CGraph* CreateGraphWithPyramidSpecific(int& num_nodes, int num_indep_nodes,
int num_layers)
{
PNL_CHECK_LEFT_BORDER( num_indep_nodes, 1 );
PNL_CHECK_LEFT_BORDER( num_layers, 1 );
int i, j, k;
CGraph *pGraph = CGraph::Create(0, NULL, NULL, NULL);
PNL_CHECK_IF_MEMORY_ALLOCATED( pGraph );
srand((unsigned int)time(NULL));
num_nodes = num_indep_nodes;
int num_nodes_into_curr_layer = num_indep_nodes;
for (i = 0; i < num_layers - 1; i++)
{
num_nodes += num_nodes_into_curr_layer * 2 + 1;
num_nodes_into_curr_layer = num_nodes_into_curr_layer * 2 + 1;
}
pGraph->AddNodes(num_nodes);
int StartParent = 0,
EndParent = num_indep_nodes - 1,
StartCurrLayer,
EndCurrLayer;
int Child1,
Child2,
Child3;
int NumParents;
for (int layer = 0; layer < num_layers - 1; layer++ )
{
StartCurrLayer = EndParent + 1;
EndCurrLayer = StartCurrLayer + 2 * (EndParent - StartParent + 1);
NumParents = 0;
for (j = StartParent; j <= EndParent; j++ )
{
Child1 = EndParent + NumParents * 2 + 1;
Child2 = EndParent + NumParents * 2 + 2;
Child3 = EndParent + NumParents * 2 + 3;
pGraph->AddEdge(j, Child1, 1);
pGraph->AddEdge(j, Child2, 1);
pGraph->AddEdge(j, Child3, 1);
NumParents++;
}
StartParent = StartCurrLayer;
EndParent = EndCurrLayer;
}
return pGraph;
}
CGraph* CreateGraphWithRegularGridSpecific(int& num_nodes, int width,
int height, int num_layers)
{
PNL_CHECK_LEFT_BORDER( width, 2 );
PNL_CHECK_LEFT_BORDER( height, 2 );
PNL_CHECK_LEFT_BORDER( num_layers, 1 );
int i, j, k;
CGraph *pGraph = CGraph::Create(0, NULL, NULL, NULL);
PNL_CHECK_IF_MEMORY_ALLOCATED( pGraph );
srand((unsigned int)time(NULL));
int num_nodes_one_layer = width * height;
num_nodes = num_nodes_one_layer * num_layers;
pGraph->AddNodes(num_nodes);
for (i = 0; i < num_layers; i++)
{
for (j = 1; j < width; j++)
pGraph->AddEdge(
i * num_nodes_one_layer + j - 1,
i * num_nodes_one_layer + j, 1);
for (k = 1; k < height; k++)
pGraph->AddEdge(
i * num_nodes_one_layer + (k - 1) * width,
i * num_nodes_one_layer + k * width, 1);
for (j = 1; j < width; j++)
for (k = 1; k < height; k++)
{
pGraph->AddEdge(
i * num_nodes_one_layer + (k - 1) * width + j,
i * num_nodes_one_layer + k * width + j, 1);
pGraph->AddEdge(
i * num_nodes_one_layer + k * width + j - 1,
i * num_nodes_one_layer + k * width + j, 1);
}
if (i)
{
for (j = 0; j < width; j++)
for (k = 0; k < height; k++)
pGraph->AddEdge(
(i - 1) * num_nodes_one_layer + k * width + j,
i * num_nodes_one_layer + k * width + j, 1);
}
}
return pGraph;
}
CGraph* CreateCompleteGraph(int num_nodes)
{
PNL_CHECK_LEFT_BORDER( num_nodes, 1 );
int i, j, k;
CGraph *pGraph = CGraph::Create(0, NULL, NULL, NULL);
PNL_CHECK_IF_MEMORY_ALLOCATED( pGraph );
srand((unsigned int)time(NULL));
pGraph->AddNodes(num_nodes);
for (j = 1; j < num_nodes; j++ )
for (i = 0; i < j; i++ )
pGraph->AddEdge(i, j, 1);
return pGraph;
}
CGraph* CreateRandomGraphWithToyQMRSpecific(int num_nodes,
int num_indep_nodes, int max_size_family)
{
PNL_CHECK_LEFT_BORDER( num_nodes, 10 );
PNL_CHECK_RANGES( num_indep_nodes, 1, num_nodes-1 );
PNL_CHECK_RANGES( max_size_family, 2, num_nodes );
int i, j, k;
CGraph *pGraph = CGraph::Create(0, NULL, NULL, NULL);
PNL_CHECK_IF_MEMORY_ALLOCATED( pGraph );
srand((unsigned int)time(NULL));
pGraph->AddNodes(num_nodes);
int num_parents;
int ind_parent;
intVector prev_nodes(0);
for ( i = num_indep_nodes; i < num_nodes; i++)
{
prev_nodes.resize(0);
for ( j = 0; j < num_indep_nodes; j++)
prev_nodes.push_back(j);
num_parents = rand() % (max_size_family - 1);
num_parents += 1;
num_parents = (num_parents > i) ? i : num_parents;
for ( j = 0; j < num_parents; j++)
{
ind_parent = rand() % prev_nodes.size();
pGraph->AddEdge(prev_nodes[ind_parent], i, 1);
prev_nodes.erase(prev_nodes.begin() + ind_parent);
}
}
return pGraph;
}
CGraph* CreateRandomAndSpecificForIDNetGraph(int num_nodes,
int num_indep_nodes, int max_size_family)
{
PNL_CHECK_LEFT_BORDER(num_nodes, 10);
PNL_CHECK_RANGES(num_indep_nodes, 1, num_nodes-1);
PNL_CHECK_RANGES(max_size_family, 2, num_nodes);
int i, j, k;
CGraph *pGraph = CGraph::Create(0, NULL, NULL, NULL);
