Author: celestin
Date: Sat Sep 24 04:47:38 2011
New Revision: 1175100
URL: http://svn.apache.org/viewvc?rev=1175100&view=rev
Log:
Merged QRDecomposition and QRDecompositionImpl (see MATH-662).
Added:
commons/proper/math/trunk/src/main/java/org/apache/commons/math/linear/QRDecomposition.java
- copied, changed from r1175099,
commons/proper/math/trunk/src/main/java/org/apache/commons/math/linear/QRDecompositionImpl.java
commons/proper/math/trunk/src/test/java/org/apache/commons/math/linear/QRDecompositionTest.java
- copied, changed from r1175099,
commons/proper/math/trunk/src/test/java/org/apache/commons/math/linear/QRDecompositionImplTest.java
Removed:
commons/proper/math/trunk/src/main/java/org/apache/commons/math/linear/QRDecompositionImpl.java
commons/proper/math/trunk/src/test/java/org/apache/commons/math/linear/QRDecompositionImplTest.java
Modified:
commons/proper/math/trunk/src/main/java/org/apache/commons/math/ode/nonstiff/AdamsNordsieckTransformer.java
commons/proper/math/trunk/src/main/java/org/apache/commons/math/optimization/general/GaussNewtonOptimizer.java
commons/proper/math/trunk/src/main/java/org/apache/commons/math/stat/regression/OLSMultipleLinearRegression.java
commons/proper/math/trunk/src/test/java/org/apache/commons/math/linear/QRSolverTest.java
Copied:
commons/proper/math/trunk/src/main/java/org/apache/commons/math/linear/QRDecomposition.java
(from r1175099,
commons/proper/math/trunk/src/main/java/org/apache/commons/math/linear/QRDecompositionImpl.java)
URL:
http://svn.apache.org/viewvc/commons/proper/math/trunk/src/main/java/org/apache/commons/math/linear/QRDecomposition.java?p2=commons/proper/math/trunk/src/main/java/org/apache/commons/math/linear/QRDecomposition.java&p1=commons/proper/math/trunk/src/main/java/org/apache/commons/math/linear/QRDecompositionImpl.java&r1=1175099&r2=1175100&rev=1175100&view=diff
==============================================================================
---
commons/proper/math/trunk/src/main/java/org/apache/commons/math/linear/QRDecompositionImpl.java
(original)
+++
commons/proper/math/trunk/src/main/java/org/apache/commons/math/linear/QRDecomposition.java
Sat Sep 24 04:47:38 2011
@@ -32,14 +32,23 @@ import org.apache.commons.math.util.Fast
* <p>For efficiency purposes, the decomposition in packed form is transposed.
* This allows inner loop to iterate inside rows, which is much more
cache-efficient
* in Java.</p>
+ * <p>This class is based on the class with similar name from the
+ * <a href="http://math.nist.gov/javanumerics/jama/";>JAMA</a> library, with the
+ * following changes:</p>
+ * <ul>
+ * <li>a {@link #getQT() getQT} method has been added,</li>
+ * <li>the {@code solve} and {@code isFullRank} methods have been replaced
+ * by a {@link #getSolver() getSolver} method and the equivalent methods
+ * provided by the returned {@link DecompositionSolver}.</li>
+ * </ul>
*
* @see <a
href="http://mathworld.wolfram.com/QRDecomposition.html";>MathWorld</a>
* @see <a href="http://en.wikipedia.org/wiki/QR_decomposition";>Wikipedia</a>
*
* @version $Id$
- * @since 1.2
+ * @since 1.2 (changed to concrete class in 3.0)
*/
-public class QRDecompositionImpl implements QRDecomposition {
+public class QRDecomposition {
/**
* A packed TRANSPOSED representation of the QR decomposition.
@@ -68,7 +77,7 @@ public class QRDecompositionImpl impleme
* Calculates the QR-decomposition of the given matrix.
* @param matrix The matrix to decompose.
*/
- public QRDecompositionImpl(RealMatrix matrix) {
+ public QRDecomposition(RealMatrix matrix) {
final int m = matrix.getRowDimension();
final int n = matrix.getColumnDimension();
@@ -144,7 +153,11 @@ public class QRDecompositionImpl impleme
}
}
- /** {@inheritDoc} */
+ /**
+ * Returns the matrix R of the decomposition.
+ * <p>R is an upper-triangular matrix</p>
+ * @return the R matrix
+ */
public RealMatrix getR() {
if (cachedR == null) {
@@ -167,7 +180,11 @@ public class QRDecompositionImpl impleme
return cachedR;
}
- /** {@inheritDoc} */
+ /**
+ * Returns the matrix Q of the decomposition.
