Rework the learning examples

packages/CLPBN/examples/School/parschema.yap

@@ -6,17 +6,21 @@ bayes abi(K)::[h,m,l] ; abi_table ; [professor(K)].
 
 bayes pop(K)::[h,m,l], abi(K) ; pop_table ; [professor(K)].
 
-bayes diff(C) :: [h,m,l] ; diff_table ; [course(C,_)].
+bayes diff(C)::[h,m,l] ; diff_table ; [course(C,_)].
 
-bayes int(S) :: [h,m,l] ; int_table ; [student(S)].
+bayes int(S)::[h,m,l] ; int_table ; [student(S)].
 
-bayes grade(C,S)::[a,b,c,d], int(S), diff(C) ; grade_table ; [registration(_,C,S)].
+bayes grade(C,S)::[a,b,c,d], int(S), diff(C) ;
+	grade_table ;
+	[registration(_,C,S)].
 
-bayes satisfaction(C,S)::[h,m,l], abi(P), grade(C,S) ; sat_table ; [reg_satisfaction(C,S,P)].
+bayes satisfaction(C,S)::[h,m,l], abi(P), grade(C,S) ;
+	sat_table ;
+	[reg_satisfaction(C,S,P)].
 
-bayes rat(C) :: [h,m,l], Sats ; avg ; [course_rat(C, Sats)].
+bayes rat(C)::[h,m,l], Sats ; avg ; [course_rat(C, Sats)].
 
-bayes rank(S) :: [a,b,c,d], Grades ; avg ; [student_ranking(S,Grades)].
+bayes rank(S)::[a,b,c,d], Grades ; avg ; [student_ranking(S,Grades)].
 
 
 grade(Key, Grade) :-
@@ -30,19 +34,27 @@ reg_satisfaction(CKey, SKey, PKey) :-
 course_rat(CKey, Sats) :-
 	course(CKey,  _),
 	setof(satisfaction(CKey,SKey),
-	   PKey^reg_satisfaction(CKey, SKey, PKey),
+		PKey^reg_satisfaction(CKey, SKey, PKey),
-          Sats).
+		Sats).
 
 student_ranking(SKey, Grades) :-
 	student(SKey),
-	setof(grade(CKey,SKey), RKey^registration(RKey,CKey,SKey), Grades).
+	setof(grade(CKey,SKey),
+		RKey^registration(RKey,CKey,SKey),
+		Grades).
 
 :- ensure_loaded(tables).
 
 % convert to longer names 
-professor_ability(P,A) :- abi(P, A).
+professor_ability(P,A) :- abi(P,A).
 
-professor_popularity(P,A) :- pop(P, A).
+professor_popularity(P,A) :- pop(P,A).
+
+course_difficulty(P,A) :- diff(P,A).
+
+student_intelligence(P,A) :- int(P,A).
+	
+course_rating(C,X) :- rat(C,X).
 
 registration_grade(R,A) :-
 	registration(R,C,S),
@@ -52,24 +64,14 @@ registration_satisfaction(R,A) :-
 	registration(R,C,S),
 	satisfaction(C,S,A).
 
-student_intelligence(P,A) :- int(P, A).
+registration_course(R,C) :- registration(R,C,_).
 
-course_difficulty(P,A) :- diff(P, A).
+registration_student(R,S) :- registration(R,_,S).
-
-
-registration_course(R,C) :-
-	registration(R, C, _).
-
-registration_student(R,S) :-
-	registration(R, _, S).
-
-course_rating(C,X) :- rat(C,X).
 
 %
-% evidence
+% Evidence
 %
 %abi(p0, h).
-
 %pop(p1, m).
 %pop(p2, h).
 

packages/CLPBN/examples/School/schema.yap

@@ -1,5 +1,4 @@
-
+/* Base file for school database. Supposed to be called from school_*.yap */
-/* base file for school database. Supposed to be called from school_*.yap */
 
 professor_key(Key) :-
 	professor(Key).
@@ -67,5 +66,3 @@ student_ranking(Key, Rank) :-
 
 :- ensure_loaded(tables).
 
-
-

packages/CLPBN/examples/School/school_64.yap

@@ -4702,5 +4702,3 @@ registration(r3457,c5,s1023).
 registration(r3458,c37,s1023).
 registration(r3459,c57,s1023).
 
-
-

packages/CLPBN/examples/School/tables.yap

@@ -1,30 +1,49 @@
 
-int_table(_,T ,[h, m, l]) :- int_table(T).
+abi_table(
+/* h */ [ 0.50,
+/* m */   0.40,
+/* l */   0.10 ]).
 
-int_table([0.5,
+abi_table(_, T) :- abi_table(T).
-	0.4,
-	0.1]).
 
