List of distance() Examples

Examples of distance()

Hexel.math.Vector3d.distance()
algo.FlightDijkstra.distance()
be.ac.ulg.montefiore.run.jahmm.toolbox.KullbackLeiblerDistanceCalculator.distance()
Computes the Kullback-Leibler distance between two HMMs. @param hmm1 The first HMM against which the distance is computed.The distance is mesured with regard to this HMM (this must be defined since the Kullback-Leibler distance is not symetric). @param hmm2 The second HMM against which the distance is computed. @return The distance between hmm1 and hmm2 withregard to hmm1
chunmap.model.elem.Line.distance()
点到直线的距离 @param point @return
co.ideago.AdvancedPoint.PointND.distance()
com.ansj.vec.Word2VEC.distance()
com.ardor3d.math.Vector3.distance()
@param x @param y @param z @return the distance between the point described by this vector and the given x, y, z point.
com.datastax.driver.core.policies.LoadBalancingPolicy.distance()
Returns the distance assigned by this policy to the provided host.
The distance of an host influence how much connections are kept to the node (see {@link HostDistance}). A policy should assign a {@code LOCAL} distance to nodes that are susceptible to be returned first by{@code newQueryPlan} and it is useless for {@code newQueryPlan} toreturn hosts to which it assigns an {@code IGNORED} distance.
The host distance is primarily used to prevent keeping too many connections to host in remote datacenters when the policy itself always picks host in the local datacenter first. @param host the host of which to return the distance of. @return the HostDistance to {@code host}.
com.gameloftProgrammersCup.clientInterfaces.Point.distance()
com.github.davidmoten.rtree.geometry.Rectangle.distance()
com.jme.math.Vector3f.distance()
com.jme3.math.Vector3f.distance()
distance calculates the distance between this vector and vector v. @param v the second vector to determine the distance. @return the distance between the two vectors.
com.spatial4j.core.distance.DistanceCalculator.distance()
The distance between from and to.
com.vividsolutions.jts.geom.Coordinate.distance()
Computes the 2-dimensional Euclidean distance to another location. The Z-ordinate is ignored. @param p a point @return the 2-dimensional Euclidean distance between the locations
com.vividsolutions.jts.geom.Geometry.distance()
Returns the minimum distance between this Geometry and the Geometry g @param g the Geometry from which to compute the distance @return the distance between the geometries @return 0 if either input geometry is empty @throws IllegalArgumentException if g is null
com.vividsolutions.jts.geom.LineSegment.distance()
Computes the distance between this line segment and another segment. @return the distance to the other segment
com.vividsolutions.jts.geom.LineString.distance()
com.vividsolutions.jts.geom.Point.distance()
com.vividsolutions.jts.linearref.LinearLocation.distance()
com.vividsolutions.jts.operation.distance.DistanceOp.distance()
Compute the distance between the nearest points of two geometries. @param g0 a {@link Geometry} @param g1 another {@link Geometry} @return the distance between the geometries
crazypants.vecmath.Vector3d.distance()
de.lmu.ifi.dbs.elki.distance.distancefunction.WeightedDistanceFunction.distance()
de.lmu.ifi.dbs.elki.distance.distancefunction.correlation.ERiCDistanceFunction.distance()
Computes the distance between two given DatabaseObjects according to this distance function. Note, that the first pca must have equal or more strong eigenvectors than the second pca. @param v1 first DatabaseObject @param v2 second DatabaseObject @param pca1 first PCA @param pca2 second PCA @return the distance between two given DatabaseObjects according to thisdistance function
de.lmu.ifi.dbs.elki.distance.distancefunction.subspace.DimensionsSelectingEuclideanDistanceFunction.distance()
de.lmu.ifi.dbs.elki.distance.distancefunction.subspace.SubspaceEuclideanDistanceFunction.distance()
eas.math.geometry.Vector2D.distance()
Berechnet den Abstand von diesem Vektor (als Punkt interpretiert) zu einem anderen. @param anderer Der andere Punkt-Vektor. @return Der Abstand der beiden Punkte zueinander.
eas.simulation.spatial.sim2D.physicalSimulation.physicsEngine.net.phys2d.math.Vector2f.distance()
Get the distance from this point to another @param other The other point we're measuring to @return The distance to the other point
java.awt.Point.distance()
java.awt.geom.Point2D.distance()
Returns the distance between two points. @param x1 the X coordinate of the first specified point @param y1 the Y coordinate of the first specified point @param x2 the X coordinate of the second specified point @param y2 the Y coordinate of the second specified point @return the distance between the two sets of specifiedcoordinates. @since 1.2
