Author: erans
Date: Thu Sep 1 12:30:50 2011
New Revision: 1164044
URL: http://svn.apache.org/viewvc?rev=1164044&view=rev
Log:
MATH-413
Removed setters; convergence checker, line search solver and preconditioner
set in contructor.
Modified:
commons/proper/math/trunk/src/main/java/org/apache/commons/math/optimization/general/NonLinearConjugateGradientOptimizer.java
commons/proper/math/trunk/src/test/java/org/apache/commons/math/optimization/general/NonLinearConjugateGradientOptimizerTest.java
Modified:
commons/proper/math/trunk/src/main/java/org/apache/commons/math/optimization/general/NonLinearConjugateGradientOptimizer.java
URL:
http://svn.apache.org/viewvc/commons/proper/math/trunk/src/main/java/org/apache/commons/math/optimization/general/NonLinearConjugateGradientOptimizer.java?rev=1164044&r1=1164043&r2=1164044&view=diff
==============================================================================
---
commons/proper/math/trunk/src/main/java/org/apache/commons/math/optimization/general/NonLinearConjugateGradientOptimizer.java
(original)
+++
commons/proper/math/trunk/src/main/java/org/apache/commons/math/optimization/general/NonLinearConjugateGradientOptimizer.java
Thu Sep 1 12:30:50 2011
@@ -24,6 +24,8 @@ import org.apache.commons.math.analysis.
import org.apache.commons.math.exception.util.LocalizedFormats;
import org.apache.commons.math.optimization.GoalType;
import org.apache.commons.math.optimization.RealPointValuePair;
+import org.apache.commons.math.optimization.SimpleScalarValueChecker;
+import org.apache.commons.math.optimization.ConvergenceChecker;
import org.apache.commons.math.util.FastMath;
/**
@@ -43,47 +45,82 @@ public class NonLinearConjugateGradientO
/** Update formula for the beta parameter. */
private final ConjugateGradientFormula updateFormula;
/** Preconditioner (may be null). */
- private Preconditioner preconditioner;
+ private final Preconditioner preconditioner;
/** solver to use in the line search (may be null). */
- private UnivariateRealSolver solver;
+ private final UnivariateRealSolver solver;
/** Initial step used to bracket the optimum in line search. */
private double initialStep;
/** Current point. */
private double[] point;
/**
- * Simple constructor with default settings.
- * The convergence check is set to a {@link
- * org.apache.commons.math.optimization.SimpleVectorialValueChecker}.
+ * Constructor with default {@link SimpleScalarValueChecker checker},
+ * {@link BrentSolver line search solver} and
+ * {@link IdentityPreconditioner preconditioner}.
*
* @param updateFormula formula to use for updating the β parameter,
* must be one of {@link ConjugateGradientFormula#FLETCHER_REEVES} or
{@link
- * ConjugateGradientFormula#POLAK_RIBIERE}
+ * ConjugateGradientFormula#POLAK_RIBIERE}.
*/
public NonLinearConjugateGradientOptimizer(final ConjugateGradientFormula
updateFormula) {
- this.updateFormula = updateFormula;
- preconditioner = null;
- solver = null;
- initialStep = 1.0;
+ this(updateFormula,
+ new SimpleScalarValueChecker());
}
/**
- * Set the preconditioner.
- * @param preconditioner preconditioner to use for next optimization,
- * may be null to remove an already registered preconditioner
+ * Constructor with default {@link BrentSolver line search solver} and
+ * {@link IdentityPreconditioner preconditioner}.
+ *
+ * @param updateFormula formula to use for updating the β parameter,
+ * must be one of {@link ConjugateGradientFormula#FLETCHER_REEVES} or
{@link
+ * ConjugateGradientFormula#POLAK_RIBIERE}.
+ * @param checker Convergence checker.
