1 + 6] = t[idx5];
a[idx1 + 7] = t[idx5 + 1];
}
}
} else if (columns == 4 * nthreads) {
for (int r = 0; r < rows; r++) {
idx1 = r * columns + 4 * n0;
idx2 = 2 * r;
idx3 = 2 * rows + 2 * r;
t[idx2] = a[idx1];
t[idx2 + 1] = a[idx1 + 1];
t[idx3] = a[idx1 + 2];
t[idx3 + 1] = a[idx1 + 3];
}
fftRows.complexForward(t, 0);
fftRows.complexForward(t, 2 * rows);
for (int r = 0; r < rows; r++) {
idx1 = r * columns + 4 * n0;
idx2 = 2 * r;
idx3 = 2 * rows + 2 * r;
a[idx1] = t[idx2];
a[idx1 + 1] = t[idx2 + 1];
a[idx1 + 2] = t[idx3];
a[idx1 + 3] = t[idx3 + 1];
}
} else if (columns == 2 * nthreads) {
for (int r = 0; r < rows; r++) {
idx1 = r * columns + 2 * n0;
idx2 = 2 * r;
t[idx2] = a[idx1];
t[idx2 + 1] = a[idx1 + 1];
}
fftRows.complexForward(t, 0);
for (int r = 0; r < rows; r++) {
idx1 = r * columns + 2 * n0;
idx2 = 2 * r;
a[idx1] = t[idx2];
a[idx1 + 1] = t[idx2 + 1];
}
}
} else {
if (columns > 4 * nthreads) {
for (int c = 8 * n0; c < columns; c += 8 * nthreads) {
for (int r = 0; r < rows; r++) {
idx1 = r * columns + c;
idx2 = 2 * r;
idx3 = 2 * rows + 2 * r;
idx4 = idx3 + 2 * rows;
idx5 = idx4 + 2 * rows;
t[idx2] = a[idx1];
t[idx2 + 1] = a[idx1 + 1];
t[idx3] = a[idx1 + 2];
t[idx3 + 1] = a[idx1 + 3];
t[idx4] = a[idx1 + 4];
t[idx4 + 1] = a[idx1 + 5];
t[idx5] = a[idx1 + 6];
t[idx5 + 1] = a[idx1 + 7];
}
fftRows.complexInverse(t, 0, scale);
fftRows.complexInverse(t, 2 * rows, scale);
fftRows.complexInverse(t, 4 * rows, scale);
fftRows.complexInverse(t, 6 * rows, scale);
for (int r = 0; r < rows; r++) {
idx1 = r * columns + c;
idx2 = 2 * r;
idx3 = 2 * rows + 2 * r;
idx4 = idx3 + 2 * rows;
idx5 = idx4 + 2 * rows;
a[idx1] = t[idx2];
a[idx1 + 1] = t[idx2 + 1];
a[idx1 + 2] = t[idx3];
a[idx1 + 3] = t[idx3 + 1];
a[idx1 + 4] = t[idx4];
a[idx1 + 5] = t[idx4 + 1];
a[idx1 + 6] = t[idx5];
a[idx1 + 7] = t[idx5 + 1];
}
}
} else if (columns == 4 * nthreads) {
for (int r = 0; r < rows; r++) {
idx1 = r * columns + 4 * n0;
idx2 = 2 * r;
idx3 = 2 * rows + 2 * r;
t[idx2] = a[idx1];
t[idx2 + 1] = a[idx1 + 1];
t[idx3] = a[idx1 + 2];
t[idx3 + 1] = a[idx1 + 3];
}
fftRows.complexInverse(t, 0, scale);
fftRows.complexInverse(t, 2 * rows, scale);
for (int r = 0; r < rows; r++) {
idx1 = r * columns + 4 * n0;
idx2 = 2 * r;
idx3 = 2 * rows + 2 * r;
a[idx1] = t[idx2];
a[idx1 + 1] = t[idx2 + 1];
a[idx1 + 2] = t[idx3];
a[idx1 + 3] = t[idx3 + 1];
}
} else if (columns == 2 * nthreads) {
for (int r = 0; r < rows; r++) {
idx1 = r * columns + 2 * n0;
idx2 = 2 * r;
t[idx2] = a[idx1];
t[idx2 + 1] = a[idx1 + 1];
}
fftRows.complexInverse(t, 0, scale);
for (int r = 0; r < rows; r++) {
idx1 = r * columns + 2 * n0;
idx2 = 2 * r;
a[idx1] = t[idx2];
a[idx1 + 1] = t[idx2 + 1];
}
}
}
}
});
}
ConcurrencyUtils.waitForCompletion(futures);
