no.uib.cipr.matrix.Matrices Maven / Gradle / Ivy
Show all versions of mtj Show documentation
/*
* Copyright (C) 2003-2006 Bjørn-Ove Heimsund
*
* This file is part of MTJ.
*
* This library is free software; you can redistribute it and/or modify it
* under the terms of the GNU Lesser General Public License as published by the
* Free Software Foundation; either version 2.1 of the License, or (at your
* option) any later version.
*
* This library is distributed in the hope that it will be useful, but WITHOUT
* ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or
* FITNESS FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License
* for more details.
*
* You should have received a copy of the GNU Lesser General Public License
* along with this library; if not, write to the Free Software Foundation,
* Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA
*/
package no.uib.cipr.matrix;
import java.util.Arrays;
/**
* Static utility methods for matrices and vectors
*/
public final class Matrices {
private Matrices() {
// No need to instantiate
}
/**
* max(1, M) provided as a convenience for 'leading dimension'
* calculations.
*
* @param n
*/
static int ld(int n) {
return Math.max(1, n);
}
/**
* max(1, max(M, N)) provided as a convenience for 'leading
* dimension' calculations.
*
* @param m
* @param n
*/
static int ld(int m, int n) {
return Math.max(1, Math.max(m, n));
}
/**
* Returns the number of non-zero entries in the given vector
*/
public static int cardinality(Vector x) {
int nz = 0;
for (VectorEntry e : x)
if (e.get() != 0)
nz++;
return nz;
}
/**
* Returns the number of non-zero entries in the given matrix
*/
public static int cardinality(Matrix A) {
int nz = 0;
for (MatrixEntry e : A)
if (e.get() != 0)
nz++;
return nz;
}
/**
* Returns an array of arrays containing a copy of the given matrix. Each
* array contains one row.
*/
public static double[][] getArray(Matrix A) {
double[][] Ad = new double[A.numRows()][A.numColumns()];
for (MatrixEntry e : A)
Ad[e.row()][e.column()] = e.get();
return Ad;
}
/**
* Returns a dense array containing a copy of the given vector
*/
public static double[] getArray(Vector x) {
double[] xd = new double[x.size()];
for (VectorEntry e : x)
xd[e.index()] = e.get();
return xd;
}
/**
* Returns the identity matrix of the given size
*
* @param size
* Number of rows/columns of the matrix
* @return Matrix of the given size, with ones on the main diagonal
*/
public static DenseMatrix identity(int size) {
DenseMatrix A = new DenseMatrix(size, size);
for (int i = 0; i < size; ++i)
A.set(i, i, 1);
return A;
}
/**
* Creates a random vector. Numbers are drawn from a uniform distribution
* between 0 and 1
*
* @param size
* Size of the vector
*/
public static Vector random(int size) {
return random(new DenseVector(size));
}
/**
* Populates a vector with random numbers drawn from a uniform distribution
* between 0 and 1
*
* @param x
* Vector to populate
*/
public static Vector random(Vector x) {
for (int i = 0; i < x.size(); ++i)
x.set(i, Math.random());
return x;
}
/**
* Creates a random matrix. Numbers are drawn from a uniform distribution
* between 0 and 1
*
* @param numRows
* Number of rows
* @param numColumns
* Number of columns
*/
public static Matrix random(int numRows, int numColumns) {
return random(new DenseMatrix(numRows, numColumns));
}
/**
* Populates a matrix with random numbers drawn from a uniform distribution
* between 0 and 1
*
* @param A
* Matrix to populate
*/
public static Matrix random(Matrix A) {
for (int j = 0; j < A.numColumns(); ++j)
for (int i = 0; i < A.numRows(); ++i)
A.set(i, j, Math.random());
return A;
}
/**
* Returns a synchronized vector which wraps the given vector. Only the
* set(int, double) and add(int, double) methods
* and their blocked versions are synchronized.
*
* Note: Do not use the wrapped vector for any operations besides
* matrix assembly, as these operations may be very slow.
