当前位置: 首页>>代码示例>>C++>>正文

C++ CBNet::AttachFactor方法代码示例

本文整理汇总了C++中CBNet::AttachFactor方法的典型用法代码示例。如果您正苦于以下问题：C++ CBNet::AttachFactor方法的具体用法？C++ CBNet::AttachFactor怎么用？C++ CBNet::AttachFactor使用的例子？那么, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类CBNet的用法示例。


在下文中一共展示了CBNet::AttachFactor方法的9个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的C++代码示例。

示例1: CreateRandomBayessian


//.........这里部分代码省略.........
    }
    if (pGraph->NumberOfConnectivityComponents() > 1)
    {
        PNL_THROW( CInconsistentType, " the graph should be linked " );
    }

    int i, j, k;

    int num_nodes = pGraph->GetNumberOfNodes();
    CNodeType *nodeTypes = new CNodeType [num_nodes];
    int num_states;
    
    for ( i = 0; i < num_nodes; i++ )
    {
        num_states = GetRandomNumberOfStates(max_num_states);
        nodeTypes[i].SetType(1, num_states, nsChance);
    }

    int *nodeAssociation = new int[num_nodes];
    for ( i = 0; i < num_nodes; i++ )
    {
        nodeAssociation[i] = i;
    }

    CBNet *pBNet = CBNet::Create( num_nodes, num_nodes, nodeTypes,
                                     nodeAssociation, pGraph );
    
    CModelDomain* pMD = pBNet->GetModelDomain();
    
    CFactor **myParams = new CFactor*[num_nodes];
    int *nodeNumbers = new int[num_nodes];
    int **domains = new int*[num_nodes];

    intVector parents(0);
    for ( i = 0; i < num_nodes; i++)
    {
        nodeNumbers[i] = pGraph->GetNumberOfParents(i) + 1;
        domains[i] = new int[nodeNumbers[i]];
        pGraph->GetParents(i, &parents);
        
        for ( j = 0; j < parents.size(); j++ )
            domains[i][j] = parents[j];
        domains[i][nodeNumbers[i]-1] = i;
    }

    pBNet->AllocFactors();

    for( i = 0; i < num_nodes; i++ )
    {
        myParams[i] = CTabularCPD::Create( domains[i], 
            nodeNumbers[i], pMD);
    }

    float **data = new float*[num_nodes];
    int size_data;
    int num_states_node;
    int num_blocks;
    intVector size_nodes(0);
    float belief, sum_beliefs;

    for ( i = 0; i < num_nodes; i++ )
    {
        size_data = 1;
        size_nodes.resize(0);
        for ( j = 0; j < nodeNumbers[i]; j++ )
        {
            size_nodes.push_back(pBNet->GetNodeType(
                domains[i][j])->GetNodeSize());
            size_data *= size_nodes[j];
        }
        num_states_node = size_nodes[size_nodes.size() - 1];
        num_blocks = size_data / num_states_node;
        
        data[i] = new float[size_data];

        for ( j = 0; j < num_blocks; j++ )
        {
            sum_beliefs = 0.0;
            for ( k = 0; k < num_states_node - 1; k++ )
            {
                belief = GetBelief(1.0 - sum_beliefs);
                data[i][j * num_states_node + k] = belief;
                sum_beliefs += belief;
            }
            belief = 1.0 - sum_beliefs;
            data[i][j * num_states_node + num_states_node - 1] = belief;
        }
    }

    for( i = 0; i < num_nodes; i++ )
    {
        myParams[i]->AllocMatrix(data[i], matTable);
        pBNet->AttachFactor(myParams[i]);
    }    

    delete [] nodeTypes;
    delete [] nodeAssociation;

