X-Git-Url: https://git.donarmstrong.com/?p=mothur.git;a=blobdiff_plain;f=trialSwap2.cpp;h=9959443c9ffbb0c411dfcd0fc6dd6920fbe6f5c8;hp=812077d16c98c5a3c865f197d1ba6f50fbce07a6;hb=050a3ff02473a3d4c0980964e1a9ebe52e55d6b8;hpb=41a0537df3cb09cb8c725eab126fcf9bf28ebd8d

diff --git a/trialSwap2.cpp b/trialSwap2.cpp
index 812077d..9959443 100644
--- a/trialSwap2.cpp
+++ b/trialSwap2.cpp
@@ -4,531 +4,7 @@
 //The sum_of_squares, havel_hakimi and calc_c_score algorithms have been adapted from I. Miklos and J. Podani. 2004. Randomization of presence-absence matrices: comments and new algorithms. Ecology 85:86-92.
 
 
-/**************************************************************************************************/
-int TrialSwap2::sim1(vector<vector<int> > &co_matrix){ 
-    try {
-        vector<int> randRow;
-        vector<vector<int> > tmpmatrix;
-        int nrows = co_matrix.size();
-        int ncols = co_matrix[0].size();
-        
-        //clear co_matrix
-        //     for(i=0;i<nrows;i++)
-        //     {
-        //         co_matrix.clear();
-        //     }
-        
-        //cout << "building matrix" << endl;
-        for(int i=0;i<nrows;i++){
-            if (m->control_pressed) { break; }
-            
-            for(int j=0;j<ncols;j++){
-                double randNum = rand() / double(RAND_MAX);
-                //cout << randNum << endl;
-                
-                if(randNum > 0.5) {
-                    randRow.push_back(1);
-                }else{
-                    randRow.push_back(0);
-                }
-            }
-            tmpmatrix.push_back(randRow);
-            randRow.clear();
-            //cout << endl;
-        }
-        co_matrix = tmpmatrix;
-        
-        return 0;
-    }
-	catch(exception& e) {
-		m->errorOut(e, "TrialSwap2", "sim1");
-		exit(1);
-	}
-}
-/**************************************************************************************************/
-/*
- *row sums fixed, columns equiprobable 
- */
-void TrialSwap2::sim2(vector<vector<int> > &co_matrix)
-{ 
-    try {
-        
-        for(int i=0;i<co_matrix.size();i++)
-        {
-            if (m->control_pressed) { break; }
-            random_shuffle( co_matrix[i].begin(), co_matrix[i].end() ); 
-        }
-    }
-	catch(exception& e) {
-		m->errorOut(e, "TrialSwap2", "sim2");
-		exit(1);
-	}
-}
-/**************************************************************************************************/
-int TrialSwap2::sim2plus(vector<int> rowtotal, vector<vector<int> > &co_matrix)
-{
-    try {
-        int nrows = co_matrix.size();
-        int ncols = co_matrix[0].size();
-        double cellprob = 1.0/ncols;
-        vector<double> cellprobvec;
-        vector<int> tmprow;
-        vector<vector<int> > tmpmatrix;
-        //double randNum;
-        
-        double start = 0.0;
-        
-        for(int i=0; i<ncols; i++)
-        {
-            if (m->control_pressed) { return 0; }
-            cellprobvec.push_back(start + cellprob);
-            start = cellprobvec[i];
-        }
-        
-        for(int i=0; i<nrows; i++)
-        {
-            tmprow.assign(ncols, 0);
-            
-            while( accumulate( tmprow.begin(), tmprow.end(), 0 ) < rowtotal[i])
-            {
-                if (m->control_pressed) { return 0; }
-                double randNum = rand() / double(RAND_MAX);
-                //cout << randNum << endl;
-                if(randNum <= cellprobvec[0])
-                {
-                    tmprow[0] = 1;
-                    continue;
-                }
-                for(int j=1;j<ncols;j++)
-                {
-                    //cout << range[j] << endl;
-                    if(randNum <= cellprobvec[j] && randNum > cellprobvec[j-1] && tmprow[j] != 1)
-                    {
-                        tmprow[j] = 1;
-                    }
-                }
-            }
-            tmpmatrix.push_back(tmprow);
-            tmprow.clear();
-        }
-        co_matrix = tmpmatrix;
-        tmpmatrix.clear();
-        cellprobvec.clear();
-        
-        return 0;
-    }
-	catch(exception& e) {
-		m->errorOut(e, "TrialSwap2", "sim2plus");
-		exit(1);
-	}
-}
-/**************************************************************************************************/
-/*
- * same as sim2 but using initmatrix which is the initial co-occurrence matrix before transposition
- * may have to be changed depending on what matrix 'seed' is used. One way to use is to transpose
