cern.colt.matrix.tlong.LongMatrix2D Maven / Gradle / Ivy
Show all versions of parallelcolt Show documentation
/*
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.tlong;
import java.util.Iterator;
import java.util.Set;
import java.util.concurrent.Callable;
import java.util.concurrent.ExecutionException;
import java.util.concurrent.Future;
import cern.colt.list.tint.IntArrayList;
import cern.colt.list.tlong.LongArrayList;
import cern.colt.matrix.AbstractMatrix2D;
import cern.colt.matrix.tlong.impl.DenseLongMatrix1D;
import cern.colt.matrix.tlong.impl.DenseLongMatrix2D;
import edu.emory.mathcs.utils.ConcurrencyUtils;
/**
* Abstract base class for 2-d matrices holding int elements. First see
* the package summary and javadoc tree view to get the broad picture.
*
* A matrix has a number of rows and columns, which are assigned upon instance
* construction - The matrix's size is then rows()*columns(). Elements
* are accessed via [row,column] coordinates. Legal coordinates range
* from [0,0] to [rows()-1,columns()-1]. Any attempt to access
* an element at a coordinate
* column<0 || column>=columns() || row<0 || row>=rows()
* will throw an IndexOutOfBoundsException.
*
* Note that this implementation is not synchronized.
*
* @author [email protected]
* @version 1.0, 09/24/99
*
* @author Piotr Wendykier ([email protected])
*
*/
public abstract class LongMatrix2D extends AbstractMatrix2D {
/**
*
*/
private static final long serialVersionUID = 1L;
/**
* Makes this class non instantiable, but still let's others inherit from
* it.
*/
protected LongMatrix2D() {
}
/**
* Applies a function to each cell and aggregates the results. Returns a
* value v such that v==a(size()) where
* a(i) == aggr( a(i-1), f(get(row,column)) ) and terminators are
* a(1) == f(get(0,0)), a(0)==Long.NaN.
*
* Example:
*
*
* cern.jet.math.Functions F = cern.jet.math.Functions.functions;
* 2 x 2 matrix
* 0 1
* 2 3
*
* // Sum( x[row,col]*x[row,col] )
* matrix.aggregate(F.plus,F.square);
* --> 14
*
*
*
* For further examples, see the package doc.
*
* @param aggr
* an aggregation function taking as first argument the current
* aggregation and as second argument the transformed current
* cell value.
* @param f
* a function transforming the current cell value.
* @return the aggregated measure.
* @see cern.jet.math.tlong.LongFunctions
*/
public long aggregate(final cern.colt.function.tlong.LongLongFunction aggr,
final cern.colt.function.tlong.LongFunction f) {
if (size() == 0)
throw new IllegalArgumentException("size == 0");
long a = 0;
int nthreads = ConcurrencyUtils.getNumberOfThreads();
if ((nthreads > 1) && (rows * columns >= ConcurrencyUtils.getThreadsBeginN_2D())) {
nthreads = Math.min(nthreads, rows);
Future[] futures = new Future[nthreads];
int k = rows / nthreads;
for (int j = 0; j < nthreads; j++) {
final int firstRow = j * k;
final int lastRow = (j == nthreads - 1) ? rows : firstRow + k;
futures[j] = ConcurrencyUtils.submit(new Callable() {
public Long call() throws Exception {
long a = f.apply(getQuick(firstRow, 0));
int d = 1;
for (int r = firstRow; r < lastRow; r++) {
for (int c = d; c < columns; c++) {
a = aggr.apply(a, f.apply(getQuick(r, c)));
}
d = 0;
}
return Long.valueOf(a);
}
});
}
a = ConcurrencyUtils.waitForCompletion(futures, aggr);
} else {
a = f.apply(getQuick(0, 0));
int d = 1; // first cell already done
for (int r = 0; r < rows; r++) {
for (int c = d; c < columns; c++) {
a = aggr.apply(a, f.apply(getQuick(r, c)));
}
d = 0;
}
}
return a;
}
/**
* Applies a function to each cell that satisfies a condition and aggregates
* the results.
*
* @param aggr
* an aggregation function taking as first argument the current
* aggregation and as second argument the transformed current
* cell value.
* @param f
* a function transforming the current cell value.
* @param cond
* a condition.
* @return the aggregated measure.
* @see cern.jet.math.tlong.LongFunctions
*/
public long aggregate(final cern.colt.function.tlong.LongLongFunction aggr,
final cern.colt.function.tlong.LongFunction f, final cern.colt.function.tlong.LongProcedure cond) {
if (size() == 0)
throw new IllegalArgumentException("size == 0");
long a = 0;
int nthreads = ConcurrencyUtils.getNumberOfThreads();
if ((nthreads > 1) && (rows * columns >= ConcurrencyUtils.getThreadsBeginN_2D())) {
nthreads = Math.min(nthreads, rows);
Future[] futures = new Future[nthreads];
int k = rows / nthreads;
for (int j = 0; j < nthreads; j++) {
final int firstRow = j * k;
final int lastRow = (j == nthreads - 1) ? rows : firstRow + k;
futures[j] = ConcurrencyUtils.submit(new Callable() {
public Long call() throws Exception {
long elem = getQuick(firstRow, 0);
long a = 0;
if (cond.apply(elem) == true) {
a = aggr.apply(a, f.apply(elem));
}
int d = 1;
for (int r = firstRow; r < lastRow; r++) {
for (int c = d; c < columns; c++) {
elem = getQuick(r, c);
if (cond.apply(elem) == true) {
a = aggr.apply(a, f.apply(elem));
}
}
d = 0;
}
return Long.valueOf(a);
}
});
}
a = ConcurrencyUtils.waitForCompletion(futures, aggr);
} else {
long elem = getQuick(0, 0);
if (cond.apply(elem) == true) {
a = aggr.apply(a, f.apply(elem));
}
int d = 1; // first cell already done
for (int r = 0; r < rows; r++) {
for (int c = d; c < columns; c++) {
elem = getQuick(r, c);
if (cond.apply(elem) == true) {
a = aggr.apply(a, f.apply(elem));
}
}
d = 0;
}
}
return a;
}
/**
*
* Applies a function to all cells with a given indexes and aggregates the
* results.
*
* @param aggr
* an aggregation function taking as first argument the current
* aggregation and as second argument the transformed current
* cell value.
* @param f
* a function transforming the current cell value.
* @param rowList
* row indexes.
* @param columnList
* column indexes.
*
* @return the aggregated measure.
* @see cern.jet.math.tlong.LongFunctions
*/
public long aggregate(final cern.colt.function.tlong.LongLongFunction aggr,
final cern.colt.function.tlong.LongFunction f, final IntArrayList rowList, final IntArrayList columnList) {
if (size() == 0)
throw new IllegalArgumentException("size == 0");
final int size = rowList.size();
final int[] rowElements = rowList.elements();
final int[] columnElements = columnList.elements();
long a = 0;
int nthreads = ConcurrencyUtils.getNumberOfThreads();
if ((nthreads > 1) && (size >= ConcurrencyUtils.getThreadsBeginN_2D())) {
nthreads = Math.min(nthreads, size);
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 Long call() throws Exception {
long a = f.apply(getQuick(rowElements[firstIdx], columnElements[firstIdx]));
long elem;
for (int i = firstIdx + 1; i < lastIdx; i++) {
elem = getQuick(rowElements[i], columnElements[i]);
a = aggr.apply(a, f.apply(elem));
}
return a;
}
});
}
a = ConcurrencyUtils.waitForCompletion(futures, aggr);
} else {
long elem;
a = f.apply(getQuick(rowElements[0], columnElements[0]));
for (int i = 1; i < size; i++) {
elem = getQuick(rowElements[i], columnElements[i]);
a = aggr.apply(a, f.apply(elem));
}
}
return a;
}
/**
* Applies a function to each corresponding cell of two matrices and
* aggregates the results. Returns a value v such that
* v==a(size()) where
* a(i) == aggr( a(i-1), f(get(row,column),other.get(row,column)) )
* and terminators are
* a(1) == f(get(0,0),other.get(0,0)), a(0)==Long.NaN.