javax.vecmath.Point2d.distance()
javax.vecmath.Point3d.distance()
javax.vecmath.Point3f.distance()
jdepend.framework.JavaPackage.distance()
@return The package's distance from the main sequence (D).
megamek.common.Coords.distance()
Returns the distance to another coordinate.
micdoodle8.mods.galacticraft.api.vector.Vector3.distance()
Gets the distance between two vectors @return The distance
net.phys2d.math.Vector2f.distance()
Get the distance from this point to another @param other The other point we're measuring to @return The distance to the other point
org.andrewberman.ui.Point.distance()
org.apache.commons.math3.geometry.euclidean.threed.Line.distance()
Compute the distance between the instance and a point. @param p to check @return distance between the instance and the point
org.apache.commons.math3.geometry.euclidean.twod.Line.distance()
Compute the distance between the instance and a point.
This is a shortcut for invoking FastMath.abs(getOffset(p)), and provides consistency with what is in the org.apache.commons.math3.geometry.euclidean.threed.Line class.
@param p to check @return distance between the instance and the point @since 3.1
org.apache.commons.math3.geometry.euclidean.twod.Vector2D.distance()
{@inheritDoc}
org.apache.mahout.common.distance.CosineDistanceMeasure.distance()
org.apache.mahout.common.distance.DistanceMeasure.distance()
Returns the distance metric applied to the arguments @param v1 a Vector defining a multidimensional point in some feature space @param v2 a Vector defining a multidimensional point in some feature space @return a scalar doubles of the distance
org.apache.mahout.common.distance.EuclideanDistanceMeasure.distance()
org.apache.mahout.common.distance.ManhattanDistanceMeasure.distance()
org.apache.mahout.common.distance.SquaredEuclideanDistanceMeasure.distance()
org.apache.mahout.utils.EuclideanDistanceMeasure.distance()
org.bukkit.Location.distance()
Get the distance between this location and another. The value of this method is not cached and uses a costly square-root function, so do not repeatedly call this method to get the location's magnitude. NaN will be returned if the inner result of the sqrt() function overflows, which will be caused if the distance is too long. @see Vector @param o The other location @return the distance @throws IllegalArgumentException for differing worlds
org.bukkit.util.BlockVector.distance()
org.codemap.util.geom.Point2D.distance()
Returns the distance between two points. @param x1 the X coordinate of the first specified point @param y1 the Y coordinate of the first specified point @param x2 the X coordinate of the second specified point @param y2 the Y coordinate of the second specified point @return the distance between the two sets of specifiedcoordinates. @since 1.2
org.elasticsearch.index.search.geo.GeoDistanceFilter.distance()
org.encog.ml.hmm.alog.KullbackLeiblerDistanceCalculator.distance()
org.geomajas.gwt.client.spatial.LineSegment.distance()
Return the distance from a point to this linesegment. If the point is not perpendicular to the linesegment, the closest endpoint will be returned. @param c The {@link Coordinate} to check distance from.
org.geotools.geometry.DirectPosition2D.distance()
org.geotools.geometry.iso.primitive.CurveImpl.distance()
org.jmol.modelset.Atom.distance()
org.newdawn.slick.geom.Vector2f.distance()
Get the distance from this point to another @param other The other point we're measuring to @return The distance to the other point
org.openstreetmap.josm.data.coor.EastNorth.distance()
Returns the euclidean distance from this {@code EastNorth} to a specified {@code EastNorth}. @param en the specified coordinate to be measured against this {@code EastNorth} @return the euclidean distance from this {@code EastNorth} to a specified {@code EastNorth} @since 6166
org.opentripplanner.common.geometry.DistanceLibrary.distance()
org.owasp.passfault.dictionary.LevenshteinDistance.distance()
org.spout.api.geo.discrete.Point.distance()
pythagoras.f.Point.distance()
soc.qase.state.Origin.distance()
Compute and return the distance between this point and the argument point. @param o the point to which to find the distance
soc.qase.tools.vecmath.Vector3f.distance()
Compute and return the distance between this vector and the argument vector, treating the vectors as points. @param v the vector to which to find the distance
stallone.coordinates.MinimalRMSDistance3D.distance()
tv.floe.metronome.clustering.kmeans.DistanceMeasurer.distance()

