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[DL-Learner SVN] SF.net SVN: dl-learner:[2725] trunk
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From: <jen...@us...> - 2011-03-17 11:25:05
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Revision: 2725
http://dl-learner.svn.sourceforge.net/dl-learner/?rev=2725&view=rev
Author: jenslehmann
Date: 2011-03-17 11:24:56 +0000 (Thu, 17 Mar 2011)
Log Message:
-----------
refactored learning algorithm class to (officially) allow algorithms learning SPARQL queries and fuzzy expressions
Modified Paths:
--------------
trunk/autosparql/src/main/resources/log4j.properties
trunk/components-core/src/main/java/org/dllearner/algorithms/BruteForceLearner.java
trunk/components-core/src/main/java/org/dllearner/algorithms/RandomGuesser.java
trunk/components-core/src/main/java/org/dllearner/algorithms/celoe/CELOE.java
trunk/components-core/src/main/java/org/dllearner/algorithms/el/ELLearningAlgorithm.java
trunk/components-core/src/main/java/org/dllearner/algorithms/el/ELLearningAlgorithmDisjunctive.java
trunk/components-core/src/main/java/org/dllearner/algorithms/gp/GP.java
trunk/components-core/src/main/java/org/dllearner/algorithms/isle/ISLE.java
trunk/components-core/src/main/java/org/dllearner/algorithms/ocel/OCEL.java
trunk/components-core/src/main/java/org/dllearner/algorithms/refinement/ROLearner.java
trunk/components-core/src/main/java/org/dllearner/core/ComponentManager.java
trunk/components-core/src/main/java/org/dllearner/core/LearningAlgorithm.java
trunk/components-core/src/main/java/org/dllearner/core/LearningProblemUnsupportedException.java
trunk/components-core/src/main/java/org/dllearner/core/options/CommonConfigOptions.java
trunk/components-core/src/main/java/org/dllearner/utilities/components/ComponentCombo.java
trunk/components-core/src/main/java/org/dllearner/utilities/learn/LearnConfiguration.java
trunk/components-core/src/main/java/org/dllearner/utilities/learn/LearnOWLFileConfiguration.java
trunk/components-core/src/main/java/org/dllearner/utilities/learn/LearnSPARQLConfiguration.java
trunk/components-core/src/test/java/org/dllearner/test/ClassCastExceptionTest.java
trunk/components-core/src/test/java/org/dllearner/test/ComponentTest.java
trunk/components-core/src/test/java/org/dllearner/test/SworeTest.java
trunk/interfaces/src/main/java/org/dllearner/cli/ConfMapper.java
trunk/interfaces/src/main/java/org/dllearner/cli/DocumentationGenerator.java
trunk/interfaces/src/main/java/org/dllearner/cli/Start.java
trunk/interfaces/src/main/java/org/dllearner/gui/ComponentPanel.java
trunk/interfaces/src/main/java/org/dllearner/gui/Config.java
trunk/interfaces/src/main/java/org/dllearner/gui/ConfigSave.java
trunk/interfaces/src/main/java/org/dllearner/gui/MiniGUI.java
trunk/interfaces/src/main/java/org/dllearner/gui/StartGUI.java
trunk/interfaces/src/main/java/org/dllearner/server/ClientState.java
trunk/interfaces/src/main/java/org/dllearner/server/DLLearnerWS.java
trunk/interfaces/src/test/java/org/dllearner/test/junit/ReasonerTests.java
trunk/protege/src/main/java/org/dllearner/tools/protege/Manager.java
trunk/scripts/src/main/java/org/dllearner/examples/KRKModular.java
trunk/scripts/src/main/java/org/dllearner/scripts/ConfigJavaGenerator.java
trunk/scripts/src/main/java/org/dllearner/scripts/CrossValidation.java
trunk/scripts/src/main/java/org/dllearner/scripts/NestedCrossValidation.java
trunk/scripts/src/main/java/org/dllearner/scripts/Sample.java
trunk/scripts/src/main/java/org/dllearner/scripts/SemanticBibleComparison.java
trunk/scripts/src/main/java/org/dllearner/scripts/tiger/TestIterativeLearning.java
Added Paths:
-----------
trunk/components-core/src/main/java/org/dllearner/core/AbstractCELA.java
trunk/components-core/src/main/java/org/dllearner/core/ClassExpressionLearningAlgorithm.java
trunk/components-core/src/main/java/org/dllearner/core/FuzzyClassExpressionLearningAlgorithm.java
trunk/components-core/src/main/java/org/dllearner/core/SparqlQueryLearningAlgorithm.java
Modified: trunk/autosparql/src/main/resources/log4j.properties
===================================================================
--- trunk/autosparql/src/main/resources/log4j.properties 2011-03-16 21:14:14 UTC (rev 2724)
+++ trunk/autosparql/src/main/resources/log4j.properties 2011-03-17 11:24:56 UTC (rev 2725)
@@ -25,7 +25,7 @@
# appenders are the output-targets defined above
# loglevels: trace, debug, info, warn, error, fatal
#
-log4j.rootLogger=debug, stdout, file
+log4j.rootLogger=debug, stdout
### set log levels - for more verbose logging change 'info' to 'debug' ###
@@ -34,6 +34,6 @@
log4j.category.org.dllearner.autosparql.server=INFO
####SparqlQueryGenerator
-log4j.category.org.dllearner.sparqlquerygenerator=DEBUG
+log4j.category.org.dllearner.sparqlquerygenerator=INFO
Modified: trunk/components-core/src/main/java/org/dllearner/algorithms/BruteForceLearner.java
===================================================================
--- trunk/components-core/src/main/java/org/dllearner/algorithms/BruteForceLearner.java 2011-03-16 21:14:14 UTC (rev 2724)
+++ trunk/components-core/src/main/java/org/dllearner/algorithms/BruteForceLearner.java 2011-03-17 11:24:56 UTC (rev 2725)
@@ -26,7 +26,7 @@
import java.util.List;
import java.util.Map;
-import org.dllearner.core.LearningAlgorithm;
+import org.dllearner.core.AbstractCELA;
import org.dllearner.core.LearningProblem;
import org.dllearner.core.ReasonerComponent;
import org.dllearner.core.configurators.BruteForceLearnerConfigurator;
@@ -57,7 +57,7 @@
* @author Jens Lehmann
*
*/
-public class BruteForceLearner extends LearningAlgorithm {
+public class BruteForceLearner extends AbstractCELA {
private BruteForceLearnerConfigurator configurator;
@Override
Modified: trunk/components-core/src/main/java/org/dllearner/algorithms/RandomGuesser.java
===================================================================
--- trunk/components-core/src/main/java/org/dllearner/algorithms/RandomGuesser.java 2011-03-16 21:14:14 UTC (rev 2724)
+++ trunk/components-core/src/main/java/org/dllearner/algorithms/RandomGuesser.java 2011-03-17 11:24:56 UTC (rev 2725)
@@ -25,7 +25,7 @@
import org.apache.log4j.Logger;
import org.dllearner.algorithms.gp.GPUtilities;
import org.dllearner.core.EvaluatedDescription;
-import org.dllearner.core.LearningAlgorithm;
+import org.dllearner.core.AbstractCELA;
import org.dllearner.core.LearningProblem;
import org.dllearner.core.ReasonerComponent;
import org.dllearner.core.Score;
@@ -48,7 +48,7 @@
* @author Jens Lehmann
*
*/
-public class RandomGuesser extends LearningAlgorithm {
+public class RandomGuesser extends AbstractCELA {
private RandomGuesserConfigurator configurator;
@Override
Modified: trunk/components-core/src/main/java/org/dllearner/algorithms/celoe/CELOE.java
===================================================================
--- trunk/components-core/src/main/java/org/dllearner/algorithms/celoe/CELOE.java 2011-03-16 21:14:14 UTC (rev 2724)
+++ trunk/components-core/src/main/java/org/dllearner/algorithms/celoe/CELOE.java 2011-03-17 11:24:56 UTC (rev 2725)
@@ -33,7 +33,7 @@
import org.apache.log4j.Logger;
import org.dllearner.core.ComponentInitException;
import org.dllearner.core.EvaluatedDescription;
-import org.dllearner.core.LearningAlgorithm;
+import org.dllearner.core.AbstractCELA;
import org.dllearner.core.LearningProblem;
import org.dllearner.core.ReasonerComponent;
import org.dllearner.core.configurators.CELOEConfigurator;
@@ -75,7 +75,7 @@
* @author Jens Lehmann