+ * <p>Q is an orthogonal matrix</p>
+ * @return the Q matrix
+ */
public RealMatrix getQ() {
if (cachedQ == null) {
cachedQ = getQT().transpose();
@@ -175,7 +192,11 @@ public class QRDecompositionImpl impleme
return cachedQ;
}
- /** {@inheritDoc} */
+ /**
+ * Returns the transpose of the matrix Q of the decomposition.
+ * <p>Q is an orthogonal matrix</p>
+ * @return the Q matrix
+ */
public RealMatrix getQT() {
if (cachedQT == null) {
@@ -216,7 +237,13 @@ public class QRDecompositionImpl impleme
return cachedQT;
}
- /** {@inheritDoc} */
+ /**
+ * Returns the Householder reflector vectors.
+ * <p>H is a lower trapezoidal matrix whose columns represent
+ * each successive Householder reflector vector. This matrix is used
+ * to compute Q.</p>
+ * @return a matrix containing the Householder reflector vectors
+ */
public RealMatrix getH() {
if (cachedH == null) {
@@ -234,7 +261,10 @@ public class QRDecompositionImpl impleme
return cachedH;
}
- /** {@inheritDoc} */
+ /**
+ * Get a solver for finding the A × X = B solution in least square
sense.
+ * @return a solver
+ */
public DecompositionSolver getSolver() {
return new Solver(qrt, rDiag);
}
Modified:
commons/proper/math/trunk/src/main/java/org/apache/commons/math/ode/nonstiff/AdamsNordsieckTransformer.java
URL:
http://svn.apache.org/viewvc/commons/proper/math/trunk/src/main/java/org/apache/commons/math/ode/nonstiff/AdamsNordsieckTransformer.java?rev=1175100&r1=1175099&r2=1175100&view=diff
==============================================================================
---
commons/proper/math/trunk/src/main/java/org/apache/commons/math/ode/nonstiff/AdamsNordsieckTransformer.java
(original)
+++
commons/proper/math/trunk/src/main/java/org/apache/commons/math/ode/nonstiff/AdamsNordsieckTransformer.java
Sat Sep 24 04:47:38 2011
@@ -30,7 +30,6 @@ import org.apache.commons.math.linear.Fi
import org.apache.commons.math.linear.FieldMatrix;
import org.apache.commons.math.linear.MatrixUtils;
import org.apache.commons.math.linear.QRDecomposition;
-import org.apache.commons.math.linear.QRDecompositionImpl;
import org.apache.commons.math.linear.RealMatrix;
/** Transformer to Nordsieck vectors for Adams integrators.
@@ -291,7 +290,8 @@ public class AdamsNordsieckTransformer {
// solve the rectangular system in the least square sense
// to get the best estimate of the Nordsieck vector [s2 ... sk]
- QRDecomposition decomposition = new QRDecompositionImpl(new
Array2DRowRealMatrix(a, false));
+ QRDecomposition decomposition;
+ decomposition = new QRDecomposition(new Array2DRowRealMatrix(a,
false));
RealMatrix x = decomposition.getSolver().solve(new
Array2DRowRealMatrix(b, false));
return new Array2DRowRealMatrix(x.getData(), false);
}
Modified:
commons/proper/math/trunk/src/main/java/org/apache/commons/math/optimization/general/GaussNewtonOptimizer.java
URL:
http://svn.apache.org/viewvc/commons/proper/math/trunk/src/main/java/org/apache/commons/math/optimization/general/GaussNewtonOptimizer.java?rev=1175100&r1=1175099&r2=1175100&view=diff
==============================================================================
---
commons/proper/math/trunk/src/main/java/org/apache/commons/math/optimization/general/GaussNewtonOptimizer.java
(original)
+++
commons/proper/math/trunk/src/main/java/org/apache/commons/math/optimization/general/GaussNewtonOptimizer.java
Sat Sep 24 04:47:38 2011
@@ -23,7 +23,7 @@ import org.apache.commons.math.linear.Ar
import org.apache.commons.math.linear.BlockRealMatrix;
import org.apache.commons.math.linear.DecompositionSolver;
import org.apache.commons.math.linear.LUDecomposition;
-import org.apache.commons.math.linear.QRDecompositionImpl;
+import org.apache.commons.math.linear.QRDecomposition;
import org.apache.commons.math.linear.RealMatrix;
import org.apache.commons.math.linear.SingularMatrixException;
import org.apache.commons.math.optimization.ConvergenceChecker;
@@ -145,7 +145,7 @@ public class GaussNewtonOptimizer extend
RealMatrix mA = new BlockRealMatrix(a);
DecompositionSolver solver = useLU ?