PNL_CHECK_IF_MEMORY_ALLOCATED(pGraph);
srand((unsigned int)time(NULL));
pGraph->AddNodes(num_nodes);
int num_parents;
int ind_parent;
intVector prev_nodes(0);
for (i = num_indep_nodes; i < num_nodes; i++)
{
prev_nodes.resize(0);
for (j = 0; j < i; j++)
prev_nodes.push_back(j);
num_parents = rand() % (max_size_family - 1);
num_parents += 1;
num_parents = (num_parents > i) ? i : num_parents;
for (j = 0; j < num_parents; j++)
{
ind_parent = rand() % prev_nodes.size();
pGraph->AddEdge(prev_nodes[ind_parent], i, 1);
prev_nodes.erase(prev_nodes.begin() + ind_parent);
}
}
intVector parents(0);
intVector childs(0);
for (i = 0; i < num_nodes; i++)
{
if (pGraph->GetNumberOfChildren(i) == 0)
{
pGraph->GetParents(i, &parents);
for (j = 0; j < parents.size(); j++)
{
pGraph->GetChildren(parents[j], &childs);
for (k = 0; k < childs.size(); k++)
if ((childs[k] != i) &&
(pGraph->GetNumberOfChildren(childs[k]) == 0) &&
(pGraph->GetNumberOfParents(childs[k]) == 1))
{
if (i < childs[k])
{
pGraph->RemoveEdge(parents[j], childs[k]);
pGraph->AddEdge(i, childs[k], 1);
}
else
{
pGraph->AddEdge(childs[k], i, 1);
}
}
}
}
}
return pGraph;
}
CIDNet* CreateLIMIDWith2DecInClick()
{
const int nnodes = 7;
const int numberOfNodeTypes = 7;
int i;
CGraph *pGraph = CGraph::Create(0, NULL, NULL, NULL);
pGraph->AddNodes(nnodes);
pGraph->AddEdge(0,1,1);
pGraph->AddEdge(2,3,1);
pGraph->AddEdge(1,4,1);
pGraph->AddEdge(3,4,1);
pGraph->AddEdge(1,5,1);
pGraph->AddEdge(4,6,1);
CNodeType *nodeTypes = new CNodeType [numberOfNodeTypes];
nodeTypes[0].SetType(1, 2, nsChance);
nodeTypes[1].SetType(1, 2, nsDecision);
nodeTypes[2].SetType(1, 2, nsChance);
nodeTypes[3].SetType(1, 2, nsDecision);
nodeTypes[4].SetType(1, 2, nsChance);
nodeTypes[5].SetType(1, 1, nsValue);
nodeTypes[6].SetType(1, 1, nsValue);
int *nodeAssociation = new int[nnodes];
for (i = 0; i < nnodes; i++)
{
nodeAssociation[i] = i;
}
CIDNet *pIDNet = CIDNet::Create(nnodes, numberOfNodeTypes, nodeTypes,
nodeAssociation, pGraph);
CModelDomain* pMD = pIDNet->GetModelDomain();
CFactor **myParams = new CFactor*[nnodes];
int *nodeNumbers = new int [nnodes];
int domain0[] = { 0 };
nodeNumbers[0] = 1;
int domain1[] = { 0, 1 };
nodeNumbers[1] = 2;
int domain2[] = { 2 };
nodeNumbers[2] = 1;
int domain3[] = { 2, 3 };
nodeNumbers[3] = 2;
int domain4[] = { 1, 3, 4 };
nodeNumbers[4] = 3;
int domain5[] = { 1, 5 };
nodeNumbers[5] = 2;
int domain6[] = { 4, 6 };
nodeNumbers[6] = 2;
int *domains[] = { domain0, domain1, domain2, domain3, domain4,
domain5, domain6 };
pIDNet->AllocFactors();
for (i = 0; i < nnodes; i++)
{
myParams[i] = CTabularCPD::Create(domains[i], nodeNumbers[i], pMD);
}
float data0[] = {0.200000f, 0.800000f};
float data1[] = {0.500000f, 0.500000f, 0.500000f, 0.500000f};
float data2[] = {0.600000f, 0.400000f};
float data3[] = {0.500000f, 0.500000f, 0.500000f, 0.500000f};
float data4[] = {0.500000f, 0.500000f, 0.100000f, 0.900000f, 0.800000f, 0.200000f, 0.020000f, 0.980000f};
float data5[] = {10000.000000f, -2000.000000f};
float data6[] = {-5000.000000f, 10000.000000f};
float *data[] = { data0, data1, data2, data3, data4,
data5, data6 };
for (i = 0; i < nnodes; i++)
{
myParams[i]->AllocMatrix(data[i], matTable);
pIDNet->AttachFactor(myParams[i]);
}
delete [] nodeTypes;
delete [] nodeAssociation;
return pIDNet;
}
PNL_USING
CIDNet* CreatePigsLIMID()
{
const int nnodes = 14;
const int numberOfNodeTypes = 14;
int i;
CGraph *pGraph = CGraph::Create(0, NULL, NULL, NULL);
pGraph->AddNodes(nnodes);
pGraph->AddEdge(0,1,1);
pGraph->AddEdge(0,3,1);
pGraph->AddEdge(1,2,1);
pGraph->AddEdge(2,3,1);
pGraph->AddEdge(3,4,1);
pGraph->AddEdge(3,6,1);
pGraph->AddEdge(4,5,1);
pGraph->AddEdge(5,6,1);
pGraph->AddEdge(6,7,1);
pGraph->AddEdge(6,9,1);
pGraph->AddEdge(7,8,1);
pGraph->AddEdge(8,9,1);
pGraph->AddEdge(2,10,1);
pGraph->AddEdge(5,11,1);
pGraph->AddEdge(8,12,1);
pGraph->AddEdge(9,13,1);
CNodeType *nodeTypes = new CNodeType [numberOfNodeTypes];
nodeTypes[0].SetType(1, 2, nsChance);
nodeTypes[1].SetType(1, 2, nsChance);
nodeTypes[2].SetType(1, 2, nsDecision);