*
*/
-public class CELOE extends LearningAlgorithm {
+public class CELOE extends AbstractCELA {
private static Logger logger = Logger.getLogger(CELOE.class);
private CELOEConfigurator configurator;
Modified: trunk/components-core/src/main/java/org/dllearner/algorithms/el/ELLearningAlgorithm.java
===================================================================
--- trunk/components-core/src/main/java/org/dllearner/algorithms/el/ELLearningAlgorithm.java 2011-03-16 21:14:14 UTC (rev 2724)
+++ trunk/components-core/src/main/java/org/dllearner/algorithms/el/ELLearningAlgorithm.java 2011-03-17 11:24:56 UTC (rev 2725)
@@ -27,7 +27,7 @@
import org.apache.log4j.Logger;
import org.dllearner.core.ComponentInitException;
import org.dllearner.core.EvaluatedDescription;
-import org.dllearner.core.LearningAlgorithm;
+import org.dllearner.core.AbstractCELA;
import org.dllearner.core.LearningProblem;
import org.dllearner.core.ReasonerComponent;
import org.dllearner.core.configurators.Configurator;
@@ -51,7 +51,7 @@
* @author Jens Lehmann
*
*/
-public class ELLearningAlgorithm extends LearningAlgorithm {
+public class ELLearningAlgorithm extends AbstractCELA {
private static Logger logger = Logger.getLogger(ELLearningAlgorithm.class);
private ELLearningAlgorithmConfigurator configurator;
@@ -65,7 +65,7 @@
private long treeStartTime;
// a set with limited size (currently the ordering is defined in the class itself)
- private EvaluatedDescriptionSet bestEvaluatedDescriptions = new EvaluatedDescriptionSet(LearningAlgorithm.MAX_NR_OF_RESULTS);
+ private EvaluatedDescriptionSet bestEvaluatedDescriptions = new EvaluatedDescriptionSet(AbstractCELA.MAX_NR_OF_RESULTS);
private SearchTreeNode startNode;
private ELHeuristic heuristic;
Modified: trunk/components-core/src/main/java/org/dllearner/algorithms/el/ELLearningAlgorithmDisjunctive.java
===================================================================
--- trunk/components-core/src/main/java/org/dllearner/algorithms/el/ELLearningAlgorithmDisjunctive.java 2011-03-16 21:14:14 UTC (rev 2724)
+++ trunk/components-core/src/main/java/org/dllearner/algorithms/el/ELLearningAlgorithmDisjunctive.java 2011-03-17 11:24:56 UTC (rev 2725)
@@ -30,7 +30,7 @@
import org.apache.log4j.Logger;
import org.dllearner.core.ComponentInitException;
import org.dllearner.core.EvaluatedDescription;
-import org.dllearner.core.LearningAlgorithm;
+import org.dllearner.core.AbstractCELA;
import org.dllearner.core.LearningProblem;
import org.dllearner.core.ReasonerComponent;
import org.dllearner.core.configurators.Configurator;
@@ -83,7 +83,7 @@
* @author Jens Lehmann
*
*/
-public class ELLearningAlgorithmDisjunctive extends LearningAlgorithm {
+public class ELLearningAlgorithmDisjunctive extends AbstractCELA {
private static Logger logger = Logger.getLogger(ELLearningAlgorithmDisjunctive.class);
private ELLearningAlgorithmDisjunctiveConfigurator configurator;
Modified: trunk/components-core/src/main/java/org/dllearner/algorithms/gp/GP.java
===================================================================
--- trunk/components-core/src/main/java/org/dllearner/algorithms/gp/GP.java 2011-03-16 21:14:14 UTC (rev 2724)
+++ trunk/components-core/src/main/java/org/dllearner/algorithms/gp/GP.java 2011-03-17 11:24:56 UTC (rev 2725)
@@ -30,7 +30,7 @@
import java.util.Map.Entry;
import org.dllearner.algorithms.hybridgp.Psi;
-import org.dllearner.core.LearningAlgorithm;
+import org.dllearner.core.AbstractCELA;
import org.dllearner.core.LearningProblem;
import org.dllearner.core.ReasonerComponent;
import org.dllearner.core.configurators.GPConfigurator;
@@ -55,7 +55,7 @@
* @author Jens Lehmann
*
*/
-public class GP extends LearningAlgorithm {
+public class GP extends AbstractCELA {
private GPConfigurator configurator;
@Override
Modified: trunk/components-core/src/main/java/org/dllearner/algorithms/isle/ISLE.java
===================================================================
--- trunk/components-core/src/main/java/org/dllearner/algorithms/isle/ISLE.java 2011-03-16 21:14:14 UTC (rev 2724)
+++ trunk/components-core/src/main/java/org/dllearner/algorithms/isle/ISLE.java 2011-03-17 11:24:56 UTC (rev 2725)
@@ -34,7 +34,7 @@
import org.dllearner.algorithms.celoe.OENode;
import org.dllearner.core.ComponentInitException;
import org.dllearner.core.EvaluatedDescription;
-import org.dllearner.core.LearningAlgorithm;
+import org.dllearner.core.AbstractCELA;
import org.dllearner.core.LearningProblem;
import org.dllearner.core.ReasonerComponent;
import org.dllearner.core.configurators.ISLEConfigurator;
@@ -71,7 +71,7 @@
* @author Jens Lehmann
*
*/
-public class ISLE extends LearningAlgorithm {
+public class ISLE extends AbstractCELA {
private static Logger logger = Logger.getLogger(CELOE.class);
private ISLEConfigurator configurator;
Modified: trunk/components-core/src/main/java/org/dllearner/algorithms/ocel/OCEL.java
===================================================================
--- trunk/components-core/src/main/java/org/dllearner/algorithms/ocel/OCEL.java 2011-03-16 21:14:14 UTC (rev 2724)
+++ trunk/components-core/src/main/java/org/dllearner/algorithms/ocel/OCEL.java 2011-03-17 11:24:56 UTC (rev 2725)
@@ -30,7 +30,7 @@
import org.apache.log4j.Level;
import org.apache.log4j.Logger;
import org.dllearner.core.ComponentInitException;
-import org.dllearner.core.LearningAlgorithm;
+import org.dllearner.core.AbstractCELA;
import org.dllearner.core.LearningProblem;
import org.dllearner.core.ReasonerComponent;
import org.dllearner.core.configurators.OCELConfigurator;
@@ -81,7 +81,7 @@
* @author Jens Lehmann
*
*/
-public class OCEL extends LearningAlgorithm {
+public class OCEL extends AbstractCELA {
private OCELConfigurator configurator;
@Override
Modified: trunk/components-core/src/main/java/org/dllearner/algorithms/refinement/ROLearner.java
===================================================================
--- trunk/components-core/src/main/java/org/dllearner/algorithms/refinement/ROLearner.java 2011-03-16 21:14:14 UTC (rev 2724)
+++ trunk/components-core/src/main/java/org/dllearner/algorithms/refinement/ROLearner.java 2011-03-17 11:24:56 UTC (rev 2725)
@@ -14,7 +14,7 @@
import org.apache.log4j.Level;
import org.apache.log4j.Logger;
-import org.dllearner.core.LearningAlgorithm;
+import org.dllearner.core.AbstractCELA;
import org.dllearner.core.LearningProblem;
import org.dllearner.core.ReasonerComponent;
import org.dllearner.core.configurators.ROLearnerConfigurator;
@@ -42,7 +42,7 @@
import org.dllearner.utilities.owl.ConceptTransformation;
import org.dllearner.utilities.owl.EvaluatedDescriptionPosNegComparator;
-public class ROLearner extends LearningAlgorithm {
+public class ROLearner extends AbstractCELA {
private ROLearnerConfigurator configurator;
@Override
@@ -51,7 +51,7 @@
}
private static Logger logger = Logger
- .getLogger(LearningAlgorithm.class);
+ .getLogger(AbstractCELA.class);
private String logLevel = CommonConfigOptions.logLevelDefault;
Copied: trunk/components-core/src/main/java/org/dllearner/core/AbstractCELA.java (from rev 2724, trunk/components-core/src/main/java/org/dllearner/core/LearningAlgorithm.java)
===================================================================
--- trunk/components-core/src/main/java/org/dllearner/core/AbstractCELA.java (rev 0)
+++ trunk/components-core/src/main/java/org/dllearner/core/AbstractCELA.java 2011-03-17 11:24:56 UTC (rev 2725)
@@ -0,0 +1,305 @@
+/**
+ * Copyright (C) 2007-2011, Jens Lehmann
+ *
+ * This file is part of DL-Learner.
