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[DL-Learner SVN] SF.net SVN: dl-learner:[2046] trunk/src/dl-learner/org/dllearner
|
From: <ku...@us...> - 2010-02-16 14:06:01
|
Revision: 2046
http://dl-learner.svn.sourceforge.net/dl-learner/?rev=2046&view=rev
Author: kurzum
Date: 2010-02-16 14:05:54 +0000 (Tue, 16 Feb 2010)
Log Message:
-----------
Modified Paths:
--------------
trunk/src/dl-learner/org/dllearner/scripts/tiger/TestIterativeLearning.java
trunk/src/dl-learner/org/dllearner/utilities/experiments/Table.java
Modified: trunk/src/dl-learner/org/dllearner/scripts/tiger/TestIterativeLearning.java
===================================================================
--- trunk/src/dl-learner/org/dllearner/scripts/tiger/TestIterativeLearning.java 2010-02-16 13:23:18 UTC (rev 2045)
+++ trunk/src/dl-learner/org/dllearner/scripts/tiger/TestIterativeLearning.java 2010-02-16 14:05:54 UTC (rev 2046)
@@ -58,10 +58,12 @@
static DecimalFormat df = new DecimalFormat("00.###%");
public static DecimalFormat dftime = new DecimalFormat("#####.#");
-// static String backgroundXML = "files/tiger.noSchema.noImports.rdf";
+ // static String backgroundXML = "files/tiger.noSchema.noImports.rdf";
static String backgroundXML = "files/tiger_trimmed_toPOS.rdf";
static String propertiesXML = "files/propertiesOnly.rdf";
static String sentenceXMLFolder = "files/tiger/";
+ static String resultFolder = "tigerResults/";
+
static String sentenceprefix = "http://nlp2rdf.org/ontology/s";
static String prefix = "http://nlp2rdf.org/ontology/";
@@ -77,24 +79,24 @@
static String sparqlEndpointURL = "http://db0.aksw.org:8893/sparql";
static String graph = "http://nlp2rdf.org/tiger";
static String rulegraph = "http://nlp2rdf.org/schema/rules1";
-
-
- static MonKeyImp logFMeasure = new MonKeyImp("F-Measure",Jamon.PERCENTAGE);
- static MonKeyImp logPrecision = new MonKeyImp("Precision",Jamon.PERCENTAGE);
- static MonKeyImp logRecall = new MonKeyImp("Recall",Jamon.PERCENTAGE);
- static MonKeyImp logAccuracy = new MonKeyImp("Accuracy",Jamon.PERCENTAGE);
-
- static MonKeyImp logLearningTime = new MonKeyImp("Learning Time",Jamon.MS);
- static MonKeyImp logIterationTime = new MonKeyImp("Iteration Time",Jamon.MS);
-
-
- static List<MonKeyImp> mks = new ArrayList<MonKeyImp>(Arrays.asList(new MonKeyImp[]{logPrecision, logRecall, logFMeasure, logLearningTime, logIterationTime}));
-
+
+ static MonKeyImp logFMeasure = new MonKeyImp("F-Measure", Jamon.PERCENTAGE);
+ static MonKeyImp logPrecision = new MonKeyImp("Precision", Jamon.PERCENTAGE);
+ static MonKeyImp logRecall = new MonKeyImp("Recall", Jamon.PERCENTAGE);
+ static MonKeyImp logAccuracy = new MonKeyImp("Accuracy", Jamon.PERCENTAGE);
+
+ static MonKeyImp logLearningTime = new MonKeyImp("Learning Time", Jamon.MS);
+ static MonKeyImp logIterationTime = new MonKeyImp("Iteration Time", Jamon.MS);
+
+ static List<MonKeyImp> mks = new ArrayList<MonKeyImp>(Arrays.asList(new MonKeyImp[] { logPrecision,
+ logRecall, logFMeasure, logLearningTime, logIterationTime }));
+
static int iterations = 4;
- static int folds = 6;
+ static int folds = 10;
static int printSentences = 3;
- //no randomization in examples
+ // no randomization in examples
+
public static void main(String[] args) {
LogHelper.initLoggers();
Logger.getLogger(Cache.class).setLevel(Level.INFO);
@@ -102,9 +104,9 @@
Logger.getLogger(ROLearner2.class).setLevel(Level.INFO);
Logger.getLogger(RhoDRDown.class).setLevel(Level.INFO);
Logger.getLogger(SparqlQuery.class).setLevel(Level.INFO);
-
- Files.mkdir("results");
-
+
+ Files.mkdir(resultFolder);
+
try {
sparqlEndpoint = new SparqlEndpoint(new URL(sparqlEndpointURL), new ArrayList<String>(Arrays
.asList(new String[] { graph })), new ArrayList<String>());
@@ -113,289 +115,291 @@
e.printStackTrace();
}
- folds = 2;
- iterations = 2;
+ // folds = 2;
+ // iterations = 2;
long n = System.currentTimeMillis();
passiveNoZU();
-// passiveWithZu();
+ // passiveWithZu();
- logger.warn("finished, needed: "+(System.currentTimeMillis()-n));
