Kmeans valid, giving station and its centroid

kmeans.py

 from cassandra.cluster import Cluster
 from datetime import datetime
 
+from sklearn.cluster import KMeans
+import numpy as np
+
 import loading as l
 import history as h
 
@@ -53,10 +56,41 @@ def getDecileForAllStations(startPeriod, endPeriod, table, nb_indicators, indica
 			deciles[station].append({indicators_list[i] : []})
 			# Compute deciles, from 0 to 10 (= includes min and max)
 			for d in range(11):
-				deciles[station][i][indicators_list[i]].append(l[t[3]][i][indicators_list[i]][len(l[t[3]][i][indicators_list[i]]) // 10 * d])
+				if d == 10:
+					deciles[station][i][indicators_list[i]].append(l[station][i][indicators_list[i]][len(l[station][i][indicators_list[i]]) - 1])
+				else:
+					deciles[station][i][indicators_list[i]].append(l[station][i][indicators_list[i]][len(l[station][i][indicators_list[i]]) // 10 * d])
 
 	return deciles
 
+def applyKmeans(deciles, nb_indicators, indicators_list, startPeriod, endPeriod):
+	# Create table without map
+	table = []
+	# Create list with stations name
+	stations_name = []
+
+	for station in deciles.keys():
+		t = []
+		stations_name.append(station)
+		for i in range(nb_indicators):
+			t += deciles[station][i][indicators_list[i]]
+			print (t)
+		table.append(t)
+
+	if len(stations_name) < nb_clusters:
+		print(f"Le nombre de villes ayant des données est trop inférieur ({len(stations_name)}) pour appliquer les kmeans pour la période du {startPeriod} au {endPeriod}")
+		return None
+
+	kmeans = KMeans(n_clusters = 3, max_iter = 100).fit(table)
+
+	res = {}
+	i = 0
+	for station in stations_name:
+		res[station] = kmeans.labels_[i]
+		i += 1
+
+	return res
+
 
 def kmeans(startPeriod, endPeriod, indicators_list):
 	startDate = datetime.strptime(startPeriod, "%Y-%m-%d")
@@ -86,14 +120,17 @@ def kmeans(startPeriod, endPeriod, indicators_list):
 				indicators += "," + ind
 				indicators_list_numeric.append(ind)
 				nb_indicators += 1
-	# print(indicators, nb_indicators)
 	
 	table = getDatasForPeriod(startPeriod, endPeriod, indicators)
 	table = list(table)
 
 	# Get the map with all deciles for all stations and indicators
-	table_decile = getDecileForAllStations(startPeriod, endPeriod, table, nb_indicators, indicators_list_numeric)
-	print (table_decile)
+	table_deciles = getDecileForAllStations(startPeriod, endPeriod, table, nb_indicators, indicators_list_numeric)
+
+	station_with_center = applyKmeans(table_deciles, nb_indicators, indicators_list_numeric, startPeriod, endPeriod)
+	if station_with_center != None:
+		print(f"Voici les villes et le cluster auxquelles elles appartiennent:")
+		print(f"{station_with_center}")
 
 if __name__ == '__main__':
 	cluster = Cluster()
@@ -101,5 +138,6 @@ if __name__ == '__main__':
 	session.set_keyspace("bazinsim_roisinos_metar")
 
 	print()
+	# kmeans("2001-01-01", "2010-12-31", ["tmpf", "skyc1"])
 	kmeans("2001-01-01", "2010-12-31", ["tmpf", "dwpf", "skyc1"])
 	print()