nodeTypes[3].SetType(1, 2, nsChance);
nodeTypes[4].SetType(1, 2, nsChance);
nodeTypes[5].SetType(1, 2, nsDecision);
nodeTypes[6].SetType(1, 2, nsChance);
nodeTypes[7].SetType(1, 2, nsChance);
nodeTypes[8].SetType(1, 2, nsDecision);
nodeTypes[9].SetType(1, 2, nsChance);
nodeTypes[10].SetType(1, 1, nsValue);
nodeTypes[11].SetType(1, 1, nsValue);
nodeTypes[12].SetType(1, 1, nsValue);
nodeTypes[13].SetType(1, 1, nsValue);
int *nodeAssociation = new int[nnodes];
for (i = 0; i < nnodes; i++)
{
nodeAssociation[i] = i;
}
CIDNet *pIDNet = CIDNet::Create(nnodes, numberOfNodeTypes, nodeTypes,
nodeAssociation, pGraph);
CModelDomain* pMD = pIDNet->GetModelDomain();
CFactor **myParams = new CFactor*[nnodes];
int *nodeNumbers = new int [nnodes];
int domain0[] = { 0 };
nodeNumbers[0] = 1;
int domain1[] = { 0, 1 };
nodeNumbers[1] = 2;
int domain2[] = { 1, 2 };
nodeNumbers[2] = 2;
int domain3[] = { 2, 10 };
nodeNumbers[3] = 2;
int domain4[] = { 0, 2, 3 };
nodeNumbers[4] = 3;
int domain5[] = { 3, 4 };
nodeNumbers[5] = 2;
int domain6[] = { 4, 5 };
nodeNumbers[6] = 2;
int domain7[] = { 5, 11 };
nodeNumbers[7] = 2;
int domain8[] = { 3, 5, 6 };
nodeNumbers[8] = 3;
int domain9[] = { 6, 7 };
nodeNumbers[9] = 2;
int domain10[] = { 7, 8 };
nodeNumbers[10] = 2;
int domain11[] = { 8, 12 };
nodeNumbers[11] = 2;
int domain12[] = { 6, 8, 9 };
nodeNumbers[12] = 3;
int domain13[] = { 9, 13 };
nodeNumbers[13] = 2;
int *domains[] = { domain0, domain1, domain2, domain3, domain4,
domain5, domain6, domain7, domain8, domain9, domain10, domain11,
domain12, domain13 };
pIDNet->AllocFactors();
for (i = 0; i < nnodes; i++)
{
myParams[i] = CTabularCPD::Create(domains[i], nodeNumbers[i], pMD);
}
float data0[] = {0.900000f, 0.100000f};
float data1[] = {0.100000f, 0.900000f, 0.800000f, 0.200000f};
float data2[] = {0.500000f, 0.500000f, 0.500000f, 0.500000f};
float data3[] = {-100.000000f, 0.000000f};
float data4[] = {0.900000f, 0.100000f, 0.800000f, 0.200000f, 0.500000f, 0.500000f, 0.100000f, 0.900000f};
float data5[] = {0.100000f, 0.900000f, 0.800000f, 0.200000f};
float data6[] = {0.500000f, 0.500000f, 0.500000f, 0.500000f};
float data7[] = {-100.000000f, 0.000000f};
float data8[] = {0.900000f, 0.100000f, 0.800000f, 0.200000f, 0.500000f, 0.500000f, 0.100000f, 0.900000f};
float data9[] = {0.100000f, 0.900000f, 0.800000f, 0.200000f};
float data10[] = {0.500000f, 0.500000f, 0.500000f, 0.500000f};
float data11[] = {-100.000000f, 0.000000f};
float data12[] = {0.900000f, 0.100000f, 0.800000f, 0.200000f, 0.500000f, 0.500000f, 0.100000f, 0.900000f};
float data13[] = {1000.000000f, 300.000000f};
float *data[] = { data0, data1, data2, data3, data4,
data5, data6, data7, data8, data9,
data10, data11, data12, data13 };
for (i = 0; i < nnodes; i++)
{
myParams[i]->AllocMatrix(data[i], matTable);
pIDNet->AttachFactor(myParams[i]);
}
delete [] nodeTypes;
delete [] nodeAssociation;
return pIDNet;
}
void CBICLearningEngine::Learn()
{
CEMLearningEngine *pLearn = NULL;
float resultBIC = -FLT_MAX;
CBNet *pResultBNet = NULL;
intVector resultOrder;
pEvidencesVector pEv(m_Vector_pEvidences.size(), NULL );
CModelDomain *pMD = m_pGrModel->GetModelDomain();
int nnodes = m_pGrModel->GetNumberOfNodes();
nodeTypeVector varTypes;
pMD->GetVariableTypes(&varTypes);
intVector varAss( pMD->GetVariableAssociations(), pMD->GetVariableAssociations() + nnodes );
intVector currentAssociation(nnodes);
intVector currentObsNodes(nnodes);
int i;
for( i = 0; i < nnodes; i++ )
{
currentObsNodes[i] = i;
}
CGraph *pGraph = CGraph::Create(nnodes, NULL, NULL, NULL);
CBNet *pBNet;
int lineSz = int( nnodes * ( nnodes - 1 ) / 2 );
intVecVector connect;
intVector indexes(lineSz, 0);
int startNode, endNode;
int ind;
for( ind = 0; ind < lineSz ; )
{
if( indexes[ind] == 1 )
{
FindNodesByNumber(&startNode, &endNode, nnodes, ind);
pGraph->RemoveEdge(startNode, endNode );
indexes[ind] = 0;
ind++;
}
else
{
FindNodesByNumber(&startNode, &endNode, nnodes, ind);
pGraph->AddEdge(startNode, endNode, 1 );
indexes[ind] = 1;
ind = 0;
connect.clear();