+ logger.info("finished, needed: " + (System.currentTimeMillis() - n));
JamonMonitorLogger.writeHTMLReport("log/tiger.html");
}
-
- public static void passiveNoZU(){
- ExperimentCollector eColl_passiveNoZU = new ExperimentCollector("passiveNoZU");
-
- SortedSet<String> positives = read(passiveNoZU);
- SortedSet<String> negatives = read(active);
-
- //removing overlap
- positives.removeAll(negatives);
- negatives.removeAll(positives);
-
- Examples allExamples = new Examples();
- allExamples.addPosTrain(positives);
- allExamples.addNegTrain(negatives);
-
- logger.debug("All examples \n"+allExamples);
-
- List<Examples> folds = new ExMakerCrossFolds(allExamples).splitLeaveOneOut(TestIterativeLearning.folds);
-// ExMakerCrossFolds.printFolds(folds);
- List<IteratedConfig> configs = getConfigs();
- for (IteratedConfig experimentConfig : configs) {
- experimentConfig.init(mks);
- logger.warn("next: passiveNoZU."+experimentConfig.experimentName);
- int i = 1;
- for (Examples examples : folds) {
- logger.warn("beginning fold: "+(i++));
-
- conductExperiment( examples, experimentConfig);
-
- }
- Table t = new Table();
- t.addTableRowColumn(experimentConfig.getTableRows());
- t.sortByLabel();
- JamonMonitorLogger.writeHTMLReport("/tmp/tiger.html");
- System.out.println(t.getGnuPlotAsColumn());
- if (true) {
- System.exit(0);
- }
-
-// eColl_passiveNoZU.addExperimentConfig(experimentConfig);
- logger.info(experimentConfig);
-// eColl_passiveNoZU.write(iterations);
+
+ public static void passiveNoZU() {
+
+ SortedSet<String> positives = read(passiveNoZU);
+ SortedSet<String> negatives = read(active);
+
+ // removing overlap
+ positives.removeAll(negatives);
+ negatives.removeAll(positives);
+
+ Examples allExamples = new Examples();
+ allExamples.addPosTrain(positives);
+ allExamples.addNegTrain(negatives);
+
+ logger.debug("All examples \n" + allExamples);
+
+ List<Examples> folds = new ExMakerCrossFolds(allExamples)
+ .splitLeaveOneOut(TestIterativeLearning.folds);
+ // ExMakerCrossFolds.printFolds(folds);
+ List<IteratedConfig> configs = getConfigs();
+ Table masterTable = new Table();
+ for (IteratedConfig experimentConfig : configs) {
+ experimentConfig.init(mks);
+ logger.info("next: passiveNoZU." + experimentConfig.experimentName);
+ int i = 1;
+ for (Examples examples : folds) {
+ logger.info("beginning fold: " + (i++));
+ conductExperiment(examples, experimentConfig);
}
-
-
+ Table expTable = new Table();
+ expTable.addTableRowColumn(experimentConfig.getTableRows());
+ expTable.write(resultFolder, experimentConfig.experimentName);
+ masterTable.addTable(expTable);
+ masterTable.sortByExperimentName();
+ masterTable.write(resultFolder, "master_by_expname");
+ masterTable.sortByLabel();
+ masterTable.write(resultFolder, "master_by_label");
+
+ JamonMonitorLogger.writeHTMLReport("/tmp/tiger.html");
+ logger.info(experimentConfig);
+
+ }
+
}
-
- public static void passiveWithZu(){
+
+ public static void passiveWithZu() {
ExperimentCollector eColl_passiveWithZu = new ExperimentCollector("passiveWithZu");
- SortedSet<String> positives = read(passiveWithZu);
- SortedSet<String> negatives = read(active);
-
- //removing overlap
- positives.removeAll(negatives);
- negatives.removeAll(positives);
-
- Examples allExamples = new Examples();
- allExamples.addPosTrain(positives);
- allExamples.addNegTrain(negatives);
-
- logger.debug("All examples \n"+allExamples);
-
- List<Examples> runs = new ArrayList<Examples>();
- runs.add(new ExMakerRandomizer(allExamples).split(0.7d));
- runs.add(new ExMakerRandomizer(allExamples).split(0.7d));
- runs.add(new ExMakerRandomizer(allExamples).split(0.7d));
- runs.add(new ExMakerRandomizer(allExamples).split(0.7d));
- runs.add(new ExMakerRandomizer(allExamples).split(0.7d));
+ SortedSet<String> positives = read(passiveWithZu);
+ SortedSet<String> negatives = read(active);
- List<IteratedConfig> configs = getConfigs();
- for (IteratedConfig experimentConfig : configs) {
