jsat.linear.distancemetrics

Class ManhattanDistance

java.lang.Object

jsat.linear.distancemetrics.ManhattanDistance

All Implemented Interfaces:

Serializable, Cloneable, DenseSparseMetric, DistanceMetric

public class ManhattanDistance
extends Object
implements DenseSparseMetric

Manhattan Distance is the L₁ norm.

Author:

Edward Raff

See Also:

Serialized Form

Constructor Summary

Constructors

Constructor and Description
ManhattanDistance()

Method Summary

Modifier and Type	Method and Description
ManhattanDistance	clone()
double	dist(double summaryConst, Vec main, Vec target) Efficiently computes the distance from one main vector that is used many times, to some sparse target vector.
double	dist(int a, int b, List<? extends Vec> vecs, List<Double> cache) Computes the distance between 2 vectors in the original list of vectors.
double	dist(int a, Vec b, List<? extends Vec> vecs, List<Double> cache) Computes the distance between one vector in the original list of vectors with that of another vector not from the original list.
double	dist(int a, Vec b, List<Double> qi, List<? extends Vec> vecs, List<Double> cache) Computes the distance between one vector in the original list of vectors with that of another vector not from the original list, but had information generated by DistanceMetric.getQueryInfo(jsat.linear.Vec).
double	dist(Vec a, Vec b) Computes the distance between 2 vectors.
List<Double>	getAccelerationCache(List<? extends Vec> vecs) Returns a cache of double values associated with the given list of vectors in the given order.
List<Double>	getAccelerationCache(List<? extends Vec> vecs, ExecutorService threadpool) Returns a cache of double values associated with the given list of vectors in the given order.
List<Double>	getQueryInfo(Vec q) Pre computes query information that would have be generated if the query was a member of the original list of vectors when calling DistanceMetric.getAccelerationCache(java.util.List) .
double	getVectorConstant(Vec vec) Computes a summary constant value for the vector that is based on the distance metric in use.
boolean	isIndiscemible() Returns true if this distance metric obeys the rule that, for any x and y ∈ S d(x, y) = 0 if and only if x = y
boolean	isSubadditive() Returns true if this distance metric obeys the rule that, for any x, y, and z ∈ S d(x, z) ≤ d(x, y) + d(y, z)
boolean	isSymmetric() Returns true if this distance metric obeys the rule that, for any x, y, and z ∈ S d(x, y) = d(y, x)
double	metricBound() All metrics must return values greater than or equal to 0.
boolean	supportsAcceleration() Indicates if this distance metric supports building an acceleration cache using the DistanceMetric.getAccelerationCache(java.util.List) and associated distance methods.
String	toString() Returns a descriptive name of the Distance Metric in use

Methods inherited from class java.lang.Object

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

Constructor Detail

ManhattanDistance

public ManhattanDistance()

Method Detail

dist

public double dist(Vec a,
                   Vec b)

Description copied from interface: DistanceMetric

Computes the distance between 2 vectors. The smaller the value, the closer, and there for, more similar, the vectors are. 0 indicates the vectors are the same.

Specified by:

dist in interface DistanceMetric

Parameters:

a - the first vector

b - the second vector

Returns:

the distance between them

isSymmetric

public boolean isSymmetric()

Description copied from interface: DistanceMetric

Returns true if this distance metric obeys the rule that, for any x, y, and z ∈ S
d(x, y) = d(y, x)

Specified by:

isSymmetric in interface DistanceMetric

Returns:

true if this distance metric is symmetric, false if it is not

isSubadditive

public boolean isSubadditive()

Description copied from interface: DistanceMetric

Returns true if this distance metric obeys the rule that, for any x, y, and z ∈ S
d(x, z) ≤ d(x, y) + d(y, z)

Specified by:

isSubadditive in interface DistanceMetric

Returns:

true if this distance metric supports the triangle inequality, false if it does not.

isIndiscemible

public boolean isIndiscemible()

Description copied from interface: DistanceMetric

Returns true if this distance metric obeys the rule that, for any x and y ∈ S
d(x, y) = 0 if and only if x = y

Specified by:

isIndiscemible in interface DistanceMetric

Returns:

true if this distance metric is indicemible, false otherwise.

metricBound

public double metricBound()

Description copied from interface: DistanceMetric

All metrics must return values greater than or equal to 0. The upper bound on the value returned is different for different metrics. This method returns the theoretical maximal value that could be returned by this distance metric. That means Double.POSITIVE_INFINITY is a valid return value.

Specified by:

metricBound in interface DistanceMetric

Returns:

the maximal distance for any two points in that could exist by this distance metric.

toString

public String toString()

Description copied from interface: DistanceMetric

Returns a descriptive name of the Distance Metric in use

Specified by:

toString in interface DistanceMetric

Overrides:

toString in class Object

Returns:

the name of this metric

clone

public ManhattanDistance clone()

Specified by:

clone in interface DistanceMetric

Overrides:

clone in class Object

getVectorConstant

public double getVectorConstant(Vec vec)

Description copied from interface: DenseSparseMetric

Computes a summary constant value for the vector that is based on the distance metric in use. This value will be used to perform efficient dense to sparse computations.

