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Re: [cilib-devel] [PATCH] Constriction PSO
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From: Gary P. <gpa...@gm...> - 2009-07-03 07:53:24
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I've cleaned up the unit test to not need to be initialized as it was being
done. Some mocks were created for the tests and as aresult they are simpler.
Patch has been applied to next.
On Friday 03 July 2009 08:21:33 Gary Pampara wrote:
> Patch looks good. This is something that we have needed to add for a while
> now.
>
> The test cases are a little complex though. Especially the
> testUpdateAndConstraintAssertion(). The tests should ideally be testing one
> thing per test.
>
> In the first part of the test, the following is executed:
>
> MersenneTwister twister = new MersenneTwister();
> FunctionMinimisationProblem problem = new
> FunctionMinimisationProblem();
> problem.setFunction(new Spherical());
>
> StandardParticle nBest = new StandardParticle();
> StandardParticle particle = new StandardParticle();
> particle.initialise(problem);
> nBest.initialise(problem);
> particle.getVelocity().randomize(twister);
> particle.setNeighbourhoodBest(nBest);
>
> ConstrictionVelocityUpdate constrictionVelocityUpdate = new
> ConstrictionVelocityUpdate();
>
> boolean assertionExceptionOccured = false;
> try {
> constrictionVelocityUpdate.updateVelocity(particle);
> }
> catch(UnsupportedOperationException ex) {
> assertionExceptionOccured = true;
> }
>
> I understand the need to have c_1 + c_2 < 4, but is there a reason why the
> are defaultly set to 3.0? Also, the execption thrown in the check within
> the ConstrictionVelocityUpdate states that the values should be "greater or
> equal to 4". I assume that was a typo? Or is the logic incorrect?
>
> The last part of that test tests that an exception is expected. We should
> create a new test method for that with a signature similar to:
>
> @Test(expected=UnsupportedOperationException.class)
> public void illegalVelocityUpdate() {
> ....
>
> Or something similar :P I also want to see if we can't mock some of the
> objects in the test to make the unit test more isolated.
>
> Regards,
> Gary
>
> On Thursday 02 July 2009 14:46:24 Andrich wrote:
> > Added a velocity update strategy for a Constriction PSO as well as its
> > unit test. ---
> > .../ConstrictionVelocityUpdate.java | 243
> > ++++++++++++++++++++ .../ConstrictionVelocityUpdateTest.java |
> > 144 ++++++++++++ xml/constrictionPSO.xml |
> > 57 +++++
> > 3 files changed, 444 insertions(+), 0 deletions(-)
> > create mode 100644
> > src/main/java/net/sourceforge/cilib/pso/velocityupdatestrategies/Constric
> >ti onVelocityUpdate.java create mode 100644
> > src/test/java/net/sourceforge/cilib/pso/velocityupdatestrategies/Constric
> >ti onVelocityUpdateTest.java create mode 100644 xml/constrictionPSO.xml
> >
> > diff --git
> > a/src/main/java/net/sourceforge/cilib/pso/velocityupdatestrategies/Constr
> >ic tionVelocityUpdate.java
> > b/src/main/java/net/sourceforge/cilib/pso/velocityupdatestrategies/Constr
> >ic tionVelocityUpdate.java new file mode 100644
> > index 0000000..41d955b
> > --- /dev/null
> > +++
> > b/src/main/java/net/sourceforge/cilib/pso/velocityupdatestrategies/Constr
> >ic tionVelocityUpdate.java @@ -0,0 +1,243 @@
> > +/**
> > + * Copyright (C) 2003 - 2009
> > + * Computational Intelligence Research Group (CIRG@UP)
> > + * Department of Computer Science
> > + * University of Pretoria
> > + * South Africa
> > + *
> > + * This program is free software; you can redistribute it and/or modify
> > + * it under the terms of the GNU General Public License as published by
> > + * the Free Software Foundation; either version 2 of the License, or
> > + * (at your option) any later version.
> > + *
> > + * This program 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 General Public License for more details.
