org.jtransforms.dht.DoubleDHT_2D Maven / Gradle / Ivy
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* JTransforms
* Copyright (c) 2007 onward, Piotr Wendykier
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*
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package org.jtransforms.dht;
import java.util.concurrent.Future;
import org.jtransforms.utils.ConcurrencyUtils;
import pl.edu.icm.jlargearrays.DoubleLargeArray;
/**
* Computes 2D Discrete Hartley Transform (DHT) of real, double precision data.
* The sizes of both dimensions can be arbitrary numbers. This is a parallel
* implementation optimized for SMP systems.
*
* Part of 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 DoubleDHT_2D {
private int rows;
private int columns;
private long rowsl;
private long columnsl;
private DoubleDHT_1D dhtColumns, dhtRows;
private boolean isPowerOfTwo = false;
private boolean useThreads = false;
/**
* Creates new instance of DoubleDHT_2D.
*
* @param rows number of rows
* @param columns number of columns
*/
public DoubleDHT_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));
}
dhtRows = new DoubleDHT_1D(rows);
if (rows == columns) {
dhtColumns = dhtRows;
} else {
dhtColumns = new DoubleDHT_1D(columns);
}
ConcurrencyUtils.setLargeArraysBeginN(largeArraysBenginN);
}
/**
* Computes 2D real, forward DHT leaving the result in a. The
* data is stored in 1D array in row-major order.
*
* @param a data to transform
*/
public void forward(final double[] a) {
int nthreads = ConcurrencyUtils.getNumberOfThreads();
if (isPowerOfTwo) {
if ((nthreads > 1) && useThreads) {
ddxt2d_subth(-1, a, true);
ddxt2d0_subth(-1, a, true);
} else {
ddxt2d_sub(-1, a, true);
for (int i = 0; i < rows; i++) {
dhtColumns.forward(a, i * columns);
}
}
DoubleDHT_2D.this.yTransform(a);
} 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 i = firstRow; i < lastRow; i++) {
dhtColumns.forward(a, i * columns);
}
}
});
}
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[rows];
for (int c = firstColumn; c < lastColumn; c++) {
for (int r = 0; r < rows; r++) {
temp[r] = a[r * columns + c];
}
dhtRows.forward(temp);
for (int r = 0; r < rows; r++) {
a[r * columns + c] = temp[r];
}
}
}
});
}
ConcurrencyUtils.waitForCompletion(futures);
} else {
for (int i = 0; i < rows; i++) {
dhtColumns.forward(a, i * columns);
}
double[] temp = new double[rows];
for (int c = 0; c < columns; c++) {
for (int r = 0; r < rows; r++) {
temp[r] = a[r * columns + c];
}
dhtRows.forward(temp);
for (int r = 0; r < rows; r++) {
a[r * columns + c] = temp[r];
}
}
}
yTransform(a);
}
}
/**
* Computes 2D real, forward DHT leaving the result in a. The
* data is stored in 1D array in row-major order.
*
* @param a data to transform
*/
public void forward(final DoubleLargeArray a) {
int nthreads = ConcurrencyUtils.getNumberOfThreads();
if (isPowerOfTwo) {
if ((nthreads > 1) && useThreads) {
ddxt2d_subth(-1, a, true);
ddxt2d0_subth(-1, a, true);
} else {
ddxt2d_sub(-1, a, true);
for (long i = 0; i < rowsl; i++) {
dhtColumns.forward(a, i * columnsl);
}
}
yTransform(a);
} else {
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 i = firstRow; i < lastRow; i++) {
dhtColumns.forward(a, i * columnsl);
}
}
});
}
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(rowsl, false);
for (long c = firstColumn; c < lastColumn; c++) {
for (long r = 0; r < rowsl; r++) {
temp.setDouble(r, a.getDouble(r * columnsl + c));
}
dhtRows.forward(temp);
for (long r = 0; r < rowsl; r++) {
a.setDouble(r * columnsl + c, temp.getDouble(r));
}
}
}
});
}
ConcurrencyUtils.waitForCompletion(futures);
} else {
for (long i = 0; i < rowsl; i++) {
dhtColumns.forward(a, i * columnsl);
}
DoubleLargeArray temp = new DoubleLargeArray(rowsl, false);
for (long c = 0; c < columnsl; c++) {
for (long r = 0; r < rowsl; r++) {
temp.setDouble(r, a.getDouble(r * columnsl + c));
}
dhtRows.forward(temp);
for (long r = 0; r < rowsl; r++) {
a.setDouble(r * columnsl + c, temp.getDouble(r));
}
}
}
yTransform(a);
}
}
/**
* Computes 2D real, forward DHT leaving the result in a. The
* data is stored in 2D array.
