diogo/yap-6.3
Archived
1
0
Fork 0
Code Issues Pull Requests Packages Projects Releases Wiki Activity

Add support to markov networks

Browse Source
This commit is contained in:
Tiago Gomes 2012-04-05 18:38:56 +01:00
parent 6c3add2ebd
commit 0d23591058
32 changed files with 857 additions and 616 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

16
packages/CLPBN/clpbn/bp.yap
View File

@ -40,7 +40,7 @@
get_pfl_parameters/2
]).
:- use_module(library(clpbn/horus)).
% :- use_module(library(clpbn/horus)).
:- use_module(library(lists)).
@ -50,7 +50,7 @@
:- use_module(horus,
[create_ground_network/2,
[create_ground_network/4,
set_bayes_net_params/2,
run_ground_solver/3,
set_extra_vars_info/2,
@ -75,11 +75,19 @@ call_bp_ground(QueryKeys, AllKeys, Factors, Evidence, Solutions) :-
writeln(factorIds:FactorIds), writeln(''),
writeln(evidence:Evidence), writeln(''),
writeln(evIds:EvIds),
create_ground_network(Type, FactorIds, GroundNetwork).
%run_ground_solver(Network, QueryIds, EvIds, Solutions),
create_ground_network(Type, FactorIds, EvIds, Network),
run_ground_fixme_solver(ground(Network,Hash), QueryKeys, Solutions).
%free_graphical_model(Network).
run_ground_fixme_solver(ground(Network,Hash), QueryKeys, Solutions) :-
%get_dists_parameters(DistIds, DistsParams),
%set_bayes_net_params(Network, DistsParams),
%vars_to_ids(QueryVars, QueryVarsIds),
list_of_keys_to_ids(QueryKeys, Hash, QueryIds),
run_ground_solver(Network, [QueryIds], Solutions).
get_factors_type([f(bayes, _, _)|_], bayes) :- ! .
get_factors_type([f(markov, _, _)|_], markov) :- ! .

80
packages/CLPBN/clpbn/bp/BayesBall.cpp Normal file
View File

@ -0,0 +1,80 @@
#include <cstdlib>
#include <cassert>
#include <iostream>
#include <fstream>
#include <sstream>
#include "xmlParser/xmlParser.h"
#include "BayesBall.h"
#include "Util.h"
FactorGraph*
BayesBall::getMinimalFactorGraph (const VarIds& queryIds)
{
assert (fg_.isFromBayesNetwork());
Scheduling scheduling;
for (unsigned i = 0; i < queryIds.size(); i++) {
assert (dag_.getNode (queryIds[i]));
DAGraphNode* n = dag_.getNode (queryIds[i]);
scheduling.push (ScheduleInfo (n, false, true));
}
while (!scheduling.empty()) {
ScheduleInfo& sch = scheduling.front();
DAGraphNode* n = sch.node;
n->setAsVisited();
if (n->hasEvidence() == false && sch.visitedFromChild) {
if (n->isMarkedOnTop() == false) {
n->markOnTop();
scheduleParents (n, scheduling);
}
if (n->isMarkedOnBottom() == false) {
n->markOnBottom();
scheduleChilds (n, scheduling);
}
}
if (sch.visitedFromParent) {
if (n->hasEvidence() && n->isMarkedOnTop() == false) {
n->markOnTop();
scheduleParents (n, scheduling);
}
if (n->hasEvidence() == false && n->isMarkedOnBottom() == false) {
n->markOnBottom();
scheduleChilds (n, scheduling);
}
}
scheduling.pop();
}
FactorGraph* fg = new FactorGraph();
constructGraph (fg);
return fg;
}
void
BayesBall::constructGraph (FactorGraph* fg) const
{
const FgFacSet& facNodes = fg_.getFactorNodes();
for (unsigned i = 0; i < facNodes.size(); i++) {
const DAGraphNode* n = dag_.getNode (
facNodes[i]->factor()->argument (0));
if (n->isMarkedOnTop()) {
fg->addFactor (Factor (*(facNodes[i]->factor())));
} else if (n->hasEvidence() && n->isVisited()) {
VarIds varIds = { facNodes[i]->factor()->argument (0) };
Ranges ranges = { facNodes[i]->factor()->range (0) };
Params params (ranges[0], LogAware::noEvidence());
params[n->getEvidence()] = LogAware::withEvidence();
fg->addFactor (Factor (varIds, ranges, params));
}
}
}

86
packages/CLPBN/clpbn/bp/BayesBall.h Normal file
View File

@ -0,0 +1,86 @@
#ifndef HORUS_BAYESBALL_H
#define HORUS_BAYESBALL_H
#include <vector>
#include <queue>
#include <list>
#include <map>
#include "GraphicalModel.h"
#include "Horus.h"
#include "FactorGraph.h"
#include "BayesNet.h"
using namespace std;
struct ScheduleInfo
{
ScheduleInfo (DAGraphNode* n, bool vfp, bool vfc) :
node(n), visitedFromParent(vfp), visitedFromChild(vfc) { }
DAGraphNode* node;
bool visitedFromParent;
bool visitedFromChild;
};
typedef queue<ScheduleInfo, list<ScheduleInfo>> Scheduling;
class BayesBall
{
public:
BayesBall (FactorGraph& fg)
: fg_(fg) , dag_(fg.getStructure())
{
dag_.clear();
}
FactorGraph* getMinimalFactorGraph (const VarIds&);
static FactorGraph* getMinimalFactorGraph (FactorGraph& fg, VarIds vids)
{
BayesBall bb (fg);
return bb.getMinimalFactorGraph (vids);
}
private:
void constructGraph (FactorGraph* fg) const;
void scheduleParents (const DAGraphNode* n, Scheduling& sch) const;
void scheduleChilds (const DAGraphNode* n, Scheduling& sch) const;
FactorGraph& fg_;
DAGraph& dag_;
};
inline void
BayesBall::scheduleParents (const DAGraphNode* n, Scheduling& sch) const
{
const vector<DAGraphNode*>& ps = n->parents();
for (vector<DAGraphNode*>::const_iterator it = ps.begin();
it != ps.end(); it++) {
sch.push (ScheduleInfo (*it, false, true));
}
}
inline void
BayesBall::scheduleChilds (const DAGraphNode* n, Scheduling& sch) const
{
const vector<DAGraphNode*>& cs = n->childs();
for (vector<DAGraphNode*>::const_iterator it = cs.begin();
it != cs.end(); it++) {
sch.push (ScheduleInfo (*it, true, false));
}
}
#endif // HORUS_BAYESBALL_H