*
* Example:
*
*
* cern.jet.math.Functions F = cern.jet.math.Functions.functions;
* x == 2 x 2 matrix
* 0 1
* 2 3
*
* y == 2 x 2 matrix
* 0 1
* 2 3
*
* // Sum( x[row,col] * y[row,col] )
* x.aggregate(y, F.plus, F.mult);
* --> 14
*
* // Sum( (x[row,col] + y[row,col])ˆ2 )
* x.aggregate(y, F.plus, F.chain(F.square,F.plus));
* --> 56
*
*
*
* For further examples, see the package doc.
*
* @param aggr
* an aggregation function taking as first argument the current
* aggregation and as second argument the transformed current
* cell values.
* @param f
* a function transforming the current cell values.
* @return the aggregated measure.
* @throws IllegalArgumentException
* if
* columns() != other.columns() || rows() != other.rows()
* @see cern.jet.math.tlong.LongFunctions
*/
public long aggregate(final LongMatrix2D other, final cern.colt.function.tlong.LongLongFunction aggr,
final cern.colt.function.tlong.LongLongFunction f) {
checkShape(other);
if (size() == 0)
throw new IllegalArgumentException("size == 0");
long a = 0;
int nthreads = ConcurrencyUtils.getNumberOfThreads();
if ((nthreads > 1) && (rows * columns >= ConcurrencyUtils.getThreadsBeginN_2D())) {
nthreads = Math.min(nthreads, rows);
Future[] futures = new Future[nthreads];
int k = rows / nthreads;
for (int j = 0; j < nthreads; j++) {
final int firstRow = j * k;
final int lastRow = (j == nthreads - 1) ? rows : firstRow + k;
futures[j] = ConcurrencyUtils.submit(new Callable() {
public Long call() throws Exception {
long a = f.apply(getQuick(firstRow, 0), other.getQuick(firstRow, 0));
int d = 1;
for (int r = firstRow; r < lastRow; r++) {
for (int c = d; c < columns; c++) {
a = aggr.apply(a, f.apply(getQuick(r, c), other.getQuick(r, c)));
}
d = 0;
}
return Long.valueOf(a);
}
});
}
a = ConcurrencyUtils.waitForCompletion(futures, aggr);
} else {
a = f.apply(getQuick(0, 0), other.getQuick(0, 0));
int d = 1; // first cell already done
for (int r = 0; r < rows; r++) {
for (int c = d; c < columns; c++) {
a = aggr.apply(a, f.apply(getQuick(r, c), other.getQuick(r, c)));
}
d = 0;
}
}
return a;
}
/**
* Assigns the result of a function to each cell;
* x[row,col] = function(x[row,col]).
*
* Example:
*
*
* matrix = 2 x 2 matrix
* 0.5 1.5
* 2.5 3.5
*
* // change each cell to its sine
* matrix.assign(cern.jet.math.Functions.sin);
* -->
* 2 x 2 matrix
* 0.479426 0.997495
* 0.598472 -0.350783
*
*
*
* For further examples, see the package doc.
*
* @param f
* a function object taking as argument the current cell's value.
* @return this (for convenience only).
* @see cern.jet.math.tlong.LongFunctions
*/
public LongMatrix2D assign(final cern.colt.function.tlong.LongFunction f) {
int nthreads = ConcurrencyUtils.getNumberOfThreads();
if ((nthreads > 1) && (rows * columns >= ConcurrencyUtils.getThreadsBeginN_2D())) {
nthreads = Math.min(nthreads, rows);
Future[] futures = new Future[nthreads];
int k = rows / nthreads;
for (int j = 0; j < nthreads; j++) {
final int firstRow = j * k;
final int lastRow = (j == nthreads - 1) ? rows : firstRow + k;
futures[j] = ConcurrencyUtils.submit(new Runnable() {
public void run() {
for (int r = firstRow; r < lastRow; r++) {
for (int c = 0; c < columns; c++) {
setQuick(r, c, f.apply(getQuick(r, c)));
}
}
}
});
}
ConcurrencyUtils.waitForCompletion(futures);
} else {
for (int r = 0; r < rows; r++) {
for (int c = 0; c < columns; c++) {
setQuick(r, c, f.apply(getQuick(r, c)));
}
}
}
return this;
}
/**
* Assigns the result of a function to all cells that satisfy a condition.
*
* @param cond
* a condition.
*
* @param f
* a function object.
* @return this (for convenience only).
* @see cern.jet.math.tlong.LongFunctions
*/
public LongMatrix2D assign(final cern.colt.function.tlong.LongProcedure cond,
final cern.colt.function.tlong.LongFunction f) {
int nthreads = ConcurrencyUtils.getNumberOfThreads();
if ((nthreads > 1) && (rows * columns >= ConcurrencyUtils.getThreadsBeginN_2D())) {
nthreads = Math.min(nthreads, rows);
Future[] futures = new Future[nthreads];
int k = rows / nthreads;
for (int j = 0; j < nthreads; j++) {
final int firstRow = j * k;
final int lastRow = (j == nthreads - 1) ? rows : firstRow + k;
futures[j] = ConcurrencyUtils.submit(new Runnable() {
public void run() {
long elem;
for (int r = firstRow; r < lastRow; r++) {
for (int c = 0; c < columns; c++) {
elem = getQuick(r, c);
if (cond.apply(elem) == true) {
setQuick(r, c, f.apply(elem));
}
}
}
}
});
}
ConcurrencyUtils.waitForCompletion(futures);
} else {
long elem;
for (int r = 0; r < rows; r++) {
for (int c = 0; c < columns; c++) {
elem = getQuick(r, c);
if (cond.apply(elem) == true) {
setQuick(r, c, f.apply(elem));
}
}
}
}
return this;
}
/**
* Assigns a value to all cells that satisfy a condition.
*
* @param cond
* a condition.
*
* @param value
* a value.
* @return this (for convenience only).
*
*/
public LongMatrix2D assign(final cern.colt.function.tlong.LongProcedure cond, final long value) {
int nthreads = ConcurrencyUtils.getNumberOfThreads();
if ((nthreads > 1) && (rows * columns >= ConcurrencyUtils.getThreadsBeginN_2D())) {
nthreads = Math.min(nthreads, rows);
Future[] futures = new Future[nthreads];
int k = rows / nthreads;
for (int j = 0; j < nthreads; j++) {
final int firstRow = j * k;
final int lastRow = (j == nthreads - 1) ? rows : firstRow + k;
futures[j] = ConcurrencyUtils.submit(new Runnable() {
public void run() {
long elem;
for (int r = firstRow; r < lastRow; r++) {
for (int c = 0; c < columns; c++) {
elem = getQuick(r, c);
if (cond.apply(elem) == true) {
setQuick(r, c, value);
}
}
}
}
});
}
ConcurrencyUtils.waitForCompletion(futures);
} else {
long elem;
for (int r = 0; r < rows; r++) {
for (int c = 0; c < columns; c++) {
elem = getQuick(r, c);
if (cond.apply(elem) == true) {
setQuick(r, c, value);
}
}
}
}
return this;
}
/**
* Sets all cells to the state specified by value.
*
* @param value
* the value to be filled into the cells.
* @return this (for convenience only).
*/
public LongMatrix2D assign(final long value) {
int nthreads = ConcurrencyUtils.getNumberOfThreads();
if ((nthreads > 1) && (rows * columns >= ConcurrencyUtils.getThreadsBeginN_2D())) {
nthreads = Math.min(nthreads, rows);
Future[] futures = new Future[nthreads];
int k = rows / nthreads;
for (int j = 0; j < nthreads; j++) {
final int firstRow = j * k;
final int lastRow = (j == nthreads - 1) ? rows : firstRow + k;
futures[j] = ConcurrencyUtils.submit(new Runnable() {
public void run() {
for (int r = firstRow; r < lastRow; r++) {
for (int c = 0; c < columns; c++) {
setQuick(r, c, value);
}
}
}
});
}
ConcurrencyUtils.waitForCompletion(futures);
} else {
for (int r = 0; r < rows; r++) {
for (int c = 0; c < columns; c++) {
setQuick(r, c, value);
}
}
}
return this;
}
/**
* Sets all cells to the state specified by values. values
* is required to have the form values[row*column] and elements
* have to be stored in a row-wise order.
