/* ***** BEGIN LICENSE BLOCK *****
* Version: MPL 1.1/GPL 2.0/LGPL 2.1
*
* The contents of this file are subject to the Mozilla Public License Version
* 1.1 (the "License"); you may not use this file except in compliance with
* the License. You may obtain a copy of the License at
* http://www.mozilla.org/MPL/
*
* Software distributed under the License is distributed on an "AS IS" basis,
* WITHOUT WARRANTY OF ANY KIND, either express or implied. See the License
* for the specific language governing rights and limitations under the
* License.
*
* The Original Code is JTransforms.
*
* The Initial Developer of the Original Code is
* Piotr Wendykier, Emory University.
* Portions created by the Initial Developer are Copyright (C) 2007-2009
* the Initial Developer. All Rights Reserved.
*
* Alternatively, the contents of this file may be used under the terms of
* either the GNU General Public License Version 2 or later (the "GPL"), or
* the GNU Lesser General Public License Version 2.1 or later (the "LGPL"),
* in which case the provisions of the GPL or the LGPL are applicable instead
* of those above. If you wish to allow use of your version of this file only
* under the terms of either the GPL or the LGPL, and not to allow others to
* use your version of this file under the terms of the MPL, indicate your
* decision by deleting the provisions above and replace them with the notice
* and other provisions required by the GPL or the LGPL. If you do not delete
* the provisions above, a recipient may use your version of this file under
* the terms of any one of the MPL, the GPL or the LGPL.
*
* ***** END LICENSE BLOCK ***** */
package edu.emory.mathcs.jtransforms.dht;
import java.util.concurrent.Future;
import edu.emory.mathcs.utils.ConcurrencyUtils;
/**
* Computes 2D Discrete Hartley Transform (DHT) of real, single 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 (piotr.wendykier@gmail.com)
*
*/
public class FloatDHT_2D {
private int rows;
private int columns;
private float[] t;
private FloatDHT_1D dhtColumns, dhtRows;
private int oldNthreads;
private int nt;
private boolean isPowerOfTwo = false;
private boolean useThreads = false;
/**
* Creates new instance of FloatDHT_2D.
*
* @param rows
* number of rows
* @param column
* number of columns
*/
public FloatDHT_2D(int rows, int column) {
if (rows <= 1 || column <= 1) {
throw new IllegalArgumentException("rows and columns must be greater than 1");
}
this.rows = rows;
this.columns = column;
if (rows * column >= ConcurrencyUtils.getThreadsBeginN_2D()) {
this.useThreads = true;
}
if (ConcurrencyUtils.isPowerOf2(rows) && ConcurrencyUtils.isPowerOf2(column)) {
isPowerOfTwo = true;
oldNthreads = ConcurrencyUtils.getNumberOfThreads();
nt = 4 * oldNthreads * rows;
if (column == 2 * oldNthreads) {
nt >>= 1;
} else if (column < 2 * oldNthreads) {
nt >>= 2;
}
t = new float[nt];
}
dhtColumns = new FloatDHT_1D(column);
if (column == rows) {
dhtRows = dhtColumns;
} else {
dhtRows = new FloatDHT_1D(rows);
}
}
/**
* 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 float[] a) {
int nthreads = ConcurrencyUtils.getNumberOfThreads();
if (isPowerOfTwo) {
if (nthreads != oldNthreads) {
nt = 4 * nthreads * rows;
if (columns == 2 * nthreads) {
nt >>= 1;
} else if (columns < 2 * nthreads) {
nt >>= 2;
}
t = new float[nt];
oldNthreads = nthreads;
}
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);
}
}
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() {
float[] temp = new float[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);
}
float[] temp = new float[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 2D array.
*
* @param a
* data to transform
*/
public void forward(final float[][] a) {
int nthreads = ConcurrencyUtils.getNumberOfThreads();
if (isPowerOfTwo) {
if (nthreads != oldNthreads) {
nt = 4 * nthreads * rows;
if (columns == 2 * nthreads) {
nt >>= 1;
} else if (columns < 2 * nthreads) {
nt >>= 2;
}
t = new float[nt];
oldNthreads = nthreads;
}
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]);
}
}
y_transform(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() {
float[] temp = new float[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]);
}
float[] temp = new float[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];
}
}
}
y_transform(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 float[] a, final boolean scale) {
int nthreads = ConcurrencyUtils.getNumberOfThreads();
if (isPowerOfTwo) {
if (nthreads != oldNthreads) {
nt = 4 * nthreads * rows;
if (columns == 2 * nthreads) {
nt >>= 1;
} else if (columns < 2 * nthreads) {
nt >>= 2;
}
t = new float[nt];
oldNthreads = nthreads;
}
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() {
float[] temp = new float[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);
}
float[] temp = new float[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 2D array.