*/
- public void setPreconditioner(final Preconditioner preconditioner) {
- this.preconditioner = preconditioner;
+ public NonLinearConjugateGradientOptimizer(final ConjugateGradientFormula
updateFormula,
+
ConvergenceChecker<RealPointValuePair> checker) {
+ this(updateFormula,
+ checker,
+ new BrentSolver(),
+ new IdentityPreconditioner());
+ }
+
+
+ /**
+ * Constructor with default {@link IdentityPreconditioner preconditioner}.
+ *
+ * @param updateFormula formula to use for updating the β parameter,
+ * must be one of {@link ConjugateGradientFormula#FLETCHER_REEVES} or
{@link
+ * ConjugateGradientFormula#POLAK_RIBIERE}.
+ * @param checker Convergence checker.
+ * @param lineSearchSolver Solver to use during line search.
+ */
+ public NonLinearConjugateGradientOptimizer(final ConjugateGradientFormula
updateFormula,
+
ConvergenceChecker<RealPointValuePair> checker,
+ final UnivariateRealSolver
lineSearchSolver) {
+ this(updateFormula,
+ checker,
+ lineSearchSolver,
+ new IdentityPreconditioner());
}
/**
- * Set the solver to use during line search.
- * @param lineSearchSolver solver to use during line search, may be null
- * to remove an already registered solver and fall back to the
- * default {@link BrentSolver Brent solver}.
+ * @param updateFormula formula to use for updating the β parameter,
+ * must be one of {@link ConjugateGradientFormula#FLETCHER_REEVES} or
{@link
+ * ConjugateGradientFormula#POLAK_RIBIERE}.
+ * @param checker Convergence checker.
+ * @param lineSearchSolver Solver to use during line search.
+ * @param preconditioner Preconditioner.
*/
- public void setLineSearchSolver(final UnivariateRealSolver
lineSearchSolver) {
+ public NonLinearConjugateGradientOptimizer(final ConjugateGradientFormula
updateFormula,
+
ConvergenceChecker<RealPointValuePair> checker,
+ final UnivariateRealSolver
lineSearchSolver,
+ final Preconditioner
preconditioner) {
+ super(checker);
+
+ this.updateFormula = updateFormula;
solver = lineSearchSolver;
+ this.preconditioner = preconditioner;
+ initialStep = 1.0;
}
/**
@@ -107,13 +144,7 @@ public class NonLinearConjugateGradientO
/** {@inheritDoc} */
@Override
protected RealPointValuePair doOptimize() {
- // Initialization.
- if (preconditioner == null) {
- preconditioner = new IdentityPreconditioner();
- }
- if (solver == null) {
- solver = new BrentSolver();
- }
+ final ConvergenceChecker checker = getConvergenceChecker();
point = getStartPoint();
final GoalType goal = getGoalType();
final int n = point.length;
@@ -143,7 +174,7 @@ public class NonLinearConjugateGradientO
RealPointValuePair previous = current;
current = new RealPointValuePair(point, objective);
if (previous != null) {
- if (getConvergenceChecker().converged(iter, previous,
current)) {
+ if (checker.converged(iter, previous, current)) {
// We have found an optimum.