> > + *
> > + * You should have received a copy of the GNU General Public License
> > + * along with this program; if not, write to the Free Software
> > + * Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307
> > USA + */
> > +package net.sourceforge.cilib.pso.velocityupdatestrategies;
> > +
> > +import net.sourceforge.cilib.controlparameter.ConstantControlParameter;
> > +import net.sourceforge.cilib.controlparameter.ControlParameter;
> > +import
> > net.sourceforge.cilib.controlparameter.RandomizingControlParameter;
> > +import net.sourceforge.cilib.entity.Particle;
> > +import net.sourceforge.cilib.type.types.container.Vector;
> > +
> > +/**
> > + * A velocity update strategy that utilizes the constriction coefficient
> > as + * developed by Clerc. References:
> > + * <ul>
> > + * <li>
> > + * Inproceedings (Clerc1999)
> > + * Clerc, M.
> > + * The swarm and the queen: towards a deterministic and adaptive
> > particle swarm + * optimization
> > + * Evolutionary Computation, 1999. CEC 99. Proceedings of the 1999
> > Congress on, + * 1999, 3, -1957 Vol. 3
> > + * </li>
> > + * <li>
> > + * Article (Clerc2002)
> > + * Clerc, M. & Kennedy, J.
> > + * The particle swarm - explosion, stability, and convergence in a
> > + * multidimensional complex space Evolutionary Computation,
> > + * IEEE Transactions on, 2002, 6, 58-73
> > + * </li>
> > + * </ul>
> > + *
> > + * Note, this strategy does not the inertia control parameter.
> > + * Certain constraints are imposed on the other control parameters in
> > order to + * calculate the constriction coefficient, namely:
> > + * $c1r1 + c2r2 \leq 4$ , and
> > + * $\kappa \in [0, 1]$
> > + *
> > + * @author andrich
> > + */
> > +public class ConstrictionVelocityUpdate implements
> > VelocityUpdateStrategy { +
> > + protected ControlParameter socialAcceleration;
> > + protected ControlParameter cognitiveAcceleration;
> > + protected ControlParameter vMax;
> > + protected ControlParameter kappa;
> > +
> > + /**
> > + * Default constructor. The values given to the control parameters
> > attempt to + * adhere to the constraints of calculating the
> > constriction constant, but do not + * necessarily represent good
> > values.
> > + */
> > + public ConstrictionVelocityUpdate() {
> > + socialAcceleration = new RandomizingControlParameter();
> > + cognitiveAcceleration = new RandomizingControlParameter();
> > + vMax = new ConstantControlParameter();
> > + kappa = new ConstantControlParameter();
> > +
> > + socialAcceleration.setParameter(3.0);
> > + cognitiveAcceleration.setParameter(3.0);
> > + vMax.setParameter(Double.MAX_VALUE);
> > + kappa.setParameter(0.1);
> > + }
> > +
> > + /**
> > + * Copy constructor.
> > + * @param orig the ConstrictionVelocityUpdate to copy.
> > + */
> > + public ConstrictionVelocityUpdate(ConstrictionVelocityUpdate orig) {
> > + this.socialAcceleration = new
> > RandomizingControlParameter((RandomizingControlParameter)
> > orig.socialAcceleration); + this.cognitiveAcceleration = new
> > RandomizingControlParameter((RandomizingControlParameter)
> > orig.cognitiveAcceleration); + this.vMax = new
> > ConstantControlParameter((ConstantControlParameter) orig.vMax); +
> > this.kappa = new ConstantControlParameter((ConstantControlParameter)
> > orig.kappa); + }
> > +
> > + /**
> > + * {@inheritDoc }
> > + */
> > + @Override
> > + public VelocityUpdateStrategy getClone() {
> > + return new ConstrictionVelocityUpdate(this);
> > + }
> > +
> > + /**
> > + * {@inheritDoc }
> > + */
> > + @Override
> > + public void updateVelocity(Particle particle) {
> > + assertAccelerationConstraints();
> > +
> > + Vector velocity = (Vector) particle.getVelocity();
> > + Vector position = (Vector) particle.getPosition();
> > + Vector bestPosition = (Vector) particle.getBestPosition();
> > + Vector nBestPosition = (Vector)
> > particle.getNeighbourhoodBest().getBestPosition(); +
> > +
> > + for (int i = 0; i < particle.getDimension(); ++i) {
> > + // calculate the constriction coefficient
> > + double c1 = cognitiveAcceleration.getParameter();
> > + double c2 = socialAcceleration.getParameter();
> > + // c1r1 + c2r2 has to be greater or equal to 4
> > + while ((c1 + c2) < 4) {
> > + c1 = cognitiveAcceleration.getParameter();
> > + c2 = socialAcceleration.getParameter();
> > + }
> > + double phi = c1 + c2;
> > + double constrictionCoefficient = (2 * kappa.getParameter())
> > / + Math.abs(2 - phi - Math.sqrt(phi * (phi - 4.0)));
> > +
> > + double value = velocity.getReal(i) +
> > + (bestPosition.getReal(i) - position.getReal(i)) * c1
> > + + (nBestPosition.getReal(i) - position.getReal(i)) *
> > c2; + value = constrictionCoefficient * value;
> > + velocity.setReal(i, value);
> > +
> > + clamp(velocity, i);
> > + }
> > + }
> > +
> > + /**
> > + * Clamp to maximum velocity.