- * every null matrix before using an index and use the random matrix as a seed for the next null.
- */
-/**************************************************************************************************/
-void TrialSwap2::sim3(vector<vector<int> > &initmatrix)
-{
-    try {
-        for(int i=0;i<initmatrix.size();i++)
-        {
-            if (m->control_pressed) { break; }
-            random_shuffle( initmatrix[i].begin(), initmatrix[i].end() ); 
-        }
-        
-    }
-	catch(exception& e) {
-		m->errorOut(e, "TrialSwap2", "sim3");
-		exit(1);
-	}
-}
-/**************************************************************************************************/
-/*
- *
- *
- *
- */
-/**************************************************************************************************/
-int TrialSwap2::sim4(vector<int> columntotal, vector<int> rowtotal, vector<vector<int> > &co_matrix)
-{   
-    try {
-        vector<double> colProb;
-        vector<int> tmprow;//(ncols, 7);
-        vector<vector<int> > tmpmatrix;
-        vector<double> range;
-        vector<double> randNums;
-        int ncols = columntotal.size();
-        int nrows = rowtotal.size();
-        tmprow.clear();
-        
-        double colSum = accumulate( columntotal.begin(), columntotal.end(), 0 );
-        //cout << "col sum: " << colSum << endl;
-        for(int i=0;i<ncols;i++)
-        {
-            if (m->control_pressed) { return 0; }
-            colProb.push_back(columntotal[i]/colSum);
-        }
-        
-        double start = 0.0;
-        
-        for(int i=0;i<ncols;i++)
-        {
-            if (m->control_pressed) { return 0; }
-            range.push_back(start + colProb[i]);
-            start = range[i];
-        }
-        
-        for(int i=0;i<nrows;i++)
-        {
-            tmprow.assign(ncols, 0);
-            if (m->control_pressed) { return 0; }
-            
-            while ( accumulate( tmprow.begin(), tmprow.end(), 0 ) < rowtotal[i])
-            {
-                if (m->control_pressed) { return 0; }
-                
-                double randNum = rand() / double(RAND_MAX);
-                if(randNum <= range[0])
-                {
-                    tmprow[0] = 1;
-                    continue;
-                }
-                for(int j=1;j<ncols;j++)
-                {
-                    if(randNum <= range[j] && randNum > range[j-1] && tmprow[j] != 1)
-                    {
-                        tmprow[j] = 1;
-                    }
-                    
-                }
-            }
-            tmpmatrix.push_back(tmprow);
-            tmprow.clear();
-        }
-        
-        co_matrix = tmpmatrix;
-        
-        return 0;
-    }
-	catch(exception& e) {
-		m->errorOut(e, "TrialSwap2", "sim4");
-		exit(1);
-	}
-}
-/**************************************************************************************************/
-/*
- * inverse of sim4, MUST BE TRANSPOSED BEFORE CO-OCCURRENCE ANALYSIS
- *
- *
- */
-/**************************************************************************************************/
-int TrialSwap2::sim5(vector<int> initcolumntotal,vector<int> initrowtotal, vector<vector<int> > &initmatrix)
-{
-    try {
-        vector<double> colProb;
-        vector<int> tmprow;//(ncols, 7);
-        vector<vector<int> > tmpmatrix;
-        vector<double> range;
-        vector<double> randNums;
-        int ncols = initcolumntotal.size();
-        int nrows = initrowtotal.size();
-        
-        tmprow.clear();
-        
-        double colSum = accumulate( initcolumntotal.begin(), initcolumntotal.end(), 0 );
-        //cout << "col sum: " << colSum << endl;
-        for(int i=0;i<ncols;i++)
-        {
-            if (m->control_pressed) { return 0; }
-            colProb.push_back(initcolumntotal[i]/colSum);
-        }
-        
-        double start = 0.0;
-        
-        for(int i=0;i<ncols;i++)
-        {
-            if (m->control_pressed) { return 0; }
-            range.push_back(start + colProb[i]);
-            start = range[i];
-        }
-        
-        for(int i=0;i<nrows;i++)
-        {
-            tmprow.assign(ncols, 0);
-            if (m->control_pressed) { return 0; }
-            
-            while ( accumulate( tmprow.begin(), tmprow.end(), 0 ) < initrowtotal[i])
-            {
-                if (m->control_pressed) { return 0; }
-                
-                double randNum = rand() / double(RAND_MAX);
-                if(randNum <= range[0])
-                {
-                    tmprow[0] = 1;
-                    continue;
