cern.colt.matrix.tfloat.impl.DenseFloatMatrix3D Maven / Gradle / Ivy
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/*
Copyright (C) 1999 CERN - European Organization for Nuclear Research.
Permission to use, copy, modify, distribute and sell this software and its documentation for any purpose
is hereby granted without fee, provided that the above copyright notice appear in all copies and
that both that copyright notice and this permission notice appear in supporting documentation.
CERN makes no representations about the suitability of this software for any purpose.
It is provided "as is" without expressed or implied warranty.
*/
package cern.colt.matrix.tfloat.impl;
import java.util.concurrent.Callable;
import java.util.concurrent.ExecutionException;
import java.util.concurrent.Future;
import cern.colt.list.tfloat.FloatArrayList;
import cern.colt.list.tint.IntArrayList;
import cern.colt.matrix.tfcomplex.impl.DenseFComplexMatrix3D;
import cern.colt.matrix.tfloat.FloatMatrix1D;
import cern.colt.matrix.tfloat.FloatMatrix2D;
import cern.colt.matrix.tfloat.FloatMatrix3D;
import edu.emory.mathcs.jtransforms.dct.FloatDCT_3D;
import edu.emory.mathcs.jtransforms.dht.FloatDHT_3D;
import edu.emory.mathcs.jtransforms.dst.FloatDST_3D;
import edu.emory.mathcs.jtransforms.fft.FloatFFT_3D;
import edu.emory.mathcs.utils.ConcurrencyUtils;
/**
* Dense 3-d matrix holding float elements. First see the package summary and javadoc tree view to get the broad picture.
*
* Implementation:
*
* Internally holds one single contiguous one-dimensional array, addressed in
* (in decreasing order of significance): slice major, row major, column major.
* Note that this implementation is not synchronized.
*
* Time complexity:
*
* O(1) (i.e. constant time) for the basic operations get,
* getQuick, set, setQuick and size,
*
* Applications demanding utmost speed can exploit knowledge about the internal
* addressing. Setting/getting values in a loop slice-by-slice, row-by-row,
* column-by-column is quicker than, for example, column-by-column, row-by-row,
* slice-by-slice. Thus
*
*
* for (int slice = 0; slice < slices; slice++) {
* for (int row = 0; row < rows; row++) {
* for (int column = 0; column < columns; column++) {
* matrix.setQuick(slice, row, column, someValue);
* }
* }
* }
*
*
* is quicker than
*
*
* for (int column = 0; column < columns; column++) {
* for (int row = 0; row < rows; row++) {
* for (int slice = 0; slice < slices; slice++) {
* matrix.setQuick(slice, row, column, someValue);
* }
* }
* }
*
*
* @author [email protected]
* @version 1.0, 09/24/99
*
* @author Piotr Wendykier ([email protected])
*/
public class DenseFloatMatrix3D extends FloatMatrix3D {
private static final long serialVersionUID = 1L;
private FloatFFT_3D fft3;
private FloatDCT_3D dct3;
private FloatDST_3D dst3;
private FloatDHT_3D dht3;
protected float[] elements;
/**
* Constructs a matrix with a copy of the given values. values is
* required to have the form values[slice][row][column] and have
* exactly the same number of rows in in every slice and exactly the same
* number of columns in in every row.
*
* The values are copied. So subsequent changes in values are not
* reflected in the matrix, and vice-versa.
*
* @param values
* The values to be filled into the new matrix.
* @throws IllegalArgumentException
* if
* for any 1 <= slice < values.length: values[slice].length != values[slice-1].length
* .
* @throws IllegalArgumentException
* if
* for any 1 <= row < values[0].length: values[slice][row].length != values[slice][row-1].length
* .
*/
public DenseFloatMatrix3D(float[][][] values) {
this(values.length, (values.length == 0 ? 0 : values[0].length), (values.length == 0 ? 0
: values[0].length == 0 ? 0 : values[0][0].length));
assign(values);
}
/**
* Constructs a matrix with a given number of slices, rows and columns. All
* entries are initially 0.
*
* @param slices
* the number of slices the matrix shall have.
* @param rows
* the number of rows the matrix shall have.
* @param columns
* the number of columns the matrix shall have.
* @throws IllegalArgumentException
* if (float)slices*columns*rows > Integer.MAX_VALUE.
* @throws IllegalArgumentException
* if slices<0 || rows<0 || columns<0.
*/
public DenseFloatMatrix3D(int slices, int rows, int columns) {
setUp(slices, rows, columns);
this.elements = new float[slices * rows * columns];
}
/**
* Constructs a matrix with the given parameters.
*
* @param slices
* the number of slices the matrix shall have.
* @param rows
* the number of rows the matrix shall have.
* @param columns
* the number of columns the matrix shall have.
* @param elements
* the cells.
* @param sliceZero
* the position of the first element.
* @param rowZero
* the position of the first element.
* @param columnZero
* the position of the first element.
* @param sliceStride
* the number of elements between two slices, i.e.
* index(k+1,i,j)-index(k,i,j).
* @param rowStride
* the number of elements between two rows, i.e.
* index(k,i+1,j)-index(k,i,j).
* @param columnStride
* the number of elements between two columns, i.e.
* index(k,i,j+1)-index(k,i,j).
* @param isView
* if true then a matrix view is constructed
* @throws IllegalArgumentException
* if (float)slices*columns*rows > Integer.MAX_VALUE.
* @throws IllegalArgumentException
* if slices<0 || rows<0 || columns<0.
*/
public DenseFloatMatrix3D(int slices, int rows, int columns, float[] elements, int sliceZero, int rowZero,
int columnZero, int sliceStride, int rowStride, int columnStride, boolean isView) {
setUp(slices, rows, columns, sliceZero, rowZero, columnZero, sliceStride, rowStride, columnStride);
this.elements = elements;
this.isNoView = !isView;
}
public float aggregate(final cern.colt.function.tfloat.FloatFloatFunction aggr,
final cern.colt.function.tfloat.FloatFunction f) {
if (size() == 0)
return Float.NaN;
float a = 0;
final int zero = (int) index(0, 0, 0);
int nthreads = ConcurrencyUtils.getNumberOfThreads();
if ((nthreads > 1) && (size() >= ConcurrencyUtils.getThreadsBeginN_3D())) {
nthreads = Math.min(nthreads, slices);
Future[] futures = new Future[nthreads];
int k = slices / nthreads;
for (int j = 0; j < nthreads; j++) {
final int firstSlice = j * k;
final int lastSlice = (j == nthreads - 1) ? slices : firstSlice + k;
futures[j] = ConcurrencyUtils.submit(new Callable() {
public Float call() throws Exception {
float a = f.apply(elements[zero + firstSlice * sliceStride]);
int d = 1;
for (int s = firstSlice; s < lastSlice; s++) {
for (int r = 0; r < rows; r++) {
for (int c = d; c < columns; c++) {
a = aggr.apply(a, f.apply(elements[zero + s * sliceStride + r * rowStride + c
* columnStride]));
}
d = 0;
}
}
return a;
}
});
}
a = ConcurrencyUtils.waitForCompletion(futures, aggr);
} else {
a = f.apply(elements[zero]);
int d = 1; // first cell already done
for (int s = 0; s < slices; s++) {
for (int r = 0; r < rows; r++) {
for (int c = d; c < columns; c++) {
a = aggr.apply(a, f.apply(elements[zero + s * sliceStride + r * rowStride + c * columnStride]));
}
d = 0;
}
}
}
return a;
}
public float aggregate(final cern.colt.function.tfloat.FloatFloatFunction aggr,
final cern.colt.function.tfloat.FloatFunction f, final cern.colt.function.tfloat.FloatProcedure cond) {
if (size() == 0)
return Float.NaN;
float a = 0;
final int zero = (int) index(0, 0, 0);
int nthreads = ConcurrencyUtils.getNumberOfThreads();
if ((nthreads > 1) && (slices * rows * columns >= ConcurrencyUtils.getThreadsBeginN_3D())) {
nthreads = Math.min(nthreads, slices);
Future[] futures = new Future[nthreads];
int k = slices / nthreads;
for (int j = 0; j < nthreads; j++) {
final int firstSlice = j * k;
final int lastSlice = (j == nthreads - 1) ? slices : firstSlice + k;
futures[j] = ConcurrencyUtils.submit(new Callable() {
public Float call() throws Exception {
float elem = elements[zero + firstSlice * sliceStride];
float a = 0;
if (cond.apply(elem) == true) {
a = aggr.apply(a, f.apply(elem));
}
int d = 1;
for (int s = firstSlice; s < lastSlice; s++) {
for (int r = 0; r < rows; r++) {
for (int c = d; c < columns; c++) {
elem = elements[zero + s * sliceStride + r * rowStride + c * columnStride];
if (cond.apply(elem) == true) {
a = aggr.apply(a, f.apply(elem));
}
d = 0;
}
}
}
return a;
}
});
}
a = ConcurrencyUtils.waitForCompletion(futures, aggr);
} else {
float elem = elements[zero];
if (cond.apply(elem) == true) {
a = aggr.apply(a, f.apply(elem));
}
int d = 1;
for (int s = 0; s < slices; s++) {
