mrf_graph_test.cc.svn-base

Probabilistic graphical models in matlab.

#ifdef NOTUSED

#include <iostream>

#include <GraphAlgorithms.h>
#include <RandomVariable.h>
#include <Potential.h>
#include <Node.h>

using namespace std;
using namespace boost;

void create_mrf_graph_test()
{
	cout << "Testing an MRF Graph..." << endl;

	// Creating the Graph
	
	typedef property< edge_index_t, unsigned int, DiscretePotential *> MRFEdgeProperty;
	
	typedef adjacency_list<vecS, vecS, undirectedS, MessageNode <DiscreteRandomVariable, boost::adjacency_list_traits<vecS, vecS, undirectedS>::vertex_descriptor> *, MRFEdgeProperty > Graph;
	
	Graph G;

	typedef boost::graph_traits<Graph>::vertex_descriptor VertexDescriptor;

	DiscretePotential * cp = new ConstantPotential();

	DiscreteRandomVariable * rv_1 = new DiscreteRandomVariable(1,2);
	DiscreteRandomVariable * rv_2 = new DiscreteRandomVariable(2,2);
	DiscreteRandomVariable * rv_3 = new DiscreteRandomVariable(3,2);
	DiscreteRandomVariable * rv_4 = new DiscreteRandomVariable(4,2);
	DiscreteRandomVariable * rv_5 = new DiscreteRandomVariable(5,2);
	DiscreteRandomVariable * rv_6 = new DiscreteRandomVariable(6,2);

	typedef MRFMessageNode < DiscreteRandomVariable, DiscretePotential, boost::adjacency_list_traits <vecS, vecS, undirectedS>::vertex_descriptor > MRFDiscreteNode;
	
	MRFDiscreteNode * v_1 = new MRFDiscreteNode (rv_1, cp);
	
	MRFDiscreteNode * v_2 = new MRFDiscreteNode (rv_2, cp);
	
	MRFDiscreteNode * v_3 = new MRFDiscreteNode (rv_3, cp);
	
	MRFDiscreteNode * v_4 = new MRFDiscreteNode (rv_4, cp);
	
	MRFDiscreteNode * v_5 = new MRFDiscreteNode(rv_5, cp);
	
	MRFDiscreteNode * v_6 = new MRFDiscreteNode (rv_6, cp);

	/* 

	No pointers version

	MRFMessageNode<DiscreteRandomVariable, Potential, boost::graph_traits<HelperGraph>::vertex_descriptor> v_1 (rv_1, cp);
	MRFMessageNode<DiscreteRandomVariable, Potential, boost::graph_traits<HelperGraph>::vertex_descriptor> v_2 (rv_2, cp);
	MRFMessageNode<DiscreteRandomVariable, Potential, boost::graph_traits<HelperGraph>::vertex_descriptor> v_3 (rv_3, cp);
	MRFMessageNode<DiscreteRandomVariable, Potential, boost::graph_traits<HelperGraph>::vertex_descriptor> v_4 (rv_4, cp);
	MRFMessageNode<DiscreteRandomVariable, Potential, boost::graph_traits<HelperGraph>::vertex_descriptor> v_5 (rv_5, cp);
	MRFMessageNode<DiscreteRandomVariable, Potential, boost::graph_traits<HelperGraph>::vertex_descriptor> v_6 (rv_6, cp);

	*/

	VertexDescriptor vd_1 = add_vertex(v_1, G);
	VertexDescriptor vd_2 = add_vertex(v_2, G);
	VertexDescriptor vd_3 = add_vertex(v_3, G);
	VertexDescriptor vd_4 = add_vertex(v_4, G);
	VertexDescriptor vd_5 = add_vertex(v_5, G);
	VertexDescriptor vd_6 = add_vertex(v_6, G);

	// As a sidenote: we could maybe construct these Potentials when we add the edges in the Graph, since it already contains the
	// informations about which variables should be linked to the Potential

	DiscretePotential * p_1 = new DiscretePotential();
	p_1->add_variable(*rv_1);
	p_1->add_variable(*rv_2);

	DiscretePotential * p_2 = new DiscretePotential();
	p_2->add_variable(*rv_2);
	p_2->add_variable(*rv_3);


	DiscretePotential * p_3 = new DiscretePotential();
	p_3->add_variable(*rv_3);
	p_3->add_variable(*rv_4);

	DiscretePotential * p_4 = new DiscretePotential();
	p_4->add_variable(*rv_3);
	p_4->add_variable(*rv_5);

	DiscretePotential * p_5 = new DiscretePotential();
	p_5->add_variable(*rv_5);
	p_5->add_variable(*rv_6);

	vector <double> values_vec;

	values_vec.push_back (100);
	values_vec.push_back (4);
	values_vec.push_back (100);
	values_vec.push_back (5);

	p_1->setup_potential_values (values_vec);

	values_vec[0] = 8;
	values_vec[1] = 3;
	values_vec[2] = 7;
	values_vec[3] = 8;

	p_2->setup_potential_values (values_vec);

	values_vec[0] = 1;
	values_vec[1] = 5;
	values_vec[2] = 6;
	values_vec[3] = 12;

	p_3->setup_potential_values (values_vec);

	values_vec[0] = 9;
	values_vec[1] = 2;
	values_vec[2] = 4;
	values_vec[3] = 3;

	p_4->setup_potential_values (values_vec);

	values_vec[0] = 7;
	values_vec[1] = 5;
	values_vec[2] = 7;
	values_vec[3] = 1;

	p_5->setup_potential_values (values_vec);

	// Yes... it does seem really stupid to do that twice, and may introduce errors...

	G[add_edge(vd_1, vd_2, G).first]= p_1;
	G[add_edge(vd_2, vd_3, G).first]= p_2;
	G[add_edge(vd_3, vd_4, G).first]= p_3;
	G[add_edge(vd_3, vd_5, G).first]= p_4;
	G[add_edge(vd_5, vd_6, G).first]= p_5;

	// Ok. Our Graph is done!

	//End of graph creation

	cout << "Starting Message Passing..." << endl;
	message_passing (G);
	

	rv_1->display_probabilities();
	rv_2->display_probabilities();
	rv_3->display_probabilities();
	rv_4->display_probabilities();
	rv_5->display_probabilities();
	rv_6->display_probabilities();

	// Warning: the Graph isn't reinitialized, and in fact this can have side effects.
	// Example: the variables keep a memory of their marginals, Potentials are linked to the values where they were previously...
	// I should implement initialization routines.	

	cout << "Starting Tree Gibbs Sampler..." << endl;
	
	tree_gibbs_sampler (G,2,10);
	
	rv_1->display_probabilities();
	rv_2->display_probabilities();
	rv_3->display_probabilities();
	rv_4->display_probabilities();
	rv_5->display_probabilities();
	rv_6->display_probabilities();
	
	cout << "Starting Gibbs Sampler..." << endl;
		
	gibbs_sampler (G,1000,100);

	// Display of Results

	rv_1->display_probabilities();
	rv_2->display_probabilities();
	rv_3->display_probabilities();
	rv_4->display_probabilities();
	rv_5->display_probabilities();
	rv_6->display_probabilities();
	
	delete cp;
	delete rv_1;
	delete rv_2;
	delete rv_3;
	delete rv_4;
	delete rv_5;
	delete rv_6;
	delete p_1;
	delete p_2;
	delete p_3;
	delete p_4;
	delete p_5;

}

#endif