import random as rand

from clustering import clustering

from point import Point

import csv

import time

start = time.time()

geo_locs = []

#loc_ = Point(0.0, 0.0) #tuples for location

#geo_locs.append(loc_)

#read the fountains location from the csv input file and store each fountain location as a Point(latit,longit) object

f = open('data.csv', 'r')

reader = csv.reader(f, delimiter=",")

for line in reader:

loc_ = Point(line[0], float(line[1]), float(line[2])) #tuples for name and location

geo_locs.append(loc_)

#print len(geo_locs)

#for p in geo_locs:

# print "%f %f" % (p.latit, p.longit)

#let's run k_means clustering. the second parameter is the no of clusters

cluster = clustering(geo_locs, 4 )

flag = cluster.k_means()

end = time.time()

if flag == -1:

print "Error in arguments!"

else:

print "%f" % (end-start)

#the clustering results is a list of lists where each list represents one cluster

print "Clustering results:"

cluster.print_clusters(cluster.clusters)