> > + * @param velocity The {@link Vector} to be clamped.
> > + * @param i The dimension index to be clamped
> > + */
> > + protected void clamp(Vector velocity, int i) {
> > + // if vMax is not set (or set as max), it is unnecessary to
> > clamp + if (Double.compare(vMax.getParameter(), Double.MAX_VALUE)
> > == 0) { + return;
> > + }
> > + if (velocity.getReal(i) < -vMax.getParameter()) {
> > + velocity.setReal(i, -vMax.getParameter());
> > + } else if (velocity.getReal(i) > vMax.getParameter()) {
> > + velocity.setReal(i, vMax.getParameter());
> > + }
> > + }
> > +
> > + /**
> > + * {@inheritDoc }
> > + */
> > + @Override
> > + public void updateControlParameters(Particle particle) {
> > + this.kappa.updateParameter();
> > + this.cognitiveAcceleration.updateParameter();
> > + this.socialAcceleration.updateParameter();
> > + this.vMax.updateParameter();
> > + }
> > +
> > + /**
> > + * Ensure that values of c1 and c2 make it possible to calculate the
> > + * constriction coefficient.
> > + */
> > + private void assertAccelerationConstraints() {
> > + double c1 = ((RandomizingControlParameter)
> > cognitiveAcceleration).getControlParameter().getParameter(); +
> > double c2 = ((RandomizingControlParameter)
> > socialAcceleration).getControlParameter().getParameter(); + if (c1
> > + c2 < 4) {
> > + throw new UnsupportedOperationException("Parameter
> > constraint violation: " + + "The sum of the Cognitive
> > (" + c1 + ") and Social (" + c2 + ") acceleration parameters " + +
> > "has to be greater than or equal to 4.");
> > + }
> > + }
> > +
> > + /**
> > + * Get the coginitive acceleration parameter.
> > + * @return the cognitive acceleration {@link ControlParameter
> > control parameter }. + */
> > + public ControlParameter getCognitiveAcceleration() {
> > + return cognitiveAcceleration;
> > + }
> > +
> > + /**
> > + * Set the coginitive acceleration parameter.
> > + * @param cognitiveAcceleration the new cognitive acceleration
> > {@link ControlParameter control parameter }. + */
> > + public void setCognitiveAcceleration(ControlParameter
> > cognitiveAcceleration) { + this.cognitiveAcceleration =
> > cognitiveAcceleration;
> > + }
> > +
> > + /**
> > + * Get the Kappa control parameter.
> > + * @return the kappa {@link ControlParameter control parameter }.
> > + */
> > + public ControlParameter getKappa() {
> > + return kappa;
> > + }
> > +
> > + /**
> > + * Set the Kappa control parameter.
> > + * @param kappa the new kappa {@link ControlParameter control
> > parameter }. + */
> > + public void setKappa(ControlParameter kappa) {
> > + this.kappa = kappa;
> > + }
> > +
> > + /**
> > + * Get the social acceleration parameter.