234
packages/CLPBN/clpbn/bp/BayesNet.cpp
View File

@ -11,6 +11,104 @@
#include "Util.h"
void
DAGraph::addNode (DAGraphNode* n)
{
nodes_.push_back (n);
assert (Util::contains (varMap_, n->varId()) == false);
varMap_[n->varId()] = n;
}
void
DAGraph::addEdge (VarId vid1, VarId vid2)
{
unordered_map<VarId, DAGraphNode*>::iterator it1;
unordered_map<VarId, DAGraphNode*>::iterator it2;
it1 = varMap_.find (vid1);
it2 = varMap_.find (vid2);
assert (it1 != varMap_.end());
assert (it2 != varMap_.end());
it1->second->addChild (it2->second);
it2->second->addParent (it1->second);
}
const DAGraphNode*
DAGraph::getNode (VarId vid) const
{
unordered_map<VarId, DAGraphNode*>::const_iterator it;
it = varMap_.find (vid);
return it != varMap_.end() ? it->second : 0;
}
DAGraphNode*
DAGraph::getNode (VarId vid)
{
unordered_map<VarId, DAGraphNode*>::const_iterator it;
it = varMap_.find (vid);
return it != varMap_.end() ? it->second : 0;
}
void
DAGraph::setIndexes (void)
{
for (unsigned i = 0; i < nodes_.size(); i++) {
nodes_[i]->setIndex (i);
}
}
void
DAGraph::clear (void)
{
for (unsigned i = 0; i < nodes_.size(); i++) {
nodes_[i]->clear();
}
}
void
DAGraph::exportToGraphViz (const char* fileName)
{
ofstream out (fileName);
if (!out.is_open()) {
cerr << "error: cannot open file to write at " ;
cerr << "DAGraph::exportToDotFile()" << endl;
abort();
}
out << "digraph {" << endl;
out << "ranksep=1" << endl;
for (unsigned i = 0; i < nodes_.size(); i++) {
out << nodes_[i]->varId() ;
out << " [" ;
out << "label=\"" << nodes_[i]->label() << "\"" ;
if (nodes_[i]->hasEvidence()) {
out << ",style=filled, fillcolor=yellow" ;
}
out << "]" << endl;
}
for (unsigned i = 0; i < nodes_.size(); i++) {
const vector<DAGraphNode*>& childs = nodes_[i]->childs();
for (unsigned j = 0; j < childs.size(); j++) {
out << nodes_[i]->varId() << " -> " << childs[j]->varId();
out << " [style=bold]" << endl ;
}
}
out << "}" << endl;
out.close();
}
BayesNet::~BayesNet (void)
{
@ -36,8 +134,8 @@ BayesNet::readFromBifFormat (const char* fileName)
}
States states;
string label = var.getChildNode("NAME").getText();
unsigned nrStates = var.nChildNode ("OUTCOME");
for (unsigned j = 0; j < nrStates; j++) {
unsigned range = var.nChildNode ("OUTCOME");
for (unsigned j = 0; j < range; j++) {
if (var.getChildNode("OUTCOME", j).getText() == 0) {
stringstream ss;
ss << j + 1;
@ -63,7 +161,7 @@ BayesNet::readFromBifFormat (const char* fileName)
abort();
}
BnNodeSet parents;
unsigned nParams = node->nrStates();
unsigned nParams = node->range();
for (int j = 0; j < def.nChildNode ("GIVEN"); j++) {
string parentLabel = def.getChildNode("GIVEN", j).getText();
BayesNode* parentNode = getBayesNode (parentLabel);
@ -71,7 +169,7 @@ BayesNet::readFromBifFormat (const char* fileName)
cerr << "error: unknow variable `" << parentLabel << "'" << endl;
abort();
}
nParams *= parentNode->nrStates();
nParams *= parentNode->range();
parents.push_back (parentNode);
}
node->setParents (parents);
@ -87,7 +185,7 @@ BayesNet::readFromBifFormat (const char* fileName)
cerr << "for variable `" << label << "'" << endl;
abort();
}
params = reorderParameters (params, node->nrStates());
params = reorderParameters (params, node->range());
if (Globals::logDomain) {
Util::toLog (params);
}
@ -218,130 +316,6 @@ BayesNet::getLeafNodes (void) const
BayesNet*
BayesNet::getMinimalRequesiteNetwork (VarId vid) const
{
return getMinimalRequesiteNetwork (VarIds() = {vid});
}
BayesNet*
BayesNet::getMinimalRequesiteNetwork (const VarIds& queryVarIds) const
{
BnNodeSet queryVars;
Scheduling scheduling;
for (unsigned i = 0; i < queryVarIds.size(); i++) {
BayesNode* n = getBayesNode (queryVarIds[i]);
assert (n);
queryVars.push_back (n);
scheduling.push (ScheduleInfo (n, false, true));
}
vector<StateInfo*> states (nodes_.size(), 0);
while (!scheduling.empty()) {
ScheduleInfo& sch = scheduling.front();
StateInfo* state = states[sch.node->getIndex()];
if (!state) {
state = new StateInfo();
states[sch.node->getIndex()] = state;
} else {
state->visited = true;
}
if (!sch.node->hasEvidence() && sch.visitedFromChild) {
if (!state->markedOnTop) {
state->markedOnTop = true;
scheduleParents (sch.node, scheduling);
}
if (!state->markedOnBottom) {
state->markedOnBottom = true;
scheduleChilds (sch.node, scheduling);
}
}
if (sch.visitedFromParent) {
if (sch.node->hasEvidence() && !state->markedOnTop) {
state->markedOnTop = true;
scheduleParents (sch.node, scheduling);
}
if (!sch.node->hasEvidence() && !state->markedOnBottom) {
state->markedOnBottom = true;
scheduleChilds (sch.node, scheduling);
}
}
scheduling.pop();
}
/*
cout << "\t\ttop\tbottom" << endl;
cout << "variable\t\tmarked\tmarked\tvisited\tobserved" << endl;
Util::printDashedLine();
cout << endl;
for (unsigned i = 0; i < states.size(); i++) {
cout << nodes_[i]->label() << ":\t\t" ;
if (states[i]) {
states[i]->markedOnTop ? cout << "yes\t" : cout << "no\t" ;
states[i]->markedOnBottom ? cout << "yes\t" : cout << "no\t" ;
states[i]->visited ? cout << "yes\t" : cout << "no\t" ;
nodes_[i]->hasEvidence() ? cout << "yes" : cout << "no" ;
cout << endl;
} else {
cout << "no\tno\tno\t" ;
nodes_[i]->hasEvidence() ? cout << "yes" : cout << "no" ;
cout << endl;
}
}
cout << endl;
*/
BayesNet* bn = new BayesNet();
constructGraph (bn, states);
for (unsigned i = 0; i < nodes_.size(); i++) {
delete states[i];
}
return bn;
}
void
BayesNet::constructGraph (BayesNet* bn,
const vector<StateInfo*>& states) const
{
BnNodeSet mrnNodes;
vector<VarIds> parents;
for (unsigned i = 0; i < nodes_.size(); i++) {
bool isRequired = false;
if (states[i]) {
isRequired = (nodes_[i]->hasEvidence() && states[i]->visited)
||
states[i]->markedOnTop;
}
if (isRequired) {
parents.push_back (VarIds());
if (states[i]->markedOnTop) {
const BnNodeSet& ps = nodes_[i]->getParents();
for (unsigned j = 0; j < ps.size(); j++) {
parents.back().push_back (ps[j]->varId());
}
}
assert (bn->getBayesNode (nodes_[i]->varId()) == 0);
BayesNode* mrnNode = new BayesNode (nodes_[i]);
bn->addNode (mrnNode);
mrnNodes.push_back (mrnNode);
}
}
for (unsigned i = 0; i < mrnNodes.size(); i++) {
BnNodeSet ps;
for (unsigned j = 0; j < parents[i].size(); j++) {
assert (bn->getBayesNode (parents[i][j]) != 0);
ps.push_back (bn->getBayesNode (parents[i][j]));
}
mrnNodes[i]->setParents (ps);
}
bn->setIndexes();
}
bool
BayesNet::isPolyTree (void) const
@ -458,7 +432,7 @@ BayesNet::exportToBifFormat (const char* fileName) const
out << "</GIVEN>" << endl;
}
Params params = revertParameterReorder (
nodes_[i]->params(), nodes_[i]->nrStates());
nodes_[i]->params(), nodes_[i]->range());
out << "\t<TABLE>" ;
for (unsigned j = 0; j < params.size(); j++) {
out << " " << params[j];

112
packages/CLPBN/clpbn/bp/BayesNet.h
View File

@ -14,28 +14,79 @@
using namespace std;
struct ScheduleInfo
class VarNode;
class DAGraphNode : public VarNode
{
ScheduleInfo (BayesNode* n, bool vfp, bool vfc) :
node(n), visitedFromParent(vfp), visitedFromChild(vfc) { }
BayesNode* node;
bool visitedFromParent;
bool visitedFromChild;
public:
DAGraphNode (VarNode* vn) : VarNode (vn) , visited_(false),
markedOnTop_(false), markedOnBottom_(false) { }
const vector<DAGraphNode*>& childs (void) const { return childs_; }
vector<DAGraphNode*>& childs (void) { return childs_; }
const vector<DAGraphNode*>& parents (void) const { return parents_; }
vector<DAGraphNode*>& parents (void) { return parents_; }
void addParent (DAGraphNode* p) { parents_.push_back (p); }
void addChild (DAGraphNode* c) { childs_.push_back (c); }
bool isVisited (void) const { return visited_; }
void setAsVisited (void) { visited_ = true; }
bool isMarkedOnTop (void) const { return markedOnTop_; }
void markOnTop (void) { markedOnTop_ = true; }
bool isMarkedOnBottom (void) const { return markedOnBottom_; }
void markOnBottom (void) { markedOnBottom_ = true; }
void clear (void) { visited_ = markedOnTop_ = markedOnBottom_ = false; }
private:
bool visited_;
bool markedOnTop_;
bool markedOnBottom_;
vector<DAGraphNode*> childs_;
vector<DAGraphNode*> parents_;
};
struct StateInfo
class DAGraph
{
StateInfo (void) : visited(false), markedOnTop(false),
markedOnBottom(false) { }
bool visited;
bool markedOnTop;
bool markedOnBottom;
public:
DAGraph (void) { }
void addNode (DAGraphNode* n);
void addEdge (VarId vid1, VarId vid2);
const DAGraphNode* getNode (VarId vid) const;
DAGraphNode* getNode (VarId vid);
bool empty (void) const { return nodes_.empty(); }
void setIndexes (void);
void clear (void);
void exportToGraphViz (const char*);
private:
vector<DAGraphNode*> nodes_;
unordered_map<VarId, DAGraphNode*> varMap_;
};
typedef queue<ScheduleInfo, list<ScheduleInfo> > Scheduling;
class BayesNet : public GraphicalModel
{
@ -66,12 +117,6 @@ class BayesNet : public GraphicalModel
BnNodeSet getLeafNodes (void) const;
BayesNet* getMinimalRequesiteNetwork (VarId) const;
BayesNet* getMinimalRequesiteNetwork (const VarIds&) const;
void constructGraph (BayesNet*, const vector<StateInfo*>&) const;
bool isPolyTree (void) const;
void setIndexes (void);
@ -96,37 +141,10 @@ class BayesNet : public GraphicalModel
Params revertParameterReorder (const Params&, unsigned) const;
void scheduleParents (const BayesNode*, Scheduling&) const;
void scheduleChilds (const BayesNode*, Scheduling&) const;
BnNodeSet nodes_;
typedef unordered_map<unsigned, unsigned> IndexMap;
IndexMap varMap_;
};
inline void
BayesNet::scheduleParents (const BayesNode* n, Scheduling& sch) const
{
const BnNodeSet& ps = n->getParents();
for (BnNodeSet::const_iterator it = ps.begin(); it != ps.end(); it++) {
sch.push (ScheduleInfo (*it, false, true));
}
}
inline void
BayesNet::scheduleChilds (const BayesNode* n, Scheduling& sch) const
{
const BnNodeSet& cs = n->getChilds();
for (BnNodeSet::const_iterator it = cs.begin(); it != cs.end(); it++) {
sch.push (ScheduleInfo (*it, true, false));
}
}
#endif // HORUS_BAYESNET_H

4
packages/CLPBN/clpbn/bp/BayesNode.cpp
View File

@ -127,7 +127,7 @@ BayesNode::getDomainHeaders (void) const
States states = parents_[i]->states();
unsigned index = 0;
while (index < rowSize) {
for (unsigned j = 0; j < parents_[i]->nrStates(); j++) {
for (unsigned j = 0; j < parents_[i]->range(); j++) {
for (unsigned r = 0; r < nReps; r++) {
if (headers[index] != "") {
headers[index] = states[j] + "," + headers[index];
@ -138,7 +138,7 @@ BayesNode::getDomainHeaders (void) const
}
}
}
nReps *= parents_[i]->nrStates();
nReps *= parents_[i]->range();
}
return headers;
}

8
packages/CLPBN/clpbn/bp/BayesNode.h
View File

@ -16,12 +16,12 @@ class BayesNode : public VarNode
BayesNode (const VarNode& v) : VarNode (v) { }
BayesNode (const BayesNode* n) :
VarNode (n->varId(), n->nrStates(), n->getEvidence()),
VarNode (n->varId(), n->range(), n->getEvidence()),
params_(n->params()), distId_(n->distId()) { }
BayesNode (VarId vid, unsigned nrStates, int ev,
BayesNode (VarId vid, unsigned range, int ev,
const Params& ps, unsigned id)
: VarNode (vid, nrStates, ev) , params_(ps), distId_(id) { }
: VarNode (vid, range, ev) , params_(ps), distId_(id) { }
const BnNodeSet& getParents (void) const { return parents_; }
@ -33,7 +33,7 @@ class BayesNode : public VarNode
unsigned getRowSize (void) const
{
return params_.size() / nrStates();
return params_.size() / range();
}
double getProbability (int row, unsigned col)

