Commit 86c8b86e authored by Oscar Roisin's avatar Oscar Roisin
Browse files

clean code + add map to kmeans

parent 24cbaffa
......@@ -3,15 +3,17 @@ from datetime import datetime
from sklearn.cluster import KMeans
import numpy as np
import folium
import loading as l
import history as h
colours = ['blue', 'red', 'green', 'orange', 'pink', 'white', 'purple', 'gray']
def getDatasForPeriod(startPeriod, endPeriod, indicators):
datas = []
for i in range(int(startPeriod[0:4]), int(endPeriod[0:4]) + 1):
datas += session.execute(f"SELECT year, month, day, station, {indicators} FROM {l.table_name_date} where year = {i}")
datas += session.execute(f"SELECT year, month, day, station, lat, lon, {indicators} FROM {l.table_name_date} where year = {i}")
return datas
......@@ -35,12 +37,12 @@ def getDecileForAllStations(startPeriod, endPeriod, table, nb_indicators, indica
if t[3] not in l.keys():
l[t[3]] = []
for i in range(nb_indicators):
if t[4 + i] != None:
l[t[3]].append({indicators_list[i] : [float(t[4 + i])]})
if t[6 + i] != None:
l[t[3]].append({indicators_list[i] : [float(t[6 + i])]})
for i in range(nb_indicators):
if t[4 + i] != None:
l[t[3]][i][indicators_list[i]].append(float(t[4 + i]))
if t[6 + i] != None:
l[t[3]][i][indicators_list[i]].append(float(t[6 + i]))
# Sort all lists of values
for station in l.keys():
......@@ -77,7 +79,7 @@ def applyKmeans(deciles, nb_indicators, indicators_list, startPeriod, endPeriod)
t += deciles[station][i][indicators_list[i]]
nb_clusters = 3
nb_clusters = 4
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
......@@ -124,14 +126,26 @@ def kmeans(startPeriod, endPeriod, indicators_list):
table = getDatasForPeriod(startPeriod, endPeriod, indicators)
table = list(table)
# Get coordinates
coord = dict()
for t in table:
coord[t[3]]=(t[4], t[5])
# Get the map with all deciles for all stations and indicators
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:")
file_name = f"{startPeriod} to {endPeriod}.html"
# Create map
m = folium.Map(location=[64.2815, 27.6753])
# Add Marker for each station
for key, value in station_with_center.items():
folium.Marker([coord[key][0], coord[key][1]], popup=f"<b>{key}</b>", icon=folium.Icon(color=colours[value])).add_to(m)
# Save map
print(f"La carte a été enregistrée à {file_name}")
print(f"Aucune clusterisation déterminée")
if __name__ == '__main__':
cluster = Cluster()
......@@ -307,7 +307,7 @@ def createTableQueryPartitionningByDate(table):
peak_wind_drct decimal,
peak_wind_time decimal,
metar varchar,
PRIMARY KEY((year, month), day, station, hour, minute)
PRIMARY KEY((year), month, day, station, hour, minute)
return query
......@@ -358,7 +358,7 @@ def insertQueryData(row, table):
return query
# Not to execute when importing file
# Not to execute when importing file
if __name__ == '__main__':
cluster = Cluster()
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