    return pBNet;
}
开发者ID:JacobCWard，项目名称:PyPNL，代码行数:101，代码来源:CreateBNets.cpp

示例2: types

CBNet *CreateTestTabularNetWithDecTreeNodeBNet()
{
	//   Baysam network     
	//        0 1...8 9       0,1, 9- discrete nodes distribution type is tabular, size is 2
	//        \ \  / /      10 - is discrete desigion tree node
	//            10        
	//          
	//      
	//
	// Desigion tree on the node 10 is
	//
	//     0
	//    / \	
	//   1	 2
	//  / \ / \
	// 3  4 5  6
	//  	   
    const int nnodes = 11; //Number of nodes
    const int numNt =  1; //number of Node types (all nodes are discrete)
    CNodeType* nodeTypes = new CNodeType [numNt];
	int size = 2;
    int i;
	nodeTypes[0] = CNodeType( 1,size );
    int *nodeAssociation = new int[nnodes];
    for( i = 0; i < nnodes; i++ )
	{
		nodeAssociation[i] = 0;
	};
    int *numOfNeigh;
    numOfNeigh = new int[nnodes];

	for( i = 0; i < nnodes - 1; i++ )
	{
		numOfNeigh[i] = 1;
	};
	numOfNeigh[nnodes - 1] = nnodes - 1;

    int **neigh;
	neigh = new int*[nnodes];
    for( i = 0; i < nnodes - 1; i++ )
	{
		neigh[i] = new int;
		neigh[i][0] = nnodes - 1;

	};
	neigh[nnodes - 1] = new int[nnodes - 1];

    for( i = 0; i < nnodes - 1; i++ )
	{
		neigh[nnodes - 1][i] = i;
	};

	ENeighborType **orient;
    orient = new ENeighborType*[nnodes];

	for( i = 0; i < nnodes - 1; i++ )
	{
		orient[i] = new ENeighborType;
		orient[i][0] = ntChild;

	};
    
	orient[nnodes - 1] = new ENeighborType[nnodes - 1];

	for( i = 0; i < nnodes - 1; i++ )
	{
		orient[nnodes - 1][i] = ntParent;
	};

    CGraph* pGraph = CGraph::Create( nnodes, numOfNeigh, neigh, orient);

    //Create static BNet
    CBNet* pBNet = CBNet::Create( nnodes, numNt, nodeTypes, nodeAssociation, pGraph );
    pBNet->AllocFactors();


    int nnodesInDom = 1;
    int *domains;
	domains = new int[nnodes -1];
	for( i = 0; i < nnodes - 1; i++ )
	{
		domains[i] = i;
	};
    float table[] = { 0.3f, 0.7f};

    CTabularCPD **pCPDPar;
	pCPDPar = new CTabularCPD*[nnodes - 1];
	for( i = 0; i < nnodes - 1; i++ )
	{
		pCPDPar[i] = CTabularCPD::Create( &domains[i], nnodesInDom, pBNet->GetModelDomain(), table );
		pBNet->AttachFactor(pCPDPar[i]);
	};	
		

    int nnodesInChilddom = nnodes;
	int *domainChild; 
	domainChild = new int[ nnodes ];

		for( i = 0; i < nnodes; i++ )
		{
//.........这里部分代码省略.........
开发者ID:billryan，项目名称:OpenPNL，代码行数:101，代码来源:AGibbsInfEngine.cpp

示例3: CreateFourNodeExampleNew

CBNet* CreateFourNodeExampleNew(void)
{

    CBNet *pBNet;
    const int nnodes = 4;
    const int numberOfNodeTypes = 2;

    int numOfNeigh[] = { 1, 1, 3, 1 };

    int neigh0[] = { 2 };
    int neigh1[] = { 2 };
    int neigh2[] = { 0, 1, 3 };
    int neigh3[] = { 2 };

    ENeighborType orient0[] = { ntChild };
    ENeighborType orient1[] = { ntChild };
    ENeighborType orient2[] = { ntParent, ntParent, ntChild };
    ENeighborType orient3[] = { ntParent };

    int *neigh[] = { neigh0,  neigh1, neigh2, neigh3 };

    ENeighborType *orient[] = { orient0, orient1, orient2, orient3 };

    CGraph *pGraph = CGraph::Create( nnodes, numOfNeigh, neigh, orient );

    CNodeType *nodeTypes = new CNodeType [numberOfNodeTypes];
    nodeTypes[0].SetType(1, 2);
    nodeTypes[1].SetType(0, 1);

    int *nodeAssociation = new int[nnodes];

    nodeAssociation[0]=0;
    nodeAssociation[1]=1;
    nodeAssociation[2]=1;
    nodeAssociation[3]=1;

    pBNet = CBNet::Create(nnodes, numberOfNodeTypes, nodeTypes, nodeAssociation, pGraph);