pGraph->GetConnectivityComponents(&connect);
if( connect.size() == 1 )
{
do
{
CGraph *pCopyGraph = CGraph::Copy(pGraph);
int j;
for( j = 0; j < nnodes; j++ )
{
currentAssociation[j] = varAss[currentObsNodes[j]];
}
pBNet = CBNet::Create(nnodes, varTypes, currentAssociation, pCopyGraph);
pBNet->AllocFactors();
for( j = 0; j < nnodes; j++ )
{
pBNet->AllocFactor( j );
pBNet->GetFactor(j)->CreateAllNecessaryMatrices();
}
int dimOfModel = DimOfModel(pBNet);
int k;
for( k = 0; k < pEv.size(); k++ )
{
valueVector vls;
m_Vector_pEvidences[k]->GetRawData(&vls);
pEv[k] = CEvidence::Create( pBNet->GetModelDomain(),currentObsNodes, vls );
}
pLearn = CEMLearningEngine::Create(pBNet);
pLearn->SetData(pEv.size(), &pEv.front());
pLearn->Learn();
int nsteps;
const float *score;
pLearn->GetCriterionValue(&nsteps, &score);
float log_lik = score[nsteps-1];
float BIC = log_lik - 0.5f*float( dimOfModel*log(float(pEv.size())) );
if( BIC >= resultBIC )
{
delete pResultBNet;
resultBIC = BIC;
m_critValue.push_back(BIC);
pResultBNet = pBNet;
resultOrder.assign( currentObsNodes.begin(), currentObsNodes.end() );
}
else
{
delete pBNet;
}
for( k = 0; k < pEv.size(); k++ )
{
delete pEv[k];
}
delete pLearn;
}while(std::next_permutation(currentObsNodes.begin(), currentObsNodes.end()));
}
}
}
delete pGraph;
m_pResultGrModel = pResultBNet;
m_resultRenaming.assign(resultOrder.begin(), resultOrder.end());
}
PNL_USING
int main()
{
int nnodes = 16;
int nodeslice = 8;
CBNet* pKjaerulf = pnlExCreateKjaerulfsBNet();
CDBN* pKj = CDBN::Create(pKjaerulf);
int nSeries = 50;
int nslices = 101;
int i;
intVector nS(nSeries);
for(i = 0; i < nSeries; i++)
{
nS[i] = nslices;
}
valueVector vValues;
vValues.resize(nodeslice);
intVector obsNodes(nodeslice);
for( i=0; i<nodeslice; i++)obsNodes[i] = i;
CEvidence ***pEv;
pEv = new CEvidence **[nSeries];
int series, slice, node, val;
FILE * fp;
fp = fopen("../Data/kjaerulff.dat", "r");
if( !fp )
{
std::cout<<"can't open cases file"<<std::endl;
exit(1);
}
for( series = 0; series < nSeries; series++ )
{
pEv[series] = new CEvidence*[ nslices ];
for( slice = 0; slice < nslices; slice++ )
{
for( node = 0; node < nodeslice; node++)
{
fscanf(fp, "%d,", &val);
vValues[node].SetFlt(val);
}
(pEv[series])[slice] = CEvidence::Create(pKj->GetModelDomain(), obsNodes, vValues );
}
}
fclose(fp);
CGraph *pGraph = CGraph::Create(nnodes, NULL, NULL, NULL);
for(i=0; i<nnodes-1; i++)
{
pGraph->AddEdge(i, i+1,1);
}
CNodeType *nodeTypes = new CNodeType[1];
nodeTypes[0].SetType(1, 2);
int *nodeAssociation = new int[nnodes];
for ( i = 0; i < nnodes; i++ )
{
nodeAssociation[i] = 0;
}
CBNet *pBnet = CBNet::Create( nnodes, 1, nodeTypes, nodeAssociation, pGraph );
pBnet -> AllocFactors();
floatVector data;
data.assign(64, 0.0f);
for ( node = 0; node < nnodes; node++ )
{
pBnet->AllocFactor( node );
(pBnet->GetFactor( node )) ->AllocMatrix( &data.front(), matTable );
}
CDBN* pDBN = CDBN::Create(pBnet);
CMlDynamicStructLearn *pLearn = CMlDynamicStructLearn::Create(pDBN, itDBNStructLearnML,
StructLearnHC, BIC, 4, 1, 30);
pLearn -> SetData(nSeries, &nS.front(), pEv);
// pLearn->SetLearnPriorSlice(true);
// pLearn->SetMinProgress((float)1e-4);
pLearn ->Learn();
const CDAG* pDAG = pLearn->GetResultDag();
pDAG->Dump();
////////////////////////////////////////////////////////////////////////////
delete pLearn;
delete pDBN;
delete pKj;
for(series = 0; series < nSeries; series++ )
{
for( slice = 0; slice < nslices; slice++ )
{
delete (pEv[series])[slice];
}
delete[] pEv[series];
}
delete[] pEv;
return 0;
}
int main()
{
int i, j;
CBNet* pAlarm = CreateAlarmBNet();
const int nnodes = pAlarm->GetNumberOfNodes();
pAlarm->GetGraph()->Dump();
CGraph *graph = CGraph::Create( nnodes, NULL, NULL, NULL );
for(i=0; i<nnodes-1; i++)
{
graph->AddEdge(i, i+1, 1);
}
CBNet *bnet = CBNet::CreateWithRandomMatrices( graph, pAlarm->GetModelDomain() );
int nEv = 50;
CEvidence **pEvidences = new CEvidence *[nEv];
int dataSize = nnodes;//summ all sizes
int* obs_nodes = new int[nnodes];
for(i=0; i<nnodes; i++)obs_nodes[i] = i;
