//for each word
for (int i = 0; i < numKmers; i++) {
+ //m->mothurOut("[DEBUG]: kmer = " + toString(i) + "\n");
+
if (m->control_pressed) { break; }
#ifdef USE_MPI
}
}
+ if (m->debug) { m->mothurOut("[DEBUG]: about to generateWordPairDiffArr\n"); }
generateWordPairDiffArr();
+ if (m->debug) { m->mothurOut("[DEBUG]: done generateWordPairDiffArr\n"); }
//save probabilities
if (rdb->save) { rdb->wordGenusProb = wordGenusProb; rdb->WordPairDiffArr = WordPairDiffArr; }
}
}
- if (queryKmers.size() == 0) { m->mothurOut(seq->getName() + "is bad."); m->mothurOutEndLine(); simpleTax = "unknown;"; return "unknown;"; }
+ if (queryKmers.size() == 0) { m->mothurOut(seq->getName() + " is bad. It has no kmers of length " + toString(kmerSize) + "."); m->mothurOutEndLine(); simpleTax = "unknown;"; return "unknown;"; }
int index = getMostProbableTaxonomy(queryKmers);
//bootstrap - to set confidenceScore
int numToSelect = queryKmers.size() / 8;
+ if (m->debug) { m->mothurOut(seq->getName() + "\t"); }
+
tax = bootstrapResults(queryKmers, index, numToSelect);
+
+ if (m->debug) { m->mothurOut("\n"); }
return tax;
}
int seqTaxIndex = tax;
TaxNode seqTax = phyloTree->get(tax);
+
while (seqTax.level != 0) { //while you are not at the root
itBoot2 = confidenceScores.find(seqTaxIndex); //is this a classification we already have a count on
confidence = itBoot2->second;
}
+ if (m->debug) { m->mothurOut(seqTax.name + "(" + toString(((confidence/(float)iters) * 100)) + ");"); }
+
if (((confidence/(float)iters) * 100) >= confidenceThreshold) {
confidenceTax = seqTax.name + "(" + toString(((confidence/(float)iters) * 100)) + ");" + confidenceTax;
simpleTax = seqTax.name + ";" + simpleTax;
}
-
+
seqTaxIndex = seqTax.parent;
seqTax = phyloTree->get(seqTax.parent);
}