- logger.warn("next: passiveWithZu."+experimentConfig.experimentName);
- int i=1;
- for (Examples examples : runs) {
- logger.warn("beginning run: "+(i++));
- conductExperiment( examples, experimentConfig);
-
- }
- eColl_passiveWithZu.addExperimentConfig(experimentConfig);
-
- logger.info(experimentConfig);
+ // removing overlap
+ positives.removeAll(negatives);
+ negatives.removeAll(positives);
+
+ Examples allExamples = new Examples();
+ allExamples.addPosTrain(positives);
+ allExamples.addNegTrain(negatives);
+
+ logger.debug("All examples \n" + allExamples);
+
+ List<Examples> runs = new ArrayList<Examples>();
+ runs.add(new ExMakerRandomizer(allExamples).split(0.7d));
+ runs.add(new ExMakerRandomizer(allExamples).split(0.7d));
+ runs.add(new ExMakerRandomizer(allExamples).split(0.7d));
+ runs.add(new ExMakerRandomizer(allExamples).split(0.7d));
+ runs.add(new ExMakerRandomizer(allExamples).split(0.7d));
+
+ List<IteratedConfig> configs = getConfigs();
+ for (IteratedConfig experimentConfig : configs) {
+ logger.info("next: passiveWithZu." + experimentConfig.experimentName);
+ int i = 1;
+ for (Examples examples : runs) {
+ logger.info("beginning run: " + (i++));
+ conductExperiment(examples, experimentConfig);
+
}
- eColl_passiveWithZu.write(iterations);
-
+ eColl_passiveWithZu.addExperimentConfig(experimentConfig);
+
+ logger.info(experimentConfig);
+ }
+ eColl_passiveWithZu.write(iterations);
+
}
-
- public static List<IteratedConfig> getConfigs(){
-
+
+ public static List<IteratedConfig> getConfigs() {
+
List<IteratedConfig> l = new ArrayList<IteratedConfig>();
IteratedConfig baseline = new IteratedConfig("baseline_5_5", iterations);
-
-
+
IteratedConfig reducedExamples = new IteratedConfig("reducedExamples_2_2", iterations);
reducedExamples.initialsplits = 2;
reducedExamples.splits = 2;
-
-
+ // reducedExamples.adaptMaxRuntime=false;
+ // reducedExamples.maxExecutionTime = 20;
+ reducedExamples.factor = 3.0d;
+
IteratedConfig fixRuntime = new IteratedConfig("fixRuntime_20s", iterations);
- fixRuntime.adaptMaxRuntime=false;
+ fixRuntime.adaptMaxRuntime = false;
fixRuntime.maxExecutionTime = 20;
-
-
+
IteratedConfig useLemma = new IteratedConfig("useLemma_false", iterations);
- useLemma.useDataHasValue=false;
-
-
+ useLemma.useDataHasValue = false;
+
l.add(baseline);
-// l.add(reducedExamples);
-// l.add(fixRuntime);
-// l.add(useLemma);
-
+ l.add(reducedExamples);
+ l.add(fixRuntime);
+ l.add(useLemma);
return l;
}
-
- public static void conductExperiment(Examples allExamples, IteratedConfig config){
+
+ public static void conductExperiment(Examples allExamples, IteratedConfig config) {
Examples tmp = new Examples();
tmp.addPosTrain(allExamples.getPosTrain());
tmp.addNegTrain(allExamples.getNegTrain());
-
+
ExMakerFixedSize fs = new ExMakerFixedSize(tmp);
Examples learn = fs.select(config.initialsplits, config.initialsplits);
- logger.debug("Total set \n"+allExamples);
- logger.debug("Initial training set \n"+learn);
-
+ logger.debug("Total set \n" + allExamples);
+ logger.debug("Initial training set \n" + learn);
+
SortedSet<String> posAsPos = new TreeSet<String>();
SortedSet<String> retrieved = new TreeSet<String>();
SortedSet<String> newTestRetrieved = new TreeSet<String>();
SortedSet<String> newTrainRetrieved = new TreeSet<String>();
-
- String lastConcept="";
+
+ String lastConcept = "";
double precision = 0.0;
double recall = 0.0;
double fmeasure = 0.0;
-
- for(int i = 0 ; config.stopCondition(i, precision, recall, fmeasure, lastConcept) ;i++ ) {
- Monitor iterationTime = JamonMonitorLogger.getTimeMonitor(TestIterativeLearning.class, "iterationTime").start();
+
+ for (int i = 0; config.stopCondition(i, precision, recall, fmeasure, lastConcept); i++) {
+ Monitor iterationTime = JamonMonitorLogger.getTimeMonitor(TestIterativeLearning.class,
+ "iterationTime").start();
Monitor literationTime = config.start(logIterationTime, i);
-// try {
-// Thread.sleep(2000);
-// } catch (InterruptedException e) {
-// // TODO Auto-generated catch block