*
* @param x
* Vector to be wrapped
* @return A thin wrapper around x
*/
public static Vector synchronizedVector(Vector x) {
return new SynchronizedVector(x);
}
/**
* Returns a synchronized matrix which wraps the given matrix. Only the
* set(int, int, double) and add(int, int, double)
* methods and their blocked versions are synchronized.
*
* Note: Do not use the wrapped matrix for any operations besides
* matrix assembly, as these operations may be very slow.
*
* @param A
* Matrix to be wrapped
* @return A thin wrapper around A
*/
public static Matrix synchronizedMatrix(Matrix A) {
return new SynchronizedMatrix(A);
}
/**
* Returns a synchronized matrix which wraps the given matrix. Only the
* set(int, int, double) and add(int, int, double)
* methods and their blocked versions are synchronized.
*
* The locking provided is finer than the locking of the whole matrix, as
* different threads can access different rows simultaneous, while only one
* thread can access a given row at a time. Use this for row-major matrices,
* not for column-major matrices.
*
* Note: Do not use the wrapped matrix for any operations besides
* matrix assembly, as these operations may be very slow.
*
* @param A
* Matrix to be wrapped
* @return A thin wrapper around A. Individual rows are locked
*/
public static Matrix synchronizedMatrixByRows(Matrix A) {
return new SynchronizedRowMatrix(A);
}
/**
* Returns a synchronized matrix which wraps the given matrix. Only the
* set(int, int, double) and add(int, int, double)
* methods and their blocked versions are synchronized.
*
* The locking provided is finer than the locking of the whole matrix, as
* different threads can access different columns simultaneous, while only
* one thread can access a given column at a time. Use this for column-major
* matrices, not for row-major matrices.
*
* Note: Do not use the wrapped matrix for any operations besides
* matrix assembly, as these operations may be very slow.
*
* @param A
* Matrix to be wrapped
* @return A thin wrapper around A. Individual columns are
* locked
*/
public static Matrix synchronizedMatrixByColumns(Matrix A) {
return new SynchronizedColumnMatrix(A);
}
/**
* Returns a view into the given matrix. This view is only for easing some
* matrix-assembly cases, not for general use. To extract a more
* higher-performing and general matrix, create a copy of the submatrix. The
* result is a {@link no.uib.cipr.matrix.DenseMatrix DenseMatrix}.
*
* @param A
* Matrix to create view on
* @param row
* Rows to access. Must be within the bounds of A
* @param column
* Columns to access. Must be within the bounds of A
* @return Submatrix of A. Changing it will change the backing
* matrix
*/
public static Matrix getSubMatrix(Matrix A, int[] row, int[] column) {
return new RefMatrix(A, row, column);
}
/**
* Returns a view into the given vector. This view is only for easing some
* vector-assembly cases, not for general use. To extract a more
* higher-performing and general vector, create a copy of the subvector. The
* result is a {@link no.uib.cipr.matrix.DenseVector DenseVector}.