}
private void cdft2d_subth(final int isgn, final DoubleLargeArray a, final boolean scale)
{
int nthread = (int) Math.min(columnsl / 2, ConcurrencyUtils.getNumberOfThreads());
long nt = 8 * rowsl;
if (columnsl == 4) {
nt >>= 1;
} else if (columnsl < 4) {
nt >>= 2;
}
final long ntf = nt;
Future[] futures = new Future[nthread];
final int nthreads = nthread;
for (int i = 0; i < nthread; i++) {
final long n0 = i;
futures[i] = ConcurrencyUtils.submit(new Runnable()
{
public void run()
{
long idx1, idx2, idx3, idx4, idx5;
DoubleLargeArray t = new DoubleLargeArray(ntf, false);
if (isgn == -1) {
if (columnsl > 4 * nthreads) {
for (long c = 8 * n0; c < columnsl; c += 8 * nthreads) {
for (long r = 0; r < rowsl; r++) {
idx1 = r * columnsl + c;
idx2 = 2 * r;
idx3 = 2 * rowsl + 2 * r;
idx4 = idx3 + 2 * rowsl;
idx5 = idx4 + 2 * rowsl;
t.setDouble(idx2, a.getDouble(idx1));
t.setDouble(idx2 + 1, a.getDouble(idx1 + 1));
t.setDouble(idx3, a.getDouble(idx1 + 2));
t.setDouble(idx3 + 1, a.getDouble(idx1 + 3));
t.setDouble(idx4, a.getDouble(idx1 + 4));
t.setDouble(idx4 + 1, a.getDouble(idx1 + 5));
t.setDouble(idx5, a.getDouble(idx1 + 6));
t.setDouble(idx5 + 1, a.getDouble(idx1 + 7));
}
fftRows.complexForward(t, 0);
fftRows.complexForward(t, 2 * rowsl);
fftRows.complexForward(t, 4 * rowsl);
fftRows.complexForward(t, 6 * rowsl);
for (long r = 0; r < rowsl; r++) {
idx1 = r * columnsl + c;
idx2 = 2 * r;
idx3 = 2 * rowsl + 2 * r;
idx4 = idx3 + 2 * rowsl;
idx5 = idx4 + 2 * rowsl;
a.setDouble(idx1, t.getDouble(idx2));
a.setDouble(idx1 + 1, t.getDouble(idx2 + 1));
a.setDouble(idx1 + 2, t.getDouble(idx3));
a.setDouble(idx1 + 3, t.getDouble(idx3 + 1));
a.setDouble(idx1 + 4, t.getDouble(idx4));
a.setDouble(idx1 + 5, t.getDouble(idx4 + 1));
a.setDouble(idx1 + 6, t.getDouble(idx5));
a.setDouble(idx1 + 7, t.getDouble(idx5 + 1));
}
}
} else if (columnsl == 4 * nthreads) {
for (long r = 0; r < rowsl; r++) {
idx1 = r * columnsl + 4 * n0;
idx2 = 2 * r;
idx3 = 2 * rowsl + 2 * r;
t.setDouble(idx2, a.getDouble(idx1));
t.setDouble(idx2 + 1, a.getDouble(idx1 + 1));
t.setDouble(idx3, a.getDouble(idx1 + 2));
t.setDouble(idx3 + 1, a.getDouble(idx1 + 3));
}
fftRows.complexForward(t, 0);
fftRows.complexForward(t, 2 * rowsl);
for (long r = 0; r < rowsl; r++) {
idx1 = r * columnsl + 4 * n0;
idx2 = 2 * r;
idx3 = 2 * rowsl + 2 * r;
a.setDouble(idx1, t.getDouble(idx2));
a.setDouble(idx1 + 1, t.getDouble(idx2 + 1));
a.setDouble(idx1 + 2, t.getDouble(idx3));
a.setDouble(idx1 + 3, t.getDouble(idx3 + 1));
}
} else if (columnsl == 2 * nthreads) {
for (long r = 0; r < rowsl; r++) {
idx1 = r * columnsl + 2 * n0;
idx2 = 2 * r;
t.setDouble(idx2, a.getDouble(idx1));
t.setDouble(idx2 + 1, a.getDouble(idx1 + 1));
