smile.math.distance

Class SparseManhattanDistance

java.lang.Object

smile.math.distance.SparseManhattanDistance

All Implemented Interfaces:

java.io.Serializable, Distance<SparseArray>, Metric<SparseArray>

public class SparseManhattanDistance
extends java.lang.Object
implements Metric<SparseArray>, java.io.Serializable

Manhattan distance, also known as L₁ distance or L₁ norm, is the sum of the (absolute) differences of their coordinates. Use getInstance() to get the standard unweighted Manhattan distance. Or create an instance with a specified weight vector. For float or double arrays, missing values (i.e. NaN) are also handled. Also support sparse arrays of which zeros are excluded to save space.

See Also:

Serialized Form

Constructor Summary

Constructors

Constructor and Description
SparseManhattanDistance() Constructor.
SparseManhattanDistance(double[] weight) Constructor.

Method Summary

Modifier and Type	Method and Description
double	d(SparseArray x, SparseArray y) Returns the distance measure between two objects.
java.lang.String	toString()

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, wait, wait, wait

Constructor Detail

SparseManhattanDistance

public SparseManhattanDistance()

Constructor.

SparseManhattanDistance

public SparseManhattanDistance(double[] weight)

Constructor.

Parameters:

weight - the weight vector.

Method Detail

toString

public java.lang.String toString()

Overrides:

toString in class java.lang.Object

d

public double d(SparseArray x,
                SparseArray y)

Description copied from interface: Distance

Returns the distance measure between two objects.

Specified by:

d in interface Distance<SparseArray>