% 2005/06/21.
% copied from jc_llhood_ratio_fa_multi, this version
% gives the loglikelihood of a single BN.
% _multi_ because it
% looks for the frequency of data at the last argument of data/n.
% :- requires( bims:kv_compose/3 ).
% :- requires( bims:kvs_insert/4 ).
:- ensure_loaded( 'src/kv_compose' ).
:- ensure_loaded( 'src/kvs_insert' ).
:- ensure_loaded( 'src/kvs_replace_v_or_insert' ).
% note currently the code assumes nodes are represented by 1...n, natural numbers.
% Nicos, 2005/05/21, could we store OldContrib ?
% Nicos, 2004/10/18.
scm_rel_likelihood( NewFamily, OldFamily, RelL ) :-
llhood_family_contrib( NewFamily, NewContrib ),
llhood_family_contrib( OldFamily, OldContrib ),
RelL is exp(NewContrib - OldContrib).
% end of Nicos' code and comments.
/*
>From jc@cs.york.ac.uk Tue Mar 6 15:53:27 2001
Date: Tue, 6 Mar 2001 11:31:49 GMT
From: jc@cs.york.ac.uk
To: nicos@cs.york.ac.uk
*/
/***********************************************************************
Written Tue Mar 6 11:19:36 GMT 2001
Only llhood_ratio/3 is called from outside
This computes the log of the likelihood ratio of 2 BNs
BNs look like this:
bn(1,[1-[5],2-[],3-[1,5],4-[2],5-[4]]).
bn(2,[1-[5],2-[1,5],3-[4],4-[1],5-[]]).
bn(3,[1-[2,5],2-[5],3-[1,4,5],4-[1,5],5-[]]).
Data (not in this file) looks like this:
data(0,0,1,1,0,1,1,0).
Only works for data in data/8 format
***********************************************************************/
:- use_module(library(ugraphs)).
:- use_module(library(lists)).
:- bims:pl( swi(_), true, use_module(library(terms)) ).
:- use_module(library(ordsets)).
% :- dynamic cached_family_contrib/2.
% :- dynamic cached_family_contrib/3.
% :- user:datafile( Data ),
% user:write( using_data(Data) ), nl,
% compile( Data ).
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%START COMPUTATION OF LOG OF LIKELIHOOD RATIO%%%%%%%%%%%%%%%%%%%%%%%%%
/*---------------------------------------------------------------------
Predicate: llhood_ratio(+BN1,+BN2,-LogofRatio)
Args: BN1 = Bayesian net as a list of familiies
BN2 = Bayesian net as a list of familiies
LogofRatio = log(P(data|BN1)/P(data|BN2))
Succeeds: 1
Comments: This is a function
---------------------------------------------------------------------*/
llhood_ratio(BN1,BN2,LogofRatio) :-
llhood_ratio(BN1,BN2,0,LogofRatio).
/*---------------------------------------------------------------------
Predicate: llhood_ratio(+BN1,+BN2,+Acc,-LogofRatio)
Args: BN1 = Bayesian net as a list of familiies
BN2 = Bayesian net as a list of familiies
Acc = accumulator
LogofRatio = Acc + log(P(data|BN1)/P(data|BN2))
Succeeds: 1
Comments: This is a function
if families are identical then both cancel out, and can be ignored
---------------------------------------------------------------------
Nicos: 2005/06/21, added
*/
llhood_ratio([],[],L,[],L).
llhood_ratio([Child-Parents|Rest1],[Child-Parents+Family_Contrib|Rest2],In,StLStr,Out) :- %identical families
!,
StLStr = [Child-Parents+Family_Contrib|RestLStr],
llhood_ratio(Rest1,Rest2,In,RestLStr,Out).
llhood_ratio([Family1|Rest1],[_Family2+Family_Contrib2|Rest2],In,StLStr,Out) :-
llhood_family_contrib(Family1,Family_Contrib1),
% llhood_family_contrib(Family2,Family_Contrib2),
Mid is In + Family_Contrib1 - Family_Contrib2,
StLStr = [Family1+Family_Contrib1|RestLStr],
llhood_ratio(Rest1,Rest2,Mid,RestLStr,Out).
/*---------------------------------------------------------------------
Predicate: llhood_family_contrib(+Family,-Contrib)
Args: Family = Child-[Parent1,Parent2,...]