}
fftRows.complexForward(t, 0);
for (long r = 0; r < rowsl; r++) {
idx1 = r * columnsl + 2 * n0;
idx2 = 2 * r;
a.setDouble(idx1, t.getDouble(idx2));
a.setDouble(idx1 + 1, t.getDouble(idx2 + 1));
}
}
} else {
if (columnsl > 4 * nthreads) {
for (long c = 8 * n0; c < columnsl; c += 8 * nthreads) {
for (long r = 0; r < rowsl; r++) {
idx1 = r * columnsl + c;
idx2 = 2 * r;
idx3 = 2 * rowsl + 2 * r;
idx4 = idx3 + 2 * rowsl;
idx5 = idx4 + 2 * rowsl;
t.setDouble(idx2, a.getDouble(idx1));
t.setDouble(idx2 + 1, a.getDouble(idx1 + 1));
t.setDouble(idx3, a.getDouble(idx1 + 2));
t.setDouble(idx3 + 1, a.getDouble(idx1 + 3));
t.setDouble(idx4, a.getDouble(idx1 + 4));
t.setDouble(idx4 + 1, a.getDouble(idx1 + 5));
t.setDouble(idx5, a.getDouble(idx1 + 6));
t.setDouble(idx5 + 1, a.getDouble(idx1 + 7));
}
fftRows.complexInverse(t, 0, scale);
fftRows.complexInverse(t, 2 * rowsl, scale);
fftRows.complexInverse(t, 4 * rowsl, scale);
fftRows.complexInverse(t, 6 * rowsl, scale);
for (long r = 0; r < rowsl; r++) {
idx1 = r * columnsl + c;
idx2 = 2 * r;
idx3 = 2 * rowsl + 2 * r;
idx4 = idx3 + 2 * rowsl;
idx5 = idx4 + 2 * rowsl;
a.setDouble(idx1, t.getDouble(idx2));
a.setDouble(idx1 + 1, t.getDouble(idx2 + 1));
a.setDouble(idx1 + 2, t.getDouble(idx3));
a.setDouble(idx1 + 3, t.getDouble(idx3 + 1));
a.setDouble(idx1 + 4, t.getDouble(idx4));
a.setDouble(idx1 + 5, t.getDouble(idx4 + 1));
a.setDouble(idx1 + 6, t.getDouble(idx5));
a.setDouble(idx1 + 7, t.getDouble(idx5 + 1));
}
}
} else if (columnsl == 4 * nthreads) {
for (long r = 0; r < rowsl; r++) {
idx1 = r * columnsl + 4 * n0;
idx2 = 2 * r;
idx3 = 2 * rowsl + 2 * r;
t.setDouble(idx2, a.getDouble(idx1));
t.setDouble(idx2 + 1, a.getDouble(idx1 + 1));
t.setDouble(idx3, a.getDouble(idx1 + 2));
t.setDouble(idx3 + 1, a.getDouble(idx1 + 3));
}
fftRows.complexInverse(t, 0, scale);
fftRows.complexInverse(t, 2 * rowsl, scale);
for (long r = 0; r < rowsl; r++) {
idx1 = r * columnsl + 4 * n0;
idx2 = 2 * r;
idx3 = 2 * rowsl + 2 * r;
a.setDouble(idx1, t.getDouble(idx2));
a.setDouble(idx1 + 1, t.getDouble(idx2 + 1));
a.setDouble(idx1 + 2, t.getDouble(idx3));
a.setDouble(idx1 + 3, t.getDouble(idx3 + 1));
}
} else if (columnsl == 2 * nthreads) {
for (long r = 0; r < rowsl; r++) {
idx1 = r * columnsl + 2 * n0;
idx2 = 2 * r;
t.setDouble(idx2, a.getDouble(idx1));
t.setDouble(idx2 + 1, a.getDouble(idx1 + 1));
}
fftRows.complexInverse(t, 0, scale);
for (long r = 0; r < rowsl; r++) {
idx1 = r * columnsl + 2 * n0;
idx2 = 2 * r;
a.setDouble(idx1, t.getDouble(idx2));
a.setDouble(idx1 + 1, t.getDouble(idx2 + 1));
}
}
}
}
});
}
ConcurrencyUtils.waitForCompletion(futures);
}
private void cdft2d_subth(final int isgn, final double[][] a, final boolean scale)