-	   /* h h   h m  h l  m h  m m  m l  l h  l m l l */
+pop_table(
-grade_table([
+/*        h     m    l */
-             0.2,  0.7, 0.85, 0.1, 0.2, 0.5, 0.01, 0.05,0.1 ,
+/* h */ [ 0.9,  0.2, 0.01,
-	     0.6, 0.25, 0.12, 0.3, 0.6,0.35,0.04, 0.15, 0.4 ,
+/* m */   0.09, 0.6, 0.09,
-             0.15,0.04, 0.02, 0.4,0.15,0.12, 0.5, 0.6, 0.4,
+/* l */   0.01, 0.2, 0.9  ]).
-	     0.05,0.01, 0.01, 0.2,0.05,0.03, 0.45, 0.2, 0.1 ]).
+
+pop_table(_, T) :- pop_table(T). 
+
+diff_table(
+/* h */ [ 0.25,
+/* m */   0.50,
+/* l */   0.25 ]).
+
+dif_table(_, T) :- diff_table(T). 
+
+int_table(
+/* h */ [ 0.5,
+/* m */   0.4,
+/* l */   0.1 ]).
+
+int_table(_,T ,[h,m,l]) :- int_table(T).
+
+grade_table(
+/*        h h   h m   h l   m h  m m   m l   l h   l m   l l */
+/* a */ [ 0.2,  0.7,  0.85, 0.1, 0.2,  0.5,  0.01, 0.05, 0.1,
+/* b */   0.6,  0.25, 0.12, 0.3, 0.6,  0.35, 0.04, 0.15, 0.4,
+/* c */   0.15, 0.04, 0.02, 0.4, 0.15, 0.12, 0.5,  0.6,  0.4,
+/* d */   0.05, 0.01, 0.01, 0.2, 0.05, 0.03, 0.45, 0.2,  0.1 ]).
 
 grade_table(I, D, 
-	   /* h h   h m  h l  m h  m m  m l  l h  l m l l */
+	p([a,b,c,d], T, [I,D])) :- grade_table(T).
-	    p([a,b,c,d], T, [I,D])) :- grade_table(T).
     
 sat_table(
-       /*   h a  h b  h c   h d  m a   m b  m c  m d   l a   l b  l c  l d */
+/*        h a   h b   h c   h d  m a   m b  m c  m d   l a   l b  l c   l d */
-/*h*/     [0.98, 0.9, 0.8 , 0.6, 0.9,  0.4, 0.2, 0.01, 0.5,  0.2, 0.01, 0.01,
+/* h */ [ 0.98, 0.9,  0.8 , 0.6, 0.9,  0.4, 0.2, 0.01, 0.5,  0.2, 0.01, 0.01,
-/*m*/	   0.01, 0.09,0.15, 0.3, 0.05, 0.4, 0.3, 0.04, 0.35, 0.3, 0.09, 0.01 ,
+/* m */   0.01, 0.09, 0.15, 0.3, 0.05, 0.4, 0.3, 0.04, 0.35, 0.3, 0.09, 0.01,
-/*l*/	   0.01, 0.01,0.05, 0.1, 0.05, 0.2, 0.5, 0.95, 0.15, 0.5, 0.9,  0.98]).	
+/* l */   0.01, 0.01, 0.05, 0.1, 0.05, 0.2, 0.5, 0.95, 0.15, 0.5, 0.9,  0.98 ]).
-/*
+
-  A: professor's ability;
-  B: student's grade (for course registration).
-*/
 satisfaction_table(A, G, p([h,m,l], T, [A,G])) :- sat_table(T).
 
 
@@ -35,22 +54,8 @@ satisfaction_table(A, G, p([h,m,l], T, [A,G])) :- sat_table(T).
 %
 % add all and divide on the number of elements on the table!
 %
-rating_prob_table([0.9,0.05,0.01,
+rating_prob_table(
-		   0.09,0.9,0.09,
+  [ 0.9,  0.05, 0.01,
-		   0.01,0.05,0.9]).
+    0.09, 0.9,  0.09,
-
+    0.01, 0.05, 0.9  ]).
-abi_table( [0.50, 0.40,  0.10]).
-
-abi_table( _, T) :- abi_table(T).
-
-
-pop_table( [0.9, 0.2, 0.01,
-           0.09, 0.6, 0.09,
-           0.01, 0.2, 0.9]).
-
-pop_table(_, T) :- pop_table(T). 
-
-diff_table([0.25, 0.50, 0.25]).
-
-dif_table(_, T) :- diff_table(T). 
 

packages/CLPBN/examples/learning/prof_params.pfl

@@ -1,21 +1,31 @@
-% learn distribution for school database.
+/* Learn distribution for professor database. */
 
 :- use_module(library(pfl)).
 
 :- use_module(library(clpbn/learning/em)).
 
+%:- clpbn:set_clpbn_flag(em_solver,gibbs).
+%:- clpbn:set_clpbn_flag(em_solver,jt).
+%:- clpbn:set_clpbn_flag(em_solver,hve).
+:- clpbn:set_clpbn_flag(em_solver,ve).
+%:- clpbn:set_clpbn_flag(em_solver,bp).
+%:- clpbn:set_clpbn_flag(em_solver,bdd).
+
 bayes abi(K)::[h,m,l] ; abi_table ; [professor(K)].
 
 bayes pop(K)::[h,m,l], abi(K) ; pop_table ; [professor(K)].
 
