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stim/biomodels/network.h 10.2 KB
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  #ifndef STIM_NETWORK_H
  #define STIM_NETWORK_H
  
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  #include <stdlib.h>
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  #include <assert.h> 
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  #include <sstream>
  #include <fstream>
  #include <algorithm>
  #include <string.h>
  #include <math.h>
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  #include <stim/math/vector.h>
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  #include <stim/visualization/obj.h>
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  #include <stim/biomodels/fiber.h>
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  #include <ANN/ANN.h>
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  #include <boost/tuple/tuple.hpp>
  
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  namespace stim{
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  /** This is the a class that interfaces with gl_spider in order to store the currently
   *   segmented network. The following data is stored and can be extracted:
   *   1)Network geometry and centerline.
   *   2)Network connectivity (a graph of nodes and edges), reconstructed using ANN library.
  */
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  template<typename T>
  class network{
  
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  	///Each edge is a fiber with two nodes.
  	///Each node is an in index to the endpoint of the fiber in the nodes array.
  	class edge : public fiber<T>
  	{
  		public:
  		unsigned v[2];		//unique id's designating the starting and ending
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  		// default constructor
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  		 edge() : fiber<T>(){v[1] = -1; v[0] = -1;}
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  		/// Constructor - creates an edge from a list of points by calling the stim::fiber constructor
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  		///@param p is an array of positions in space
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  		edge(std::vector< stim::vec<T> > p) : fiber<T>(p){}
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  		/// Copy constructor creates an edge from a fiber
  		edge(stim::fiber<T> f) : fiber<T>(f) {}
  
  		/// Resamples an edge by calling the fiber resampling function
  		edge resample(T spacing){
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  			edge e(fiber<T>::resample(spacing));	//call the fiber->edge constructor
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  			e.v[0] = v[0];					//copy the vertex data
  			e.v[1] = v[1];
  
  			return e;						//return the new edge
  		}
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  		/// Output the edge information as a string
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  		std::string str(){
  			std::stringstream ss;
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  			ss<<"("<<fiber<T>::N<<")\tl = "<<length()<<"\t"<<v[0]<<"----"<<v[1];
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  			return ss.str();
  		}
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  	};	
  	
  	///Node class that stores the physical position of the node as well as the edges it is connected to (edges that connect to it), As well as any additional data necessary.
  	class vertex : public stim::vec<T>
  	{
  		public:
  			//std::vector<unsigned int> edges;		//indices of edges connected to this node.
  			std::vector<unsigned int> e[2];			//indices of edges going out (e[0]) and coming in (e[1])
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  			//stim::vec<T> p;						//position of this node in physical space.
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  			//constructor takes a stim::vec
  			vertex(stim::vec<T> p) : stim::vec<T>(p){}
  
  			/// Output the vertex information as a string
  			std::string	str(){
  				std::stringstream ss;
  				ss<<"\t(x, y, z) = "<<stim::vec<T>::str();
  
  				if(e[0].size() > 0){
  					ss<<"\t> ";
  					for(unsigned int o = 0; o < e[0].size(); o++)
  						ss<<e[0][o]<<" ";
  				}
  				if(e[1].size() > 0){
  					ss<<"\t< ";
  					for(unsigned int i = 0; i < e[1].size(); i++)
  						ss<<e[1][i]<<" ";
  				}
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  				return ss.str();
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  			}
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  	};
  
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  	private:
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  	std::vector<edge> E;       //list of edges
  	std::vector<vertex> V;	    //list of vertices.
  	
  	public:
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  	///Returns the number of edges in the network.
  	unsigned int edges(){
  		return E.size();
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  	}
  
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  	///Returns the number of nodes in the network.
  	unsigned int vertices(){
  		return V.size();
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  	}
  
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  	stim::fiber<T> get_fiber(unsigned f){
  		return E[f];					//return the specified edge (casting it to a fiber)
  	}
  
