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-rw-r--r--src/de/lmu/ifi/dbs/elki/algorithm/benchmark/RangeQueryBenchmarkAlgorithm.java121
1 files changed, 56 insertions, 65 deletions
diff --git a/src/de/lmu/ifi/dbs/elki/algorithm/benchmark/RangeQueryBenchmarkAlgorithm.java b/src/de/lmu/ifi/dbs/elki/algorithm/benchmark/RangeQueryBenchmarkAlgorithm.java
index 1b5e827b..b5336aac 100644
--- a/src/de/lmu/ifi/dbs/elki/algorithm/benchmark/RangeQueryBenchmarkAlgorithm.java
+++ b/src/de/lmu/ifi/dbs/elki/algorithm/benchmark/RangeQueryBenchmarkAlgorithm.java
@@ -4,7 +4,7 @@ package de.lmu.ifi.dbs.elki.algorithm.benchmark;
This file is part of ELKI:
Environment for Developing KDD-Applications Supported by Index-Structures
- Copyright (C) 2013
+ Copyright (C) 2014
Ludwig-Maximilians-Universität München
Lehr- und Forschungseinheit für Datenbanksysteme
ELKI Development Team
@@ -25,7 +25,6 @@ package de.lmu.ifi.dbs.elki.algorithm.benchmark;
import de.lmu.ifi.dbs.elki.algorithm.AbstractDistanceBasedAlgorithm;
import de.lmu.ifi.dbs.elki.data.NumberVector;
-import de.lmu.ifi.dbs.elki.data.NumberVector.Factory;
import de.lmu.ifi.dbs.elki.data.type.TypeInformation;
import de.lmu.ifi.dbs.elki.data.type.TypeUtil;
import de.lmu.ifi.dbs.elki.data.type.VectorFieldTypeInformation;
@@ -34,7 +33,7 @@ import de.lmu.ifi.dbs.elki.database.ids.DBIDIter;
import de.lmu.ifi.dbs.elki.database.ids.DBIDRange;
import de.lmu.ifi.dbs.elki.database.ids.DBIDUtil;
import de.lmu.ifi.dbs.elki.database.ids.DBIDs;
-import de.lmu.ifi.dbs.elki.database.ids.distance.DistanceDBIDList;
+import de.lmu.ifi.dbs.elki.database.ids.DoubleDBIDList;
import de.lmu.ifi.dbs.elki.database.query.distance.DistanceQuery;
import de.lmu.ifi.dbs.elki.database.query.range.RangeQuery;
import de.lmu.ifi.dbs.elki.database.relation.Relation;
@@ -42,12 +41,11 @@ import de.lmu.ifi.dbs.elki.database.relation.RelationUtil;
import de.lmu.ifi.dbs.elki.datasource.DatabaseConnection;
import de.lmu.ifi.dbs.elki.datasource.bundle.MultipleObjectsBundle;
import de.lmu.ifi.dbs.elki.distance.distancefunction.DistanceFunction;
-import de.lmu.ifi.dbs.elki.distance.distancevalue.NumberDistance;
import de.lmu.ifi.dbs.elki.logging.Logging;
import de.lmu.ifi.dbs.elki.logging.progress.FiniteProgress;
import de.lmu.ifi.dbs.elki.math.MeanVariance;
+import de.lmu.ifi.dbs.elki.math.random.RandomFactory;
import de.lmu.ifi.dbs.elki.result.Result;
-import de.lmu.ifi.dbs.elki.utilities.RandomFactory;
import de.lmu.ifi.dbs.elki.utilities.Util;
import de.lmu.ifi.dbs.elki.utilities.exceptions.AbortException;
import de.lmu.ifi.dbs.elki.utilities.optionhandling.OptionID;
@@ -93,11 +91,10 @@ import de.lmu.ifi.dbs.elki.utilities.optionhandling.parameters.RandomParameter;
* @author Erich Schubert
*
* @param <O> Vector type
- * @param <D> Distance type
*
* @apiviz.uses RangeQuery
*/
-public class RangeQueryBenchmarkAlgorithm<O extends NumberVector<?>, D extends NumberDistance<D, ?>> extends AbstractDistanceBasedAlgorithm<O, D, Result> {
+public class RangeQueryBenchmarkAlgorithm<O extends NumberVector> extends AbstractDistanceBasedAlgorithm<O, Result> {
/**
* The logger for this class.