return current;
}
@@ -230,7 +261,7 @@ public class NonLinearConjugateGradientO
}
/** Default identity preconditioner. */
- private static class IdentityPreconditioner implements Preconditioner {
+ public static class IdentityPreconditioner implements Preconditioner {
/** {@inheritDoc} */
public double[] precondition(double[] variables, double[] r) {
Modified:
commons/proper/math/trunk/src/test/java/org/apache/commons/math/optimization/general/NonLinearConjugateGradientOptimizerTest.java
URL:
http://svn.apache.org/viewvc/commons/proper/math/trunk/src/test/java/org/apache/commons/math/optimization/general/NonLinearConjugateGradientOptimizerTest.java?rev=1164044&r1=1164043&r2=1164044&view=diff
==============================================================================
---
commons/proper/math/trunk/src/test/java/org/apache/commons/math/optimization/general/NonLinearConjugateGradientOptimizerTest.java
(original)
+++
commons/proper/math/trunk/src/test/java/org/apache/commons/math/optimization/general/NonLinearConjugateGradientOptimizerTest.java
Thu Sep 1 12:30:50 2011
@@ -100,8 +100,8 @@ public class NonLinearConjugateGradientO
LinearProblem problem =
new LinearProblem(new double[][] { { 2 } }, new double[] { 3 });
NonLinearConjugateGradientOptimizer optimizer =
- new
NonLinearConjugateGradientOptimizer(ConjugateGradientFormula.POLAK_RIBIERE);
- optimizer.setConvergenceChecker(new SimpleScalarValueChecker(1.0e-6,
1.0e-6));
+ new
NonLinearConjugateGradientOptimizer(ConjugateGradientFormula.POLAK_RIBIERE,
+ new
SimpleScalarValueChecker(1e-6, 1e-6));
RealPointValuePair optimum =
optimizer.optimize(100, problem, GoalType.MINIMIZE, new double[] {
0 });
Assert.assertEquals(1.5, optimum.getPoint()[0], 1.0e-10);
@@ -115,8 +115,8 @@ public class NonLinearConjugateGradientO
new double[] { 4.0, 6.0, 1.0 });
NonLinearConjugateGradientOptimizer optimizer =
- new
NonLinearConjugateGradientOptimizer(ConjugateGradientFormula.POLAK_RIBIERE);
- optimizer.setConvergenceChecker(new SimpleScalarValueChecker(1.0e-6,
1.0e-6));
+ new
NonLinearConjugateGradientOptimizer(ConjugateGradientFormula.POLAK_RIBIERE,
+ new
SimpleScalarValueChecker(1e-6, 1e-6));
RealPointValuePair optimum =
optimizer.optimize(100, problem, GoalType.MINIMIZE, new double[] {
0, 0 });
Assert.assertEquals(7.0, optimum.getPoint()[0], 1.0e-10);
@@ -136,8 +136,8 @@ public class NonLinearConjugateGradientO
{ 0, 0, 0, 0, 0, 2 }
}, new double[] { 0.0, 1.1, 2.2, 3.3, 4.4, 5.5 });
NonLinearConjugateGradientOptimizer optimizer =
- new
NonLinearConjugateGradientOptimizer(ConjugateGradientFormula.POLAK_RIBIERE);
- optimizer.setConvergenceChecker(new SimpleScalarValueChecker(1.0e-6,
1.0e-6));
+ new
NonLinearConjugateGradientOptimizer(ConjugateGradientFormula.POLAK_RIBIERE,
+ new
SimpleScalarValueChecker(1e-6, 1e-6));
RealPointValuePair optimum =
optimizer.optimize(100, problem, GoalType.MINIMIZE, new double[] {
0, 0, 0, 0, 0, 0 });
for (int i = 0; i < problem.target.length; ++i) {
@@ -153,8 +153,8 @@ public class NonLinearConjugateGradientO
{ 0, -1, 1 }
}, new double[] { 1, 1, 1});
NonLinearConjugateGradientOptimizer optimizer =
- new
NonLinearConjugateGradientOptimizer(ConjugateGradientFormula.POLAK_RIBIERE);