    CModelDomain* pMD = pBNet->GetModelDomain();

//number of parameters is the same as number of nodes - one CPD per node
//  CFactor *myParams = new CFactor[1];
    int *nodeNumbers = new int [nnodes];

    int domain0[] = { 0 };
    int domain1[] = { 1 };
    int domain2[] = { 0, 1, 2 };
    int domain3[] = { 2, 3 };
    int *domains[] = { domain0, domain1, domain2, domain3 };
    nodeNumbers[0] = 1;
    nodeNumbers[1] = 1;
    nodeNumbers[2] = 3;
    nodeNumbers[3] = 2;

    pBNet->AllocParameters();

    CFactor *myParams = CTabularCPD::Create( domains[0], nodeNumbers[0], pMD );

// data creation for all CPDs of the model
    float data0[] = { 0.5f, 0.5f };

    myParams->AllocMatrix(data0, matTable);
    pBNet->AttachParameter(myParams);

    float mean0 = 0.0f;
    float cov0 = 1.0f;
    CGaussianCPD* pCPD = CGaussianCPD::Create( domain1, 1, pMD );
    pCPD->AllocDistribution( &mean0, &cov0, 1.0f, NULL);
    pBNet->AttachFactor(pCPD);

    float mean1[] = { 8.0f };
    float mean2[] = { 2.0f };
    float cov1[] = { 1.0f };
    float cov2[] = { 1.0f };

    float weight[] = { 0.01f, 0.03f };
    float weight1[] = { 0.01f };
    const float *pData = weight;
    const float *pData1 = weight1;

    CGaussianCPD* pCPD1 = CGaussianCPD::Create( domain2, 3, pMD );
    int ParentCom[] = { 0, 1 };
    pCPD1->AllocDistribution( mean1, cov1, 0.5f, &pData, &ParentCom[0] );
    pCPD1->AllocDistribution( mean2, cov2, 0.5f, &pData, &ParentCom[1] );
    pBNet->AttachFactor(pCPD1);

    CGaussianCPD* pCPD2 = CGaussianCPD::Create( domain3, 2, pMD );
    pCPD2->AllocDistribution( mean1, cov1, 0.5f, &pData1 );
    pBNet->AttachFactor(pCPD2);


    delete [] nodeTypes;
    return pBNet;
}
开发者ID:JacobCWard，项目名称:PyPNL，代码行数:94，代码来源:SamplesOfSMNet.cpp

示例4: LearnOneStep


//.........这里部分代码省略.........
		PNL_THROW(CInternalError, "There are some internal errors");
	}

	intVector vRenaming, Old2New;
	CDAG* iDAG;
	int TopologicSorted = pDAG->IsTopologicallySorted();
	if( TopologicSorted )
	{
		iDAG = pDAG->Clone();
		for(i=0; i<m_nNodes; i++) vRenaming.push_back(i);
	}
	else
		iDAG = pDAG->TopologicalCreateDAG(vRenaming);
	pDAG->Dump();
	intVector gRename;
	for(i=0; i<m_nNodes; i++)
	{
		node = vRenaming[i];
		node1 = m_vGlobalRenaming[node];
		gRename.push_back(node1);
	}
	m_vGlobalRenaming.assign(gRename.begin(), gRename.end());

	int pos;
	for(i=0; i<m_nNodes; i++)
	{
		pos = std::find(vRenaming.begin(), vRenaming.end(), i) - vRenaming.begin();
		Old2New.push_back(pos);
	}