+ *
+ * DL-Learner 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 3 of the License, or
+ * (at your option) any later version.
+ *
+ * DL-Learner 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, see <http://www.gnu.org/licenses/>.
+ *
+ */
+package org.dllearner.core;
+
+import java.util.Collection;
+import java.util.LinkedList;
+import java.util.List;
+import java.util.TreeSet;
+
+import org.dllearner.core.owl.Description;
+import org.dllearner.utilities.datastructures.DescriptionSubsumptionTree;
+import org.dllearner.utilities.owl.ConceptTransformation;
+
+/**
+ * Abstract superclass of all class expression learning algorithm implementations.
+ * Includes support for anytime learning algorithms and resumable
+ * learning algorithms. Provides methods for filtering the best
+ * descriptions found by the algorithm. As results of the algorithm,
+ * you can either get only descriptions or evaluated descriptions.
+ * Evaluated descriptions have information about accuracy and
+ * example coverage associated with them. However, retrieving those
+ * may require addition reasoner queries, because the learning
+ * algorithms usually use but do not necessarily store this information.
+ *
+ * @author Jens Lehmann
+ *
+ */
+public abstract class AbstractCELA extends Component {
+
+ /**
+ * The learning problem variable, which must be used by
+ * all learning algorithm implementations.
+ */
+ protected LearningProblem learningProblem;
+
+ /**
+ * The reasoning service variable, which must be used by
+ * all learning algorithm implementations.
+ */
+ protected ReasonerComponent reasoner;
+
+ /**
+ * Each learning algorithm gets a learning problem and
+ * a reasoner as input.
+ * @param learningProblem The learning problem to solve.
+ * @param reasoningService The reasoner connecting to the
+ * underlying knowledge base.
+ */
+ public AbstractCELA(LearningProblem learningProblem, ReasonerComponent reasoningService) {
+ this.learningProblem = learningProblem;
+ this.reasoner = reasoningService;
+ }
+
+ /**
+ * Call this when you want to change the learning problem, but
+ * leave everything else as is. Method can be used to apply
+ * a configured algorithm to different learning problems.
+ * Implementations, which do not only use the provided learning
+ * algorithm variable, must make sure that a call to this method
+ * indeed changes the learning problem.
+ * @param learningProblem The new learning problem.
+ */
+ public void changeLearningProblem(LearningProblem learningProblem) {
+ this.learningProblem = learningProblem;
+ }
+
+ /**
+ * Call this when you want to change the reasoning service, but
+ * leave everything else as is. Method can be used to use
+ * a configured algorithm with different reasoners.
+ * Implementations, which do not only use the provided reasoning
+ * service class variable, must make sure that a call to this method
+ * indeed changes the reasoning service.
+ * @param reasoningService The new reasoning service.
+ */
+ public void changeReasonerComponent(ReasonerComponent reasoningService) {
+ this.reasoner = reasoningService;
+ }
+
+ /**
+ * This is the maximum number of results, which the learning
+ * algorithms are asked to store. (Note, that algorithms are not
+ * required to store any results except the best one, so this limit
+ * is used to limit the performance cost for those which
+ * choose to store results.)
+ */
+ public static final int MAX_NR_OF_RESULTS = 100;
+
+ /**
+ * Starts the algorithm. It runs until paused, stopped, or
+ * a termination criterion has been reached.
+ */
+ public abstract void start();
+
+ /**
+ * Pauses the algorithm (not all algorithms need to implement
+ * this operation).
+ */
+ public void pause() { };
+
+ /**
+ * Resumes the algorithm (not all algorithms need to implement
+ * this operation). You can use this method to continue
+ * an algorithm run even after a termination criterion has been
+ * reached. It will run until paused, stopped, or terminated
+ * again.
+ */
+ public void resume() { };
+
+ /**
+ * Stops the algorithm gracefully. A stopped algorithm cannot be resumed anymore.
+ * Use this method for cleanup and freeing memory.
+ */
+ public abstract void stop();
+
+ /**
+ * Returns whether the learning algorithm is running. Implementation
+ * should use a boolean status variable in their implementations of
+ * the start and resume methods.
+ * @return True if the algorithm is running, false otherwise.
+ */
+ public abstract boolean isRunning();
+
+ /**
+ * Every algorithm must be able to return the score of the
+ * best solution found.
+ *
+ * @return Best score.
+ */
+// @Deprecated
+// public abstract Score getSolutionScore();
+
+ /**
+ * @see #getCurrentlyBestEvaluatedDescription()
+ * @return The best class description found by the learning algorithm so far.
+ */
+ public abstract Description getCurrentlyBestDescription();
+
+ /**
+ * @see #getCurrentlyBestEvaluatedDescriptions()
+ * @return The best class descriptions found by the learning algorithm so far.
+ */
+ public List<Description> getCurrentlyBestDescriptions() {
+ List<Description> ds = new LinkedList<Description>();
+ ds.add(getCurrentlyBestDescription());
+ return ds;
+ }
+
+ /**
+ * @see #getCurrentlyBestEvaluatedDescriptions(int)
+ * @param nrOfDescriptions Limit for the number or returned descriptions.
+ * @return The best class descriptions found by the learning algorithm so far.
+ */
+ public synchronized List<Description> getCurrentlyBestDescriptions(int nrOfDescriptions) {
+ return getCurrentlyBestDescriptions(nrOfDescriptions, false);
+ }
+
+ /**
+ * @see #getCurrentlyBestEvaluatedDescriptions(int,double,boolean)
+ * @param nrOfDescriptions Limit for the number or returned descriptions.
+ * @param filterNonMinimalDescriptions Remove non-minimal descriptions (e.g. those which can be shortened
+ * to an equivalent concept) from the returned set.
+ * @return The best class descriptions found by the learning algorithm so far.