*
* 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 cells.
* @return this (for convenience only).
* @throws IllegalArgumentException
* if values.length != rows()*columns().
*/
public LongMatrix2D assign(final long[] values) {
if (values.length != rows * columns)
throw new IllegalArgumentException("Must have same length: length=" + values.length + "rows()*columns()="
+ rows() * columns());
int nthreads = ConcurrencyUtils.getNumberOfThreads();
if ((nthreads > 1) && (rows * columns >= ConcurrencyUtils.getThreadsBeginN_2D())) {
nthreads = Math.min(nthreads, rows);
Future[] futures = new Future[nthreads];
int k = rows / nthreads;
for (int j = 0; j < nthreads; j++) {
final int firstRow = j * k;
final int lastRow = (j == nthreads - 1) ? rows : firstRow + k;
futures[j] = ConcurrencyUtils.submit(new Runnable() {
public void run() {
int idx = firstRow * columns;
for (int r = firstRow; r < lastRow; r++) {
for (int c = 0; c < columns; c++) {
setQuick(r, c, values[idx++]);
}
}
}
});
}
ConcurrencyUtils.waitForCompletion(futures);
} else {
int idx = 0;
for (int r = 0; r < rows; r++) {
for (int c = 0; c < columns; c++) {
setQuick(r, c, values[idx++]);
}
}
}
return this;
}
/**
* Sets all cells to the state specified by values. values
* is required to have the form values[row*column] and elements
* have to be stored in a row-wise order.
*
* 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 cells.
* @return this (for convenience only).
* @throws IllegalArgumentException
* if values.length != rows()*columns().
*/
public LongMatrix2D assign(final int[] values) {
if (values.length != rows * columns)
throw new IllegalArgumentException("Must have same length: length=" + values.length + "rows()*columns()="
+ rows() * columns());
int nthreads = ConcurrencyUtils.getNumberOfThreads();
if ((nthreads > 1) && (rows * columns >= ConcurrencyUtils.getThreadsBeginN_2D())) {
nthreads = Math.min(nthreads, rows);
Future[] futures = new Future[nthreads];
int k = rows / nthreads;
for (int j = 0; j < nthreads; j++) {
final int firstRow = j * k;
final int lastRow = (j == nthreads - 1) ? rows : firstRow + k;
futures[j] = ConcurrencyUtils.submit(new Runnable() {
public void run() {
int idx = firstRow * columns;
for (int r = firstRow; r < lastRow; r++) {
for (int c = 0; c < columns; c++) {
setQuick(r, c, values[idx++]);
}
}
}
});
}
ConcurrencyUtils.waitForCompletion(futures);
} else {
int idx = 0;
for (int r = 0; r < rows; r++) {
for (int c = 0; c < columns; c++) {
setQuick(r, c, values[idx++]);
}
}
}
return this;
}
/**
* Sets all cells to the state specified by values. values
* is required to have the form values[row][column] and have
* exactly the same number of rows and columns as the receiver.
*
* 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 cells.
* @return this (for convenience only).
* @throws IllegalArgumentException
* if
* values.length != rows() || for any 0 <= row < rows(): values[row].length != columns()
* .
*/
public LongMatrix2D assign(final long[][] values) {
if (values.length != rows)
throw new IllegalArgumentException("Must have same number of rows: rows=" + values.length + "rows()="
+ rows());
int nthreads = ConcurrencyUtils.getNumberOfThreads();
if ((nthreads > 1) && (rows * columns >= ConcurrencyUtils.getThreadsBeginN_2D())) {
nthreads = Math.min(nthreads, rows);
Future[] futures = new Future[nthreads];
int k = rows / nthreads;
for (int j = 0; j < nthreads; j++) {
final int firstRow = j * k;
final int lastRow = (j == nthreads - 1) ? rows : firstRow + k;
futures[j] = ConcurrencyUtils.submit(new Runnable() {
public void run() {
for (int r = firstRow; r < lastRow; r++) {
long[] currentRow = values[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++) {
setQuick(r, c, currentRow[c]);
}
}
}
});
}
ConcurrencyUtils.waitForCompletion(futures);
} else {
for (int r = 0; r < rows; r++) {
long[] currentRow = values[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++) {
setQuick(r, c, currentRow[c]);
}
}
}
return this;
}
/**
* Replaces all cell values of the receiver with the values of another
* matrix. Both matrices must have the same number of rows and columns. If
* both matrices share the same cells (as is the case if they are views
* derived from the same matrix) and intersect in an ambiguous way, then
* replaces as if using an intermediate auxiliary deep copy of
* other.
*
* @param other
* the source matrix to copy from (may be identical to the
* receiver).
* @return this (for convenience only).
* @throws IllegalArgumentException
* if
* columns() != other.columns() || rows() != other.rows()
*/
public LongMatrix2D assign(LongMatrix2D other) {
if (other == this)
return this;
checkShape(other);
final LongMatrix2D other_loc;
if (haveSharedCells(other)) {
other_loc = other.copy();
} else {
other_loc = other;
}
int nthreads = ConcurrencyUtils.getNumberOfThreads();
if ((nthreads > 1) && (rows * columns >= ConcurrencyUtils.getThreadsBeginN_2D())) {
nthreads = Math.min(nthreads, rows);
Future[] futures = new Future[nthreads];
int k = rows / nthreads;
for (int j = 0; j < nthreads; j++) {
final int firstRow = j * k;
final int lastRow = (j == nthreads - 1) ? rows : firstRow + k;
futures[j] = ConcurrencyUtils.submit(new Runnable() {
public void run() {
for (int r = firstRow; r < lastRow; r++) {
for (int c = 0; c < columns; c++) {
setQuick(r, c, other_loc.getQuick(r, c));
}
}
}
});
}
ConcurrencyUtils.waitForCompletion(futures);
} else {
for (int r = 0; r < rows; r++) {
for (int c = 0; c < columns; c++) {
setQuick(r, c, other_loc.getQuick(r, c));
}
}
}
return this;
}
/**
* Assigns the result of a function to each cell;
* x[row,col] = function(x[row,col],y[row,col]).
*
* Example:
*
*
* // assign x[row,col] = x[row,col]<sup>y[row,col]</sup>
* m1 = 2 x 2 matrix
* 0 1
* 2 3
*
* m2 = 2 x 2 matrix
* 0 2
* 4 6
*
* m1.assign(m2, cern.jet.math.Functions.pow);
* -->
* m1 == 2 x 2 matrix
* 1 1
* 16 729
*
*
*
* For further examples, see the package doc.
*
* @param y
* the secondary matrix to operate on.
* @param function
* a function object taking as first argument the current cell's
* value of this, and as second argument the current
* cell's value of y,
* @return this (for convenience only).
* @throws IllegalArgumentException
* if
* columns() != other.columns() || rows() != other.rows()
* @see cern.jet.math.tlong.LongFunctions
*/
public LongMatrix2D assign(final LongMatrix2D y, final cern.colt.function.tlong.LongLongFunction function) {
checkShape(y);
int nthreads = ConcurrencyUtils.getNumberOfThreads();
if ((nthreads > 1) && (rows * columns >= ConcurrencyUtils.getThreadsBeginN_2D())) {
nthreads = Math.min(nthreads, rows);
Future[] futures = new Future[nthreads];
int k = rows / nthreads;
for (int j = 0; j < nthreads; j++) {
final int firstRow = j * k;
final int lastRow = (j == nthreads - 1) ? rows : firstRow + k;
futures[j] = ConcurrencyUtils.submit(new Runnable() {
public void run() {
for (int r = firstRow; r < lastRow; r++) {
for (int c = 0; c < columns; c++) {
setQuick(r, c, function.apply(getQuick(r, c), y.getQuick(r, c)));
}
}
}
});
}
ConcurrencyUtils.waitForCompletion(futures);
} else {
for (int r = 0; r < rows; r++) {
for (int c = 0; c < columns; c++) {
setQuick(r, c, function.apply(getQuick(r, c), y.getQuick(r, c)));
}
}
}
return this;
}
/**
* Assigns the result of a function to all cells with a given indexes
*
* @param y
* the secondary matrix to operate on.
