mml

Class MotifD.M

java.lang.Object

la.la.Value

mml.Model

mml.UPModel.M

mml.Graphs.M

mml.Graphs.Motifs.M

mml.MotifD.M

All Implemented Interfaces:

java.lang.Comparable<Value>

Enclosing class:

MotifD

public class MotifD.M
extends Graphs.Motifs.M

The fully parameterised MotifD Model of Graphs. See mdlV, mdlE, motifs and nlPr(g). The UnParameterised Model is MotifD. Also see MotifA.M.

Nested Class Summary

Nested classes/interfaces inherited from class mml.Model

Model.Defaults, Model.Transform

Nested classes/interfaces inherited from class la.la.Value

Value.Atomic, Value.Bool, Value.Char, Value.Chars, Value.Cts, Value.Defer, Value.Discrete, Value.Enum, Value.Inc_Or, Value.Int, Value.Lambda, Value.List, Value.Maybe, Value.Option, Value.Real, Value.Scannable, Value.Structured, Value.Triv, Value.Tuple

Field Summary

Fields

Modifier and Type	Field and Description
Discretes.Bounded.M	mdlE The fully parameterised (Adaptive) Model of that part of the Adjacency Matrix not covered by instances of motifs[.].
protected Graph[]	motifs The motifs (patterns, templates), sorted on |V|, that can be used to compress a given Graph.
int	sgMaxV |V| for the smallest and largest of the motifs[.].
int	sgMinV |V| for the smallest and largest of the motifs[.].

Fields inherited from class mml.Graphs.M

mdlV

Fields inherited from class mml.Model

msg1, msg2, sp

Fields inherited from class la.la.Value

C, comparator, CR, E, eight, ffalse, five, fiveR, four, fourR, half, negCR, negOne, negOneR, negTenR, nilVal, nine, None, one, oneR, PI, PIby2, point01, point1, point5, point9, quarter, seven, six, ten, tenR, three, threeR, triv, ttrue, two, twoR, zero, zeroR

Constructor Summary

Constructors

Constructor and Description
M(double msg1, double msg2, Value sp) sp = ⟨spmdlV, motifs⟩.

Method Summary

Modifier and Type	Method and Description
Graph[]	motifs() Returns motifs[]; see Graphs.Motifs.M.motifs().
double	nlLH(Value ss) ss = stats(ds,lo,hi), requires that ss is ds, the Vector (data-set) of Graphs itself.
double	nlPr(Value G) The negative log probability of datum (Graph) G.
Graph	random() Generate a random Graph according to 'this' Model.

Methods inherited from class mml.Graphs.Motifs.M

msgMotifs, msgMotifs

Methods inherited from class mml.Graphs.M

mdlV

Methods inherited from class mml.UPModel.M

asGiven, asGiven, stats, stats, toString

Methods inherited from class mml.Model

asEstimator, asUPModel, m1m2sp, msg, msg1, msg1bits, msg2, msg2bits, msgBits, nl2LH, nl2Pr, pr, random, randomSeries, statParams, stats, stats, sumNlPr, transform, type, zeroTriv

Methods inherited from class la.la.Value

AoM, apply, bOp, compareTo, cons, cts, elt, errMsg, error, force, isTuple, just, main, n, nElts, nlAoM, pair, print, quad, real, RTE, triple, tuple, UOE, uOp, x

Methods inherited from class java.lang.Object

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

Field Detail

mdlE

public final Discretes.Bounded.M mdlE

The fully parameterised (Adaptive) Model of that part of the Adjacency Matrix not covered by instances of motifs[.]. Also see MotifD.upmE.

motifs

protected final Graph[] motifs

The motifs (patterns, templates), sorted on |V|, that can be used to compress a given Graph. There will be good compression if there are many instances of motifs[.] in the Graph. The motifs may be "given" or estimated.

sgMinV

public final int sgMinV

|V| for the smallest and largest of the motifs[.]. Also see the different MotifD.sgMinV and sgMaxV.

sgMaxV

public final int sgMaxV

|V| for the smallest and largest of the motifs[.]. Also see the different MotifD.sgMinV and sgMaxV.

Constructor Detail

M

public M(double msg1,
         double msg2,
         Value sp)

sp = ⟨sp_mdlV, motifs⟩.

Method Detail

motifs

public Graph[] motifs()

Returns motifs[]; see Graphs.Motifs.M.motifs().

Specified by:

motifs in class Graphs.Motifs.M

nlLH

public double nlLH(Value ss)

ss = stats(ds,lo,hi), requires that ss is ds, the Vector (data-set) of Graphs itself.

Overrides:

nlLH in class Graphs.M

nlPr

public double nlPr(Value G)

The negative log probability of datum (Graph) G. Any two instances may not share any Vertices of G.

Specified by:

nlPr in class Model

random

public Graph random()

Generate a random Graph according to 'this' Model.

Overrides:

random in class Graphs.M