Class ManhattanDistance

java.lang.Object

smile.math.distance.ManhattanDistance

All Implemented Interfaces:

Serializable, ToDoubleBiFunction<double[],double[]>, Distance<double[]>, Metric<double[]>

public class ManhattanDistance
extends Object
implements Metric<double[]>

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.

See Also:

• SparseManhattanDistance
• Serialized Form

Constructor Summary

Constructors

Constructor	Description
ManhattanDistance()	Constructor.
ManhattanDistance(double[] weight)	Constructor.

Method Summary

Modifier and Type	Method	Description
double	d(double[] x, double[] y)	Manhattan distance between two arrays of type double.
double	d(float[] x, float[] y)	Manhattan distance between two arrays of type float.
double	d(int[] x, int[] y)	Manhattan distance between two arrays of type integer.
String	toString()

Methods inherited from class Object

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

Methods inherited from interface Distance

apply, applyAsDouble, pdist, pdist

Constructor Details

ManhattanDistance

public ManhattanDistance()

Constructor.

ManhattanDistance

public ManhattanDistance(double[] weight)

Constructor.

Parameters:

weight - the weight vector.

Method Details

toString

public String toString()

Overrides:

toString in class Object

d

public double d(int[] x,
 int[] y)

Manhattan distance between two arrays of type integer.

Parameters:

x - a vector.

y - a vector.

Returns:

the distance.

d

public double d(float[] x,
 float[] y)

Manhattan distance between two arrays of type float. NaN will be treated as missing values and will be excluded from the calculation. Let m be the number non-missing values, and n be the number of all values. The returned distance is n * d / m, where d is the distance between non-missing values.

Parameters:

x - a vector.

y - a vector.

Returns:

the distance.

d

public double d(double[] x,
 double[] y)

Manhattan distance between two arrays of type double. NaN will be treated as missing values and will be excluded from the calculation. Let m be the number non-missing values, and n be the number of all values. The returned distance is n * d / m, where d is the distance between non-missing values.

Specified by:

d in interface Distance<double[]>

Parameters:

x - an object.

y - an object.

Returns:

the distance.