- optimizer.setConvergenceChecker(new SimpleScalarValueChecker(1.0e-6,
1.0e-6));
+ new
NonLinearConjugateGradientOptimizer(ConjugateGradientFormula.POLAK_RIBIERE,
+ new
SimpleScalarValueChecker(1e-6, 1e-6));
RealPointValuePair optimum =
optimizer.optimize(100, problem, GoalType.MINIMIZE, new double[] {
0, 0, 0 });
Assert.assertEquals(1.0, optimum.getPoint()[0], 1.0e-10);
@@ -175,22 +175,26 @@ public class NonLinearConjugateGradientO
{ 0, 0, 0, 0, 1, 1 }
}, new double[] { 2, -9, 2, 2, 1 + epsilon * epsilon, 2});
- NonLinearConjugateGradientOptimizer optimizer =
- new
NonLinearConjugateGradientOptimizer(ConjugateGradientFormula.POLAK_RIBIERE);
- optimizer.setPreconditioner(new Preconditioner() {
- public double[] precondition(double[] point, double[] r) {
- double[] d = r.clone();
- d[0] /= 72.0;
- d[1] /= 30.0;
- d[2] /= 314.0;
- d[3] /= 260.0;
- d[4] /= 2 * (1 + epsilon * epsilon);
- d[5] /= 4.0;
- return d;
- }
- });
- optimizer.setConvergenceChecker(new SimpleScalarValueChecker(1.0e-13,
1.0e-13));
-
+ final Preconditioner preconditioner
+ = new Preconditioner() {
+ public double[] precondition(double[] point, double[] r) {
+ double[] d = r.clone();
+ d[0] /= 72.0;
+ d[1] /= 30.0;
+ d[2] /= 314.0;
+ d[3] /= 260.0;
+ d[4] /= 2 * (1 + epsilon * epsilon);
+ d[5] /= 4.0;
+ return d;
+ }
+ };
+
+ NonLinearConjugateGradientOptimizer optimizer =
+ new
NonLinearConjugateGradientOptimizer(ConjugateGradientFormula.POLAK_RIBIERE,
+ new
SimpleScalarValueChecker(1e-13, 1e-13),
+ new BrentSolver(),
+ preconditioner);
+
RealPointValuePair optimum =
optimizer.optimize(100, problem, GoalType.MINIMIZE, new double[] {
0, 0, 0, 0, 0, 0 });
Assert.assertEquals( 3.0, optimum.getPoint()[0], 1.0e-10);
@@ -210,8 +214,8 @@ public class NonLinearConjugateGradientO
{ -3, 0, -9 }
}, new double[] { 1, 1, 1 });
NonLinearConjugateGradientOptimizer optimizer =
- new
NonLinearConjugateGradientOptimizer(ConjugateGradientFormula.POLAK_RIBIERE);
- optimizer.setConvergenceChecker(new SimpleScalarValueChecker(1.0e-6,
1.0e-6));
+ new
NonLinearConjugateGradientOptimizer(ConjugateGradientFormula.POLAK_RIBIERE,
+ new
SimpleScalarValueChecker(1e-6, 1e-6));
RealPointValuePair optimum =
optimizer.optimize(100, problem, GoalType.MINIMIZE, new
double[] { 0, 0, 0 });
Assert.assertTrue(optimum.getValue() > 0.5);
@@ -226,10 +230,9 @@ public class NonLinearConjugateGradientO
{ 7.0, 5.0, 9.0, 10.0 }
}, new double[] { 32, 23, 33, 31 });
NonLinearConjugateGradientOptimizer optimizer =
- new
NonLinearConjugateGradientOptimizer(ConjugateGradientFormula.POLAK_RIBIERE);
- optimizer.setConvergenceChecker(new SimpleScalarValueChecker(1.0e-13,
1.0e-13));
- BrentSolver solver = new BrentSolver(1e-15, 1e-15);
- optimizer.setLineSearchSolver(solver);
+ new
NonLinearConjugateGradientOptimizer(ConjugateGradientFormula.POLAK_RIBIERE,
+ new
SimpleScalarValueChecker(1e-13, 1e-13),
+ new BrentSolver(1e-15,
1e-15));
RealPointValuePair optimum1 =
optimizer.optimize(200, problem1, GoalType.MINIMIZE, new double[]
{ 0, 1, 2, 3 });
Assert.assertEquals(1.0, optimum1.getPoint()[0], 1.0e-4);
@@ -261,8 +264,8 @@ public class NonLinearConjugateGradientO
