Examples with LinearScanDistanceKNNQuery de.lmu.ifi.dbs.elki.database.query.knn.LinearScanDistanceKNNQuery used on opensource projects

Example 6 with LinearScanDistanceKNNQuery

use of de.lmu.ifi.dbs.elki.database.query.knn.LinearScanDistanceKNNQuery in project elki by elki-project.

the class SpacefillingMaterializeKNNPreprocessorTest method testPreprocessor.

@Test
public void testPreprocessor() {
    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(// 
    SpacefillingMaterializeKNNPreprocessor.Factory.Parameterizer.CURVES_ID, // 
    HilbertSpatialSorter.class.getName() + "," + PeanoSpatialSorter.class.getName() + "," + ZCurveSpatialSorter.class.getName() + "," + BinarySplitSpatialSorter.class.getName());
    config.addParameter(SpacefillingMaterializeKNNPreprocessor.Factory.K_ID, k);
    config.addParameter(SpacefillingMaterializeKNNPreprocessor.Factory.Parameterizer.VARIANTS_ID, 10);
    config.addParameter(SpacefillingMaterializeKNNPreprocessor.Factory.Parameterizer.WINDOW_ID, 1.);
    config.addParameter(SpacefillingMaterializeKNNPreprocessor.Factory.Parameterizer.RANDOM_ID, 0L);
    SpacefillingMaterializeKNNPreprocessor.Factory<DoubleVector> preprocf = ClassGenericsUtil.parameterizeOrAbort(SpacefillingMaterializeKNNPreprocessor.Factory.class, config);
    SpacefillingMaterializeKNNPreprocessor<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);
}

Example 7 with LinearScanDistanceKNNQuery

use of de.lmu.ifi.dbs.elki.database.query.knn.LinearScanDistanceKNNQuery in project elki by elki-project.

the class NNDescentTest method testPreprocessor.

@Test
public void testPreprocessor() {
    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(NNDescent.Factory.DISTANCE_FUNCTION_ID, distanceQuery.getDistanceFunction());
    config.addParameter(NNDescent.Factory.K_ID, k);
    config.addParameter(NNDescent.Factory.Parameterizer.SEED_ID, 0);
    config.addParameter(NNDescent.Factory.Parameterizer.DELTA_ID, 0.1);
    config.addParameter(NNDescent.Factory.Parameterizer.RHO_ID, 0.5);
    NNDescent.Factory<DoubleVector> preprocf = ClassGenericsUtil.parameterizeOrAbort(NNDescent.Factory.class, config);
    NNDescent<DoubleVector> preproc = preprocf.instantiate(rel);
    KNNQuery<DoubleVector> preproc_knn_query = preproc.getKNNQuery(distanceQuery, k);
    // add as index
    db.getHierarchy().add(rel, preproc);
    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);
}

Example 8 with LinearScanDistanceKNNQuery

use of de.lmu.ifi.dbs.elki.database.query.knn.LinearScanDistanceKNNQuery 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);
}