Contrib = Family's contribution to the log-likelihood
Succeeds: 1
Comments: Computes the 'score' for each family
ie its contribution to the log-likelihood
Either grab cached value or compute it
This is a function
---------------------------------------------------------------------*/
% :- ensure_loaded( llhood_family_contrib_direct_enc ).
llhood_family_contrib(Family,Contrib) :-
% term_hash(Family,HashValue),
% (
% cached_family_contrib(HashValue,Family,Contrib) ->
% true ;
counts_for_family(Family,ChildCountsList),
compute_llhood_family_contrib(ChildCountsList,Family,0,Contrib).
% assert(cached_family_contrib(HashValue,Family,Contrib))
% ).
%Fri Sep 24 10:29:18 BST 2004 debugging jc
% write(counts_for_family(Family,ChildCountsList)),nl,
% write(compute_llhood_family_contrib(ChildCountsList,Family,0,Contrib)),nl,nl.
/*---------------------------------------------------------------------
Predicate: cached_family_contrib(+Family,-Contrib)
Args: Family = Child-[Parent1,Parent2,...]
Contrib = Family's contribution to the log-likelihood
Succeeds: 1
Comments: Caches scores for future retreival
No definition, it gets asserted!
---------------------------------------------------------------------*/
%%%%%%%%%%%%%%%%%%%%%%%%%%%%END COMPUTATION OF LOG OF LIKELIHOOD RATIO
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%START PREDICATES FOR GETTING COUNTS%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
/*---------------------------------------------------------------------
Predicate: counts_for_family(+Family,-ChildCountsList)
Args: Family = Child-[Parent1,Parent2,...]
ChildCountsList = for each configuration of the parents
a list of labelled counts for child
Succeeds: 1
Comments: This is a function
Each element of ChildCountsList is something like [1-20,2-30,3-50]-[1,3]
Child counts are for Parent1=1, Parent2=3
[1-20,2-30,3-50] means that the child took value=1 20 times, etc
---------------------------------------------------------------------*/
% Change 3.
counts_for_family(Child-Parents,ChildCountsList) :-
% Goal = data(_,_,_,_,_,_,_,_),
%%% data_format( _TheGoal, _Last ),
% no arg/3 version.
%% kv_compose( [Child,Last|Parents], [ChildVar,Tms|PVars], Comp ),
kv_compose( Parents, PaVars, PKVs ),
%%% Nicos 2005/06/22, keysort is wasteful if Parents are sorted.
% keysort( Comp, SortOfInterest ),
kvs_insert( PKVs, Child, ChVar, SortOfInterest ),
pairs_with_var_list( SortOfInterest, 1, ArgsList ),
%%% bb_get( multi_data_format, Goal ),
%% Goal =.. [data,ArgsList,Tms],
Goal = data(ArgsList,Tms),
%% bind([TmsPos,Child|Parents],Goal,[Tms,ChildVar|PVars]),
% arg( 1, Goal, VarsArg ),
% arg( 2, Goal, Tms ),
% ord_add_element( Parents, Child, SortedFamily ),
% bind_list( SortedFamily, VarsArg, 1, [ChVar|PaVars] ),
% arg( Last, Goal, Tms ),
findall(PaVars-(ChVar,Tms),data:Goal,Instances), % constructs massive list
child_counts_split( Instances, ChildCountsList, [] ).
%%% keysort(Instances,SortedInstances), % order by values of parents
%%% child_counts_list(SortedInstances,[],ChildCountsList).
child_counts_split( [], Cont, Cont ).
child_counts_split( [PaVals-(ChVal,Tms)|T], [ChCounts-PaVals|TCnts], Cont ) :-
count_pvals_and_split( T, PaVals, [ChVal-Tms], ChCounts, L, R ),
child_counts_split( L, TCnts, LCont ),
child_counts_split( R, LCont, Cont ).
count_pvals_and_split( [], _SeenVals, ChCounts, ChCounts, [], [] ).
count_pvals_and_split( [TheseVals-(ChVal,Tms)|T], SeenVals, SoFar, ChCounts, L, R ) :-
compare( Op, TheseVals, SeenVals ),
( Op == (=) ->
kvs_replace_v_or_insert( SoFar, ChVal, Old, New, ThusFar ),
% ( Old == null__ -> )
( Old == [] ->
New is Tms
;
New is Old + Tms
),
TailL = L, TailR = R
;
ThusFar = SoFar,
( Op == (<) ->
L = [TheseVals-(ChVal,Tms)|TailL],
TailR = R
;
TailL = L,
R = [TheseVals-(ChVal,Tms)|TailR]
)
),
count_pvals_and_split( T, SeenVals, ThusFar, ChCounts, TailL, TailR ).
pairs_with_var_list( [], _, _ ).