* @param function
* a function object taking as first argument the current cell's
* value of this, and as second argument the current
* cell's value of y,
* @param rowList
* row indexes.
* @param columnList
* column indexes.
*
* @return this (for convenience only).
* @throws IllegalArgumentException
* if
* columns() != other.columns() || rows() != other.rows()
* @see cern.jet.math.tlong.LongFunctions
*/
public LongMatrix2D assign(final LongMatrix2D y, final cern.colt.function.tlong.LongLongFunction function,
IntArrayList rowList, IntArrayList columnList) {
checkShape(y);
final int size = rowList.size();
final int[] rowElements = rowList.elements();
final int[] columnElements = columnList.elements();
int nthreads = ConcurrencyUtils.getNumberOfThreads();
if ((nthreads > 1) && (size >= ConcurrencyUtils.getThreadsBeginN_2D())) {
nthreads = Math.min(nthreads, size);
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++) {
setQuick(rowElements[i], columnElements[i], function.apply(getQuick(rowElements[i],
columnElements[i]), y.getQuick(rowElements[i], columnElements[i])));
}
}
});
}
ConcurrencyUtils.waitForCompletion(futures);
} else {
for (int i = 0; i < size; i++) {
setQuick(rowElements[i], columnElements[i], function.apply(getQuick(rowElements[i], columnElements[i]),
y.getQuick(rowElements[i], columnElements[i])));
}
}
return this;
}
/**
* Returns the number of cells having non-zero values; ignores tolerance.
*
* @return cardinality
*/
public int cardinality() {
int cardinality = 0;
int nthreads = ConcurrencyUtils.getNumberOfThreads();
if ((nthreads > 1) && (rows * columns >= ConcurrencyUtils.getThreadsBeginN_2D())) {
nthreads = Math.min(nthreads, rows);
Future[] futures = new Future[nthreads];
Integer[] results = new Integer[nthreads];
int k = rows / nthreads;
for (int j = 0; j < nthreads; j++) {
final int firstRow = j * k;
final int lastRow = (j == nthreads - 1) ? rows : firstRow + k;
futures[j] = ConcurrencyUtils.submit(new Callable() {
public Integer call() throws Exception {
int cardinality = 0;
for (int r = firstRow; r < lastRow; r++) {
for (int c = 0; c < columns; c++) {
if (getQuick(r, c) != 0)
cardinality++;
}
}
return cardinality;
}
});
}
try {
for (int j = 0; j < nthreads; j++) {
results[j] = (Integer) futures[j].get();
}
cardinality = results[0].intValue();
for (int j = 1; j < nthreads; j++) {
cardinality += results[j].intValue();
}
} catch (ExecutionException ex) {
ex.printStackTrace();
} catch (InterruptedException e) {
e.printStackTrace();
}
} else {
for (int r = 0; r < rows; r++) {
for (int c = 0; c < columns; c++) {
if (getQuick(r, c) != 0)
cardinality++;
}
}
}
return cardinality;
}
/**
* Constructs and returns a deep copy of the receiver.
*
* Note that the returned matrix is an independent deep copy. The
* returned matrix is not backed by this matrix, so changes in the returned
* matrix are not reflected in this matrix, and vice-versa.
*
* @return a deep copy of the receiver.
*/
public LongMatrix2D copy() {
return like().assign(this);
}
/**
* Returns the elements of this matrix.
*
* @return the elements
*/
public abstract Object elements();
/**
* Returns whether all cells are equal to the given value.
*
* @param value
* the value to test against.
* @return true if all cells are equal to the given value,
* false otherwise.
*/
public boolean equals(long value) {
return cern.colt.matrix.tlong.algo.LongProperty.DEFAULT.equals(this, value);
}
/**
* Compares this object against the specified object. The result is
* true if and only if the argument is not null
* and is at least a LongMatrix2D object that has the same
* number of columns and rows as the receiver and has exactly the same
* values at the same coordinates.
*
* @param obj
* the object to compare with.
* @return true if the objects are the same; false
* otherwise.
*/
public boolean equals(Object obj) {
if (this == obj)
return true;
if (obj == null)
return false;
if (!(obj instanceof LongMatrix2D))
return false;
return cern.colt.matrix.tlong.algo.LongProperty.DEFAULT.equals(this, (LongMatrix2D) obj);
}
/**
* Assigns the result of a function to each non-zero cell;
* x[row,col] = function(x[row,col]). Use this method for fast
* special-purpose iteration. If you want to modify another matrix instead
* of this (i.e. work in read-only mode), simply return the input
* value unchanged.
*
* Parameters to function are as follows: first==row,
* second==column, third==nonZeroValue.
*
* @param function
* a function object taking as argument the current non-zero
* cell's row, column and value.
* @return this (for convenience only).
*/
public LongMatrix2D forEachNonZero(final cern.colt.function.tlong.IntIntLongFunction function) {
int nthreads = ConcurrencyUtils.getNumberOfThreads();
if ((nthreads > 1) && (size() >= ConcurrencyUtils.getThreadsBeginN_2D())) {
nthreads = Math.min(nthreads, rows);
Future[] futures = new Future[nthreads];
int k = rows / nthreads;
for (int j = 0; j < nthreads; j++) {
final int firstRow = j * k;
final int lastRow = (j == nthreads - 1) ? rows : firstRow + k;
futures[j] = ConcurrencyUtils.submit(new Runnable() {
public void run() {
for (int r = firstRow; r < lastRow; r++) {
for (int c = 0; c < columns; c++) {
long value = getQuick(r, c);
if (value != 0) {
long a = function.apply(r, c, value);
if (a != value)
setQuick(r, c, a);
}
}
}
}
});
}
ConcurrencyUtils.waitForCompletion(futures);
} else {
for (int r = 0; r < rows; r++) {
for (int c = 0; c < columns; c++) {
long value = getQuick(r, c);
if (value != 0) {
long a = function.apply(r, c, value);
if (a != value)
setQuick(r, c, a);
}
}
}
}
return this;
}
/**
* Returns the matrix cell value at coordinate [row,column].
*
* @param row
* the index of the row-coordinate.
* @param column
* the index of the column-coordinate.
* @return the value of the specified cell.
* @throws IndexOutOfBoundsException
* if
* column<0 || column>=columns() || row<0 || row>=rows()
*/
public long get(int row, int column) {
if (column < 0 || column >= columns || row < 0 || row >= rows)
throw new IndexOutOfBoundsException("row:" + row + ", column:" + column);
return getQuick(row, column);
}
/**
* Returns the content of this matrix if it is a wrapper; or this
* otherwise. Override this method in wrappers.
*/
protected LongMatrix2D getContent() {
return this;
}
/**
* Fills the coordinates and values of cells having negative values into the
* specified lists. Fills into the lists, starting at index 0. After this
* call returns the specified lists all have a new size, the number of
* non-zero values.
*
* @param rowList
* the list to be filled with row indexes, can have any size.
* @param columnList
* the list to be filled with column indexes, can have any size.
* @param valueList
* the list to be filled with values, can have any size.
*/
public void getNegativeValues(final IntArrayList rowList, final IntArrayList columnList,
final LongArrayList valueList) {
rowList.clear();
columnList.clear();
valueList.clear();
for (int r = 0; r < rows; r++) {
for (int c = 0; c < columns; c++) {
long value = getQuick(r, c);
if (value < 0) {
rowList.add(r);
columnList.add(c);
valueList.add(value);
}
}
}
}
/**
* Fills the coordinates and values of cells having non-zero values into the
* specified lists. Fills into the lists, starting at index 0. After this
* call returns the specified lists all have a new size, the number of
* non-zero values.