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  	//load a network from an OBJ file
  	void load_obj(std::string filename){
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  		stim::obj<T> O;			//create an OBJ object
  		O.load(filename);		//load the OBJ file as an object
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  		std::vector<unsigned> id2vert;	//this list stores the OBJ vertex ID associated with each network vertex
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  		unsigned i[2];					//temporary, IDs associated with the first and last points in an OBJ line
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  		//for each line in the OBJ object
  		for(unsigned int l = 1; l <= O.numL(); l++){
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  			std::vector< stim::vec<T> > c;				//allocate an array of points for the vessel centerline
  			O.getLine(l, c);							//get the fiber centerline
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  			edge new_edge = c;							//create an edge from the given centerline
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  			//get the first and last vertex IDs for the line
  			std::vector< unsigned > id;					//create an array to store the centerline point IDs
  			O.getLinei(l, id);							//get the list of point IDs for the line			
  			i[0] = id.front();							//get the OBJ ID for the first element of the line
  			i[1] = id.back();							//get the OBJ ID for the last element of the line
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  			std::vector<unsigned>::iterator it;			//create an iterator for searching the id2vert array
  			unsigned it_idx;							//create an integer for the id2vert entry index
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  			//find out if the nodes for this fiber have already been created
  			it = find(id2vert.begin(), id2vert.end(), i[0]);	//look for the first node
  			it_idx = std::distance(id2vert.begin(), it);
  			if(it == id2vert.end()){							//if i[0] hasn't already been used
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  				vertex new_vertex = new_edge[0];				//create a new vertex, assign it a position
  				new_vertex.e[0].push_back(E.size());			//add the current edge as outgoing
  				new_edge.v[0] = V.size();						//add the new vertex to the edge
  				V.push_back(new_vertex);						//add the new vertex to the vertex list
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  				id2vert.push_back(i[0]);						//add the ID to the ID->vertex conversion list
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  			}
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  			else{												//if the vertex already exists
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  				V[it_idx].e[0].push_back(E.size());				//add the current edge as outgoing
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  				new_edge.v[0] = it_idx;
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  			}
  
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  			it = find(id2vert.begin(), id2vert.end(), i[1]);	//look for the second ID
  			it_idx = std::distance(id2vert.begin(), it);
  			if(it == id2vert.end()){							//if i[1] hasn't already been used
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  				vertex new_vertex = new_edge.back();							//create a new vertex, assign it a position
  				new_vertex.e[1].push_back(E.size());						//add the current edge as incoming
  				new_edge.v[1] = V.size();
  				V.push_back(new_vertex);									//add the new vertex to the vertex list
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  				id2vert.push_back(i[1]);						//add the ID to the ID->vertex conversion list
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  			}
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  			else{												//if the vertex already exists
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  				V[it_idx].e[1].push_back(E.size());				//add the current edge as incoming
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  				new_edge.v[1] = it_idx;
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  			}
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  			E.push_back(new_edge);								//push the edge to the list
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  		}
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  	}
  
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  	/// Output the network as a string
  	std::string str(){
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  		std::stringstream ss;
  		ss<<"Nodes ("<<V.size()<<")--------"<<std::endl;
  		for(unsigned int v = 0; v < V.size(); v++){
  			ss<<"\t"<<v<<V[v].str()<<std::endl;
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  		}
  
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  		ss<<"Edges ("<<E.size()<<")--------"<<std::endl;
  		for(unsigned e = 0; e < E.size(); e++){
  			ss<<"\t"<<e<<E[e].str()<<std::endl;
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  		}
  
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  		return ss.str();
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  	}
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  	/// This function resamples all fibers in a network given a desired minimum spacing
  	stim::network<T> resample(T spacing){
  		stim::network<T> n;					//create a new network that will be an exact copy, with resampled fibers
  		n.V = V;							//copy all vertices
  
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  		n.E.resize(edges());				//allocate space for the edge list
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  		//copy all fibers, resampling them in the process
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  		for(unsigned e = 0; e < edges(); e++){				//for each edge in the edge list
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  			n.E[e] = E[e].resample(spacing);				//resample the edge and copy it to the new network
  		}
  