//read data from file alarm.dat to evidences
FILE * fp = fopen("../../examples/Data/alarm.dat", "r");
if( !fp && !(fp = fopen("../../c_pgmtk/examples/Data/alarm.dat", "r")) )
{
std::cout<<"can't open cases file"<<std::endl;
exit(1);
}
valueVector input_data;
input_data.resize(dataSize);
for(i = 0 ; i < nEv; i++)
{
for (j = 0; j < dataSize ; j++)
{
int val;
fscanf(fp, "%d,", &val);
input_data[j].SetInt(val);
}
pEvidences[i] = CEvidence::Create(pAlarm, nnodes, obs_nodes, input_data);
}
fclose(fp);
intVector vA;
intVector vD;
CMlStaticStructLearn *pLearn = CMlStaticStructLearnHC::Create(bnet, itStructLearnML,
StructLearnHC, BIC, 5, vA, vD, 1);
pLearn->SetData(nEv, pEvidences);
pLearn->Learn();
// pLearn->CreateResultBNet(const_cast<CDAG*>(pLearn->GetResultDAG()));
// const CBNet* pBNet = pLearn->GetResultBNet();
///////////////////////////////////////////////////////////////////////////////
const CDAG* pDAG = pLearn->GetResultDAG();
CDAG* iDAG = CDAG::Create(*(pAlarm->GetGraph()));
int diff = iDAG->SymmetricDifference(pDAG);
pDAG->Dump();
delete pLearn;
delete iDAG;
delete[] obs_nodes;
delete pAlarm;
delete bnet;
for( i = 0; i < nEv; i++)
{
delete pEvidences[i];
}
return 1;
}
PNL_USING
CBNet* CreateAlarmBNet()
{
const int nnodes = 37;
const int numberOfNodeTypes = 37;
int i;
CGraph *pGraph = CGraph::Create(0, NULL, NULL, NULL);
pGraph->AddNodes(37);
pGraph->AddEdge(0,1,1);
pGraph->AddEdge(0,3,1);
pGraph->AddEdge(2,3,1);
pGraph->AddEdge(3,4,1);
pGraph->AddEdge(3,5,1);
pGraph->AddEdge(0,6,1);
pGraph->AddEdge(2,6,1);
pGraph->AddEdge(11,12,1);
pGraph->AddEdge(10,13,1);
pGraph->AddEdge(12,13,1);
pGraph->AddEdge(8,14,1);
pGraph->AddEdge(9,14,1);
pGraph->AddEdge(13,14,1);
pGraph->AddEdge(8,15,1);
pGraph->AddEdge(14,15,1);
pGraph->AddEdge(15,16,1);
pGraph->AddEdge(15,19,1);
pGraph->AddEdge(18,19,1);
pGraph->AddEdge(8,21,1);
pGraph->AddEdge(20,21,1);
pGraph->AddEdge(19,22,1);
pGraph->AddEdge(21,22,1);
pGraph->AddEdge(23,24,1);
pGraph->AddEdge(16,25,1);
pGraph->AddEdge(17,25,1);
pGraph->AddEdge(22,25,1);
pGraph->AddEdge(24,25,1);
pGraph->AddEdge(25,26,1);
pGraph->AddEdge(7,27,1);
pGraph->AddEdge(26,27,1);
pGraph->AddEdge(26,29,1);
pGraph->AddEdge(28,29,1);
pGraph->AddEdge(26,30,1);
pGraph->AddEdge(28,30,1);
pGraph->AddEdge(14,31,1);
pGraph->AddEdge(16,31,1);
pGraph->AddEdge(8,32,1);
pGraph->AddEdge(14,32,1);
pGraph->AddEdge(20,33,1);
pGraph->AddEdge(8,34,1);
pGraph->AddEdge(9,34,1);
pGraph->AddEdge(13,34,1);
pGraph->AddEdge(6,35,1);
pGraph->AddEdge(26,35,1);
pGraph->AddEdge(24,36,1);
pGraph->AddEdge(35,36,1);
CNodeType *nodeTypes = new CNodeType [37];
nodeTypes[0].SetType(1, 2);
nodeTypes[1].SetType(1, 2);
nodeTypes[2].SetType(1, 2);
nodeTypes[3].SetType(1, 3);
nodeTypes[4].SetType(1, 3);
nodeTypes[5].SetType(1, 3);
nodeTypes[6].SetType(1, 3);
nodeTypes[7].SetType(1, 2);
nodeTypes[8].SetType(1, 3);
nodeTypes[9].SetType(1, 2);
nodeTypes[10].SetType(1, 2);
nodeTypes[11].SetType(1, 3);
nodeTypes[12].SetType(1, 4);
nodeTypes[13].SetType(1, 4);
nodeTypes[14].SetType(1, 4);
nodeTypes[15].SetType(1, 4);
nodeTypes[16].SetType(1, 3);
nodeTypes[17].SetType(1, 2);
nodeTypes[18].SetType(1, 2);
nodeTypes[19].SetType(1, 3);
nodeTypes[20].SetType(1, 2);
nodeTypes[21].SetType(1, 2);
nodeTypes[22].SetType(1, 3);
nodeTypes[23].SetType(1, 2);
nodeTypes[24].SetType(1, 3);
nodeTypes[25].SetType(1, 2);
nodeTypes[26].SetType(1, 3);
nodeTypes[27].SetType(1, 3);
nodeTypes[28].SetType(1, 2);
nodeTypes[29].SetType(1, 3);
nodeTypes[30].SetType(1, 3);
nodeTypes[31].SetType(1, 4);
nodeTypes[32].SetType(1, 4);
nodeTypes[33].SetType(1, 3);
nodeTypes[34].SetType(1, 4);
nodeTypes[35].SetType(1, 3);
nodeTypes[36].SetType(1, 3);
int *nodeAssociation = new int[nnodes];
for ( i = 0; i < nnodes; i++ )
{
nodeAssociation[i] = i;
}
CBNet *pBNet = CBNet::Create( nnodes, numberOfNodeTypes, nodeTypes,
nodeAssociation, pGraph );
CModelDomain* pMD = pBNet->GetModelDomain();
//number of factors is the same as number of nodes - one CPD per node
CFactor **myParams = new CFactor*[nnodes];
int *nodeNumbers = new int [nnodes];
