# Import
import sys
sys.path.append('../')
import loadData
import datetime
# Data
data = loadData.getID2Data()
data_ordered = []
N = len(data)
i = N - 1
while i >= 0:
data_ordered.append(data[i])
i -= 1
file = open("../Trans_Data/ID2_ordered.csv", "w")
file.write("latitude,longitude,time\n")
for p in data_ordered:
file.write(str(p[0]) + ',' + str(p[1]) + ',' + str(p[2]) + "\n")
file.close()
__author__ = "Gabriel"
"""
Kmean on position
"""
import loadData as ld
import clustering as clus
import sklearn.cluster as cluster
import numpy as np
from statistics import mean, median
data = ld.getID2Data()
######If you want to select particular moments in the day
timeShift = -8 # San Francisco
data = ld.dataSelectTime(data, 0, 24, [0, 1, 2, 5, 6], timeShift)
####### Modulo 24 hours
# data = clus.temporalAround24removed(data)
data = clus.temporalAround7Daysremoved(data)
#######Remove time
# data=clus.removeTime(data)
kk = cluster.KMeans(n_clusters=5, random_state=0)
out = kk.fit(data)
clus.plotCluster(data, out.labels_, 5)
print("Cluster center " + str(out.cluster_centers_))