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  		return n;							              //return the resampled network
  	}
  
  
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  	// total number of points on all fibers after resampling -- function used only on a resampled network
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  	unsigned total_points(){
  		unsigned n = 0;
  		for(unsigned e = 0; e < E.size(); e++)
  			n += E[e].size();
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  		return n;
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  	}
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  	// gaussian function
  	float gaussianFunction(float x, float std=25){ return exp(-x/(2*std*std));} // by default std = 25
  
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      // stim 3d vector to annpoint of 3 dimensions
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  	void stim2ann(ANNpoint &a, stim::vec<T> b){
  		a[0] = b[0];
  		a[1] = b[1];
  		a[2] = b[2];
  	}
  
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  	/// This function compares two networks and returns a metric
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  	float compare(stim::network<T> A, float sigma){
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  		float metric = 0.0;                               // initialize metric to be returned after comparing the networks
  		ANNkd_tree* kdt;                                 // initialize a pointer to a kd tree
  		double **c;						                 // centerline (array of double pointers) - points on kdtree must be double
  		unsigned int n_data = total_points();          // set the number of points
  		c = (double**) malloc(sizeof(double*) * n_data); // allocate the array pointer
  		for(unsigned int i = 0; i < n_data; i++)		 // allocate space for each point of 3 dimensions
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  			c[i] = (double*) malloc(sizeof(double) * 3);
  		//std::vector<stim::vec<T> > pointsVector = points_afterResampling(); //get vertices in the network after resampling
  		unsigned t = 0;
  		for(unsigned e = 0; e < E.size(); e++){					//for each edge in the network
  			for(unsigned p = 0; p < E[e].size(); p++){			//for each point in the edge
  				for(unsigned d = 0; d < 3; d++){				//for each coordinate
  
  					c[t][d] = E[e][p][d];
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  				}
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  				t++;
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  			}
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  		}
  
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  		ANNpointArray pts = (ANNpointArray)c;           // create an array of data points of type double
  		kdt = new ANNkd_tree(pts, n_data, 3);			// build a KD tree using the annpointarray
  		double eps = 0; // error bound
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  		ANNdistArray dists = new ANNdist[1];     // near neighbor distances
  		ANNidxArray nnIdx = new ANNidx[1];				// near neighbor indices // allocate near neigh indices
  
  		stim::vec<T> p0, p1;
  		float m0, m1;
  		float M = 0;											//stores the total metric value
  		float l;												//stores the segment length
  		float L = 0;											//stores the total network length
  		ANNpoint queryPt = annAllocPt(3);
  		for(unsigned e = 0; e < A.E.size(); e++){					//for each edge in A
  			M = 0;												//total metric value for the fiber
  			p0 = A.E[e][0];										//get the first point in the edge
  			stim2ann(queryPt, p0);
  			kdt->annkSearch( queryPt, 1, nnIdx, dists, eps);	//find the distance between A and the current network
  			m0 = 1.0f - gaussianFunction(dists[0], sigma);		//calculate the metric value based on the distance
  
  			for(unsigned p = 1; p < A.E[e].size(); p++){			//for each point in the edge
  
  				p1 = A.E[e][p];									//get the next point in the edge
  				stim2ann(queryPt, p1);
  				kdt->annkSearch( queryPt, 1, nnIdx, dists, eps);	//find the distance between A and the current network
  				m1 = 1.0f - gaussianFunction(dists[0], sigma);		//calculate the metric value based on the distance
  
  				//average the metric and scale
  				l = (p1 - p0).len();							//calculate the length of the segment
  				L += l;											//add the length of this segment to the total network length
  				M += (m0 + m1)/2 * l;							//scale the metric based on segment length
  
  				//swap points
  				p0 = p1;
  				m0 = m1;
  			}
  		}
  
  		return M/L;
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  	}
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  };		//end stim::network class
  };		//end stim namespace
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  #endif