Merge branch 'master' of ssh://yap.git.sourceforge.net/gitroot/yap/yap-6.3
This commit is contained in:
Vítor Santos Costa
commit
02a9709431
@ -699,48 +699,48 @@ pfl_init_solver(QueryKeys, AllKeys, Factors, Evidence, State) :-
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;
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format("Error: solver '~w' is unknown.", [Solver]), fail
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),
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pfl_init_solver(QueryKeys, AllKeys, Factors, Evidence, State, Solver).
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pfl_init_solver(Solver, QueryKeys, AllKeys, Factors, Evidence, State).
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pfl_init_solver(QueryKeys, AllKeys, Factors, Evidence, State, ve) :- !,
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pfl_init_solver(ve, QueryKeys, AllKeys, Factors, Evidence, State) :- !,
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init_ve_ground_solver(QueryKeys, AllKeys, Factors, Evidence, State).
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pfl_init_solver(QueryKeys, AllKeys, Factors, Evidence, State, hve) :- !,
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pfl_init_solver(hve, QueryKeys, AllKeys, Factors, Evidence, State) :- !,
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clpbn_horus:set_horus_flag(ground_solver, hve),
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init_horus_ground_solver(QueryKeys, AllKeys, Factors, Evidence, State).
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pfl_init_solver(QueryKeys, AllKeys, Factors, Evidence, State, bdd) :- !,
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pfl_init_solver(bdd, QueryKeys, AllKeys, Factors, Evidence, State) :- !,
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init_bdd_ground_solver(QueryKeys, AllKeys, Factors, Evidence, State).
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pfl_init_solver(QueryKeys, AllKeys, Factors, Evidence, State, bp) :- !,
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pfl_init_solver(bp, QueryKeys, AllKeys, Factors, Evidence, State) :- !,
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clpbn_horus:set_horus_flag(ground_solver, bp),
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init_horus_ground_solver(QueryKeys, AllKeys, Factors, Evidence, State).
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pfl_init_solver(QueryKeys, AllKeys, Factors, Evidence, State, cbp) :- !,
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pfl_init_solver(cbp, QueryKeys, AllKeys, Factors, Evidence, State) :- !,
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clpbn_horus:set_horus_flag(ground_solver, cbp),
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init_horus_ground_solver(QueryKeys, AllKeys, Factors, Evidence, State).
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pfl_init_solver(_, _, _, _, _, Solver) :-
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pfl_init_solver(Solver, _, _, _, _, _) :-
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format("Error: solver '~w' can't be used for learning.", [Solver]),
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fail.
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pfl_run_solver(LVs, LPs, State) :-
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em_solver(Solver),
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pfl_run_solver(LVs, LPs, State, Solver).
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pfl_run_solver(Solver, LVs, LPs, State).
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pfl_run_solver(LVs, LPs, State, ve) :- !,
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pfl_run_solver(ve, LVs, LPs, State) :- !,
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run_ve_ground_solver(LVs, LPs, State).
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pfl_run_solver(LVs, LPs, State, hve) :- !,
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pfl_run_solver(hve, LVs, LPs, State) :- !,
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run_horus_ground_solver(LVs, LPs, State).
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pfl_run_solver(LVs, LPs, State, bdd) :- !,
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pfl_run_solver(bdd, LVs, LPs, State) :- !,
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run_bdd_ground_solver(LVs, LPs, State).
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pfl_run_solver(LVs, LPs, State, bp) :- !,
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pfl_run_solver(bp, LVs, LPs, State) :- !,
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run_horus_ground_solver(LVs, LPs, State).
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pfl_run_solver(LVs, LPs, State, cbp) :- !,
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pfl_run_solver(cbp, LVs, LPs, State) :- !,
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run_horus_ground_solver(LVs, LPs, State).
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pfl_end_solver(State) :-
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@ -950,26 +950,27 @@ LiftedCircuit::createSmoothNode (
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vector<LogVarTypes>
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LiftedCircuit::getAllPossibleTypes (unsigned nrLogVars) const
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{
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if (nrLogVars == 0) {
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return {};
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}
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if (nrLogVars == 1) {
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return {{LogVarType::POS_LV},{LogVarType::NEG_LV}};
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}
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vector<LogVarTypes> res;
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Ranges ranges (nrLogVars, 2);
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Indexer indexer (ranges);
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while (indexer.valid()) {
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LogVarTypes types;
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for (size_t i = 0; i < nrLogVars; i++) {
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if (indexer[i] == 0) {
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types.push_back (LogVarType::POS_LV);
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} else {
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types.push_back (LogVarType::NEG_LV);
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if (nrLogVars == 0) {
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// do nothing
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} else if (nrLogVars == 1) {
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res.push_back ({ LogVarType::POS_LV });
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res.push_back ({ LogVarType::NEG_LV });
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} else {
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Ranges ranges (nrLogVars, 2);
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Indexer indexer (ranges);
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while (indexer.valid()) {
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LogVarTypes types;
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for (size_t i = 0; i < nrLogVars; i++) {
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if (indexer[i] == 0) {
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types.push_back (LogVarType::POS_LV);
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} else {
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types.push_back (LogVarType::NEG_LV);
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}
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}
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res.push_back (types);
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++ indexer;
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}
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res.push_back (types);
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++ indexer;
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}
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return res;
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}
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@ -38,7 +38,7 @@ CRACS \& INESC TEC, Faculty of Sciences, University of Porto
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\thispagestyle{empty}
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\vspace{5cm}
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\begin{center}
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\large Last revision: January 11, 2013
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\large Last revision: January 18, 2013
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\end{center}
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\newpage
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@ -60,7 +60,7 @@ The package also includes implementations for a set of well-known inference algo
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%------------------------------------------------------------------------------
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%------------------------------------------------------------------------------
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\section{Installation}
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PFL is included with the \href{http://www.dcc.fc.up.pt/~vsc/Yap/}{YAP} Prolog system. However, there isn't yet a stable release of YAP that includes PFL. So you will need to install a development version of YAP. To to so, you must have installed the \href{http://git-scm.com/}{Git} version control system. The commands to perform a default installation of YAP in your home directory in a Unix-based environment are shown next.
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PFL is included with the \href{http://www.dcc.fc.up.pt/~vsc/Yap/}{YAP} Prolog system. However, there isn't yet a stable release of YAP that includes PFL and you will need to install a development version. To do so, you must have installed the \href{http://git-scm.com/}{Git} version control system. The commands to perform a default installation of YAP in your home directory in a Unix-based environment are shown next.
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\begin{enumerate}
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\setlength\itemindent{-0.01cm}
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@ -433,7 +433,7 @@ Parameter learning is done by calling the \texttt{em/5} predicate. Its arguments
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Where,
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\begin{itemize}
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\item \texttt{Data} is a list of samples for the distribution that we want to estimate. Each sample is a list of either observed random variables or unobserved random variables (denoted when its state value is not instantiated).
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\item \texttt{Data} is a list of samples for the distribution that we want to estimate. Each sample is a list of either observed random variables or unobserved random variables (denoted when its state or value is not instantiated).
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\item \texttt{MaxError} is the maximum error allowed before stopping the EM loop.
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\item \texttt{MaxIters} is the maximum number of iterations for the EM loop.
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\item \texttt{CPTs} is a list with the estimated conditional probability tables.
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@ -1 +1 @@
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Subproject commit b98ea2bb69599c44bdda52c7f1d3e6e3152b97aa
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Subproject commit 980a0b9950ca0b52b327234fd2f66e0790f9c4e1
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