41
packages/CLPBN/clpbn/bp/BnBpSolver.cpp
View File

@ -109,7 +109,7 @@ BnBpSolver::initializeSolver (void)
for (unsigned i = 0; i < roots.size(); i++) {
const Params& params = roots[i]->params();
Params& piVals = ninf(roots[i])->getPiValues();
for (unsigned ri = 0; ri < roots[i]->nrStates(); ri++) {
for (unsigned ri = 0; ri < roots[i]->range(); ri++) {
piVals[ri] = params[ri];
}
}
@ -137,7 +137,7 @@ BnBpSolver::initializeSolver (void)
if (nodes[i]->hasEvidence()) {
Params& piVals = ninf(nodes[i])->getPiValues();
Params& ldVals = ninf(nodes[i])->getLambdaValues();
for (unsigned xi = 0; xi < nodes[i]->nrStates(); xi++) {
for (unsigned xi = 0; xi < nodes[i]->range(); xi++) {
piVals[xi] = LogAware::noEvidence();
ldVals[xi] = LogAware::noEvidence();
}
@ -310,7 +310,7 @@ BnBpSolver::updatePiValues (BayesNode* x)
const BnNodeSet& ps = x->getParents();
Ranges ranges;
for (unsigned i = 0; i < ps.size(); i++) {
ranges.push_back (ps[i]->nrStates());
ranges.push_back (ps[i]->range());
}
StatesIndexer indexer (ranges, false);
stringstream* calcs1 = 0;
@ -354,7 +354,7 @@ BnBpSolver::updatePiValues (BayesNode* x)
++ indexer;
}
for (unsigned xi = 0; xi < x->nrStates(); xi++) {
for (unsigned xi = 0; xi < x->range(); xi++) {
double sum = LogAware::addIdenty();
if (Constants::DEBUG >= 5) {
calcs1 = new stringstream;
@ -409,7 +409,7 @@ BnBpSolver::updateLambdaValues (BayesNode* x)
stringstream* calcs1 = 0;
stringstream* calcs2 = 0;
for (unsigned xi = 0; xi < x->nrStates(); xi++) {
for (unsigned xi = 0; xi < x->range(); xi++) {
if (Constants::DEBUG >= 5) {
calcs1 = new stringstream;
calcs2 = new stringstream;
@ -461,7 +461,7 @@ BnBpSolver::calculatePiMessage (BpLink* link)
stringstream* calcs2 = 0;
const Params& zPiValues = ninf(z)->getPiValues();
for (unsigned zi = 0; zi < z->nrStates(); zi++) {
for (unsigned zi = 0; zi < z->range(); zi++) {
double product = zPiValues[zi];
if (Constants::DEBUG >= 5) {
calcs1 = new stringstream;
@ -526,12 +526,12 @@ BnBpSolver::calculateLambdaMessage (BpLink* link)
const BnNodeSet& ps = y->getParents();
Ranges ranges;
for (unsigned i = 0; i < ps.size(); i++) {
ranges.push_back (ps[i]->nrStates());
ranges.push_back (ps[i]->range());
}
StatesIndexer indexer (ranges, false);
unsigned N = indexer.size() / x->nrStates();
unsigned N = indexer.size() / x->range();
Params messageProducts (N);
for (unsigned k = 0; k < N; k++) {
while (indexer[parentIndex] != 0) {
@ -579,13 +579,13 @@ BnBpSolver::calculateLambdaMessage (BpLink* link)
}
}
for (unsigned xi = 0; xi < x->nrStates(); xi++) {
for (unsigned xi = 0; xi < x->range(); xi++) {
if (Constants::DEBUG >= 5) {
calcs1 = new stringstream;
calcs2 = new stringstream;
}
double outerSum = LogAware::addIdenty();
for (unsigned yi = 0; yi < y->nrStates(); yi++) {
for (unsigned yi = 0; yi < y->range(); yi++) {
if (Constants::DEBUG >= 5) {
(yi != 0) ? *calcs1 << " + {" : *calcs1 << "{" ;
(yi != 0) ? *calcs2 << " + {" : *calcs2 << "{" ;
@ -645,6 +645,7 @@ BnBpSolver::calculateLambdaMessage (BpLink* link)
Params
BnBpSolver::getJointByConditioning (const VarIds& jointVarIds) const
{
/*
BnNodeSet jointVars;
for (unsigned i = 0; i < jointVarIds.size(); i++) {
assert (bayesNet_->getBayesNode (jointVarIds[i]));
@ -685,7 +686,7 @@ BnBpSolver::getJointByConditioning (const VarIds& jointVarIds) const
int count = -1;
for (unsigned j = 0; j < newBeliefs.size(); j++) {
if (j % jointVars[i]->nrStates() == 0) {
if (j % jointVars[i]->range() == 0) {
count ++;
}
newBeliefs[j] *= prevBeliefs[count];
@ -695,6 +696,8 @@ BnBpSolver::getJointByConditioning (const VarIds& jointVarIds) const
delete mrn;
}
return prevBeliefs;
*/
return Params();
}
@ -714,7 +717,7 @@ BnBpSolver::printPiLambdaValues (const BayesNode* var) const
const Params& piVals = ninf(var)->getPiValues();
const Params& ldVals = ninf(var)->getLambdaValues();
const Params& beliefs = ninf(var)->getBeliefs();
for (unsigned xi = 0; xi < var->nrStates(); xi++) {
for (unsigned xi = 0; xi < var->range(); xi++) {
cout << setw (10) << states[xi];
cout << setw (19) << piVals[xi];
cout << setw (19) << ldVals[xi];
@ -741,8 +744,8 @@ BnBpSolver::printAllMessageStatus (void) const
BpNodeInfo::BpNodeInfo (BayesNode* node)
{
node_ = node;
piVals_.resize (node->nrStates(), LogAware::one());
ldVals_.resize (node->nrStates(), LogAware::one());
piVals_.resize (node->range(), LogAware::one());
ldVals_.resize (node->range(), LogAware::one());
}
@ -751,20 +754,20 @@ Params
BpNodeInfo::getBeliefs (void) const
{
double sum = 0.0;
Params beliefs (node_->nrStates());
Params beliefs (node_->range());
if (Globals::logDomain) {
for (unsigned xi = 0; xi < node_->nrStates(); xi++) {
for (unsigned xi = 0; xi < node_->range(); xi++) {
beliefs[xi] = exp (piVals_[xi] + ldVals_[xi]);
sum += beliefs[xi];
}
} else {
for (unsigned xi = 0; xi < node_->nrStates(); xi++) {
for (unsigned xi = 0; xi < node_->range(); xi++) {
beliefs[xi] = piVals_[xi] * ldVals_[xi];
sum += beliefs[xi];
}
}
assert (sum);
for (unsigned xi = 0; xi < node_->nrStates(); xi++) {
for (unsigned xi = 0; xi < node_->range(); xi++) {
beliefs[xi] /= sum;
}
return beliefs;
@ -779,7 +782,7 @@ BpNodeInfo::receivedBottomInfluence (void) const
// this node neither its descendents have evidence,
// we can use this to don't send lambda messages his parents
bool childInfluenced = false;
for (unsigned xi = 1; xi < node_->nrStates(); xi++) {
for (unsigned xi = 1; xi < node_->range(); xi++) {
if (ldVals_[xi] != ldVals_[0]) {
childInfluenced = true;
break;

8
packages/CLPBN/clpbn/bp/BnBpSolver.h
View File

@ -27,11 +27,11 @@ class BpLink
destin_ = d;
orientation_ = o;
if (orientation_ == LinkOrientation::DOWN) {
v1_.resize (s->nrStates(), LogAware::tl (1.0 / s->nrStates()));
v2_.resize (s->nrStates(), LogAware::tl (1.0 / s->nrStates()));
v1_.resize (s->range(), LogAware::tl (1.0 / s->range()));
v2_.resize (s->range(), LogAware::tl (1.0 / s->range()));
} else {
v1_.resize (d->nrStates(), LogAware::tl (1.0 / d->nrStates()));
v2_.resize (d->nrStates(), LogAware::tl (1.0 / d->nrStates()));
v1_.resize (d->range(), LogAware::tl (1.0 / d->range()));
v2_.resize (d->range(), LogAware::tl (1.0 / d->range()));
}
currMsg_ = &v1_;
nextMsg_ = &v2_;

2
packages/CLPBN/clpbn/bp/CFactorGraph.cpp
View File

@ -51,7 +51,7 @@ CFactorGraph::setInitialColors (void)
VarColorMap colorMap;
const FgVarSet& varNodes = groundFg_->getVarNodes();
for (unsigned i = 0; i < varNodes.size(); i++) {
unsigned dsize = varNodes[i]->nrStates();
unsigned dsize = varNodes[i]->range();
VarColorMap::iterator it = colorMap.find (dsize);
if (it == colorMap.end()) {
it = colorMap.insert (make_pair (

6
packages/CLPBN/clpbn/bp/CbpSolver.cpp
View File

@ -20,10 +20,10 @@ CbpSolver::getPosterioriOf (VarId vid)
FgVarNode* var = lfg_->getEquivalentVariable (vid);
Params probs;
if (var->hasEvidence()) {
probs.resize (var->nrStates(), LogAware::noEvidence());
probs.resize (var->range(), LogAware::noEvidence());
probs[var->getEvidence()] = LogAware::withEvidence();
} else {
probs.resize (var->nrStates(), LogAware::multIdenty());
probs.resize (var->range(), LogAware::multIdenty());
const SpLinkSet& links = ninf(var)->getLinks();
if (Globals::logDomain) {
for (unsigned i = 0; i < links.size(); i++) {
@ -196,7 +196,7 @@ CbpSolver::getVar2FactorMsg (const SpLink* link) const
const FgFacNode* dst = link->getFactor();
const CbpSolverLink* l = static_cast<const CbpSolverLink*> (link);
if (src->hasEvidence()) {
msg.resize (src->nrStates(), LogAware::noEvidence());
msg.resize (src->range(), LogAware::noEvidence());
double value = link->getMessage()[src->getEvidence()];
msg[src->getEvidence()] = LogAware::pow (value, l->getNumberOfEdges() - 1);
} else {

2
packages/CLPBN/clpbn/bp/CbpSolver.h
View File

@ -12,7 +12,7 @@ class CbpSolverLink : public SpLink
CbpSolverLink (FgFacNode* fn, FgVarNode* vn, unsigned c) : SpLink (fn, vn)
{
edgeCount_ = c;
poweredMsg_.resize (vn->nrStates(), LogAware::one());
poweredMsg_.resize (vn->range(), LogAware::one());
}
unsigned getNumberOfEdges (void) const { return edgeCount_; }