	const int* oldNodeAsso = m_pCurrBNet->GetNodeAssociations();
	intVector newNodeAsso(m_nNodes,0);
	for(i=0; i<m_nNodes; i++)
	{
		newNodeAsso[i] = oldNodeAsso[vRenaming[i]];
	}
	nodeTypeVector vpnt;
	m_pCurrBNet->GetNodeTypes(&vpnt);
	CBNet* pBNet = CBNet::Create(m_nNodes, vpnt.size(), &vpnt.front(), 
		           &newNodeAsso.front(), static_cast<CGraph*>(iDAG));
	CModelDomain* pMDnew = pBNet->GetModelDomain();
	pBNet->AllocFactors();
	intVector domainNew, domainOld;
	const CFactor* factor=0;
	CFactor* curFactor;
	for(i=0; i<m_nNodes; i++)
	{
		domainNew.clear();
		newnode = Old2New[i];
		if( (i != start) && (i != end) )
		{
			factor = m_pCurrBNet->GetFactor(i);
		}
		else
		{
			if(changeType == DAG_REV)
			{
				if(i == start)
					factor = addCPD->Clone();
				if(i == end)
					factor = delCPD->Clone();
			}
			if(changeType == DAG_DEL)
			{
				if(i == start)
					factor = m_pCurrBNet->GetFactor(i);
				if(i == end)
					factor = delCPD->Clone();
			}
			if(changeType == DAG_ADD)
			{
				if(i == start)
					factor = m_pCurrBNet->GetFactor(i);
				if(i == end)
					factor = addCPD->Clone();
			}
		}
		factor->GetDomain(&domainOld);
		for(j=0; j<domainOld.size(); j++)
		{
			domainNew.push_back(Old2New[domainOld[j]]);
		}
		curFactor = CFactor::CopyWithNewDomain(factor, domainNew, pMDnew);
		pBNet->AttachFactor(curFactor);
	}

	if(changeType == DAG_REV)
	{
		delete addCPD;
		delete delCPD;
	}
	if(changeType == DAG_ADD)delete addCPD;
	if(changeType == DAG_DEL)delete delCPD;

	delete m_pCurrBNet;
	delete pDAG;
	m_pCurrBNet = pBNet;
	m_critValue.push_back(total_score);
	return true;
}
开发者ID:lspatial，项目名称:spstatics_parallel，代码行数:101，代码来源:pnlStaticStructLearnSEM.cpp

示例5: CreateTwoNodeEx

CBNet* CreateTwoNodeEx(void)
{
    const int numOfNds = 2;
    int numOfNbrs[numOfNds] = { 1, 1 };

    int nbrs0[] = { 1 };
    int nbrs1[] = { 0 };

    ENeighborType nbrsTypes0[] = { ntChild };
    ENeighborType nbrsTypes1[] = { ntParent };

    int *nbrs[] = { nbrs0, nbrs1 };
    ENeighborType *nbrsTypes[] = { nbrsTypes0, nbrsTypes1 };

    CGraph* pGraph = CGraph::Create(numOfNds, numOfNbrs, nbrs, nbrsTypes);

    CModelDomain* pMD;

    nodeTypeVector variableTypes;

    int nVariableTypes = 2;
    variableTypes.resize(nVariableTypes);

    variableTypes[0].SetType(0, 1);
    variableTypes[1].SetType(1, 2);

    intVector variableAssociation;
    int nnodes = pGraph->GetNumberOfNodes();
    variableAssociation.assign(nnodes, 1);
    variableAssociation[0] = 0;
    variableAssociation[1] = 1;

    pMD = CModelDomain::Create(variableTypes, variableAssociation);

    CBNet *pBNet = CBNet::Create(pGraph, pMD);

    pBNet->AllocFactors();

    int nnodes0 = 1;
    int domain0[] = { 0 };
    float mean0 = 0.0f;
    float cov0 = 1.0f;
    CGaussianCPD *pCPD0 = CGaussianCPD::Create(domain0, nnodes0, pMD);
    pCPD0->AllocDistribution(&mean0, &cov0, 1.0f, NULL);
    pBNet->AttachFactor(pCPD0);

    int nnodes1 = 2;
    int domain1[] = { 0, 1 };

    CSoftMaxCPD *pCPD3 = CSoftMaxCPD::Create(domain1, nnodes1, pMD);

    int parInd0[] = { 0 };