-// e.printStackTrace();
-// }
-// literationTime.stop();
-// System.out.println(literationTime);
-// if (true) {
-// System.exit(0);
-// }
+ // try {
+ // Thread.sleep(2000);
+ // } catch (InterruptedException e) {
+ // // TODO Auto-generated catch block
+ // e.printStackTrace();
+ // }
+ // literationTime.stop();
+ // System.out.println(literationTime);
+ // if (true) {
+ // System.exit(0);
+ // }
- /*LEARNING*/
+ /* LEARNING */
Monitor lLearningTime = config.start(logLearningTime, i);
EvaluatedDescription ed = learn(learn, config, i);
lLearningTime.stop();
lastConcept = PrefixMap.toKBSyntaxString(ed.getDescription());
- logger.debug("USING CONCEPT: "+lastConcept);
-
- /*RETRIEVING*/
- Monitor queryTime = JamonMonitorLogger.getTimeMonitor(TestIterativeLearning.class, "queryTime").start();
+ logger.debug("USING CONCEPT: " + lastConcept);
+
+ /* RETRIEVING */
+ Monitor queryTime = JamonMonitorLogger.getTimeMonitor(TestIterativeLearning.class, "queryTime")
+ .start();
retrieved = getSentences(ed, config.resultLimit);
queryTime.stop();
- //remove all that are not to be tested
- newTestRetrieved = Helper.intersection(allExamples.getTestExamples(), retrieved );
- newTrainRetrieved = Helper.intersection(allExamples.getTrainExamples(), retrieved );
-
-// logger.debug("Retrieved "+retrieved.size()+" sentences");
-
-
- /*MASHING*/
- //Menge aller positiven geschn. mit den gefundenen
+ // remove all that are not to be tested
+ newTestRetrieved = Helper.intersection(allExamples.getTestExamples(), retrieved);
+ newTrainRetrieved = Helper.intersection(allExamples.getTrainExamples(), retrieved);
+
+ // logger.debug("Retrieved "+retrieved.size()+" sentences");
+
+ /* MASHING */
+ // Menge aller positiven geschn. mit den gefundenen
posAsPos = Helper.intersection(newTestRetrieved, allExamples.getPosTest());
- logger.debug("Number of retrieved positives: "+posAsPos.size());
- logger.debug("Number of total positives: "+allExamples.getPosTest().size());
-
- precision = precision( posAsPos.size(), retrieved.size());
- config.add(logPrecision, i, precision);
- recall = recall( posAsPos.size(),allExamples.getPosTest().size());
- config.add(logRecall, i, recall);
- fmeasure = fmeasure(precision, recall);
- config.add(logFMeasure, i, fmeasure);
-
- //Menge aller positiven geschn. mit den gefundenen
+ logger.debug("Number of retrieved positives: " + posAsPos.size());
+ logger.debug("Number of total positives: " + allExamples.getPosTest().size());
+
+ precision = precision(posAsPos.size(), retrieved.size());
+ config.add(logPrecision, i, precision);
+ recall = recall(posAsPos.size(), allExamples.getPosTest().size());
+ config.add(logRecall, i, recall);
+ fmeasure = fmeasure(precision, recall);
+ config.add(logFMeasure, i, fmeasure);
+
+ // Menge aller positiven geschn. mit den gefundenen
SortedSet<String> negAsPos = Helper.intersection(newTestRetrieved, allExamples.getNegTest());
- logger.debug("Number of retrieved negatives: "+negAsPos.size());
- logger.debug("Number of total negatives: "+allExamples.getNegTest().size());
- logger.debug("Total: "+posAsPos.size()+" + "+negAsPos.size() +" = "+newTestRetrieved.size());
-
-
+ logger.debug("Number of retrieved negatives: " + negAsPos.size());
+ logger.debug("Number of total negatives: " + allExamples.getNegTest().size());
+ logger.debug("Total: " + posAsPos.size() + " + " + negAsPos.size() + " = "
+ + newTestRetrieved.size());
+
Examples newlyFound = new Examples();
- SortedSet<String> discoveredPosInStore = Helper.intersection(newTrainRetrieved, allExamples.getPosTrain());
- SortedSet<String> misclassifiedNegInStore = Helper.intersection(newTrainRetrieved, allExamples.getNegTrain());
+ SortedSet<String> discoveredPosInStore = Helper.intersection(newTrainRetrieved, allExamples
+ .getPosTrain());
+ SortedSet<String> misclassifiedNegInStore = Helper.intersection(newTrainRetrieved, allExamples
+ .getNegTrain());
newlyFound.addPosTrain(discoveredPosInStore);
newlyFound.addNegTrain(misclassifiedNegInStore);