249
packages/CLPBN/clpbn/bp/ElimGraph.cpp
View File

@ -3,52 +3,37 @@
#include <fstream>
#include "ElimGraph.h"
#include "BayesNet.h"
ElimHeuristic ElimGraph::elimHeuristic_ = MIN_NEIGHBORS;
ElimGraph::ElimGraph (const BayesNet& bayesNet)
ElimGraph::ElimGraph (const vector<Factor*>& factors)
{
const BnNodeSet& bnNodes = bayesNet.getBayesNodes();
for (unsigned i = 0; i < bnNodes.size(); i++) {
if (bnNodes[i]->hasEvidence() == false) {
addNode (new EgNode (bnNodes[i]));
for (unsigned i = 0; i < factors.size(); i++) {
const VarIds& vids = factors[i]->arguments();
for (unsigned j = 0; j < vids.size() - 1; j++) {
EgNode* n1 = getEgNode (vids[j]);
if (n1 == 0) {
n1 = new EgNode (vids[j], factors[i]->range (j));
addNode (n1);
}
for (unsigned k = j + 1; k < vids.size(); k++) {
EgNode* n2 = getEgNode (vids[k]);
if (n2 == 0) {
n2 = new EgNode (vids[k], factors[i]->range (k));
addNode (n2);
}
for (unsigned i = 0; i < bnNodes.size(); i++) {
if (bnNodes[i]->hasEvidence() == false) {
EgNode* n = getEgNode (bnNodes[i]->varId());
const BnNodeSet& childs = bnNodes[i]->getChilds();
for (unsigned j = 0; j < childs.size(); j++) {
if (childs[j]->hasEvidence() == false) {
addEdge (n, getEgNode (childs[j]->varId()));
if (neighbors (n1, n2) == false) {
addEdge (n1, n2);
}
}
}
}
for (unsigned i = 0; i < bnNodes.size(); i++) {
vector<EgNode*> neighs;
const vector<BayesNode*>& parents = bnNodes[i]->getParents();
for (unsigned i = 0; i < parents.size(); i++) {
if (parents[i]->hasEvidence() == false) {
neighs.push_back (getEgNode (parents[i]->varId()));
}
}
if (neighs.size() > 0) {
for (unsigned i = 0; i < neighs.size() - 1; i++) {
for (unsigned j = i+1; j < neighs.size(); j++) {
if (!neighbors (neighs[i], neighs[j])) {
addEdge (neighs[i], neighs[j]);
if (vids.size() == 1) {
if (getEgNode (vids[0]) == 0) {
addNode (new EgNode (vids[0], factors[i]->range (0)));
}
}
}
}
}
setIndexes();
}
@ -63,6 +48,102 @@ ElimGraph::~ElimGraph (void)
VarIds
ElimGraph::getEliminatingOrder (const VarIds& exclude)
{
VarIds elimOrder;
marked_.resize (nodes_.size(), false);
for (unsigned i = 0; i < exclude.size(); i++) {
assert (getEgNode (exclude[i]));
EgNode* node = getEgNode (exclude[i]);
marked_[*node] = true;
}
unsigned nVarsToEliminate = nodes_.size() - exclude.size();
for (unsigned i = 0; i < nVarsToEliminate; i++) {
EgNode* node = getLowestCostNode();
marked_[*node] = true;
elimOrder.push_back (node->varId());
connectAllNeighbors (node);
}
return elimOrder;
}
void
ElimGraph::print (void) const
{
for (unsigned i = 0; i < nodes_.size(); i++) {
cout << "node " << nodes_[i]->label() << " neighs:" ;
vector<EgNode*> neighs = nodes_[i]->neighbors();
for (unsigned j = 0; j < neighs.size(); j++) {
cout << " " << neighs[j]->label();
}
cout << endl;
}
}
void
ElimGraph::exportToGraphViz (
const char* fileName,
bool showNeighborless,
const VarIds& highlightVarIds) const
{
ofstream out (fileName);
if (!out.is_open()) {
cerr << "error: cannot open file to write at " ;
cerr << "Markov::exportToDotFile()" << endl;
abort();
}
out << "strict graph {" << endl;
for (unsigned i = 0; i < nodes_.size(); i++) {
if (showNeighborless || nodes_[i]->neighbors().size() != 0) {
out << '"' << nodes_[i]->label() << '"' << endl;
}
}
for (unsigned i = 0; i < highlightVarIds.size(); i++) {
EgNode* node =getEgNode (highlightVarIds[i]);
if (node) {
out << '"' << node->label() << '"' ;
out << " [shape=box3d]" << endl;
} else {
cout << "error: invalid variable id: " << highlightVarIds[i] << endl;
abort();
}
}
for (unsigned i = 0; i < nodes_.size(); i++) {
vector<EgNode*> neighs = nodes_[i]->neighbors();
for (unsigned j = 0; j < neighs.size(); j++) {
out << '"' << nodes_[i]->label() << '"' << " -- " ;
out << '"' << neighs[j]->label() << '"' << endl;
}
}
out << "}" << endl;
out.close();
}
VarIds
ElimGraph::getEliminationOrder (
const vector<Factor*> factors,
VarIds excludedVids)
{
ElimGraph graph (factors);
// graph.print();
// graph.exportToGraphViz ("_egg.dot");
return graph.getEliminatingOrder (excludedVids);
}
void
ElimGraph::addNode (EgNode* n)
{
@ -75,36 +156,9 @@ ElimGraph::addNode (EgNode* n)
EgNode*
ElimGraph::getEgNode (VarId vid) const
{
unordered_map<VarId,EgNode*>::const_iterator it =varMap_.find (vid);
if (it ==varMap_.end()) {
return 0;
} else {
return it->second;
}
}
VarIds
ElimGraph::getEliminatingOrder (const VarIds& exclude)
{
VarIds elimOrder;
marked_.resize (nodes_.size(), false);
for (unsigned i = 0; i < exclude.size(); i++) {
EgNode* node = getEgNode (exclude[i]);
assert (node);
marked_[*node] = true;
}
unsigned nVarsToEliminate = nodes_.size() - exclude.size();
for (unsigned i = 0; i < nVarsToEliminate; i++) {
EgNode* node = getLowestCostNode();
marked_[*node] = true;
elimOrder.push_back (node->varId());
connectAllNeighbors (node);
}
return elimOrder;
unordered_map<VarId, EgNode*>::const_iterator it;
it = varMap_.find (vid);
return (it != varMap_.end()) ? it->second : 0;
}
@ -166,7 +220,7 @@ ElimGraph::getWeightCost (const EgNode* n) const
const vector<EgNode*>& neighs = n->neighbors();
for (unsigned i = 0; i < neighs.size(); i++) {
if (marked_[*neighs[i]] == false) {
cost *= neighs[i]->nrStates();
cost *= neighs[i]->range();
}
}
return cost;
@ -206,7 +260,7 @@ ElimGraph::getWeightedFillCost (const EgNode* n) const
for (unsigned j = i+1; j < neighs.size(); j++) {
if (marked_[*neighs[j]] == true) continue;
if (!neighbors (neighs[i], neighs[j])) {
cost += neighs[i]->nrStates() * neighs[j]->nrStates();
cost += neighs[i]->range() * neighs[j]->range();
}
}
}
@ -257,68 +311,3 @@ ElimGraph::setIndexes (void)
}
}
void
ElimGraph::printGraphicalModel (void) const
{
for (unsigned i = 0; i < nodes_.size(); i++) {
cout << "node " << nodes_[i]->label() << " neighs:" ;
vector<EgNode*> neighs = nodes_[i]->neighbors();
for (unsigned j = 0; j < neighs.size(); j++) {
cout << " " << neighs[j]->label();
}
cout << endl;
}
}
void
ElimGraph::exportToGraphViz (const char* fileName,
bool showNeighborless,
const VarIds& highlightVarIds) const
{
ofstream out (fileName);
if (!out.is_open()) {
cerr << "error: cannot open file to write at " ;
cerr << "Markov::exportToDotFile()" << endl;
abort();
}
out << "strict graph {" << endl;
for (unsigned i = 0; i < nodes_.size(); i++) {
if (showNeighborless || nodes_[i]->neighbors().size() != 0) {
out << '"' << nodes_[i]->label() << '"' ;
if (nodes_[i]->hasEvidence()) {
out << " [style=filled, fillcolor=yellow]" << endl;
} else {
out << endl;
}
}
}
for (unsigned i = 0; i < highlightVarIds.size(); i++) {
EgNode* node =getEgNode (highlightVarIds[i]);
if (node) {
out << '"' << node->label() << '"' ;
out << " [shape=box3d]" << endl;
} else {
cout << "error: invalid variable id: " << highlightVarIds[i] << endl;
abort();
}
}
for (unsigned i = 0; i < nodes_.size(); i++) {
vector<EgNode*> neighs = nodes_[i]->neighbors();
for (unsigned j = 0; j < neighs.size(); j++) {
out << '"' << nodes_[i]->label() << '"' << " -- " ;
out << '"' << neighs[j]->label() << '"' << endl;
}
}
out << "}" << endl;
out.close();
}

40
packages/CLPBN/clpbn/bp/ElimGraph.h
View File

@ -20,7 +20,7 @@ enum ElimHeuristic
class EgNode : public VarNode
{
public:
EgNode (VarNode* var) : VarNode (var) { }
EgNode (VarId vid, unsigned range) : VarNode (vid, range) { }
void addNeighbor (EgNode* n) { neighs_.push_back (n); }
@ -34,10 +34,26 @@ class EgNode : public VarNode
class ElimGraph
{
public:
ElimGraph (const BayesNet&);
ElimGraph (const vector<Factor*>&); // TODO
~ElimGraph (void);
VarIds getEliminatingOrder (const VarIds&);
void print (void) const;
void exportToGraphViz (const char*, bool = true,
const VarIds& = VarIds()) const;
static VarIds getEliminationOrder (const vector<Factor*>, VarIds);
static void setEliminationHeuristic (ElimHeuristic h)
{
elimHeuristic_ = h;
}
private:
void addEdge (EgNode* n1, EgNode* n2)
{
assert (n1 != n2);
@ -48,22 +64,6 @@ class ElimGraph
void addNode (EgNode*);
EgNode* getEgNode (VarId) const;
VarIds getEliminatingOrder (const VarIds&);
void printGraphicalModel (void) const;
void exportToGraphViz (const char*, bool = true,
const VarIds& = VarIds()) const;
void setIndexes();
static void setEliminationHeuristic (ElimHeuristic h)
{
elimHeuristic_ = h;
}
private:
EgNode* getLowestCostNode (void) const;
unsigned getNeighborsCost (const EgNode*) const;
@ -78,9 +78,11 @@ class ElimGraph
bool neighbors (const EgNode*, const EgNode*) const;
void setIndexes (void);
vector<EgNode*> nodes_;
vector<bool> marked_;
unordered_map<VarId,EgNode*> varMap_;
unordered_map<VarId, EgNode*> varMap_;
static ElimHeuristic elimHeuristic_;
};