int domain0[] = { 0 };
nodeNumbers[0] = 1;
int domain1[] = { 0, 1 };
nodeNumbers[1] = 2;
int domain2[] = { 2 };
nodeNumbers[2] = 1;
int domain3[] = { 0, 2, 3 };
nodeNumbers[3] = 3;
int domain4[] = { 3, 4 };
nodeNumbers[4] = 2;
int domain5[] = { 3, 5 };
nodeNumbers[5] = 2;
int domain6[] = { 0, 2, 6 };
nodeNumbers[6] = 3;
int domain7[] = { 7 };
nodeNumbers[7] = 1;
int domain8[] = { 8 };
nodeNumbers[8] = 1;
int domain9[] = { 9 };
nodeNumbers[9] = 1;
int domain10[] = { 10 };
nodeNumbers[10] = 1;
int domain11[] = { 11 };
nodeNumbers[11] = 1;
int domain12[] = { 11, 12 };
nodeNumbers[12] = 2;
int domain13[] = { 10, 12, 13 };
nodeNumbers[13] = 3;
int domain14[] = { 8, 9, 13, 14 };
nodeNumbers[14] = 4;
int domain15[] = { 8, 14, 15 };
nodeNumbers[15] = 3;
int domain16[] = { 15, 16 };
nodeNumbers[16] = 2;
int domain17[] = { 17 };
nodeNumbers[17] = 1;
int domain18[] = { 18 };
nodeNumbers[18] = 1;
int domain19[] = { 15, 18, 19 };
nodeNumbers[19] = 3;
int domain20[] = { 20 };
nodeNumbers[20] = 1;
int domain21[] = { 8, 20, 21 };
nodeNumbers[21] = 3;
int domain22[] = { 19, 21, 22 };
nodeNumbers[22] = 3;
int domain23[] = { 23 };
nodeNumbers[23] = 1;
int domain24[] = { 23, 24 };
nodeNumbers[24] = 2;
int domain25[] = { 16, 17, 22, 24, 25 };
nodeNumbers[25] = 5;
int domain26[] = { 25, 26 };
nodeNumbers[26] = 2;
int domain27[] = { 7, 26, 27 };
nodeNumbers[27] = 3;
int domain28[] = { 28 };
nodeNumbers[28] = 1;
int domain29[] = { 26, 28, 29 };
nodeNumbers[29] = 3;
int domain30[] = { 26, 28, 30 };
nodeNumbers[30] = 3;
int domain31[] = { 14, 16, 31 };
nodeNumbers[31] = 3;
int domain32[] = { 8, 14, 32 };
nodeNumbers[32] = 3;
int domain33[] = { 20, 33 };
nodeNumbers[33] = 2;
int domain34[] = { 8, 9, 13, 34 };
nodeNumbers[34] = 4;
int domain35[] = { 6, 26, 35 };
nodeNumbers[35] = 3;
int domain36[] = { 24, 35, 36 };
nodeNumbers[36] = 3;
int *domains[] = { domain0, domain1, domain2, domain3, domain4,
domain5, domain6, domain7, domain8, domain9,
domain10, domain11, domain12, domain13, domain14,
domain15, domain16, domain17, domain18, domain19,
domain20, domain21, domain22, domain23, domain24,
domain25, domain26, domain27, domain28, domain29,
domain30, domain31, domain32, domain33, domain34,
domain35, domain36};
pBNet->AllocFactors();
for( i = 0; i < nnodes; i++ )
{
myParams[i] = CTabularCPD::Create( domains[i], nodeNumbers[i], pMD);
}
// data creation for all CPDs of the model
float data0[] = {0.050000f, 0.950000f};
float data1[] = {0.900000f, 0.100000f, 0.010000f, 0.990000f};
float data2[] = {0.200000f, 0.800000f};
float data3[] = {0.950000f, 0.040000f, 0.010000f, 0.980000f, 0.010000f, 0.010000f, 0.010000f, 0.090000f, 0.900000f, 0.050000f, 0.900000f, 0.050000f};
float data4[] = {0.950000f, 0.040000f, 0.010000f, 0.040000f, 0.950000f, 0.010000f, 0.010000f, 0.290000f, 0.700000f};
float data5[] = {0.950000f, 0.040000f, 0.010000f, 0.040000f, 0.950000f, 0.010000f, 0.010000f, 0.040000f, 0.950000f};
float data6[] = {0.980000f, 0.010000f, 0.010000f, 0.950000f, 0.040000f, 0.010000f, 0.500000f, 0.490000f, 0.010000f, 0.050000f, 0.900000f, 0.050000f};
float data7[] = {0.050000f, 0.950000f};
float data8[] = {0.920000f, 0.030000f, 0.050000f};
float data9[] = {0.040000f, 0.960000f};
float data10[] = {0.100000f, 0.900000f};
float data11[] = {0.050000f, 0.900000f, 0.050000f};
float data12[] = {0.050000f, 0.930000f, 0.010000f, 0.010000f, 0.050000f, 0.010000f, 0.930000f, 0.010000f, 0.050000f, 0.010000f, 0.010000f, 0.930000f};
float data13[] = {0.970000f, 0.010000f, 0.010000f, 0.010000f, 0.970000f, 0.010000f, 0.010000f, 0.010000f, 0.970000f, 0.010000f, 0.010000f, 0.010000f, 0.010000f, 0.010000f, 0.970000f, 0.010000f, 0.970000f, 0.010000f, 0.010000f, 0.010000f, 0.970000f, 0.010000f, 0.010000f, 0.010000f, 0.010000f, 0.970000f, 0.010000f, 0.010000f, 0.010000f, 0.010000f, 0.010000f, 0.970000f};
