no.uib.cipr.matrix.AbstractMatrix Maven / Gradle / Ivy
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/*
* 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.Formatter;
import java.util.Iterator;
/**
* Partial implementation of Matrix. The following methods throw
* UnsupportedOperationException, and should be overridden by a
* subclass:
*
* get(int,int)set(int,int,double)copy- All the direct solution methods
*
*
* For the rest of the methods, simple default implementations using a matrix
* iterator has been provided. There are some kernel operations which the
* simpler operations forward to, for instance, mult(Matrix,Matrix)
* forwards to multAdd(double,Matrix,Matrix). Subclasses can
* thus focus on overriding the kernel operations, which are:
*
* -
multAdd(double,Vector,Vector) and
* transMultAdd(double,Vector,Vector).
* -
rank1(double,Vector,Vector) and
* rank1(double,Vector,Vector).
* -
multAdd(double,Matrix,Matrix),
* transAmultAdd(double,Matrix,Matrix),
* transBmultAdd(double,Matrix,Matrix), and
* transABmultAdd(double,Matrix,Matrix).
* -
scale(double).
* -
set(double,Matrix) and add(double,Matrix).
*
* -
transpose and transpose(Matrix).
* - All the norms.
*
*
* Finally, a default iterator is provided by this class, which works by calling
* the get function. A tailored replacement should be used by
* subclasses.
*
*/
public abstract class AbstractMatrix implements Matrix {
/**
* Number of rows
*/
protected int numRows;
/**
* Number of columns
*/
protected int numColumns;
/**
* Constructor for AbstractMatrix
*/
protected AbstractMatrix(int numRows, int numColumns) {
if (numRows < 0 || numColumns < 0)
throw new IndexOutOfBoundsException(
"Matrix size cannot be negative");
this.numRows = numRows;
this.numColumns = numColumns;
}
/**
* Constructor for AbstractMatrix, same size as A. The invoking constructor
* should set this matrix equal the argument matrix
*/
protected AbstractMatrix(Matrix A) {
this(A.numRows(), A.numColumns());
}
public int numRows() {
return numRows;
}
public int numColumns() {
return numColumns;
}
public boolean isSquare() {
return numRows == numColumns;
}
public void set(int row, int column, double value) {
throw new UnsupportedOperationException();
}
public void add(int row, int column, double value) {
set(row, column, value + get(row, column));
}
public double get(int row, int column) {
throw new UnsupportedOperationException();
}
/**
* Checks the passed row and column indices
*/
protected void check(int row, int column) {
if (row < 0)
throw new IndexOutOfBoundsException("row index is negative (" + row
+ ")");
if (column < 0)
throw new IndexOutOfBoundsException("column index is negative ("
+ column + ")");
if (row >= numRows)
throw new IndexOutOfBoundsException("row index >= numRows (" + row
+ " >= " + numRows + ")");
if (column >= numColumns)
throw new IndexOutOfBoundsException("column index >= numColumns ("
+ column + " >= " + numColumns + ")");
}
public Matrix copy() {
throw new UnsupportedOperationException();
}
public Matrix zero() {
for (MatrixEntry e : this)
e.set(0);
return this;
}
public Vector mult(Vector x, Vector y) {
return mult(1, x, y);
}
public Vector mult(double alpha, Vector x, Vector y) {
return multAdd(alpha, x, y.zero());
}
public Vector multAdd(Vector x, Vector y) {
return multAdd(1, x, y);
}
public Vector multAdd(double alpha, Vector x, Vector y) {
checkMultAdd(x, y);
if (alpha != 0)
for (MatrixEntry e : this)
y.add(e.row(), alpha * e.get() * x.get(e.column()));
return y;
}
/**
* Checks the arguments to mult and multAdd
*/
protected void checkMultAdd(Vector x, Vector y) {
if (numColumns != x.size())
throw new IndexOutOfBoundsException("A.numColumns != x.size ("
+ numColumns + " != " + x.size() + ")");
if (numRows != y.size())
throw new IndexOutOfBoundsException("A.numRows != y.size ("
+ numRows + " != " + y.size() + ")");
}
public Vector transMult(Vector x, Vector y) {
return transMult(1, x, y);
}
public Vector transMult(double alpha, Vector x, Vector y) {
return transMultAdd(alpha, x, y.zero());
}
public Vector transMultAdd(Vector x, Vector y) {
return transMultAdd(1, x, y);
}
public Vector transMultAdd(double alpha, Vector x, Vector y) {
checkTransMultAdd(x, y);
if (alpha != 0)
for (MatrixEntry e : this)
y.add(e.column(), alpha * e.get() * x.get(e.row()));
return y;
}
/**
* Checks the arguments to transMult and
* transMultAdd
*/
protected void checkTransMultAdd(Vector x, Vector y) {
if (numRows != x.size())
throw new IndexOutOfBoundsException("A.numRows != x.size ("
+ numRows + " != " + x.size() + ")");
if (numColumns != y.size())
throw new IndexOutOfBoundsException("A.numColumns != y.size ("
+ numColumns + " != " + y.size() + ")");
}
public Vector solve(Vector b, Vector x) {
throw new UnsupportedOperationException();
}
public Vector transSolve(Vector b, Vector x) {
throw new UnsupportedOperationException();
}
/**
* Checks that a matrix inversion is legal for the given arguments. This is
* for the square case, not for least-squares problems
*/
protected void checkSolve(Vector b, Vector x) {
if (!isSquare())
throw new IndexOutOfBoundsException("!A.isSquare");
if (numRows != b.size())
throw new IndexOutOfBoundsException("numRows != b.size (" + numRows
+ " != " + b.size() + ")");
if (numColumns != x.size())
throw new IndexOutOfBoundsException("numColumns != x.size ("
+ numColumns + " != " + x.size() + ")");
}
public Matrix rank1(Vector x) {
return rank1(1, x);
}
public Matrix rank1(double alpha, Vector x) {
return rank1(alpha, x, x);
}
public Matrix rank1(Vector x, Vector y) {
return rank1(1, x, y);
}
public Matrix rank1(double alpha, Vector x, Vector y) {
checkRank1(x, y);
if (alpha == 0)
return this;
for (VectorEntry ei : x)
if (ei.get() != 0)
for (VectorEntry ej : y)
if (ej.get() != 0)
add(ei.index(), ej.index(), alpha * ei.get() * ej.get());
return this;
}
/**
* Checks that a vector rank1 update is possible for the given vectors
*/
protected void checkRank1(Vector x, Vector y) {
if (!isSquare())
throw new IndexOutOfBoundsException("!A.isSquare");
if (x.size() != numRows)
throw new IndexOutOfBoundsException("x.size != A.numRows ("
+ x.size() + " != " + numRows + ")");
if (y.size() != numColumns)
throw new IndexOutOfBoundsException("y.size != A.numColumns ("
+ y.size() + " != " + numColumns + ")");
}
public Matrix rank2(Vector x, Vector y) {
return rank2(1, x, y);
}
public Matrix rank2(double alpha, Vector x, Vector y) {
checkRank2(x, y);
if (alpha == 0)
return this;
for (VectorEntry ei : x)
for (VectorEntry ej : y) {
add(ei.index(), ej.index(), alpha * ei.get() * ej.get());
add(ej.index(), ei.index(), alpha * ei.get() * ej.get());
}
return this;
}
/**
* Checks that a vector rank2 update is legal with the given vectors
*/
protected void checkRank2(Vector x, Vector y) {
if (!isSquare())
throw new IndexOutOfBoundsException("!A.isSquare");
if (x.size() != numRows)
throw new IndexOutOfBoundsException("x.size != A.numRows ("
+ x.size() + " != " + numRows + ")");
if (y.size() != numRows)
throw new IndexOutOfBoundsException("y.size != A.numRows ("
+ y.size() + " != " + numRows + ")");
}
public Matrix mult(Matrix B, Matrix C) {
return mult(1, B, C);
}
public Matrix mult(double alpha, Matrix B, Matrix C) {
return multAdd(alpha, B, C.zero());
}
public Matrix multAdd(Matrix B, Matrix C) {
return multAdd(1, B, C);
}
public Matrix multAdd(double alpha, Matrix B, Matrix C) {
checkMultAdd(B, C);
if (alpha != 0)
for (int i = 0; i < numRows; ++i)
for (int j = 0; j < C.numColumns(); ++j) {
double dot = 0;
for (int k = 0; k < numColumns; ++k)
dot += get(i, k) * B.get(k, j);
C.add(i, j, alpha * dot);
}
return C;
}
/**
* Checks the arguments to mult and multAdd
*/
protected void checkMultAdd(Matrix B, Matrix C) {
if (numRows != C.numRows())
throw new IndexOutOfBoundsException("A.numRows != C.numRows ("
+ numRows + " != " + C.numRows() + ")");
if (numColumns != B.numRows())
throw new IndexOutOfBoundsException("A.numColumns != B.numRows ("
+ numColumns + " != " + B.numRows() + ")");
if (B.numColumns() != C.numColumns())
throw new IndexOutOfBoundsException(
"B.numColumns != C.numColumns (" + B.numRows() + " != "
+ C.numColumns() + ")");
}
public Matrix transAmult(Matrix B, Matrix C) {
return transAmult(1, B, C);
}
public Matrix transAmult(double alpha, Matrix B, Matrix C) {
return transAmultAdd(alpha, B, C.zero());
}
public Matrix transAmultAdd(Matrix B, Matrix C) {
return transAmultAdd(1, B, C);
}
public Matrix transAmultAdd(double alpha, Matrix B, Matrix C) {
checkTransAmultAdd(B, C);
if (alpha != 0)
for (int i = 0; i < numColumns; ++i)
for (int j = 0; j < C.numColumns(); ++j) {
double dot = 0;
for (int k = 0; k < numRows; ++k)
dot += get(k, i) * B.get(k, j);
C.add(i, j, alpha * dot);
}
return C;
}
/**
* Checks the arguments to transAmult and
* transAmultAdd
*/
protected void checkTransAmultAdd(Matrix B, Matrix C) {
if (numRows != B.numRows())
throw new IndexOutOfBoundsException("A.numRows != B.numRows ("
+ numRows + " != " + B.numRows() + ")");
if (numColumns != C.numRows())
throw new IndexOutOfBoundsException("A.numColumns != C.numRows ("
+ numColumns + " != " + C.numRows() + ")");
if (B.numColumns() != C.numColumns())
throw new IndexOutOfBoundsException(
"B.numColumns != C.numColumns (" + B.numColumns() + " != "
+ C.numColumns() + ")");
}
public Matrix transBmult(Matrix B, Matrix C) {
return transBmult(1, B, C);
}
public Matrix transBmult(double alpha, Matrix B, Matrix C) {
return transBmultAdd(alpha, B, C.zero());
}
public Matrix transBmultAdd(Matrix B, Matrix C) {
return transBmultAdd(1, B, C);
}
public Matrix transBmultAdd(double alpha, Matrix B, Matrix C) {
checkTransBmultAdd(B, C);
if (alpha != 0)
for (int i = 0; i < numRows; ++i)
for (int j = 0; j < C.numColumns(); ++j) {
double dot = 0;
for (int k = 0; k < numColumns; ++k)
dot += get(i, k) * B.get(j, k);
C.add(i, j, alpha * dot);
}
return C;
}
/**
* Checks the arguments to transBmult and
* transBmultAdd
*/
protected void checkTransBmultAdd(Matrix B, Matrix C) {
if (numColumns != B.numColumns())
throw new IndexOutOfBoundsException(
"A.numColumns != B.numColumns (" + numColumns + " != "
+ B.numColumns() + ")");
if (numRows != C.numRows())
throw new IndexOutOfBoundsException("A.numRows != C.numRows ("
+ numRows + " != " + C.numRows() + ")");
if (B.numRows() != C.numColumns())
throw new IndexOutOfBoundsException("B.numRows != C.numColumns ("
+ B.numRows() + " != " + C.numColumns() + ")");
}
public Matrix transABmult(Matrix B, Matrix C) {
return transABmult(1, B, C);
}
public Matrix transABmult(double alpha, Matrix B, Matrix C) {
return transABmultAdd(alpha, B, C.zero());
}
public Matrix transABmultAdd(Matrix B, Matrix C) {
return transABmultAdd(1, B, C);
}
public Matrix transABmultAdd(double alpha, Matrix B, Matrix C) {
checkTransABmultAdd(B, C);
if (alpha != 0)
for (int i = 0; i < numColumns; ++i)
for (int j = 0; j < C.numColumns(); ++j) {
double dot = 0;
for (int k = 0; k < numRows; ++k)
dot += get(k, i) * B.get(j, k);
C.add(i, j, alpha * dot);
}
return C;
}
/**
* Checks the arguments to transABmultAdd and
* transABmultAdd
*/
protected void checkTransABmultAdd(Matrix B, Matrix C) {
if (numRows != B.numColumns())
throw new IndexOutOfBoundsException("A.numRows != B.numColumns ("
+ numRows + " != " + B.numColumns() + ")");
if (numColumns != C.numRows())
throw new IndexOutOfBoundsException("A.numColumns != C.numRows ("
+ numColumns + " != " + C.numRows() + ")");
if (B.numRows() != C.numColumns())
throw new IndexOutOfBoundsException("B.numRows != C.numColumns ("
+ B.numRows() + " != " + C.numColumns() + ")");
}
public Matrix solve(Matrix B, Matrix X) {
throw new UnsupportedOperationException();
}
public Matrix transSolve(Matrix B, Matrix X) {
throw new UnsupportedOperationException();
}
/**
* Checks that a matrix inversion is legal for the given arguments. This is
* for the square case, not for least-squares problems
*/
protected void checkSolve(Matrix B, Matrix X) {
if (!isSquare())
throw new IndexOutOfBoundsException("!A.isSquare");
if (B.numRows() != numRows)
throw new IndexOutOfBoundsException("B.numRows != A.numRows ("
+ B.numRows() + " != " + numRows + ")");
if (B.numColumns() != X.numColumns())
throw new IndexOutOfBoundsException(
"B.numColumns != X.numColumns (" + B.numColumns() + " != "
+ X.numColumns() + ")");
if (X.numRows() != numColumns)
throw new IndexOutOfBoundsException("X.numRows != A.numColumns ("
+ X.numRows() + " != " + numColumns + ")");
}
public Matrix rank1(Matrix C) {
return rank1(1, C);
}
public Matrix rank1(double alpha, Matrix C) {
checkRank1(C);
if (alpha == 0)
return this;
return C.transBmultAdd(alpha, C, this);
}
/**
* Checks that a matrix rank1 update is possible for the given matrix
*/
protected void checkRank1(Matrix C) {
if (!isSquare())
throw new IndexOutOfBoundsException("!A.isSquare");
if (numRows != C.numRows())
throw new IndexOutOfBoundsException("A.numRows != C.numRows ("
+ numRows + " != " + C.numRows() + ")");
}
public Matrix transRank1(Matrix C) {
return transRank1(1, C);
}
public Matrix transRank1(double alpha, Matrix C) {
checkTransRank1(C);
if (alpha == 0)
return this;
return C.transAmultAdd(alpha, C, this);
}
/**
* Checks that a transposed rank1 update is leagal with the given argument
*/
protected void checkTransRank1(Matrix C) {
