working on nmds

[mothur.git] / linearalgebra.cpp

diff --git a/linearalgebra.cpp b/linearalgebra.cpp
index 6b56597f10501b4720d77b28ca08961d2c35554e..27d35ac2cd7c40d4502aa469ffa62f2d01ff31ec 100644 (file)
--- a/linearalgebra.cpp
+++ b/linearalgebra.cpp
@@ -326,41 +326,46 @@ vector< vector<double> > LinearAlgebra::calculateEuclidianDistance(vector< vecto
        }
 }
 /*********************************************************************************************************************************/
+//assumes both matrices are square and the same size
 double LinearAlgebra::calcPearson(vector< vector<double> >& euclidDists, vector< vector<double> >& userDists){
        try {
                
                //find average for - X
-               vector<float> averageEuclid; averageEuclid.resize(euclidDists.size(), 0.0);
+               int count = 0;
+               float averageEuclid = 0.0; 
                for (int i = 0; i < euclidDists.size(); i++) {
-                       for (int j = 0; j < euclidDists[i].size(); j++) {
-                               averageEuclid[i] += euclidDists[i][j];  
+                       for (int j = 0; j < i; j++) {
+                               averageEuclid += euclidDists[i][j];  
+                               count++;
                        }
                }
-               for (int i = 0; i < averageEuclid.size(); i++) {  averageEuclid[i] = averageEuclid[i] / (float) euclidDists.size();   }
-               
+               averageEuclid = averageEuclid / (float) count;   
+                       
                //find average for - Y
-               vector<float> averageUser; averageUser.resize(userDists.size(), 0.0);
+               count = 0;
+               float averageUser = 0.0; 
                for (int i = 0; i < userDists.size(); i++) {
-                       for (int j = 0; j < userDists[i].size(); j++) {
-                               averageUser[i] += userDists[i][j];  
+                       for (int j = 0; j < i; j++) {
+                               averageUser += userDists[i][j]; 
+                               count++;
                        }
                }
-               for (int i = 0; i < averageUser.size(); i++) {  averageUser[i] = averageUser[i] / (float) userDists.size();  }
-               
+               averageUser = averageUser / (float) count;  
+
                double numerator = 0.0;
                double denomTerm1 = 0.0;
                double denomTerm2 = 0.0;
                
                for (int i = 0; i < euclidDists.size(); i++) {
                        
-                       for (int k = 0; k < i; k++) {
+                       for (int k = 0; k < i; k++) { //just lt dists
                                
                                float Yi = userDists[i][k];
                                float Xi = euclidDists[i][k];
                                
-                               numerator += ((Xi - averageEuclid[k]) * (Yi - averageUser[k]));
-                               denomTerm1 += ((Xi - averageEuclid[k]) * (Xi - averageEuclid[k]));
-                               denomTerm2 += ((Yi - averageUser[k]) * (Yi - averageUser[k]));
+                               numerator += ((Xi - averageEuclid) * (Yi - averageUser));
+                               denomTerm1 += ((Xi - averageEuclid) * (Xi - averageEuclid));
+                               denomTerm2 += ((Yi - averageUser) * (Yi - averageUser));
                        }
                }
                
@@ -368,6 +373,7 @@ double LinearAlgebra::calcPearson(vector< vector<double> >& euclidDists, vector<
                double r = numerator / denom;
                
                return r;
+               
        }
        catch(exception& e) {
                m->errorOut(e, "LinearAlgebra", "calculateEuclidianDistance");