Examples with SpacefillingKNNPreprocessor de.lmu.ifi.dbs.elki.index.preprocessed.knn.SpacefillingKNNPreprocessor used on opensource projects

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Example 1 with SpacefillingKNNPreprocessor

use of de.lmu.ifi.dbs.elki.index.preprocessed.knn.SpacefillingKNNPreprocessor in project elki by elki-project.

the class SpacefillingKNNPreprocessorTest method testGaussian.

@Test
public void testGaussian() {
    Database db = AbstractSimpleAlgorithmTest.makeSimpleDatabase(dataset, shoulds);
    Relation<DoubleVector> rel = db.getRelation(TypeUtil.DOUBLE_VECTOR_FIELD);
    DistanceQuery<DoubleVector> distanceQuery = db.getDistanceQuery(rel, EuclideanDistanceFunction.STATIC);
    // get linear queries
    LinearScanDistanceKNNQuery<DoubleVector> lin_knn_query = new LinearScanDistanceKNNQuery<>(distanceQuery);
    // get preprocessed queries
    ListParameterization config = new ListParameterization();
    // 
    config.addParameter(// 
    SpacefillingKNNPreprocessor.Factory.Parameterizer.CURVES_ID, // 
    HilbertSpatialSorter.class.getName() + "," + PeanoSpatialSorter.class.getName() + "," + ZCurveSpatialSorter.class.getName() + "," + BinarySplitSpatialSorter.class.getName());
    config.addParameter(SpacefillingKNNPreprocessor.Factory.Parameterizer.DIM_ID, 7);
    config.addParameter(SpacefillingKNNPreprocessor.Factory.Parameterizer.PROJECTION_ID, GaussianRandomProjectionFamily.class);
    config.addParameter(SpacefillingKNNPreprocessor.Factory.Parameterizer.VARIANTS_ID, 10);
    config.addParameter(SpacefillingKNNPreprocessor.Factory.Parameterizer.WINDOW_ID, 5.);
    config.addParameter(SpacefillingKNNPreprocessor.Factory.Parameterizer.RANDOM_ID, 0L);
    config.addParameter(GaussianRandomProjectionFamily.Parameterizer.RANDOM_ID, 0L);
    SpacefillingKNNPreprocessor.Factory<DoubleVector> preprocf = ClassGenericsUtil.parameterizeOrAbort(SpacefillingKNNPreprocessor.Factory.class, config);
    SpacefillingKNNPreprocessor<DoubleVector> preproc = preprocf.instantiate(rel);
    preproc.initialize();
    // add as index
    db.getHierarchy().add(rel, preproc);
    KNNQuery<DoubleVector> preproc_knn_query = preproc.getKNNQuery(distanceQuery, k);
    assertFalse("Preprocessor knn query class incorrect.", preproc_knn_query instanceof LinearScanDistanceKNNQuery);
    // test queries
    testKNNQueries(rel, lin_knn_query, preproc_knn_query, k);
    // also test partial queries, forward only
    testKNNQueries(rel, lin_knn_query, preproc_knn_query, k / 2);
}
Also used : SpacefillingKNNPreprocessor(de.lmu.ifi.dbs.elki.index.preprocessed.knn.SpacefillingKNNPreprocessor) LinearScanDistanceKNNQuery(de.lmu.ifi.dbs.elki.database.query.knn.LinearScanDistanceKNNQuery) Database(de.lmu.ifi.dbs.elki.database.Database) DoubleVector(de.lmu.ifi.dbs.elki.data.DoubleVector) HilbertSpatialSorter(de.lmu.ifi.dbs.elki.math.spacefillingcurves.HilbertSpatialSorter) ListParameterization(de.lmu.ifi.dbs.elki.utilities.optionhandling.parameterization.ListParameterization) Test(org.junit.Test) AbstractSimpleAlgorithmTest(de.lmu.ifi.dbs.elki.algorithm.AbstractSimpleAlgorithmTest)

Example 2 with SpacefillingKNNPreprocessor

use of de.lmu.ifi.dbs.elki.index.preprocessed.knn.SpacefillingKNNPreprocessor in project elki by elki-project.

the class SpacefillingKNNPreprocessorTest method testHenzinger.