+ */
+ public synchronized List<Description> getCurrentlyBestDescriptions(int nrOfDescriptions, boolean filterNonMinimalDescriptions) {
+ List<Description> currentlyBest = getCurrentlyBestDescriptions();
+ List<Description> returnList = new LinkedList<Description>();
+ for(Description ed : currentlyBest) {
+ if(returnList.size() >= nrOfDescriptions) {
+ return returnList;
+ }
+
+ if(!filterNonMinimalDescriptions || ConceptTransformation.isDescriptionMinimal(ed)) {
+ returnList.add(ed);
+ }
+
+ }
+ return returnList;
+ }
+
+ /**
+ * Returns the best descriptions obtained so far.
+ * @return Best class description found so far.
+ */
+ public abstract EvaluatedDescription getCurrentlyBestEvaluatedDescription();
+
+ /**
+ * Returns a sorted set of the best descriptions found so far. We
+ * assume that they are ordered such that the best ones come in
+ * last. (In Java, iterators traverse a SortedSet in ascending order.)
+ * @return Best class descriptions found so far.
+ */
+ public TreeSet<? extends EvaluatedDescription> getCurrentlyBestEvaluatedDescriptions() {
+ TreeSet<EvaluatedDescription> ds = new TreeSet<EvaluatedDescription>();
+ ds.add(getCurrentlyBestEvaluatedDescription());
+ return ds;
+ }
+
+ /**
+ * Returns a filtered list of currently best class descriptions.
+ *
+ * @param nrOfDescriptions Maximum number of restrictions. Use Integer.MAX_VALUE
+ * if you do not want this filter to be active.
+ *
+ * @param accuracyThreshold Minimum accuracy. All class descriptions with lower
+ * accuracy are disregarded. Specify a value between 0.0 and 1.0. Use 0.0 if
+ * you do not want this filter to be active.
+ *
+ * @param filterNonMinimalDescriptions If true, non-minimal descriptions are
+ * filtered, e.g. ALL r.TOP (being equivalent to TOP), male AND male (can be
+ * shortened to male). Currently, non-minimal descriptions are just skipped,
+ * i.e. they are completely omitted from the return list. Later, implementation
+ * might be changed to return shortened versions of those descriptions.
+ *
+ * @return A list of currently best class descriptions.
+ */
+ public synchronized List<? extends EvaluatedDescription> getCurrentlyBestEvaluatedDescriptions(int nrOfDescriptions, double accuracyThreshold, boolean filterNonMinimalDescriptions) {
+ TreeSet<? extends EvaluatedDescription> currentlyBest = getCurrentlyBestEvaluatedDescriptions();
+ List<EvaluatedDescription> returnList = new LinkedList<EvaluatedDescription>();
+ for(EvaluatedDescription ed : currentlyBest.descendingSet()) {
+ // once we hit a description with a below threshold accuracy, we simply return
+ // because learning algorithms are advised to order descriptions by accuracy,
+ // so we won't find any concept with higher accuracy in the remaining list
+// if(ed.getAccuracy() < accuracyThreshold) {
+ if(ed.getAccuracy() < accuracyThreshold) {
+ return returnList;
+ }
+
+ // return if we have sufficiently many descriptions
+ if(returnList.size() >= nrOfDescriptions) {
+ return returnList;
+ }
+
+ if(!filterNonMinimalDescriptions || ConceptTransformation.isDescriptionMinimal(ed.getDescription())) {
+ // before we add the description we replace EXISTS r.TOP with
+ // EXISTS r.range(r) if range(r) is atomic
+ // (we need to clone, otherwise we change descriptions which could
+ // be in the search of the learning algorith, which leads to
+ // unpredictable behaviour)
+ Description d = ed.getDescription().clone();
+
+ //commented out because reasoner is called. leads in swing applications sometimes to exceptions
+// ConceptTransformation.replaceRange(d, reasoner);
+ ed.setDescription(d);
+
+ returnList.add(ed);
+ }
+
+ }
+ return returnList;
+ }
+
+ /**
+ * Return the best currently found concepts up to some maximum
+ * count (no minimality filter used).
+ * @param nrOfDescriptions Maximum number of descriptions returned.
+ * @return Return value is getCurrentlyBestDescriptions(nrOfDescriptions, 0.0, false).
+ */
+ public synchronized List<? extends EvaluatedDescription> getCurrentlyBestEvaluatedDescriptions(int nrOfDescriptions) {
+ return getCurrentlyBestEvaluatedDescriptions(nrOfDescriptions, 0.0, false);
+ }
+
+ /**
+ * Returns a fraction of class descriptions with sufficiently high accuracy.
+ * @param accuracyThreshold Only return solutions with this accuracy or higher.
+ * @return Return value is getCurrentlyBestDescriptions(Integer.MAX_VALUE, accuracyThreshold, false).
+ */
+ public synchronized List<? extends EvaluatedDescription> getCurrentlyBestEvaluatedDescriptions(double accuracyThreshold) {
+ return getCurrentlyBestEvaluatedDescriptions(Integer.MAX_VALUE, accuracyThreshold, false);
+ }
+
+ public synchronized List<? extends EvaluatedDescription> getCurrentlyBestMostGeneralEvaluatedDescriptions() {
+ List<? extends EvaluatedDescription> l = getCurrentlyBestEvaluatedDescriptions(getCurrentlyBestEvaluatedDescriptions().last().getAccuracy());
+ DescriptionSubsumptionTree t = new DescriptionSubsumptionTree(reasoner);
+ t.insert(l);
+ return t.getMostGeneralDescriptions(true);
+ }
+
+ /**
+ * Returns all learning problems supported by this component. This can be used to indicate that, e.g.
+ * an algorithm is only suitable for positive only learning.
+ * @return All classes implementing learning problems, which are supported by this learning algorithm.
+ */
+ public static Collection<Class<? extends LearningProblem>> supportedLearningProblems() {
+ return new LinkedList<Class<? extends LearningProblem>>();
+ }
+
+}
Added: trunk/components-core/src/main/java/org/dllearner/core/ClassExpressionLearningAlgorithm.java
===================================================================
--- trunk/components-core/src/main/java/org/dllearner/core/ClassExpressionLearningAlgorithm.java (rev 0)
+++ trunk/components-core/src/main/java/org/dllearner/core/ClassExpressionLearningAlgorithm.java 2011-03-17 11:24:56 UTC (rev 2725)
@@ -0,0 +1,30 @@
+/**
+ * Copyright (C) 2007-2011, Jens Lehmann
+ *
+ * This file is part of DL-Learner.
+ *
+ * DL-Learner 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 3 of the License, or
+ * (at your option) any later version.
+ *
+ * DL-Learner 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, see <http://www.gnu.org/licenses/>.
+ *
+ */
+package org.dllearner.core;
+
+/**
+ * Basic interface for algorithms learning OWL/DL class expressions.