for (int r = 0; r < rows; r++) {
for (int c = d; c < columns; c++) {
elem = elements[zero + s * sliceStride + r * rowStride + c * columnStride];
if (cond.apply(elem) == true) {
a = aggr.apply(a, f.apply(elem));
}
d = 0;
}
}
}
}
return a;
}
public float aggregate(final cern.colt.function.tfloat.FloatFloatFunction aggr,
final cern.colt.function.tfloat.FloatFunction f, final IntArrayList sliceList, final IntArrayList rowList,
final IntArrayList columnList) {
if (size() == 0)
return Float.NaN;
if (sliceList.size() == 0 || rowList.size() == 0 || columnList.size() == 0)
return Float.NaN;
final int size = sliceList.size();
final int[] sliceElements = sliceList.elements();
final int[] rowElements = rowList.elements();
final int[] columnElements = columnList.elements();
final int zero = (int) index(0, 0, 0);
float a = 0;
int nthreads = ConcurrencyUtils.getNumberOfThreads();
if ((nthreads > 1) && (size >= ConcurrencyUtils.getThreadsBeginN_3D())) {
nthreads = Math.min(nthreads, slices);
Future[] futures = new Future[nthreads];
int k = size / nthreads;
for (int j = 0; j < nthreads; j++) {
final int firstIdx = j * k;
final int lastIdx = (j == nthreads - 1) ? size : firstIdx + k;
futures[j] = ConcurrencyUtils.submit(new Callable() {
public Float call() throws Exception {
float a = f.apply(elements[zero + sliceElements[firstIdx] * sliceStride + rowElements[firstIdx]
* rowStride + columnElements[firstIdx] * columnStride]);
float elem;
for (int i = firstIdx + 1; i < lastIdx; i++) {
elem = elements[zero + sliceElements[i] * sliceStride + rowElements[i] * rowStride
+ columnElements[i] * columnStride];
a = aggr.apply(a, f.apply(elem));
}
return a;
}
});
}
a = ConcurrencyUtils.waitForCompletion(futures, aggr);
} else {
a = f.apply(elements[zero + sliceElements[0] * sliceStride + rowElements[0] * rowStride + columnElements[0]
* columnStride]);
float elem;
for (int i = 1; i < size; i++) {
elem = elements[zero + sliceElements[i] * sliceStride + rowElements[i] * rowStride + columnElements[i]
* columnStride];
a = aggr.apply(a, f.apply(elem));
}
}
return a;
}
public float aggregate(final FloatMatrix3D other, final cern.colt.function.tfloat.FloatFloatFunction aggr,
final cern.colt.function.tfloat.FloatFloatFunction f) {
if (!(other instanceof DenseFloatMatrix3D)) {
return super.aggregate(other, aggr, f);
}
checkShape(other);
if (size() == 0)
return Float.NaN;
float a = 0;
final int zero = (int) index(0, 0, 0);
final int zeroOther = (int) other.index(0, 0, 0);
final int sliceStrideOther = other.sliceStride();
final int rowStrideOther = other.rowStride();
final int columnStrideOther = other.columnStride();
final float[] elementsOther = (float[]) other.elements();
int nthreads = ConcurrencyUtils.getNumberOfThreads();
if ((nthreads > 1) && (size() >= ConcurrencyUtils.getThreadsBeginN_3D())) {
nthreads = Math.min(nthreads, slices);
Future[] futures = new Future[nthreads];
int k = slices / nthreads;
for (int j = 0; j < nthreads; j++) {
final int firstSlice = j * k;
final int lastSlice = (j == nthreads - 1) ? slices : firstSlice + k;
futures[j] = ConcurrencyUtils.submit(new Callable() {
public Float call() throws Exception {
int idx = zero + firstSlice * sliceStride;
int idxOther = zeroOther + firstSlice * sliceStrideOther;
float a = f.apply(elements[idx], elementsOther[idxOther]);
int d = 1;
for (int s = firstSlice; s < lastSlice; s++) {
for (int r = 0; r < rows; r++) {
for (int c = d; c < columns; c++) {
idx = zero + s * sliceStride + r * rowStride + c * columnStride;
idxOther = zeroOther + s * sliceStrideOther + r * rowStrideOther + c
* columnStrideOther;
a = aggr.apply(a, f.apply(elements[idx], elementsOther[idxOther]));
}
d = 0;
}
}
return a;
}
});
}
a = ConcurrencyUtils.waitForCompletion(futures, aggr);
} else {
a = f.apply(getQuick(0, 0, 0), other.getQuick(0, 0, 0));
int d = 1; // first cell already done
int idx;
int idxOther;
for (int s = 0; s < slices; s++) {
for (int r = 0; r < rows; r++) {
for (int c = d; c < columns; c++) {
idx = zero + s * sliceStride + r * rowStride + c * columnStride;
idxOther = zeroOther + s * sliceStrideOther + r * rowStrideOther + c * columnStrideOther;
a = aggr.apply(a, f.apply(elements[idx], elementsOther[idxOther]));
}
d = 0;
}
}
}
return a;
}
public FloatMatrix3D assign(final cern.colt.function.tfloat.FloatFunction function) {
final int zero = (int) index(0, 0, 0);
int nthreads = ConcurrencyUtils.getNumberOfThreads();
if ((nthreads > 1) && (size() >= ConcurrencyUtils.getThreadsBeginN_3D())) {
nthreads = Math.min(nthreads, slices);
Future[] futures = new Future[nthreads];
int k = slices / nthreads;
for (int j = 0; j < nthreads; j++) {
final int firstSlice = j * k;
final int lastSlice = (j == nthreads - 1) ? slices : firstSlice + k;
futures[j] = ConcurrencyUtils.submit(new Runnable() {
public void run() {
int idx;
for (int s = firstSlice; s < lastSlice; s++) {
for (int r = 0; r < rows; r++) {
idx = zero + s * sliceStride + r * rowStride;
for (int c = 0; c < columns; c++) {
elements[idx] = function.apply(elements[idx]);
idx += columnStride;
}
}
}
}
});
}
ConcurrencyUtils.waitForCompletion(futures);
} else {
int idx;
for (int s = 0; s < slices; s++) {
for (int r = 0; r < rows; r++) {
idx = zero + s * sliceStride + r * rowStride;
for (int c = 0; c < columns; c++) {
elements[idx] = function.apply(elements[idx]);
idx += columnStride;
}
}
}
}
return this;
}
public FloatMatrix3D assign(final cern.colt.function.tfloat.FloatProcedure cond,
final cern.colt.function.tfloat.FloatFunction f) {
final int zero = (int) index(0, 0, 0);
int nthreads = ConcurrencyUtils.getNumberOfThreads();
if ((nthreads > 1) && (slices * rows * columns >= ConcurrencyUtils.getThreadsBeginN_3D())) {
nthreads = Math.min(nthreads, slices);
Future[] futures = new Future[nthreads];
int k = slices / nthreads;
for (int j = 0; j < nthreads; j++) {
final int firstSlice = j * k;
final int lastSlice = (j == nthreads - 1) ? slices : firstSlice + k;
futures[j] = ConcurrencyUtils.submit(new Runnable() {
public void run() {
float elem;
int idx;
for (int s = firstSlice; s < lastSlice; s++) {
for (int r = 0; r < rows; r++) {
idx = zero + s * sliceStride + r * rowStride;
for (int c = 0; c < columns; c++) {
elem = elements[idx];
if (cond.apply(elem) == true) {
elements[idx] = f.apply(elem);
}
idx += columnStride;
}
}
}
}
});
}
ConcurrencyUtils.waitForCompletion(futures);
} else {
float elem;
int idx;
for (int s = 0; s < slices; s++) {
for (int r = 0; r < rows; r++) {
idx = zero + s * sliceStride + r * rowStride;
for (int c = 0; c < columns; c++) {
elem = elements[idx];
if (cond.apply(elem) == true) {
elements[idx] = f.apply(elem);
}
idx += columnStride;
}
}
}
}
return this;
}
public FloatMatrix3D assign(final cern.colt.function.tfloat.FloatProcedure cond, final float value) {
final int zero = (int) index(0, 0, 0);
int nthreads = ConcurrencyUtils.getNumberOfThreads();
if ((nthreads > 1) && (slices * rows * columns >= ConcurrencyUtils.getThreadsBeginN_3D())) {
nthreads = Math.min(nthreads, slices);
Future[] futures = new Future[nthreads];
int k = slices / nthreads;
for (int j = 0; j < nthreads; j++) {
final int firstSlice = j * k;
final int lastSlice = (j == nthreads - 1) ? slices : firstSlice + k;
futures[j] = ConcurrencyUtils.submit(new Runnable() {
public void run() {
float elem;
int idx;
for (int s = firstSlice; s < lastSlice; s++) {
for (int r = 0; r < rows; r++) {
idx = zero + s * sliceStride + r * rowStride;
for (int c = 0; c < columns; c++) {
elem = elements[idx];
if (cond.apply(elem) == true) {
elements[idx] = value;
}
idx += columnStride;
}
}
}
}
});
}
ConcurrencyUtils.waitForCompletion(futures);
} else {
float elem;
int idx;
for (int s = 0; s < slices; s++) {
for (int r = 0; r < rows; r++) {
idx = zero + s * sliceStride + r * rowStride;
for (int c = 0; c < columns; c++) {
elem = elements[idx];
if (cond.apply(elem) == true) {
elements[idx] = value;
}
idx += columnStride;
}
}
}
}
return this;
}
public FloatMatrix3D assign(final float value) {
final int zero = (int) index(0, 0, 0);
int nthreads = ConcurrencyUtils.getNumberOfThreads();
if ((nthreads > 1) && (size() >= ConcurrencyUtils.getThreadsBeginN_3D())) {
nthreads = Math.min(nthreads, slices);
Future[] futures = new Future[nthreads];
int k = slices / nthreads;
for (int j = 0; j < nthreads; j++) {
final int firstSlice = j * k;
final int lastSlice = (j == nthreads - 1) ? slices : firstSlice + k;
futures[j] = ConcurrencyUtils.submit(new Runnable() {
public void run() {