@Test
public void testHenzinger() {
    Database db = AbstractSimpleAlgorithmTest.makeSimpleDatabase(dataset, shoulds);
    Relation<DoubleVector> rel = db.getRelation(TypeUtil.DOUBLE_VECTOR_FIELD);
    DistanceQuery<DoubleVector> distanceQuery = db.getDistanceQuery(rel, EuclideanDistanceFunction.STATIC);
    // get linear queries
    LinearScanDistanceKNNQuery<DoubleVector> lin_knn_query = new LinearScanDistanceKNNQuery<>(distanceQuery);
    // get preprocessed queries
    ListParameterization config = new ListParameterization();
    // 
    config.addParameter(// 
    SpacefillingKNNPreprocessor.Factory.Parameterizer.CURVES_ID, // 
    HilbertSpatialSorter.class.getName() + "," + PeanoSpatialSorter.class.getName() + "," + ZCurveSpatialSorter.class.getName() + "," + BinarySplitSpatialSorter.class.getName());
    config.addParameter(SpacefillingKNNPreprocessor.Factory.Parameterizer.DIM_ID, 7);
    config.addParameter(SpacefillingKNNPreprocessor.Factory.Parameterizer.PROJECTION_ID, SimplifiedRandomHyperplaneProjectionFamily.class);
    config.addParameter(SpacefillingKNNPreprocessor.Factory.Parameterizer.VARIANTS_ID, 10);
    config.addParameter(SpacefillingKNNPreprocessor.Factory.Parameterizer.WINDOW_ID, 5.);
    config.addParameter(SpacefillingKNNPreprocessor.Factory.Parameterizer.RANDOM_ID, 0L);
    config.addParameter(SimplifiedRandomHyperplaneProjectionFamily.Parameterizer.RANDOM_ID, 1L);
    SpacefillingKNNPreprocessor.Factory<DoubleVector> preprocf = ClassGenericsUtil.parameterizeOrAbort(SpacefillingKNNPreprocessor.Factory.class, config);
    SpacefillingKNNPreprocessor<DoubleVector> preproc = preprocf.instantiate(rel);
    preproc.initialize();
    // add as index
    db.getHierarchy().add(rel, preproc);
    KNNQuery<DoubleVector> preproc_knn_query = preproc.getKNNQuery(distanceQuery, k);
    assertFalse("Preprocessor knn query class incorrect.", preproc_knn_query instanceof LinearScanDistanceKNNQuery);
    // test queries
    testKNNQueries(rel, lin_knn_query, preproc_knn_query, k);
    // also test partial queries, forward only
    testKNNQueries(rel, lin_knn_query, preproc_knn_query, k / 2);
}
Also used : SpacefillingKNNPreprocessor(de.lmu.ifi.dbs.elki.index.preprocessed.knn.SpacefillingKNNPreprocessor) LinearScanDistanceKNNQuery(de.lmu.ifi.dbs.elki.database.query.knn.LinearScanDistanceKNNQuery) Database(de.lmu.ifi.dbs.elki.database.Database) DoubleVector(de.lmu.ifi.dbs.elki.data.DoubleVector) HilbertSpatialSorter(de.lmu.ifi.dbs.elki.math.spacefillingcurves.HilbertSpatialSorter) ListParameterization(de.lmu.ifi.dbs.elki.utilities.optionhandling.parameterization.ListParameterization) Test(org.junit.Test) AbstractSimpleAlgorithmTest(de.lmu.ifi.dbs.elki.algorithm.AbstractSimpleAlgorithmTest)

Example 3 with SpacefillingKNNPreprocessor

use of de.lmu.ifi.dbs.elki.index.preprocessed.knn.SpacefillingKNNPreprocessor in project elki by elki-project.

the class SpacefillingKNNPreprocessorTest method testAchlioptas.