*
* @param a data to transform
*/
public void forward(final double[][] a) {
int nthreads = ConcurrencyUtils.getNumberOfThreads();
if (isPowerOfTwo) {
if ((nthreads > 1) && useThreads) {
ddxt2d_subth(-1, a, true);
ddxt2d0_subth(-1, a, true);
} else {
ddxt2d_sub(-1, a, true);
for (int i = 0; i < rows; i++) {
dhtColumns.forward(a[i]);
}
}
yTransform(a);
} 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 i = firstRow; i < lastRow; i++) {
dhtColumns.forward(a[i]);
}
}
});
}
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[rows];
for (int c = firstColumn; c < lastColumn; c++) {
for (int r = 0; r < rows; r++) {
temp[r] = a[r][c];
}
dhtRows.forward(temp);
for (int r = 0; r < rows; r++) {
a[r][c] = temp[r];
}
}
}
});
}
ConcurrencyUtils.waitForCompletion(futures);
} else {
for (int i = 0; i < rows; i++) {
dhtColumns.forward(a[i]);
}
double[] temp = new double[rows];
for (int c = 0; c < columns; c++) {
for (int r = 0; r < rows; r++) {
temp[r] = a[r][c];
}
dhtRows.forward(temp);
for (int r = 0; r < rows; r++) {
a[r][c] = temp[r];
}
}
}
yTransform(a);
}
}
/**
* Computes 2D real, inverse DHT leaving the result in a. The
* data is stored in 1D array in row-major order.
*
* @param a data to transform
* @param scale if true then scaling is performed
*/
public void inverse(final double[] a, final boolean scale) {
int nthreads = ConcurrencyUtils.getNumberOfThreads();
if (isPowerOfTwo) {
if ((nthreads > 1) && useThreads) {
ddxt2d_subth(1, a, scale);
ddxt2d0_subth(1, a, scale);
} else {
ddxt2d_sub(1, a, scale);
for (int i = 0; i < rows; i++) {
dhtColumns.inverse(a, i * columns, scale);
}
}
yTransform(a);
} 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 i = firstRow; i < lastRow; i++) {
dhtColumns.inverse(a, i * columns, 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[rows];
for (int c = firstColumn; c < lastColumn; c++) {
for (int r = 0; r < rows; r++) {
temp[r] = a[r * columns + c];
}
dhtRows.inverse(temp, scale);
for (int r = 0; r < rows; r++) {
a[r * columns + c] = temp[r];
}
}
}
});
}
ConcurrencyUtils.waitForCompletion(futures);
} else {
for (int i = 0; i < rows; i++) {
dhtColumns.inverse(a, i * columns, scale);
}
double[] temp = new double[rows];
for (int c = 0; c < columns; c++) {
for (int r = 0; r < rows; r++) {
temp[r] = a[r * columns + c];
}
dhtRows.inverse(temp, scale);
for (int r = 0; r < rows; r++) {
a[r * columns + c] = temp[r];
}
}
}
yTransform(a);
}
}
/**
* Computes 2D real, inverse DHT leaving the result in a. The
* data is stored in 1D array in row-major order.