int idx;
for (int s = firstSlice; s < lastSlice; s++) {
for (int r = 0; r < rows; r++) {
idx = zero + s * sliceStride + r * rowStride;
for (int c = 0; c < columns; c++) {
elements[idx] = value;
idx += columnStride;
}
}
}
}
});
}
ConcurrencyUtils.waitForCompletion(futures);
} else {
int idx;
for (int s = 0; s < slices; s++) {
for (int r = 0; r < rows; r++) {
idx = zero + s * sliceStride + r * rowStride;
for (int c = 0; c < columns; c++) {
elements[idx] = value;
idx += columnStride;
}
}
}
}
return this;
}
public FloatMatrix3D assign(final float[] values) {
if (values.length != size())
throw new IllegalArgumentException("Must have same length: length=" + values.length
+ "slices()*rows()*columns()=" + slices() * rows() * columns());
int nthreads = ConcurrencyUtils.getNumberOfThreads();
if (this.isNoView) {
System.arraycopy(values, 0, this.elements, 0, values.length);
} else {
final int zero = (int) index(0, 0, 0);
if ((nthreads > 1) && (size() >= ConcurrencyUtils.getThreadsBeginN_3D())) {
nthreads = Math.min(nthreads, slices);
Future[] futures = new Future[nthreads];
int k = slices / nthreads;
for (int j = 0; j < nthreads; j++) {
final int firstSlice = j * k;
final int lastSlice = (j == nthreads - 1) ? slices : firstSlice + k;
futures[j] = ConcurrencyUtils.submit(new Runnable() {
public void run() {
int idxOther = firstSlice * rows * columns;
int idx;
for (int s = firstSlice; s < lastSlice; s++) {
for (int r = 0; r < rows; r++) {
idx = zero + s * sliceStride + r * rowStride;
for (int c = 0; c < columns; c++) {
elements[idx] = values[idxOther++];
idx += columnStride;
}
}
}
}
});
}
try {
for (int j = 0; j < nthreads; j++) {
futures[j].get();
}
} catch (ExecutionException ex) {
ex.printStackTrace();
} catch (InterruptedException e) {
e.printStackTrace();
}
} else {
int idxOther = 0;
int idx;
for (int s = 0; s < slices; s++) {
for (int r = 0; r < rows; r++) {
idx = zero + s * sliceStride + r * rowStride;
for (int c = 0; c < columns; c++) {
elements[idx] = values[idxOther++];
idx += columnStride;
}
}
}
}
}
return this;
}
public FloatMatrix3D assign(final float[][][] values) {
if (values.length != slices)
throw new IllegalArgumentException("Must have same number of slices: slices=" + values.length + "slices()="
+ slices());
int nthreads = ConcurrencyUtils.getNumberOfThreads();
if (this.isNoView) {
if ((nthreads > 1) && (size() >= ConcurrencyUtils.getThreadsBeginN_3D())) {
nthreads = Math.min(nthreads, slices);
Future[] futures = new Future[nthreads];
int k = slices / nthreads;
for (int j = 0; j < nthreads; j++) {
final int firstSlice = j * k;
final int lastSlice = (j == nthreads - 1) ? slices : firstSlice + k;
futures[j] = ConcurrencyUtils.submit(new Runnable() {
public void run() {
int i = firstSlice * sliceStride;
for (int s = firstSlice; s < lastSlice; s++) {
float[][] currentSlice = values[s];
if (currentSlice.length != rows)
throw new IllegalArgumentException(
"Must have same number of rows in every slice: rows=" + currentSlice.length
+ "rows()=" + rows());
for (int r = 0; r < rows; r++) {
float[] currentRow = currentSlice[r];
if (currentRow.length != columns)
throw new IllegalArgumentException(
"Must have same number of columns in every row: columns="
+ currentRow.length + "columns()=" + columns());
System.arraycopy(currentRow, 0, elements, i, columns);
i += columns;
}
}
}
});
}
try {
for (int j = 0; j < nthreads; j++) {
futures[j].get();
}
} catch (ExecutionException ex) {
ex.printStackTrace();
} catch (InterruptedException e) {
e.printStackTrace();
}
} else {
int i = 0;
for (int s = 0; s < slices; s++) {
float[][] currentSlice = values[s];
if (currentSlice.length != rows)
throw new IllegalArgumentException("Must have same number of rows in every slice: rows="
+ currentSlice.length + "rows()=" + rows());
for (int r = 0; r < rows; r++) {
float[] currentRow = currentSlice[r];
if (currentRow.length != columns)
throw new IllegalArgumentException(
"Must have same number of columns in every row: columns=" + currentRow.length
+ "columns()=" + columns());
System.arraycopy(currentRow, 0, this.elements, i, columns);
i += columns;
}
}
}
} else {
final int zero = (int) index(0, 0, 0);
if ((nthreads > 1) && (size() >= ConcurrencyUtils.getThreadsBeginN_3D())) {
nthreads = Math.min(nthreads, slices);
Future[] futures = new Future[nthreads];
int k = slices / nthreads;
for (int j = 0; j < nthreads; j++) {
final int firstSlice = j * k;
final int lastSlice = (j == nthreads - 1) ? slices : firstSlice + k;
futures[j] = ConcurrencyUtils.submit(new Runnable() {
public void run() {
int idx;
for (int s = firstSlice; s < lastSlice; s++) {
float[][] currentSlice = values[s];
if (currentSlice.length != rows)
throw new IllegalArgumentException(
"Must have same number of rows in every slice: rows=" + currentSlice.length
+ "rows()=" + rows());
for (int r = 0; r < rows; r++) {
idx = zero + s * sliceStride + r * rowStride;
float[] currentRow = currentSlice[r];
if (currentRow.length != columns)
throw new IllegalArgumentException(
"Must have same number of columns in every row: columns="
+ currentRow.length + "columns()=" + columns());
for (int c = 0; c < columns; c++) {
elements[idx] = currentRow[c];
idx += columnStride;
}
}
}
}
});
}
try {
for (int j = 0; j < nthreads; j++) {
futures[j].get();
}
} catch (ExecutionException ex) {
ex.printStackTrace();
} catch (InterruptedException e) {
e.printStackTrace();
}
} else {
int idx;
for (int s = 0; s < slices; s++) {
float[][] currentSlice = values[s];
if (currentSlice.length != rows)
throw new IllegalArgumentException("Must have same number of rows in every slice: rows="
+ currentSlice.length + "rows()=" + rows());
for (int r = 0; r < rows; r++) {
idx = zero + s * sliceStride + r * rowStride;
float[] currentRow = currentSlice[r];
if (currentRow.length != columns)
throw new IllegalArgumentException(
"Must have same number of columns in every row: columns=" + currentRow.length
+ "columns()=" + columns());
for (int c = 0; c < columns; c++) {
elements[idx] = currentRow[c];
idx += columnStride;
}
}
}
}
}
return this;
}
public FloatMatrix3D assign(FloatMatrix3D source) {
// overriden for performance only
if (!(source instanceof DenseFloatMatrix3D)) {
super.assign(source);
return this;
}
DenseFloatMatrix3D other = (DenseFloatMatrix3D) source;
if (other == this)
return this;
checkShape(other);
if (haveSharedCells(other)) {
FloatMatrix3D c = other.copy();
if (!(c instanceof DenseFloatMatrix3D)) { // should not happen
super.assign(source);
return this;
}
other = (DenseFloatMatrix3D) c;
}
final DenseFloatMatrix3D other_final = other;
int nthreads = ConcurrencyUtils.getNumberOfThreads();
if (this.isNoView && other.isNoView) { // quickest
System.arraycopy(other_final.elements, 0, this.elements, 0, this.elements.length);
return this;
} else {
final int zero = (int) index(0, 0, 0);
final int zeroOther = (int) other_final.index(0, 0, 0);
final int sliceStrideOther = other_final.sliceStride;
final int rowStrideOther = other_final.rowStride;
final int columnStrideOther = other_final.columnStride;
final float[] elementsOther = other_final.elements;
if ((nthreads > 1) && (size() >= ConcurrencyUtils.getThreadsBeginN_3D())) {
nthreads = Math.min(nthreads, slices);
Future[] futures = new Future[nthreads];
int k = slices / nthreads;
for (int j = 0; j < nthreads; j++) {
final int firstSlice = j * k;
final int lastSlice = (j == nthreads - 1) ? slices : firstSlice + k;
futures[j] = ConcurrencyUtils.submit(new Runnable() {
public void run() {
int idx;
int idxOther;
for (int s = firstSlice; s < lastSlice; s++) {
for (int r = 0; r < rows; r++) {
idx = zero + s * sliceStride + r * rowStride;
idxOther = zeroOther + s * sliceStrideOther + r * rowStrideOther;
for (int c = 0; c < columns; c++) {
elements[idx] = elementsOther[idxOther];
idx += columnStride;
idxOther += columnStrideOther;
}
}
}
}
});
}
try {
for (int j = 0; j < nthreads; j++) {
futures[j].get();
}
} catch (ExecutionException ex) {
ex.printStackTrace();
} catch (InterruptedException e) {
e.printStackTrace();
}
} else {
int idx;
int idxOther;
for (int s = 0; s < slices; s++) {
for (int r = 0; r < rows; r++) {
idx = zero + s * sliceStride + r * rowStride;
idxOther = zeroOther + s * sliceStrideOther + r * rowStrideOther;
for (int c = 0; c < columns; c++) {
elements[idx] = elementsOther[idxOther];
idx += columnStride;
idxOther += columnStrideOther;
}
}
}
}
return this;
}
}
public FloatMatrix3D assign(final FloatMatrix3D y, final cern.colt.function.tfloat.FloatFloatFunction function) {
