options["-s"]=int(options["-s"])-1
#Gaussians data generation case:
if options["-t"] == "random":
print("génération de donnée aléatoire...")
gaussienne_sample=[]
gaussienne_sample.append({"1":{"direction":[1,0.5],"centre":[5,3]},\
"2":{"direction":[0.1,1],"centre":[0,0]}})
gaussienne_sample.append({"1":{"direction":[1,0.5],"centre":[2,2]},\
"2":{"direction":[0.1,1],"centre":[0,0]}})
gaussienne_sample.append({"1":{"direction":[1,0.5],"centre":[-2,-2]},\
"2":{"direction":[0.1,1],"centre":[0,0]},"3":{"direction":[1,0.5],"centre":[2,2]}})
gen_random_data(gaussienne_sample[options["-s"]])
print("... gaussiennes "+str(options["-s"]+1)+" générées.")
#Iris data generation case:
elif options["-t"] == "iris":
print("generation des données iris...")
gen_iris_data()
print("... données iris générées.")
#picture data generation case:
elif options["-t"] == "picture":
print("génération des données d'image...")
gen_picture_data(options["-n"])
print("... données d'image chargées.")
if options["-d"] == "True":
es.display(es.read_kmeans_input(),None,"Generated datas :",True)
#Read the options: i=1 while i <len(sys.argv): if sys.argv[i] in options: options[sys.argv[i]]=sys.argv[i+1] i+=1 i=i+1 #Process the options display = False k = int(options["-k"]) alpha = float(options["-a"]) #Setting the display option if options["-d"] == "True": display = True #Getting the population population = es.read_kmeans_input() if options["-g"] == "True": #Computing g-means compute_gmeans(population,display=display, k=k, alpha = alpha) else: #computing k-means compute_kmeans(k, population, display = (options['-d']))