*/
@@ -126,7 +123,7 @@ public class RangeQueryBenchmarkAlgorithm<O extends NumberVector<?>, D extends N
* @param sampling Sampling rate
* @param random Random factory
*/
- public RangeQueryBenchmarkAlgorithm(DistanceFunction<? super O, D> distanceFunction, DatabaseConnection queries, double sampling, RandomFactory random) {
+ public RangeQueryBenchmarkAlgorithm(DistanceFunction<? super O> distanceFunction, DatabaseConnection queries, double sampling, RandomFactory random) {
super(distanceFunction);
this.queries = queries;
this.sampling = sampling;
@@ -141,45 +138,42 @@ public class RangeQueryBenchmarkAlgorithm<O extends NumberVector<?>, D extends N
* @param radrel Radius relation
* @return Null result
*/
- public Result run(Database database, Relation<O> relation, Relation<NumberVector<?>> radrel) {
- if (queries != null) {
+ public Result run(Database database, Relation<O> relation, Relation<NumberVector> radrel) {
+ if(queries != null) {
throw new AbortException("This 'run' method will not use the given query set!");
}
// Get a distance and kNN query instance.
- DistanceQuery<O, D> distQuery = database.getDistanceQuery(relation, getDistanceFunction());
- RangeQuery<O, D> rangeQuery = database.getRangeQuery(distQuery);
- D dfactory = distQuery.getDistanceFactory();
+ DistanceQuery<O> distQuery = database.getDistanceQuery(relation, getDistanceFunction());
+ RangeQuery<O> rangeQuery = database.getRangeQuery(distQuery);
final DBIDs sample;
- if (sampling <= 0) {
+ if(sampling <= 0) {
sample = relation.getDBIDs();
- } else if (sampling < 1.1) {
+ }
+ else if(sampling < 1.1) {
int size = (int) Math.min(sampling * relation.size(), relation.size());
sample = DBIDUtil.randomSample(relation.getDBIDs(), size, random);
- } else {
+ }
+ else {
int size = (int) Math.min(sampling, relation.size());
sample = DBIDUtil.randomSample(relation.getDBIDs(), size, random);
}
FiniteProgress prog = LOG.isVeryVerbose() ? new FiniteProgress("kNN queries", sample.size(), LOG) : null;
int hash = 0;
MeanVariance mv = new MeanVariance();
- for (DBIDIter iditer = sample.iter(); iditer.valid(); iditer.advance()) {
- D r = dfactory.fromDouble(radrel.get(iditer).doubleValue(0));
- DistanceDBIDList<D> rres = rangeQuery.getRangeForDBID(iditer, r);
+ for(DBIDIter iditer = sample.iter(); iditer.valid(); iditer.advance()) {
+ double r = radrel.get(iditer).doubleValue(0);
+ DoubleDBIDList rres = rangeQuery.getRangeForDBID(iditer, r);
int ichecksum = 0;
- for (DBIDIter it = rres.iter(); it.valid(); it.advance()) {
- ichecksum += it.internalGetIndex();
+ for(DBIDIter it = rres.iter(); it.valid(); it.advance()) {
+ ichecksum += DBIDUtil.asInteger(it);
}
hash = Util.mixHashCodes(hash, ichecksum);
mv.put(rres.size());
- if (prog != null) {
- prog.incrementProcessed(LOG);
- }
+ LOG.incrementProcessed(prog);
}
- if (prog != null) {
- prog.ensureCompleted(LOG);
- }
- if (LOG.isStatistics()) {
+ LOG.ensureCompleted(prog);
+ if(LOG.isStatistics()) {
LOG.statistics("Result hashcode: " + hash);
LOG.statistics("Mean number of results: " + mv.getMean() + " +- " + mv.getNaiveStddev());
}
@@ -194,33 +188,32 @@ public class RangeQueryBenchmarkAlgorithm<O extends NumberVector<?>, D extends N
* @return Null result
*/
public Result run(Database database, Relation<O> relation) {
- if (queries == null) {
+ if(queries == null) {
throw new AbortException("A query set is required for this 'run' method.");
}
// Get a distance and kNN query instance.