if (!(y instanceof DenseFloatMatrix3D)) {
super.assign(y, function);
return this;
}
checkShape(y);
final int zero = (int) index(0, 0, 0);
final int zeroOther = (int) y.index(0, 0, 0);
final int sliceStrideOther = y.sliceStride();
final int rowStrideOther = y.rowStride();
final int columnStrideOther = y.columnStride();
final float[] elementsOther = (float[]) y.elements();
int nthreads = ConcurrencyUtils.getNumberOfThreads();
if ((nthreads > 1) && (size() >= ConcurrencyUtils.getThreadsBeginN_3D())) {
nthreads = Math.min(nthreads, slices);
Future[] futures = new Future[nthreads];
int k = slices / nthreads;
for (int j = 0; j < nthreads; j++) {
final int firstSlice = j * k;
final int lastSlice = (j == nthreads - 1) ? slices : firstSlice + k;
futures[j] = ConcurrencyUtils.submit(new Runnable() {
public void run() {
int idx;
int idxOther;
for (int s = firstSlice; s < lastSlice; s++) {
for (int r = 0; r < rows; r++) {
idx = zero + s * sliceStride + r * rowStride;
idxOther = zeroOther + s * sliceStrideOther + r * rowStrideOther;
for (int c = 0; c < columns; c++) {
elements[idx] = function.apply(elements[idx], elementsOther[idxOther]);
idx += columnStride;
idxOther += columnStrideOther;
}
}
}
}
});
}
ConcurrencyUtils.waitForCompletion(futures);
} else {
int idx;
int idxOther;
for (int s = 0; s < slices; s++) {
for (int r = 0; r < rows; r++) {
idx = zero + s * sliceStride + r * rowStride;
idxOther = zeroOther + s * sliceStrideOther + r * rowStrideOther;
for (int c = 0; c < columns; c++) {
elements[idx] = function.apply(elements[idx], elementsOther[idxOther]);
idx += columnStride;
idxOther += columnStrideOther;
}
}
}
}
return this;
}
public FloatMatrix3D assign(final FloatMatrix3D y, final cern.colt.function.tfloat.FloatFloatFunction function,
final IntArrayList sliceList, final IntArrayList rowList, final IntArrayList columnList) {
if (!(y instanceof DenseFloatMatrix3D)) {
super.assign(y, function);
return this;
}
checkShape(y);
final int zero = (int) index(0, 0, 0);
final int zeroOther = (int) y.index(0, 0, 0);
final int sliceStrideOther = y.sliceStride();
final int rowStrideOther = y.rowStride();
final int columnStrideOther = y.columnStride();
final float[] elementsOther = (float[]) y.elements();
int size = sliceList.size();
final int[] sliceElements = sliceList.elements();
final int[] rowElements = rowList.elements();
final int[] columnElements = columnList.elements();
int nthreads = ConcurrencyUtils.getNumberOfThreads();
if ((nthreads > 1) && (size >= ConcurrencyUtils.getThreadsBeginN_3D())) {
nthreads = Math.min(nthreads, slices);
Future[] futures = new Future[nthreads];
int k = size / nthreads;
for (int j = 0; j < nthreads; j++) {
final int firstIdx = j * k;
final int lastIdx = (j == nthreads - 1) ? size : firstIdx + k;
futures[j] = ConcurrencyUtils.submit(new Runnable() {
public void run() {
for (int i = firstIdx; i < lastIdx; i++) {
int idx = zero + sliceElements[i] * sliceStride + rowElements[i] * rowStride
+ columnElements[i] * columnStride;
int idxOther = zeroOther + sliceElements[i] * sliceStrideOther + rowElements[i]
* rowStrideOther + columnElements[i] * columnStrideOther;
elements[idx] = function.apply(elements[idx], elementsOther[idxOther]);
}
}
});
}
ConcurrencyUtils.waitForCompletion(futures);
} else {
for (int i = 0; i < size; i++) {
int idx = zero + sliceElements[i] * sliceStride + rowElements[i] * rowStride + columnElements[i]
* columnStride;
int idxOther = zeroOther + sliceElements[i] * sliceStrideOther + rowElements[i] * rowStrideOther
+ columnElements[i] * columnStrideOther;
elements[idx] = function.apply(elements[idx], elementsOther[idxOther]);
}
}
return this;
}
public int cardinality() {
int cardinality = 0;
final int zero = (int) index(0, 0, 0);
int nthreads = ConcurrencyUtils.getNumberOfThreads();
if ((nthreads > 1) && (size() >= ConcurrencyUtils.getThreadsBeginN_3D())) {
nthreads = Math.min(nthreads, slices);
Future[] futures = new Future[nthreads];
Integer[] results = new Integer[nthreads];
int k = slices / nthreads;
for (int j = 0; j < nthreads; j++) {
final int firstSlice = j * k;
final int lastSlice = (j == nthreads - 1) ? slices : firstSlice + k;
futures[j] = ConcurrencyUtils.submit(new Callable() {
public Integer call() throws Exception {
int cardinality = 0;
int idx;
for (int s = firstSlice; s < lastSlice; s++) {
for (int r = 0; r < rows; r++) {
idx = zero + s * sliceStride + r * rowStride;
for (int c = 0; c < columns; c++) {
if (elements[idx] != 0) {
cardinality++;
}
idx += columnStride;
}
}
}
return Integer.valueOf(cardinality);
}
});
}
try {
for (int j = 0; j < nthreads; j++) {
results[j] = (Integer) futures[j].get();
}
cardinality = results[0];
for (int j = 1; j < nthreads; j++) {
cardinality += results[j];
}
} catch (ExecutionException ex) {
ex.printStackTrace();
} catch (InterruptedException e) {
e.printStackTrace();
}
} else {
int idx;
for (int s = 0; s < slices; s++) {
for (int r = 0; r < rows; r++) {
idx = zero + s * sliceStride + r * rowStride;
for (int c = 0; c < columns; c++) {
if (elements[idx] != 0) {
cardinality++;
}
idx += columnStride;
}
}
}
}
return cardinality;
}
/**
* Computes the 2D discrete cosine transform (DCT-II) of each slice of this
* matrix.
*
* @param scale
* if true then scaling is performed
*
*/
public void dct2Slices(final boolean scale) {
int oldNthreads = ConcurrencyUtils.getNumberOfThreads();
ConcurrencyUtils.setNumberOfThreads(ConcurrencyUtils.nextPow2(oldNthreads));
int nthreads = ConcurrencyUtils.getNumberOfThreads();
if ((nthreads > 1) && (size() >= ConcurrencyUtils.getThreadsBeginN_3D())) {
nthreads = Math.min(nthreads, slices);
Future[] futures = new Future[nthreads];
int k = slices / nthreads;
for (int j = 0; j < nthreads; j++) {
final int firstSlice = j * k;
final int lastSlice = (j == nthreads - 1) ? slices : firstSlice + k;
futures[j] = ConcurrencyUtils.submit(new Runnable() {
public void run() {
for (int s = firstSlice; s < lastSlice; s++) {
((DenseFloatMatrix2D) viewSlice(s)).dct2(scale);
}
}
});
}
ConcurrencyUtils.waitForCompletion(futures);
} else {
for (int s = 0; s < slices; s++) {
((DenseFloatMatrix2D) viewSlice(s)).dct2(scale);
}
}
ConcurrencyUtils.setNumberOfThreads(oldNthreads);
}
/**
* Computes the 3D discrete cosine transform (DCT-II) of this matrix.
*
* @param scale
* if true then scaling is performed
*
*/
public void dct3(boolean scale) {
int oldNthreads = ConcurrencyUtils.getNumberOfThreads();
ConcurrencyUtils.setNumberOfThreads(ConcurrencyUtils.nextPow2(oldNthreads));
if (dct3 == null) {
dct3 = new FloatDCT_3D(slices, rows, columns);
}
if (isNoView == true) {
dct3.forward(elements, scale);
} else {
FloatMatrix3D copy = this.copy();
dct3.forward((float[]) copy.elements(), scale);
this.assign((float[]) copy.elements());
}
ConcurrencyUtils.setNumberOfThreads(oldNthreads);
}
/**
* Computes the 2D discrete Hartley transform (DHT) of each slice of this
* matrix.
*
*/
public void dht2Slices() {
int oldNthreads = ConcurrencyUtils.getNumberOfThreads();
ConcurrencyUtils.setNumberOfThreads(ConcurrencyUtils.nextPow2(oldNthreads));
int nthreads = ConcurrencyUtils.getNumberOfThreads();
if ((nthreads > 1) && (size() >= ConcurrencyUtils.getThreadsBeginN_3D())) {
nthreads = Math.min(nthreads, slices);
Future[] futures = new Future[nthreads];
int k = slices / nthreads;
for (int j = 0; j < nthreads; j++) {
final int firstSlice = j * k;
final int lastSlice = (j == nthreads - 1) ? slices : firstSlice + k;
futures[j] = ConcurrencyUtils.submit(new Runnable() {
public void run() {
for (int s = firstSlice; s < lastSlice; s++) {
((DenseFloatMatrix2D) viewSlice(s)).dht2();
}
}
});
}
ConcurrencyUtils.waitForCompletion(futures);
} else {
for (int s = 0; s < slices; s++) {
((DenseFloatMatrix2D) viewSlice(s)).dht2();
}
}
ConcurrencyUtils.setNumberOfThreads(oldNthreads);
}
/**
* Computes the 3D discrete Hartley transform (DHT) of this matrix.
*
*/
public void dht3() {
int oldNthreads = ConcurrencyUtils.getNumberOfThreads();
ConcurrencyUtils.setNumberOfThreads(ConcurrencyUtils.nextPow2(oldNthreads));
if (dht3 == null) {
dht3 = new FloatDHT_3D(slices, rows, columns);
}
if (isNoView == true) {
dht3.forward(elements);
} else {
FloatMatrix3D copy = this.copy();
dht3.forward((float[]) copy.elements());
this.assign((float[]) copy.elements());
}
ConcurrencyUtils.setNumberOfThreads(oldNthreads);
}
/**
* Computes the 2D discrete sine transform (DST-II) of each slice of this
* matrix.