{
int nthread = Math.min(columns / 2, ConcurrencyUtils.getNumberOfThreads());
int nt = 8 * rows;
if (columns == 4) {
nt >>= 1;
} else if (columns < 4) {
nt >>= 2;
}
final int ntf = nt;
Future[] futures = new Future[nthread];
final int nthreads = nthread;
for (int i = 0; i < nthreads; i++) {
final int n0 = i;
futures[i] = ConcurrencyUtils.submit(new Runnable()
{
public void run()
{
int idx2, idx3, idx4, idx5;
double[] t = new double[ntf];
if (isgn == -1) {
if (columns > 4 * nthreads) {
for (int c = 8 * n0; c < columns; c += 8 * nthreads) {
for (int r = 0; r < rows; r++) {
idx2 = 2 * r;
idx3 = 2 * rows + 2 * r;
idx4 = idx3 + 2 * rows;
idx5 = idx4 + 2 * rows;
t[idx2] = a[r][c];
t[idx2 + 1] = a[r][c + 1];
t[idx3] = a[r][c + 2];
t[idx3 + 1] = a[r][c + 3];
t[idx4] = a[r][c + 4];
t[idx4 + 1] = a[r][c + 5];
t[idx5] = a[r][c + 6];
t[idx5 + 1] = a[r][c + 7];
}
fftRows.complexForward(t, 0);
fftRows.complexForward(t, 2 * rows);
fftRows.complexForward(t, 4 * rows);
fftRows.complexForward(t, 6 * rows);
for (int r = 0; r < rows; r++) {
idx2 = 2 * r;
idx3 = 2 * rows + 2 * r;
idx4 = idx3 + 2 * rows;
idx5 = idx4 + 2 * rows;
a[r][c] = t[idx2];
a[r][c + 1] = t[idx2 + 1];
a[r][c + 2] = t[idx3];
a[r][c + 3] = t[idx3 + 1];
a[r][c + 4] = t[idx4];
a[r][c + 5] = t[idx4 + 1];
a[r][c + 6] = t[idx5];
a[r][c + 7] = t[idx5 + 1];
}
}
} else if (columns == 4 * nthreads) {
for (int r = 0; r < rows; r++) {
idx2 = 2 * r;
idx3 = 2 * rows + 2 * r;
t[idx2] = a[r][4 * n0];
t[idx2 + 1] = a[r][4 * n0 + 1];
t[idx3] = a[r][4 * n0 + 2];
t[idx3 + 1] = a[r][4 * n0 + 3];
}
fftRows.complexForward(t, 0);
fftRows.complexForward(t, 2 * rows);
for (int r = 0; r < rows; r++) {
idx2 = 2 * r;
idx3 = 2 * rows + 2 * r;
a[r][4 * n0] = t[idx2];
a[r][4 * n0 + 1] = t[idx2 + 1];
a[r][4 * n0 + 2] = t[idx3];
a[r][4 * n0 + 3] = t[idx3 + 1];
}
} else if (columns == 2 * nthreads) {
for (int r = 0; r < rows; r++) {
idx2 = 2 * r;
t[idx2] = a[r][2 * n0];
t[idx2 + 1] = a[r][2 * n0 + 1];
}
fftRows.complexForward(t, 0);
for (int r = 0; r < rows; r++) {
idx2 = 2 * r;
a[r][2 * n0] = t[idx2];
a[r][2 * n0 + 1] = t[idx2 + 1];
}
}
} else {
if (columns > 4 * nthreads) {
for (int c = 8 * n0; c < columns; c += 8 * nthreads) {
for (int r = 0; r < rows; r++) {
idx2 = 2 * r;
idx3 = 2 * rows + 2 * r;
idx4 = idx3 + 2 * rows;
idx5 = idx4 + 2 * rows;
t[idx2] = a[r][c];
t[idx2 + 1] = a[r][c + 1];
t[idx3] = a[r][c + 2];
t[idx3 + 1] = a[r][c + 3];
t[idx4] = a[r][c + 4];
t[idx4 + 1] = a[r][c + 5];
t[idx5] = a[r][c + 6];
t[idx5 + 1] = a[r][c + 7];
}
fftRows.complexInverse(t, 0, scale);
fftRows.complexInverse(t, 2 * rows, scale);
fftRows.complexInverse(t, 4 * rows, scale);
fftRows.complexInverse(t, 6 * rows, scale);