}, new double[] { 7.0, 3.0, 5.0 });
NonLinearConjugateGradientOptimizer optimizer =
- new
NonLinearConjugateGradientOptimizer(ConjugateGradientFormula.POLAK_RIBIERE);
- optimizer.setConvergenceChecker(new SimpleScalarValueChecker(1.0e-6,
1.0e-6));
+ new
NonLinearConjugateGradientOptimizer(ConjugateGradientFormula.POLAK_RIBIERE,
+ new
SimpleScalarValueChecker(1e-6, 1e-6));
RealPointValuePair optimum =
optimizer.optimize(100, problem, GoalType.MINIMIZE, new double[] {
7, 6, 5, 4 });
Assert.assertEquals(0, optimum.getValue(), 1.0e-10);
@@ -279,8 +282,8 @@ public class NonLinearConjugateGradientO
{ 0.0, 0.0, 0.0, -1.0, 1.0, 0.0 }
}, new double[] { 3.0, 12.0, -1.0, 7.0, 1.0 });
NonLinearConjugateGradientOptimizer optimizer =
- new
NonLinearConjugateGradientOptimizer(ConjugateGradientFormula.POLAK_RIBIERE);
- optimizer.setConvergenceChecker(new SimpleScalarValueChecker(1.0e-6,
1.0e-6));
+ new
NonLinearConjugateGradientOptimizer(ConjugateGradientFormula.POLAK_RIBIERE,
+ new
SimpleScalarValueChecker(1e-6, 1e-6));
RealPointValuePair optimum =
optimizer.optimize(100, problem, GoalType.MINIMIZE, new double[] {
2, 2, 2, 2, 2, 2 });
Assert.assertEquals(0, optimum.getValue(), 1.0e-10);
@@ -295,8 +298,8 @@ public class NonLinearConjugateGradientO
}, new double[] { 3.0, 1.0, 5.0 });
NonLinearConjugateGradientOptimizer optimizer =
- new
NonLinearConjugateGradientOptimizer(ConjugateGradientFormula.POLAK_RIBIERE);
- optimizer.setConvergenceChecker(new SimpleScalarValueChecker(1.0e-6,
1.0e-6));
+ new
NonLinearConjugateGradientOptimizer(ConjugateGradientFormula.POLAK_RIBIERE,
+ new
SimpleScalarValueChecker(1e-6, 1e-6));
RealPointValuePair optimum =
optimizer.optimize(100, problem, GoalType.MINIMIZE, new double[] {
1, 1 });
Assert.assertEquals(2.0, optimum.getPoint()[0], 1.0e-8);
@@ -313,8 +316,8 @@ public class NonLinearConjugateGradientO
}, new double[] { 3.0, 1.0, 4.0 });
NonLinearConjugateGradientOptimizer optimizer =
- new
NonLinearConjugateGradientOptimizer(ConjugateGradientFormula.POLAK_RIBIERE);
- optimizer.setConvergenceChecker(new SimpleScalarValueChecker(1.0e-6,
1.0e-6));
+ new
NonLinearConjugateGradientOptimizer(ConjugateGradientFormula.POLAK_RIBIERE,
+ new
SimpleScalarValueChecker(1e-6, 1e-6));
RealPointValuePair optimum =
optimizer.optimize(100, problem, GoalType.MINIMIZE, new double[] {
1, 1 });
Assert.assertTrue(optimum.getValue() > 0.1);
@@ -330,10 +333,9 @@ public class NonLinearConjugateGradientO
circle.addPoint( 35.0, 15.0);
circle.addPoint( 45.0, 97.0);
NonLinearConjugateGradientOptimizer optimizer =
- new
NonLinearConjugateGradientOptimizer(ConjugateGradientFormula.POLAK_RIBIERE);
- optimizer.setConvergenceChecker(new SimpleScalarValueChecker(1.0e-30,
1.0e-30));
- UnivariateRealSolver solver = new BrentSolver(1e-15, 1e-13);
- optimizer.setLineSearchSolver(solver);
+ new
NonLinearConjugateGradientOptimizer(ConjugateGradientFormula.POLAK_RIBIERE,
+ new
SimpleScalarValueChecker(1e-30, 1e-30),
+ new BrentSolver(1e-15,
1e-13));
RealPointValuePair optimum =
optimizer.optimize(100, circle, GoalType.MINIMIZE, new double[] {
98.680, 47.345 });
Point2D.Double center = new Point2D.Double(optimum.getPointRef()[0],
optimum.getPointRef()[1]);