*
* In general, fill order is unspecified. This implementation fills
* like for (row = 0..rows-1) for (column = 0..columns-1) do ... .
* However, subclasses are free to us any other order, even an order that
* may change over time as cell values are changed. (Of course, result lists
* indexes are guaranteed to correspond to the same cell).
*
* Example:
*
*
* 2 x 3 matrix:
* 0, 0, 8
* 0, 7, 0
* -->
* rowList = (0,1)
* columnList = (2,1)
* valueList = (8,7)
*
*
*
* In other words, get(0,2)==8, get(1,1)==7.
*
* @param rowList
* the list to be filled with row indexes, can have any size.
* @param columnList
* the list to be filled with column indexes, can have any size.
* @param valueList
* the list to be filled with values, can have any size.
*/
public void getNonZeros(final IntArrayList rowList, final IntArrayList columnList, final LongArrayList valueList) {
rowList.clear();
columnList.clear();
valueList.clear();
for (int r = 0; r < rows; r++) {
for (int c = 0; c < columns; c++) {
long value = getQuick(r, c);
if (value != 0) {
rowList.add(r);
columnList.add(c);
valueList.add(value);
}
}
}
}
/**
* Fills the coordinates and values of cells having positive values into the
* specified lists. Fills into the lists, starting at index 0. After this
* call returns the specified lists all have a new size, the number of
* non-zero values.
*
* @param rowList
* the list to be filled with row indexes, can have any size.
* @param columnList
* the list to be filled with column indexes, can have any size.
* @param valueList
* the list to be filled with values, can have any size.
*/
public void getPositiveValues(final IntArrayList rowList, final IntArrayList columnList,
final LongArrayList valueList) {
rowList.clear();
columnList.clear();
valueList.clear();
for (int r = 0; r < rows; r++) {
for (int c = 0; c < columns; c++) {
long value = getQuick(r, c);
if (value > 0) {
rowList.add(r);
columnList.add(c);
valueList.add(value);
}
}
}
}
/**
* Returns the matrix cell value at coordinate [row,column].
*
*
* Provided with invalid parameters this method may return invalid objects
* without throwing any exception. You should only use this method when
* you are absolutely sure that the coordinate is within bounds.
* Precondition (unchecked):
* 0 <= column < columns() && 0 <= row < rows().
*
* @param row
* the index of the row-coordinate.
* @param column
* the index of the column-coordinate.
* @return the value at the specified coordinate.
*/
public abstract long getQuick(int row, int column);
/**
* Returns true if both matrices share at least one identical cell.
*/
protected boolean haveSharedCells(LongMatrix2D other) {
if (other == null)
return false;
if (this == other)
return true;
return getContent().haveSharedCellsRaw(other.getContent());
}
/**
* Returns true if both matrices share at least one identical cell.
*/
protected boolean haveSharedCellsRaw(LongMatrix2D other) {
return false;
}
/**
* Construct and returns a new empty matrix of the same dynamic type
* as the receiver, having the same number of rows and columns. For example,
* if the receiver is an instance of type DenseLongMatrix2D the new
* matrix must also be of type DenseLongMatrix2D, if the receiver
* is an instance of type SparseLongMatrix2D the new matrix must
* also be of type SparseLongMatrix2D, etc. In general, the new
* matrix should have internal parametrization as similar as possible.
*
* @return a new empty matrix of the same dynamic type.
*/
public LongMatrix2D like() {
return like(rows, columns);
}
/**
* Construct and returns a new empty matrix of the same dynamic type
* as the receiver, having the specified number of rows and columns. For
* example, if the receiver is an instance of type
* DenseLongMatrix2D the new matrix must also be of type
* DenseLongMatrix2D, if the receiver is an instance of type
* SparseLongMatrix2D the new matrix must also be of type
* SparseLongMatrix2D, etc. In general, the new matrix should have
* internal parametrization as similar as possible.
*
* @param rows
* the number of rows the matrix shall have.
* @param columns
* the number of columns the matrix shall have.
* @return a new empty matrix of the same dynamic type.
*/
public abstract LongMatrix2D like(int rows, int columns);
/**
* Construct and returns a new 1-d matrix of the corresponding dynamic
* type, entirelly independent of the receiver. For example, if the
* receiver is an instance of type DenseLongMatrix2D the new matrix
* must be of type DenseLongMatrix1D, if the receiver is an
* instance of type SparseLongMatrix2D the new matrix must be of
* type SparseLongMatrix1D, etc.
*
* @param size
* the number of cells the matrix shall have.
* @return a new matrix of the corresponding dynamic type.
*/
public abstract LongMatrix1D like1D(int size);
/**
* Construct and returns a new 1-d matrix of the corresponding dynamic
* type, sharing the same cells. For example, if the receiver is an
* instance of type DenseLongMatrix2D the new matrix must be of
* type DenseLongMatrix1D, if the receiver is an instance of type
* SparseLongMatrix2D the new matrix must be of type
* SparseLongMatrix1D, etc.
*
* @param size
* the number of cells the matrix shall have.
* @param zero
* the index of the first element.
* @param stride
* the number of indexes between any two elements, i.e.
* index(i+1)-index(i).
* @return a new matrix of the corresponding dynamic type.
*/
protected abstract LongMatrix1D like1D(int size, int zero, int stride);
/**
* Return the maximum value of this matrix together with its location
*
* @return maximum_value, row_location, column_location };
*/
public long[] getMaxLocation() {
int rowLocation = 0;
int columnLocation = 0;
long maxValue = 0;
int nthreads = ConcurrencyUtils.getNumberOfThreads();
if ((nthreads > 1) && (size() >= ConcurrencyUtils.getThreadsBeginN_2D())) {
nthreads = Math.min(nthreads, rows);
Future[] futures = new Future[nthreads];
long[][] results = new long[nthreads][2];
int k = rows / nthreads;
for (int j = 0; j < nthreads; j++) {
final int firstRow = j * k;
final int lastRow = (j == nthreads - 1) ? rows : firstRow + k;
futures[j] = ConcurrencyUtils.submit(new Callable() {
public long[] call() throws Exception {
int rowLocation = firstRow;
int columnLocation = 0;
long maxValue = getQuick(rowLocation, 0);
int d = 1;
long elem;
for (int r = firstRow; r < lastRow; r++) {
for (int c = d; c < columns; c++) {
elem = getQuick(r, c);
if (maxValue < elem) {
maxValue = elem;
rowLocation = r;
columnLocation = c;
}
}
d = 0;
}
return new long[] { maxValue, rowLocation, columnLocation };
}
});
}
try {
for (int j = 0; j < nthreads; j++) {
results[j] = (long[]) futures[j].get();
}
maxValue = results[0][0];
rowLocation = (int) results[0][1];
columnLocation = (int) results[0][2];
for (int j = 1; j < nthreads; j++) {
if (maxValue < results[j][0]) {
maxValue = results[j][0];
rowLocation = (int) results[j][1];
columnLocation = (int) results[j][2];
}
}
} catch (ExecutionException ex) {
ex.printStackTrace();
} catch (InterruptedException e) {
e.printStackTrace();
}
} else {
maxValue = getQuick(0, 0);
long elem;
int d = 1;
for (int r = 0; r < rows; r++) {
for (int c = d; c < columns; c++) {
elem = getQuick(r, c);
if (maxValue < elem) {
maxValue = elem;
rowLocation = r;
columnLocation = c;
}
}
d = 0;
}
}
return new long[] { maxValue, rowLocation, columnLocation };
}
/**
* Return the minimum value of this matrix together with its location
*
* @return minimum_value, row_location, column_location};
*/
public long[] getMinLocation() {
int rowLocation = 0;
int columnLocation = 0;
long minValue = 0;
int nthreads = ConcurrencyUtils.getNumberOfThreads();
if ((nthreads > 1) && (size() >= ConcurrencyUtils.getThreadsBeginN_2D())) {
nthreads = Math.min(nthreads, rows);
Future[] futures = new Future[nthreads];
long[][] results = new long[nthreads][2];
int k = rows / nthreads;
for (int j = 0; j < nthreads; j++) {
final int firstRow = j * k;
final int lastRow = (j == nthreads - 1) ? rows : firstRow + k;
futures[j] = ConcurrencyUtils.submit(new Callable() {
public long[] call() throws Exception {
int rowLocation = firstRow;
int columnLocation = 0;
long minValue = getQuick(rowLocation, 0);
int d = 1;
long elem;
for (int r = firstRow; r < lastRow; r++) {
for (int c = d; c < columns; c++) {
elem = getQuick(r, c);
if (minValue > elem) {
minValue = elem;
rowLocation = r;
columnLocation = c;
}
}
d = 0;
}
return new long[] { minValue, rowLocation, columnLocation };
}
});
}
try {
for (int j = 0; j < nthreads; j++) {
results[j] = (long[]) futures[j].get();
}
minValue = results[0][0];
rowLocation = (int) results[0][1];
columnLocation = (int) results[0][2];
for (int j = 1; j < nthreads; j++) {
if (minValue > results[j][0]) {
minValue = results[j][0];
rowLocation = (int) results[j][1];
columnLocation = (int) results[j][2];
}
}
} catch (ExecutionException ex) {
ex.printStackTrace();
} catch (InterruptedException e) {
e.printStackTrace();
}
} else {
minValue = getQuick(0, 0);
long elem;
int d = 1;
for (int r = 0; r < rows; r++) {
for (int c = d; c < columns; c++) {
elem = getQuick(r, c);
if (minValue > elem) {
minValue = elem;
rowLocation = r;
columnLocation = c;
}
}
d = 0;
}
}
return new long[] { minValue, rowLocation, columnLocation };
}
/**
* Sets the matrix cell at coordinate [row,column] to the specified
* value.