-                }
-                for(int j=1;j<ncols;j++)
-                {
-                    if(randNum <= range[j] && randNum > range[j-1] && tmprow[j] != 1)
-                    {
-                        tmprow[j] = 1;
-                    }
-                    
-                }
-            }
-            tmpmatrix.push_back(tmprow);
-            tmprow.clear();
-        }
-        
-        initmatrix = tmpmatrix;
-        return 0;
-    }
-	catch(exception& e) {
-		m->errorOut(e, "TrialSwap2", "sim5");
-		exit(1);
-	}
-}
-/**************************************************************************************************/
-/*
- *
- *
- *
- */
-/**************************************************************************************************/
-int TrialSwap2::sim6(vector<int> columntotal, vector<vector<int> > &co_matrix)
-{
-    try {
-        vector<vector<int> > tmpmatrix;
-        vector<double> colProb;
-        vector<int> tmprow;
-        vector<double> range;
-        int ncols = columntotal.size();
-        int nrows = co_matrix.size();
-        
-        int colSum = accumulate( columntotal.begin(), columntotal.end(), 0 );
-        
-        for(int i=0;i<ncols;i++)
-        {
-            if (m->control_pressed) { return 0; }
-            colProb.push_back(columntotal[i]/double (colSum));
-        }
-        
-        double start = 0.0;
-        
-        for(int i=0;i<ncols;i++)
-        {
-            if (m->control_pressed) { return 0; }
-            range.push_back(start + colProb[i]);
-            start = range[i];
-        }
-        
-        for(int i=0;i<nrows;i++)
-        {
-            if (m->control_pressed) { return 0; }
-            tmprow.assign(ncols, 0);
-            int tmprowtotal;
-            tmprowtotal = (rand() / double (RAND_MAX)) * 10;
-            while ( tmprowtotal > ncols) {
-                if (m->control_pressed) { return 0; }
-                tmprowtotal = (rand() / double (RAND_MAX)) * 10;
-            }
-            //cout << tmprowtotal << endl;
-            //cout << accumulate( tmprow.begin(), tmprow.end(), 0 ) << endl;
-            
-            while ( accumulate( tmprow.begin(), tmprow.end(), 0 ) < tmprowtotal)
-            {
-                if (m->control_pressed) { return 0; }
-                double randNum = rand() / double(RAND_MAX);
-                //cout << randNum << endl;
-                if(randNum <= range[0])
-                {
-                    tmprow[0] = 1;
-                    continue;
-                }
-                for(int j=1;j<ncols;j++)
-                {
-                    //cout << range[j] << endl;
-                    if(randNum <= range[j] && randNum > range[j-1] && tmprow[j] != 1)
-                    {
-                        tmprow[j] = 1;
-                    }
-                    
-                }
-                
-                
-            }
-            
-            tmpmatrix.push_back(tmprow);
-            tmprow.clear();
-        }
-        
-        co_matrix = tmpmatrix;
-        tmpmatrix.clear();
-        
-        return 0;
-    }
-	catch(exception& e) {
-		m->errorOut(e, "TrialSwap2", "sim6");
-		exit(1);
-	}
-}
-/**************************************************************************************************/
-/*
- * MUST BE TRANSPOSED BEFORE CO-OCCURRENCE ANALYSIS
- *
- *
- */
-/**************************************************************************************************/
-int TrialSwap2::sim7(vector<int> initrowtotal, vector<vector<int> > &co_matrix)
-{
-    try {
-        vector<vector<double> > probmatrix;
-        vector<vector<int> > tmpmatrix;
-        vector<double> colProb;
-        vector<double> probrow;
-        vector<int> tmprow;
-        vector<double> range;
-        double nc;
-        int ncols = co_matrix[0].size(); int nrows = co_matrix.size(); 
-        
-        tmpmatrix.assign(nrows, vector<int>(ncols, 0.));
-        
-        int rowsum = accumulate( initrowtotal.begin(), initrowtotal.end(), 0 );
-        
-        nc = rowsum * ncols;
-        //cout << nc << endl;
-        
-        //assign null matrix based on probabilities
-        
-        double start = 0.0; // don't reset start -- probs should be from 0-1 thoughout the entire matrix 
-        
-        for(int i=0;i<nrows;i++)
-        {
-            if (m->control_pressed) { return 0; }
-            //cout << initrowtotal[i]/double(nc) << endl;
-            double cellprob = initrowtotal[i]/double(nc);
-            //cout << cellprob << endl;