//  float weight30[] = { -1.0f,-1.0f };
//  float offset30[] = { 1.0f, 1.0f };

    float weight30[] = { -0.3059f, -1.1777f };
    float offset30[] = { 0.0886f, 0.2034f };

    pCPD3->AllocDistribution(weight30, offset30, parInd0);

    pBNet->AttachFactor(pCPD3);

    return pBNet;
}
开发者ID:JacobCWard，项目名称:PyPNL，代码行数:65，代码来源:SamplesOfSMNet.cpp

示例6: CreateSevenNodeEx

// ----------------------------------------------------------------------------
CBNet* CreateSevenNodeEx(void)
{

    // 0  1   2
    // |\ \  /
    // | \ \ /
    // |    3
    // |   / \ 
    // |  4   5
    // |/
    // 6
    // 0, 1, 5 - continuous
    // 3, 6 - softmax
    // 2, 4 - discrete

    const int numOfNds = 7;
    int numOfNbrs[numOfNds] = { 2, 1, 1, 5, 2, 1, 2 };

    int nbrs0[] = { 3, 6 };
    int nbrs1[] = { 3 };
    int nbrs2[] = { 3 };
    int nbrs3[] = { 0, 1, 2, 4, 5 };
    int nbrs4[] = { 3, 6 };
    int nbrs5[] = { 3 };
    int nbrs6[] = { 0, 4 };

    ENeighborType nbrsTypes0[] = { ntChild, ntChild };
    ENeighborType nbrsTypes1[] = { ntChild };
    ENeighborType nbrsTypes2[] = { ntChild };
    ENeighborType nbrsTypes3[] = { ntParent, ntParent, ntParent, ntChild, ntChild };
    ENeighborType nbrsTypes4[] = { ntParent, ntChild };
    ENeighborType nbrsTypes5[] = { ntParent };
    ENeighborType nbrsTypes6[] = { ntParent, ntParent };

    int *nbrs[] = { nbrs0, nbrs1, nbrs2, nbrs3, nbrs4, nbrs5, nbrs6 };
    ENeighborType *nbrsTypes[] = { nbrsTypes0, nbrsTypes1, nbrsTypes2, nbrsTypes3, nbrsTypes4,
                                   nbrsTypes5, nbrsTypes6
                                 };

    CGraph* pGraph = CGraph::Create( numOfNds, numOfNbrs, nbrs, nbrsTypes );

    // 2) Creation of the Model Domain.
    CModelDomain* pMD;

    nodeTypeVector variableTypes;

    int nVariableTypes = 2;
    variableTypes.resize( nVariableTypes );

    variableTypes[0].SetType( 0, 1 ); // continuous
    variableTypes[1].SetType( 1, 2 ); // discrete, 2 states

    intVector variableAssociation;
    int nnodes = pGraph->GetNumberOfNodes();
    variableAssociation.assign(nnodes, 1);
    variableAssociation[0] = 0;
    variableAssociation[1] = 0;
    variableAssociation[2] = 1;
    variableAssociation[3] = 1;
    variableAssociation[4] = 1;
    variableAssociation[5] = 0;
    variableAssociation[6] = 1;

    pMD = CModelDomain::Create( variableTypes, variableAssociation );

    // 2) Creation base for BNet using Graph, and Model Domain

    CBNet *pBNet = CBNet::Create(pGraph, pMD);

    // 3)Allocation space for all factors of the model
    pBNet->AllocFactors();

    int nnodes0 = 1;
    int domain0[] = { 0 };
    float mean0 = 0.5f;
    float cov0 = 1.0f;
    CGaussianCPD *pCPD0 = CGaussianCPD::Create( domain0, nnodes0, pMD );
    pCPD0->AllocDistribution( &mean0, &cov0, 1.0f, NULL );
    pBNet->AttachFactor( pCPD0 );

    int nnodes1 = 1;
    int domain1[] = { 1 };
    float mean1 = 0.5f;
    float cov1 = 1.0f;
    CGaussianCPD *pCPD1 = CGaussianCPD::Create( domain1, nnodes1, pMD );
    pCPD1->AllocDistribution( &mean1, &cov1, 1.0f, NULL );
    pBNet->AttachFactor( pCPD1 );

    int nnodes2 = 1;
    int domain2[] = { 2 };
    float table2[] = { 0.3f, 0.7f};
    CTabularCPD *pCPD2 = CTabularCPD::Create( domain2, nnodes2, pMD, table2 );
    pCPD2->AllocMatrix(table2, matTable);
    pBNet->AttachParameter(pCPD2);

    int nnodes3 = 4;
    int domain3[] = { 0, 1, 2, 3 };
    CSoftMaxCPD *pCPD3 = CSoftMaxCPD::Create( domain3, nnodes3, pMD );