*
* @param x
* Vector to create view on
* @param index
* Indices to access. Must be within the bounds of x
* @return Submatrix of x. Changing it will change the backing
* matrix
*/
public static Vector getSubVector(Vector x, int[] index) {
return new RefVector(x, index);
}
/**
* Matrix backed by another matrix. Used by getSubMatrix
*/
private static class RefMatrix extends AbstractMatrix {
private Matrix A;
private int[] row, column;
public RefMatrix(Matrix A, int[] row, int[] column) {
super(row.length, column.length);
this.A = A;
this.row = row;
this.column = column;
}
@Override
public void add(int row, int column, double value) {
A.add(this.row[row], this.column[column], value);
}
@Override
public DenseMatrix copy() {
return new DenseMatrix(this);
}
@Override
public double get(int row, int column) {
return A.get(this.row[row], this.column[column]);
}
@Override
public void set(int row, int column, double value) {
A.set(this.row[row], this.column[column], value);
}
}
/**
* Vector backed by another vector. Used by getSubVector
*/
private static class RefVector extends AbstractVector {
private Vector x;
private int[] index;
public RefVector(Vector x, int[] index) {
super(index.length);
this.x = x;
this.index = index;
}
@Override
public void add(int index, double value) {
x.add(this.index[index], value);
}
@Override
public DenseVector copy() {
return new DenseVector(this);
}
@Override
public double get(int index) {
return x.get(this.index[index]);
}
@Override
public void set(int index, double value) {
x.set(this.index[index], value);
}
}
/**
* Ensures correctness in the vector assembly. Since it extends the
* AbstractVector class, algebraic operations will be slow. It is not
* possible to implement Vector and delegate calls to the imbedded vector,
* since casting to the imbedded vector is not possible
*/
private static class SynchronizedVector extends AbstractVector {
private Vector x;
public SynchronizedVector(Vector x) {
super(x);
this.x = x;
}
@Override
public synchronized void add(int index, double value) {
x.add(index, value);
}
@Override
public synchronized void set(int index, double value) {
x.set(index, value);
}
@Override
public synchronized double get(int index) {
return x.get(index);
}
@Override
public Vector copy() {
return Matrices.synchronizedVector(x.copy());
}
}
/**
* Ensures correctness in the matrix assembly. Since it extends the
* AbstractMatrix class, algebraic operations will be slow. It is not
* possible to implement Matrix and delegate calls to the imbedded matrix,
* since casting to the imbedded matrix is not possible
*/
private static class SynchronizedMatrix extends AbstractMatrix {
private Matrix A;
public SynchronizedMatrix(Matrix A) {
super(A);
this.A = A;
}
@Override
public synchronized void add(int row, int column, double value) {
A.add(row, column, value);
}
@Override
public synchronized void set(int row, int column, double value) {
A.set(row, column, value);
}
@Override
public synchronized double get(int row, int column) {
return A.get(row, column);
}
@Override
public Matrix copy() {
return Matrices.synchronizedMatrix(A.copy());
}
}
/**
* Ensures correctness in the matrix assembly. Since it extends the
* AbstractMatrix class, algebraic operations will be slow. It is not
* possible to implement Matrix and delegate calls to the imbedded matrix,
* since casting to the imbedded matrix is not possible
*
* Locks individual rows instead of the whole matrix
*/
private static class SynchronizedRowMatrix extends AbstractMatrix {
private Matrix A;
private Object[] lock;
public SynchronizedRowMatrix(Matrix A) {
super(A);
this.A = A;
lock = new Object[A.numRows()];
for (int i = 0; i < lock.length; ++i)
lock[i] = new Object();
}
@Override
public void add(int row, int column, double value) {
synchronized (lock[row]) {
A.add(row, column, value);
}
}
@Override
public void set(int row, int column, double value) {
synchronized (lock[row]) {
A.set(row, column, value);
}
}
@Override
public double get(int row, int column) {
return A.get(row, column);
}
@Override
public Matrix copy() {
return Matrices.synchronizedMatrixByRows(A.copy());
}
}
/**
* Ensures correctness in the matrix assembly. Implements matrix instead of
* subclassing the abstract matrix in order to correctly delegate every
* method to possbly overridden method in the encapsulated matrix.
*
* Locks individual columns instead of the whole matrix
*/
private static class SynchronizedColumnMatrix extends AbstractMatrix {
private Matrix A;
private Object[] lock;
public SynchronizedColumnMatrix(Matrix A) {
super(A);
this.A = A;
lock = new Object[A.numColumns()];
for (int i = 0; i < lock.length; ++i)
lock[i] = new Object();
}
@Override
public void add(int row, int column, double value) {
synchronized (lock[column]) {
A.add(row, column, value);
}
}
@Override
public void set(int row, int column, double value) {
synchronized (lock[column]) {
A.set(row, column, value);
}
}
@Override
public double get(int row, int column) {
return A.get(row, column);
}
@Override
public Matrix copy() {
return Matrices.synchronizedMatrixByColumns(A.copy());
}
}
/**
* Creates a continuous linear index.