*
* @param scale
* if true then scaling is performed
*
*/
public void dst2Slices(final boolean scale) {
int oldNthreads = ConcurrencyUtils.getNumberOfThreads();
ConcurrencyUtils.setNumberOfThreads(ConcurrencyUtils.nextPow2(oldNthreads));
int nthreads = ConcurrencyUtils.getNumberOfThreads();
if ((nthreads > 1) && (size() >= ConcurrencyUtils.getThreadsBeginN_3D())) {
nthreads = Math.min(nthreads, slices);
Future[] futures = new Future[nthreads];
int k = slices / nthreads;
for (int j = 0; j < nthreads; j++) {
final int firstSlice = j * k;
final int lastSlice = (j == nthreads - 1) ? slices : firstSlice + k;
futures[j] = ConcurrencyUtils.submit(new Runnable() {
public void run() {
for (int s = firstSlice; s < lastSlice; s++) {
((DenseFloatMatrix2D) viewSlice(s)).dst2(scale);
}
}
});
}
ConcurrencyUtils.waitForCompletion(futures);
} else {
for (int s = 0; s < slices; s++) {
((DenseFloatMatrix2D) viewSlice(s)).dst2(scale);
}
}
ConcurrencyUtils.setNumberOfThreads(oldNthreads);
}
/**
* Computes the 3D discrete sine transform (DST-II) of this matrix.
*
* @param scale
* if true then scaling is performed
*
*/
public void dst3(boolean scale) {
int oldNthreads = ConcurrencyUtils.getNumberOfThreads();
ConcurrencyUtils.setNumberOfThreads(ConcurrencyUtils.nextPow2(oldNthreads));
if (dst3 == null) {
dst3 = new FloatDST_3D(slices, rows, columns);
}
if (isNoView == true) {
dst3.forward(elements, scale);
} else {
FloatMatrix3D copy = this.copy();
dst3.forward((float[]) copy.elements(), scale);
this.assign((float[]) copy.elements());
}
ConcurrencyUtils.setNumberOfThreads(oldNthreads);
}
public float[] elements() {
return elements;
}
/**
* Computes the 3D discrete Fourier transform (DFT) of this matrix. The
* physical layout of the output data is as follows:
*
*
* this[k1][k2][2*k3] = Re[k1][k2][k3]
* = Re[(n1-k1)%n1][(n2-k2)%n2][n3-k3],
* this[k1][k2][2*k3+1] = Im[k1][k2][k3]
* = -Im[(n1-k1)%n1][(n2-k2)%n2][n3-k3],
* 0<=k1<n1, 0<=k2<n2, 0<k3<n3/2,
* this[k1][k2][0] = Re[k1][k2][0]
* = Re[(n1-k1)%n1][n2-k2][0],
* this[k1][k2][1] = Im[k1][k2][0]
* = -Im[(n1-k1)%n1][n2-k2][0],
* this[k1][n2-k2][1] = Re[(n1-k1)%n1][k2][n3/2]
* = Re[k1][n2-k2][n3/2],
* this[k1][n2-k2][0] = -Im[(n1-k1)%n1][k2][n3/2]
* = Im[k1][n2-k2][n3/2],
* 0<=k1<n1, 0<k2<n2/2,
* this[k1][0][0] = Re[k1][0][0]
* = Re[n1-k1][0][0],
* this[k1][0][1] = Im[k1][0][0]
* = -Im[n1-k1][0][0],
* this[k1][n2/2][0] = Re[k1][n2/2][0]
* = Re[n1-k1][n2/2][0],
* this[k1][n2/2][1] = Im[k1][n2/2][0]
* = -Im[n1-k1][n2/2][0],
* this[n1-k1][0][1] = Re[k1][0][n3/2]
* = Re[n1-k1][0][n3/2],
* this[n1-k1][0][0] = -Im[k1][0][n3/2]
* = Im[n1-k1][0][n3/2],
* this[n1-k1][n2/2][1] = Re[k1][n2/2][n3/2]
* = Re[n1-k1][n2/2][n3/2],
* this[n1-k1][n2/2][0] = -Im[k1][n2/2][n3/2]
* = Im[n1-k1][n2/2][n3/2],
* 0<k1<n1/2,
* this[0][0][0] = Re[0][0][0],
* this[0][0][1] = Re[0][0][n3/2],
* this[0][n2/2][0] = Re[0][n2/2][0],
* this[0][n2/2][1] = Re[0][n2/2][n3/2],
* this[n1/2][0][0] = Re[n1/2][0][0],
* this[n1/2][0][1] = Re[n1/2][0][n3/2],
* this[n1/2][n2/2][0] = Re[n1/2][n2/2][0],
* this[n1/2][n2/2][1] = Re[n1/2][n2/2][n3/2]
*
*
*
* 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 getFft3. To get back the original
* data, use ifft3.
*
* @throws IllegalArgumentException
* if the slice size or the row size or the column size of this
* matrix is not a power of 2 number.
*/
public void fft3() {
int oldNthreads = ConcurrencyUtils.getNumberOfThreads();
ConcurrencyUtils.setNumberOfThreads(ConcurrencyUtils.nextPow2(oldNthreads));
if (fft3 == null) {
fft3 = new FloatFFT_3D(slices, rows, columns);
}
if (isNoView == true) {
fft3.realForward(elements);
} else {
FloatMatrix3D copy = this.copy();
fft3.realForward((float[]) copy.elements());
this.assign((float[]) copy.elements());
}
ConcurrencyUtils.setNumberOfThreads(oldNthreads);
}
/**
* Returns new complex matrix which is the 2D discrete Fourier transform
* (DFT) of each slice of this matrix.
*
* @return the 2D discrete Fourier transform (DFT) of each slice of this
* matrix.
*
*/
public DenseFComplexMatrix3D getFft2Slices() {
int oldNthreads = ConcurrencyUtils.getNumberOfThreads();
ConcurrencyUtils.setNumberOfThreads(ConcurrencyUtils.nextPow2(oldNthreads));
final DenseFComplexMatrix3D C = new DenseFComplexMatrix3D(slices, rows, columns);
int nthreads = ConcurrencyUtils.getNumberOfThreads();
if ((nthreads > 1) && (size() >= ConcurrencyUtils.getThreadsBeginN_3D())) {
nthreads = Math.min(nthreads, slices);
Future[] futures = new Future[nthreads];
int k = slices / nthreads;
for (int j = 0; j < nthreads; j++) {
final int firstSlice = j * k;
final int lastSlice = (j == nthreads - 1) ? slices : firstSlice + k;
futures[j] = ConcurrencyUtils.submit(new Runnable() {
public void run() {
for (int s = firstSlice; s < lastSlice; s++) {
C.viewSlice(s).assign(((DenseFloatMatrix2D) viewSlice(s)).getFft2());
}
}
});
}
ConcurrencyUtils.waitForCompletion(futures);
} else {
for (int s = 0; s < slices; s++) {
C.viewSlice(s).assign(((DenseFloatMatrix2D) viewSlice(s)).getFft2());
}
}
ConcurrencyUtils.setNumberOfThreads(oldNthreads);
return C;
}
/**
* Returns new complex matrix which is the 3D discrete Fourier transform
* (DFT) of this matrix.
*
* @return the 3D discrete Fourier transform (DFT) of this matrix.
*/
public DenseFComplexMatrix3D getFft3() {
int oldNthreads = ConcurrencyUtils.getNumberOfThreads();
ConcurrencyUtils.setNumberOfThreads(ConcurrencyUtils.nextPow2(oldNthreads));
DenseFComplexMatrix3D C = new DenseFComplexMatrix3D(slices, rows, columns);
final int sliceStride = rows * columns;
final int rowStride = columns;
final float[] elems;
if (isNoView == true) {
elems = elements;
} else {
elems = (float[]) this.copy().elements();
}
final float[] cElems = (C).elements();
int nthreads = ConcurrencyUtils.getNumberOfThreads();
if ((nthreads > 1) && (size() >= ConcurrencyUtils.getThreadsBeginN_3D())) {
nthreads = Math.min(nthreads, slices);
Future[] futures = new Future[nthreads];
int k = slices / nthreads;
for (int j = 0; j < nthreads; j++) {
final int firstSlice = j * k;
final int lastSlice = (j == nthreads - 1) ? slices : firstSlice + k;
futures[j] = ConcurrencyUtils.submit(new Runnable() {
public void run() {
int idx;
for (int s = firstSlice; s < lastSlice; s++) {
for (int r = 0; r < rows; r++) {
idx = s * sliceStride + r * rowStride;
System.arraycopy(elems, idx, cElems, idx, columns);
}
}
}
});
}
ConcurrencyUtils.waitForCompletion(futures);
} else {
int idx;
for (int s = 0; s < slices; s++) {
for (int r = 0; r < rows; r++) {
idx = s * sliceStride + r * rowStride;
System.arraycopy(elems, idx, cElems, idx, columns);
}
}
}
if (fft3 == null) {
fft3 = new FloatFFT_3D(slices, rows, columns);
}
fft3.realForwardFull(cElems);
ConcurrencyUtils.setNumberOfThreads(oldNthreads);
return C;
}
/**
* Returns new complex matrix which is the 2D inverse of the discrete
* Fourier transform (IDFT) of each slice of this matrix.
*
* @param scale
* if true then scaling is performed
*
* @return the 2D inverse of the discrete Fourier transform (IDFT) of each
* slice of this matrix.