new LUDecomposition(mA).getSolver() :
- new QRDecompositionImpl(mA).getSolver();
+ new QRDecomposition(mA).getSolver();
final double[] dX = solver.solve(new ArrayRealVector(b,
false)).toArray();
// update the estimated parameters
for (int i = 0; i < cols; ++i) {
Modified:
commons/proper/math/trunk/src/main/java/org/apache/commons/math/stat/regression/OLSMultipleLinearRegression.java
URL:
http://svn.apache.org/viewvc/commons/proper/math/trunk/src/main/java/org/apache/commons/math/stat/regression/OLSMultipleLinearRegression.java?rev=1175100&r1=1175099&r2=1175100&view=diff
==============================================================================
---
commons/proper/math/trunk/src/main/java/org/apache/commons/math/stat/regression/OLSMultipleLinearRegression.java
(original)
+++
commons/proper/math/trunk/src/main/java/org/apache/commons/math/stat/regression/OLSMultipleLinearRegression.java
Sat Sep 24 04:47:38 2011
@@ -19,7 +19,6 @@ package org.apache.commons.math.stat.reg
import org.apache.commons.math.linear.Array2DRowRealMatrix;
import org.apache.commons.math.linear.LUDecomposition;
import org.apache.commons.math.linear.QRDecomposition;
-import org.apache.commons.math.linear.QRDecompositionImpl;
import org.apache.commons.math.linear.RealMatrix;
import org.apache.commons.math.linear.RealVector;
import org.apache.commons.math.stat.StatUtils;
@@ -33,7 +32,7 @@ import org.apache.commons.math.stat.desc
* <pre><code> X<sup>T</sup> X b = X<sup>T</sup> y </code></pre></p>
*
* <p>To solve the normal equations, this implementation uses QR decomposition
- * of the <code>X</code> matrix. (See {@link QRDecompositionImpl} for details
on the
+ * of the <code>X</code> matrix. (See {@link QRDecomposition} for details on
the
* decomposition algorithm.) The <code>X</code> matrix, also known as the
<i>design matrix,</i>
* has rows corresponding to sample observations and columns corresponding to
independent
* variables. When the model is estimated using an intercept term (i.e. when
@@ -79,7 +78,7 @@ public class OLSMultipleLinearRegression
@Override
public void newSampleData(double[] data, int nobs, int nvars) {
super.newSampleData(data, nobs, nvars);
- qr = new QRDecompositionImpl(X);
+ qr = new QRDecomposition(X);
}
/**
@@ -198,7 +197,7 @@ public class OLSMultipleLinearRegression
@Override
protected void newXSampleData(double[][] x) {
super.newXSampleData(x);
- qr = new QRDecompositionImpl(X);
+ qr = new QRDecomposition(X);
}
/**
Copied:
commons/proper/math/trunk/src/test/java/org/apache/commons/math/linear/QRDecompositionTest.java
(from r1175099,
commons/proper/math/trunk/src/test/java/org/apache/commons/math/linear/QRDecompositionImplTest.java)
URL:
http://svn.apache.org/viewvc/commons/proper/math/trunk/src/test/java/org/apache/commons/math/linear/QRDecompositionTest.java?p2=commons/proper/math/trunk/src/test/java/org/apache/commons/math/linear/QRDecompositionTest.java&p1=commons/proper/math/trunk/src/test/java/org/apache/commons/math/linear/QRDecompositionImplTest.java&r1=1175099&r2=1175100&rev=1175100&view=diff
==============================================================================
---
commons/proper/math/trunk/src/test/java/org/apache/commons/math/linear/QRDecompositionImplTest.java
(original)
+++
commons/proper/math/trunk/src/test/java/org/apache/commons/math/linear/QRDecompositionTest.java
Sat Sep 24 04:47:38 2011
@@ -23,7 +23,7 @@ import org.junit.Assert;
import org.junit.Test;
-public class QRDecompositionImplTest {
+public class QRDecompositionTest {
double[][] testData3x3NonSingular = {
{ 12, -51, 4 },
{ 6, 167, -68 },
@@ -69,7 +69,7 @@ public class QRDecompositionImplTest {
private void checkDimension(RealMatrix m) {
int rows = m.getRowDimension();
int columns = m.getColumnDimension();
