added split.abund comand

[mothur.git] / bayesian.cpp

diff --git a/bayesian.cpp b/bayesian.cpp
index 00467ff0feb0a5df82314685520943376582278e..22eab72b60574679f61eca1f02990a3178aecd75 100644 (file)
--- a/bayesian.cpp
+++ b/bayesian.cpp
@@ -177,6 +177,18 @@ Classify(), kmerSize(ksize), confidenceThreshold(cutoff), iters(i)  {
                exit(1);
        }
 }
+/**************************************************************************************************/
+Bayesian::~Bayesian() {
+       try {
+                delete phyloTree; 
+                if (database != NULL) {  delete database; }
+       }
+       catch(exception& e) {
+               m->errorOut(e, "Bayesian", "~Bayesian");
+               exit(1);
+       }
+}
+
 /**************************************************************************************************/
 string Bayesian::getTaxonomy(Sequence* seq) {
        try {
@@ -216,17 +228,11 @@ string Bayesian::getTaxonomy(Sequence* seq) {
 /**************************************************************************************************/
 string Bayesian::bootstrapResults(vector<int> kmers, int tax, int numToSelect) {
        try {
-               
-               //taxConfidenceScore.clear(); //clear out previous seqs scores
                                
-               vector< map<string, int> > confidenceScores; //you need the added vector level of confusion to account for the level that name is seen since they can be the same
-                                                                               //map of classification to confidence for all areas seen
-                                                                          //ie. Bacteria;Alphaproteobacteria;Rhizobiales;Azorhizobium_et_rel.;Methylobacterium_et_rel.;Bosea;
-                                                                          //ie. Bacteria -> 100, Alphaproteobacteria -> 100, Rhizobiales -> 87, Azorhizobium_et_rel. -> 78, Methylobacterium_et_rel. -> 70, Bosea -> 50
-               confidenceScores.resize(100);  //if you have more than 100 levels of classification...
-               
-               map<string, int>::iterator itBoot;
-               map<string, int>::iterator itBoot2;
+               map<int, int> confidenceScores; 
+                               
+               map<int, int>::iterator itBoot;
+               map<int, int>::iterator itBoot2;
                map<int, int>::iterator itConvert;
                
                for (int i = 0; i < iters; i++) {
@@ -248,14 +254,15 @@ string Bayesian::bootstrapResults(vector<int> kmers, int tax, int numToSelect) {
                        //add to confidence results
                        while (taxonomy.level != 0) { //while you are not at the root
                                
-                               itBoot2 = confidenceScores[taxonomy.level].find(taxonomy.name); //is this a classification we already have a count on
+                               itBoot2 = confidenceScores.find(newTax); //is this a classification we already have a count on
                                
-                               if (itBoot2 == confidenceScores[taxonomy.level].end()) { //not already in confidence scores
-                                       confidenceScores[taxonomy.level][taxonomy.name] = 1;
+                               if (itBoot2 == confidenceScores.end()) { //not already in confidence scores
+                                       confidenceScores[newTax] = 1;
                                }else{
-                                       confidenceScores[taxonomy.level][taxonomy.name]++;
+                                       confidenceScores[newTax]++;
                                }
-               
+                               
+                               newTax = taxonomy.parent;
                                taxonomy = phyloTree->get(taxonomy.parent);
                        }
        
@@ -263,15 +270,17 @@ string Bayesian::bootstrapResults(vector<int> kmers, int tax, int numToSelect) {
                
                string confidenceTax = "";
                simpleTax = "";
+               
+               int seqTaxIndex = tax;
                TaxNode seqTax = phyloTree->get(tax);
                
                while (seqTax.level != 0) { //while you are not at the root
                                        
-                               itBoot2 = confidenceScores[seqTax.level].find(seqTax.name); //is this a classification we already have a count on
+                               itBoot2 = confidenceScores.find(seqTaxIndex); //is this a classification we already have a count on
                                
                                int confidence = 0;
-                               if (itBoot2 != confidenceScores[seqTax.level].end()) { //not already in confidence scores
-                                       confidence = confidenceScores[seqTax.level][seqTax.name];
+                               if (itBoot2 != confidenceScores.end()) { //already in confidence scores
+                                       confidence = confidenceScores[seqTaxIndex];
                                }
                                
                                if (((confidence/(float)iters) * 100) >= confidenceThreshold) {
@@ -279,6 +288,7 @@ string Bayesian::bootstrapResults(vector<int> kmers, int tax, int numToSelect) {
                                        simpleTax = seqTax.name + ";" + simpleTax;
                                }
                                
+                               seqTaxIndex = seqTax.parent;
                                seqTax = phyloTree->get(seqTax.parent);
                }