*
* @param a data to transform
* @param scale if true then scaling is performed
*/
public void inverse(final DoubleLargeArray a, final boolean scale) {
int nthreads = ConcurrencyUtils.getNumberOfThreads();
if (isPowerOfTwo) {
if ((nthreads > 1) && useThreads) {
ddxt2d_subth(1, a, scale);
ddxt2d0_subth(1, a, scale);
} else {
ddxt2d_sub(1, a, scale);
for (long i = 0; i < rowsl; i++) {
dhtColumns.inverse(a, i * columnsl, scale);
}
}
yTransform(a);
} else {
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 i = firstRow; i < lastRow; i++) {
dhtColumns.inverse(a, i * columnsl, 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(rowsl, false);
for (long c = firstColumn; c < lastColumn; c++) {
for (long r = 0; r < rowsl; r++) {
temp.setDouble(r, a.getDouble(r * columnsl + c));
}
dhtRows.inverse(temp, scale);
for (long r = 0; r < rowsl; r++) {
a.setDouble(r * columnsl + c, temp.getDouble(r));
}
}
}
});
}
ConcurrencyUtils.waitForCompletion(futures);
} else {
for (long i = 0; i < rowsl; i++) {
dhtColumns.inverse(a, i * columnsl, scale);
}
DoubleLargeArray temp = new DoubleLargeArray(rowsl, false);
for (long c = 0; c < columnsl; c++) {
for (long r = 0; r < rowsl; r++) {
temp.setDouble(r, a.getDouble(r * columnsl + c));
}
dhtRows.inverse(temp, scale);
for (long r = 0; r < rowsl; r++) {
a.setDouble(r * columnsl + c, temp.getDouble(r));
}
}
}
yTransform(a);
}
}
/**
* Computes 2D real, inverse DHT leaving the result in a. The
* data is stored in 2D array.
*
* @param a data to transform
* @param scale if true then scaling is performed
*/
public void inverse(final double[][] a, final boolean scale) {
int nthreads = ConcurrencyUtils.getNumberOfThreads();
if (isPowerOfTwo) {
if ((nthreads > 1) && useThreads) {
ddxt2d_subth(1, a, scale);
ddxt2d0_subth(1, a, scale);
} else {
ddxt2d_sub(1, a, scale);
for (int i = 0; i < rows; i++) {
dhtColumns.inverse(a[i], scale);
}
}
yTransform(a);
} 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 i = firstRow; i < lastRow; i++) {
dhtColumns.inverse(a[i], 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[rows];
for (int c = firstColumn; c < lastColumn; c++) {
for (int r = 0; r < rows; r++) {
temp[r] = a[r][c];
}
dhtRows.inverse(temp, scale);
for (int r = 0; r < rows; r++) {
a[r][c] = temp[r];
}
}
}
});
}
ConcurrencyUtils.waitForCompletion(futures);
} else {
for (int i = 0; i < rows; i++) {
dhtColumns.inverse(a[i], scale);
}
double[] temp = new double[rows];
for (int c = 0; c < columns; c++) {
for (int r = 0; r < rows; r++) {
temp[r] = a[r][c];
}
dhtRows.inverse(temp, scale);
for (int r = 0; r < rows; r++) {
a[r][c] = temp[r];
}
}
}
yTransform(a);
}
}
private void ddxt2d_subth(final int isgn, final double[] a, final boolean scale) {
int nthread = Math.min(columns, ConcurrencyUtils.getNumberOfThreads());
int nt = 4 * rows;