*
* @param from
* Start, inclusive
* @param to
* Stop, exclusive
*/
public static int[] index(int from, int to) {
int length = to - from;
if (length < 0)
length = 0;
int[] index = new int[length];
for (int i = from, j = 0; j < length; ++i, ++j)
index[j] = i;
return index;
}
/**
* Creates a strided linear index.
*
* @param from
* Start, inclusive
* @param stride
* stride=1 for continuous. Negative strides are
* allowed
* @param to
* Stop, exclusive
*/
public static int[] index(int from, int stride, int to) {
if (stride == 1)
return index(from, to);
else if (stride == 0)
return new int[0];
if (to <= from && stride > 0)
return new int[0];
if (from <= to && stride < 0)
return new int[0];
int length = Math.abs((to - from) / stride);
if (Math.abs((to - from) % stride) > 0)
length++;
if (length < 0)
length = 0;
int[] index = new int[length];
for (int i = from, j = 0; j < length; i += stride, ++j)
index[j] = i;
return index;
}
/**
* Finds the number of non-zero entries on each row
*/
public static int[] rowBandwidth(Matrix A) {
int[] nz = new int[A.numRows()];
for (MatrixEntry e : A)
nz[e.row()]++;
return nz;
}
/**
* Finds the number of non-zero entries on each column
*/
public static int[] columnBandwidth(Matrix A) {
int[] nz = new int[A.numColumns()];
for (MatrixEntry e : A)
nz[e.column()]++;
return nz;
}
/**
* Finds the number of diagonals below the main diagonal. Useful for
* converting a general matrix into a banded matrix
*/
public static int getNumSubDiagonals(Matrix A) {
int kl = 0;
for (MatrixEntry e : A)
kl = Math.max(kl, e.row() - e.column());
return kl;
}
/**
* Finds the number of diagonals above the main diagonal. Useful for
* converting a general matrix into a banded matrix
*/
public static int getNumSuperDiagonals(Matrix A) {
int ku = 0;
for (MatrixEntry e : A)
ku = Math.max(ku, e.column() - e.row());
return ku;
}
/**
* Sets the selected rows of A equal zero, and puts
* diagonal on the diagonal of those rows. Useful for enforcing
* boundary conditions
*/
public static void zeroRows(Matrix A, double diagonal, int... row) {
// Sort the rows
int[] rowS = row.clone();
Arrays.sort(rowS);
for (MatrixEntry e : A) {
int j = java.util.Arrays.binarySearch(rowS, e.row());
if (j >= 0) { // Found
if (e.row() == e.column()) // Diagonal
e.set(diagonal);
else
// Off diagonal
e.set(0);
}
}
// Ensure the diagonal is set. This is necessary in case of missing
// rows
if (diagonal != 0)
for (int rowI : row)
A.set(rowI, rowI, diagonal);
}
/**
* Sets the selected columns of A equal zero, and puts
* diagonal on the diagonal of those columns. Useful for
* enforcing boundary conditions
*/
public static void zeroColumns(Matrix A, double diagonal, int... column) {
// Sort the columns
int[] columnS = column.clone();
Arrays.sort(columnS);
for (MatrixEntry e : A) {
int j = java.util.Arrays.binarySearch(columnS, e.column());
if (j >= 0) { // Found
if (e.row() == e.column()) // Diagonal
e.set(diagonal);
else
// Off diagonal
e.set(0);
}
}
// Ensure the diagonal is set. This is necessary in case of missing
// columns
if (diagonal != 0)
for (int columnI : column)
A.set(columnI, columnI, diagonal);
}
public static DenseVector getColumn(Matrix m, int j) {
DenseVector v = new DenseVector(m.numRows());
for (int i = 0; i < v.size(); i++) {
v.set(i, m.get(i, j));
}
return v;
}
}