mml

Class MotifA

java.lang.Object

la.la.Value

la.la.Function

la.la.Function.Native

mml.UPModel

mml.Graphs

mml.Graphs.Motifs

mml.MotifA

All Implemented Interfaces:

java.lang.Comparable<Value>

public class MotifA
extends Graphs.Motifs

'MotifA', the UnParameterised adaptive Motif Model of' Graphs. The fully parameterised Model is MotifA.M. Also see MotifD.

Nested Class Summary

Nested Classes

Modifier and Type	Class and Description
class	MotifA.M The fully parameterised MotifA Model of Graphs.

Nested classes/interfaces inherited from class mml.Graphs

Graphs.GERadaptive, Graphs.GERfixed, Graphs.IndependentEdges, Graphs.Motifs, Graphs.Skewed

Nested classes/interfaces inherited from class mml.UPModel

UPModel.Est, UPModel.Transform

Nested classes/interfaces inherited from class la.la.Function.Native

Function.Native.WithInverse

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

Function.Cts2Cts, Function.Cts2Cts2Cts, Function.CtsD2CtsD, Function.HasInverse, Function.Native, Function.Native2, Function.Native3

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
int	sgMaxV Bounds [sgMinV, sgMaxV] on |V| for the motifs (patterns) that the estimator will search for (but not necessarily find).
int	sgMinV Bounds [sgMinV, sgMaxV] on |V| for the motifs (patterns) that the estimator will search for (but not necessarily find).
Discretes.Bounded	upmE The UnParameterised (Adaptive) background Model over the existence of possible Edges outside instances of motifs.

Fields inherited from class mml.Graphs.Motifs

mdlMotif, mdlNmotifs, verbosity

Fields inherited from class mml.Graphs

gType, upmV

Fields inherited from class mml.UPModel

dp

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
MotifA(Value dp) Problem definition parameters dp = ⟨gType, upmV, ⟨sgMinV, sgMaxV⟩⟩.

Method Summary

Modifier and Type	Method and Description
UPModel.Est	estimator(Value ps) Return an Estimator for a Motif Model.
MotifA.M	sp2Model(double msg1, double msg2, Value sp) Return a fully parameterised MotifA Model.
Vector	stats(boolean add, Value ss0, Value ss1) Combine sufficient statisticses 'ss0' and 'ss1' additively (add=true), or remove ss1 from ss0 (add=false).
Vector	stats(Vector ds, int lo, int hi) Sufficient statistics are elements [lo, hi) of the data-set ds itself.

Methods inherited from class mml.Graphs.Motifs

greedy, greedy, msgMotifs, msgMotifs

Methods inherited from class mml.Graphs

ds2mdlV, gType, upmV, vStats

Methods inherited from class mml.UPModel

apply, defnParams, main, stats, stats, toString, transform

Methods inherited from class la.la.Function

bOp, fromBop, fromUop, type, uOp

Methods inherited from class la.la.Value

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

Methods inherited from class java.lang.Object

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

Field Detail

upmE

public final Discretes.Bounded upmE

The UnParameterised (Adaptive) background Model over the existence of possible Edges outside instances of motifs. Also see mdlE.

sgMinV

public final int sgMinV

Bounds [sgMinV, sgMaxV] on |V| for the motifs (patterns) that the estimator will search for (but not necessarily find). Also see mdlMotif.

sgMaxV

public final int sgMaxV

Bounds [sgMinV, sgMaxV] on |V| for the motifs (patterns) that the estimator will search for (but not necessarily find). Also see mdlMotif.

Constructor Detail

MotifA

public MotifA(Value dp)

Problem definition parameters dp = ⟨gType, upmV, ⟨sgMinV, sgMaxV⟩⟩.

Method Detail

stats

public Vector stats(Vector ds,
                    int lo,
                    int hi)

Sufficient statistics are elements [lo, hi) of the data-set ds itself.

Overrides:

stats in class Graphs

stats

public Vector stats(boolean add,
                    Value ss0,
                    Value ss1)

Description copied from class: UPModel

Combine sufficient statisticses 'ss0' and 'ss1' additively (add=true), or remove ss1 from ss0 (add=false). Also see stats(ds,lo,hi).

Overrides:

stats in class Graphs

sp2Model

public MotifA.M sp2Model(double msg1,
                         double msg2,
                         Value sp)

Return a fully parameterised MotifA Model.

Specified by:

sp2Model in class Graphs.Motifs

estimator

public UPModel.Est estimator(Value ps)

Return an Estimator for a Motif Model. Parameters 'ps' are for upmV.estimator(ps). Estimating mdlV is standard but finding good motifs is hard so heuristics are used. The time complexity should be approximately O(#G.V.d^sgMaxV-1), given a data-set of #G Graphs of average size V and average degree d.

Overrides:

estimator in class UPModel