@Test
public void testAchlioptas() {
    Database db = AbstractSimpleAlgorithmTest.makeSimpleDatabase(dataset, shoulds);
    Relation<DoubleVector> rel = db.getRelation(TypeUtil.DOUBLE_VECTOR_FIELD);
    DistanceQuery<DoubleVector> distanceQuery = db.getDistanceQuery(rel, EuclideanDistanceFunction.STATIC);
    // get linear queries
    LinearScanDistanceKNNQuery<DoubleVector> lin_knn_query = new LinearScanDistanceKNNQuery<>(distanceQuery);
    // get preprocessed queries
    ListParameterization config = new ListParameterization();
    // 
    config.addParameter(// 
    SpacefillingKNNPreprocessor.Factory.Parameterizer.CURVES_ID, // 
    HilbertSpatialSorter.class.getName() + "," + PeanoSpatialSorter.class.getName() + "," + ZCurveSpatialSorter.class.getName() + "," + BinarySplitSpatialSorter.class.getName());
    config.addParameter(SpacefillingKNNPreprocessor.Factory.Parameterizer.DIM_ID, 7);
    config.addParameter(SpacefillingKNNPreprocessor.Factory.Parameterizer.PROJECTION_ID, AchlioptasRandomProjectionFamily.class);
    config.addParameter(SpacefillingKNNPreprocessor.Factory.Parameterizer.VARIANTS_ID, 10);
    config.addParameter(SpacefillingKNNPreprocessor.Factory.Parameterizer.WINDOW_ID, 5.);
    config.addParameter(SpacefillingKNNPreprocessor.Factory.Parameterizer.RANDOM_ID, 0L);
    config.addParameter(AchlioptasRandomProjectionFamily.Parameterizer.RANDOM_ID, 0L);
    SpacefillingKNNPreprocessor.Factory<DoubleVector> preprocf = ClassGenericsUtil.parameterizeOrAbort(SpacefillingKNNPreprocessor.Factory.class, config);
    SpacefillingKNNPreprocessor<DoubleVector> preproc = preprocf.instantiate(rel);
    preproc.initialize();
    // add as index
    db.getHierarchy().add(rel, preproc);
    KNNQuery<DoubleVector> preproc_knn_query = preproc.getKNNQuery(distanceQuery, k);
    assertFalse("Preprocessor knn query class incorrect.", preproc_knn_query instanceof LinearScanDistanceKNNQuery);
    // test queries
    testKNNQueries(rel, lin_knn_query, preproc_knn_query, k);
    // also test partial queries, forward only
    testKNNQueries(rel, lin_knn_query, preproc_knn_query, k / 2);
}
Also used : SpacefillingKNNPreprocessor(de.lmu.ifi.dbs.elki.index.preprocessed.knn.SpacefillingKNNPreprocessor) LinearScanDistanceKNNQuery(de.lmu.ifi.dbs.elki.database.query.knn.LinearScanDistanceKNNQuery) Database(de.lmu.ifi.dbs.elki.database.Database) DoubleVector(de.lmu.ifi.dbs.elki.data.DoubleVector) HilbertSpatialSorter(de.lmu.ifi.dbs.elki.math.spacefillingcurves.HilbertSpatialSorter) ListParameterization(de.lmu.ifi.dbs.elki.utilities.optionhandling.parameterization.ListParameterization) Test(org.junit.Test) AbstractSimpleAlgorithmTest(de.lmu.ifi.dbs.elki.algorithm.AbstractSimpleAlgorithmTest)

Example 4 with SpacefillingKNNPreprocessor

use of de.lmu.ifi.dbs.elki.index.preprocessed.knn.SpacefillingKNNPreprocessor in project elki by elki-project.

the class SpacefillingKNNPreprocessorTest method testSubset.

