# -*- coding: utf-8 -*-
'''
Created on 03-05-2011

@author: jakub
'''
from base import *
import sys, math, random

def kMeans(distanceObject, points, k, cutoff):
    randomPoints = random.sample(points, k)
    clusters = []
    for p in randomPoints:
        clusters.append(CCluster([p]))
    while True:
        lists = []
        for c in clusters:
            lists.append([])
        for p in points:
            nearestCluster = distanceObject.getDistanceBetweenPoints(p, distanceObject.getCentroid(clusters[0]))
            index = 0
            for i in range(len(clusters[1:])):
                distance = distanceObject.getDistanceBetweenPoints(p, distanceObject.getCentroid(clusters[i + 1]))
                if distance < nearestCluster:
                    nearestCluster = distance
                    index = i + 1
            lists[index].append(p)
        bigestChange = 0.0
        for i in range(len(clusters)):
            shift = clusters[i].update(lists[i])
            bigestChange = max(bigestChange, shift)
        if bigestChange < cutoff: break
    return clusters

def makeRandomPunkt(n, lower, upper):
    coords = []
    for i in range(n): coords.append(random.uniform(lower, upper))
    return CPoint(coords)
def main(args):
    input = [x.split(',') for x in open('input').read().split('\n')]
    print input
    punkty = []
    for i in input:
        punkty.append(CPoint(i[:-1]))
    klastry = kSrodki(punkty, len(set([x[0] for x in input])), 0.5)
    print "\nPunkty:"
    for p in punkty: print "P:", p
    print "\nklastry:"
    for c in klastry: print "C:", len(c.punkty), c
if __name__ == "__main__": main(sys.argv)