- SortedSet<String> posAsNegInformative = Helper.difference(allExamples.getPositiveExamples(), retrieved);
-
- logger.info("Discovered: "+discoveredPosInStore.size()+" positive sentences in store (printing "+printSentences+"):");
+ SortedSet<String> posAsNegInformative = Helper.difference(allExamples.getPositiveExamples(),
+ retrieved);
+
+ logger.debug("Discovered: " + discoveredPosInStore.size()
+ + " positive sentences in store (printing " + printSentences + "):");
_getLabels(discoveredPosInStore, printSentences);
- logger.info("Misclassified: "+misclassifiedNegInStore.size()+" negative sentences in store (printing "+printSentences+"):");
+ logger.debug("Misclassified: " + misclassifiedNegInStore.size()
+ + " negative sentences in store (printing " + printSentences + "):");
_getLabels(misclassifiedNegInStore, printSentences);
- logger.info("Not found positives: "+posAsNegInformative.size()+" positive sentences in store (printing "+printSentences+"):");
+ logger.debug("Not found positives: " + posAsNegInformative.size()
+ + " positive sentences in store (printing " + printSentences + "):");
_getLabels(posAsNegInformative, printSentences);
-
-
-
+
fs = new ExMakerFixedSize(newlyFound);
newlyFound = fs.select(config.splits, config.splits);
-
+
learn.addPosTrain(newlyFound.getPosTrain());
learn.addNegTrain(newlyFound.getNegTrain());
- logger.debug("Next training set \n"+learn);
+ logger.debug("Next training set \n" + learn);
iterationTime.stop();
literationTime.stop();
- logger.warn("finished iteration "+(i+1)+" needed on avg: "+dftime.format(iterationTime.getAvg()));
- logger.warn("learning: "+dftime.format(lLearningTime.getLastValue())+" Acc: "+ed.getAccuracy());
- logger.warn("learning: "+PrefixMap.toManchesterSyntaxString(ed));
- logger.warn("query: "+dftime.format(queryTime.getLastValue()));
- logger.warn("F-Measure on Store = "+df.format(fmeasure));
- logger.warn("******************");
-
+ logger.info("finished iteration " + (i + 1) + " needed on avg: "
+ + dftime.format(iterationTime.getAvg()));
+ logger.info("learning: " + dftime.format(lLearningTime.getLastValue()) + " Acc: "
+ + ed.getAccuracy());
+ logger.info("learning: " + PrefixMap.toManchesterSyntaxString(ed));
+ logger.info("query: " + dftime.format(queryTime.getLastValue()));
+ logger.info("F-Measure on Store = " + df.format(fmeasure));
+ logger.info("******************");
+
}
-
-
-
-
-
+
}
-
- public static double accuracy (int posAsPos, int negAsNeg, int posAsNeg, int negAsPos){
+
+ public static double accuracy(int posAsPos, int negAsNeg, int posAsNeg, int negAsPos) {
return 0.0d;
}
-
- public static double fmeasure(double precision, double recall){
- double fmeasure = (precision+recall == 0)?0.0d: (2*precision*recall)/(precision+recall);
- logger.info("F-Measure: "+df.format(fmeasure));
+
+ public static double fmeasure(double precision, double recall) {
+ double fmeasure = (precision + recall == 0) ? 0.0d : (2 * precision * recall) / (precision + recall);
+ logger.debug("F-Measure: " + df.format(fmeasure));
return fmeasure;
}
-
- public static double precision( int posAsPos, int retrieved){
- double precision = (retrieved==0)?0.0d:((double)posAsPos)/((double)retrieved);
- logger.info("Precision: "+df.format(precision));
+
+ public static double precision(int posAsPos, int retrieved) {
+ double precision = (retrieved == 0) ? 0.0d : ((double) posAsPos) / ((double) retrieved);
+ logger.debug("Precision: " + df.format(precision));
return precision;
}
- public static double recall( int posAsPos, int allPositives){
- double recall = ((double)posAsPos)/((double)allPositives);
- logger.info("Recall: "+df.format(recall));
+
+ public static double recall(int posAsPos, int allPositives) {
+ double recall = ((double) posAsPos) / ((double) allPositives);
+ logger.debug("Recall: " + df.format(recall));
return recall;
-
+
}
- private static Set<KnowledgeSource> _getOWL(Examples ex) throws Exception{
+ private static Set<KnowledgeSource> _getOWL(Examples ex) throws Exception {