> > + * @return the social acceleration {@link ControlParameter control
> > parameter }. + */
> > + public ControlParameter getSocialAcceleration() {
> > + return socialAcceleration;
> > + }
> > +
> > + /**
> > + * Set the social acceleration parameter.
> > + * @param socialAcceleration the new social accerelation {@link
> > ControlParameter control parameter }. + */
> > + public void setSocialAcceleration(ControlParameter
> > socialAcceleration) { + this.socialAcceleration =
> > socialAcceleration;
> > + }
> > +
> > + /**
> > + * Get the maximum velocity parameter.
> > + * @return the maximum velocity {@link ControlParameter control
> > parameter }. + */
> > + public ControlParameter getVMax() {
> > + return vMax;
> > + }
> > +
> > + /**
> > + * Set the maximum velocity parameter.
> > + * @param vMax the new maximum velocity {@link ControlParameter
> > control parameter }. + */
> > + public void setVMax(ControlParameter vMax) {
> > + this.vMax = vMax;
> > + }
> > +}
> > diff --git
> > a/src/test/java/net/sourceforge/cilib/pso/velocityupdatestrategies/Constr
> >ic tionVelocityUpdateTest.java
> > b/src/test/java/net/sourceforge/cilib/pso/velocityupdatestrategies/Constr
> >ic tionVelocityUpdateTest.java new file mode 100644
> > index 0000000..189cca9
> > --- /dev/null
> > +++
> > b/src/test/java/net/sourceforge/cilib/pso/velocityupdatestrategies/Constr
> >ic tionVelocityUpdateTest.java @@ -0,0 +1,144 @@
> > +/**
> > + * Copyright (C) 2003 - 2009
> > + * Computational Intelligence Research Group (CIRG@UP)
> > + * Department of Computer Science
> > + * University of Pretoria
> > + * South Africa
> > + *
> > + * This program is free software; you can redistribute it and/or modify
> > + * it under the terms of the GNU General Public License as published by
> > + * the Free Software Foundation; either version 2 of the License, or
> > + * (at your option) any later version.
> > + *
> > + * This program 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 General Public License for more details.
> > + *
> > + * You should have received a copy of the GNU General Public License
> > + * along with this program; if not, write to the Free Software
> > + * Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307
> > USA + */
> > +package net.sourceforge.cilib.pso.velocityupdatestrategies;
> > +
> > +import net.sourceforge.cilib.controlparameter.ConstantControlParameter;
> > +import
> > net.sourceforge.cilib.controlparameter.RandomizingControlParameter;
> > +import net.sourceforge.cilib.functions.continuous.Spherical;
> > +import net.sourceforge.cilib.math.Maths;
> > +import net.sourceforge.cilib.math.random.generator.MersenneTwister;
> > +import net.sourceforge.cilib.problem.FunctionMinimisationProblem;
> > +import net.sourceforge.cilib.pso.particle.StandardParticle;
> > +import net.sourceforge.cilib.type.types.Numeric;
> > +import net.sourceforge.cilib.type.types.container.Vector;
> > +import org.junit.Assert;
> > +import org.junit.Test;
> > +
> > +/**
> > + * Unit test for the constriction velocity update.
> > + * @author andrich
> > + */
> > +public class ConstrictionVelocityUpdateTest {
> > +
> > + /**
> > + * Test cloning and implicetly the copy constructor.