*/
public DenseFComplexMatrix3D getIfft2Slices(final boolean scale) {
int oldNthreads = ConcurrencyUtils.getNumberOfThreads();
ConcurrencyUtils.setNumberOfThreads(ConcurrencyUtils.nextPow2(oldNthreads));
final DenseFComplexMatrix3D C = new DenseFComplexMatrix3D(slices, rows, columns);
int nthreads = ConcurrencyUtils.getNumberOfThreads();
if ((nthreads > 1) && (size() >= ConcurrencyUtils.getThreadsBeginN_3D())) {
nthreads = Math.min(nthreads, slices);
Future[] futures = new Future[nthreads];
int k = slices / nthreads;
for (int j = 0; j < nthreads; j++) {
final int firstSlice = j * k;
final int lastSlice = (j == nthreads - 1) ? slices : firstSlice + k;
futures[j] = ConcurrencyUtils.submit(new Runnable() {
public void run() {
for (int s = firstSlice; s < lastSlice; s++) {
C.viewSlice(s).assign(((DenseFloatMatrix2D) viewSlice(s)).getIfft2(scale));
}
}
});
}
ConcurrencyUtils.waitForCompletion(futures);
} else {
for (int s = 0; s < slices; s++) {
C.viewSlice(s).assign(((DenseFloatMatrix2D) viewSlice(s)).getIfft2(scale));
}
}
ConcurrencyUtils.setNumberOfThreads(oldNthreads);
return C;
}
/**
* Returns new complex matrix which is the 3D inverse of the discrete
* Fourier transform (IDFT) of this matrix.
*
* @param scale
* if true then scaling is performed
*
* @return the 3D inverse of the discrete Fourier transform (IDFT) of this
* matrix.
*
*/
public DenseFComplexMatrix3D getIfft3(boolean scale) {
int oldNthreads = ConcurrencyUtils.getNumberOfThreads();
ConcurrencyUtils.setNumberOfThreads(ConcurrencyUtils.nextPow2(oldNthreads));
DenseFComplexMatrix3D C = new DenseFComplexMatrix3D(slices, rows, columns);
final int sliceStride = rows * columns;
final int rowStride = columns;
final float[] cElems = (C).elements();
final float[] elems;
if (isNoView == true) {
elems = elements;
} else {
elems = (float[]) this.copy().elements();
}
int nthreads = ConcurrencyUtils.getNumberOfThreads();
if ((nthreads > 1) && (size() >= ConcurrencyUtils.getThreadsBeginN_3D())) {
nthreads = Math.min(nthreads, slices);
Future[] futures = new Future[nthreads];
int k = slices / nthreads;
for (int j = 0; j < nthreads; j++) {
final int firstSlice = j * k;
final int lastSlice = (j == nthreads - 1) ? slices : firstSlice + k;
futures[j] = ConcurrencyUtils.submit(new Runnable() {
public void run() {
int idx;
for (int s = firstSlice; s < lastSlice; s++) {
for (int r = 0; r < rows; r++) {
idx = s * sliceStride + r * rowStride;
System.arraycopy(elems, idx, cElems, idx, columns);
}
}
}
});
}
ConcurrencyUtils.waitForCompletion(futures);
} else {
int idx;
for (int s = 0; s < slices; s++) {
for (int r = 0; r < rows; r++) {
idx = s * sliceStride + r * rowStride;
System.arraycopy(elems, idx, cElems, idx, columns);
}
}
}
if (fft3 == null) {
fft3 = new FloatFFT_3D(slices, rows, columns);
}
fft3.realInverseFull(cElems, scale);
ConcurrencyUtils.setNumberOfThreads(oldNthreads);
return C;
}
public float[] getMaxLocation() {
final int zero = (int) index(0, 0, 0);
int slice_loc = 0;
int row_loc = 0;
int col_loc = 0;
float maxValue = 0;
int nthreads = ConcurrencyUtils.getNumberOfThreads();
if ((nthreads > 1) && (size() >= ConcurrencyUtils.getThreadsBeginN_3D())) {
nthreads = Math.min(nthreads, slices);
Future[] futures = new Future[nthreads];
float[][] results = new float[nthreads][2];
int k = slices / nthreads;
for (int j = 0; j < nthreads; j++) {
final int firstSlice = j * k;
final int lastSlice = (j == nthreads - 1) ? slices : firstSlice + k;
futures[j] = ConcurrencyUtils.submit(new Callable() {
public float[] call() throws Exception {
int slice_loc = firstSlice;
int row_loc = 0;
int col_loc = 0;
float maxValue = elements[zero + firstSlice * sliceStride];
int d = 1;
float elem;
for (int s = firstSlice; s < lastSlice; s++) {
for (int r = 0; r < rows; r++) {
for (int c = d; c < columns; c++) {
elem = elements[zero + s * sliceStride + r * rowStride + c * columnStride];
if (maxValue < elem) {
maxValue = elem;
slice_loc = s;
row_loc = r;
col_loc = c;
}
}
d = 0;
}
}
return new float[] { maxValue, slice_loc, row_loc, col_loc };
}
});
}
try {
for (int j = 0; j < nthreads; j++) {
results[j] = (float[]) futures[j].get();
}
maxValue = results[0][0];
slice_loc = (int) results[0][1];
row_loc = (int) results[0][2];
col_loc = (int) results[0][3];
for (int j = 1; j < nthreads; j++) {
if (maxValue < results[j][0]) {
maxValue = results[j][0];
slice_loc = (int) results[j][1];
row_loc = (int) results[j][2];
col_loc = (int) results[j][3];
}
}
} catch (ExecutionException ex) {
ex.printStackTrace();
} catch (InterruptedException e) {
e.printStackTrace();
}
} else {
maxValue = elements[zero];
float elem;
int d = 1;
for (int s = 0; s < slices; s++) {
for (int r = 0; r < rows; r++) {
for (int c = d; c < columns; c++) {
elem = elements[zero + s * sliceStride + r * rowStride + c * columnStride];
if (maxValue < elem) {
maxValue = elem;
slice_loc = s;
row_loc = r;
col_loc = c;
}
}
d = 0;
}
}
}
return new float[] { maxValue, slice_loc, row_loc, col_loc };
}
public float[] getMinLocation() {
final int zero = (int) index(0, 0, 0);
int slice_loc = 0;
int row_loc = 0;
int col_loc = 0;
float minValue = 0;
int nthreads = ConcurrencyUtils.getNumberOfThreads();
if ((nthreads > 1) && (size() >= ConcurrencyUtils.getThreadsBeginN_3D())) {
nthreads = Math.min(nthreads, slices);
Future[] futures = new Future[nthreads];
float[][] results = new float[nthreads][2];
int k = slices / nthreads;
for (int j = 0; j < nthreads; j++) {
final int firstSlice = j * k;
final int lastSlice = (j == nthreads - 1) ? slices : firstSlice + k;
futures[j] = ConcurrencyUtils.submit(new Callable() {
public float[] call() throws Exception {
int slice_loc = firstSlice;
int row_loc = 0;
int col_loc = 0;
float minValue = elements[zero + slice_loc * sliceStride];
int d = 1;
float elem;
for (int s = firstSlice; s < lastSlice; s++) {
for (int r = 0; r < rows; r++) {
for (int c = d; c < columns; c++) {
elem = elements[zero + s * sliceStride + r * rowStride + c * columnStride];
if (minValue > elem) {
minValue = elem;
slice_loc = s;
row_loc = r;
col_loc = c;
}
}
d = 0;
}
}
return new float[] { minValue, slice_loc, row_loc, col_loc };
}
});
}
try {
for (int j = 0; j < nthreads; j++) {
results[j] = (float[]) futures[j].get();
}
minValue = results[0][0];
slice_loc = (int) results[0][1];
row_loc = (int) results[0][2];
col_loc = (int) results[0][3];
for (int j = 1; j < nthreads; j++) {
if (minValue > results[j][0]) {
minValue = results[j][0];
slice_loc = (int) results[j][1];
row_loc = (int) results[j][2];
col_loc = (int) results[j][3];
}
}
} catch (ExecutionException ex) {
ex.printStackTrace();
} catch (InterruptedException e) {
e.printStackTrace();
}
} else {
minValue = elements[zero];
float elem;
int d = 1;
for (int s = 0; s < slices; s++) {
for (int r = 0; r < rows; r++) {
for (int c = d; c < columns; c++) {
elem = elements[zero + s * sliceStride + r * rowStride + c * columnStride];
if (minValue > elem) {
minValue = elem;
slice_loc = s;
row_loc = r;
col_loc = c;
}
}
d = 0;
}
}
}
return new float[] { minValue, slice_loc, row_loc, col_loc };
}
public void getNegativeValues(final IntArrayList sliceList, final IntArrayList rowList,
final IntArrayList columnList, final FloatArrayList valueList) {
sliceList.clear();
rowList.clear();
columnList.clear();
valueList.clear();
int zero = (int) index(0, 0, 0);
int idx;
for (int s = 0; s < slices; s++) {
for (int r = 0; r < rows; r++) {
idx = zero + s * sliceStride + r * rowStride;
for (int c = 0; c < columns; c++) {
float value = elements[idx];
if (value < 0) {
sliceList.add(s);
rowList.add(r);
columnList.add(c);
valueList.add(value);
}
idx += columnStride;
}
}
}
}
public void getNonZeros(final IntArrayList sliceList, final IntArrayList rowList, final IntArrayList columnList,
final FloatArrayList valueList) {
sliceList.clear();
rowList.clear();
columnList.clear();
valueList.clear();
int zero = (int) index(0, 0, 0);
int idx;
for (int s = 0; s < slices; s++) {
for (int r = 0; r < rows; r++) {
idx = zero + s * sliceStride + r * rowStride;
for (int c = 0; c < columns; c++) {
float value = elements[idx];
if (value != 0) {
sliceList.add(s);
rowList.add(r);
columnList.add(c);
valueList.add(value);
}
idx += columnStride;
}
}
}
}
public void getPositiveValues(final IntArrayList sliceList, final IntArrayList rowList,
final IntArrayList columnList, final FloatArrayList valueList) {
sliceList.clear();
rowList.clear();
columnList.clear();
valueList.clear();
int zero = (int) index(0, 0, 0);
int idx;
for (int s = 0; s < slices; s++) {
for (int r = 0; r < rows; r++) {
idx = zero + s * sliceStride + r * rowStride;
for (int c = 0; c < columns; c++) {
float value = elements[idx];
if (value > 0) {
sliceList.add(s);
rowList.add(r);
columnList.add(c);
valueList.add(value);
}
idx += columnStride;
}
}
}
}
public float getQuick(int slice, int row, int column) {
return elements[sliceZero + slice * sliceStride + rowZero + row * rowStride + columnZero + column
* columnStride];
}
/**
* Computes the 2D inverse of the discrete cosine transform (DCT-III) of
* each slice of this matrix.