//.........这里部分代码省略.........
开发者ID:JacobCWard，项目名称:PyPNL，代码行数:101，代码来源:SamplesOfSMNet.cpp

示例7: CreateSixNodeEx

CBNet* CreateSixNodeEx(void)
{
    int i;
    const int numOfNds = 6;
    int numOfNbrs[numOfNds] = { 1, 1, 1, 1, 1, 5 };

    int nbrs0[] = { 5 };
    int nbrs1[] = { 5 };
    int nbrs2[] = { 5 };
    int nbrs3[] = { 5 };
    int nbrs4[] = { 5 };
    int nbrs5[] = { 0, 1, 2, 3, 4 };

    ENeighborType nbrsTypes0[] = { ntChild };
    ENeighborType nbrsTypes1[] = { ntChild };
    ENeighborType nbrsTypes2[] = { ntChild };
    ENeighborType nbrsTypes3[] = { ntChild };
    ENeighborType nbrsTypes4[] = { ntChild };
    ENeighborType nbrsTypes5[] = { ntParent, ntParent, ntParent, ntParent,
                                   ntParent
                                 };

    int *nbrs[] = { nbrs0, nbrs1, nbrs2, nbrs3, nbrs4, nbrs5};
    ENeighborType *nbrsTypes[] = { nbrsTypes0, nbrsTypes1, nbrsTypes2,
                                   nbrsTypes3, nbrsTypes4, nbrsTypes5
                                 };

    CGraph* pGraph = CGraph::Create(numOfNds, numOfNbrs, nbrs, nbrsTypes);

    CModelDomain* pMD;

    nodeTypeVector variableTypes;

    int nVariableTypes = 2;
    variableTypes.resize(nVariableTypes);

    variableTypes[0].SetType(0, 1);
//  variableTypes[0].SetType(1, 4);
    variableTypes[1].SetType(1, 2);

    intVector variableAssociation;
    int nnodes = pGraph->GetNumberOfNodes();
    variableAssociation.assign(nnodes, 1);
    variableAssociation[0] = 0;
    variableAssociation[1] = 0;
    variableAssociation[2] = 0;
    variableAssociation[3] = 0;
    variableAssociation[4] = 0;
    variableAssociation[5] = 1;

    pMD = CModelDomain::Create(variableTypes, variableAssociation);

    CBNet *pBNet = CBNet::Create(pGraph, pMD);

    pBNet->AllocFactors();

    int nnodes0 = 1;
    int domain0[] = { 0 };
    float mean0 = 0.0f;
    float cov0 = 1.0f;

    CGaussianCPD *pCPD0 = CGaussianCPD::Create(domain0, nnodes0, pMD);
    pCPD0->AllocDistribution(&mean0, &cov0, 1.0f, NULL);
    pBNet->AttachFactor(pCPD0);

    int nnodes1 = 1;
    int domain1[] = { 1 };
    float mean1 = 2.0f;
    float cov1 = 1.0f;

    CGaussianCPD *pCPD1 = CGaussianCPD::Create(domain1, nnodes1, pMD);
    pCPD1->AllocDistribution(&mean1, &cov1, 1.0f, NULL);
    pBNet->AttachFactor(pCPD1);

    int nnodes2 = 1;
    int domain2[] = { 2 };
    float mean2 = 1.0f;
    float cov2 = 1.0f;

    CGaussianCPD *pCPD2 = CGaussianCPD::Create(domain2, nnodes2, pMD);
    pCPD2->AllocDistribution(&mean2, &cov2, 1.0f, NULL);
    pBNet->AttachFactor(pCPD2);

    int nnodes3 = 1;
    int domain3[] = { 3 };
    float mean3 = 5.0f;
    float cov3 = 1.0f;

