@Override
public void prepareClusters() {
for (DemoPoint dp : points) {
int c = (int) (k * Math.random());
// System.out.println(dp);
dp.setCluster(c);
}
updateStep();
}
/**
* Unlike the prepareData in KMeansDemo, this method ignores and overwrites the "size" parameter.
* It scans a file and changes them to the appropriate values for the contents of the file
*/
@Override
public void prepareData() {
if (infile == null) {
infile = DEFAULT_IN;
}
DemoPoint.setDimension(this.d);
try {
Scanner in = new Scanner(new File(infile)).useDelimiter("\n");
LinkedList<String> l = new LinkedList<String>();
int count = 0;
while (in.hasNext() && count < size) {
l.add(in.next());
++count;
}
this.size = count;
this.points = new DemoPoint[size];
this.clusters = new DemoPoint[k];
int pointsp = 0;
// parse the big list into data points
for (String inS : l) {
String[] split = inS.split(",");
double[] data = new double[d];
for (int i = 0; i < d; ++i) {
Double din = new Double(split[i]);
data[i] = din;
}
points[pointsp++] = new DemoPoint(data);
}
} catch (IOException e) {
throw new RuntimeException(e); // gotta make it out somehow
}
}