*
* @param scale
* if true then scaling is performed
*/
public void idct2Slices(final boolean scale) {
int oldNthreads = ConcurrencyUtils.getNumberOfThreads();
ConcurrencyUtils.setNumberOfThreads(ConcurrencyUtils.nextPow2(oldNthreads));
int nthreads = ConcurrencyUtils.getNumberOfThreads();
if ((nthreads > 1) && (size() >= ConcurrencyUtils.getThreadsBeginN_3D())) {
nthreads = Math.min(nthreads, slices);
Future[] futures = new Future[nthreads];
int k = slices / nthreads;
for (int j = 0; j < nthreads; j++) {
final int firstSlice = j * k;
final int lastSlice = (j == nthreads - 1) ? slices : firstSlice + k;
futures[j] = ConcurrencyUtils.submit(new Runnable() {
public void run() {
for (int s = firstSlice; s < lastSlice; s++) {
((DenseFloatMatrix2D) viewSlice(s)).idct2(scale);
}
}
});
}
ConcurrencyUtils.waitForCompletion(futures);
} else {
for (int s = 0; s < slices; s++) {
((DenseFloatMatrix2D) viewSlice(s)).idct2(scale);
}
}
ConcurrencyUtils.setNumberOfThreads(oldNthreads);
}
/**
* Computes the 3D inverse of the discrete cosine transform (DCT-III) of
* this matrix.
*
* @param scale
* if true then scaling is performed
*/
public void idct3(boolean scale) {
int oldNthreads = ConcurrencyUtils.getNumberOfThreads();
ConcurrencyUtils.setNumberOfThreads(ConcurrencyUtils.nextPow2(oldNthreads));
if (dct3 == null) {
dct3 = new FloatDCT_3D(slices, rows, columns);
}
if (isNoView == true) {
dct3.inverse(elements, scale);
} else {
FloatMatrix3D copy = this.copy();
dct3.inverse((float[]) copy.elements(), scale);
this.assign((float[]) copy.elements());
}
ConcurrencyUtils.setNumberOfThreads(oldNthreads);
}
/**
* Computes the 2D inverse of the discrete Hartley transform (IDHT) of each
* slice of this matrix.
*
* @param scale
* if true then scaling is performed
*
*/
public void idht2Slices(final boolean scale) {
int oldNthreads = ConcurrencyUtils.getNumberOfThreads();
ConcurrencyUtils.setNumberOfThreads(ConcurrencyUtils.nextPow2(oldNthreads));
int nthreads = ConcurrencyUtils.getNumberOfThreads();
if ((nthreads > 1) && (size() >= ConcurrencyUtils.getThreadsBeginN_3D())) {
nthreads = Math.min(nthreads, slices);
Future[] futures = new Future[nthreads];
int k = slices / nthreads;
for (int j = 0; j < nthreads; j++) {
final int firstSlice = j * k;
final int lastSlice = (j == nthreads - 1) ? slices : firstSlice + k;
futures[j] = ConcurrencyUtils.submit(new Runnable() {
public void run() {
for (int s = firstSlice; s < lastSlice; s++) {
((DenseFloatMatrix2D) viewSlice(s)).idht2(scale);
}
}
});
}
ConcurrencyUtils.waitForCompletion(futures);
} else {
for (int s = 0; s < slices; s++) {
((DenseFloatMatrix2D) viewSlice(s)).idht2(scale);
}
}
ConcurrencyUtils.setNumberOfThreads(oldNthreads);
}
/**
* Computes the 3D inverse of the discrete Hartley transform (IDHT) of this
* matrix.
*
* @param scale
* if true then scaling is performed
*/
public void idht3(boolean scale) {
int oldNthreads = ConcurrencyUtils.getNumberOfThreads();
ConcurrencyUtils.setNumberOfThreads(ConcurrencyUtils.nextPow2(oldNthreads));
if (dht3 == null) {
dht3 = new FloatDHT_3D(slices, rows, columns);
}
if (isNoView == true) {
dht3.inverse(elements, scale);
} else {
FloatMatrix3D copy = this.copy();
dht3.inverse((float[]) copy.elements(), scale);
this.assign((float[]) copy.elements());
}
ConcurrencyUtils.setNumberOfThreads(oldNthreads);
}
/**
* Computes the 2D inverse of the discrete sine transform (DST-III) of each
* slice of this matrix.
*
* @param scale
* if true then scaling is performed
*/
public void idst2Slices(final boolean scale) {
int oldNthreads = ConcurrencyUtils.getNumberOfThreads();
ConcurrencyUtils.setNumberOfThreads(ConcurrencyUtils.nextPow2(oldNthreads));
int nthreads = ConcurrencyUtils.getNumberOfThreads();
if ((nthreads > 1) && (size() >= ConcurrencyUtils.getThreadsBeginN_3D())) {
nthreads = Math.min(nthreads, slices);
Future[] futures = new Future[nthreads];
int k = slices / nthreads;
for (int j = 0; j < nthreads; j++) {
final int firstSlice = j * k;
final int lastSlice = (j == nthreads - 1) ? slices : firstSlice + k;
futures[j] = ConcurrencyUtils.submit(new Runnable() {
public void run() {
for (int s = firstSlice; s < lastSlice; s++) {
((DenseFloatMatrix2D) viewSlice(s)).idst2(scale);
}
}
});
}
ConcurrencyUtils.waitForCompletion(futures);
} else {
for (int s = 0; s < slices; s++) {
((DenseFloatMatrix2D) viewSlice(s)).idst2(scale);
}
}
ConcurrencyUtils.setNumberOfThreads(oldNthreads);
}
/**
* Computes the 3D inverse of the discrete sine transform (DST-III) of this
* matrix.
*
* @param scale
* if true then scaling is performed
*
*/
public void idst3(boolean scale) {
int oldNthreads = ConcurrencyUtils.getNumberOfThreads();
ConcurrencyUtils.setNumberOfThreads(ConcurrencyUtils.nextPow2(oldNthreads));
if (dst3 == null) {
dst3 = new FloatDST_3D(slices, rows, columns);
}
if (isNoView == true) {
dst3.inverse(elements, scale);
} else {
FloatMatrix3D copy = this.copy();
dst3.inverse((float[]) copy.elements(), scale);
this.assign((float[]) copy.elements());
}
ConcurrencyUtils.setNumberOfThreads(oldNthreads);
}
/**
* Computes the 3D inverse of the discrete Fourier transform (IDFT) of this
* matrix. The physical layout of the input data has to be as follows:
*
*
* this[k1][k2][2*k3] = Re[k1][k2][k3]
* = Re[(n1-k1)%n1][(n2-k2)%n2][n3-k3],
* this[k1][k2][2*k3+1] = Im[k1][k2][k3]
* = -Im[(n1-k1)%n1][(n2-k2)%n2][n3-k3],
* 0<=k1<n1, 0<=k2<n2, 0<k3<n3/2,
* this[k1][k2][0] = Re[k1][k2][0]
* = Re[(n1-k1)%n1][n2-k2][0],
* this[k1][k2][1] = Im[k1][k2][0]
* = -Im[(n1-k1)%n1][n2-k2][0],
* this[k1][n2-k2][1] = Re[(n1-k1)%n1][k2][n3/2]
* = Re[k1][n2-k2][n3/2],
* this[k1][n2-k2][0] = -Im[(n1-k1)%n1][k2][n3/2]
* = Im[k1][n2-k2][n3/2],
* 0<=k1<n1, 0<k2<n2/2,
* this[k1][0][0] = Re[k1][0][0]
* = Re[n1-k1][0][0],
* this[k1][0][1] = Im[k1][0][0]
* = -Im[n1-k1][0][0],
* this[k1][n2/2][0] = Re[k1][n2/2][0]
* = Re[n1-k1][n2/2][0],
* this[k1][n2/2][1] = Im[k1][n2/2][0]
* = -Im[n1-k1][n2/2][0],
* this[n1-k1][0][1] = Re[k1][0][n3/2]
* = Re[n1-k1][0][n3/2],
* this[n1-k1][0][0] = -Im[k1][0][n3/2]
* = Im[n1-k1][0][n3/2],
* this[n1-k1][n2/2][1] = Re[k1][n2/2][n3/2]
* = Re[n1-k1][n2/2][n3/2],
* this[n1-k1][n2/2][0] = -Im[k1][n2/2][n3/2]
* = Im[n1-k1][n2/2][n3/2],
* 0<k1<n1/2,
* this[0][0][0] = Re[0][0][0],
* this[0][0][1] = Re[0][0][n3/2],
* this[0][n2/2][0] = Re[0][n2/2][0],
* this[0][n2/2][1] = Re[0][n2/2][n3/2],
* this[n1/2][0][0] = Re[n1/2][0][0],
* this[n1/2][0][1] = Re[n1/2][0][n3/2],
* this[n1/2][n2/2][0] = Re[n1/2][n2/2][0],
* this[n1/2][n2/2][1] = Re[n1/2][n2/2][n3/2]
*
*
* 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 getIfft3.
