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database_pre2.py

@@ -6,7 +6,7 @@ import re
 def connection():
     import cassandra.cluster
     cluster = cassandra.cluster.Cluster(['localhost'])
-    session = cluster.connect('meurouth_cql')
+    session = cluster.connect('caitiany')
     return session
 
 def databaseCreate_Q2(session):
@@ -143,7 +143,7 @@ def insertion_sql_Q2(filename,session):
         data["metar"])
 
         query = """
-        INSERT INTO database_time(
+        INSERT INTO database_kmeans(
         date,
         lon,
         lat,

question1.py

@@ -140,6 +140,7 @@ def drawCourbe_history(session,time,target,timeNB,targetNB,espace):
     print ("Generate successfully")
 
 
+#Check which number of the indicateur
 def checkNBvariable (x):
     i=0
     for each in table_variable:
@@ -160,7 +161,7 @@ def caculateMean_Season(result):
         i += 1
     return total/i , i
 
-
+#Draw the courbe of the fonction2
 def drawCourbe_season(session,season,target,targetNB,espace):
     data = session.execute_async("select * from caitiany.database_espace where station = '%s'"%espace )
     #We do the same map reduce as fonction 1 by fixing the time as season

question2.py

@@ -36,7 +36,7 @@ def createMap(data):
         folium.Marker([each[2],each[1]],
                       popup=string,
                       icon=folium.Icon(color='red')).add_to(m)
-    m.save("Projet-NF26/map.html")
+    m.save("Projet-NF26/map2.html")
 
 
 if __name__ == "__main__":

question3.py

@@ -72,12 +72,12 @@ def mapFonction1 (x):
 def mapFonction2 (x):
     return x[1]/x[0]
 
-
+#Test if it is a type mean
 def testNan (x):
     test = x != x
     return test
 
-
+#Map reduce to caculate the means of each station
 def mapReduce_kmeans(data,targetNB):
     results = dict()
     for row in data.result():
@@ -94,7 +94,7 @@ def mapReduce_kmeans(data,targetNB):
         results[eachEspace] = mapFonction2(results[eachEspace])
     return results
 
-
+#Caculate the difference of the number of the clusters 
 def cluster_nb_diff(centre_new,centre):
     sum = 0
     for i in range(3):
@@ -110,9 +110,8 @@ def map1_kmeans(x):
 def mapCentre(x):
     return [x[0],x[1],x[2],0]
 
-#input [tmpt,tmpt,tmpt,tmpt] and [c1,c2,c3,0] -> [|tmpt - c1|,|tmpt - c2|,|tmpt - c3|,tmpt]
-
 
+#input [tmpt,tmpt,tmpt,tmpt] and [c1,c2,c3,0] -> [|tmpt - c1|,|tmpt - c2|,|tmpt - c3|,tmpt]
 def reduceKmeans (x,y):
     result = []
     for i in range(4):
@@ -132,7 +131,7 @@ def map2_kmeans(x):
 
 
 
-
+#Update the new center by means
 def MapnewCentre(x):
     if x[0] != 0:
         return x[1]/x[0]
@@ -140,7 +139,7 @@ def MapnewCentre(x):
         return 0
 
 
-
+#The main algorithm of Kmeans
 def kmeans (data,targetNB,target):
     #cluster est pour stocler lat, lon de chaque point de chaque cluster
     cluster = [[],[],[]]
@@ -205,7 +204,6 @@ def kmeans (data,targetNB,target):
         else:
             #caculate the new centre
             print ("Cluster number differ:  ",cluster_nb_diff(centre_new,centre))
-            print (centre_new)
             for eachculster in centre_new:
                 centre_new[eachculster][1] = MapnewCentre(centre_new[eachculster])
             print("center new: ",centre_new)
@@ -216,7 +214,7 @@ def kmeans (data,targetNB,target):
             cluster = [[],[],[]]
     createMap(cluster,result)
 
-
+#Create the map of the cluster
 def createMap (cluster,result):
     mean_lat = 0
     count = 0
@@ -245,12 +243,11 @@ def createMap (cluster,result):
                         popup=label,
                         icon=folium.Icon(color=color[i])).add_to(m)
         i +=1
-    print(i)
     m.save("Projet-NF26/map.html")
     print("Generate successfully")
 
 
-
+#Check which number of the indicateur
 def checkNBvariable (x):
     i=0
     for each in table_variable: