QR decomposition: Difference between revisions

Content added Content deleted
(New post which completes the task without using external libraries. In addition to 4 existing posts, none of which complete the task, and use the external libraries "JAMA", "Colt", "Apache Commons Math" and "la4j".)
Line 2,950: Line 2,950:
0,000 -175,000 70,000
0,000 -175,000 70,000
0,000 0,000 35,000</pre>
0,000 0,000 35,000</pre>

===Without external libraries===
<syntaxhighlight lang="java">
import java.util.ArrayList;
import java.util.List;

public final class QRDecomposition {

public static void main(String[] aArgs) {
final double[][] data = new double [][] { { 12.0, -51.0, 4.0 },
{ 6.0, 167.0, -68.0 },
{ -4.0, 24.0, -41.0 },
{ -1.0, 1.0, 0.0 },
{ 2.0, 0.0, 3.0 } };
// Task 1
Matrix A = new Matrix(data);
A.display("Initial matrix A:");
MatrixPair pair = householder(A);
Matrix Q = pair.q;
Matrix R = pair.r;
Q.display("Matrix Q:");
R.display("Matrix R:");
Matrix result = Q.multiply(R);
result.display("Matrix Q * R:");
// Task 2
Matrix x = new Matrix ( new double[][] { { 0.0, 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0 } } );
Matrix y = new Matrix(
new double[][] { { 1.0, 6.0, 17.0, 34.0, 57.0, 86.0, 121.0, 162.0, 209.0, 262.0, 321.0 } } );
result = fitPolynomial(x, y, 2);
result.display("Result of fitting polynomial:");
}
private static MatrixPair householder(Matrix aMatrix) {
final int rowCount = aMatrix.getRowCount();
final int columnCount = aMatrix.getColumnCount();
List<Matrix> versionsOfQ = new ArrayList<Matrix>(rowCount);
Matrix z = new Matrix(aMatrix);
Matrix z1 = new Matrix(rowCount, columnCount);
for ( int k = 0; k < columnCount && k < rowCount - 1; k++ ) {
Matrix vectorE = new Matrix( new double[rowCount][1] );
z1 = z.minor(k);
Matrix vectorX = z1.column(k);
double magnitudeX = vectorX.magnitude();
if ( aMatrix.getEntry(k, k) > 0 ) {
magnitudeX = -magnitudeX;
}

for ( int i = 0; i < vectorE.size(); i++ ) {
vectorE.setEntry(i, 0, ( i == k ) ? 1 : 0);
}
vectorE = vectorE.scalarMultiply(magnitudeX).add(vectorX);
vectorE = vectorE.unit();
versionsOfQ.add(householderFactor(vectorE));
z = versionsOfQ.get(k).multiply(z1);
}
Matrix Q = versionsOfQ.get(0);
for ( int i = 1; i < columnCount && i < rowCount - 1; i++ ) {
Q = versionsOfQ.get(i).multiply(Q);
}

Matrix R = Q.multiply(aMatrix);
Q = Q.transpose();
return new MatrixPair(R, Q);
}
public static Matrix householderFactor(Matrix aVector) {
if ( aVector.getColumnCount() != 1 ) {
throw new RuntimeException("Incompatible matrix dimensions.");
}
final int size = aVector.size();
double[][] newData = new double[size][size];
for ( int i = 0; i < size; i++ ) {
for ( int j = 0; j < size; j++ ) {
newData[i][j] = -2 * aVector.getEntry(i, 0) * aVector.getEntry(j, 0);
}
}
for ( int i = 0; i < size; i++ ) {
newData[i][i] += 1;
}
return new Matrix(newData);
}
private static Matrix fitPolynomial(Matrix aX, Matrix aY, int aPolynomialDegree) {
Matrix vandermonde = new Matrix(aX.getColumnCount(), aPolynomialDegree + 1);
for ( int i = 0; i < aX.getColumnCount(); i++ ) {
for ( int j = 0; j < aPolynomialDegree + 1; j++ ) {
vandermonde.setEntry(i, j, Math.pow(aX.getEntry(0, i), j));
}
}
return leastSquares(vandermonde, aY.transpose());
}
private static Matrix leastSquares(Matrix aVandermonde, Matrix aB) {
MatrixPair pair = householder(aVandermonde);
return solveUpperTriangular(pair.r, pair.q.transpose().multiply(aB));
}
private static Matrix solveUpperTriangular(Matrix aR, Matrix aB) {
final int columnCount = aR.getColumnCount();
Matrix result = new Matrix(columnCount, 1);

for ( int k = columnCount - 1; k >= 0; k-- ) {
double total = 0.0;
for ( int j = k + 1; j < columnCount; j++ ) {
total += aR.getEntry(k, j) * result.getEntry(j, 0);
}
result.setEntry(k, 0, ( aB.getEntry(k, 0) - total ) / aR.getEntry(k, k));
}
return result;
}
private static record MatrixPair(Matrix r, Matrix q) {}

}

final class Matrix {

public Matrix(double[][] aData) {
rowCount = aData.length;
columnCount = aData[0].length;
data = new double[rowCount][columnCount];
for ( int i = 0; i < rowCount; i++ ) {
for ( int j = 0; j < columnCount; j++ ) {
data[i][j] = aData[i][j];
}
}
}
public Matrix(Matrix aMatrix) {
this(aMatrix.data);
}
public Matrix(int aRows, int aCols) {
this( new double[aRows][aCols] );
}

public Matrix add(Matrix aOther) {
if ( aOther.rowCount != rowCount || aOther.columnCount != columnCount ) {
throw new IllegalArgumentException("Incompatible matrix dimensions.");
}
Matrix result = new Matrix(data);
for ( int i = 0; i < rowCount; i++ ) {
for ( int j = 0; j < columnCount; j++ ) {
result.data[i][j] = data[i][j] + aOther.data[i][j];
}
}
return result;
}

public Matrix multiply(Matrix aOther) {
if ( columnCount != aOther.rowCount ) {
throw new IllegalArgumentException("Incompatible matrix dimensions.");
}
Matrix result = new Matrix(rowCount, aOther.columnCount);
for ( int i = 0; i < rowCount; i++ ) {
for ( int j = 0; j < aOther.columnCount; j++ ) {
for ( int k = 0; k < rowCount; k++ ) {
result.data[i][j] += data[i][k] * aOther.data[k][j];
}
}
}
return result;
}
public Matrix transpose() {
Matrix result = new Matrix(columnCount, rowCount);
for ( int i = 0; i < rowCount; i++ ) {
for ( int j = 0; j < columnCount; j++ ) {
result.data[j][i] = data[i][j];
}
}
return result;
}
public Matrix minor(int aIndex) {
Matrix result = new Matrix(rowCount, columnCount);
for ( int i = 0; i < aIndex; i++ ) {
result.setEntry(i, i, 1.0);
}
for ( int i = aIndex; i < rowCount; i++ ) {
for ( int j = aIndex; j < columnCount; j++ ) {
result.setEntry(i, j, data[i][j]);
}
}
return result;
}
public Matrix column(int aColumn) {
Matrix result = new Matrix(rowCount, 1);
for ( int i = 0; i < rowCount; i++ ) {
result.setEntry(i, 0, data[i][aColumn]);
}
return result;
}
public Matrix scalarMultiply(double aValue) {
if ( columnCount != 1 ) {
throw new IllegalArgumentException("Incompatible matrix dimension.");
}
Matrix result = new Matrix(rowCount, columnCount);
for ( int i = 0; i < data.length; i++ ) {
result.data[i][0] = data[i][0] * aValue;
}
return result;
}
public Matrix unit() {
if ( columnCount != 1 ) {
throw new IllegalArgumentException("Incompatible matrix dimensions.");
}
final double magnitude = magnitude();
Matrix result = new Matrix(rowCount, columnCount);
for ( int i = 0; i < data.length; i++ ) {
result.data[i][0] = data[i][0] / magnitude;
}
return result;
}
public double magnitude() {
if ( columnCount != 1 ) {
throw new IllegalArgumentException("Incompatible matrix dimensions.");
}
double norm = 0.0;
for ( int i = 0; i < data.length; i++ ) {
norm += data[i][0] * data[i][0];
}
return Math.sqrt(norm);
}
public int size() {
if ( columnCount != 1 ) {
throw new IllegalArgumentException("Incompatible matrix dimensions.");
}
return data.length;
}
public void display(String aTitle) {
System.out.println(aTitle);
for ( int i = 0; i < rowCount; i++ ) {
for ( int j = 0; j < columnCount; j++ ) {
System.out.print(String.format("%9.4f", data[i][j]));
}
System.out.println();
}
System.out.println();
}
public double getEntry(int aRow, int aCol) {
return data[aRow][aCol];
}
public void setEntry(int aRow, int aCol, double aValue) {
data[aRow][aCol] = aValue;
}
public int getRowCount() {
return rowCount;
}
public int getColumnCount() {
return columnCount;
}
private final int rowCount;
private final int columnCount;
private final double[][] data;
}
</syntaxhighlight>
{{ out }}
<pre>
Initial matrix A:
12.0000 -51.0000 4.0000
6.0000 167.0000 -68.0000
-4.0000 24.0000 -41.0000
-1.0000 1.0000 0.0000
2.0000 0.0000 3.0000

Matrix Q:
0.8464 -0.3913 0.3431 0.0815 0.0781
0.4232 0.9041 -0.0293 0.0258 0.0447
-0.2821 0.1704 0.9329 -0.0474 -0.1374
-0.0705 0.0140 -0.0011 0.9804 -0.1836
0.1411 -0.0167 -0.1058 -0.1713 -0.9692

Matrix R:
14.1774 20.6666 -13.4016
-0.0000 175.0425 -70.0803
0.0000 0.0000 -35.2015
-0.0000 -0.0000 -0.0000
0.0000 0.0000 -0.0000

Matrix Q * R:
12.0000 -51.0000 4.0000
6.0000 167.0000 -68.0000
-4.0000 24.0000 -41.0000
-1.0000 1.0000 -0.0000
2.0000 -0.0000 3.0000

Result of fitting polynomial:
1.0000
2.0000
3.0000
</pre>


=={{header|jq}}==
=={{header|jq}}==
Retrieved from "https://rosettacode.org/wiki/QR_decomposition"