-            for(int j=0;j<ncols;j++)
-            {
-                
-                probrow.push_back(start + cellprob);
-                //cout << probrow[j] << endl;
-                //cout << start << endl;
-                start = start + cellprob;
-            }
-            probmatrix.push_back(probrow);
-            probrow.clear();
-        }
-        
-        
-        //while(tmprowsum < rowsum)
-        //for(int k=0;k<rowsum;k++)
-        int k = 0;
-        while(k < rowsum)
-        {
-            if (m->control_pressed) { return 0; }
-        done:
-            //cout << k << endl;
-            //tmprowsum = accumulate( tmprowtotal.begin(), tmprowtotal.end(), 0 );
-            double randNum = rand() / double(RAND_MAX);
-            //cout << randNum << "+" << endl;
-            //special case for the first entry
-            if(randNum <= probmatrix[0][0] && tmpmatrix[0][0] != 1)
-            {
-                tmpmatrix[0][0] = 1;
-                k++;
-                //cout << k << endl;
-                continue;
-            }
-            
-            
-            for(int i=0;i<nrows;i++)
-            {
-                if (m->control_pressed) { return 0; }
-                for(int j=0;j<ncols;j++)
-                {
-                    //cout << probmatrix[i][j] << endl;
-                    if(randNum <= probmatrix[i][j] && randNum > probmatrix[i][j-1] && tmpmatrix[i][j] != 1)
-                    {
-                        tmpmatrix[i][j] = 1;
-                        k++;
-                        //cout << k << endl;
-                        goto done;
-                    }
-                    //else
-                    //k = k-1;
-                }
-                
-            }
-            
-        }
-        
-        co_matrix = tmpmatrix;
-        return 0;
-    //build probibility matrix
-    /* for(int i=0;i<nrows;i++)
-     {
-     for(int j=0;j<ncols;j++)
-     {
-     probrow.push_back(rowtotal[i]/nc);
-     }
-     probmatrix.pushback(probrow);
-     probrow.clear;
-     }
-     */
-    
-    /* int colSum = accumulate( initcolumntotal.begin(), initcolumntotal.end(), 0 );
-        
-        for(int i=0;i<ncols;i++)
-        {
-            colProb.push_back(initcolumntotal[i]/double (colSum));
-        }
-        
-        double start = 0.0;
-        
-        for(int i=0;i<ncols;i++)
-        {
-            range.push_back(start + colProb[i]);
-            start = range[i];
-        }
-        
-        for(int i=0;i<nrows;i++)
-        {
-            tmprow.assign(ncols, 0);
-            int tmprowtotal;
-            tmprowtotal = (rand() / double (RAND_MAX)) * 10;
-            while ( tmprowtotal > ncols)
-                tmprowtotal = (rand() / double (RAND_MAX)) * 10;
-            //cout << tmprowtotal << endl;
-            //cout << accumulate( tmprow.begin(), tmprow.end(), 0 ) << endl;
-            
-            while ( accumulate( tmprow.begin(), tmprow.end(), 0 ) < tmprowtotal)
-            {
-                double randNum = rand() / double(RAND_MAX);
-                //cout << randNum << endl;
-                if(randNum <= range[0])
-                {
-                    tmprow[0] = 1;
-                    continue;
-                }
-                for(int j=1;j<ncols;j++)
-                {
-                    //cout << range[j] << endl;
-                    if(randNum <= range[j] && randNum > range[j-1] && tmprow[j] != 1)
-                    {
-                        tmprow[j] = 1;
-                    }
-                }
-            }
-            
-            tmpmatrix.push_back(tmprow);
-            tmprow.clear();
-        }
-
-/**************************************************************************************************/
-double TrialSwap2::calc_c_score (vector<vector<int> > &co_matrix, vector<int>  rowtotal, int ncols, int nrows)
+double TrialSwap2::calc_c_score (vector<vector<int> > &co_matrix, vector<int> rowtotal, int ncols, int nrows)
 {
     try {
         double cscore = 0.0;
@@ -536,10 +12,10 @@ double TrialSwap2::calc_c_score (vector<vector<int> > &co_matrix, vector<int>  r
         double D;
         double normcscore = 0.0;
         int nonzeros = 0;
-        //int ncols = co_matrix[0].size(); int nrows = rowtotal.size(); 
+        //int ncols = co_matrix[0].size(); int nrows = rowtotal.size();
         vector<vector<double> > s; s.resize(nrows);
         for (int i = 0; i < nrows; i++) { s[i].resize(nrows,0.0); }//only fill half the matrix
-
+        
         