*
* @param a
* data to transform
* @param scale
* if true then scaling is performed
*/
public void inverse(final float[][] a, final boolean scale) {
int nthreads = ConcurrencyUtils.getNumberOfThreads();
if (isPowerOfTwo) {
if (nthreads != oldNthreads) {
nt = 4 * nthreads * rows;
if (columns == 2 * nthreads) {
nt >>= 1;
} else if (columns < 2 * nthreads) {
nt >>= 2;
}
t = new float[nt];
oldNthreads = nthreads;
}
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);
}
}
y_transform(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() {
float[] temp = new float[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);
}
float[] temp = new float[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];
}
}
}
y_transform(a);
}
}
private void ddxt2d_subth(final int isgn, final float[] a, final boolean scale) {
int nthread = ConcurrencyUtils.getNumberOfThreads();
int nt = 4 * rows;
if (columns == 2 * nthread) {
nt >>= 1;
} else if (columns < 2 * nthread) {
nthread = columns;
nt >>= 2;
}
final int nthreads = nthread;
Future[] futures = new Future[nthreads];
for (int i = 0; i < nthreads; i++) {
final int n0 = i;
final int startt = nt * i;
futures[i] = ConcurrencyUtils.submit(new Runnable() {
public void run() {
int idx1, idx2;
if (columns > 2 * nthreads) {
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 = startt + rows + r;
t[startt + r] = a[idx1];
t[idx2] = a[idx1 + 1];
t[idx2 + rows] = a[idx1 + 2];
t[idx2 + 2 * rows] = a[idx1 + 3];
}
dhtRows.forward(t, startt);
dhtRows.forward(t, startt + rows);
dhtRows.forward(t, startt + 2 * rows);
dhtRows.forward(t, startt + 3 * rows);
for (int r = 0; r < rows; r++) {
idx1 = r * columns + c;
idx2 = startt + rows + r;
a[idx1] = t[startt + 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 = startt + rows + r;
t[startt + r] = a[idx1];
t[idx2] = a[idx1 + 1];
t[idx2 + rows] = a[idx1 + 2];
t[idx2 + 2 * rows] = a[idx1 + 3];
}
dhtRows.inverse(t, startt, scale);
dhtRows.inverse(t, startt + rows, scale);
dhtRows.inverse(t, startt + 2 * rows, scale);
dhtRows.inverse(t, startt + 3 * rows, scale);
for (int r = 0; r < rows; r++) {
idx1 = r * columns + c;
idx2 = startt + rows + r;
a[idx1] = t[startt + r];
a[idx1 + 1] = t[idx2];
a[idx1 + 2] = t[idx2 + rows];
a[idx1 + 3] = t[idx2 + 2 * rows];
}
}
}
} else if (columns == 2 * nthreads) {
for (int r = 0; r < rows; r++) {
idx1 = r * columns + 2 * n0;
idx2 = startt + r;
t[idx2] = a[idx1];
t[idx2 + rows] = a[idx1 + 1];
}
if (isgn == -1) {
dhtRows.forward(t, startt);
dhtRows.forward(t, startt + rows);
} else {
dhtRows.inverse(t, startt, scale);
dhtRows.inverse(t, startt + rows, scale);
}
for (int r = 0; r < rows; r++) {
idx1 = r * columns + 2 * n0;
idx2 = startt + r;
a[idx1] = t[idx2];
a[idx1 + 1] = t[idx2 + rows];
}
} else if (columns == nthreads) {
for (int r = 0; r < rows; r++) {
t[startt + r] = a[r * columns + n0];
}
if (isgn == -1) {
dhtRows.forward(t, startt);
} else {
dhtRows.inverse(t, startt, scale);
}
for (int r = 0; r < rows; r++) {
a[r * columns + n0] = t[startt + r];
}
}
}
});
}
ConcurrencyUtils.waitForCompletion(futures);
}
private void ddxt2d_subth(final int isgn, final float[][] a, final boolean scale) {
int nthread = ConcurrencyUtils.getNumberOfThreads();
int nt = 4 * rows;
if (columns == 2 * nthread) {
nt >>= 1;
} else if (columns < 2 * nthread) {
nthread = columns;
nt >>= 2;
}
final int nthreads = nthread;
Future[] futures = new Future[nthreads];
for (int i = 0; i < nthreads; i++) {
final int n0 = i;
final int startt = nt * i;
futures[i] = ConcurrencyUtils.submit(new Runnable() {
public void run() {
int idx2;
if (columns > 2 * nthreads) {
if (isgn == -1) {
for (int c = 4 * n0; c < columns; c += 4 * nthreads) {
for (int r = 0; r < rows; r++) {
idx2 = startt + rows + r;
t[startt + 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, startt);
dhtRows.forward(t, startt + rows);
dhtRows.forward(t, startt + 2 * rows);
dhtRows.forward(t, startt + 3 * rows);
for (int r = 0; r < rows; r++) {
idx2 = startt + rows + r;
a[r][c] = t[startt + 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 = startt + rows + r;
t[startt + 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, startt, scale);
dhtRows.inverse(t, startt + rows, scale);
dhtRows.inverse(t, startt + 2 * rows, scale);
dhtRows.inverse(t, startt + 3 * rows, scale);
for (int r = 0; r < rows; r++) {
idx2 = startt + rows + r;
a[r][c] = t[startt + 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 * nthreads) {
for (int r = 0; r < rows; r++) {
idx2 = startt + r;
t[idx2] = a[r][2 * n0];
t[idx2 + rows] = a[r][2 * n0 + 1];
}
if (isgn == -1) {
dhtRows.forward(t, startt);
dhtRows.forward(t, startt + rows);
} else {
dhtRows.inverse(t, startt, scale);
dhtRows.inverse(t, startt + rows, scale);
}
for (int r = 0; r < rows; r++) {
idx2 = startt + r;
a[r][2 * n0] = t[idx2];
a[r][2 * n0 + 1] = t[idx2 + rows];
}
} else if (columns == nthreads) {
for (int r = 0; r < rows; r++) {
t[startt + r] = a[r][n0];
}
if (isgn == -1) {
dhtRows.forward(t, startt);
} else {
dhtRows.inverse(t, startt, scale);
}
for (int r = 0; r < rows; r++) {
a[r][n0] = t[startt + r];
}
}
}
});
}
ConcurrencyUtils.waitForCompletion(futures);
}
private void ddxt2d0_subth(final int isgn, final float[] 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 float[][] 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, float[] a, boolean scale) {
int idx1, idx2;
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, float[][] a, boolean scale) {
int idx2;
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(float[] a) {
int mRow, mCol, idx1, idx2;
float 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 y_transform(float[][] a) {
int mRow, mCol;
float 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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