*
* @param row
* the index of the row-coordinate.
* @param column
* the index of the column-coordinate.
* @param value
* the value to be filled into the specified cell.
* @throws IndexOutOfBoundsException
* if
* column<0 || column>=columns() || row<0 || row>=rows()
*/
public void set(int row, int column, long value) {
if (column < 0 || column >= columns || row < 0 || row >= rows)
throw new IndexOutOfBoundsException("row:" + row + ", column:" + column);
setQuick(row, column, value);
}
/**
* Sets the matrix cell at coordinate [row,column] to the specified
* value.
*
*
* Provided with invalid parameters this method may access illegal indexes
* without throwing any exception. You should only use this method when
* you are absolutely sure that the coordinate is within bounds.
* Precondition (unchecked):
* 0 <= column < columns() && 0 <= row < rows().
*
* @param row
* the index of the row-coordinate.
* @param column
* the index of the column-coordinate.
* @param value
* the value to be filled into the specified cell.
*/
public abstract void setQuick(int row, int column, long value);
/**
* Constructs and returns a 2-dimensional array containing the cell values.
* The returned array values has the form
* values[row][column] and has the same number of rows and columns
* as the receiver.
*
* The values are copied. So subsequent changes in values are not
* reflected in the matrix, and vice-versa.
*
* @return an array filled with the values of the cells.
*/
public long[][] toArray() {
final long[][] values = new long[rows][columns];
int nthreads = ConcurrencyUtils.getNumberOfThreads();
if ((nthreads > 1) && (size() >= ConcurrencyUtils.getThreadsBeginN_2D())) {
nthreads = Math.min(nthreads, rows);
Future[] futures = new Future[nthreads];
int k = rows / nthreads;
for (int j = 0; j < nthreads; j++) {
final int firstRow = j * k;
final int lastRow = (j == nthreads - 1) ? rows : firstRow + k;
futures[j] = ConcurrencyUtils.submit(new Runnable() {
public void run() {
for (int r = firstRow; r < lastRow; r++) {
long[] currentRow = values[r];
for (int c = 0; c < columns; c++) {
currentRow[c] = getQuick(r, c);
}
}
}
});
}
ConcurrencyUtils.waitForCompletion(futures);
} else {
for (int r = 0; r < rows; r++) {
long[] currentRow = values[r];
for (int c = 0; c < columns; c++) {
currentRow[c] = getQuick(r, c);
}
}
}
return values;
}
/**
* Returns a string representation using default formatting.
*
* @see cern.colt.matrix.tlong.algo.LongFormatter
*/
public String toString() {
return new cern.colt.matrix.tlong.algo.LongFormatter().toString(this);
}
/**
* Returns a vector obtained by stacking the columns of the matrix on top of
* one another.
*
* @return a vector of columns of this matrix.
*/
public abstract LongMatrix1D vectorize();
/**
* Constructs and returns a new view equal to the receiver. The view is a
* shallow clone. Calls clone() and casts the result.
*
* Note that the view is not a deep copy. The returned matrix is
* backed by this matrix, so changes in the returned matrix are reflected in
* this matrix, and vice-versa.
*
* Use {@link #copy()} to construct an independent deep copy rather than a
* new view.
*
* @return a new view of the receiver.
*/
protected LongMatrix2D view() {
return (LongMatrix2D) clone();
}
/**
* Constructs and returns a new slice view representing the rows of
* the given column. The returned view is backed by this matrix, so changes
* in the returned view are reflected in this matrix, and vice-versa. To
* obtain a slice view on subranges, construct a sub-ranging view (
* viewPart(...)), then apply this method to the sub-range view.
*
* Example:
*
*
* 2 x 3 matrix:
* 1, 2, 3
* 4, 5, 6
* viewColumn(0) ==>
* Matrix1D of size 2:
* 1, 4
*
*
*
* @param column
* the column to fix.
* @return a new slice view.
* @throws IndexOutOfBoundsException
* if column < 0 || column >= columns().
* @see #viewRow(int)
*/
public LongMatrix1D viewColumn(int column) {
checkColumn(column);
int viewSize = this.rows;
int viewZero = (int) index(0, column);
int viewStride = this.rowStride;
return like1D(viewSize, viewZero, viewStride);
}
/**
* Constructs and returns a new flip view along the column axis. What
* used to be column 0 is now column columns()-1, ...,
* what used to be column columns()-1 is now column 0. The
* returned view is backed by this matrix, so changes in the returned view
* are reflected in this matrix, and vice-versa.
*
* Example:
*
*
* 2 x 3 matrix:
* 1, 2, 3
* 4, 5, 6
* columnFlip ==>
* 2 x 3 matrix:
* 3, 2, 1
* 6, 5, 4
* columnFlip ==>
* 2 x 3 matrix:
* 1, 2, 3
* 4, 5, 6
*
*
*
* @return a new flip view.
* @see #viewRowFlip()
*/
public LongMatrix2D viewColumnFlip() {
return (LongMatrix2D) (view().vColumnFlip());
}
/**
* Constructs and returns a new dice (transposition) view; Swaps
* axes; example: 3 x 4 matrix --> 4 x 3 matrix. The view has both
* dimensions exchanged; what used to be columns become rows, what used to
* be rows become columns. In other words:
* view.get(row,column)==this.get(column,row). This is a zero-copy
* transposition, taking O(1), i.e. constant time. The returned view is
* backed by this matrix, so changes in the returned view are reflected in
* this matrix, and vice-versa. Use idioms like
* result = viewDice(A).copy() to generate an independent
* transposed matrix.
*
* Example:
*
*
* 2 x 3 matrix:
* 1, 2, 3
* 4, 5, 6
* transpose ==>
* 3 x 2 matrix:
* 1, 4
* 2, 5
* 3, 6
* transpose ==>
* 2 x 3 matrix:
* 1, 2, 3
* 4, 5, 6
*
*
*
* @return a new dice view.
*/
public LongMatrix2D viewDice() {
return (LongMatrix2D) (view().vDice());
}
/**
* Constructs and returns a new sub-range view that is a
* height x width sub matrix starting at [row,column].