Set<KnowledgeSource> tmp = new HashSet<KnowledgeSource>();
List<URL> urls = new ArrayList<URL>();
urls.add(new File(backgroundXML).toURI().toURL());
urls.addAll(ExampleDataCollector.convert(sentenceXMLFolder, ex.getPosTrain()));
urls.addAll(ExampleDataCollector.convert(sentenceXMLFolder, ex.getNegTrain()));
-
+
for (URL u : urls) {
OWLFile ks = ComponentFactory.getOWLFile(u);
tmp.add(ks);
}
return tmp;
}
+
@SuppressWarnings("unused")
- private static Set<KnowledgeSource> _getSPARQL(Examples ex) throws Exception{
+ private static Set<KnowledgeSource> _getSPARQL(Examples ex) throws Exception {
Set<KnowledgeSource> tmp = new HashSet<KnowledgeSource>();
Set<String> examples = new TreeSet<String>();
examples.addAll(ex.getPosTrain());
examples.addAll(ex.getNegTrain());
- SparqlKnowledgeSource ks = ComponentFactory.getSparqlKnowledgeSource(new URL(sparqlEndpointURL), examples);
+ SparqlKnowledgeSource ks = ComponentFactory.getSparqlKnowledgeSource(new URL(sparqlEndpointURL),
+ examples);
ks.getConfigurator().setUrl(new URL(sparqlEndpointURL));
- ks.getConfigurator().setDefaultGraphURIs(new HashSet<String>(Arrays.asList(new String[]{graph})));
+ ks.getConfigurator().setDefaultGraphURIs(new HashSet<String>(Arrays.asList(new String[] { graph })));
ks.getConfigurator().setInstances(examples);
ks.getConfigurator().setDissolveBlankNodes(false);
ks.getConfigurator().setRecursionDepth(2);
@@ -404,46 +408,45 @@
ks.getConfigurator().setGetAllSuperClasses(true);
ks.getConfigurator().setGetPropertyInformation(false);
ks.getConfigurator().setUseLits(true);
-// ks.getConfigurator().
+ // ks.getConfigurator().
OWLFile ks2 = ComponentFactory.getOWLFile(new File(propertiesXML).toURI().toURL());
tmp.add(ks);
tmp.add(ks2);
-
+
return tmp;
}
-
- //test if virtuoso is correct
-// public static void validate(Description d, Examples newlyFound){
-// try {
-// ExMakerFixedSize fs = new ExMakerFixedSize(newlyFound);
-// Examples tmp = fs.select(100, 100);
-// FastInstanceChecker fc = _getFastInstanceChecker(tmp);
-// @SuppressWarnings("unused")
-// SortedSet<Individual> inds = fc.getIndividuals(d);
-// } catch (Exception e) {
-// e.printStackTrace();
-// }
-// }
-
- public static FastInstanceChecker _getFastInstanceChecker(Examples ex)throws Exception{
- Set<KnowledgeSource> tmp = _getOWL(ex);
-// Set<KnowledgeSource> tmp = _getSPARQL(ex);
-
- FastInstanceChecker rc = ComponentFactory.getFastInstanceChecker(tmp);
- for (KnowledgeSource ks : tmp) {
- ks.init();
- }
- rc.init();
- return rc;
+ // test if virtuoso is correct
+ // public static void validate(Description d, Examples newlyFound){
+ // try {
+ // ExMakerFixedSize fs = new ExMakerFixedSize(newlyFound);
+ // Examples tmp = fs.select(100, 100);
+ // FastInstanceChecker fc = _getFastInstanceChecker(tmp);
+ // @SuppressWarnings("unused")
+ // SortedSet<Individual> inds = fc.getIndividuals(d);
+ // } catch (Exception e) {
+ // e.printStackTrace();
+ // }
+ // }
+
+ public static FastInstanceChecker _getFastInstanceChecker(Examples ex) throws Exception {
+ Set<KnowledgeSource> tmp = _getOWL(ex);
+ // Set<KnowledgeSource> tmp = _getSPARQL(ex);
+
+ FastInstanceChecker rc = ComponentFactory.getFastInstanceChecker(tmp);
+ for (KnowledgeSource ks : tmp) {
+ ks.init();
+ }
+ rc.init();
+ return rc;
}
-
+
public static EvaluatedDescription learn(Examples ex, IteratedConfig config, int iteration) {
- Monitor initTimeKBandReasoner = JamonMonitorLogger.getTimeMonitor(TestIterativeLearning.class, "initTimeKBandReasoner").start();
-
+ Monitor initTimeKBandReasoner = JamonMonitorLogger.getTimeMonitor(TestIterativeLearning.class,
+ "initTimeKBandReasoner").start();
EvaluatedDescription result = null;
-
+
try {
FastInstanceChecker rc = _getFastInstanceChecker(ex);
PosNegLPStandard lp = ComponentFactory
@@ -452,14 +455,15 @@
lp.init();
la.init();
initTimeKBandReasoner.stop();
- Monitor learningTime = JamonMonitorLogger.getTimeMonitor(TestIterativeLearning.class, "learningTime").start();