    CGaussianCPD *pCPD3 = CGaussianCPD::Create(domain3, nnodes3, pMD);
    pCPD3->AllocDistribution(&mean3, &cov3, 1.0f, NULL);
    pBNet->AttachFactor(pCPD3);

    int nnodes4 = 1;
    int domain4[] = { 4 };
    float mean4 = 5.0f;
    float cov4 = 1.0f;

    CGaussianCPD *pCPD4 = CGaussianCPD::Create(domain4, nnodes4, pMD);
    pCPD4->AllocDistribution(&mean4, &cov4, 1.0f, NULL);
    pBNet->AttachFactor(pCPD4);
//.........这里部分代码省略.........
开发者ID:JacobCWard，项目名称:PyPNL，代码行数:101，代码来源:SamplesOfSMNet.cpp

示例8: CreateGaussianExample

// ----------------------------------------------------------------------------
CBNet* CreateGaussianExample(void)
{
    CBNet *pBNet;
    int i;
    const int nnodes = 3;

    int numOfNeigh[] = { 1, 2, 1 };

    int neigh0[] = { 1 };
    int neigh1[] = { 0, 2 };
    int neigh2[] = { 1 };

    ENeighborType orient0[] = { ntChild };
    ENeighborType orient1[] = { ntParent, ntChild };
    ENeighborType orient2[] = { ntParent };

    int *neigh[] = { neigh0,  neigh1, neigh2 };

    ENeighborType *orient[] = { orient0, orient1, orient2 };

    CGraph *pGraph = CGraph::Create( nnodes, numOfNeigh, neigh, orient );

    const int numberOfNodeTypes = 1;

    CNodeType *nodeTypes = new CNodeType [numberOfNodeTypes];

    nodeTypes[0].SetType(0, 1);

    int *nodeAssociation = new int[nnodes];

    for (i = 0; i < nnodes; i++)
        nodeAssociation[i] = 0;

    pBNet = CBNet::Create(nnodes, numberOfNodeTypes, nodeTypes, nodeAssociation, pGraph);

    CModelDomain* pMD = pBNet->GetModelDomain();

    int domain0[] = { 0 };
    int domain1[] = { 0, 1 };
    int domain2[] = { 1, 2 };

    int *domains[] = { domain0, domain1, domain2 };

    float mean0 = 0.0f;
    float cov0 = 1.0f;
    CGaussianCPD* pCPD = CGaussianCPD::Create( domain0, 1, pMD );
    pCPD->AllocDistribution( &mean0, &cov0, 1.0f, NULL );
    pBNet->AttachFactor(pCPD);

    float meanNode1 = 8.0f;
    float covNode1 = 1.0f;
    float weightNode1[] = { 0.01f };

    pCPD = CGaussianCPD::Create( domain1, 2, pMD );

    const float *pData = weightNode1;
    pCPD->AllocDistribution( &meanNode1, &covNode1, 0.5f, &pData );
    pBNet->AttachFactor(pCPD);

    float meanNode2 = 1.0f ;
    float covNode2 = 0.01f;
    float weightNode2[] = {0.01f};

    pCPD = CGaussianCPD::Create( domain2, 2, pMD );
    const float *pData2 = weightNode2;
    pCPD->AllocDistribution( &meanNode2, &covNode2, 0.5f, &pData2 );

    pBNet->AttachFactor(pCPD);

    delete [] nodeTypes;
    delete [] nodeAssociation;
    return pBNet;
}
开发者ID:JacobCWard，项目名称:PyPNL，代码行数:74，代码来源:SamplesOfSMNet.cpp

示例9: CreateAlarmBNet


//.........这里部分代码省略.........
    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;
}
开发者ID:PyOpenPNL，项目名称:OpenPNL，代码行数:101，代码来源:testSL.cpp


注：本文中的CBNet::AttachFactor方法示例由纯净天空整理自Github/MSDocs等开源代码及文档管理平台，相关代码片段筛选自各路编程大神贡献的开源项目，源码版权归原作者所有，传播和使用请参考对应项目的License；未经允许，请勿转载。