if (columns == 2) {
nt >>= 1;
} else if (columns < 2) {
nt >>= 2;
}
final int ntf = nt;
final int nthreads = nthread;
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() {
int idx1, idx2;
double[] t = new double[ntf];
if (columns > 2) {
if (isgn == -1) {
for (int c = 4 * n0; c < columns; c += 4 * nthreads) {
for (int r = 0; r < rows; r++) {
idx1 = r * columns + c;
idx2 = rows + r;
t[r] = a[idx1];
t[idx2] = a[idx1 + 1];
t[idx2 + rows] = a[idx1 + 2];
t[idx2 + 2 * rows] = a[idx1 + 3];
}
dhtRows.forward(t, 0);
dhtRows.forward(t, rows);
dhtRows.forward(t, 2 * rows);
dhtRows.forward(t, 3 * rows);
for (int r = 0; r < rows; r++) {
idx1 = r * columns + c;
idx2 = rows + r;
a[idx1] = t[r];
a[idx1 + 1] = t[idx2];
a[idx1 + 2] = t[idx2 + rows];
a[idx1 + 3] = t[idx2 + 2 * rows];
}
}
} else {
for (int c = 4 * n0; c < columns; c += 4 * nthreads) {
for (int r = 0; r < rows; r++) {
idx1 = r * columns + c;
idx2 = rows + r;
t[r] = a[idx1];
t[idx2] = a[idx1 + 1];
t[idx2 + rows] = a[idx1 + 2];
t[idx2 + 2 * rows] = a[idx1 + 3];
}
dhtRows.inverse(t, 0, scale);
dhtRows.inverse(t, rows, scale);
dhtRows.inverse(t, 2 * rows, scale);
dhtRows.inverse(t, 3 * rows, scale);
for (int r = 0; r < rows; r++) {
idx1 = r * columns + c;
idx2 = rows + r;
a[idx1] = t[r];
a[idx1 + 1] = t[idx2];
a[idx1 + 2] = t[idx2 + rows];
a[idx1 + 3] = t[idx2 + 2 * rows];
}
}
}
} else if (columns == 2) {
for (int r = 0; r < rows; r++) {
idx1 = r * columns + 2 * n0;
idx2 = r;
t[idx2] = a[idx1];
t[idx2 + rows] = a[idx1 + 1];
}
if (isgn == -1) {
dhtRows.forward(t, 0);
dhtRows.forward(t, rows);
} else {
dhtRows.inverse(t, 0, scale);
dhtRows.inverse(t, rows, scale);
}
for (int r = 0; r < rows; r++) {
idx1 = r * columns + 2 * n0;
idx2 = r;
a[idx1] = t[idx2];
a[idx1 + 1] = t[idx2 + rows];
}
}
}
});
}
ConcurrencyUtils.waitForCompletion(futures);
}
private void ddxt2d_subth(final int isgn, final DoubleLargeArray a, final boolean scale) {
int nthread = (int) Math.min(columnsl, ConcurrencyUtils.getNumberOfThreads());
long nt = 4 * rowsl;
if (columnsl == 2) {
nt >>= 1;
} else if (columnsl < 2) {
nt >>= 2;
}
final long ntf = nt;
final int nthreads = nthread;
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() {
long idx1, idx2;
DoubleLargeArray t = new DoubleLargeArray(ntf, false);
if (columnsl > 2) {
if (isgn == -1) {
for (long c = 4 * n0; c < columnsl; c += 4 * nthreads) {
for (long r = 0; r < rowsl; r++) {
idx1 = r * columnsl + c;
idx2 = rowsl + r;
t.setDouble(r, a.getDouble(idx1));
t.setDouble(idx2, a.getDouble(idx1 + 1));
t.setDouble(idx2 + rowsl, a.getDouble(idx1 + 2));
t.setDouble(idx2 + 2 * rowsl, a.getDouble(idx1 + 3));
}
dhtRows.forward(t, 0);
dhtRows.forward(t, rowsl);
dhtRows.forward(t, 2 * rowsl);
dhtRows.forward(t, 3 * rowsl);
for (long r = 0; r < rowsl; r++) {
idx1 = r * columnsl + c;