> > + */
> > + @Test
> > + public void testClone() {
> > + ConstrictionVelocityUpdate original = new
> > ConstrictionVelocityUpdate(); + ConstrictionVelocityUpdate copy =
> > (ConstrictionVelocityUpdate) original.getClone(); +
> > + Assert.assertEquals(original.getKappa().getParameter(),
> > copy.getKappa().getParameter(), Maths.EPSILON); +
> > Assert.assertEquals(original.getVMax().getParameter(),
> > copy.getVMax().getParameter(), Maths.EPSILON); +
> > Assert.assertEquals(((RandomizingControlParameter)original.cognitiveAccel
> >er ation).getControlParameter().getParameter(), +
> > ((RandomizingControlParameter)copy.cognitiveAcceleration).getControlParam
> >et er().getParameter(), Maths.EPSILON); +
> > Assert.assertEquals(((RandomizingControlParameter)original.socialAccelera
> >ti on).getControlParameter().getParameter(), +
> > ((RandomizingControlParameter)copy.socialAcceleration).getControlParamete
> >r( ).getParameter(), Maths.EPSILON); +
> > + copy.setKappa(new ConstantControlParameter(0.7));
> > + copy.setVMax(new ConstantControlParameter(0.7));
> > + RandomizingControlParameter randomizingControlParameter = new
> > RandomizingControlParameter(); +
> > randomizingControlParameter.setParameter(4.0);
> > + copy.setSocialAcceleration(new
> > RandomizingControlParameter(randomizingControlParameter.getClone())); +
> > copy.setCognitiveAcceleration(new
> > RandomizingControlParameter(randomizingControlParameter.getClone())); +
> > +
> > Assert.assertFalse(Double.compare(original.getKappa().getParameter(),
> > copy.getKappa().getParameter()) == 0); +
> > Assert.assertFalse(Double.compare(original.getVMax().getParameter(),
> > copy.getVMax().getParameter()) == 0); +
> > Assert.assertFalse(Double.compare(((RandomizingControlParameter)original.
> >co gnitiveAcceleration).getControlParameter().getParameter(), +
> > ((RandomizingControlParameter)copy.cognitiveAcceleration).getControlParam
> >et er().getParameter()) == 0); +
> > Assert.assertFalse(Double.compare(((RandomizingControlParameter)original.
> >so cialAcceleration).getControlParameter().getParameter(), +
> > ((RandomizingControlParameter)copy.socialAcceleration).getControlParamete
> >r( ).getParameter()) == 0); + }
> > +
> > + /**
> > + * Test the velocity update as well as the constraint assertion.
> > + */
> > + @Test
> > + public void testUpdateAndConstraintAssertion() {
> > + MersenneTwister twister = new MersenneTwister();
> > + FunctionMinimisationProblem problem = new
> > FunctionMinimisationProblem(); + problem.setFunction(new
> > Spherical());
> > +
> > + StandardParticle nBest = new StandardParticle();
> > + StandardParticle particle = new StandardParticle();
> > + particle.initialise(problem);
> > + nBest.initialise(problem);
> > + ((Vector)particle.getVelocity()).randomize(twister);
> > + particle.setNeighbourhoodBest(nBest);
> > +
> > + ConstrictionVelocityUpdate constrictionVelocityUpdate = new
> > ConstrictionVelocityUpdate(); +
> > + boolean assertionExceptionOccured = false;
> > + try {
> > + constrictionVelocityUpdate.updateVelocity(particle);
> > + }
> > + catch(UnsupportedOperationException ex) {
> > + assertionExceptionOccured = true;
> > + }
> > +
> > + Assert.assertFalse(assertionExceptionOccured);
> > +
> > + RandomizingControlParameter randomizingControlParameter = new
> > RandomizingControlParameter(); +
> > randomizingControlParameter.setParameter(1.0);
> > + constrictionVelocityUpdate.setSocialAcceleration(new
> > RandomizingControlParameter(randomizingControlParameter.getClone())); +
> > constrictionVelocityUpdate.setCognitiveAcceleration(new
> > RandomizingControlParameter(randomizingControlParameter.getClone())); +
> > + assertionExceptionOccured = false;
> > + try {
> > + constrictionVelocityUpdate.updateVelocity(particle);
> > + }
> > + catch(UnsupportedOperationException ex) {
> > + assertionExceptionOccured = true;
> > + }
> > +
> > + Assert.assertTrue(assertionExceptionOccured);
> > +
> > + }
> > +
> > + /**
> > + * Test velocity clamping.