         for(int i=0;i<nrows-1;i++)
         {
@@ -569,28 +45,29 @@ double TrialSwap2::calc_c_score (vector<vector<int> > &co_matrix, vector<int>  r
                 if(maxD != 0)
                 {
                     normcscore += D/maxD;
-                    nonzeros++;    
-                }            
+                    nonzeros++;
+                }
             }
         }
         
-        cscore = cscore/(double)(nrows*(nrows-1)/2);
+        //cscore = cscore/(double)(nrows*(nrows-1)/2);  //not normalized
         //cout << "normalized c score: " << normcscore/nonzeros << endl;
-        
+        cscore = normcscore/(double)nonzeros;
+
         return cscore;
     }
-	catch(exception& e) {
-		m->errorOut(e, "TrialSwap2", "calc_c_score");
-		exit(1);
-	}
+    catch(exception& e) {
+        m->errorOut(e, "TrialSwap2", "calc_c_score");
+        exit(1);
+    }
 }
 /**************************************************************************************************/
-int TrialSwap2::calc_checker (vector<vector<int> > &co_matrix, vector<int>  rowtotal, int ncols, int nrows)
+int TrialSwap2::calc_checker (vector<vector<int> > &co_matrix, vector<int> rowtotal, int ncols, int nrows)
 {
     try {
         int cunits=0;
         //int s[nrows][ncols];
-        //int ncols = co_matrix[0].size(); int nrows = rowtotal.size(); 
+        //int ncols = co_matrix[0].size(); int nrows = rowtotal.size();
         vector<vector<int> > s; s.resize(nrows);
         for (int i = 0; i < nrows; i++) { s[i].resize(nrows,0); }//only fill half the matrix
         