26
packages/CLPBN/clpbn/bp/Factor.cpp
View File

@ -18,11 +18,11 @@ Factor::Factor (const Factor& g)
Factor::Factor (VarId vid, unsigned nrStates)
Factor::Factor (VarId vid, unsigned range)
{
args_.push_back (vid);
ranges_.push_back (nrStates);
params_.resize (nrStates, 1.0);
ranges_.push_back (range);
params_.resize (range, 1.0);
distId_ = Util::maxUnsigned();
assert (params_.size() == Util::expectedSize (ranges_));
}
@ -34,8 +34,8 @@ Factor::Factor (const VarNodes& vars)
int nrParams = 1;
for (unsigned i = 0; i < vars.size(); i++) {
args_.push_back (vars[i]->varId());
ranges_.push_back (vars[i]->nrStates());
nrParams *= vars[i]->nrStates();
ranges_.push_back (vars[i]->range());
nrParams *= vars[i]->range();
}
double val = 1.0 / nrParams;
params_.resize (nrParams, val);
@ -47,11 +47,11 @@ Factor::Factor (const VarNodes& vars)
Factor::Factor (
VarId vid,
unsigned nrStates,
unsigned range,
const Params& params)
{
args_.push_back (vid);
ranges_.push_back (nrStates);
ranges_.push_back (range);
params_ = params;
distId_ = Util::maxUnsigned();
assert (params_.size() == Util::expectedSize (ranges_));
@ -66,7 +66,7 @@ Factor::Factor (
{
for (unsigned i = 0; i < vars.size(); i++) {
args_.push_back (vars[i]->varId());
ranges_.push_back (vars[i]->nrStates());
ranges_.push_back (vars[i]->range());
}
params_ = params;
distId_ = distId;
@ -186,8 +186,8 @@ Factor::sumOut (VarId vid)
void
Factor::sumOutFirstVariable (void)
{
unsigned nStates = ranges_.front();
unsigned sep = params_.size() / nStates;
unsigned range = ranges_.front();
unsigned sep = params_.size() / range;
if (Globals::logDomain) {
for (unsigned i = sep; i < params_.size(); i++) {
params_[i % sep] = Util::logSum (params_[i % sep], params_[i]);
@ -207,14 +207,14 @@ Factor::sumOutFirstVariable (void)
void
Factor::sumOutLastVariable (void)
{
unsigned nStates = ranges_.back();
unsigned range = ranges_.back();
unsigned idx1 = 0;
unsigned idx2 = 0;
if (Globals::logDomain) {
while (idx1 < params_.size()) {
params_[idx2] = params_[idx1];
idx1 ++;
for (unsigned j = 1; j < nStates; j++) {
for (unsigned j = 1; j < range; j++) {
params_[idx2] = Util::logSum (params_[idx2], params_[idx1]);
idx1 ++;
}
@ -224,7 +224,7 @@ Factor::sumOutLastVariable (void)
while (idx1 < params_.size()) {
params_[idx2] = params_[idx1];
idx1 ++;
for (unsigned j = 1; j < nStates; j++) {
for (unsigned j = 1; j < range; j++) {
params_[idx2] += params_[idx1];
idx1 ++;
}

75
packages/CLPBN/clpbn/bp/FactorGraph.cpp
View File

@ -9,6 +9,7 @@
#include "FactorGraph.h"
#include "Factor.h"
#include "BayesNet.h"
#include "BayesBall.h"
#include "Util.h"
@ -205,13 +206,13 @@ FactorGraph::readFromLibDaiFormat (const char* fileName)
var = new FgVarNode (vids[j], dsize);
addVariable (var);
} else {
if (var->nrStates() != dsize) {
if (var->range() != dsize) {
cerr << "error: variable `" << vids[j] << "' appears in two or " ;
cerr << "more factors with different domain sizes" << endl;
}
}
neighs.push_back (var);
nParams *= var->nrStates();
nParams *= var->range();
}
Params params (nParams, 0);
unsigned nNonzeros;
@ -274,6 +275,30 @@ FactorGraph::addFactor (FgFacNode* fn)
void
FactorGraph::addFactor (const Factor& factor)
{
FgFacNode* fn = new FgFacNode (factor);
addFactor (fn);
const VarIds& vids = factor.arguments();
for (unsigned i = 0; i < vids.size(); i++) {
bool found = false;
for (unsigned j = 0; j < varNodes_.size(); j++) {
if (varNodes_[j]->varId() == vids[i]) {
addEdge (varNodes_[j], fn);
found = true;
}
}
if (found == false) {
FgVarNode* vn = new FgVarNode (vids[i], factor.range (i));
addVariable (vn);
addEdge (vn, fn);
}
}
}
void
FactorGraph::addEdge (FgVarNode* vn, FgFacNode* fn)
{
@ -322,6 +347,26 @@ FactorGraph::isTree (void) const
DAGraph&
FactorGraph::getStructure (void)
{
assert (fromBayesNet_);
if (structure_.empty()) {
for (unsigned i = 0; i < varNodes_.size(); i++) {
structure_.addNode (new DAGraphNode (varNodes_[i]));
}
for (unsigned i = 0; i < facNodes_.size(); i++) {
const VarIds& vids = facNodes_[i]->factor()->arguments();
for (unsigned j = 1; j < vids.size(); j++) {
structure_.addEdge (vids[j], vids[0]);
}
}
}
return structure_;
}
void
FactorGraph::setIndexes (void)
{
@ -339,11 +384,11 @@ void
FactorGraph::printGraphicalModel (void) const
{
for (unsigned i = 0; i < varNodes_.size(); i++) {
cout << "VarId = " << varNodes_[i]->varId() << endl;
cout << "Label = " << varNodes_[i]->label() << endl;
cout << "Nr States = " << varNodes_[i]->nrStates() << endl;
cout << "Evidence = " << varNodes_[i]->getEvidence() << endl;
cout << "Factors = " ;
cout << "var id = " << varNodes_[i]->varId() << endl;
cout << "label = " << varNodes_[i]->label() << endl;
cout << "range = " << varNodes_[i]->range() << endl;
cout << "evidence = " << varNodes_[i]->getEvidence() << endl;
cout << "factors = " ;
for (unsigned j = 0; j < varNodes_[i]->neighbors().size(); j++) {
cout << varNodes_[i]->neighbors()[j]->getLabel() << " " ;
}
@ -351,7 +396,6 @@ FactorGraph::printGraphicalModel (void) const
}
for (unsigned i = 0; i < facNodes_.size(); i++) {
facNodes_[i]->factor()->print();
cout << endl;
}
}
@ -366,22 +410,18 @@ FactorGraph::exportToGraphViz (const char* fileName) const
cerr << "FactorGraph::exportToDotFile()" << endl;
abort();
}
out << "graph \"" << fileName << "\" {" << endl;
for (unsigned i = 0; i < varNodes_.size(); i++) {
if (varNodes_[i]->hasEvidence()) {
out << '"' << varNodes_[i]->label() << '"' ;
out << " [style=filled, fillcolor=yellow]" << endl;
}
}
for (unsigned i = 0; i < facNodes_.size(); i++) {
out << '"' << facNodes_[i]->getLabel() << '"' ;
out << " [label=\"" << facNodes_[i]->getLabel();
out << "\"" << ", shape=box]" << endl;
}
for (unsigned i = 0; i < facNodes_.size(); i++) {
const FgVarSet& myVars = facNodes_[i]->neighbors();
for (unsigned j = 0; j < myVars.size(); j++) {
@ -390,7 +430,6 @@ FactorGraph::exportToGraphViz (const char* fileName) const
out << '"' << myVars[j]->label() << '"' << endl;
}
}
out << "}" << endl;
out.close();
}
@ -410,7 +449,7 @@ FactorGraph::exportToUaiFormat (const char* fileName) const
out << "MARKOV" << endl;
out << varNodes_.size() << endl;
for (unsigned i = 0; i < varNodes_.size(); i++) {
out << varNodes_[i]->nrStates() << " " ;
out << varNodes_[i]->range() << " " ;
}
out << endl;
@ -459,7 +498,7 @@ FactorGraph::exportToLibDaiFormat (const char* fileName) const
}
out << endl;
for (unsigned j = 0; j < factorVars.size(); j++) {
out << factorVars[j]->nrStates() << " " ;
out << factorVars[j]->range() << " " ;
}
out << endl;
Params params = facNodes_[i]->factor()->params();
@ -496,7 +535,8 @@ FactorGraph::containsCycle (void) const
bool
FactorGraph::containsCycle (const FgVarNode* v,
FactorGraph::containsCycle (
const FgVarNode* v,
const FgFacNode* p,
vector<bool>& visitedVars,
vector<bool>& visitedFactors) const
@ -520,7 +560,8 @@ FactorGraph::containsCycle (const FgVarNode* v,
bool
FactorGraph::containsCycle (const FgFacNode* v,
FactorGraph::containsCycle (
const FgFacNode* v,
const FgVarNode* p,
vector<bool>& visitedVars,
vector<bool>& visitedFactors) const

26
packages/CLPBN/clpbn/bp/FactorGraph.h
View File

@ -3,13 +3,14 @@
#include <vector>
#include "GraphicalModel.h"
#include "Factor.h"
#include "GraphicalModel.h"
#include "BayesNet.h"
#include "Horus.h"
using namespace std;
class BayesNet;
class FgFacNode;
@ -42,6 +43,8 @@ class FgFacNode
FgFacNode (Factor* f) : factor_(new Factor(*f)), index_(-1) { }
FgFacNode (const Factor& f) : factor_(new Factor (f)), index_(-1) { }
Factor* factor() const { return factor_; }
void addNeighbor (FgVarNode* vn) { neighs_.push_back (vn); }
@ -90,7 +93,7 @@ struct CompVarId
class FactorGraph : public GraphicalModel
{
public:
FactorGraph (void) { };
FactorGraph (void) { }
FactorGraph (const FactorGraph&);
@ -102,14 +105,14 @@ class FactorGraph : public GraphicalModel
const FgFacSet& getFactorNodes (void) const { return facNodes_; }
void setFromBayesNetwork (void) { fromBayesNet_ = true; }
bool isFromBayesNetwork (void) const { return fromBayesNet_ ; }
FgVarNode* getFgVarNode (VarId vid) const
{
IndexMap::const_iterator it = varMap_.find (vid);
if (it == varMap_.end()) {
return 0;
} else {
return varNodes_[it->second];
}
return (it != varMap_.end()) ? varNodes_[it->second] : 0;
}
void readFromUaiFormat (const char*);
@ -120,6 +123,8 @@ class FactorGraph : public GraphicalModel
void addFactor (FgFacNode*);
void addFactor (const Factor& factor);
void addEdge (FgVarNode*, FgFacNode*);
void addEdge (FgFacNode*, FgVarNode*);
@ -130,6 +135,8 @@ class FactorGraph : public GraphicalModel
bool isTree (void) const;
DAGraph& getStructure (void);
void setIndexes (void);
void printGraphicalModel (void) const;
@ -156,6 +163,9 @@ class FactorGraph : public GraphicalModel
FgVarSet varNodes_;
FgFacSet facNodes_;
bool fromBayesNet_;
DAGraph structure_;
typedef unordered_map<unsigned, unsigned> IndexMap;
IndexMap varMap_;
};