% pairs_with_var_list( [], _, [] ). % this is only valid if last arg of data
% is known to be in first argument list.
pairs_with_var_list( [K-V|T], N, AList ) :-
( K =:= N ->
AList = [V|TAList], R = T
;
AList = [_|TAList], R = [K-V|T]
),
NxN is N + 1,
pairs_with_var_list( R, NxN, TAList ).
bind_list( [], _List, _CurrPos, [] ).
bind_list( [Hpos|Tpos], [H|T], CurrPos, [Hplace|Tplaces] ) :-
( Hpos =:= CurrPos ->
Hplace = H,
Rpos = Tpos,
Rplaces = Tplaces
;
Rpos = [Hpos|Tpos],
Rplaces = [Hplace|Tplaces]
),
NxPos is CurrPos + 1,
bind_list( Rpos, T, NxPos, Rplaces ).
/*---------------------------------------------------------------------
Predicate: bind(+ArgPositions,?Term,+TermList)
Args: ArgPositions = list of argument positions
Term = any term
TermList = list of subterms of Term
Succeeds: 1 (unless ArgPositions has an arg outside arity of Term, then fail)
Comments: This is a function
Yanks out relevant arguments from Goal and puts them in TermList
---------------------------------------------------------------------*/
bind([],_Goal,[]).
bind([H|T],Goal,[H1|T1]) :-
arg(H,Goal,H1),
bind(T,Goal,T1).
/*---------------------------------------------------------------------
Predicate: child_counts_list(+SortedInstances,+SoFar,-ChildCountsList)
Args: SortedInstances = sorted instances of a family
SoFar = accumulator for counts
ChildCountsList = list of counts for child, one per parent configuration
Succeeds: 1
Comments: This is a function
Each element of ChildCountsList is something like [1-20,2-30,3-50]-[1,3]
Child counts are for Parent1=1, Parent2=3
[1-20,2-30,3-50] means that the child took value=1 20 times, etc
---------------------------------------------------------------------*/
child_counts_list([],ChildCountsList,ChildCountsList).
child_counts_list([PVals-ChildVal|T],SoFar,ChildCountsList) :-
child_counts([PVals-ChildVal|T],PVals,[],ChildCounts,Rest),
child_counts_list(Rest,[ChildCounts-PVals|SoFar],ChildCountsList).
/*---------------------------------------------------------------------
Predicate: child_counts(+SortedInstances,+PVals,+SoFar,-ChildCounts,-Rest)
Args: SortedInstances = sorted instances of a family
PVals = parent configuration
SoFar = accumulator for counts
ChildCounts = list of counts for child, for the PVals parent configuration
Rest = Counts for other parent configurations
Succeeds: 1
Comments: This is a function
---------------------------------------------------------------------*/
child_counts([PVals-(ChildVal,Tms)|T],PVals,Sofar,Out,Rest) :- %got a PVals match
% child_counts([PVals-ChildVal|T],PVals,Sofar,Out,Rest) :- %got a PVals match
!,
(
select(ChildVal-Count,Sofar,Residue) -> %if seen this ChildVal before
%n C is Count + 1, %increment count
C is Count + Tms, %increment count
NewSofar = [ChildVal-C|Residue] ; %put back
NewSofar = [ChildVal-Tms|Sofar] %else start the count for this ChildVal
% NewSofar = [ChildVal-1|Sofar] %else start the count for this ChildVal
),
child_counts(T,PVals,NewSofar,Out,Rest).
child_counts(L,_PVals,Out,Out,L). %match failed, we're done with this PVals
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%END PREDICATES FOR GETTING COUNTS
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%START COMPUTATION OF FAMILY LOG-LIKELIHOOD%%%%%%%%%%%%%%%%%%%%%%%%%%%
/*---------------------------------------------------------------------
Predicate: compute_llhood_family_contrib(+ChildCountsList,+Family,+In,-Out)
Args: ChildCountsList = list of counts for child, one per parent configuration
Family = ChildName-List of parent names
In = accumulator input, initially 0
Out = 'score' for the family
Succeeds: 1
Comments: This is a function
Each element of ChildCountsList is something like [1-20,2-30,3-50]-[1,3]
Child counts are for Parent1=1, Parent2=3
[1-20,2-30,3-50] means that the child took value=1 20 times, etc
middle loop of Heckerman's (32)
Altered: Fri Sep 24 11:43:33 BST 2004
to add calls to possible_values/2 and fix_counts/3
possible_values/2 is assumed to defined elsewhere.