@@ -619,12 +96,12 @@ int TrialSwap2::calc_checker (vector<vector<int> > &co_matrix, vector<int>  rowt
             }
         }
         
-        return cunits;   
+        return cunits;
+    }
+    catch(exception& e) {
+        m->errorOut(e, "TrialSwap2", "calc_checker");
+        exit(1);
     }
-	catch(exception& e) {
-		m->errorOut(e, "TrialSwap2", "calc_checker");
-		exit(1);
-	}
 }
 /**************************************************************************************************/
 double TrialSwap2::calc_vratio (int nrows, int ncols, vector<int> rowtotal, vector<int> columntotal)
@@ -633,14 +110,14 @@ double TrialSwap2::calc_vratio (int nrows, int ncols, vector<int> rowtotal, vect
         //int nrows = rowtotal.size();
         //int ncols = columntotal.size();
         int sumCol = accumulate(columntotal.begin(), columntotal.end(), 0 );
-       // int sumRow = accumulate(rowtotal.begin(), rowtotal.end(), 0 );
+        // int sumRow = accumulate(rowtotal.begin(), rowtotal.end(), 0 );
         
         double colAvg = (double) sumCol / (double) ncols;
- //       double rowAvg = (double) sumRow / (double) nrows;
+        // double rowAvg = (double) sumRow / (double) nrows;
         
         double p = 0.0;
         
- //       double totalRowVar = 0.0;
+        // double totalRowVar = 0.0;
         double rowVar = 0.0;
         double colVar = 0.0;
         
@@ -649,7 +126,7 @@ double TrialSwap2::calc_vratio (int nrows, int ncols, vector<int> rowtotal, vect
             if (m->control_pressed) { return 0; }
             p = (double) rowtotal[i]/(double) ncols;
             rowVar += p * (1.0-p);
-        } 
+        }
         
         for(int i=0;i<ncols;i++)
         {
@@ -665,30 +142,30 @@ double TrialSwap2::calc_vratio (int nrows, int ncols, vector<int> rowtotal, vect
         m->errorOut(e, "TrialSwap2", "calc_vratio");
         exit(1);
     }
-         
+    
 }
 /**************************************************************************************************/
 int TrialSwap2::calc_combo (int nrows, int ncols, vector<vector<int> > &nullmatrix)
 {
     try {
         //need to transpose so we can compare rows (row-major order)
-        int tmpnrows = nrows;
+        //int tmpnrows = nrows;
         vector<vector<int> > tmpmatrix;
-
+        
         vector<int> tmprow;
         if(!tmpmatrix.empty())
             tmpmatrix.clear();
         for (int i=0;i<ncols;i++)
-        {       
+        {
             for (int j=0;j<nrows;j++)
             {
                 tmprow.push_back(nullmatrix[j][i]);
             }
-
+            
             tmpmatrix.push_back(tmprow);
             tmprow.clear();
         }
-
+        
         int unique = 0;
         int match = 0;
         for(int j=0;j<ncols;j++)
@@ -697,44 +174,46 @@ int TrialSwap2::calc_combo (int nrows, int ncols, vector<vector<int> > &nullmatr
             for(int i=j+1;i<=ncols;i++)
             {
                 //comparing matrix rows
-                if( (tmpmatrix[j] == tmpmatrix[i])) 
+                if( (tmpmatrix[j] == tmpmatrix[i]))
                 {
                     match++;
                     break;
                 }
-            }        
-
+            }
+            
             //on the last iteration of a previously matched row it will add itself because it doesn't match any following rows, so that combination is counted
             if (match == 0)
                 unique++;
-    }
-    return unique;
+        }
+        return unique;
     }
     catch(exception& e) {
         m->errorOut(e, "TrialSwap2", "calc_combo");
         exit(1);
     }
-} 
+}
 /**************************************************************************************************/
-int TrialSwap2::swap_checkerboards (vector<vector<int> > &co_matrix)
+int TrialSwap2::swap_checkerboards (vector<vector<int> > &co_matrix, int ncols, int nrows)
 {
     try {
-        int ncols = co_matrix[0].size(); int nrows = co_matrix.size(); 
-        int i, j, k, l;
-        i = m->getRandomIndex(nrows-1);
-        while((j = m->getRandomIndex(nrows-1) ) == i ) {;if (m->control_pressed) { return 0; }}
-        k = m->getRandomIndex(ncols-1);
-        while((l = m->getRandomIndex(ncols-1)) == k ) {;if (m->control_pressed) { return 0; }}
+        //do 100 runs to make sure enough swaps are happening. This does NOT mean that there will be 1000 swaps, but that is the theoretical max.
+        for(int a=0;a<1000;a++){
+            int i, j, k, l;
+            i = m->getRandomIndex(nrows-1);
+            while((j = m->getRandomIndex(nrows-1) ) == i ) {;if (m->control_pressed) { return 0; }}
+            k = m->getRandomIndex(ncols-1);
+            while((l = m->getRandomIndex(ncols-1)) == k ) {;if (m->control_pressed) { return 0; }}
 