+ Monitor learningTime = JamonMonitorLogger.getTimeMonitor(TestIterativeLearning.class,
+ "learningTime").start();
la.start();
learningTime.stop();
-
+
result = la.getCurrentlyBestEvaluatedDescription();
logger.trace(PrefixMap.toKBSyntaxString(result.getDescription()));
logger.trace(PrefixMap.toManchesterSyntaxString(result.getDescription()));
-
+
} catch (Exception e) {
e.printStackTrace();
System.exit(0);
@@ -467,7 +471,8 @@
return result;
}
- public static SortedSet<String> getSentences(EvaluatedDescription ed, int resultLimit) {// Examples justforFindingTheBug
+ public static SortedSet<String> getSentences(EvaluatedDescription ed, int resultLimit) {// Examples
+ // justforFindingTheBug
Monitor m = JamonMonitorLogger.getTimeMonitor(TestIterativeLearning.class, "getSentences").start();
SortedSet<String> result = new TreeSet<String>();
SparqlQueryDescriptionConvertVisitor visit = new SparqlQueryDescriptionConvertVisitor();
@@ -475,41 +480,42 @@
visit.setLabels(false);
visit.setLimit(resultLimit);
String sparqlQueryGood = "";
-// String sparqlQueryBad = "";
+ // String sparqlQueryBad = "";
try {
sparqlQueryGood = visit.getSparqlQuery(ed.getDescription().toKBSyntaxString());
-// sparqlQueryBad = visit.getSparqlQuery(ed.getDescription());
-// if(!sparqlQueryGood.equals(sparqlQueryBad)){
-// String file = "errorDescription/"+System.currentTimeMillis();
-// justforFindingTheBug.writeExamples(file);
-// Files.appendFile(new File(file), "\n\n/**\nGood:\n"+sparqlQueryGood+"\nBad:\n"+sparqlQueryBad+"**/");
-// }
-
+ // sparqlQueryBad = visit.getSparqlQuery(ed.getDescription());
+ // if(!sparqlQueryGood.equals(sparqlQueryBad)){
+ // String file = "errorDescription/"+System.currentTimeMillis();
+ // justforFindingTheBug.writeExamples(file);
+ // Files.appendFile(new File(file),
+ // "\n\n/**\nGood:\n"+sparqlQueryGood+"\nBad:\n"+sparqlQueryBad+"**/");
+ // }
+
} catch (Exception e1) {
e1.printStackTrace();
}
-
+
sparqlQueryGood = " \n define input:inference \"" + rulegraph + "\" \n" + "" + sparqlQueryGood;
logger.trace(sparqlQueryGood);
-
result.addAll(sparqlTasks.queryAsSet(sparqlQueryGood, "subject"));
m.stop();
- logger.debug("query avg: " + ((double)m.getAvg() / (double)1000)+ " seconds (last: "+((double)m.getLastValue() / (double)1000)+")");
- if(result.isEmpty()){
-
+ logger.debug("query avg: " + ((double) m.getAvg() / (double) 1000) + " seconds (last: "
+ + ((double) m.getLastValue() / (double) 1000) + ")");
+ if (result.isEmpty()) {
+
logger.error("sparql query returned no results ");
logger.error(sparqlQueryGood);
System.exit(0);
}
return result;
}
-
- private static void _getLabels(SortedSet<String> sentenceURIs, int limit){
+
+ private static void _getLabels(SortedSet<String> sentenceURIs, int limit) {
Monitor m = JamonMonitorLogger.getTimeMonitor(TestIterativeLearning.class, "_getLabels").start();
int i = 0;
for (String sentenceURI : sentenceURIs) {
- if(i>=limit){
+ if (i >= limit) {
break;
}
i++;
@@ -517,29 +523,29 @@
}
m.stop();
}
-
- private static void _getLabel(String sentenceURI){
- String query = "SELECT * FROM <"+graph+"> " +
- "{ <"+sentenceURI+"> rdfs:label ?label . }";
- SortedSet<String> s = sparqlTasks.queryAsSet(query, "label");
- if(s.isEmpty()){
- logger.warn("no label for "+sentenceURI);
- }else{
- logger.debug(sentenceURI.replace(prefix, "")+" "+s.first());
+
+ private static void _getLabel(String sentenceURI) {
+ String query = "SELECT * FROM <" + graph + "> " + "{ <" + sentenceURI + "> rdfs:label ?label . }";
+ SortedSet<String> s = sparqlTasks.queryAsSet(query, "label");
+ if (s.isEmpty()) {
+ logger.warn("no label for " + sentenceURI);
+ } else {
+ logger.debug(sentenceURI.replace(prefix, "") + " " + s.first());
}
}
- private static LearningAlgorithm _getROLLearner(LearningProblem lp, ReasonerComponent rc, IteratedConfig config, Examples ex, int iteration)
- throws Exception {
-
+ private static LearningAlgorithm _getROLLearner(LearningProblem lp, ReasonerComponent rc,