*
* @param scale
* if true then scaling is performed
*
* @throws IllegalArgumentException
* if the slice size or the row size or the column size of this
* matrix is not a power of 2 number.
*/
public void ifft3(boolean scale) {
int oldNthreads = ConcurrencyUtils.getNumberOfThreads();
ConcurrencyUtils.setNumberOfThreads(ConcurrencyUtils.nextPow2(oldNthreads));
if (fft3 == null) {
fft3 = new FloatFFT_3D(slices, rows, columns);
}
if (isNoView == true) {
fft3.realInverse(elements, scale);
} else {
FloatMatrix3D copy = this.copy();
fft3.realInverse((float[]) copy.elements(), scale);
this.assign((float[]) copy.elements());
}
ConcurrencyUtils.setNumberOfThreads(oldNthreads);
}
public long index(int slice, int row, int column) {
return sliceZero + slice * sliceStride + rowZero + row * rowStride + columnZero + column * columnStride;
}
public FloatMatrix3D like(int slices, int rows, int columns) {
return new DenseFloatMatrix3D(slices, rows, columns);
}
public FloatMatrix2D like2D(int rows, int columns) {
return new DenseFloatMatrix2D(rows, columns);
}
public void setQuick(int slice, int row, int column, float value) {
elements[sliceZero + slice * sliceStride + rowZero + row * rowStride + columnZero + column * columnStride] = value;
}
public float[][][] toArray() {
final float[][][] values = new float[slices][rows][columns];
int nthreads = ConcurrencyUtils.getNumberOfThreads();
final int zero = (int) index(0, 0, 0);
if ((nthreads > 1) && (size() >= ConcurrencyUtils.getThreadsBeginN_3D())) {
nthreads = Math.min(nthreads, slices);
Future[] futures = new Future[nthreads];
int k = slices / nthreads;
for (int j = 0; j < nthreads; j++) {
final int firstSlice = j * k;
final int lastSlice = (j == nthreads - 1) ? slices : firstSlice + k;
futures[j] = ConcurrencyUtils.submit(new Runnable() {
public void run() {
int idx;
for (int s = firstSlice; s < lastSlice; s++) {
float[][] currentSlice = values[s];
for (int r = 0; r < rows; r++) {
idx = zero + s * sliceStride + r * rowStride;
float[] currentRow = currentSlice[r];
for (int c = 0; c < columns; c++) {
currentRow[c] = elements[idx];
idx += columnStride;
}
}
}
}
});
}
ConcurrencyUtils.waitForCompletion(futures);
} else {
int idx;
for (int s = 0; s < slices; s++) {
float[][] currentSlice = values[s];
for (int r = 0; r < rows; r++) {
idx = zero + s * sliceStride + r * rowStride;
float[] currentRow = currentSlice[r];
for (int c = 0; c < columns; c++) {
currentRow[c] = elements[idx];
idx += columnStride;
}
}
}
}
return values;
}
public FloatMatrix1D vectorize() {
FloatMatrix1D v = new DenseFloatMatrix1D((int) size());
int length = rows * columns;
for (int s = 0; s < slices; s++) {
v.viewPart(s * length, length).assign(viewSlice(s).vectorize());
}
return v;
}
public void zAssign27Neighbors(FloatMatrix3D B, cern.colt.function.tfloat.Float27Function function) {
// overridden for performance only
if (!(B instanceof DenseFloatMatrix3D)) {
super.zAssign27Neighbors(B, function);
return;
}
if (function == null)
throw new NullPointerException("function must not be null.");
checkShape(B);
int r = rows - 1;
int c = columns - 1;
if (rows < 3 || columns < 3 || slices < 3)
return; // nothing to do
DenseFloatMatrix3D BB = (DenseFloatMatrix3D) B;
int A_ss = sliceStride;
int A_rs = rowStride;
int B_rs = BB.rowStride;
int A_cs = columnStride;
int B_cs = BB.columnStride;
float[] elems = this.elements;
float[] B_elems = BB.elements;
if (elems == null || B_elems == null)
throw new InternalError();
for (int k = 1; k < slices - 1; k++) {
int A_index = (int) index(k, 1, 1);
int B_index = (int) BB.index(k, 1, 1);
for (int i = 1; i < r; i++) {
int A002 = A_index - A_ss - A_rs - A_cs;
int A012 = A002 + A_rs;
int A022 = A012 + A_rs;
int A102 = A002 + A_ss;
int A112 = A102 + A_rs;
int A122 = A112 + A_rs;
int A202 = A102 + A_ss;
int A212 = A202 + A_rs;
int A222 = A212 + A_rs;
float a000, a001, a002;
float a010, a011, a012;
float a020, a021, a022;
float a100, a101, a102;
float a110, a111, a112;
float a120, a121, a122;
float a200, a201, a202;
float a210, a211, a212;
float a220, a221, a222;
a000 = elems[A002];
A002 += A_cs;
a001 = elems[A002];
a010 = elems[A012];
A012 += A_cs;
a011 = elems[A012];
a020 = elems[A022];
A022 += A_cs;
a021 = elems[A022];
a100 = elems[A102];
A102 += A_cs;
a101 = elems[A102];
a110 = elems[A112];
A112 += A_cs;
a111 = elems[A112];
a120 = elems[A122];
A122 += A_cs;
a121 = elems[A122];
a200 = elems[A202];
A202 += A_cs;
a201 = elems[A202];
a210 = elems[A212];
A212 += A_cs;
a211 = elems[A212];
a220 = elems[A222];
A222 += A_cs;
a221 = elems[A222];
int B11 = B_index;
for (int j = 1; j < c; j++) {
// in each step 18 cells can be remembered in registers -
// they don't need to be reread from slow memory
// in each step 9 instead of 27 cells need to be read from
// memory.
a002 = elems[A002 += A_cs];
a012 = elems[A012 += A_cs];
a022 = elems[A022 += A_cs];
a102 = elems[A102 += A_cs];
a112 = elems[A112 += A_cs];
a122 = elems[A122 += A_cs];
a202 = elems[A202 += A_cs];
a212 = elems[A212 += A_cs];
a222 = elems[A222 += A_cs];
B_elems[B11] = function.apply(a000, a001, a002, a010, a011, a012, a020, a021, a022,
a100, a101, a102, a110, a111, a112, a120, a121, a122,
a200, a201, a202, a210, a211, a212, a220, a221, a222);
B11 += B_cs;
// move remembered cells
a000 = a001;
a001 = a002;
a010 = a011;
a011 = a012;
a020 = a021;
a021 = a022;
a100 = a101;
a101 = a102;
a110 = a111;
a111 = a112;
a120 = a121;
a121 = a122;
a200 = a201;
a201 = a202;
a210 = a211;
a211 = a212;
a220 = a221;
a221 = a222;
}
A_index += A_rs;
B_index += B_rs;
}
}
}
public float zSum() {
float sum = 0;
final int zero = (int) index(0, 0, 0);
int nthreads = ConcurrencyUtils.getNumberOfThreads();
if ((nthreads > 1) && (size() >= ConcurrencyUtils.getThreadsBeginN_3D())) {
nthreads = Math.min(nthreads, slices);
Future[] futures = new Future[nthreads];
int k = slices / nthreads;
for (int j = 0; j < nthreads; j++) {
final int firstSlice = j * k;
final int lastSlice = (j == nthreads - 1) ? slices : firstSlice + k;
futures[j] = ConcurrencyUtils.submit(new Callable() {
public Float call() throws Exception {
float sum = 0;
int idx;
for (int s = firstSlice; s < lastSlice; s++) {
for (int r = 0; r < rows; r++) {
idx = zero + s * sliceStride + r * rowStride;
for (int c = 0; c < columns; c++) {
sum += elements[idx];
idx += columnStride;
}
}
}
return Float.valueOf(sum);
}
});
}
try {
for (int j = 0; j < nthreads; j++) {
sum = sum + ((Float) futures[j].get());
}
} catch (ExecutionException ex) {
ex.printStackTrace();
} catch (InterruptedException e) {
e.printStackTrace();
}
} else {
int idx;
for (int s = 0; s < slices; s++) {
for (int r = 0; r < rows; r++) {
idx = zero + s * sliceStride + r * rowStride;
for (int c = 0; c < columns; c++) {
sum += elements[idx];
idx += columnStride;
}
}
}
}
return sum;
}
protected boolean haveSharedCellsRaw(FloatMatrix3D other) {
if (other instanceof SelectedDenseFloatMatrix3D) {
SelectedDenseFloatMatrix3D otherMatrix = (SelectedDenseFloatMatrix3D) other;
return this.elements == otherMatrix.elements;
} else if (other instanceof DenseFloatMatrix3D) {
DenseFloatMatrix3D otherMatrix = (DenseFloatMatrix3D) other;
return this.elements == otherMatrix.elements;
}
return false;
}
protected FloatMatrix2D like2D(int rows, int columns, int rowZero, int columnZero, int rowStride, int columnStride) {
return new DenseFloatMatrix2D(rows, columns, this.elements, rowZero, columnZero, rowStride, columnStride, true);
}
protected FloatMatrix3D viewSelectionLike(int[] sliceOffsets, int[] rowOffsets, int[] columnOffsets) {
return new SelectedDenseFloatMatrix3D(this.elements, sliceOffsets, rowOffsets, columnOffsets, 0);
}
}