@Test
public void testSubset() {
    Database db = AbstractSimpleAlgorithmTest.makeSimpleDatabase(dataset, shoulds);
    Relation<DoubleVector> rel = db.getRelation(TypeUtil.DOUBLE_VECTOR_FIELD);
    DistanceQuery<DoubleVector> distanceQuery = db.getDistanceQuery(rel, EuclideanDistanceFunction.STATIC);
    // get linear queries
    LinearScanDistanceKNNQuery<DoubleVector> lin_knn_query = new LinearScanDistanceKNNQuery<>(distanceQuery);
    // get preprocessed queries
    ListParameterization config = new ListParameterization();
    // 
    config.addParameter(// 
    SpacefillingKNNPreprocessor.Factory.Parameterizer.CURVES_ID, // 
    HilbertSpatialSorter.class.getName() + "," + PeanoSpatialSorter.class.getName() + "," + ZCurveSpatialSorter.class.getName() + "," + BinarySplitSpatialSorter.class.getName());
    config.addParameter(SpacefillingKNNPreprocessor.Factory.Parameterizer.DIM_ID, 7);
    config.addParameter(SpacefillingKNNPreprocessor.Factory.Parameterizer.PROJECTION_ID, RandomSubsetProjectionFamily.class);
    config.addParameter(SpacefillingKNNPreprocessor.Factory.Parameterizer.VARIANTS_ID, 10);
    config.addParameter(SpacefillingKNNPreprocessor.Factory.Parameterizer.WINDOW_ID, 5.);
    config.addParameter(SpacefillingKNNPreprocessor.Factory.Parameterizer.RANDOM_ID, 0L);
    config.addParameter(RandomSubsetProjectionFamily.Parameterizer.RANDOM_ID, 0L);
    SpacefillingKNNPreprocessor.Factory<DoubleVector> preprocf = ClassGenericsUtil.parameterizeOrAbort(SpacefillingKNNPreprocessor.Factory.class, config);
    SpacefillingKNNPreprocessor<DoubleVector> preproc = preprocf.instantiate(rel);
    preproc.initialize();
    // add as index
    db.getHierarchy().add(rel, preproc);
    KNNQuery<DoubleVector> preproc_knn_query = preproc.getKNNQuery(distanceQuery, k);
    assertFalse("Preprocessor knn query class incorrect.", preproc_knn_query instanceof LinearScanDistanceKNNQuery);
    // test queries
    testKNNQueries(rel, lin_knn_query, preproc_knn_query, k);
    // also test partial queries, forward only
    testKNNQueries(rel, lin_knn_query, preproc_knn_query, k / 2);
}
Also used : SpacefillingKNNPreprocessor(de.lmu.ifi.dbs.elki.index.preprocessed.knn.SpacefillingKNNPreprocessor) LinearScanDistanceKNNQuery(de.lmu.ifi.dbs.elki.database.query.knn.LinearScanDistanceKNNQuery) Database(de.lmu.ifi.dbs.elki.database.Database) DoubleVector(de.lmu.ifi.dbs.elki.data.DoubleVector) HilbertSpatialSorter(de.lmu.ifi.dbs.elki.math.spacefillingcurves.HilbertSpatialSorter) ListParameterization(de.lmu.ifi.dbs.elki.utilities.optionhandling.parameterization.ListParameterization) Test(org.junit.Test) AbstractSimpleAlgorithmTest(de.lmu.ifi.dbs.elki.algorithm.AbstractSimpleAlgorithmTest)

Example 5 with SpacefillingKNNPreprocessor

use of de.lmu.ifi.dbs.elki.index.preprocessed.knn.SpacefillingKNNPreprocessor in project elki by elki-project.

the class SpacefillingKNNPreprocessorTest method testCauchy.