if (!isSquare())
throw new IndexOutOfBoundsException("!A.isSquare");
if (numRows != C.numColumns())
throw new IndexOutOfBoundsException("A.numRows != C.numColumns ("
+ numRows + " != " + C.numColumns() + ")");
}
public Matrix rank2(Matrix B, Matrix C) {
return rank2(1, B, C);
}
public Matrix rank2(double alpha, Matrix B, Matrix C) {
checkRank2(B, C);
if (alpha == 0)
return this;
return B.transBmultAdd(alpha, C, C.transBmultAdd(alpha, B, this));
}
/**
* Checks that a rank2 update is legal for the given arguments
*/
protected void checkRank2(Matrix B, Matrix C) {
if (!isSquare())
throw new IndexOutOfBoundsException("!A.isSquare");
if (B.numRows() != C.numRows())
throw new IndexOutOfBoundsException("B.numRows != C.numRows ("
+ B.numRows() + " != " + C.numRows() + ")");
if (B.numColumns() != C.numColumns())
throw new IndexOutOfBoundsException(
"B.numColumns != C.numColumns (" + B.numColumns() + " != "
+ C.numColumns() + ")");
}
public Matrix transRank2(Matrix B, Matrix C) {
return transRank2(1, B, C);
}
public Matrix transRank2(double alpha, Matrix B, Matrix C) {
checkTransRank2(B, C);
if (alpha == 0)
return this;
return B.transAmultAdd(alpha, C, C.transAmultAdd(alpha, B, this));
}
/**
* Checks that a transposed rank2 update is leagal with the given arguments
*/
protected void checkTransRank2(Matrix B, Matrix C) {
if (!isSquare())
throw new IndexOutOfBoundsException("!A.isSquare");
if (numRows != B.numColumns())
throw new IndexOutOfBoundsException("A.numRows != B.numColumns ("
+ numRows + " != " + B.numColumns() + ")");
if (B.numRows() != C.numRows())
throw new IndexOutOfBoundsException("B.numRows != C.numRows ("
+ B.numRows() + " != " + C.numRows() + ")");
if (B.numColumns() != C.numColumns())
throw new IndexOutOfBoundsException(
"B.numColumns != C.numColumns (" + B.numColumns() + " != "
+ C.numColumns() + ")");
}
public Matrix scale(double alpha) {
if (alpha == 1)
return this;
else if (alpha == 0)
return zero();
for (MatrixEntry e : this)
e.set(alpha * e.get());
return this;
}
public Matrix set(Matrix B) {
return set(1, B);
}
public Matrix set(double alpha, Matrix B) {
checkSize(B);
if (alpha == 0.)
return zero();
if (B == this)
return scale(alpha);
zero();
for (MatrixEntry e : B)
set(e.row(), e.column(), alpha * e.get());
return this;
}
public Matrix add(Matrix B) {
return add(1, B);
}
public Matrix add(double alpha, Matrix B) {
checkSize(B);
if (alpha != 0)
for (MatrixEntry e : B)
add(e.row(), e.column(), alpha * e.get());
return this;
}
/**
* Checks that the sizes of this matrix and the given conform
*/
protected void checkSize(Matrix B) {
if (numRows != B.numRows())
throw new IndexOutOfBoundsException("A.numRows != B.numRows ("
+ numRows + " != " + B.numRows() + ")");
if (numColumns != B.numColumns())
throw new IndexOutOfBoundsException(
"A.numColumns != B.numColumns (" + numColumns + " != "
+ B.numColumns() + ")");
}
public Matrix transpose() {
checkTranspose();
for (int j = 0; j < numColumns; ++j)
for (int i = j + 1; i < numRows; ++i) {
double value = get(i, j);
set(i, j, get(j, i));
set(j, i, value);
}
return this;
}
/**
* Checks that the matrix may be transposed
*/
protected void checkTranspose() {
if (!isSquare())
throw new IndexOutOfBoundsException("!A.isSquare");
}
public Matrix transpose(Matrix B) {
checkTranspose(B);
if (B == this)