+ *
+ * @author Jens Lehmann
+ *
+ */
+public interface ClassExpressionLearningAlgorithm extends LearningAlgorithm {
+
+}
Modified: trunk/components-core/src/main/java/org/dllearner/core/ComponentManager.java
===================================================================
--- trunk/components-core/src/main/java/org/dllearner/core/ComponentManager.java 2011-03-16 21:14:14 UTC (rev 2724)
+++ trunk/components-core/src/main/java/org/dllearner/core/ComponentManager.java 2011-03-17 11:24:56 UTC (rev 2725)
@@ -72,7 +72,7 @@
private static Collection<Class<? extends KnowledgeSource>> knowledgeSources;
private static Collection<Class<? extends ReasonerComponent>> reasonerComponents;
private static Collection<Class<? extends LearningProblem>> learningProblems;
- private static Collection<Class<? extends LearningAlgorithm>> learningAlgorithms;
+ private static Collection<Class<? extends AbstractCELA>> learningAlgorithms;
// you can either use the components.ini file or directly specify the classes to use
@Deprecated
private static String componentsFile = "org/dllearner/components.ini";
@@ -111,8 +111,8 @@
private static Map<Class<? extends Component>, String> componentNames;
private static Map<Class<? extends Component>, List<ConfigOption<?>>> componentOptions;
private static Map<Class<? extends Component>, Map<String, ConfigOption<?>>> componentOptionsByName;
- private static Map<Class<? extends LearningAlgorithm>, Collection<Class<? extends LearningProblem>>> algorithmProblemsMapping;
- private static Map<Class<? extends LearningProblem>, Collection<Class<? extends LearningAlgorithm>>> problemAlgorithmsMapping;
+ private static Map<Class<? extends AbstractCELA>, Collection<Class<? extends LearningProblem>>> algorithmProblemsMapping;
+ private static Map<Class<? extends LearningProblem>, Collection<Class<? extends AbstractCELA>>> problemAlgorithmsMapping;
// list of default values of config options
// private static Map<ConfigOption<?>,Object> configOptionDefaults;
@@ -143,8 +143,8 @@
knowledgeSources = new TreeSet<Class<? extends KnowledgeSource>>(classComparator);
reasonerComponents = new TreeSet<Class<? extends ReasonerComponent>>(classComparator);
learningProblems = new TreeSet<Class<? extends LearningProblem>>(classComparator);
- learningAlgorithms = new TreeSet<Class<? extends LearningAlgorithm>>(classComparator);
- algorithmProblemsMapping = new TreeMap<Class<? extends LearningAlgorithm>, Collection<Class<? extends LearningProblem>>>(
+ learningAlgorithms = new TreeSet<Class<? extends AbstractCELA>>(classComparator);
+ algorithmProblemsMapping = new TreeMap<Class<? extends AbstractCELA>, Collection<Class<? extends LearningProblem>>>(
classComparator);
// create classes from strings
@@ -160,8 +160,8 @@
reasonerComponents.add((Class<? extends ReasonerComponent>) component);
} else if (LearningProblem.class.isAssignableFrom(component)) {
learningProblems.add((Class<? extends LearningProblem>) component);
- } else if (LearningAlgorithm.class.isAssignableFrom(component)) {
- Class<? extends LearningAlgorithm> learningAlgorithmClass = (Class<? extends LearningAlgorithm>) component;
+ } else if (AbstractCELA.class.isAssignableFrom(component)) {
+ Class<? extends AbstractCELA> learningAlgorithmClass = (Class<? extends AbstractCELA>) component;
learningAlgorithms.add(learningAlgorithmClass);
Collection<Class<? extends LearningProblem>> problems = (Collection<Class<? extends LearningProblem>>) invokeStaticMethod(
learningAlgorithmClass, "supportedLearningProblems");
@@ -447,7 +447,7 @@
* @throws LearningProblemUnsupportedException Thrown when the learning problem and
* the learning algorithm are not compatible.
*/
- public <T extends LearningAlgorithm> T learningAlgorithm(Class<T> laClass, LearningProblem lp, ReasonerComponent rs) throws LearningProblemUnsupportedException {
+ public <T extends AbstractCELA> T learningAlgorithm(Class<T> laClass, LearningProblem lp, ReasonerComponent rs) throws LearningProblemUnsupportedException {
if (!learningAlgorithms.contains(laClass)) {
System.err.println("Warning: learning algorithm " + laClass
+ " is not a registered learning algorithm component.");
@@ -661,9 +661,9 @@
* @param learningProblem A learning problem type.
* @return The set of learning algorithms applicable for this learning problem.
*/
- public List<Class<? extends LearningAlgorithm>> getApplicableLearningAlgorithms(Class<? extends LearningProblem> learningProblem) {
- List<Class<? extends LearningAlgorithm>> algorithms = new LinkedList<Class<? extends LearningAlgorithm>>();
- for(Entry<Class<? extends LearningProblem>,Collection<Class<? extends LearningAlgorithm>>> entry : problemAlgorithmsMapping.entrySet()) {
+ public List<Class<? extends AbstractCELA>> getApplicableLearningAlgorithms(Class<? extends LearningProblem> learningProblem) {
+ List<Class<? extends AbstractCELA>> algorithms = new LinkedList<Class<? extends AbstractCELA>>();
+ for(Entry<Class<? extends LearningProblem>,Collection<Class<? extends AbstractCELA>>> entry : problemAlgorithmsMapping.entrySet()) {
Class<? extends LearningProblem> prob = entry.getKey();
if(prob.isAssignableFrom(learningProblem)) {
algorithms.addAll(entry.getValue());
@@ -679,8 +679,8 @@
* @return the components A list of learning algorithm classes available in this
* instance of <code>ComponentManager</code>.
*/
- public List<Class<? extends LearningAlgorithm>> getLearningAlgorithms() {
- return new LinkedList<Class<? extends LearningAlgorithm>>(learningAlgorithms);
+ public List<Class<? extends AbstractCELA>> getLearningAlgorithms() {
+ return new LinkedList<Class<? extends AbstractCELA>>(learningAlgorithms);
}
@@ -696,11 +696,11 @@
* Retuns a list of all instanciated and registered LearningAlgorithm
* @return Currently active learning algorithms.
*/
- public List<LearningAlgorithm> getLiveLearningAlgorithms(){
- List<LearningAlgorithm> list = new ArrayList<LearningAlgorithm>();
+ public List<AbstractCELA> getLiveLearningAlgorithms(){
+ List<AbstractCELA> list = new ArrayList<AbstractCELA>();
for (Component component : cm.getLiveComponents()) {
- if(component instanceof LearningAlgorithm){
- list.add((LearningAlgorithm) component);
+ if(component instanceof AbstractCELA){
+ list.add((AbstractCELA) component);
}
}
Added: trunk/components-core/src/main/java/org/dllearner/core/FuzzyClassExpressionLearningAlgorithm.java
===================================================================
--- trunk/components-core/src/main/java/org/dllearner/core/FuzzyClassExpressionLearningAlgorithm.java (rev 0)
+++ trunk/components-core/src/main/java/org/dllearner/core/FuzzyClassExpressionLearningAlgorithm.java 2011-03-17 11:24:56 UTC (rev 2725)
@@ -0,0 +1,30 @@
+/**
+ * Copyright (C) 2007-2011, Jens Lehmann
+ *
+ * This file is part of DL-Learner.
+ *
+ * DL-Learner 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 3 of the License, or
+ * (at your option) any later version.
+ *
+ * DL-Learner 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, see <http://www.gnu.org/licenses/>.
+ *
+ */
+package org.dllearner.core;
+
+/**
+ * Basic interface for algorithms learning fuzzy OWL/DL class expressions.
+ *
+ * @author Jens Lehmann
+ *
+ */
+public interface FuzzyClassExpressionLearningAlgorithm extends LearningAlgorithm {
+
+}
Modified: trunk/components-core/src/main/java/org/dllearner/core/LearningAlgorithm.java
===================================================================
--- trunk/components-core/src/main/java/org/dllearner/core/LearningAlgorithm.java 2011-03-16 21:14:14 UTC (rev 2724)
+++ trunk/components-core/src/main/java/org/dllearner/core/LearningAlgorithm.java 2011-03-17 11:24:56 UTC (rev 2725)
@@ -1,5 +1,5 @@
/**
- * Copyright (C) 2007-2008, Jens Lehmann
+ * Copyright (C) 2007-2011, Jens Lehmann
*
* This file is part of DL-Learner.
*
@@ -19,287 +19,12 @@
*/
package org.dllearner.core;
-import java.util.Collection;
-import java.util.LinkedList;
-import java.util.List;
-import java.util.TreeSet;
-
-import org.dllearner.core.owl.Description;
-import org.dllearner.utilities.datastructures.DescriptionSubsumptionTree;
-import org.dllearner.utilities.owl.ConceptTransformation;
-
/**
- * Abstract superclass of all learning algorithm implementations.