idx2 = rowsl + r;
a.setDouble(idx1, t.getDouble(r));
a.setDouble(idx1 + 1, t.getDouble(idx2));
a.setDouble(idx1 + 2, t.getDouble(idx2 + rowsl));
a.setDouble(idx1 + 3, t.getDouble(idx2 + 2 * rowsl));
}
}
} else {
for (long c = 4 * n0; c < columnsl; c += 4 * nthreads) {
for (long r = 0; r < rowsl; r++) {
idx1 = r * columnsl + c;
idx2 = rowsl + r;
t.setDouble(r, a.getDouble(idx1));
t.setDouble(idx2, a.getDouble(idx1 + 1));
t.setDouble(idx2 + rowsl, a.getDouble(idx1 + 2));
t.setDouble(idx2 + 2 * rowsl, a.getDouble(idx1 + 3));
}
dhtRows.inverse(t, 0, scale);
dhtRows.inverse(t, rowsl, scale);
dhtRows.inverse(t, 2 * rowsl, scale);
dhtRows.inverse(t, 3 * rowsl, scale);
for (long r = 0; r < rowsl; r++) {
idx1 = r * columnsl + c;
idx2 = rowsl + r;
a.setDouble(idx1, t.getDouble(r));
a.setDouble(idx1 + 1, t.getDouble(idx2));
a.setDouble(idx1 + 2, t.getDouble(idx2 + rowsl));
a.setDouble(idx1 + 3, t.getDouble(idx2 + 2 * rowsl));
}
}
}
} else if (columnsl == 2) {
for (long r = 0; r < rowsl; r++) {
idx1 = r * columnsl + 2 * n0;
idx2 = r;
t.setDouble(idx2, a.getDouble(idx1));
t.setDouble(idx2 + rowsl, a.getDouble(idx1 + 1));
}
if (isgn == -1) {
dhtRows.forward(t, 0);
dhtRows.forward(t, rowsl);
} else {
dhtRows.inverse(t, 0, scale);
dhtRows.inverse(t, rowsl, scale);
}
for (long r = 0; r < rowsl; r++) {
idx1 = r * columnsl + 2 * n0;
idx2 = r;
a.setDouble(idx1, t.getDouble(idx2));
a.setDouble(idx1 + 1, t.getDouble(idx2 + rowsl));
}
}
}
});
}
ConcurrencyUtils.waitForCompletion(futures);
}
private void ddxt2d_subth(final int isgn, final double[][] a, final boolean scale) {
int nthread = Math.min(columns, ConcurrencyUtils.getNumberOfThreads());
int nt = 4 * rows;
if (columns == 2) {
nt >>= 1;
} else if (columns < 2) {
nt >>= 2;
}
final int ntf = nt;
final int nthreads = nthread;
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() {
int idx2;
double[] t = new double[ntf];
if (columns > 2) {
if (isgn == -1) {
for (int c = 4 * n0; c < columns; c += 4 * nthreads) {
for (int r = 0; r < rows; r++) {
idx2 = rows + r;
t[r] = a[r][c];
t[idx2] = a[r][c + 1];
t[idx2 + rows] = a[r][c + 2];
t[idx2 + 2 * rows] = a[r][c + 3];
}
dhtRows.forward(t, 0);
dhtRows.forward(t, rows);
dhtRows.forward(t, 2 * rows);
dhtRows.forward(t, 3 * rows);
for (int r = 0; r < rows; r++) {
idx2 = rows + r;
a[r][c] = t[r];
a[r][c + 1] = t[idx2];
a[r][c + 2] = t[idx2 + rows];
a[r][c + 3] = t[idx2 + 2 * rows];
}
}
} else {
for (int c = 4 * n0; c < columns; c += 4 * nthreads) {
for (int r = 0; r < rows; r++) {
idx2 = rows + r;
t[r] = a[r][c];
t[idx2] = a[r][c + 1];
t[idx2 + rows] = a[r][c + 2];
t[idx2 + 2 * rows] = a[r][c + 3];
}
dhtRows.inverse(t, 0, scale);
dhtRows.inverse(t, rows, scale);
dhtRows.inverse(t, 2 * rows, scale);
dhtRows.inverse(t, 3 * rows, scale);
for (int r = 0; r < rows; r++) {
idx2 = rows + r;