> > + */
> > + @Test
> > + public void testClamping() {
> > + MersenneTwister twister = new MersenneTwister();
> > + FunctionMinimisationProblem problem = new
> > FunctionMinimisationProblem(); + problem.setFunction(new
> > Spherical());
> > +
> > + StandardParticle nBest = new StandardParticle();
> > + StandardParticle particle = new StandardParticle();
> > + particle.initialise(problem);
> > + nBest.initialise(problem);
> > + ((Vector)particle.getVelocity()).randomize(twister);
> > + particle.setNeighbourhoodBest(nBest);
> > +
> > + ConstrictionVelocityUpdate constrictionVelocityUpdate = new
> > ConstrictionVelocityUpdate(); +
> > constrictionVelocityUpdate.setVMax(new ConstantControlParameter(0.5)); +
> > constrictionVelocityUpdate.updateVelocity(particle);
> > + Vector velocity = particle.getVelocity();
> > + for (Numeric number : velocity) {
> > + Assert.assertTrue(Double.compare(number.getReal(), 0.5) <=
> > 0); + Assert.assertTrue(Double.compare(number.getReal(), -0.5)
> > >= 0); + }
> > +
> > + }
> > +
> > +}
> > diff --git a/xml/constrictionPSO.xml b/xml/constrictionPSO.xml
> > new file mode 100644
> > index 0000000..77c3eb4
> > --- /dev/null
> > +++ b/xml/constrictionPSO.xml
> > @@ -0,0 +1,57 @@
> > +<?xml version="1.0"?>
> > +<!DOCTYPE simulator [
> > +<!ATTLIST algorithm id ID #IMPLIED>
> > +<!ATTLIST problem id ID #IMPLIED>
> > +<!ATTLIST measurements id ID #IMPLIED>
> > +]>
> > +<simulator>
> > + <algorithms>
> > + <algorithm id="constrictionPSO" class="pso.PSO">
> > + <initialisationStrategy
> > class="algorithm.initialisation.ClonedPopulationInitialisationStrategy">
> > + <entityType class="pso.particle.StandardParticle"> +
> > <velocityUpdateStrategy
> > class="pso.velocityupdatestrategies.ConstrictionVelocityUpdate"> +
> > <kappa class="controlparameter.ConstantControlParameter"
> > parameter="0.1" /> + <socialAcceleration
> > class="controlparameter.RandomizingControlParameter" parameter="3.0" /> +
> > <cognitiveAcceleration
> > class="controlparameter.RandomizingControlParameter" parameter="3.0" /> +
> > <!--vMax
> > class="controlparameter.ConstantControlParameter" parameter="0.1" /--> +
> > </velocityUpdateStrategy>
> > + </entityType>
> > + </initialisationStrategy>
> > + <topology class="entity.topologies.GBestTopology"/>
> > + <addStoppingCondition
> > class="stoppingcondition.MaximumIterations" maximumIterations="1000"/> +
> > </algorithm>
> > + </algorithms>
> > +
> > + <problems>
> > + <problem id="spherical"
> > class="problem.FunctionMinimisationProblem"> + <function
> > class="functions.continuous.Spherical"/>
> > + </problem>
> > + <problem id="rosenbrock"
> > class="problem.FunctionMinimisationProblem"> + <function
> > class="functions.continuous.Rosenbrock"/>
> > + </problem>
> > + <problem id="rastrigin"
> > class="problem.FunctionMinimisationProblem"> + <function
> > class="functions.continuous.unconstrained.Rastrigin"/> +
> > </problem> + </problems>
> > +
> > + <measurements id="fitness" class="simulator.MeasurementSuite"
> > resolution="10" samples="1"> + <addMeasurement
> > class="measurement.single.Fitness"/>
> > + </measurements>
> > + <simulations>
> > + <simulation>
> > + <algorithm idref="constrictionPSO"/>
> > + <problem idref="spherical"/>
> > + <measurements idref="fitness"
> > file="data/constrictionpso_spherical.txt"/> + </simulation>
> > + <simulation>
> > + <algorithm idref="constrictionPSO"/>
> > + <problem idref="rosenbrock"/>
> > + <measurements idref="fitness"
> > file="data/constrictionpso_rosenbrock.txt"/> + </simulation>
> > + <simulation>
> > + <algorithm idref="constrictionPSO"/>
> > + <problem idref="rastrigin"/>
> > + <measurements idref="fitness"
> > file="data/constrictionpso_rastrigin.txt"/> + </simulation>
> > + </simulations>
> > +</simulator>
>
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