- * Includes support for anytime learning algorithms and resumable
- * learning algorithms. Provides methods for filtering the best
- * descriptions found by the algorithm. As results of the algorithm,
- * you can either get only descriptions or evaluated descriptions.
- * Evaluated descriptions have information about accuracy and
- * example coverage associated with them. However, retrieving those
- * may require addition reasoner queries, because the learning
- * algorithms usually use but do not necessarily store this information.
+ * Basic interface for all DL-Learner learning algorithms.
*
* @author Jens Lehmann
*
*/
-public abstract class LearningAlgorithm extends Component {
+public interface LearningAlgorithm {
- /**
- * The learning problem variable, which must be used by
- * all learning algorithm implementations.
- */
- protected LearningProblem learningProblem;
-
- /**
- * The reasoning service variable, which must be used by
- * all learning algorithm implementations.
- */
- protected ReasonerComponent reasoner;
-
- /**
- * Each learning algorithm gets a learning problem and
- * a reasoner as input.
- * @param learningProblem The learning problem to solve.
- * @param reasoningService The reasoner connecting to the
- * underlying knowledge base.
- */
- public LearningAlgorithm(LearningProblem learningProblem, ReasonerComponent reasoningService) {
- this.learningProblem = learningProblem;
- this.reasoner = reasoningService;
- }
-
- /**
- * Call this when you want to change the learning problem, but
- * leave everything else as is. Method can be used to apply
- * a configured algorithm to different learning problems.
- * Implementations, which do not only use the provided learning
- * algorithm variable, must make sure that a call to this method
- * indeed changes the learning problem.
- * @param learningProblem The new learning problem.
- */
- public void changeLearningProblem(LearningProblem learningProblem) {
- this.learningProblem = learningProblem;
- }
-
- /**
- * Call this when you want to change the reasoning service, but
- * leave everything else as is. Method can be used to use
- * a configured algorithm with different reasoners.
- * Implementations, which do not only use the provided reasoning
- * service class variable, must make sure that a call to this method
- * indeed changes the reasoning service.
- * @param reasoningService The new reasoning service.
- */
- public void changeReasonerComponent(ReasonerComponent reasoningService) {
- this.reasoner = reasoningService;
- }
-
- /**
- * This is the maximum number of results, which the learning
- * algorithms are asked to store. (Note, that algorithms are not
- * required to store any results except the best one, so this limit
- * is used to limit the performance cost for those which
- * choose to store results.)
- */
- public static final int MAX_NR_OF_RESULTS = 100;
-
- /**
- * Starts the algorithm. It runs until paused, stopped, or
- * a termination criterion has been reached.
- */
- public abstract void start();
-
- /**
- * Pauses the algorithm (not all algorithms need to implement
- * this operation).
- */
- public void pause() { };
-
- /**
- * Resumes the algorithm (not all algorithms need to implement
- * this operation). You can use this method to continue
- * an algorithm run even after a termination criterion has been
- * reached. It will run until paused, stopped, or terminated
- * again.
- */
- public void resume() { };
-
- /**
- * Stops the algorithm gracefully. A stopped algorithm cannot be resumed anymore.
- * Use this method for cleanup and freeing memory.
- */
- public abstract void stop();
-
- /**
- * Returns whether the learning algorithm is running. Implementation
- * should use a boolean status variable in their implementations of
- * the start and resume methods.
- * @return True if the algorithm is running, false otherwise.
- */
- public abstract boolean isRunning();
-
- /**
- * Every algorithm must be able to return the score of the
- * best solution found.
- *
- * @return Best score.
- */
-// @Deprecated
-// public abstract Score getSolutionScore();
-
- /**
- * @see #getCurrentlyBestEvaluatedDescription()
- * @return The best class description found by the learning algorithm so far.
- */
- public abstract Description getCurrentlyBestDescription();
-
- /**
- * @see #getCurrentlyBestEvaluatedDescriptions()
- * @return The best class descriptions found by the learning algorithm so far.
- */
- public List<Description> getCurrentlyBestDescriptions() {
- List<Description> ds = new LinkedList<Description>();
- ds.add(getCurrentlyBestDescription());
- return ds;
- }
-
- /**
- * @see #getCurrentlyBestEvaluatedDescriptions(int)
- * @param nrOfDescriptions Limit for the number or returned descriptions.
- * @return The best class descriptions found by the learning algorithm so far.
- */
- public synchronized List<Description> getCurrentlyBestDescriptions(int nrOfDescriptions) {
- return getCurrentlyBestDescriptions(nrOfDescriptions, false);
- }
-
- /**
- * @see #getCurrentlyBestEvaluatedDescriptions(int,double,boolean)
- * @param nrOfDescriptions Limit for the number or returned descriptions.
- * @param filterNonMinimalDescriptions Remove non-minimal descriptions (e.g. those which can be shortened
- * to an equivalent concept) from the returned set.
- * @return The best class descriptions found by the learning algorithm so far.
- */
- public synchronized List<Description> getCurrentlyBestDescriptions(int nrOfDescriptions, boolean filterNonMinimalDescriptions) {
- List<Description> currentlyBest = getCurrentlyBestDescriptions();
- List<Description> returnList = new LinkedList<Description>();
- for(Description ed : currentlyBest) {
- if(returnList.size() >= nrOfDescriptions) {
- return returnList;
- }
-
- if(!filterNonMinimalDescriptions || ConceptTransformation.isDescriptionMinimal(ed)) {
- returnList.add(ed);
- }
-
- }
- return returnList;
- }
-
- /**
- * Returns the best descriptions obtained so far.
- * @return Best class description found so far.
- */
- public abstract EvaluatedDescription getCurrentlyBestEvaluatedDescription();
-
- /**
- * Returns a sorted set of the best descriptions found so far. We
- * assume that they are ordered such that the best ones come in
- * last. (In Java, iterators traverse a SortedSet in ascending order.)
- * @return Best class descriptions found so far.
- */
- public TreeSet<? extends EvaluatedDescription> getCurrentlyBestEvaluatedDescriptions() {
- TreeSet<EvaluatedDescription> ds = new TreeSet<EvaluatedDescription>();
- ds.add(getCurrentlyBestEvaluatedDescription());
- return ds;
- }
-
- /**
- * Returns a filtered list of currently best class descriptions.
- *
- * @param nrOfDescriptions Maximum number of restrictions. Use Integer.MAX_VALUE
- * if you do not want this filter to be active.
- *
- * @param accuracyThreshold Minimum accuracy. All class descriptions with lower
- * accuracy are disregarded. Specify a value between 0.0 and 1.0. Use 0.0 if
- * you do not want this filter to be active.
- *
- * @param filterNonMinimalDescriptions If true, non-minimal descriptions are
- * filtered, e.g. ALL r.TOP (being equivalent to TOP), male AND male (can be
- * shortened to male). Currently, non-minimal descriptions are just skipped,
- * i.e. they are completely omitted from the return list. Later, implementation
- * might be changed to return shortened versions of those descriptions.
- *
- * @return A list of currently best class descriptions.