@Test
public void testCauchy() {
    Database db = AbstractSimpleAlgorithmTest.makeSimpleDatabase(dataset, shoulds);
    Relation<DoubleVector> rel = db.getRelation(TypeUtil.DOUBLE_VECTOR_FIELD);
    DistanceQuery<DoubleVector> distanceQuery = db.getDistanceQuery(rel, EuclideanDistanceFunction.STATIC);
    // get linear queries
    LinearScanDistanceKNNQuery<DoubleVector> lin_knn_query = new LinearScanDistanceKNNQuery<>(distanceQuery);
    // get preprocessed queries
    ListParameterization config = new ListParameterization();
    // 
    config.addParameter(// 
    SpacefillingKNNPreprocessor.Factory.Parameterizer.CURVES_ID, // 
    HilbertSpatialSorter.class.getName() + "," + PeanoSpatialSorter.class.getName() + "," + ZCurveSpatialSorter.class.getName() + "," + BinarySplitSpatialSorter.class.getName());
    config.addParameter(SpacefillingKNNPreprocessor.Factory.Parameterizer.DIM_ID, 7);
    config.addParameter(SpacefillingKNNPreprocessor.Factory.Parameterizer.PROJECTION_ID, CauchyRandomProjectionFamily.class);
    config.addParameter(SpacefillingKNNPreprocessor.Factory.Parameterizer.VARIANTS_ID, 10);
    config.addParameter(SpacefillingKNNPreprocessor.Factory.Parameterizer.WINDOW_ID, 5.);
    config.addParameter(SpacefillingKNNPreprocessor.Factory.Parameterizer.RANDOM_ID, 0L);
    config.addParameter(CauchyRandomProjectionFamily.Parameterizer.RANDOM_ID, 0L);
    SpacefillingKNNPreprocessor.Factory<DoubleVector> preprocf = ClassGenericsUtil.parameterizeOrAbort(SpacefillingKNNPreprocessor.Factory.class, config);
    SpacefillingKNNPreprocessor<DoubleVector> preproc = preprocf.instantiate(rel);
    preproc.initialize();
    // add as index
    db.getHierarchy().add(rel, preproc);
    KNNQuery<DoubleVector> preproc_knn_query = preproc.getKNNQuery(distanceQuery, k);
    assertFalse("Preprocessor knn query class incorrect.", preproc_knn_query instanceof LinearScanDistanceKNNQuery);
    // test queries
    testKNNQueries(rel, lin_knn_query, preproc_knn_query, k);
    // also test partial queries, forward only
    testKNNQueries(rel, lin_knn_query, preproc_knn_query, k / 2);
}
Also used : SpacefillingKNNPreprocessor(de.lmu.ifi.dbs.elki.index.preprocessed.knn.SpacefillingKNNPreprocessor) LinearScanDistanceKNNQuery(de.lmu.ifi.dbs.elki.database.query.knn.LinearScanDistanceKNNQuery) Database(de.lmu.ifi.dbs.elki.database.Database) DoubleVector(de.lmu.ifi.dbs.elki.data.DoubleVector) HilbertSpatialSorter(de.lmu.ifi.dbs.elki.math.spacefillingcurves.HilbertSpatialSorter) ListParameterization(de.lmu.ifi.dbs.elki.utilities.optionhandling.parameterization.ListParameterization) Test(org.junit.Test) AbstractSimpleAlgorithmTest(de.lmu.ifi.dbs.elki.algorithm.AbstractSimpleAlgorithmTest)

Aggregations

AbstractSimpleAlgorithmTest (de.lmu.ifi.dbs.elki.algorithm.AbstractSimpleAlgorithmTest)5 DoubleVector (de.lmu.ifi.dbs.elki.data.DoubleVector)5 Database (de.lmu.ifi.dbs.elki.database.Database)5 LinearScanDistanceKNNQuery (de.lmu.ifi.dbs.elki.database.query.knn.LinearScanDistanceKNNQuery)5 SpacefillingKNNPreprocessor (de.lmu.ifi.dbs.elki.index.preprocessed.knn.SpacefillingKNNPreprocessor)5 HilbertSpatialSorter (de.lmu.ifi.dbs.elki.math.spacefillingcurves.HilbertSpatialSorter)5 ListParameterization (de.lmu.ifi.dbs.elki.utilities.optionhandling.parameterization.ListParameterization)5 Test (org.junit.Test)5
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