stim/biomodels/network.h

#ifndef STIM_NETWORK_H
#define STIM_NETWORK_H
#include <stdlib.h>
#include <assert.h> 
#include <sstream>
#include <fstream>
#include <algorithm>
#include <string.h>
#include <math.h>
#include <stim/math/vector.h>
#include <stim/visualization/obj.h>
#include <stim/biomodels/fiber.h>
#include <ANN/ANN.h>
#include <boost/tuple/tuple.hpp>
namespace stim{
/** 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.
*/
template<typename T>
class network{
	///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
		// default constructor
		 edge() : fiber<T>(){v[1] = -1; v[0] = -1;}
		/// Constructor - creates an edge from a list of points by calling the stim::fiber constructor
		///@param p is an array of positions in space
		edge(std::vector< stim::vec<T> > p) : fiber<T>(p){}
		/// 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){
			edge e(fiber<T>::resample(spacing));	//call the fiber->edge constructor
			e.v[0] = v[0];					//copy the vertex data
			e.v[1] = v[1];
			return e;						//return the new edge
		}
			
		/// Output the edge information as a string
		std::string str(){
			std::stringstream ss;
			ss<<"("<<fiber<T>::N<<")\tl = "<<length()<<"\t"<<v[0]<<"----"<<v[1];
			return ss.str();
		}
	};	
	
	///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])
			//stim::vec<T> p;						//position of this node in physical space.
			//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]<<" ";
				}
				return ss.str();
			}
			
	};
	private:
	std::vector<edge> E;       //list of edges
	std::vector<vertex> V;	    //list of vertices.
	
	public:
	///Returns the number of edges in the network.
	unsigned int edges(){
		return E.size();
	}
	///Returns the number of nodes in the network.
	unsigned int vertices(){
		return V.size();
	}
	stim::fiber<T> get_fiber(unsigned f){
		return E[f];					//return the specified edge (casting it to a fiber)
	}
	//load a network from an OBJ file
	void load_obj(std::string filename){
		stim::obj<T> O;			//create an OBJ object
		O.load(filename);		//load the OBJ file as an object
		std::vector<unsigned> id2vert;	//this list stores the OBJ vertex ID associated with each network vertex
		unsigned i[2];					//temporary, IDs associated with the first and last points in an OBJ line
		//for each line in the OBJ object
		for(unsigned int l = 1; l <= O.numL(); l++){
			std::vector< stim::vec<T> > c;				//allocate an array of points for the vessel centerline
			O.getLine(l, c);							//get the fiber centerline
			edge new_edge = c;							//create an edge from the given centerline
			//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
			std::vector<unsigned>::iterator it;			//create an iterator for searching the id2vert array
			unsigned it_idx;							//create an integer for the id2vert entry index
			//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
				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
				id2vert.push_back(i[0]);						//add the ID to the ID->vertex conversion list
			}
			else{												//if the vertex already exists
				V[it_idx].e[0].push_back(E.size());				//add the current edge as outgoing
				new_edge.v[0] = it_idx;
			}
			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
				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
				id2vert.push_back(i[1]);						//add the ID to the ID->vertex conversion list
			}
			else{												//if the vertex already exists
				V[it_idx].e[1].push_back(E.size());				//add the current edge as incoming
				new_edge.v[1] = it_idx;
			}
			