22
packages/CLPBN/clpbn/bp/FgBpSolver.cpp
View File

@ -71,10 +71,10 @@ FgBpSolver::getPosterioriOf (VarId vid)
FgVarNode* var = factorGraph_->getFgVarNode (vid);
Params probs;
if (var->hasEvidence()) {
probs.resize (var->nrStates(), LogAware::noEvidence());
probs.resize (var->range(), LogAware::noEvidence());
probs[var->getEvidence()] = LogAware::withEvidence();
} else {
probs.resize (var->nrStates(), LogAware::multIdenty());
probs.resize (var->range(), LogAware::multIdenty());
const SpLinkSet& links = ninf(var)->getLinks();
if (Globals::logDomain) {
for (unsigned i = 0; i < links.size(); i++) {
@ -113,7 +113,7 @@ FgBpSolver::getJointDistributionOf (const VarIds& jointVarIds)
const SpLinkSet& links = ninf(factorNodes[idx])->getLinks();
for (unsigned i = 0; i < links.size(); i++) {
Factor msg (links[i]->getVariable()->varId(),
links[i]->getVariable()->nrStates(),
links[i]->getVariable()->range(),
getVar2FactorMsg (links[i]));
res.multiply (msg);
}
@ -325,7 +325,7 @@ FgBpSolver::calculateFactor2VariableMsg (SpLink* link) const
// to factor `src', except from var `dst'
unsigned msgSize = 1;
for (unsigned i = 0; i < links.size(); i++) {
msgSize *= links[i]->getVariable()->nrStates();
msgSize *= links[i]->getVariable()->range();
}
unsigned repetitions = 1;
Params msgProduct (msgSize, LogAware::multIdenty());
@ -333,9 +333,9 @@ FgBpSolver::calculateFactor2VariableMsg (SpLink* link) const
for (int i = links.size() - 1; i >= 0; i--) {
if (links[i]->getVariable() != dst) {
Util::add (msgProduct, getVar2FactorMsg (links[i]), repetitions);
repetitions *= links[i]->getVariable()->nrStates();
repetitions *= links[i]->getVariable()->range();
} else {
unsigned ds = links[i]->getVariable()->nrStates();
unsigned ds = links[i]->getVariable()->range();
Util::add (msgProduct, Params (ds, 1.0), repetitions);
repetitions *= ds;
}
@ -348,9 +348,9 @@ FgBpSolver::calculateFactor2VariableMsg (SpLink* link) const
cout << ": " << endl;
}
Util::multiply (msgProduct, getVar2FactorMsg (links[i]), repetitions);
repetitions *= links[i]->getVariable()->nrStates();
repetitions *= links[i]->getVariable()->range();
} else {
unsigned ds = links[i]->getVariable()->nrStates();
unsigned ds = links[i]->getVariable()->range();
Util::multiply (msgProduct, Params (ds, 1.0), repetitions);
repetitions *= ds;
}
@ -392,13 +392,13 @@ FgBpSolver::getVar2FactorMsg (const SpLink* link) const
const FgFacNode* dst = link->getFactor();
Params msg;
if (src->hasEvidence()) {
msg.resize (src->nrStates(), LogAware::noEvidence());
msg.resize (src->range(), LogAware::noEvidence());
msg[src->getEvidence()] = LogAware::withEvidence();
if (Constants::DEBUG >= 5) {
cout << msg;
}
} else {
msg.resize (src->nrStates(), LogAware::one());
msg.resize (src->range(), LogAware::one());
}
if (Constants::DEBUG >= 5) {
cout << msg;
@ -467,7 +467,7 @@ FgBpSolver::getJointByConditioning (const VarIds& jointVarIds) const
int count = -1;
for (unsigned j = 0; j < newBeliefs.size(); j++) {
if (j % jointVars[i]->nrStates() == 0) {
if (j % jointVars[i]->range() == 0) {
count ++;
}
newBeliefs[j] *= prevBeliefs[count];

4
packages/CLPBN/clpbn/bp/FgBpSolver.h
View File

@ -20,8 +20,8 @@ class SpLink
{
fac_ = fn;
var_ = vn;
v1_.resize (vn->nrStates(), LogAware::tl (1.0 / vn->nrStates()));
v2_.resize (vn->nrStates(), LogAware::tl (1.0 / vn->nrStates()));
v1_.resize (vn->range(), LogAware::tl (1.0 / vn->range()));
v2_.resize (vn->range(), LogAware::tl (1.0 / vn->range()));
currMsg_ = &v1_;
nextMsg_ = &v2_;
msgSended_ = false;

2
packages/CLPBN/clpbn/bp/Horus.h
View File

@ -50,7 +50,7 @@ extern InfAlgorithms infAlgorithm;
namespace Constants {
// level of debug information
const unsigned DEBUG = 2;
const unsigned DEBUG = 1;
const int NO_EVIDENCE = -1;

27
packages/CLPBN/clpbn/bp/HorusCli.cpp
View File

@ -10,6 +10,8 @@
#include "FgBpSolver.h"
#include "CbpSolver.h"
#include "ElimGraph.h"
using namespace std;
void processArguments (BayesNet&, int, const char* []);
@ -23,6 +25,31 @@ const string USAGE = "usage: \
int
main (int argc, const char* argv[])
{
VarIds vids1 = { 4, 1, 2, 3 } ;
VarIds vids2 = { 4, 5 } ;
VarIds vids3 = { 4, 6 } ;
VarIds vids4 = { 4, 7 } ;
// Factor f1 (vids1, {2,2,2,2},{0.1,0.2,0.3,0.4,0.5,0.6,0.7,0.8,0.9,0.10,0.11,0.12,0.13,0.14,0.15,0.16});
// Factor f2 (vids2, {2,2},{0.1,0.2,0.3,0.4});
// Factor f3 (vids3, {2,2},{0.1,0.2,0.3,0.4});
// Factor f4 (vids4, {2,2},{0.1,0.2,0.3,0.4});
Factor* f1 = new Factor (vids1, {2,2,2,2},{0.1,0.2,0.3,0.4,0.5,0.6,0.7,0.8,0.9,0.10,0.11,0.12,0.13,0.14,0.15,0.16});
Factor* f2 = new Factor (vids2, {2,2},{0.1,0.2,0.3,0.4});
Factor* f3 = new Factor (vids3, {2,2},{0.1,0.2,0.3,0.4});
Factor* f4 = new Factor (vids4, {2,2},{0.1,0.2,0.3,0.4});
Factor* f5 = new Factor (vids4, {2,2},{0.1,0.2,0.3,0.4});
vector<Factor*> fs = {f1,f2,f3,f4,f5};
//FactorGraph fg;
//fg.addFactor (f1);
//fg.addFactor (f2);
//fg.addFactor (f3);
//fg.addFactor (f4);
ElimGraph eg (fs);
eg.exportToGraphViz ("_eg.dot");
return 0;
if (!argv[1]) {
cerr << "error: no graphical model specified" << endl;
cerr << USAGE << endl;