return transpose();
B.zero();
for (MatrixEntry e : this)
B.set(e.column(), e.row(), e.get());
return B;
}
/**
* Checks that this matrix can be transposed into the given matrix
*/
protected void checkTranspose(Matrix B) {
if (numRows != B.numColumns())
throw new IndexOutOfBoundsException("A.numRows != B.numColumns ("
+ numRows + " != " + B.numColumns() + ")");
if (numColumns != B.numRows())
throw new IndexOutOfBoundsException("A.numColumns != B.numRows ("
+ numColumns + " != " + B.numRows() + ")");
}
public double norm(Norm type) {
if (type == Norm.One)
return norm1();
else if (type == Norm.Frobenius)
return normF();
else if (type == Norm.Infinity)
return normInf();
else
// Maxvalue
return max();
}
/**
* Computes the 1 norm
*/
protected double norm1() {
double[] rowSum = new double[numRows];
for (MatrixEntry e : this)
rowSum[e.row()] += Math.abs(e.get());
return max(rowSum);
}
/**
* Computes the Frobenius norm. This implementation is overflow resistant
*/
protected double normF() {
double scale = 0, ssq = 1;
for (MatrixEntry e : this) {
double Aval = e.get();
if (Aval != 0) {
double absxi = Math.abs(Aval);
if (scale < absxi) {
ssq = 1 + ssq * Math.pow(scale / absxi, 2);
scale = absxi;
} else
ssq = ssq + Math.pow(absxi / scale, 2);
}
}
return scale * Math.sqrt(ssq);
}
/**
* Computes the infinity norm
*/
protected double normInf() {
double[] columnSum = new double[numColumns];
for (MatrixEntry e : this)
columnSum[e.column()] += Math.abs(e.get());
return max(columnSum);
}
/**
* Returns the largest absolute value
*/
protected double max() {
double max = 0;
for (MatrixEntry e : this)
max = Math.max(Math.abs(e.get()), max);
return max;
}
/**
* Returns the largest element of the passed array
*/
protected double max(double[] x) {
double max = 0;
for (int i = 0; i < x.length; ++i)
max = Math.max(x[i], max);
return max;
}
@Override
public String toString() {
// Output into coordinate format. Indices start from 1 instead of 0
Formatter out = new Formatter();
out.format("%10d %10d %19d\n", numRows, numColumns, Matrices
.cardinality(this));
for (MatrixEntry e : this)
if (e.get() != 0)
out.format("%10d %10d % .12e\n", e.row() + 1, e.column() + 1, e
.get());
return out.toString();
}
public Iterator iterator() {
return new RefMatrixIterator();
}
/**
* Iterator over a general matrix. Uses column-major traversal
*/
class RefMatrixIterator implements Iterator {
/**
* Matrix cursor
*/
int row, column;
/**
* Matrix entry
*/
final RefMatrixEntry entry = new RefMatrixEntry();
public boolean hasNext() {
return (row < numRows) && (column < numColumns);
}
public MatrixEntry next() {
entry.update(row, column);
// Traversal first down the columns, then the rows
if (row < numRows - 1)
row++;
else {
column++;
row = 0;
}
return entry;
}
public void remove() {
entry.set(0);
}
}
/**
* Matrix entry backed by the matrix. May be reused for higher performance
*/
class RefMatrixEntry implements MatrixEntry {
/**
* Matrix position
*/
private int row, column;
/**
* Updates the entry
*/
public void update(int row, int column) {
this.row = row;
this.column = column;
}
public int row() {
return row;
}
public int column() {
return column;
}
public double get() {
return AbstractMatrix.this.get(row, column);
}
public void set(double value) {
AbstractMatrix.this.set(row, column, value);
}
}
}