import numpy as np

def geo_mean(iterable):
    a = np.array(iterable)
    return a.prod()**(1.0/len(a))

def get_vector(A):
    W = []
    norm = 0
    for i in range(A[0].size):
        W.append(geo_mean(A[i]))
        norm += W[i]
    return W/norm



#1
cena = np.array([[1,1/7,1/5],
                [7,1,3],
                [5,1/3,1]])
#2
rozmiar_domu = np.array([[1,5,9],
                [1/5,1,4],
                [1/9,1/4,1]])
#3
dostep = np.array([[1,4,1/5],
                [1/4,1,1/9],
                [5,9,1]])
#4
dzielnica = np.array([[1,9,4],
                [1/9,1,1/4],
                [1/4,4,1]])
#5
wiek = np.array([[1,1,1],
                [1,1,1],
                [1,1,1]])
#6
rozmiar_ogrodka = np.array([[1,6,4],
                [1/6,1,1/3],
                [1/4,3,1]])
#7
wyposazenie = np.array([[1,9,6],
                [1/9,1,1/3],
                [1/6,3,1]])
#8
stan = np.array([[1,1/2,1/2],
                [2,1,1],
                [2,1,1]])


parametry = np.array([[1,4,7,5,8,6,6,2],
                       [1/4,1,5,3,7,6,6,1/3],
                       [1/7,1/5,1,1/3,5,3,3,1/5],
                       [1/5,1/3,3,1,6,3,4,1/2],
                       [1/8,1/7,1/5,1/6,1,1/3,1/4,1/7],
                       [1/6,1/6,1/3,1/3,3,1,1/2,1/5],
                       [1/6,1/6,1/3,1/4,4,2,1,1/5],
                       [1/2,3,5,2,7,5,5,1]])

ranking = get_vector(parametry)
print(ranking)