for (int r = 0; r < rows; r++) {
idx2 = 2 * r;
idx3 = 2 * rows + 2 * r;
idx4 = idx3 + 2 * rows;
idx5 = idx4 + 2 * rows;
a[r][c] = t[idx2];
a[r][c + 1] = t[idx2 + 1];
a[r][c + 2] = t[idx3];
a[r][c + 3] = t[idx3 + 1];
a[r][c + 4] = t[idx4];
a[r][c + 5] = t[idx4 + 1];
a[r][c + 6] = t[idx5];
a[r][c + 7] = t[idx5 + 1];
}
}
} else if (columns == 4 * nthreads) {
for (int r = 0; r < rows; r++) {
idx2 = 2 * r;
idx3 = 2 * rows + 2 * r;
t[idx2] = a[r][4 * n0];
t[idx2 + 1] = a[r][4 * n0 + 1];
t[idx3] = a[r][4 * n0 + 2];
t[idx3 + 1] = a[r][4 * n0 + 3];
}
fftRows.complexInverse(t, 0, scale);
fftRows.complexInverse(t, 2 * rows, scale);
for (int r = 0; r < rows; r++) {
idx2 = 2 * r;
idx3 = 2 * rows + 2 * r;
a[r][4 * n0] = t[idx2];
a[r][4 * n0 + 1] = t[idx2 + 1];
a[r][4 * n0 + 2] = t[idx3];
a[r][4 * n0 + 3] = t[idx3 + 1];
}
} else if (columns == 2 * nthreads) {
for (int r = 0; r < rows; r++) {
idx2 = 2 * r;
t[idx2] = a[r][2 * n0];
t[idx2 + 1] = a[r][2 * n0 + 1];
}
fftRows.complexInverse(t, 0, scale);
for (int r = 0; r < rows; r++) {
idx2 = 2 * r;
a[r][2 * n0] = t[idx2];
a[r][2 * n0 + 1] = t[idx2 + 1];
}
}
}
}
});
}
ConcurrencyUtils.waitForCompletion(futures);
}
private void fillSymmetric(final double[] a)
{
final int twon2 = 2 * columns;
int idx1, idx2, idx3, idx4;
int n1d2 = rows / 2;
for (int r = (rows - 1); r >= 1; r--) {
idx1 = r * columns;
idx2 = 2 * idx1;
for (int c = 0; c < columns; c += 2) {
a[idx2 + c] = a[idx1 + c];
a[idx1 + c] = 0;
a[idx2 + c + 1] = a[idx1 + c + 1];
a[idx1 + c + 1] = 0;
}
}
int nthreads = ConcurrencyUtils.getNumberOfThreads();
if ((nthreads > 1) && useThreads && (n1d2 >= nthreads)) {
Future[] futures = new Future[nthreads];
int l1k = n1d2 / nthreads;
final int newn2 = 2 * columns;
for (int i = 0; i < nthreads; i++) {
final int l1offa, l1stopa, l2offa, l2stopa;
if (i == 0)
l1offa = i * l1k + 1;
else {
l1offa = i * l1k;
}
l1stopa = i * l1k + l1k;
l2offa = i * l1k;
if (i == nthreads - 1) {
l2stopa = i * l1k + l1k + 1;
} else {
l2stopa = i * l1k + l1k;
}
futures[i] = ConcurrencyUtils.submit(new Runnable()
{
public void run()
{
int idx1, idx2, idx3, idx4;
for (int r = l1offa; r < l1stopa; r++) {
idx1 = r * newn2;
idx2 = (rows - r) * newn2;
idx3 = idx1 + columns;
a[idx3] = a[idx2 + 1];
a[idx3 + 1] = -a[idx2];
}
for (int r = l1offa; r < l1stopa; r++) {
idx1 = r * newn2;
idx3 = (rows - r + 1) * newn2;
for (int c = columns + 2; c < newn2; c += 2) {
idx2 = idx3 - c;
idx4 = idx1 + c;
a[idx4] = a[idx2];
a[idx4 + 1] = -a[idx2 + 1];
}
}
for (int r = l2offa; r < l2stopa; r++) {
idx3 = ((rows - r) % rows) * newn2;
idx4 = r * newn2;
for (int c = 0; c < newn2; c += 2) {
idx1 = idx3 + (newn2 - c) % newn2;
idx2 = idx4 + c;
a[idx1] = a[idx2];
a[idx1 + 1] = -a[idx2 + 1];
