removed functions not in use

pranathivemuri
1 parent 797f8ab0
Showing 2 changed files with 1 additions and 118 deletions Show diff stats
stim/biomodels/fiber.h
stim/biomodels/network.h
@@ -281,39 +281,6 @@ public:
 	T radius(int idx){
 		return r[idx];
 	}
-	/// get index of a node on a fiber
-	// by matching the node on fiber to already set vertices (both strings)
-	// used in obj file conversion
-	int
-	getIndexes(std::string* input, std::string searched, int sizeV)
-	{
-		int result = 0;
-		for (int i = 0; i < sizeV; i++)
-		{
-			if (input[i] == searched)
-			{
-				result = i + 1;
-			}
-		}
-		return result;
-    }
-		// strObj returns a string of fiber indices corresponding to vectors of positions in the fiber including intermediate nodes
-	std::string
-	strObj(std::string* strArray, int sizeV)
-	{
-		std::stringstream ss;
-		std::stringstream oss;
-		for(unsigned int i = 0; i < N; i++)
-		{
-			ss.str(std::string());
-			for(unsigned int d = 0; d < 3; d++)
-			{
-				ss<<c[i][d];
-			}
-			oss<<getIndexes(strArray, ss.str(), sizeV)<<" ";
-		}
-		return oss.str();
-	}
  
 	/// Return the point on the fiber closest to q
 	/// @param q is the query point used to locate the nearest point on the fiber centerline
@@ -207,66 +207,19 @@ class 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);
-	}
-
+    // stim 3d vector to annpoint of 3 dimensions
 	void stim2ann(ANNpoint &a, stim::vec<T> b){
 		a[0] = b[0];
 		a[1] = b[1];
@@ -333,43 +286,6 @@ class network{
 		}
  
 		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