- */
- public synchronized List<? extends EvaluatedDescription> getCurrentlyBestEvaluatedDescriptions(int nrOfDescriptions, double accuracyThreshold, boolean filterNonMinimalDescriptions) {
- TreeSet<? extends EvaluatedDescription> currentlyBest = getCurrentlyBestEvaluatedDescriptions();
- List<EvaluatedDescription> returnList = new LinkedList<EvaluatedDescription>();
- for(EvaluatedDescription ed : currentlyBest.descendingSet()) {
- // once we hit a description with a below threshold accuracy, we simply return
- // because learning algorithms are advised to order descriptions by accuracy,
- // so we won't find any concept with higher accuracy in the remaining list
-// if(ed.getAccuracy() < accuracyThreshold) {
- if(ed.getAccuracy() < accuracyThreshold) {
- return returnList;
- }
-
- // return if we have sufficiently many descriptions
- if(returnList.size() >= nrOfDescriptions) {
- return returnList;
- }
-
- if(!filterNonMinimalDescriptions || ConceptTransformation.isDescriptionMinimal(ed.getDescription())) {
- // before we add the description we replace EXISTS r.TOP with
- // EXISTS r.range(r) if range(r) is atomic
- // (we need to clone, otherwise we change descriptions which could
- // be in the search of the learning algorith, which leads to
- // unpredictable behaviour)
- Description d = ed.getDescription().clone();
-
- //commented out because reasoner is called. leads in swing applications sometimes to exceptions
-// ConceptTransformation.replaceRange(d, reasoner);
- ed.setDescription(d);
-
- returnList.add(ed);
- }
-
- }
- return returnList;
- }
-
- /**
- * Return the best currently found concepts up to some maximum
- * count (no minimality filter used).
- * @param nrOfDescriptions Maximum number of descriptions returned.
- * @return Return value is getCurrentlyBestDescriptions(nrOfDescriptions, 0.0, false).
- */
- public synchronized List<? extends EvaluatedDescription> getCurrentlyBestEvaluatedDescriptions(int nrOfDescriptions) {
- return getCurrentlyBestEvaluatedDescriptions(nrOfDescriptions, 0.0, false);
- }
-
- /**
- * Returns a fraction of class descriptions with sufficiently high accuracy.
- * @param accuracyThreshold Only return solutions with this accuracy or higher.
- * @return Return value is getCurrentlyBestDescriptions(Integer.MAX_VALUE, accuracyThreshold, false).
- */
- public synchronized List<? extends EvaluatedDescription> getCurrentlyBestEvaluatedDescriptions(double accuracyThreshold) {
- return getCurrentlyBestEvaluatedDescriptions(Integer.MAX_VALUE, accuracyThreshold, false);
- }
-
- public synchronized List<? extends EvaluatedDescription> getCurrentlyBestMostGeneralEvaluatedDescriptions() {
- List<? extends EvaluatedDescription> l = getCurrentlyBestEvaluatedDescriptions(getCurrentlyBestEvaluatedDescriptions().last().getAccuracy());
- DescriptionSubsumptionTree t = new DescriptionSubsumptionTree(reasoner);
- t.insert(l);
- return t.getMostGeneralDescriptions(true);
- }
-
- /**
- * Returns all learning problems supported by this component. This can be used to indicate that, e.g.
- * an algorithm is only suitable for positive only learning.
- * @return All classes implementing learning problems, which are supported by this learning algorithm.
- */
- public static Collection<Class<? extends LearningProblem>> supportedLearningProblems() {
- return new LinkedList<Class<? extends LearningProblem>>();
- }
-
}
Modified: trunk/components-core/src/main/java/org/dllearner/core/LearningProblemUnsupportedException.java
===================================================================
--- trunk/components-core/src/main/java/org/dllearner/core/LearningProblemUnsupportedException.java 2011-03-16 21:14:14 UTC (rev 2724)
+++ trunk/components-core/src/main/java/org/dllearner/core/LearningProblemUnsupportedException.java 2011-03-17 11:24:56 UTC (rev 2725)
@@ -33,12 +33,12 @@
private static final long serialVersionUID = 177919265073997460L;
- public LearningProblemUnsupportedException(Class<? extends LearningProblem> problemClass, Class<? extends LearningAlgorithm> algorithmClass) {
+ public LearningProblemUnsupportedException(Class<? extends LearningProblem> problemClass, Class<? extends AbstractCELA> algorithmClass) {
super("Warning: No suitable constructor registered for algorithm "
+ algorithmClass.getName() + " and problem " + problemClass.getClass().getName() + ".");
}
- public LearningProblemUnsupportedException(Class<? extends LearningProblem> problemClass, Class<? extends LearningAlgorithm> algorithmClass, Collection<Class<? extends LearningProblem>> supportedProblems) {
+ public LearningProblemUnsupportedException(Class<? extends LearningProblem> problemClass, Class<? extends AbstractCELA> algorithmClass, Collection<Class<? extends LearningProblem>> supportedProblems) {
super("Warning: No suitable constructor registered for algorithm "
+ algorithmClass.getName() + " and problem " + problemClass.getClass().getName()
+ ". Registered constructors for " + algorithmClass.getName() + ": "
Added: trunk/components-core/src/main/java/org/dllearner/core/SparqlQueryLearningAlgorithm.java
===================================================================
--- trunk/components-core/src/main/java/org/dllearner/core/SparqlQueryLearningAlgorithm.java (rev 0)
+++ trunk/components-core/src/main/java/org/dllearner/core/SparqlQueryLearningAlgorithm.java 2011-03-17 11:24:56 UTC (rev 2725)
@@ -0,0 +1,30 @@
+/**
+ * Copyright (C) 2007-2011, Jens Lehmann
+ *
+ * This file is part of DL-Learner.
+ *
+ * DL-Learner 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 3 of the License, or
+ * (at your option) any later version.
+ *
+ * DL-Learner 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, see <http://www.gnu.org/licenses/>.
+ *
+ */
+package org.dllearner.core;
+
+/**
+ * Basic interface for algorithms learning SPARQL queries.
+ *
+ * @author Jens Lehmann
+ *
+ */
+public interface SparqlQueryLearningAlgorithm extends LearningAlgorithm {
+
+}
Modified: trunk/components-core/src/main/java/org/dllearner/core/options/CommonConfigOptions.java
===================================================================
--- trunk/components-core/src/main/java/org/dllearner/core/options/CommonConfigOptions.java 2011-03-16 21:14:14 UTC (rev 2724)
+++ trunk/components-core/src/main/java/org/dllearner/core/options/CommonConfigOptions.java 2011-03-17 11:24:56 UTC (rev 2725)
@@ -19,7 +19,7 @@
*/
package org.dllearner.core.options;
-import org.dllearner.core.LearningAlgorithm;
+import org.dllearner.core.AbstractCELA;
@@ -193,7 +193,7 @@
public static IntegerConfigOption maxNrOfResults(int defaultValue) {
IntegerConfigOption opt = new IntegerConfigOption("maxNrOfResults", "Sets the maximum number of results one is interested in. (Setting this to a lower value may increase performance as the learning algorithm has to store/evaluate/beautify less descriptions).", defaultValue);
opt.setLowerLimit(1);
- opt.setUpperLimit(LearningAlgorithm.MAX_NR_OF_RESULTS);
+ opt.setUpperLimit(AbstractCELA.MAX_NR_OF_RESULTS);
return opt;
}
Modified: trunk/components-core/src/main/java/org/dllearner/utilities/components/ComponentCombo.java
===================================================================
--- trunk/components-core/src/main/java/org/dllearner/utilities/components/ComponentCombo.java 2011-03-16 21:14:14 UTC (rev 2724)
+++ trunk/components-core/src/main/java/org/dllearner/utilities/components/ComponentCombo.java 2011-03-17 11:24:56 UTC (rev 2725)
@@ -27,7 +27,7 @@
import org.dllearner.core.ComponentInitException;
import org.dllearner.core.ComponentManager;
import org.dllearner.core.KnowledgeSource;
-import org.dllearner.core.LearningAlgorithm;
+import org.dllearner.core.AbstractCELA;
import org.dllearner.core.LearningProblem;
import org.dllearner.core.LearningProblemUnsupportedException;
import org.dllearner.core.ReasonerComponent;
@@ -50,7 +50,7 @@
private Set<KnowledgeSource> sources;
private ReasonerComponent reasoner;
private LearningProblem problem;
- private LearningAlgorithm algorithm;
+ private AbstractCELA algorithm;
/**
* Builds a component combination object from the specified components.