}
}
}
});
}
ConcurrencyUtils.waitForCompletion(futures);
} else {
for (int r = 1; r < n1d2; r++) {
idx2 = r * twon2;
idx3 = (rows - r) * twon2;
a[idx2 + columns] = a[idx3 + 1];
a[idx2 + columns + 1] = -a[idx3];
}
for (int r = 1; r < n1d2; r++) {
idx2 = r * twon2;
idx3 = (rows - r + 1) * twon2;
for (int c = columns + 2; c < twon2; c += 2) {
a[idx2 + c] = a[idx3 - c];
a[idx2 + c + 1] = -a[idx3 - c + 1];
}
}
for (int r = 0; r <= rows / 2; r++) {
idx1 = r * twon2;
idx4 = ((rows - r) % rows) * twon2;
for (int c = 0; c < twon2; c += 2) {
idx2 = idx1 + c;
idx3 = idx4 + (twon2 - c) % twon2;
a[idx3] = a[idx2];
a[idx3 + 1] = -a[idx2 + 1];
}
}
}
a[columns] = -a[1];
a[1] = 0;
idx1 = n1d2 * twon2;
a[idx1 + columns] = -a[idx1 + 1];
a[idx1 + 1] = 0;
a[idx1 + columns + 1] = 0;
}
private void fillSymmetric(final DoubleLargeArray a)
{
final long twon2 = 2 * columnsl;
long idx1, idx2, idx3, idx4;
long n1d2 = rowsl / 2;
for (long r = (rowsl - 1); r >= 1; r--) {
idx1 = r * columnsl;
idx2 = 2 * idx1;
for (long c = 0; c < columnsl; c += 2) {
a.setDouble(idx2 + c, a.getDouble(idx1 + c));
a.setDouble(idx1 + c, 0);
a.setDouble(idx2 + c + 1, a.getDouble(idx1 + c + 1));
a.setDouble(idx1 + c + 1, 0);
}
}
int nthreads = ConcurrencyUtils.getNumberOfThreads();
if ((nthreads > 1) && useThreads && (n1d2 >= nthreads)) {
Future[] futures = new Future[nthreads];
long l1k = n1d2 / nthreads;
final long newn2 = 2 * columnsl;
for (int i = 0; i < nthreads; i++) {
final long l1offa, l1stopa, l2offa, l2stopa;
if (i == 0)
l1offa = i * l1k + 1;
else {
l1offa = i * l1k;
}
l1stopa = i * l1k + l1k;
l2offa = i * l1k;
if (i == nthreads - 1) {
l2stopa = i * l1k + l1k + 1;
} else {
l2stopa = i * l1k + l1k;
}
futures[i] = ConcurrencyUtils.submit(new Runnable()
{
public void run()
{
long idx1, idx2, idx3, idx4;
for (long r = l1offa; r < l1stopa; r++) {
idx1 = r * newn2;
idx2 = (rowsl - r) * newn2;
idx3 = idx1 + columnsl;
a.setDouble(idx3, a.getDouble(idx2 + 1));
a.setDouble(idx3 + 1, -a.getDouble(idx2));
}
for (long r = l1offa; r < l1stopa; r++) {
idx1 = r * newn2;
idx3 = (rowsl - r + 1) * newn2;
for (long c = columnsl + 2; c < newn2; c += 2) {
idx2 = idx3 - c;
idx4 = idx1 + c;
a.setDouble(idx4, a.getDouble(idx2));
a.setDouble(idx4 + 1, -a.getDouble(idx2 + 1));
}
}
for (long r = l2offa; r < l2stopa; r++) {
idx3 = ((rowsl - r) % rowsl) * newn2;
idx4 = r * newn2;
for (long c = 0; c < newn2; c += 2) {
idx1 = idx3 + (newn2 - c) % newn2;
idx2 = idx4 + c;
a.setDouble(idx1, a.getDouble(idx2));
a.setDouble(idx1 + 1, -a.getDouble(idx2 + 1));
}
}
}
});
}
ConcurrencyUtils.waitForCompletion(futures);
} else {
for (long r = 1; r < n1d2; r++) {
idx2 = r * twon2;
idx3 = (rowsl - r) * twon2;