*
* Operations on the returned view can only be applied to the restricted
* range. Any attempt to access coordinates not contained in the view will
* throw an IndexOutOfBoundsException.
*
* Note that the view is really just a range restriction: The
* returned matrix is backed by this matrix, so changes in the returned
* matrix are reflected in this matrix, and vice-versa.
*
* The view contains the cells from [row,column] to
* [row+height-1,column+width-1], all inclusive. and has
* view.rows() == height; view.columns() == width;. A view's legal
* coordinates are again zero based, as usual. In other words, legal
* coordinates of the view range from [0,0] to
* [view.rows()-1==height-1,view.columns()-1==width-1]. As usual,
* any attempt to access a cell at a coordinate
* column<0 || column>=view.columns() || row<0 || row>=view.rows()
* will throw an IndexOutOfBoundsException.
*
* @param row
* The index of the row-coordinate.
* @param column
* The index of the column-coordinate.
* @param height
* The height of the box.
* @param width
* The width of the box.
* @throws IndexOutOfBoundsException
* if
* column<0 || width<0 || column+width>columns() || row<0 || height<0 || row+height>rows()
* @return the new view.
*
*/
public LongMatrix2D viewPart(int row, int column, int height, int width) {
return (LongMatrix2D) (view().vPart(row, column, height, width));
}
/**
* Constructs and returns a new slice view representing the columns
* of the given row. The returned view is backed by this matrix, so changes
* in the returned view are reflected in this matrix, and vice-versa. To
* obtain a slice view on subranges, construct a sub-ranging view (
* viewPart(...)), then apply this method to the sub-range view.
*
* Example:
*
*
* 2 x 3 matrix:
* 1, 2, 3
* 4, 5, 6
* viewRow(0) ==>
* Matrix1D of size 3:
* 1, 2, 3
*
*
*
* @param row
* the row to fix.
* @return a new slice view.
* @throws IndexOutOfBoundsException
* if row < 0 || row >= rows().
* @see #viewColumn(int)
*/
public LongMatrix1D viewRow(int row) {
checkRow(row);
int viewSize = this.columns;
int viewZero = (int) index(row, 0);
int viewStride = this.columnStride;
return like1D(viewSize, viewZero, viewStride);
}
/**
* Constructs and returns a new flip view along the row axis. What
* used to be row 0 is now row rows()-1, ..., what used to
* be row rows()-1 is now row 0. The returned view is
* backed by this matrix, so changes in the returned view are reflected in
* this matrix, and vice-versa.
*
* Example:
*
*
* 2 x 3 matrix:
* 1, 2, 3
* 4, 5, 6
* rowFlip ==>
* 2 x 3 matrix:
* 4, 5, 6
* 1, 2, 3
* rowFlip ==>
* 2 x 3 matrix:
* 1, 2, 3
* 4, 5, 6
*
*
*
* @return a new flip view.
* @see #viewColumnFlip()
*/
public LongMatrix2D viewRowFlip() {
return (LongMatrix2D) (view().vRowFlip());
}
/**
* Constructs and returns a new selection view that is a matrix
* holding all rows matching the given condition. Applies the
* condition to each row and takes only those row where
* condition.apply(viewRow(i)) yields true. To match
* columns, use a dice view.
*
* Example:
*
*
* // extract and view all rows which have a value < threshold in the first column (representing "age")
* final int threshold = 16;
* matrix.viewSelection(
* new LongMatrix1DProcedure() {
* public final boolean apply(LongMatrix1D m) { return m.get(0) < threshold; }
* }
* );
*
* // extract and view all rows with RMS < threshold
* // The RMS (Root-Mean-Square) is a measure of the average "size" of the elements of a data sequence.
* matrix = 0 1 2 3
* final int threshold = 0.5;
* matrix.viewSelection(
* new LongMatrix1DProcedure() {
* public final boolean apply(LongMatrix1D m) { return Math.sqrt(m.aggregate(F.plus,F.square) / m.size()) < threshold; }
* }
* );
*
*
*
* For further examples, see the package doc. The returned
* view is backed by this matrix, so changes in the returned view are
* reflected in this matrix, and vice-versa.
*
* @param condition
* The condition to be matched.
* @return the new view.
*/
public LongMatrix2D viewSelection(LongMatrix1DProcedure condition) {
IntArrayList matches = new IntArrayList();
for (int i = 0; i < rows; i++) {
if (condition.apply(viewRow(i)))
matches.add(i);
}
matches.trimToSize();
return viewSelection(matches.elements(), null); // take all columns
}
/**
* Constructs and returns a new selection view that is a matrix
* holding the indicated cells. There holds
* view.rows() == rowIndexes.length, view.columns() == columnIndexes.length
* and view.get(i,j) == this.get(rowIndexes[i],columnIndexes[j]).
* Indexes can occur multiple times and can be in arbitrary order.
*
* Example:
*
*
* this = 2 x 3 matrix:
* 1, 2, 3
* 4, 5, 6
* rowIndexes = (0,1)
* columnIndexes = (1,0,1,0)
* -->
* view = 2 x 4 matrix:
* 2, 1, 2, 1
* 5, 4, 5, 4
*
*
*
* Note that modifying the index arguments after this call has returned has
* no effect on the view. The returned view is backed by this matrix, so
* changes in the returned view are reflected in this matrix, and
* vice-versa.
*
* To indicate "all" rows or "all columns", simply set the respective
* parameter
*
* @param rowIndexes
* The rows of the cells that shall be visible in the new view.
* To indicate that all rows shall be visible, simply set
* this parameter to null.
* @param columnIndexes
* The columns of the cells that shall be visible in the new
* view. To indicate that all columns shall be visible,
* simply set this parameter to null.
* @return the new view.
* @throws IndexOutOfBoundsException
* if !(0 <= rowIndexes[i] < rows()) for any
* i=0..rowIndexes.length()-1.
* @throws IndexOutOfBoundsException
* if !(0 <= columnIndexes[i] < columns()) for any
* i=0..columnIndexes.length()-1.
*/
public LongMatrix2D viewSelection(int[] rowIndexes, int[] columnIndexes) {
// check for "all"
if (rowIndexes == null) {
rowIndexes = new int[rows];
for (int i = 0; i < rows; i++)
rowIndexes[i] = i;
}
if (columnIndexes == null) {
columnIndexes = new int[columns];
for (int i = 0; i < columns; i++)
columnIndexes[i] = i;
}
checkRowIndexes(rowIndexes);
checkColumnIndexes(columnIndexes);
int[] rowOffsets = new int[rowIndexes.length];
int[] columnOffsets = new int[columnIndexes.length];
for (int i = 0; i < rowIndexes.length; i++) {
rowOffsets[i] = _rowOffset(_rowRank(rowIndexes[i]));
}
for (int i = 0; i < columnIndexes.length; i++) {
columnOffsets[i] = _columnOffset(_columnRank(columnIndexes[i]));
}
return viewSelectionLike(rowOffsets, columnOffsets);
}
public LongMatrix2D viewSelection(Set indexes) {
int n = indexes.size();
int[] rowIndexes = new int[n];
int[] columnIndexes = new int[n];
int idx = 0;
for (Iterator iterator = indexes.iterator(); iterator.hasNext();) {
int[] is = iterator.next();
rowIndexes[idx] = is[0];
columnIndexes[idx] = is[1];
idx++;
}
checkRowIndexes(rowIndexes);
checkColumnIndexes(columnIndexes);
int[] rowOffsets = new int[rowIndexes.length];
int[] columnOffsets = new int[columnIndexes.length];
for (int i = 0; i < rowIndexes.length; i++) {
rowOffsets[i] = _rowOffset(_rowRank(rowIndexes[i]));
}
for (int i = 0; i < columnIndexes.length; i++) {
columnOffsets[i] = _columnOffset(_columnRank(columnIndexes[i]));
}
return viewSelectionLike(rowOffsets, columnOffsets);
}
/**
* Construct and returns a new selection view.
*
* @param rowOffsets
* the offsets of the visible elements.
* @param columnOffsets
* the offsets of the visible elements.