a[r][c] = t[r];
a[r][c + 1] = t[idx2];
a[r][c + 2] = t[idx2 + rows];
a[r][c + 3] = t[idx2 + 2 * rows];
}
}
}
} else if (columns == 2) {
for (int r = 0; r < rows; r++) {
idx2 = r;
t[idx2] = a[r][2 * n0];
t[idx2 + rows] = a[r][2 * n0 + 1];
}
if (isgn == -1) {
dhtRows.forward(t, 0);
dhtRows.forward(t, rows);
} else {
dhtRows.inverse(t, 0, scale);
dhtRows.inverse(t, rows, scale);
}
for (int r = 0; r < rows; r++) {
idx2 = r;
a[r][2 * n0] = t[idx2];
a[r][2 * n0 + 1] = t[idx2 + rows];
}
}
}
});
}
ConcurrencyUtils.waitForCompletion(futures);
}
private void ddxt2d0_subth(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 (isgn == -1) {
for (int r = n0; r < rows; r += nthreads) {
dhtColumns.forward(a, r * columns);
}
} else {
for (int r = n0; r < rows; r += nthreads) {
dhtColumns.inverse(a, r * columns, scale);
}
}
}
});
}
ConcurrencyUtils.waitForCompletion(futures);
}
private void ddxt2d0_subth(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 long n0 = i;
futures[i] = ConcurrencyUtils.submit(new Runnable() {
public void run() {
if (isgn == -1) {
for (long r = n0; r < rowsl; r += nthreads) {
dhtColumns.forward(a, r * columnsl);
}
} else {
for (long r = n0; r < rowsl; r += nthreads) {
dhtColumns.inverse(a, r * columnsl, scale);
}
}
}
});
}
ConcurrencyUtils.waitForCompletion(futures);
}
private void ddxt2d0_subth(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 (isgn == -1) {
for (int r = n0; r < rows; r += nthreads) {
dhtColumns.forward(a[r]);
}
} else {
for (int r = n0; r < rows; r += nthreads) {
dhtColumns.inverse(a[r], scale);
}
}
}
});
}
ConcurrencyUtils.waitForCompletion(futures);
}
private void ddxt2d_sub(int isgn, double[] a, boolean scale) {
int idx1, idx2;
int nt = 4 * rows;
if (columns == 2) {
nt >>= 1;
} else if (columns < 2) {
nt >>= 2;
}
double[] t = new double[nt];
if (columns > 2) {
if (isgn == -1) {
for (int c = 0; c < columns; c += 4) {
for (int r = 0; r < rows; r++) {
idx1 = r * columns + c;
idx2 = rows + r;
t[r] = a[idx1];
t[idx2] = a[idx1 + 1];
t[idx2 + rows] = a[idx1 + 2];
t[idx2 + 2 * rows] = a[idx1 + 3];
}
dhtRows.forward(t, 0);
dhtRows.forward(t, rows);
dhtRows.forward(t, 2 * rows);
dhtRows.forward(t, 3 * rows);
for (int r = 0; r < rows; r++) {
idx1 = r * columns + c;
idx2 = rows + r;
a[idx1] = t[r];
a[idx1 + 1] = t[idx2];
a[idx1 + 2] = t[idx2 + rows];
a[idx1 + 3] = t[idx2 + 2 * rows];
}
}
} else {
for (int c = 0; c < columns; c += 4) {
for (int r = 0; r < rows; r++) {
idx1 = r * columns + c;
idx2 = rows + r;
t[r] = a[idx1];
t[idx2] = a[idx1 + 1];
t[idx2 + rows] = a[idx1 + 2];
t[idx2 + 2 * rows] = a[idx1 + 3];
}
dhtRows.inverse(t, 0, scale);
dhtRows.inverse(t, rows, scale);
dhtRows.inverse(t, 2 * rows, scale);
dhtRows.inverse(t, 3 * rows, scale);
for (int r = 0; r < rows; r++) {
idx1 = r * columns + c;
idx2 = rows + r;