---------------------------------------------------------------------*/
compute_llhood_family_contrib([],_Family,Out,Out).
compute_llhood_family_contrib([ChildVals-ParentVals|T],Family,In,Out) :-
Family = Child-_Parents,
data:possible_values(Child,PossibleValues), % defined elsewhere
fix_counts(PossibleValues,ChildVals,FixedChildVals),
config_contrib(FixedChildVals,Family,ParentVals,In,0,0,Mid),
compute_llhood_family_contrib(T,Family,Mid,Out).
/*---------------------------------------------------------------------
Predicate: fix_counts(+PossibleValues,+ChildVals,-FixedChildVals)
Args: PossibleValues = labelled counts for the child
ChildVals = labelled counts for the child
FixedChildVals = labelled counts for every possible value of the child
Succeeds: 1
Comments: Adds explicit zero count if missing. A hack for quick debugging.
Added by JC Fri Sep 24 11:43:05 BST 2004
---------------------------------------------------------------------*/
/* Nicos 20051124, a more steadfast version. We make sure all child vals
are in PossValue.
*/
fix_counts([],ChildVals,[]) :-
( ChildVals == [] -> true ;
throw( impossible_child_values(ChildVals) ) ).
fix_counts([PossValue|T],ChildVals,[PossValue-FixedCount|Rest]) :-
( bims:nth(_,ChildVals,PossValue-Count,RemChildVals) ->
FixedCount=Count
;
RemChildVals = ChildVals,
FixedCount is 0
),
fix_counts(T,RemChildVals,Rest).
/* James' version, pre 20051124:
fix_counts([],_ChildVals,[]).
fix_counts([PossValue|T],ChildVals,[PossValue-FixedCount|Rest]) :-
(
member(PossValue-Count,ChildVals)
->
FixedCount=Count
;
FixedCount=0
),
fix_counts(T,ChildVals,Rest).
*/
/*---------------------------------------------------------------------
Predicate: config_contrib(+ChildVals,+Family,+ParentVals,+In,+AIn,+ANIn,-Out)
Args: ChildVals = labelled counts for the child
Family = names of child and parents
ParentVals = the values of the parents for this configuration
In = main accumulator input
AIn = accumulator for Alpha_ij
ANIn = accumulator for Alpha_ijplusN_ij
Out = the result!
Succeeds: 1
Comments: This is a function
inner loop of Heckerman's (32)
Suppose variable x has parents y and z and when y=1,z=3 the counts for x are
x=1 20 times, x=2 30 times and x=3 50 times, then goal would be:
config_contrib([1-20,2-30,3-50],x-[y,z],[1,3]In,0,0,Out)
we just add two accumulators for the sum of alphas and sum of alphas+counts
---------------------------------------------------------------------*/
config_contrib([],_Family,_ParentVals,In,Alpha_ij,Alpha_ijplusN_ij,Out) :-
/* logamma(Alpha_ij,Tmp),
logamma(Alpha_ijplusN_ij,Tmp2),
Out is Tmp - Tmp2 + In. */
Out is lgamma(Alpha_ij) - lgamma(Alpha_ijplusN_ij) + In.
config_contrib([ChildVal-N_ijk|T],Family,ParentVals,In,AIn,ANIn,Out) :-
alpha(Family,ChildVal,ParentVals,Alpha_ijk),
Tmp is N_ijk + Alpha_ijk,
/* logamma(Tmp,Tmp2),
logamma(Alpha_ijk,Tmp3),
Mid is In + Tmp2 - Tmp3,
*/
Mid is In + lgamma(Tmp) + lgamma(Alpha_ijk),
AMid is AIn + Alpha_ijk,
ANMid is ANIn + Tmp,
config_contrib(T,Family,ParentVals,Mid,AMid,ANMid,Out).
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%END COMPUTATION OF FAMILY LOG-LIKELIHOOD
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%START DEFINITION OF PARAMETER PRIORS%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% Now in alpha_xxx.pl files
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% END DEFINITION OF PARAMETER PRIORS
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
/**********************************************************************
NOT USED
NOT USED
NOT USED
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% START COMPUTATION OF LIKELIHOOD
%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
llhood(BN,L) :-
llhood(BN,0,L).
% for each family
% does outermost loop of Heckerman's (32)
llhood([],L,L).
llhood([Family|Families],In,Out) :-
llhood_family_contrib(Family,Family_Contrib), %this is the 'score' for this family
Mid is In + Family_Contrib,
llhood(Families,Mid,Out).
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% END COMPUTATION OF LIKELIHOOD
%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
**********************************************************************/