- DistanceQuery<O, D> distQuery = database.getDistanceQuery(relation, getDistanceFunction());
- RangeQuery<O, D> rangeQuery = database.getRangeQuery(distQuery);
- D dfactory = distQuery.getDistanceFactory();
- Factory<O, ?> ofactory = RelationUtil.getNumberVectorFactory(relation);
+ DistanceQuery<O> distQuery = database.getDistanceQuery(relation, getDistanceFunction());
+ RangeQuery<O> rangeQuery = database.getRangeQuery(distQuery);
+ NumberVector.Factory<O> ofactory = RelationUtil.getNumberVectorFactory(relation);
int dim = RelationUtil.dimensionality(relation);
// Separate query set.
- TypeInformation res = new VectorFieldTypeInformation<NumberVector<?>>(NumberVector.class, dim + 1);
+ TypeInformation res = VectorFieldTypeInformation.typeRequest(NumberVector.class, dim + 1, dim + 1);
MultipleObjectsBundle bundle = queries.loadData();
int col = -1;
- for (int i = 0; i < bundle.metaLength(); i++) {
- if (res.isAssignableFromType(bundle.meta(i))) {
+ for(int i = 0; i < bundle.metaLength(); i++) {
+ if(res.isAssignableFromType(bundle.meta(i))) {
col = i;
break;
}
}
- if (col < 0) {
+ if(col < 0) {
StringBuilder buf = new StringBuilder();
buf.append("No compatible data type in query input was found. Expected: ");
buf.append(res.toString());
buf.append(" have: ");
- for (int i = 0; i < bundle.metaLength(); i++) {
- if (i > 0) {
+ for(int i = 0; i < bundle.metaLength(); i++) {
+ if(i > 0) {
buf.append(' ');
}
buf.append(bundle.meta(i).toString());
@@ -232,12 +225,14 @@ public class RangeQueryBenchmarkAlgorithm<O extends NumberVector<?>, D extends N
DBIDRange sids = DBIDUtil.generateStaticDBIDRange(bundle.dataLength());
final DBIDs sample;
- if (sampling <= 0) {
+ if(sampling <= 0) {
sample = sids;
- } else if (sampling < 1.1) {
+ }
+ else if(sampling < 1.1) {
int size = (int) Math.min(sampling * relation.size(), relation.size());
sample = DBIDUtil.randomSample(sids, size, random);
- } else {
+ }
+ else {
int size = (int) Math.min(sampling, sids.size());
sample = DBIDUtil.randomSample(sids, size, random);
}
@@ -245,30 +240,26 @@ public class RangeQueryBenchmarkAlgorithm<O extends NumberVector<?>, D extends N
int hash = 0;
MeanVariance mv = new MeanVariance();
double[] buf = new double[dim];
- for (DBIDIter iditer = sample.iter(); iditer.valid(); iditer.advance()) {
+ for(DBIDIter iditer = sample.iter(); iditer.valid(); iditer.advance()) {
int off = sids.binarySearch(iditer);
assert (off >= 0);
- NumberVector<?> o = (NumberVector<?>) bundle.data(off, col);
- for (int i = 0; i < dim; i++) {
+ NumberVector o = (NumberVector) bundle.data(off, col);
+ for(int i = 0; i < dim; i++) {
buf[i] = o.doubleValue(i);
}
O v = ofactory.newNumberVector(buf);
- D r = dfactory.fromDouble(o.doubleValue(dim));
- DistanceDBIDList<D> rres = rangeQuery.getRangeForObject(v, r);
+ double r = o.doubleValue(dim);