			E.push_back(new_edge);								//push the edge to the list
		}
	}
	/// Output the network as a string
	std::string str(){
		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;
		}
		ss<<"Edges ("<<E.size()<<")--------"<<std::endl;
		for(unsigned e = 0; e < E.size(); e++){
			ss<<"\t"<<e<<E[e].str()<<std::endl;
		}
		return ss.str();
	}
	/// 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
		n.E.resize(edges());				//allocate space for the edge list
		//copy all fibers, resampling them in the process
		for(unsigned e = 0; e < edges(); e++){				//for each edge in the edge list
			n.E[e] = E[e].resample(spacing);				//resample the edge and copy it to the new network
		}
		return n;							              //return the resampled network
	}
	// this function gives sum of lengths of all the fibers in the network
	float lengthOfNetwork(){
		stim::fiber<T> FIBER; // initialize a fiber used in looping through all edges casting into fibers in the network
		float networkLength=0;float N=0; // initialize variables for finding total length of all the fibers
		// for each edge in the network
		for (unsigned int i=0; i < E.size(); i ++)
		{
			FIBER = get_fiber(i);                // cast each edge to fiber
			N= FIBER.length();                   // find length of the fiber
			networkLength = networkLength + N;   // running sum of fiber lengths
		}
		return networkLength;
		}
	// list of all the points after resampling -- function used only on a resampled network
	std::vector<stim::vec<T> > points_afterResampling(){
		std::vector<stim::vec<T> > pointsVector; // points in the resampled network
		stim::fiber<T> FIBER; // initialize a fiber used in looping through all edges casting into fibers in the network
		std::vector<stim::vec<T> > pointsFiber;  // resampled points on each fiber of the network
		for(unsigned e = 0; e < E.size(); e++){				 // for each edge in the edge list
			FIBER = get_fiber(e);                            // Cast edge to a fiber
			pointsFiber = FIBER.centerline();              // find points on the edge returns a stim vec
			for (unsigned v = 0; v < FIBER.n_pts(); v++){    // iterate one point at a time from the stim::vec
				pointsVector.push_back(pointsFiber[v]);} //add the points on centerline to the stim::vec points list
		}
		return pointsVector;
	}
	// total number of points on all fibers after resampling -- function used only on a resampled network
	unsigned total_points(){
		unsigned n = 0;
		for(unsigned e = 0; e < E.size(); e++)
			n += E[e].size();
		//unsigned int n = points_afterResampling().size();
		return n;
	}
	// gaussian function
	float gaussianFunction(float x, float std=25){ return exp(-x/(2*std*std));} // by default std = 25
	// sum of values in a stim vector
	float sum(stim::vec<T> metricList){
		float sumMetricList = 0;           // Initialize variable to calculate sum
		for (unsigned int count=0; count<metricList.size(); count++) // for each element in the stim vector
			{ sumMetricList += metricList[count];}                   // running sum of values
		return sumMetricList;
	}
	// distance between two points
	double dist(stim::vec<T> p0, stim::vec<T> p1){
		double sum = 0;                             // initialize variables
		stim::vec<T> v = p1 - p0;;                  // direction vector
		for(unsigned int d = 0; d < 3; d++){        // for each dimension
			sum += v[d] * v[d];}                    // running sum of modulus of direction vector
		return sqrt(sum);
	}
	void stim2ann(ANNpoint &a, stim::vec<T> b){
		a[0] = b[0];
		a[1] = b[1];
		a[2] = b[2];
	}
	/// This function compares two networks and returns a metric
	float compare(stim::network<T> A, float sigma){
		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
			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];
				}
				t++;
			}
		}
		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
		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;
		/*int N;                                        // number of points on the fiber in the second network
		float totalNetworkLength = A.lengthOfNetwork();
		stim::vec<float> fiberMetric(A.edges());    // allocate space for accumulating fiber metric as each fiber is evaluated
	    stim::fiber<T> FIBER;                           // Initialize a fiber will be used in calculating the metric
		//for each fiber in the second network, find nearest distance in the kd tree
		for (unsigned int i=0; i < A.edges(); i ++)   // loop through all the edges/fibers in the network
		{
			FIBER = A.get_fiber(i);              // Get the fiber corresponding to the index i
			std::vector< stim::vec<T> > fiberPoints = FIBER.centerline(); // Get the points on the fiber
			N = FIBER.size();    // number of points on the fiber
			stim::vec<float> segmentMetric(N-1); // allocate space for a vec array that stores metric for each segmen in the fiber
			// for each segment in the fiber
			for (unsigned j = 0; j < N - 1; j++)
			{
				stim::vec<T> p1 = fiberPoints[j];stim::vec<T> p2 = fiberPoints[j+1]; // starting and ending points on the segments
				ANNpoint queryPt1; queryPt1 = annAllocPt(3);  // allocate memory for query points
				ANNpoint queryPt2; queryPt2 = annAllocPt(3);
				//for each dimension of the points connecting segment
				for (unsigned d = 0; d < 3; d++){
					queryPt1[d] = double(fiberPoints[j][d]);       // starting point on segment in network whose closest distance on KD tree should be found
					queryPt2[d] = double(fiberPoints[j + 1][d]);   // ending point on segment in network whose closest distance on KD tree should be found
				}
				kdt->annkSearch( queryPt1, 1, nnIdx1, dists1, eps); // search the nearest point in KD tree to query point(point on network), find the distance
				kdt->annkSearch( queryPt2, 1, nnIdx2, dists2, eps); // search the nearest point in KD tree to query point(point on network), find the distance
				// find the gaussian of the distance and subtract it from 1 to calculate the error 
				float error1 = 1.0f - gaussianFunction(float(dists1[0]), sigma);float error2 = 1.0f - gaussianFunction(float(dists2[0]), sigma);
				// average the error and scale it with distance between the points
				segmentMetric[j] = ((error1 + error2) / 2) * dist(p1, p2) ;
			}
			fiberMetric[i] = sum(segmentMetric);
		}
		metric =  sum(fiberMetric)/totalNetworkLength; //normalize the scaled error of all the points with total length of the network
		assert (0<=metric <=1); //assert metroc os always less than or equal to one and greater than or equal to zero
		return metric;*/
	}
};		//end stim::network class
};		//end stim namespace
#endif