-abi_table([0.3,0.3,0.4]).
+abi_table([0.3, 0.3, 0.4]).
 
-pop_table([0.3,0.3,0.4,0.3,0.3,0.4,0.3,0.3,0.4]).
+pop_table([0.3, 0.3, 0.4, 0.3, 0.3, 0.4, 0.3, 0.3, 0.4]).
 
-goal_list([/*abi(p0,h),
+goal_list([
+/*
+	abi(p0,h),
 	abi(p1,m),
 	abi(p2,m),
-	abi(p3,m),*/
+	abi(p3,m),
+*/
 	abi(p4,l),
 	pop(p5,h),
 	abi(p5,_),
@@ -32,13 +42,6 @@ professor(p6).
 professor(p7).
 professor(p8).
 
-%:- clpbn:set_clpbn_flag(em_solver,gibbs).
-%:- clpbn:set_clpbn_flag(em_solver,jt).
-:- clpbn:set_clpbn_flag(em_solver,hve).
-:- clpbn:set_clpbn_flag(em_solver,ve).
-%:- clpbn:set_clpbn_flag(em_solver,bp).
-%:- clpbn:set_clpbn_flag(em_solver,bdd).
-
 timed_main :-
 	statistics(runtime, _),
 	main(Lik),
@@ -47,13 +50,5 @@ timed_main :-
 
 main(Lik) :-
 	goal_list(L),
-%	run_queries(L),
+	em(L,0.01,10,_,Lik).
-        em(L,0.01,10,_,Lik).
-
-run_queries([]).
-run_queries(Q.L) :-
-	call(Q),
-	run_queries(L).
-
-
 

packages/CLPBN/examples/learning/sprinkler_params.yap

@@ -1,9 +1,16 @@
-% learn distribution for school database.
+/* Learn distribution for a sprinkler database. */
 
 :- ['../sprinkler.pfl'].
 
 :- use_module(library(clpbn/learning/em)).
 
+%:- clpbn:set_clpbn_flag(em_solver,gibbs).
+%:- clpbn:set_clpbn_flag(em_solver,jt).
+%:- clpbn:set_clpbn_flag(em_solver,hve).
+:- clpbn:set_clpbn_flag(em_solver,bdd).
+%:- clpbn:set_clpbn_flag(em_solver,bp).
+%:- clpbn:set_clpbn_flag(em_solver,ve).
+
 data(t,t,t,t).
 data(_,t,_,t).
 data(t,t,f,f).
@@ -18,12 +25,7 @@ data(t,t,_,f).
 data(t,f,f,t).
 data(t,f,t,t).
 
-%:- clpbn:set_clpbn_flag(em_solver,gibbs).
+:- dynamic id/1.
-%:- clpbn:set_clpbn_flag(em_solver,jt).
-:- clpbn:set_clpbn_flag(em_solver,hve).
-:- clpbn:set_clpbn_flag(em_solver,bdd).
-%:- clpbn:set_clpbn_flag(em_solver,bp).
-%:- clpbn:set_clpbn_flag(em_solver,ve).
 
 timed_main :-
 	statistics(runtime, _),
@@ -33,19 +35,16 @@ timed_main :-
 
 main(Lik) :-
 	findall(X,scan_data(X),L),
-        em(L,0.01,10,_,Lik).
+	em(L,0.01,10,_,Lik).
 
 scan_data(I:[wet_grass(W),sprinkler(S),rain(R),cloudy(C)]) :-
 	data(W, S, R, C),
 	new_id(I).
 
-:- dynamic id/1.
-
 new_id(I) :-
-    retract(id(I)),
+	retract(id(I)),
-    I1 is I+1,
+	I1 is I+1,
-    assert(id(I1)).
+	assert(id(I1)).
 
 id(0).
 
-

packages/CLPBN/examples/social_domain2.pfl

@@ -20,17 +20,17 @@ people(X,Y) :-
     people(Y).
 %    X \== Y.
 
-markov smokes(X); [1.0, 4.0552]; [people(X)].
+markov smokes(X) ; [1.0, 4.0552]; [people(X)].
 
-markov asthma(X); [1.0, 9.9742] ; [people(X)].
+markov asthma(X) ; [1.0, 9.9742] ; [people(X)].
 
-markov friends(X,Y); [1.0, 99.48432] ; [people(X,Y)].
+markov friends(X,Y) ; [1.0, 99.48432] ; [people(X,Y)].
 
-markov asthma(X), smokes(X);
+markov asthma(X), smokes(X) ;
     [4.48169, 4.48169, 1.0, 4.48169] ;
     [people(X)].
 
-markov asthma(X), friends(X,Y), smokes(Y);
+markov asthma(X), friends(X,Y), smokes(Y) ;
     [3.004166, 3.004166, 3.004166, 3.004166, 3.004166, 1.0, 1.0, 3.004166] ;
     [people(X,Y)].