Examples of org.apache.commons.math3.geometry.euclidean.twod.Vector2D.distance()


                    // Jacobian of the radius residuals.
                    double[][] jacobian = new double[n][2];
                    for (int i = 0; i < n; i++) {
                        final Vector2D pi = points.get(i);
                        final double di = pi.distance(center);
                        jacobian[i][0] = (center.getX() - pi.getX()) / di - dRdX;
                        jacobian[i][1] = (center.getY() - pi.getY()) / di - dRdY;
                    }


                    return jacobian;

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Examples of org.apache.commons.math3.geometry.euclidean.twod.Vector2D.distance()

        final double tolerance = getTolerance();


        if (hull.size() == 1) {
            // ensure that we do not add an identical point
            final Vector2D p1 = hull.get(0);
            if (p1.distance(point) < tolerance) {
                return;
            }
        }


        while (hull.size() >= 2) {

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Examples of org.apache.commons.math3.geometry.euclidean.twod.Vector2D.distance()

            final double offset = new Line(p1, p2, tolerance).getOffset(point);
            if (FastMath.abs(offset) < tolerance) {
                // the point is collinear to the line (p1, p2)


                final double distanceToCurrent = p1.distance(point);
                if (distanceToCurrent < tolerance || p2.distance(point) < tolerance) {
                    // the point is assumed to be identical to either p1 or p2
                    return;
                }


                final double distanceToLast = p1.distance(p2);

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Examples of org.apache.mahout.common.distance.CosineDistanceMeasure.distance()

    double min = Double.MAX_VALUE;
    double sum = 0;
    int count = 0;
    for (int i = 0; i < clusters.size(); i++) {
      for (int j = i + 1; j < clusters.size(); j++) {
        double d = measure.distance(clusters.get(i)
            .getCenter(), clusters.get(j).getCenter());
        min = Math.min(d, min);
        max = Math.max(d, max);
        sum += d;
        count++;

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Examples of org.apache.mahout.common.distance.DistanceMeasure.distance()

    double min = Double.MAX_VALUE;
    double sum = 0;
    int count = 0;
    for (int i = 0; i < clusters.size(); i++) {
      for (int j = i + 1; j < clusters.size(); j++) {
        double d = measure.distance(clusters.get(i)
            .getCenter(), clusters.get(j).getCenter());
        min = Math.min(d, min);
        max = Math.max(d, max);
        sum += d;
        count++;

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Examples of org.apache.mahout.common.distance.EuclideanDistanceMeasure.distance()

      Map<String,Cluster> clusterMap = loadClusterMap(clusters);
      for (String key : collector.getKeys()) {
        Cluster cluster = clusterMap.get(key);
        List<KMeansInfo> values = collector.getValue(key);
        for (KMeansInfo value : values) {
          double distance = euclideanDistanceMeasure.distance(cluster.getCenter(), value.getPointTotal());
          for (Cluster c : clusters) {
            assertTrue("distance error", distance <= euclideanDistanceMeasure.distance(value.getPointTotal(),
              c.getCenter()));
          }
        }

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Examples of org.apache.mahout.common.distance.EuclideanDistanceMeasure.distance()

        Cluster cluster = clusterMap.get(key);
        List<KMeansInfo> values = collector.getValue(key);
        for (KMeansInfo value : values) {
          double distance = euclideanDistanceMeasure.distance(cluster.getCenter(), value.getPointTotal());
          for (Cluster c : clusters) {
            assertTrue("distance error", distance <= euclideanDistanceMeasure.distance(value.getPointTotal(),
              c.getCenter()));
          }
        }
      }
    }

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Examples of org.apache.mahout.common.distance.ManhattanDistanceMeasure.distance()

    FileWriter writer = new FileWriter(affinities.toString());
    PrintWriter out = new PrintWriter(writer);
    try {
      for (int i = 0; i < SAMPLE_DATA.size(); i++) {
        for (int j = 0; j < SAMPLE_DATA.size(); j++) {
          out.println(i + "," + j + "," + measure.distance(SAMPLE_DATA.get(i).get(), SAMPLE_DATA.get(j).get()));
        }
      }
    } finally {
      out.close();
    }

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Examples of org.apache.mahout.common.distance.SquaredEuclideanDistanceMeasure.distance()

    // Given the centroid, we can compute \Delta_1^2(X), the total squared distance for the datapoints
    // this accelerates seed selection.
    double radius = 0;
    DistanceMeasure l2 = new SquaredEuclideanDistanceMeasure();
    for (WeightedVector row : datapoints) {
      radius += l2.distance(row, center);
    }


    // Find the first seed c_1 (and conceptually the second, c_2) as might be done in the 2-means clustering so that
    // the probability of selecting c_1 and c_2 is proportional to || c_1 - c_2 ||^2.  This is done
    // by first selecting c_1 with probability:

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Examples of org.apache.mahout.utils.EuclideanDistanceMeasure.distance()

        List<Text> values = collector.getValue(key);
        for (Writable value : values) {
          String[] pointInfo = value.toString().split("\t");


          Vector point = AbstractVector.decodeVector(pointInfo[1]);
          double distance = euclideanDistanceMeasure.distance(cluster
              .getCenter(), point);
          for (Cluster c : clusters)
            assertTrue("distance error", distance <= euclideanDistanceMeasure
                .distance(point, c.getCenter()));
        }

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