* @return a new view.
*/
protected abstract LongMatrix2D viewSelectionLike(int[] rowOffsets, int[] columnOffsets);
/**
* Sorts the matrix rows into ascending order, according to the natural
* ordering of the matrix values in the given column. This sort is
* guaranteed to be stable. For further information, see
* {@link cern.colt.matrix.tlong.algo.LongSorting#sort(LongMatrix2D,int)}.
* For more advanced sorting functionality, see
* {@link cern.colt.matrix.tlong.algo.LongSorting}.
*
* @return a new sorted vector (matrix) view.
* @throws IndexOutOfBoundsException
* if column < 0 || column >= columns().
*/
public LongMatrix2D viewSorted(int column) {
return cern.colt.matrix.tlong.algo.LongSorting.mergeSort.sort(this, column);
}
/**
* Constructs and returns a new stride view which is a sub matrix
* consisting of every i-th cell. More specifically, the view has
* this.rows()/rowStride rows and
* this.columns()/columnStride columns holding cells
* this.get(i*rowStride,j*columnStride) for all
* i = 0..rows()/rowStride - 1, j = 0..columns()/columnStride - 1.
* The returned view is backed by this matrix, so changes in the returned
* view are reflected in this matrix, and vice-versa.
*
* @param rowStride
* the row step factor.
* @param columnStride
* the column step factor.
* @return a new view.
* @throws IndexOutOfBoundsException
* if rowStride<=0 || columnStride<=0.
*/
public LongMatrix2D viewStrides(int rowStride, int columnStride) {
return (LongMatrix2D) (view().vStrides(rowStride, columnStride));
}
/**
* Linear algebraic matrix-vector multiplication; z = A * y;
* Equivalent to return A.zMult(y,z,1,0);
*/
public LongMatrix1D zMult(LongMatrix1D y, LongMatrix1D z) {
return zMult(y, z, 1, (z == null ? 1 : 0), false);
}
/**
* Linear algebraic matrix-vector multiplication;
* z = alpha * A * y + beta*z.
* z[i] = alpha*Sum(A[i,j] * y[j]) + beta*z[i], i=0..A.rows()-1, j=0..y.size()-1
* . Where A == this.
* Note: Matrix shape conformance is checked after potential
* transpositions.
*
* @param y
* the source vector.
* @param z
* the vector where results are to be stored. Set this parameter
* to null to indicate that a new result vector shall be
* constructed.
* @return z (for convenience only).
*
* @throws IllegalArgumentException
* if A.columns() != y.size() || A.rows() > z.size()).
*/
public LongMatrix1D zMult(final LongMatrix1D y, LongMatrix1D z, final long alpha, final long beta,
final boolean transposeA) {
if (transposeA)
return viewDice().zMult(y, z, alpha, beta, false);
final LongMatrix1D z_loc;
if (z == null) {
z_loc = new DenseLongMatrix1D(this.rows);
} else {
z_loc = z;
}
if (columns != y.size() || rows > z_loc.size())
throw new IllegalArgumentException("Incompatible args: " + toStringShort() + ", " + y.toStringShort()
+ ", " + z_loc.toStringShort());
int nthreads = ConcurrencyUtils.getNumberOfThreads();
if ((nthreads > 1) && (size() >= ConcurrencyUtils.getThreadsBeginN_2D())) {
nthreads = Math.min(nthreads, rows);
Future[] futures = new Future[nthreads];
int k = rows / nthreads;
for (int j = 0; j < nthreads; j++) {
final int firstRow = j * k;
final int lastRow = (j == nthreads - 1) ? rows : firstRow + k;
futures[j] = ConcurrencyUtils.submit(new Runnable() {
public void run() {
for (int r = firstRow; r < lastRow; r++) {
int s = 0;
for (int c = 0; c < columns; c++) {
s += getQuick(r, c) * y.getQuick(c);
}
z_loc.setQuick(r, alpha * s + beta * z_loc.getQuick(r));
}
}
});
}
ConcurrencyUtils.waitForCompletion(futures);
} else {
for (int r = 0; r < rows; r++) {
int s = 0;
for (int c = 0; c < columns; c++) {
s += getQuick(r, c) * y.getQuick(c);
}
z_loc.setQuick(r, alpha * s + beta * z_loc.getQuick(r));
}
}
return z_loc;
}
/**
* Linear algebraic matrix-matrix multiplication; C = A x B;
* Equivalent to A.zMult(B,C,1,0,false,false).
*/
public LongMatrix2D zMult(LongMatrix2D B, LongMatrix2D C) {
return zMult(B, C, 1, (C == null ? 1 : 0), false, false);
}
/**
* Linear algebraic matrix-matrix multiplication;
* C = alpha * A x B + beta*C.
* C[i,j] = alpha*Sum(A[i,k] * B[k,j]) + beta*C[i,j], k=0..n-1.
* Matrix shapes: A(m x n), B(n x p), C(m x p).
* Note: Matrix shape conformance is checked after potential
* transpositions.
*
* @param B
* the second source matrix.
* @param C
* the matrix where results are to be stored. Set this parameter
* to null to indicate that a new result matrix shall be
* constructed.
* @return C (for convenience only).
*
* @throws IllegalArgumentException
* if B.rows() != A.columns().
* @throws IllegalArgumentException
* if
* C.rows() != A.rows() || C.columns() != B.columns().
* @throws IllegalArgumentException
* if A == C || B == C.
*/
public LongMatrix2D zMult(final LongMatrix2D B, LongMatrix2D C, final long alpha, final long beta,
final boolean transposeA, final boolean transposeB) {
if (transposeA)
return viewDice().zMult(B, C, alpha, beta, false, transposeB);
if (transposeB)
return this.zMult(B.viewDice(), C, alpha, beta, transposeA, false);
final int m = rows;
final int n = columns;
final int p = B.columns;
final LongMatrix2D C_loc;
if (C == null) {
C_loc = new DenseLongMatrix2D(m, p);
} else {
C_loc = C;
}
if (B.rows != n)
throw new IllegalArgumentException("Matrix2D inner dimensions must agree:" + toStringShort() + ", "
+ B.toStringShort());
if (C_loc.rows != m || C_loc.columns != p)
throw new IllegalArgumentException("Incompatibe result matrix: " + toStringShort() + ", "
+ B.toStringShort() + ", " + C_loc.toStringShort());
if (this == C_loc || B == C_loc)
throw new IllegalArgumentException("Matrices must not be identical");
int nthreads = ConcurrencyUtils.getNumberOfThreads();
if ((nthreads > 1) && (size() >= ConcurrencyUtils.getThreadsBeginN_2D())) {
nthreads = Math.min(nthreads, p);
Future[] futures = new Future[nthreads];
int k = p / nthreads;
for (int j = 0; j < nthreads; j++) {
final int firstIdx = j * k;
final int lastIdx = (j == nthreads - 1) ? p : firstIdx + k;
futures[j] = ConcurrencyUtils.submit(new Runnable() {
public void run() {
for (int a = firstIdx; a < lastIdx; a++) {
for (int b = 0; b < m; b++) {
int s = 0;
for (int c = 0; c < n; c++) {
s += getQuick(b, c) * B.getQuick(c, a);
}
C_loc.setQuick(b, a, alpha * s + beta * C_loc.getQuick(b, a));
}
}
}
});
}
ConcurrencyUtils.waitForCompletion(futures);
} else {
for (int a = 0; a < p; a++) {
for (int b = 0; b < m; b++) {
long s = 0;
for (int c = 0; c < n; c++) {
s += getQuick(b, c) * B.getQuick(c, a);
}
C_loc.setQuick(b, a, alpha * s + beta * C_loc.getQuick(b, a));
}
}
}
return C_loc;
}
/**
* Returns the sum of all cells; Sum( x[i,j] ).
*
* @return the sum.
*/
public long zSum() {
if (size() == 0)
return 0;
return aggregate(cern.jet.math.tlong.LongFunctions.plus, cern.jet.math.tlong.LongFunctions.identity);
}
}