public static FastKNN loadKNN(BTFData btf) throws IOException {
System.out.println("[AntKNN] Loading BTF data...");
FastKNN knn = new FastKNN(FEATURE_DIM, 3);
String[] desiredVel = btf.loadColumn("dvel");
String[] desiredVelBool = btf.loadColumn("dbool");
String[] wallVec = btf.loadColumn("wallvec");
String[] wallBool = btf.loadColumn("wallbool");
String[] antVec = btf.loadColumn("antvec");
String[] antBool = btf.loadColumn("antbool");
String[] homeVec = btf.loadColumn("homevec");
String[] foodVec = btf.loadColumn("foodvec");
String[] prevVec = btf.loadColumn("pvel");
String[] prevBoolVec = btf.loadColumn("pbool");
int numRows = desiredVel.length;
double[] sample = new double[FEATURE_DIM];
double[] velclass = new double[3];
for (int i = 0; i < numRows; i++) {
if (i % (numRows / 10) == 0) System.out.println("[AntKNN] " + i + "/" + numRows);
if (Boolean.parseBoolean(desiredVelBool[i])) {
String[] tmp = desiredVel[i].split(" ");
velclass[0] = Double.parseDouble(tmp[0]);
velclass[1] = Double.parseDouble(tmp[1]);
velclass[2] = Double.parseDouble(tmp[2]);
tmp = antVec[i].split(" ");
sample[0] = Double.parseDouble(tmp[0]);
sample[1] = Double.parseDouble(tmp[1]);
tmp = wallVec[i].split(" ");
sample[2] = Double.parseDouble(tmp[0]);
sample[3] = Double.parseDouble(tmp[1]);
tmp = homeVec[i].split(" ");
sample[4] = Double.parseDouble(tmp[0]);
sample[5] = Double.parseDouble(tmp[1]);
// tmp = foodVec[i].split(" ");
// sample[6] = Double.parseDouble(tmp[0]);
// sample[7] = Double.parseDouble(tmp[1]);
// tmp = prevVec[i].split(" ");
// sample[4] = Double.parseDouble(tmp[0]);
// sample[5] = Double.parseDouble(tmp[1]);
// sample[6] = Double.parseDouble(tmp[2]);
// tmp = homeVec[i].split(" ");
// sample[7] = Double.parseDouble(tmp[0]);
// sample[8] = Double.parseDouble(tmp[1]);
knn.add(sample, velclass);
}
}
// sigmaNormalize currently broken, don't use it! (Dec 4th, 2012)
// knn.sigmaNormalize();
System.out.println("[AntKNN] Done!");
return knn;
}
