added threshold parameter to make.contigs command.

[mothur.git] / cooccurrencecommand.cpp

diff --git a/cooccurrencecommand.cpp b/cooccurrencecommand.cpp
index b4965f5a91a2d12e4101aadc3b7258741de4945f..e4c915d6a14e4a9755a17d64c073fdda1440803b 100644 (file)
--- a/cooccurrencecommand.cpp
+++ b/cooccurrencecommand.cpp
@@ -180,7 +180,7 @@ int CooccurrenceCommand::execute(){
         m->openOutputFile(outputFileName, out);
         outputNames.push_back(outputFileName);  outputTypes["summary"].push_back(outputFileName);
         out.setf(ios::fixed, ios::floatfield); out.setf(ios::showpoint);
-        out << "metric\tlabel\tScore\tpValue\n";
+        out << "metric\tlabel\tScore\tzScore\tstandardDeviation\n";
 
                //as long as you are not at the end of the file or done wih the lines you want
                while((lookup[0] != NULL) && ((allLines == 1) || (userLabels.size() != 0))) {
@@ -272,6 +272,12 @@ int CooccurrenceCommand::execute(){
 int CooccurrenceCommand::getCooccurrence(vector<SharedRAbundVector*>& thisLookUp, ofstream& out){
     try {
         int numOTUS = thisLookUp[0]->getNumBins();
+        
+        if(numOTUS < 2) {
+            m->mothurOut("Not enough OTUs for co-occurrence analysis, skipping"); m->mothurOutEndLine();
+            return 0;
+        }
+        
         vector< vector<int> > co_matrix; co_matrix.resize(thisLookUp[0]->getNumBins());
         for (int i = 0; i < thisLookUp[0]->getNumBins(); i++) { co_matrix[i].resize((thisLookUp.size()), 0); }
         vector<int> columntotal; columntotal.resize(thisLookUp.size(), 0);
@@ -318,7 +324,7 @@ int CooccurrenceCommand::getCooccurrence(vector<SharedRAbundVector*>& thisLookUp
             }
         }
         //don't need a prob matrix because we just shuffle the rows, may use this in the future
-//        else if (matrix == "sim2") {
+        else if (matrix == "sim2") { }
 //            for(int i=0;i<nrows;i++) {
 //                start = 0.0;
 //                for(int j=0;j<ncols;j++) {
@@ -385,7 +391,7 @@ int CooccurrenceCommand::getCooccurrence(vector<SharedRAbundVector*>& thisLookUp
                 }
             }
         }
-        else if (matrix == "sim9") { }
+        else if (matrix == "sim9" || matrix == "sim2") { }
         else {
             m->mothurOut("[ERROR]: No model selected! \n");
             m->control_pressed = true;
@@ -408,11 +414,11 @@ int CooccurrenceCommand::getCooccurrence(vector<SharedRAbundVector*>& thisLookUp
 
         //burn-in for sim9    
         if(matrix == "sim9") {
-            for(int i=0;i<10000;i++) trial.swap_checkerboards (co_matrix, rowtotal, columntotal, ncols, nrows);
+            for(int i=0;i<10000;i++) trial.swap_checkerboards (co_matrix, ncols, nrows);
         }
 
         //populate null matrix from probability matrix, do this a lot.
-        for(int i=0;i<runs;i++){
+        for(int k=0;k<runs;k++){
             nullmatrix.clear();
             //zero-fill the null matrix
             nullmatrix.assign(nrows, vector<int>(ncols, 0));
@@ -420,6 +426,7 @@ int CooccurrenceCommand::getCooccurrence(vector<SharedRAbundVector*>& thisLookUp
             if(matrix == "sim1" || matrix == "sim6" || matrix == "sim8" || matrix == "sim7") {
                 count = 0;
                 while(count < n) {
+                    if (m->control_pressed) { return 0; }
                 nextnum2:
                     previous = 0.0;
                     randnum = rand() / double(RAND_MAX);
@@ -450,9 +457,10 @@ int CooccurrenceCommand::getCooccurrence(vector<SharedRAbundVector*>& thisLookUp
             
             else if(matrix == "sim4") {
                 for(int i=0;i<nrows;i++) {
-                    previous = 0.0;
                     count = 0;
                     while(count < rowtotal[i]) {
+                        previous = 0.0;
+                        if (m->control_pressed) { return 0; }
                         randnum = rand() / double(RAND_MAX);
                         for(int j=0;j<ncols;j++) {
                             current = probabilityMatrix[ncols * i + j];
@@ -473,6 +481,7 @@ int CooccurrenceCommand::getCooccurrence(vector<SharedRAbundVector*>& thisLookUp
                 for(int j=0;j<ncols;j++) {
                     count = 0;
                     while(count < columntotal[j]) {
+                        if (m->control_pressed) { return 0; }
                         randnum = rand() / double(RAND_MAX);
                         for(int i=0;i<nrows;i++) {
                             current = probabilityMatrix[ncols * i + j];
@@ -490,7 +499,8 @@ int CooccurrenceCommand::getCooccurrence(vector<SharedRAbundVector*>& thisLookUp
             
             //swap_checkerboards takes the original matrix and swaps checkerboards
             else if(matrix == "sim9") {
-                trial.swap_checkerboards (co_matrix, rowtotal, columntotal, ncols, nrows);
+                trial.swap_checkerboards (co_matrix, ncols, nrows);
+                nullmatrix = co_matrix;
             }
             else {
                 m->mothurOut("[ERROR]: No null model selected!\n\n"); m->control_pressed = true;
@@ -526,12 +536,20 @@ int CooccurrenceCommand::getCooccurrence(vector<SharedRAbundVector*>& thisLookUp
         
         m->mothurOutEndLine(); m->mothurOut("average metric score: " + toString(nullMean)); m->mothurOutEndLine();
         
+        //calc_p_value is not a statistical p-value, it's just the average that are either > or < the initscore.
+        //All it does is show what is expected in a competitively structured community
+        //zscore is output so p-value can be looked up in a ztable
         double pvalue = 0.0;
         if (metric == "cscore" || metric == "checker") { pvalue = trial.calc_pvalue_greaterthan (stats, initscore); }
         else{ pvalue = trial.calc_pvalue_lessthan (stats, initscore); }
+
+        double sd = trial.getSD(runs, stats, nullMean);
+
+        double zscore = trial.get_zscore(sd, nullMean, initscore);
         
-        m->mothurOut("pvalue: " + toString(pvalue)); m->mothurOutEndLine();
-        out << metric << '\t' << thisLookUp[0]->getLabel() << '\t' << nullMean << '\t' << pvalue << endl;
+        m->mothurOut("zscore: " + toString(zscore)); m->mothurOutEndLine();
+        m->mothurOut("standard deviation: " + toString(sd)); m->mothurOutEndLine();
+        out << metric << '\t' << thisLookUp[0]->getLabel() << '\t' << nullMean << '\t' << zscore << '\t' << sd << endl;
         
         return 0;
     }