+ IteratedConfig config, Examples ex, int iteration) throws Exception {
+
int maxExecutionTime = config.maxExecutionTime;
int valueFrequencyThreshold = ex.getPosTrain().size();
int noise = config.noise + (iteration);
- if(config.adaptMaxRuntime){
- maxExecutionTime = (int)Math.floor(config.factor * (double)ex.sizeOfTrainingSets());
-// valueFrequencyThreshold = (int) Math.floor(0.8d*((double)ex.getPosTrain().size()));
+ if (config.adaptMaxRuntime) {
+ maxExecutionTime = (int) Math.floor(config.factor * (double) ex.sizeOfTrainingSets());
+ // valueFrequencyThreshold = (int)
+ // Math.floor(0.8d*((double)ex.getPosTrain().size()));
}
-
+
ROLComponent2 la = ComponentFactory.getROLComponent2(lp, rc);
la.getConfigurator().setUseExistsConstructor(true);
@@ -549,26 +555,25 @@
la.getConfigurator().setUseHasValueConstructor(false);
la.getConfigurator().setUseDataHasValueConstructor(config.useDataHasValue);
la.getConfigurator().setValueFrequencyThreshold(valueFrequencyThreshold);
-
- la.getConfigurator().setIgnoredConcepts(new HashSet<String>(Arrays.asList(new String[]{
- "http://nlp2rdf.org/ontology/sentencefinalpunctuation_tag",
- "http://nlp2rdf.org/ontology/comma_tag",
- "http://nachhalt.sfb632.uni-potsdam.de/owl/stts.owl#SentenceFinalPunctuation",
- "http://nlp2rdf.org/ontology/generalsentenceinternalpunctuation_tag"
- })));
-
+ la.getConfigurator().setIgnoredConcepts(
+ new HashSet<String>(Arrays.asList(new String[] {
+ "http://nlp2rdf.org/ontology/sentencefinalpunctuation_tag",
+ "http://nlp2rdf.org/ontology/comma_tag",
+ "http://nachhalt.sfb632.uni-potsdam.de/owl/stts.owl#SentenceFinalPunctuation",
+ "http://nlp2rdf.org/ontology/generalsentenceinternalpunctuation_tag" })));
+
la.getConfigurator().setNoisePercentage(noise);
la.getConfigurator().setTerminateOnNoiseReached(true);
la.getConfigurator().setMaxExecutionTimeInSeconds(maxExecutionTime);
-
- if(config.useStartClass){
+
+ if (config.useStartClass) {
la.getConfigurator().setStartClass(prefix + "Sentence");
}
-
- la.getConfigurator().setWriteSearchTree(config.searchTree);
- la.getConfigurator().setSearchTreeFile("log/searchTreeTiger.txt");
- la.getConfigurator().setReplaceSearchTree(true);
+
+ la.getConfigurator().setWriteSearchTree(config.searchTree);
+ la.getConfigurator().setSearchTreeFile("log/searchTreeTiger.txt");
+ la.getConfigurator().setReplaceSearchTree(true);
return la;
}
Modified: trunk/src/dl-learner/org/dllearner/utilities/experiments/Table.java
===================================================================
--- trunk/src/dl-learner/org/dllearner/utilities/experiments/Table.java 2010-02-16 13:23:18 UTC (rev 2045)
+++ trunk/src/dl-learner/org/dllearner/utilities/experiments/Table.java 2010-02-16 14:05:54 UTC (rev 2046)
@@ -1,5 +1,6 @@
package org.dllearner.utilities.experiments;
+import java.io.File;
import java.util.ArrayList;
import java.util.List;
import java.util.Random;
@@ -7,6 +8,7 @@
import java.util.TreeSet;
import org.apache.log4j.Logger;
+import org.dllearner.utilities.Files;
import org.dllearner.utilities.JamonMonitorLogger;
import com.jamonapi.Monitor;
@@ -73,6 +75,12 @@
}
}
+ public void addTable(Table t){
+ for (TableRowColumn trc : t.tableRowColumns) {
+ addTableRowColumn(trc);
+ }
+ }
+
public void addTableRowColumn(TableRowColumn trc) {
try{
trc.toLatexRow();
@@ -205,7 +213,17 @@
tableRowColumns = newTrc;
}
+ public void write(String folder, String fileprefix){
+ Files.mkdir(folder);
+ Files.createFile(new File(folder+fileprefix+"_GNU_ROWS"), getGnuPlotAsRows());
+ Files.createFile(new File(folder+fileprefix+"_GNU_COLUMNS_I"), getGnuPlotAsColumn(true));
+ Files.createFile(new File(folder+fileprefix+"_GNU_COLUMNS"), getGnuPlotAsColumn());
+
+
+ Files.createFile(new File(folder+fileprefix+"_LATEX_ROWS"), getLatexAsRows());
+ Files.createFile(new File(folder+fileprefix+"_LATEX_COLUMNS"), getLatexAsColumn());
+ Files.createFile(new File(folder+fileprefix+"_LATEX_COLUMNS_I"), getLatexAsColumn(true));
+ }
-
}
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