a.setDouble(idx2 + columnsl, a.getDouble(idx3 + 1));
a.setDouble(idx2 + columnsl + 1, -a.getDouble(idx3));
}
for (long r = 1; r < n1d2; r++) {
idx2 = r * twon2;
idx3 = (rowsl - r + 1) * twon2;
for (long c = columnsl + 2; c < twon2; c += 2) {
a.setDouble(idx2 + c, a.getDouble(idx3 - c));
a.setDouble(idx2 + c + 1, -a.getDouble(idx3 - c + 1));
}
}
for (long r = 0; r <= rowsl / 2; r++) {
idx1 = r * twon2;
idx4 = ((rowsl - r) % rowsl) * twon2;
for (long c = 0; c < twon2; c += 2) {
idx2 = idx1 + c;
idx3 = idx4 + (twon2 - c) % twon2;
a.setDouble(idx3, a.getDouble(idx2));
a.setDouble(idx3 + 1, -a.getDouble(idx2 + 1));
}
}
}
a.setDouble(columnsl, -a.getDouble(1));
a.setDouble(1, 0);
idx1 = n1d2 * twon2;
a.setDouble(idx1 + columnsl, -a.getDouble(idx1 + 1));
a.setDouble(idx1 + 1, 0);
a.setDouble(idx1 + columnsl + 1, 0);
}
private void fillSymmetric(final double[][] a)
{
final int newn2 = 2 * columns;
int n1d2 = rows / 2;
int nthreads = ConcurrencyUtils.getNumberOfThreads();
if ((nthreads > 1) && useThreads && (n1d2 >= nthreads)) {
Future[] futures = new Future[nthreads];
int l1k = n1d2 / nthreads;
for (int i = 0; i < nthreads; i++) {
final int l1offa, l1stopa, l2offa, l2stopa;
if (i == 0)
l1offa = i * l1k + 1;
else {
l1offa = i * l1k;
}
l1stopa = i * l1k + l1k;
l2offa = i * l1k;
if (i == nthreads - 1) {
l2stopa = i * l1k + l1k + 1;
} else {
l2stopa = i * l1k + l1k;
}
futures[i] = ConcurrencyUtils.submit(new Runnable()
{
public void run()
{
int idx1, idx2;
for (int r = l1offa; r < l1stopa; r++) {
idx1 = rows - r;
a[r][columns] = a[idx1][1];
a[r][columns + 1] = -a[idx1][0];
}
for (int r = l1offa; r < l1stopa; r++) {
idx1 = rows - r;
for (int c = columns + 2; c < newn2; c += 2) {
idx2 = newn2 - c;
a[r][c] = a[idx1][idx2];
a[r][c + 1] = -a[idx1][idx2 + 1];
}
}
for (int r = l2offa; r < l2stopa; r++) {
idx1 = (rows - r) % rows;
for (int c = 0; c < newn2; c = c + 2) {
idx2 = (newn2 - c) % newn2;
a[idx1][idx2] = a[r][c];
a[idx1][idx2 + 1] = -a[r][c + 1];
}
}
}
});
}
ConcurrencyUtils.waitForCompletion(futures);
} else {
for (int r = 1; r < n1d2; r++) {
int idx1 = rows - r;
a[r][columns] = a[idx1][1];
a[r][columns + 1] = -a[idx1][0];
}
for (int r = 1; r < n1d2; r++) {
int idx1 = rows - r;
for (int c = columns + 2; c < newn2; c += 2) {
int idx2 = newn2 - c;
a[r][c] = a[idx1][idx2];
a[r][c + 1] = -a[idx1][idx2 + 1];
}
}
for (int r = 0; r <= rows / 2; r++) {
int idx1 = (rows - r) % rows;
for (int c = 0; c < newn2; c += 2) {
int idx2 = (newn2 - c) % newn2;
a[idx1][idx2] = a[r][c];
a[idx1][idx2 + 1] = -a[r][c + 1];
}
}
}
a[0][columns] = -a[0][1];
a[0][1] = 0;
a[n1d2][columns] = -a[n1d2][1];
a[n1d2][1] = 0;
a[n1d2][columns + 1] = 0;
}
}
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