201
packages/CLPBN/clpbn/bp/HorusYap.cpp
View File

@ -16,6 +16,7 @@
#include "FgBpSolver.h"
#include "CbpSolver.h"
#include "ElimGraph.h"
#include "BayesBall.h"
using namespace std;
@ -46,6 +47,7 @@ readUnsignedList (YAP_Term list)
}
int createLiftedNetwork (void)
{
Parfactors parfactors;
@ -212,14 +214,7 @@ void readLiftedEvidence (
int
createGroundNetwork (void)
{
Statistics::incrementPrimaryNetworksCounting();
// cout << "creating network number " ;
// cout << Statistics::getPrimaryNetworksCounting() << endl;
// if (Statistics::getPrimaryNetworksCounting() > 98) {
// Statistics::writeStatisticsToFile ("../../compressing.stats");
// }
BayesNet* bn = new BayesNet();
FactorGraph* fg = new FactorGraph();;
string factorsType ((char*) YAP_AtomName (YAP_AtomOfTerm (YAP_ARG1)));
cout << "factors type: '" << factorsType << "'" << endl;
@ -234,45 +229,27 @@ createGroundNetwork (void)
Params params = readParameters (YAP_ArgOfTerm (3, factor));
// read dist id
unsigned distId = (unsigned) YAP_IntOfTerm (YAP_ArgOfTerm (4, factor));
fg->addFactor (Factor (varIds, ranges, params, distId));
factorList = YAP_TailOfTerm (factorList);
Factor f (varIds, ranges, params, distId);
f.print();
}
assert (false);
/*
vector<VarIds> parents;
while (varList != YAP_TermNil()) {
YAP_Term var = YAP_HeadOfTerm (varList);
VarId vid = (VarId) YAP_IntOfTerm (YAP_ArgOfTerm (1, var));
unsigned dsize = (unsigned) YAP_IntOfTerm (YAP_ArgOfTerm (2, var));
int evidence = (int) YAP_IntOfTerm (YAP_ArgOfTerm (3, var));
YAP_Term parentL = YAP_ArgOfTerm (4, var);
unsigned distId = (unsigned) YAP_IntOfTerm (YAP_ArgOfTerm (5, var));
parents.push_back (VarIds());
while (parentL != YAP_TermNil()) {
unsigned parentId = (unsigned) YAP_IntOfTerm (YAP_HeadOfTerm (parentL));
parents.back().push_back (parentId);
parentL = YAP_TailOfTerm (parentL);
if (factorsType == "bayes") {
fg->setFromBayesNetwork();
}
assert (bn->getBayesNode (vid) == 0);
BayesNode* newNode = new BayesNode (
vid, dsize, evidence, Params(), distId);
bn->addNode (newNode);
varList = YAP_TailOfTerm (varList);
fg->setIndexes();
YAP_Term evidenceList = YAP_ARG3;
while (evidenceList != YAP_TermNil()) {
YAP_Term evTerm = YAP_HeadOfTerm (evidenceList);
unsigned vid = (unsigned) YAP_IntOfTerm ((YAP_ArgOfTerm (1, evTerm)));
unsigned ev = (unsigned) YAP_IntOfTerm ((YAP_ArgOfTerm (2, evTerm)));
cout << vid << " == " << ev << endl;
assert (fg->getFgVarNode (vid));
fg->getFgVarNode (vid)->setEvidence (ev);
evidenceList = YAP_TailOfTerm (evidenceList);
}
const BnNodeSet& nodes = bn->getBayesNodes();
for (unsigned i = 0; i < nodes.size(); i++) {
BnNodeSet ps;
for (unsigned j = 0; j < parents[i].size(); j++) {
assert (bn->getBayesNode (parents[i][j]) != 0);
ps.push_back (bn->getBayesNode (parents[i][j]));
}
nodes[i]->setParents (ps);
}
bn->setIndexes();
*/
YAP_Int p = (YAP_Int) (bn);
return YAP_Unify (YAP_MkIntTerm (p), YAP_ARG2);
YAP_Int p = (YAP_Int) (fg);
return YAP_Unify (YAP_MkIntTerm (p), YAP_ARG4);
}
@ -354,72 +331,33 @@ runLiftedSolver (void)
void runVeSolver (FactorGraph* fg, const vector<VarIds>& tasks,
vector<Params>& results);
void runBpSolver (FactorGraph* fg, const vector<VarIds>& tasks,
vector<Params>& results);
int
runGroundSolver (void)
{
BayesNet* bn = (BayesNet*) YAP_IntOfTerm (YAP_ARG1);
YAP_Term taskList = YAP_ARG2;
FactorGraph* fg = (FactorGraph*) YAP_IntOfTerm (YAP_ARG1);
vector<VarIds> tasks;
std::set<VarId> vids;
YAP_Term taskList = YAP_ARG2;
while (taskList != YAP_TermNil()) {
VarIds queryVars;
YAP_Term jointList = YAP_HeadOfTerm (taskList);
while (jointList != YAP_TermNil()) {
VarId vid = (unsigned) YAP_IntOfTerm (YAP_HeadOfTerm (jointList));
assert (bn->getBayesNode (vid));
queryVars.push_back (vid);
vids.insert (vid);
jointList = YAP_TailOfTerm (jointList);
}
tasks.push_back (queryVars);
tasks.push_back (readUnsignedList (YAP_HeadOfTerm (taskList)));
taskList = YAP_TailOfTerm (taskList);
}
Solver* bpSolver = 0;
GraphicalModel* graphicalModel = 0;
CFactorGraph::checkForIdenticalFactors = false;
if (Globals::infAlgorithm != InfAlgorithms::VE) {
BayesNet* mrn = bn->getMinimalRequesiteNetwork (
VarIds (vids.begin(), vids.end()));
if (Globals::infAlgorithm == InfAlgorithms::BN_BP) {
graphicalModel = mrn;
bpSolver = new BnBpSolver (*static_cast<BayesNet*> (graphicalModel));
} else if (Globals::infAlgorithm == InfAlgorithms::FG_BP) {
graphicalModel = new FactorGraph (*mrn);
bpSolver = new FgBpSolver (*static_cast<FactorGraph*> (graphicalModel));
delete mrn;
} else if (Globals::infAlgorithm == InfAlgorithms::CBP) {
graphicalModel = new FactorGraph (*mrn);
bpSolver = new CbpSolver (*static_cast<FactorGraph*> (graphicalModel));
delete mrn;
}
bpSolver->runSolver();
}
fg->printGraphicalModel();
vector<Params> results;
results.reserve (tasks.size());
for (unsigned i = 0; i < tasks.size(); i++) {
if (Globals::infAlgorithm == InfAlgorithms::VE) {
BayesNet* mrn = bn->getMinimalRequesiteNetwork (tasks[i]);
VarElimSolver* veSolver = new VarElimSolver (*mrn);
if (tasks[i].size() == 1) {
results.push_back (veSolver->getPosterioriOf (tasks[i][0]));
runVeSolver (fg, tasks, results);
} else {
results.push_back (veSolver->getJointDistributionOf (tasks[i]));
runBpSolver (fg, tasks, results);
}
delete mrn;
delete veSolver;
} else {
if (tasks[i].size() == 1) {
results.push_back (bpSolver->getPosterioriOf (tasks[i][0]));
} else {
results.push_back (bpSolver->getJointDistributionOf (tasks[i]));
}
}
}
delete bpSolver;
delete graphicalModel;
cout << "results: " << results << endl;
YAP_Term list = YAP_TermNil();
for (int i = results.size() - 1; i >= 0; i--) {
const Params& beliefs = results[i];
@ -433,12 +371,77 @@ runGroundSolver (void)
}
list = YAP_MkPairTerm (queryBeliefsL, list);
}
return YAP_Unify (list, YAP_ARG3);
}
void runVeSolver (
FactorGraph* fg,
const vector<VarIds>& tasks,
vector<Params>& results)
{
results.reserve (tasks.size());
for (unsigned i = 0; i < tasks.size(); i++) {
FactorGraph* mfg = fg;
if (fg->isFromBayesNetwork()) {
mfg = BayesBall::getMinimalFactorGraph (*fg, tasks[i]);
}
VarElimSolver solver (*mfg);
if (tasks[i].size() == 1) {
results.push_back (solver.getPosterioriOf (tasks[i][0]));
} else {
results.push_back (solver.getJointDistributionOf (tasks[i]));
}
if (fg->isFromBayesNetwork()) {
delete mfg;
}
}
}
void runBpSolver (
FactorGraph* fg,
const vector<VarIds>& tasks,
vector<Params>& results)
{
std::set<VarId> vids;
for (unsigned i = 0; i < tasks.size(); i++) {
Util::addToSet (vids, tasks[i]);
}
Solver* solver = 0;
FactorGraph* mfg = fg;
if (fg->isFromBayesNetwork()) {
mfg = BayesBall::getMinimalFactorGraph (
*fg, VarIds (vids.begin(),vids.end()));
}
if (Globals::infAlgorithm == InfAlgorithms::FG_BP) {
solver = new FgBpSolver (*mfg);
} else if (Globals::infAlgorithm == InfAlgorithms::CBP) {
CFactorGraph::checkForIdenticalFactors = false;
solver = new CbpSolver (*mfg);
} else {
cerr << "error: unknow solver" << endl;
abort();
}
solver->runSolver();
results.reserve (tasks.size());
for (unsigned i = 0; i < tasks.size(); i++) {
if (tasks[i].size() == 1) {
results.push_back (solver->getPosterioriOf (tasks[i][0]));
} else {
results.push_back (solver->getJointDistributionOf (tasks[i]));
}
}
if (fg->isFromBayesNetwork()) {
delete mfg;
}
delete solver;
}
int
setParfactorsParams (void)
{
@ -621,7 +624,7 @@ extern "C" void
init_predicates (void)
{
YAP_UserCPredicate ("create_lifted_network", createLiftedNetwork, 3);
YAP_UserCPredicate ("create_ground_network", createGroundNetwork, 3);
YAP_UserCPredicate ("create_ground_network", createGroundNetwork, 4);
YAP_UserCPredicate ("run_lifted_solver", runLiftedSolver, 3);
YAP_UserCPredicate ("run_ground_solver", runGroundSolver, 3);
YAP_UserCPredicate ("set_parfactors_params", setParfactorsParams, 2);

4
packages/CLPBN/clpbn/bp/Indexer.h
View File

@ -37,8 +37,8 @@ class StatesIndexer
indices_.resize (vars.size(), 0);
ranges_.reserve (vars.size());
for (unsigned i = 0; i < vars.size(); i++) {
ranges_.push_back (vars[i]->nrStates());
size_ *= vars[i]->nrStates();
ranges_.push_back (vars[i]->range());
size_ *= vars[i]->range();
}
li_ = 0;
if (calcOffsets) {

4
packages/CLPBN/clpbn/bp/Makefile.in
View File

@ -47,6 +47,7 @@ CWD=$(PWD)
HEADERS = \
$(srcdir)/GraphicalModel.h \
$(srcdir)/BayesNet.h \
$(srcdir)/BayesBall.h \
$(srcdir)/BayesNode.h \
$(srcdir)/ElimGraph.h \
$(srcdir)/FactorGraph.h \
@ -73,6 +74,7 @@ HEADERS = \
CPP_SOURCES = \
$(srcdir)/BayesNet.cpp \
$(srcdir)/BayesBall.cpp \
$(srcdir)/BayesNode.cpp \
$(srcdir)/ElimGraph.cpp \
$(srcdir)/FactorGraph.cpp \
@ -98,6 +100,7 @@ CPP_SOURCES = \
OBJS = \
BayesNet.o \
BayesBall.o \
BayesNode.o \
ElimGraph.o \
FactorGraph.o \
@ -121,6 +124,7 @@ OBJS = \
HCLI_OBJS = \
BayesNet.o \
BayesBall.o \
BayesNode.o \
ElimGraph.o \
FactorGraph.o \

14
packages/CLPBN/clpbn/bp/Util.h
View File

@ -5,6 +5,7 @@
#include <cassert>
#include <limits>
#include <algorithm>
#include <vector>
#include <set>
#include <queue>
@ -22,6 +23,8 @@ namespace Util {
template <typename T> void addToVector (vector<T>&, const vector<T>&);
template <typename T> void addToSet (set<T>&, const vector<T>&);
template <typename T> void addToQueue (queue<T>&, const vector<T>&);
template <typename T> bool contains (const vector<T>&, const T&);
@ -83,6 +86,14 @@ Util::addToVector (vector<T>& v, const vector<T>& elements)
template <typename T> void
Util::addToSet (set<T>& s, const vector<T>& elements)
{
s.insert (elements.begin(), elements.end());
}
template <typename T> void
Util::addToQueue (queue<T>& q, const vector<T>& elements)
{
@ -110,8 +121,7 @@ Util::contains (const set<T>& s, const T& e)
template <typename K, typename V> bool
Util::contains (
const unordered_map<K, V>& m, const K& k)
Util::contains (const unordered_map<K, V>& m, const K& k)
{
return m.find (k) != m.end();
}

