@Override public Sampler< T > getSampler() { return getSampler( 0 ); }
@Override public double getSquareDistance() { return getSquareDistance( 0 ); }
@Override public double getDistance() { return getDistance( 0 ); }
@Override public boolean test( final RealLocalizable l ) { search.search( l ); return search.getSquareDistance() <= 0; }
@Override public Sampler< T > getSampler() { return getSampler( 0 ); }
@Override public RealLocalizable getPosition() { return getPosition( 0 ); }
@Override public double getDistance() { return getDistance( 0 ); }
/** * Creates a {@link RealPointCollection}. * * @param interval * Contains the points which will be included in this collection. * This will be used to create a * {@link NearestNeighborSearchOnIterableRealInterval}.The first * point determines the dimensionality of the collection. */ public NNSRealPointCollection( final IterableRealInterval< L > interval ) { this( interval, new NearestNeighborSearchOnIterableRealInterval<>( interval ) ); }
@Override public double getSquareDistance() { return getSquareDistance( 0 ); }
public NearestNeighborSearchInterpolator( final NearestNeighborSearch< T > search ) { super( search.numDimensions() ); this.search = search; }
@Override public RealLocalizable getPosition() { return getPosition( 0 ); }
@Override public Sampler< T > getSampler() { return getSampler( 0 ); }
@Override public Sampler< T > getSampler() { return getSampler( 0 ); }
@Override public RealLocalizable getPosition() { return getPosition( 0 ); }
@Override public double getDistance() { return getDistance( 0 ); }
@Override public double getSquareDistance() { return getSquareDistance( 0 ); }
@Override public double getDistance() { return getDistance( 0 ); }
@Override public double getSquareDistance() { return getSquareDistance( 0 ); }
public NearestNeighborSearchInterpolator( final NearestNeighborSearch< T > search ) { super( search.numDimensions() ); this.search = search; }
@Override public RealLocalizable getPosition() { return getPosition( 0 ); }