-        if((co_matrix[i][k]*co_matrix[j][l]==1 && co_matrix[i][l]+co_matrix[j][k]==0)||(co_matrix[i][k]+co_matrix[j][l]==0 && co_matrix[i][l]*co_matrix[j][k]==1)) //checking for checkerboard value and swap
-        {
-            co_matrix[i][k]=1-co_matrix[i][k];
-            co_matrix[i][l]=1-co_matrix[i][l];
-            co_matrix[j][k]=1-co_matrix[j][k];
-            co_matrix[j][l]=1-co_matrix[j][l];
+            if((co_matrix[i][k]*co_matrix[j][l]==1 && co_matrix[i][l]+co_matrix[j][k]==0)||(co_matrix[i][k]+co_matrix[j][l]==0 && co_matrix[i][l]*co_matrix[j][k]==1)) //checking for checkerboard value and swap
+            {
+                co_matrix[i][k]=1-co_matrix[i][k];
+                co_matrix[i][l]=1-co_matrix[i][l];
+                co_matrix[j][k]=1-co_matrix[j][k];
+                co_matrix[j][l]=1-co_matrix[j][l];
 
+            }
         }
-
+        
         return 0;
     }
     catch(exception& e) {
@@ -797,11 +276,11 @@ double TrialSwap2::t_test (double initialscore, int runs, double nullMean, vecto
         
         m->mothurOut("nullMean: " + toString(nullMean)); m->mothurOutEndLine();
         
-        m->mothurOut("sum: " + toString(sum));  m->mothurOutEndLine();
+        m->mothurOut("sum: " + toString(sum)); m->mothurOutEndLine();
         
         sampleSD = sqrt( (1/runs) * sum );
         
-        m->mothurOut("samplSD: " + toString(sampleSD));  m->mothurOutEndLine();
+        m->mothurOut("samplSD: " + toString(sampleSD)); m->mothurOutEndLine();
         
         t = (nullMean - initialscore) / (sampleSD / sqrt(runs));
         
@@ -813,18 +292,46 @@ double TrialSwap2::t_test (double initialscore, int runs, double nullMean, vecto
     }
 }
 /**************************************************************************************************/
+double TrialSwap2::getSD (int runs, vector<double> scorevec, double nullMean)
+{
+    try{
+        double sum = 0;
+        for(int i=0;i<runs;i++)
+            {
+                if (m->control_pressed) { return 0; }
+                sum += pow((scorevec[i] - nullMean),2);
+            }
+        return sqrt( (1/double(runs)) * sum );
+    }
+    catch(exception& e) {
+        m->errorOut(e, "TrialSwap2", "getSD");
+        exit(1);
+    }
+}
+/**************************************************************************************************/
+double TrialSwap2::get_zscore (double sd, double nullMean, double initscore)
+{
+    try {
+        return (initscore - nullMean) / sd;
+    }
+    catch(exception& e) {
+        m->errorOut(e, "TrialSwap2", "get_zscore");
+        exit(1);
+    }
+}
+/**************************************************************************************************/
 int TrialSwap2::print_matrix(vector<vector<int> > &matrix, int nrows, int ncols)
 {
     try {
-         m->mothurOut("matrix:");  m->mothurOutEndLine();
+        m->mothurOut("matrix:"); m->mothurOutEndLine();
         
         for (int i = 0; i < nrows; i++)
         {
             if (m->control_pressed) { return 0; }
             for (int j = 0; j < ncols; j++)
             {
-                m->mothurOut(toString(matrix[i][j]));            
-            }    
+                m->mothurOut(toString(matrix[i][j]));
+            }
             m->mothurOutEndLine();
         }
         return 0;
@@ -840,4 +347,3 @@ int TrialSwap2::print_matrix(vector<vector<int> > &matrix, int nrows, int ncols)
 
 
 
-