float data14[] = {0.970000f, 0.010000f, 0.010000f, 0.010000f, 0.970000f, 0.010000f, 0.010000f, 0.010000f, 0.970000f, 0.010000f, 0.010000f, 0.010000f, 0.970000f, 0.010000f, 0.010000f, 0.010000f, 0.300000f, 0.680000f, 0.010000f, 0.010000f, 0.950000f, 0.030000f, 0.010000f, 0.010000f, 0.010000f, 0.010000f, 0.010000f, 0.970000f, 0.010000f, 0.970000f, 0.010000f, 0.010000f, 0.950000f, 0.030000f, 0.010000f, 0.010000f, 0.970000f, 0.010000f, 0.010000f, 0.010000f, 0.010000f, 0.970000f, 0.010000f, 0.010000f, 0.970000f, 0.010000f, 0.010000f, 0.010000f, 0.970000f, 0.010000f, 0.010000f, 0.010000f, 0.500000f, 0.480000f, 0.010000f, 0.010000f, 0.970000f, 0.010000f, 0.010000f, 0.010000f, 0.010000f, 0.010000f, 0.970000f, 0.010000f, 0.400000f, 0.580000f, 0.010000f, 0.010000f, 0.970000f, 0.010000f, 0.010000f, 0.010000f, 0.010000f, 0.010000f, 0.970000f, 0.010000f, 0.970000f, 0.010000f, 0.010000f, 0.010000f, 0.970000f, 0.010000f, 0.010000f, 0.010000f, 0.300000f, 0.680000f, 0.010000f, 0.010000f, 0.970000f, 0.010000f, 0.010000f, 0.010000f, 0.010000f, 0.010000f, 0.010000f, 0.970000f};
float data15[] = {0.970000f, 0.010000f, 0.010000f, 0.010000f, 0.010000f, 0.010000f, 0.010000f, 0.970000f, 0.010000f, 0.010000f, 0.970000f, 0.010000f, 0.030000f, 0.950000f, 0.010000f, 0.010000f, 0.010000f, 0.970000f, 0.010000f, 0.010000f, 0.970000f, 0.010000f, 0.010000f, 0.010000f, 0.010000f, 0.010000f, 0.010000f, 0.970000f, 0.010000f, 0.940000f, 0.040000f, 0.010000f, 0.010000f, 0.010000f, 0.970000f, 0.010000f, 0.010000f, 0.970000f, 0.010000f, 0.010000f, 0.970000f, 0.010000f, 0.010000f, 0.010000f, 0.010000f, 0.880000f, 0.100000f, 0.010000f};
float data16[] = {0.010000f, 0.010000f, 0.980000f, 0.010000f, 0.010000f, 0.980000f, 0.040000f, 0.920000f, 0.040000f, 0.900000f, 0.090000f, 0.010000f};
float data17[] = {0.100000f, 0.900000f};
float data18[] = {0.050000f, 0.950000f};
float data19[] = {1.000000f, 0.000000f, 0.000000f, 0.950000f, 0.040000f, 0.010000f, 1.000000f, 0.000000f, 0.000000f, 0.010000f, 0.950000f, 0.040000f, 0.990000f, 0.010000f, 0.000000f, 0.950000f, 0.040000f, 0.010000f, 0.950000f, 0.040000f, 0.010000f, 0.010000f, 0.010000f, 0.980000f};
float data20[] = {0.010000f, 0.990000f};
float data21[] = {0.100000f, 0.900000f, 0.950000f, 0.050000f, 0.100000f, 0.900000f, 0.950000f, 0.050000f, 0.010000f, 0.990000f, 0.050000f, 0.950000f};
float data22[] = {0.980000f, 0.010000f, 0.010000f, 0.980000f, 0.010000f, 0.010000f, 0.010000f, 0.980000f, 0.010000f, 0.980000f, 0.010000f, 0.010000f, 0.010000f, 0.010000f, 0.980000f, 0.690000f, 0.300000f, 0.010000f};
float data23[] = {0.010000f, 0.990000f};
float data24[] = {0.980000f, 0.010000f, 0.010000f, 0.300000f, 0.400000f, 0.300000f};
float data25[] = {0.010000f, 0.990000f, 0.010000f, 0.990000f, 0.700000f, 0.300000f, 0.010000f, 0.990000f, 0.050000f, 0.950000f, 0.700000f, 0.300000f, 0.010000f, 0.990000f, 0.050000f, 0.950000f, 0.950000f, 0.050000f, 0.010000f, 0.990000f, 0.050000f, 0.950000f, 0.700000f, 0.300000f, 0.010000f, 0.990000f, 0.050000f, 0.950000f, 0.950000f, 0.050000f, 0.050000f, 0.950000f, 0.050000f, 0.950000f, 0.950000f, 0.050000f, 0.010000f, 0.990000f, 0.010000f, 0.990000f, 0.700000f, 0.300000f, 0.010000f, 0.990000f, 0.050000f, 0.950000f, 0.700000f, 0.300000f, 0.010000f, 0.990000f, 0.050000f, 0.950000f, 0.990000f, 0.010000f, 0.010000f, 0.990000f, 0.050000f, 0.950000f, 0.700000f, 0.300000f, 0.010000f, 0.990000f, 0.050000f, 0.950000f, 0.990000f, 0.010000f, 0.050000f, 0.950000f, 0.050000f, 0.950000f, 0.990000f, 0.010000f, 0.010000f, 0.990000f, 0.010000f, 0.990000f, 0.100000f, 0.900000f, 0.010000f, 0.990000f, 0.010000f, 0.990000f, 0.100000f, 0.900000f, 0.010000f, 0.990000f, 0.010000f, 0.990000f, 0.300000f, 0.700000f, 0.010000f, 0.990000f, 0.010000f, 0.990000f, 0.100000f, 0.900000f, 0.010000f, 0.990000f, 0.010000f, 0.990000f, 0.300000f, 0.700000f, 0.010000f, 0.990000f, 0.010000f, 0.990000f, 0.300000f, 0.700000f};
float data26[] = {0.050000f, 0.900000f, 0.050000f, 0.010000f, 0.090000f, 0.900000f};
float data27[] = {0.980000f, 0.010000f, 0.010000f, 0.300000f, 0.400000f, 0.300000f, 0.010000f, 0.980000f, 0.010000f, 0.400000f, 0.590000f, 0.010000f, 0.980000f, 0.010000f, 0.010000f, 0.010000f, 0.010000f, 0.980000f};
float data28[] = {0.100000f, 0.900000f};