Specified by:

getVectorConstant in interface DenseSparseMetric

Parameters:

vec - the vector that will be used in many distance computations

Returns:

the summary value for the vector

dist

public double dist(double summaryConst,
                   Vec main,
                   Vec target)

Description copied from interface: DenseSparseMetric

Efficiently computes the distance from one main vector that is used many times, to some sparse target vector. If the target vector dose not return true for Vec.isSparse(), the distance will be calculated using DistanceMetric.dist(jsat.linear.Vec, jsat.linear.Vec) instead.

Specified by:

dist in interface DenseSparseMetric

Parameters:

summaryConst - the summary constant for the main vector obtained with DenseSparseMetric.getVectorConstant(jsat.linear.Vec)

main - the main vector the summary constant is for

target - the target vector to compute the distance to

Returns:

the distance between the two vectors dist(main, target)

supportsAcceleration

public boolean supportsAcceleration()

Description copied from interface: DistanceMetric

Indicates if this distance metric supports building an acceleration cache using the DistanceMetric.getAccelerationCache(java.util.List) and associated distance methods. By default this method will return false. If true, then a cache can be obtained from this distance metric and used in conjunction with DistanceMetric.dist(int, jsat.linear.Vec, java.util.List, java.util.List) and DistanceMetric.dist(int, int, java.util.List, java.util.List) to perform distance computations.

Specified by:

supportsAcceleration in interface DistanceMetric

Returns:

true if cache acceleration is supported for this metric, false otherwise.

getAccelerationCache

public List<Double> getAccelerationCache(List<? extends Vec> vecs)

Description copied from interface: DistanceMetric

Returns a cache of double values associated with the given list of vectors in the given order. This can be used by the distance metric to increase runtime at the cost of memory. This is an optional method.
If this metric does not support acceleration, null will be returned.

Specified by:

getAccelerationCache in interface DistanceMetric

Parameters:

vecs - the list of vectors to build an acceleration cache for

Returns:

the list of double for the cache

dist

public double dist(int a,
                   int b,
                   List<? extends Vec> vecs,
                   List<Double> cache)

Description copied from interface: DistanceMetric

Computes the distance between 2 vectors in the original list of vectors.
If the cache input is null, then DistanceMetric.dist(jsat.linear.Vec, jsat.linear.Vec) will be called directly.

Specified by:

dist in interface DistanceMetric

Parameters:

a - the index of the first vector

b - the index of the second vector

vecs - the list of vectors used to build the cache

cache - the cache associated with the given list of vectors

Returns:

the distance between the two vectors

dist

public double dist(int a,
                   Vec b,
                   List<? extends Vec> vecs,
                   List<Double> cache)

Description copied from interface: DistanceMetric

Computes the distance between one vector in the original list of vectors with that of another vector not from the original list.
If the cache input is null, then DistanceMetric.dist(jsat.linear.Vec, jsat.linear.Vec) will be called directly.

Specified by:

dist in interface DistanceMetric

Parameters:

a - the index of the vector in the cache

b - the other vector

vecs - the list of vectors used to build the cache

cache - the cache associated with the given list of vectors

Returns:

the distance between the two vectors

getQueryInfo

public List<Double> getQueryInfo(Vec q)

Description copied from interface: DistanceMetric

Pre computes query information that would have be generated if the query was a member of the original list of vectors when calling DistanceMetric.getAccelerationCache(java.util.List) . This can then be used if a large number of distance computations are going to be done against points in the original set for a point that is outside the original space.

If this metric does not support acceleration, null will be returned.

Specified by:

getQueryInfo in interface DistanceMetric

Parameters:

q - the query point to generate cache information for

Returns:

the cache information for the query point

getAccelerationCache

public List<Double> getAccelerationCache(List<? extends Vec> vecs,
                                         ExecutorService threadpool)

Description copied from interface: DistanceMetric

Returns a cache of double values associated with the given list of vectors in the given order. This can be used by the distance metric to increase runtime at the cost of memory. This is an optional method.
If this metric does not support acceleration, null will be returned.

Specified by:

getAccelerationCache in interface DistanceMetric

Parameters:

vecs - the list of vectors to build an acceleration cache for

threadpool - source of threads for parallel computation of result. This may be null, which means the singled threaded version may be used.

Returns:

the list of double for the cache

dist

public double dist(int a,
                   Vec b,
                   List<Double> qi,
                   List<? extends Vec> vecs,
                   List<Double> cache)

Description copied from interface: DistanceMetric

Computes the distance between one vector in the original list of vectors with that of another vector not from the original list, but had information generated by DistanceMetric.getQueryInfo(jsat.linear.Vec).
If the cache input is null, then DistanceMetric.dist(jsat.linear.Vec, jsat.linear.Vec) will be called directly.

Specified by:

dist in interface DistanceMetric

Parameters:

a - the index of the vector in the cache

b - the other vector

qi - the query information about b

vecs - the list of vectors used to build the cache

cache - the cache associated with the given list of vectors

Returns:

the distance between the two vectors