43
packages/CLPBN/clpbn/bp/VarElimSolver.cpp
View File

@ -6,17 +6,8 @@
#include "Util.h"
VarElimSolver::VarElimSolver (const BayesNet& bn) : Solver (&bn)
{
bayesNet_ = &bn;
factorGraph_ = new FactorGraph (bn);
}
VarElimSolver::VarElimSolver (const FactorGraph& fg) : Solver (&fg)
{
bayesNet_ = 0;
factorGraph_ = &fg;
}
@ -24,9 +15,7 @@ VarElimSolver::VarElimSolver (const FactorGraph& fg) : Solver (&fg)
VarElimSolver::~VarElimSolver (void)
{
if (bayesNet_) {
delete factorGraph_;
}
delete factorList_.back();
}
@ -37,7 +26,7 @@ VarElimSolver::getPosterioriOf (VarId vid)
assert (factorGraph_->getFgVarNode (vid));
FgVarNode* vn = factorGraph_->getFgVarNode (vid);
if (vn->hasEvidence()) {
Params params (vn->nrStates(), 0.0);
Params params (vn->range(), 0.0);
params[vn->getEvidence()] = 1.0;
return params;
}
@ -53,14 +42,13 @@ VarElimSolver::getJointDistributionOf (const VarIds& vids)
varFactors_.clear();
elimOrder_.clear();
createFactorList();
introduceEvidence();
chooseEliminationOrder (vids);
absorveEvidence();
findEliminationOrder (vids);
processFactorList (vids);
Params params = factorList_.back()->params();
if (Globals::logDomain) {
Util::fromLog (params);
}
delete factorList_.back();
return params;
}
@ -89,7 +77,7 @@ VarElimSolver::createFactorList (void)
void
VarElimSolver::introduceEvidence (void)
VarElimSolver::absorveEvidence (void)
{
const FgVarSet& varNodes = factorGraph_->getVarNodes();
for (unsigned i = 0; i < varNodes.size(); i++) {
@ -107,26 +95,15 @@ VarElimSolver::introduceEvidence (void)
}
}
}
printActiveFactors();
}
void
VarElimSolver::chooseEliminationOrder (const VarIds& vids)
VarElimSolver::findEliminationOrder (const VarIds& vids)
{
if (bayesNet_) {
ElimGraph graph (*bayesNet_);
elimOrder_ = graph.getEliminatingOrder (vids);
} else {
const FgVarSet& varNodes = factorGraph_->getVarNodes();
for (unsigned i = 0; i < varNodes.size(); i++) {
VarId vid = varNodes[i]->varId();
if (Util::contains (vids, vid) == false &&
varNodes[i]->hasEvidence() == false) {
elimOrder_.push_back (vid);
}
}
}
elimOrder_ = ElimGraph::getEliminationOrder (factorList_, vids);
}
@ -165,7 +142,6 @@ void
VarElimSolver::eliminate (VarId elimVar)
{
Factor* result = 0;
FgVarNode* vn = factorGraph_->getFgVarNode (elimVar);
vector<unsigned>& idxs = varFactors_.find (elimVar)->second;
for (unsigned i = 0; i < idxs.size(); i++) {
unsigned idx = idxs[i];
@ -180,7 +156,7 @@ VarElimSolver::eliminate (VarId elimVar)
}
}
if (result != 0 && result->nrArguments() != 1) {
result->sumOut (vn->varId());
result->sumOut (elimVar);
factorList_.push_back (result);
const VarIds& resultVarIds = result->arguments();
for (unsigned i = 0; i < resultVarIds.size(); i++) {
@ -199,7 +175,6 @@ VarElimSolver::printActiveFactors (void)
for (unsigned i = 0; i < factorList_.size(); i++) {
if (factorList_[i] != 0) {
factorList_[i]->print();
cout << endl;
}
}
}

8
packages/CLPBN/clpbn/bp/VarElimSolver.h
View File

@ -5,7 +5,6 @@
#include "Solver.h"
#include "FactorGraph.h"
#include "BayesNet.h"
#include "Horus.h"
@ -15,8 +14,6 @@ using namespace std;
class VarElimSolver : public Solver
{
public:
VarElimSolver (const BayesNet&);
VarElimSolver (const FactorGraph&);
~VarElimSolver (void);
@ -30,9 +27,9 @@ class VarElimSolver : public Solver
private:
void createFactorList (void);
void introduceEvidence (void);
void absorveEvidence (void);
void chooseEliminationOrder (const VarIds&);
void findEliminationOrder (const VarIds&);
void processFactorList (const VarIds&);
@ -40,7 +37,6 @@ class VarElimSolver : public Solver
void printActiveFactors (void);
const BayesNet* bayesNet_;
const FactorGraph* factorGraph_;
vector<Factor*> factorList_;
VarIds elimOrder_;

16
packages/CLPBN/clpbn/bp/VarNode.cpp
View File

@ -10,19 +10,19 @@ using namespace std;
VarNode::VarNode (const VarNode* v)
{
varId_ = v->varId();
nrStates_ = v->nrStates();
range_ = v->range();
evidence_ = v->getEvidence();
index_ = std::numeric_limits<unsigned>::max();
}
VarNode::VarNode (VarId varId, unsigned nrStates, int evidence)
VarNode::VarNode (VarId varId, unsigned range, int evidence)
{
assert (nrStates != 0);
assert (evidence < (int) nrStates);
assert (range != 0);
assert (evidence < (int) range);
varId_ = varId;
nrStates_ = nrStates;
range_ = range;
evidence_ = evidence;
index_ = std::numeric_limits<unsigned>::max();
}
@ -32,7 +32,7 @@ VarNode::VarNode (VarId varId, unsigned nrStates, int evidence)
bool
VarNode::isValidState (int stateIndex)
{
return stateIndex >= 0 && stateIndex < (int) nrStates_;
return stateIndex >= 0 && stateIndex < (int) range_;
}
@ -49,7 +49,7 @@ VarNode::isValidState (const string& stateName)
void
VarNode::setEvidence (int ev)
{
assert (ev < (int) nrStates_);
assert (ev < (int) range_);
evidence_ = ev;
}
@ -90,7 +90,7 @@ VarNode::states (void) const
return GraphicalModel::getVarInformation (varId_).states;
}
States states;
for (unsigned i = 0; i < nrStates_; i++) {
for (unsigned i = 0; i < range_; i++) {
stringstream ss;
ss << i ;
states.push_back (ss.str());

10
packages/CLPBN/clpbn/bp/VarNode.h
View File

@ -20,7 +20,7 @@ class VarNode
unsigned varId (void) const { return varId_; }
unsigned nrStates (void) const { return nrStates_; }
unsigned range (void) const { return range_; }
int getEvidence (void) const { return evidence_; }
@ -37,15 +37,13 @@ class VarNode
bool operator== (const VarNode& var) const
{
cout << "equal operator called" << endl;
assert (!(varId_ == var.varId() && nrStates_ != var.nrStates()));
assert (!(varId_ == var.varId() && range_ != var.range()));
return varId_ == var.varId();
}
bool operator!= (const VarNode& var) const
{
cout << "diff operator called" << endl;
assert (!(varId_ == var.varId() && nrStates_ != var.nrStates()));
assert (!(varId_ == var.varId() && range_ != var.range()));
return varId_ != var.varId();
}
@ -63,7 +61,7 @@ class VarNode
private:
VarId varId_;
unsigned nrStates_;
unsigned range_;
int evidence_;
unsigned index_;

44
packages/CLPBN/clpbn/bp/examples/burglary-alarm.yap
View File

@ -1,29 +1,41 @@
:- use_module(library(clpbn)).
:- use_module(library(pfl)).
:- set_clpbn_flag(solver, bp).
%:- set_pfl_flag(solver,ve).
:- set_pfl_flag(solver,bp), clpbn_horus:set_horus_flag(inf_alg,ve).
%:- set_pfl_flag(solver,bp), clpbn_horus:set_horus_flag(inf_alg,fg_bp).
%:- set_pfl_flag(solver,fove).
r(R) :- r_cpt(RCpt),
{ R = r with p([r1, r2], RCpt) }.
% :- yap_flag(write_strings, off).
t(T) :- t_cpt(TCpt),
{ T = t with p([t1, t2], TCpt) }.
a(A) :- r(R), t(T), a_cpt(ACpt),
{ A = a with p([a1, a2], ACpt, [R, T]) }.
bayes burglary::[b1,b3] ; [0.001, 0.999] ; [].
j(J) :- a(A), j_cpt(JCpt),
{ J = j with p([j1, j2], JCpt, [A]) }.
bayes earthquake::[e1,e2] ; [0.002, 0.998]; [].
m(M) :- a(A), m_cpt(MCpt),
{ M = m with p([m1, m2], MCpt, [A]) }.
bayes alarm::[a1,a2] , burglary, earthquake ; [0.95, 0.94, 0.29, 0.001, 0.05, 0.06, 0.71, 0.999] ; [].
bayes john_calls::[j1,j2] , alarm ; [0.9, 0.05, 0.1, 0.95] ; [].
bayes mary_calls::[m1,m2] , alarm ; [0.7, 0.01, 0.3, 0.99] ; [].
b_cpt([0.001, 0.999]).
e_cpt([0.002, 0.998]).
r_cpt([0.001, 0.999]).
t_cpt([0.002, 0.998]).
a_cpt([0.95, 0.94, 0.29, 0.001,
0.05, 0.06, 0.71, 0.999]).
j_cpt([0.9, 0.05,
jc_cpt([0.9, 0.05,
0.1, 0.95]).
m_cpt([0.7, 0.01,
mc_cpt([0.7, 0.01,
0.3, 0.99]).
% ?- alarm(A).
?- john_calls(J), mary_calls(m1).
%?- john_calls(J), mary_calls(m1), alarm(a1).
%?- john_calls(J), alarm(a1).

17
packages/CLPBN/clpbn/bp/examples/smokers.yap
View File

@ -2,19 +2,19 @@
:- use_module(library(pfl)).
%:- set_pfl_flag(solver,ve).
:- set_pfl_flag(solver,bp), clpbn_bp:set_horus_flag(inf_alg,ve).
:- set_pfl_flag(solver,bp), clpbn_horus:set_horus_flag(inf_alg,ve).
% :- set_pfl_flag(solver,fove).
:- yap_flag(write_strings, off).
friendly(P1, P2) :-
friends(P1, P2) :-
person(P1),
person(P2),
P1 @> P2.
P1 \= P2.
person(john).
person(maggie).
person(harry).
%person(harry).
%person(bill).
%person(matt).
%person(diana).
@ -27,8 +27,13 @@ person(harry).
markov smokes(P)::[t,f] , cancer(P)::[t,f] ; [0.1, 0.2, 0.3, 0.4] ; [person(P)].
markov friend(P1,P2)::[t,f], smokes(P1)::[t,f], smokes(P2)::[t,f] ; [0.5, 0.6, 0.7, 0.8, 0.5, 0.6, 0.7, 0.8] ; [friendly(P1, P2)].
markov friend(P1,P2)::[t,f], smokes(P1)::[t,f], smokes(P2)::[t,f] ; [0.5, 0.6, 0.7, 0.8, 0.5, 0.6, 0.7, 0.8] ; [friends(P1, P2)].
% ?- smokes(person_0, t), smokes(person_1, t), friend(person_0, person_1, F).
?- smokes(john, t), smokes(maggie, f), friend(john, maggie, X).
% ?- smokes(john, t), smokes(maggie, f), friend(john, maggie, X).
?- smokes(john, t), friend(john, maggie, X).
% ?- friend(john, maggie, X).

2
packages/CLPBN/clpbn/horus.yap
View File

@ -7,7 +7,7 @@
:- module(clpbn_horus,
[create_lifted_network/3,
create_ground_network/3,
create_ground_network/4,
set_parfactors_params/2,
set_bayes_net_params/2,
run_lifted_solver/3,