- QRDecomposition qr = new QRDecompositionImpl(m);
+ QRDecomposition qr = new QRDecomposition(m);
Assert.assertEquals(rows, qr.getQ().getRowDimension());
Assert.assertEquals(rows, qr.getQ().getColumnDimension());
Assert.assertEquals(rows, qr.getR().getRowDimension());
@@ -97,7 +97,7 @@ public class QRDecompositionImplTest {
}
private void checkAEqualQR(RealMatrix m) {
- QRDecomposition qr = new QRDecompositionImpl(m);
+ QRDecomposition qr = new QRDecomposition(m);
double norm = qr.getQ().multiply(qr.getR()).subtract(m).getNorm();
Assert.assertEquals(0, norm, normTolerance);
}
@@ -123,7 +123,7 @@ public class QRDecompositionImplTest {
}
private void checkQOrthogonal(RealMatrix m) {
- QRDecomposition qr = new QRDecompositionImpl(m);
+ QRDecomposition qr = new QRDecomposition(m);
RealMatrix eye =
MatrixUtils.createRealIdentityMatrix(m.getRowDimension());
double norm = qr.getQT().multiply(qr.getQ()).subtract(eye).getNorm();
Assert.assertEquals(0, norm, normTolerance);
@@ -133,25 +133,25 @@ public class QRDecompositionImplTest {
@Test
public void testRUpperTriangular() {
RealMatrix matrix =
MatrixUtils.createRealMatrix(testData3x3NonSingular);
- checkUpperTriangular(new QRDecompositionImpl(matrix).getR());
+ checkUpperTriangular(new QRDecomposition(matrix).getR());
matrix = MatrixUtils.createRealMatrix(testData3x3Singular);
- checkUpperTriangular(new QRDecompositionImpl(matrix).getR());
+ checkUpperTriangular(new QRDecomposition(matrix).getR());
matrix = MatrixUtils.createRealMatrix(testData3x4);
- checkUpperTriangular(new QRDecompositionImpl(matrix).getR());
+ checkUpperTriangular(new QRDecomposition(matrix).getR());
matrix = MatrixUtils.createRealMatrix(testData4x3);
- checkUpperTriangular(new QRDecompositionImpl(matrix).getR());
+ checkUpperTriangular(new QRDecomposition(matrix).getR());
Random r = new Random(643895747384642l);
int p = (5 * BlockRealMatrix.BLOCK_SIZE) / 4;
int q = (7 * BlockRealMatrix.BLOCK_SIZE) / 4;
matrix = createTestMatrix(r, p, q);
- checkUpperTriangular(new QRDecompositionImpl(matrix).getR());
+ checkUpperTriangular(new QRDecomposition(matrix).getR());
matrix = createTestMatrix(r, p, q);
- checkUpperTriangular(new QRDecompositionImpl(matrix).getR());
+ checkUpperTriangular(new QRDecomposition(matrix).getR());
}
@@ -170,25 +170,25 @@ public class QRDecompositionImplTest {
@Test
public void testHTrapezoidal() {
RealMatrix matrix =
MatrixUtils.createRealMatrix(testData3x3NonSingular);
- checkTrapezoidal(new QRDecompositionImpl(matrix).getH());
+ checkTrapezoidal(new QRDecomposition(matrix).getH());
matrix = MatrixUtils.createRealMatrix(testData3x3Singular);
- checkTrapezoidal(new QRDecompositionImpl(matrix).getH());
+ checkTrapezoidal(new QRDecomposition(matrix).getH());
matrix = MatrixUtils.createRealMatrix(testData3x4);
- checkTrapezoidal(new QRDecompositionImpl(matrix).getH());
+ checkTrapezoidal(new QRDecomposition(matrix).getH());
matrix = MatrixUtils.createRealMatrix(testData4x3);
- checkTrapezoidal(new QRDecompositionImpl(matrix).getH());
+ checkTrapezoidal(new QRDecomposition(matrix).getH());
Random r = new Random(643895747384642l);
int p = (5 * BlockRealMatrix.BLOCK_SIZE) / 4;
int q = (7 * BlockRealMatrix.BLOCK_SIZE) / 4;
matrix = createTestMatrix(r, p, q);
- checkTrapezoidal(new QRDecompositionImpl(matrix).getH());
+ checkTrapezoidal(new QRDecomposition(matrix).getH());
matrix = createTestMatrix(r, p, q);
- checkTrapezoidal(new QRDecompositionImpl(matrix).getH());
+ checkTrapezoidal(new QRDecomposition(matrix).getH());
}
@@ -206,7 +206,7 @@ public class QRDecompositionImplTest {
@Test
public void testMatricesValues() {
QRDecomposition qr =
- new
QRDecompositionImpl(MatrixUtils.createRealMatrix(testData3x3NonSingular));
+ new