a[idx1] = t[r];
a[idx1 + 1] = t[idx2];
a[idx1 + 2] = t[idx2 + rows];
a[idx1 + 3] = t[idx2 + 2 * rows];
}
}
}
} else if (columns == 2) {
for (int r = 0; r < rows; r++) {
idx1 = r * columns;
t[r] = a[idx1];
t[rows + r] = a[idx1 + 1];
}
if (isgn == -1) {
dhtRows.forward(t, 0);
dhtRows.forward(t, rows);
} else {
dhtRows.inverse(t, 0, scale);
dhtRows.inverse(t, rows, scale);
}
for (int r = 0; r < rows; r++) {
idx1 = r * columns;
a[idx1] = t[r];
a[idx1 + 1] = t[rows + r];
}
}
}
private void ddxt2d_sub(int isgn, DoubleLargeArray a, boolean scale) {
long idx1, idx2;
long nt = 4 * rowsl;
if (columnsl == 2) {
nt >>= 1;
} else if (columnsl < 2) {
nt >>= 2;
}
DoubleLargeArray t = new DoubleLargeArray(nt, false);
if (columnsl > 2) {
if (isgn == -1) {
for (long c = 0; c < columnsl; c += 4) {
for (long r = 0; r < rowsl; r++) {
idx1 = r * columnsl + c;
idx2 = rowsl + r;
t.setDouble(r, a.getDouble(idx1));
t.setDouble(idx2, a.getDouble(idx1 + 1));
t.setDouble(idx2 + rowsl, a.getDouble(idx1 + 2));
t.setDouble(idx2 + 2 * rowsl, a.getDouble(idx1 + 3));
}
dhtRows.forward(t, 0);
dhtRows.forward(t, rowsl);
dhtRows.forward(t, 2 * rowsl);
dhtRows.forward(t, 3 * rowsl);
for (long r = 0; r < rowsl; r++) {
idx1 = r * columnsl + c;
idx2 = rowsl + r;
a.setDouble(idx1, t.getDouble(r));
a.setDouble(idx1 + 1, t.getDouble(idx2));
a.setDouble(idx1 + 2, t.getDouble(idx2 + rowsl));
a.setDouble(idx1 + 3, t.getDouble(idx2 + 2 * rowsl));
}
}
} else {
for (long c = 0; c < columnsl; c += 4) {
for (long r = 0; r < rowsl; r++) {
idx1 = r * columnsl + c;
idx2 = rowsl + r;
t.setDouble(r, a.getDouble(idx1));
t.setDouble(idx2, a.getDouble(idx1 + 1));
t.setDouble(idx2 + rowsl, a.getDouble(idx1 + 2));
t.setDouble(idx2 + 2 * rowsl, a.getDouble(idx1 + 3));
}
dhtRows.inverse(t, 0, scale);
dhtRows.inverse(t, rowsl, scale);
dhtRows.inverse(t, 2 * rowsl, scale);
dhtRows.inverse(t, 3 * rowsl, scale);
for (long r = 0; r < rowsl; r++) {
idx1 = r * columnsl + c;
idx2 = rowsl + r;
a.setDouble(idx1, t.getDouble(r));
a.setDouble(idx1 + 1, t.getDouble(idx2));
a.setDouble(idx1 + 2, t.getDouble(idx2 + rowsl));
a.setDouble(idx1 + 3, t.getDouble(idx2 + 2 * rowsl));
}
}
}
} else if (columnsl == 2) {
for (long r = 0; r < rowsl; r++) {
idx1 = r * columnsl;
t.setDouble(r, a.getDouble(idx1));
t.setDouble(rowsl + r, a.getDouble(idx1 + 1));
}
if (isgn == -1) {
dhtRows.forward(t, 0);
dhtRows.forward(t, rowsl);
} else {
dhtRows.inverse(t, 0, scale);
dhtRows.inverse(t, rowsl, scale);
}
for (long r = 0; r < rowsl; r++) {
idx1 = r * columnsl;
a.setDouble(idx1, t.getDouble(r));
a.setDouble(idx1 + 1, t.getDouble(rowsl + r));
}
}
}
private void ddxt2d_sub(int isgn, double[][] a, boolean scale) {
int idx2;
int nt = 4 * rows;
if (columns == 2) {
nt >>= 1;
} else if (columns < 2) {
nt >>= 2;
}
double[] t = new double[nt];