float data29[] = {0.333333f, 0.333333f, 0.333333f, 0.010000f, 0.980000f, 0.010000f, 0.980000f, 0.010000f, 0.010000f, 0.333333f, 0.333333f, 0.333333f, 0.333333f, 0.333333f, 0.333333f, 0.010000f, 0.010000f, 0.980000f};
float data30[] = {0.333333f, 0.333333f, 0.333333f, 0.010000f, 0.980000f, 0.010000f, 0.980000f, 0.010000f, 0.010000f, 0.333333f, 0.333333f, 0.333333f, 0.333333f, 0.333333f, 0.333333f, 0.010000f, 0.010000f, 0.980000f};
float data31[] = {0.970000f, 0.010000f, 0.010000f, 0.010000f, 0.010000f, 0.010000f, 0.970000f, 0.010000f, 0.010000f, 0.010000f, 0.010000f, 0.970000f, 0.970000f, 0.010000f, 0.010000f, 0.010000f, 0.010000f, 0.010000f, 0.010000f, 0.970000f, 0.010000f, 0.970000f, 0.010000f, 0.010000f, 0.970000f, 0.010000f, 0.010000f, 0.010000f, 0.010000f, 0.970000f, 0.010000f, 0.010000f, 0.010000f, 0.010000f, 0.970000f, 0.010000f, 0.010000f, 0.970000f, 0.010000f, 0.010000f, 0.010000f, 0.010000f, 0.970000f, 0.010000f, 0.010000f, 0.010000f, 0.010000f, 0.970000f};
float data32[] = {0.970000f, 0.010000f, 0.010000f, 0.010000f, 0.010000f, 0.010000f, 0.010000f, 0.970000f, 0.500000f, 0.480000f, 0.010000f, 0.010000f, 0.010000f, 0.970000f, 0.010000f, 0.010000f, 0.010000f, 0.970000f, 0.010000f, 0.010000f, 0.970000f, 0.010000f, 0.010000f, 0.010000f, 0.500000f, 0.480000f, 0.010000f, 0.010000f, 0.010000f, 0.010000f, 0.970000f, 0.010000f, 0.010000f, 0.010000f, 0.970000f, 0.010000f, 0.600000f, 0.380000f, 0.010000f, 0.010000f, 0.970000f, 0.010000f, 0.010000f, 0.010000f, 0.010000f, 0.010000f, 0.010000f, 0.970000f};
float data33[] = {0.010000f, 0.190000f, 0.800000f, 0.050000f, 0.900000f, 0.050000f};
float data34[] = {0.970000f, 0.010000f, 0.010000f, 0.010000f, 0.050000f, 0.250000f, 0.250000f, 0.450000f, 0.970000f, 0.010000f, 0.010000f, 0.010000f, 0.200000f, 0.750000f, 0.040000f, 0.010000f, 0.010000f, 0.010000f, 0.010000f, 0.970000f, 0.010000f, 0.290000f, 0.300000f, 0.400000f, 0.010000f, 0.010000f, 0.010000f, 0.970000f, 0.010000f, 0.900000f, 0.080000f, 0.010000f, 0.010000f, 0.300000f, 0.490000f, 0.200000f, 0.010000f, 0.150000f, 0.250000f, 0.590000f, 0.010000f, 0.970000f, 0.010000f, 0.010000f, 0.200000f, 0.700000f, 0.090000f, 0.010000f, 0.970000f, 0.010000f, 0.010000f, 0.010000f, 0.010000f, 0.010000f, 0.080000f, 0.900000f, 0.970000f, 0.010000f, 0.010000f, 0.010000f, 0.010000f, 0.010000f, 0.380000f, 0.600000f, 0.010000f, 0.010000f, 0.080000f, 0.900000f, 0.970000f, 0.010000f, 0.010000f, 0.010000f, 0.010000f, 0.010000f, 0.970000f, 0.010000f, 0.970000f, 0.010000f, 0.010000f, 0.010000f, 0.100000f, 0.840000f, 0.050000f, 0.010000f, 0.010000f, 0.010000f, 0.010000f, 0.970000f, 0.400000f, 0.580000f, 0.010000f, 0.010000f, 0.010000f, 0.010000f, 0.010000f, 0.970000f};
float data35[] = {0.980000f, 0.010000f, 0.010000f, 0.950000f, 0.040000f, 0.010000f, 0.800000f, 0.190000f, 0.010000f, 0.950000f, 0.040000f, 0.010000f, 0.040000f, 0.950000f, 0.010000f, 0.010000f, 0.040000f, 0.950000f, 0.300000f, 0.690000f, 0.010000f, 0.010000f, 0.300000f, 0.690000f, 0.010000f, 0.010000f, 0.980000f};
float data36[] = {0.980000f, 0.010000f, 0.010000f, 0.980000f, 0.010000f, 0.010000f, 0.900000f, 0.090000f, 0.010000f, 0.980000f, 0.010000f, 0.010000f, 0.100000f, 0.850000f, 0.050000f, 0.050000f, 0.200000f, 0.750000f, 0.300000f, 0.600000f, 0.100000f, 0.050000f, 0.400000f, 0.550000f, 0.010000f, 0.090000f, 0.900000f};
float *data[] = { data0, data1, data2, data3, data4,
data5, data6, data7, data8, data9,
data10, data11, data12, data13, data14,
data15, data16, data17, data18, data19,
data20, data21, data22, data23, data24,
data25, data26, data27, data28, data29,
data30, data31, data32, data33, data34,
data35, data36};
for( i = 0; i < nnodes; i++ )
{
myParams[i]->AllocMatrix(data[i], matTable);
pBNet->AttachFactor(myParams[i]);
}
delete [] nodeTypes;
delete[] nodeAssociation;
CContextPersistence xmlContext;
xmlContext.Put(pBNet, "MyModel");
if(!xmlContext.SaveAsXML("myFavoriteObjects.xml"))
{
fprintf(stderr, "Persistence: error!\n");
// something goes wrong – can’t create
}
else
{
fprintf(stderr, "Persistence: good!\n");
}
return pBNet;
}