QRDecomposition(MatrixUtils.createRealMatrix(testData3x3NonSingular));
RealMatrix qRef = MatrixUtils.createRealMatrix(new double[][] {
{ -12.0 / 14.0, 69.0 / 175.0, -58.0 / 175.0 },
{ -6.0 / 14.0, -158.0 / 175.0, 6.0 / 175.0 },
Modified:
commons/proper/math/trunk/src/test/java/org/apache/commons/math/linear/QRSolverTest.java
URL:
http://svn.apache.org/viewvc/commons/proper/math/trunk/src/test/java/org/apache/commons/math/linear/QRSolverTest.java?rev=1175100&r1=1175099&r2=1175100&view=diff
==============================================================================
---
commons/proper/math/trunk/src/test/java/org/apache/commons/math/linear/QRSolverTest.java
(original)
+++
commons/proper/math/trunk/src/test/java/org/apache/commons/math/linear/QRSolverTest.java
Sat Sep 24 04:47:38 2011
@@ -54,16 +54,16 @@ public class QRSolverTest {
@Test
public void testRank() {
DecompositionSolver solver =
- new
QRDecompositionImpl(MatrixUtils.createRealMatrix(testData3x3NonSingular)).getSolver();
+ new
QRDecomposition(MatrixUtils.createRealMatrix(testData3x3NonSingular)).getSolver();
Assert.assertTrue(solver.isNonSingular());
- solver = new
QRDecompositionImpl(MatrixUtils.createRealMatrix(testData3x3Singular)).getSolver();
+ solver = new
QRDecomposition(MatrixUtils.createRealMatrix(testData3x3Singular)).getSolver();
Assert.assertFalse(solver.isNonSingular());
- solver = new
QRDecompositionImpl(MatrixUtils.createRealMatrix(testData3x4)).getSolver();
+ solver = new
QRDecomposition(MatrixUtils.createRealMatrix(testData3x4)).getSolver();
Assert.assertTrue(solver.isNonSingular());
- solver = new
QRDecompositionImpl(MatrixUtils.createRealMatrix(testData4x3)).getSolver();
+ solver = new
QRDecomposition(MatrixUtils.createRealMatrix(testData4x3)).getSolver();
Assert.assertTrue(solver.isNonSingular());
}
@@ -72,7 +72,7 @@ public class QRSolverTest {
@Test
public void testSolveDimensionErrors() {
DecompositionSolver solver =
- new
QRDecompositionImpl(MatrixUtils.createRealMatrix(testData3x3NonSingular)).getSolver();
+ new
QRDecomposition(MatrixUtils.createRealMatrix(testData3x3NonSingular)).getSolver();
RealMatrix b = MatrixUtils.createRealMatrix(new double[2][2]);
try {
solver.solve(b);
@@ -92,7 +92,7 @@ public class QRSolverTest {
@Test
public void testSolveRankErrors() {
DecompositionSolver solver =
- new
QRDecompositionImpl(MatrixUtils.createRealMatrix(testData3x3Singular)).getSolver();
+ new
QRDecomposition(MatrixUtils.createRealMatrix(testData3x3Singular)).getSolver();
RealMatrix b = MatrixUtils.createRealMatrix(new double[3][2]);
try {
solver.solve(b);
@@ -112,7 +112,7 @@ public class QRSolverTest {
@Test
public void testSolve() {
QRDecomposition decomposition =
- new
QRDecompositionImpl(MatrixUtils.createRealMatrix(testData3x3NonSingular));
+ new
QRDecomposition(MatrixUtils.createRealMatrix(testData3x3NonSingular));
DecompositionSolver solver = decomposition.getSolver();
RealMatrix b = MatrixUtils.createRealMatrix(new double[][] {
{ -102, 12250 }, { 544, 24500 }, { 167, -36750 }
@@ -161,7 +161,7 @@ public class QRSolverTest {
});
// despite perturbation, the least square solution should be pretty
good
- RealMatrix x = new QRDecompositionImpl(a).getSolver().solve(b);
+ RealMatrix x = new QRDecomposition(a).getSolver().solve(b);
Assert.assertEquals(0, x.subtract(xRef).getNorm(), 0.01 * noise * p *
q);
}
@@ -174,7 +174,7 @@ public class QRSolverTest {
RealMatrix a = createTestMatrix(r, p, q);
RealMatrix xRef = createTestMatrix(r, q, BlockRealMatrix.BLOCK_SIZE
+ 3);
RealMatrix b = a.multiply(xRef);
- RealMatrix x = new QRDecompositionImpl(a).getSolver().solve(b);
+ RealMatrix x = new QRDecomposition(a).getSolver().solve(b);
// too many equations, the system cannot be solved at all
Assert.assertTrue(x.subtract(xRef).getNorm() / (p * q) > 0.01);