+ DoubleDBIDList rres = rangeQuery.getRangeForObject(v, r);
int ichecksum = 0;
- for (DBIDIter it = rres.iter(); it.valid(); it.advance()) {
- ichecksum += it.internalGetIndex();
+ for(DBIDIter it = rres.iter(); it.valid(); it.advance()) {
+ ichecksum += DBIDUtil.asInteger(it);
}
hash = Util.mixHashCodes(hash, ichecksum);
mv.put(rres.size());
- if (prog != null) {
- prog.incrementProcessed(LOG);
- }
+ LOG.incrementProcessed(prog);
}
- if (prog != null) {
- prog.ensureCompleted(LOG);
- }
- if (LOG.isStatistics()) {
+ LOG.ensureCompleted(prog);
+ if(LOG.isStatistics()) {
LOG.statistics("Result hashcode: " + hash);
LOG.statistics("Mean number of results: " + mv.getMean() + " +- " + mv.getNaiveStddev());
}
@@ -277,9 +268,10 @@ public class RangeQueryBenchmarkAlgorithm<O extends NumberVector<?>, D extends N
@Override
public TypeInformation[] getInputTypeRestriction() {
- if (queries == null) {
- return TypeUtil.array(getDistanceFunction().getInputTypeRestriction(), new VectorFieldTypeInformation<NumberVector<?>>(NumberVector.class, 1));
- } else {
+ if(queries == null) {
+ return TypeUtil.array(getDistanceFunction().getInputTypeRestriction(), TypeUtil.NUMBER_VECTOR_FIELD_1D);
+ }
+ else {
return TypeUtil.array(getDistanceFunction().getInputTypeRestriction());
}
}
@@ -297,9 +289,8 @@ public class RangeQueryBenchmarkAlgorithm<O extends NumberVector<?>, D extends N
* @author Erich Schubert
*
* @param <O> Object type
- * @param <D> Distance type
*/
- public static class Parameterizer<O extends NumberVector<?>, D extends NumberDistance<D, ?>> extends AbstractDistanceBasedAlgorithm.Parameterizer<O, D> {
+ public static class Parameterizer<O extends NumberVector> extends AbstractDistanceBasedAlgorithm.Parameterizer<O> {
/**
* Parameter for the query dataset.
*/
@@ -335,22 +326,22 @@ public class RangeQueryBenchmarkAlgorithm<O extends NumberVector<?>, D extends N
super.makeOptions(config);
ObjectParameter<DatabaseConnection> queryP = new ObjectParameter<>(QUERY_ID, DatabaseConnection.class);
queryP.setOptional(true);
- if (config.grab(queryP)) {
+ if(config.grab(queryP)) {
queries = queryP.instantiateClass(config);
}
DoubleParameter samplingP = new DoubleParameter(SAMPLING_ID);
samplingP.setOptional(true);
- if (config.grab(samplingP)) {
+ if(config.grab(samplingP)) {
sampling = samplingP.doubleValue();
}
RandomParameter randomP = new RandomParameter(RANDOM_ID, RandomFactory.DEFAULT);
- if (config.grab(randomP)) {
+ if(config.grab(randomP)) {
random = randomP.getValue();
}
}
@Override
- protected RangeQueryBenchmarkAlgorithm<O, D> makeInstance() {
+ protected RangeQueryBenchmarkAlgorithm<O> makeInstance() {
return new RangeQueryBenchmarkAlgorithm<>(distanceFunction, queries, sampling, random);
}
}
generated by cgit v1.2.3 (git 2.25.1) at 2024-06-01 17:48:50 +0000