added classify.shared command and random forest files. added count file to pcr.seqs...

[mothur.git] / rftreenode.cpp

diff --git a/rftreenode.cpp b/rftreenode.cpp
new file mode 100644 (file)
index 0000000..170cfb1
--- /dev/null
+++ b/rftreenode.cpp
@@ -0,0 +1,92 @@
+//
+//  rftreenode.cpp
+//  Mothur
+//
+//  Created by Sarah Westcott on 10/2/12.
+//  Copyright (c) 2012 Schloss Lab. All rights reserved.
+//
+
+#include "rftreenode.hpp"
+
+/***********************************************************************/
+RFTreeNode::RFTreeNode(vector< vector<int> > bootstrappedTrainingSamples,
+           vector<int> globalDiscardedFeatureIndices,
+           int numFeatures,
+           int numSamples,
+           int numOutputClasses,
+           int generation)
+
+: bootstrappedTrainingSamples(bootstrappedTrainingSamples),
+globalDiscardedFeatureIndices(globalDiscardedFeatureIndices),
+numFeatures(numFeatures),
+numSamples(numSamples),
+numOutputClasses(numOutputClasses),
+generation(generation),
+isLeaf(false),
+outputClass(-1),
+splitFeatureIndex(-1),
+splitFeatureValue(-1),
+splitFeatureEntropy(-1.0),
+ownEntropy(-1.0),
+bootstrappedFeatureVectors(numFeatures, vector<int>(numSamples, 0)),
+bootstrappedOutputVector(numSamples, 0),
+leftChildNode(NULL),
+rightChildNode(NULL),
+parentNode(NULL) {
+    m = MothurOut::getInstance();
+    
+    for (int i = 0; i < numSamples; i++) {    // just doing a simple transpose of the matrix
+        if (m->control_pressed) { break; }
+        for (int j = 0; j < numFeatures; j++) { bootstrappedFeatureVectors[j][i] = bootstrappedTrainingSamples[i][j]; }
+    }
+    
+    for (int i = 0; i < numSamples; i++) { if (m->control_pressed) { break; } bootstrappedOutputVector[i] = bootstrappedTrainingSamples[i][numFeatures]; }
+    
+    createLocalDiscardedFeatureList();
+    updateNodeEntropy();
+}
+/***********************************************************************/
+int RFTreeNode::createLocalDiscardedFeatureList(){
+    try {
+
+        for (int i = 0; i < numFeatures; i++) {
+            if (m->control_pressed) { return 0; } 
+            vector<int>::iterator it = find(globalDiscardedFeatureIndices.begin(), globalDiscardedFeatureIndices.end(), i);
+            if (it == globalDiscardedFeatureIndices.end()){                           // NOT FOUND
+                double standardDeviation = m->getStandardDeviation(bootstrappedFeatureVectors[i]);  
+                if (standardDeviation <= 0){ localDiscardedFeatureIndices.push_back(i); }
+            }
+        }
+        
+        return 0;
+    }
+    catch(exception& e) {
+        m->errorOut(e, "RFTreeNode", "createLocalDiscardedFeatureList");
+        exit(1);
+    }  
+}
+/***********************************************************************/
+int RFTreeNode::updateNodeEntropy() {
+    try {
+        
+        vector<int> classCounts(numOutputClasses, 0);
+        for (int i = 0; i < bootstrappedOutputVector.size(); i++) { classCounts[bootstrappedOutputVector[i]]++; }
+        int totalClassCounts = accumulate(classCounts.begin(), classCounts.end(), 0);
+        double nodeEntropy = 0.0;
+        for (int i = 0; i < classCounts.size(); i++) {
+            if (m->control_pressed) { return 0; }
+            if (classCounts[i] == 0) continue;
+            double probability = (double)classCounts[i] / (double)totalClassCounts;
+            nodeEntropy += -(probability * log2(probability));
+        }
+        ownEntropy = nodeEntropy;
+        
+        return 0;
+    }
+    catch(exception& e) {
+        m->errorOut(e, "RFTreeNode", "updateNodeEntropy");
+        exit(1);
+    } 
+}
+
+/***********************************************************************/