if (columns > 2) {
if (isgn == -1) {
for (int c = 0; c < columns; c += 4) {
for (int r = 0; r < rows; r++) {
idx2 = rows + r;
t[r] = a[r][c];
t[idx2] = a[r][c + 1];
t[idx2 + rows] = a[r][c + 2];
t[idx2 + 2 * rows] = a[r][c + 3];
}
dhtRows.forward(t, 0);
dhtRows.forward(t, rows);
dhtRows.forward(t, 2 * rows);
dhtRows.forward(t, 3 * rows);
for (int r = 0; r < rows; r++) {
idx2 = rows + r;
a[r][c] = t[r];
a[r][c + 1] = t[idx2];
a[r][c + 2] = t[idx2 + rows];
a[r][c + 3] = t[idx2 + 2 * rows];
}
}
} else {
for (int c = 0; c < columns; c += 4) {
for (int r = 0; r < rows; r++) {
idx2 = rows + r;
t[r] = a[r][c];
t[idx2] = a[r][c + 1];
t[idx2 + rows] = a[r][c + 2];
t[idx2 + 2 * rows] = a[r][c + 3];
}
dhtRows.inverse(t, 0, scale);
dhtRows.inverse(t, rows, scale);
dhtRows.inverse(t, 2 * rows, scale);
dhtRows.inverse(t, 3 * rows, scale);
for (int r = 0; r < rows; r++) {
idx2 = rows + r;
a[r][c] = t[r];
a[r][c + 1] = t[idx2];
a[r][c + 2] = t[idx2 + rows];
a[r][c + 3] = t[idx2 + 2 * rows];
}
}
}
} else if (columns == 2) {
for (int r = 0; r < rows; r++) {
t[r] = a[r][0];
t[rows + r] = a[r][1];
}
if (isgn == -1) {
dhtRows.forward(t, 0);
dhtRows.forward(t, rows);
} else {
dhtRows.inverse(t, 0, scale);
dhtRows.inverse(t, rows, scale);
}
for (int r = 0; r < rows; r++) {
a[r][0] = t[r];
a[r][1] = t[rows + r];
}
}
}
private void yTransform(double[] a) {
int mRow, mCol, idx1, idx2;
double A, B, C, D, E;
for (int r = 0; r <= rows / 2; r++) {
mRow = (rows - r) % rows;
idx1 = r * columns;
idx2 = mRow * columns;
for (int c = 0; c <= columns / 2; c++) {
mCol = (columns - c) % columns;
A = a[idx1 + c];
B = a[idx2 + c];
C = a[idx1 + mCol];
D = a[idx2 + mCol];
E = ((A + D) - (B + C)) / 2;
a[idx1 + c] = A - E;
a[idx2 + c] = B + E;
a[idx1 + mCol] = C + E;
a[idx2 + mCol] = D - E;
}
}
}
private void yTransform(DoubleLargeArray a) {
long mRow, mCol, idx1, idx2;
double A, B, C, D, E;
for (long r = 0; r <= rowsl / 2; r++) {
mRow = (rowsl - r) % rowsl;
idx1 = r * columnsl;
idx2 = mRow * columnsl;
for (long c = 0; c <= columnsl / 2; c++) {
mCol = (columnsl - c) % columnsl;
A = a.getDouble(idx1 + c);
B = a.getDouble(idx2 + c);
C = a.getDouble(idx1 + mCol);
D = a.getDouble(idx2 + mCol);
E = ((A + D) - (B + C)) / 2;
a.setDouble(idx1 + c, A - E);
a.setDouble(idx2 + c, B + E);
a.setDouble(idx1 + mCol, C + E);
a.setDouble(idx2 + mCol, D - E);
}
}
}
private void yTransform(double[][] a) {
int mRow, mCol;
double A, B, C, D, E;
for (int r = 0; r <= rows / 2; r++) {
mRow = (rows - r) % rows;
for (int c = 0; c <= columns / 2; c++) {
mCol = (columns - c) % columns;
A = a[r][c];
B = a[mRow][c];
C = a[r][mCol];
D = a[mRow][mCol];
E = ((A + D) - (B + C)) / 2;
a[r][c] = A - E;
a[mRow][c] = B + E;
a[r][mCol] = C + E;
a[mRow][mCol] = D - E;
}
}
}
}
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