@@ -59,7 +59,7 @@
* @param problem A learning problem.
* @param algorithm A learning algorithm.
*/
- public ComponentCombo(KnowledgeSource source, ReasonerComponent reasoner, LearningProblem problem, LearningAlgorithm algorithm) {
+ public ComponentCombo(KnowledgeSource source, ReasonerComponent reasoner, LearningProblem problem, AbstractCELA algorithm) {
this(getSourceSet(source), reasoner, problem, algorithm);
}
@@ -70,7 +70,7 @@
* @param problem A learning problem.
* @param algorithm A learning algorithm.
*/
- public ComponentCombo(Set<KnowledgeSource> sources, ReasonerComponent reasoner, LearningProblem problem, LearningAlgorithm algorithm) {
+ public ComponentCombo(Set<KnowledgeSource> sources, ReasonerComponent reasoner, LearningProblem problem, AbstractCELA algorithm) {
this.sources = sources;
this.reasoner = reasoner;
this.problem = problem;
@@ -144,7 +144,7 @@
/**
* @return the algorithm
*/
- public LearningAlgorithm getAlgorithm() {
+ public AbstractCELA getAlgorithm() {
return algorithm;
}
Modified: trunk/components-core/src/main/java/org/dllearner/utilities/learn/LearnConfiguration.java
===================================================================
--- trunk/components-core/src/main/java/org/dllearner/utilities/learn/LearnConfiguration.java 2011-03-16 21:14:14 UTC (rev 2724)
+++ trunk/components-core/src/main/java/org/dllearner/utilities/learn/LearnConfiguration.java 2011-03-17 11:24:56 UTC (rev 2725)
@@ -5,7 +5,7 @@
import org.dllearner.core.ComponentManager;
import org.dllearner.core.KnowledgeSource;
-import org.dllearner.core.LearningAlgorithm;
+import org.dllearner.core.AbstractCELA;
import org.dllearner.core.LearningProblem;
import org.dllearner.core.ReasonerComponent;
@@ -28,7 +28,7 @@
public boolean replaceSearchTree = true;
- public void applyConfigEntries(ComponentManager cm, KnowledgeSource ks, LearningProblem lp, ReasonerComponent rs, LearningAlgorithm la) {
+ public void applyConfigEntries(ComponentManager cm, KnowledgeSource ks, LearningProblem lp, ReasonerComponent rs, AbstractCELA la) {
try {
// LEARNINGALGORITHM
Modified: trunk/components-core/src/main/java/org/dllearner/utilities/learn/LearnOWLFileConfiguration.java
===================================================================
--- trunk/components-core/src/main/java/org/dllearner/utilities/learn/LearnOWLFileConfiguration.java 2011-03-16 21:14:14 UTC (rev 2724)
+++ trunk/components-core/src/main/java/org/dllearner/utilities/learn/LearnOWLFileConfiguration.java 2011-03-17 11:24:56 UTC (rev 2725)
@@ -4,7 +4,7 @@
import org.dllearner.core.ComponentManager;
import org.dllearner.core.KnowledgeSource;
-import org.dllearner.core.LearningAlgorithm;
+import org.dllearner.core.AbstractCELA;
import org.dllearner.core.LearningProblem;
import org.dllearner.core.ReasonerComponent;
@@ -22,7 +22,7 @@
}
@Override
- public void applyConfigEntries(ComponentManager cm, KnowledgeSource ks, LearningProblem lp, ReasonerComponent rs, LearningAlgorithm la) {
+ public void applyConfigEntries(ComponentManager cm, KnowledgeSource ks, LearningProblem lp, ReasonerComponent rs, AbstractCELA la) {
try {
super.applyConfigEntries(cm, ks, lp, rs, la);
// KNOWLEDGESOURCE
Modified: trunk/components-core/src/main/java/org/dllearner/utilities/learn/LearnSPARQLConfiguration.java
===================================================================
--- trunk/components-core/src/main/java/org/dllearner/utilities/learn/LearnSPARQLConfiguration.java 2011-03-16 21:14:14 UTC (rev 2724)
+++ trunk/components-core/src/main/java/org/dllearner/utilities/learn/LearnSPARQLConfiguration.java 2011-03-17 11:24:56 UTC (rev 2725)
@@ -2,7 +2,7 @@
import org.dllearner.core.ComponentManager;
import org.dllearner.core.KnowledgeSource;
-import org.dllearner.core.LearningAlgorithm;
+import org.dllearner.core.AbstractCELA;
import org.dllearner.core.LearningProblem;
import org.dllearner.core.ReasonerComponent;
import org.dllearner.kb.sparql.Cache;
@@ -24,7 +24,7 @@
@Override
- public void applyConfigEntries(ComponentManager cm, KnowledgeSource ks, LearningProblem lp, ReasonerComponent rs, LearningAlgorithm la) {
+ public void applyConfigEntries(ComponentManager cm, KnowledgeSource ks, LearningProblem lp, ReasonerComponent rs, AbstractCELA la) {
try {
super.applyConfigEntries(cm, ks, lp, rs, la);
// KNOWLEDGESOURCE
Modified: trunk/components-core/src/test/java/org/dllearner/test/ClassCastExceptionTest.java
===================================================================
--- trunk/components-core/src/test/java/org/dllearner/test/ClassCastExceptionTest.java 2011-03-16 21:14:14 UTC (rev 2724)
+++ trunk/components-core/src/test/java/org/dllearner/test/ClassCastExceptionTest.java 2011-03-17 11:24:56 UTC (rev 2725)
@@ -8,7 +8,7 @@
import org.dllearner.core.ComponentManager;
import org.dllearner.core.EvaluatedDescription;
import org.dllearner.core.KnowledgeSource;
-import org.dllearner.core.LearningAlgorithm;
+import org.dllearner.core.AbstractCELA;
import org.dllearner.core.LearningProblem;
import org.dllearner.core.LearningProblemUnsupportedException;
import org.dllearner.core.ReasonerComponent;
@@ -47,7 +47,7 @@
lp.init();
// create the learning algorithm
- LearningAlgorithm la = null;
+ AbstractCELA la = null;
try {
la = cm.learningAlgorithm(CELOE.class, lp, reasoner);
cm.applyConfigEntry(la, "maxExecutionTimeInSeconds", 2);
Modified: trunk/components-core/src/test/java/org/dllearner/test/ComponentTest.java
===================================================================
--- trunk/components-core/src/test/java/org/dllearner/test/ComponentTest.java 2011-03-16 21:14:14 UTC (rev 2724)
+++ trunk/components-core/src/test/java/org/dllearner/test/ComponentTest.java 2011-03-17 11:24:56 UTC (rev 2725)
@@ -28,7 +28,7 @@
import org.dllearner.core.ComponentInitException;
import org.dllearner.core.ComponentManager;
import org.dllearner.core.KnowledgeSource;
-import org.dllearner.core.LearningAlgorithm;
+import org.dllearner.core.AbstractCELA;
import org.dllearner.core.LearningProblem;
import org.dllearner.core.LearningProblemUnsupportedException;
import org.dllearner.core.ReasonerComponent;
@@ -78,7 +78,7 @@
lp.init();
// create the learning algorithm
- LearningAlgorithm la = null;
+ AbstractCELA la = null;
try {
la = cm.learningAlgorithm(OCEL.class, lp, reasoner);
la.init();
Modified: trunk/components-core/src/test/java/org/dllearner/test/SworeTest.java
===================================================================
--- trunk/components-core/src/test/java/org/dllearner/test...
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