def testiraj_anp4():
print("ANP 1 - normalizacija matricom prijelaza s fiktivnom alternativom")
global U, Z
checkDependencies()
global anp
anp = ANP(U, Z)
anp.simulate(matricaPrijelaza=True, fiktivnaAlt=True)
return option_end()
def testiraj_anp1():
print("ANP 1 - normalizacija zbrojem bez fiktivne alternative")
global U, Z
checkDependencies()
global anp
anp = ANP(U, Z)
anp.simulate(matricaPrijelaza=False)
return option_end()
def doClusterTest(usporedba, zavisnost):
usp = MatricaUsporedbi(Generator.izradiMatUsporedbe(ast.literal_eval(usporedba), brojKriterija))
zav = MatricaZavisnosti(Generator.izradiMatZavisnosti(ast.literal_eval(zavisnost), brojKriterija))
anp1 = ANP(usp.weights, zav.Z)
anp1.simulate()
anp2 = ANP(usp.weights, zav.Z)
anp2.simulate(fiktivnaAlt=True, matricaPrijelaza=False)
anp3 = ANP(usp.weights, zav.Z)
anp3.simulate(fiktivnaAlt=False, matricaPrijelaza=True)
anp4 = ANP(usp.weights, zav.Z)
anp4.simulate(matricaPrijelaza=True, fiktivnaAlt=True)
k_anp1 = ANP(usp.weights, zav.Z)
k_anp1.simulate(variant='klasters')
k_anp2 = ANP(usp.weights, zav.Z)
k_anp2.simulate(fiktivnaAlt=True, matricaPrijelaza=False, variant='klasters')
k_anp3 = ANP(usp.weights, zav.Z)
k_anp3.simulate(fiktivnaAlt=False, matricaPrijelaza=True, variant='klasters')
k_anp4 = ANP(usp.weights, zav.Z)
k_anp4.simulate(matricaPrijelaza=True, fiktivnaAlt=True, variant='klasters')
dif1 = np.round(np.abs(anp1.tezine.flatten() - k_anp1.tezine.flatten()), 5)
dif2 = np.round(np.abs(anp2.tezine.flatten() - k_anp2.tezine.flatten()), 5)
dif3 = np.round(np.abs(anp3.tezine.flatten() - k_anp3.tezine.flatten()), 5)
dif4 = np.round(np.abs(anp4.tezine.flatten() - k_anp4.tezine.flatten()), 5)
avg1 = np.average(dif1)
avg2 = np.average(dif2)
avg3 = np.average(dif3)
avg4 = np.average(dif4)
return ((zavisnost, usporedba),
{'ANP1': anp1.tezine.flatten(), 'ANP2': anp2.tezine.flatten(),
'ANP3': anp3.tezine.flatten(), 'ANP4': anp4.tezine.flatten(),
'K_ANP1': k_anp1.tezine.flatten(), 'K_ANP2': k_anp2.tezine.flatten(),
'K_ANP3': k_anp3.tezine.flatten(), 'K_ANP4': k_anp4.tezine.flatten(),
'diff1': dif1, 'diff2': dif2, 'diff3': dif3, 'diff4': dif4,
'avg1': avg1, 'avg2': avg2, 'avg3': avg3, 'avg4': avg4})
def doSimulation(usporedba, zavisnost):
counter = 0
usp = MatricaUsporedbi(
Generator.izradiMatUsporedbe(ast.literal_eval(usporedba),
brojKriterija))
zav = MatricaZavisnosti(
Generator.izradiMatZavisnosti(ast.literal_eval(zavisnost),
brojKriterija))
anp1 = ANP(usp.weights, zav.Z)
anp1.simulate()
anp2 = ANP(usp.weights, zav.Z)
anp2.simulate(fiktivnaAlt=True, matricaPrijelaza=False)
anp3 = ANP(usp.weights, zav.Z)
anp3.simulate(fiktivnaAlt=False, matricaPrijelaza=True)
anp4 = ANP(usp.weights, zav.Z)
anp4.simulate(matricaPrijelaza=True, fiktivnaAlt=True)
snap = SNAP(usp.weights, zav.Z)
snap.simulate()
anp_array = np.hstack((anp1.tezine, anp2.tezine, anp3.tezine, anp4.tezine))
min_anp = np.amin(anp_array, axis=1)
max_anp = np.amax(anp_array, axis=1)
r1_min = min_anp * 0.9
r1_max = max_anp * 1.1
snap_elem_r1 = np.average(
np.logical_and(snap.tezine_S1 <= r1_max, snap.tezine_S1 >= r1_min))
snap2_elem_r1 = np.average(
np.logical_and(snap.tezine_S2 <= r1_max, snap.tezine_S2 >= r1_min))
snap3_elem_r1 = np.average(
np.logical_and(snap.tezine_S3 <= r1_max, snap.tezine_S3 >= r1_min))
snap4_elem_r1 = np.average(
np.logical_and(snap.tezine_S4 <= r1_max, snap.tezine_S4 >= r1_min))
snap5_elem_r1 = np.average(
np.logical_and(snap.tezine_S5 <= r1_max, snap.tezine_S5 >= r1_min))
snap6_elem_r1 = np.average(
np.logical_and(snap.tezine_S6 <= r1_max, snap.tezine_S6 >= r1_min))
snap7_elem_r1 = np.average(
np.logical_and(snap.tezine_S7 <= r1_max, snap.tezine_S7 >= r1_min))
snap8_elem_r1 = np.average(
np.logical_and(snap.tezine_S8 <= r1_max, snap.tezine_S8 >= r1_min))
snap9_elem_r1 = np.average(
np.logical_and(snap.tezine_S9 <= r1_max, snap.tezine_S9 >= r1_min))
snap10_elem_r1 = np.average(
np.logical_and(snap.tezine_S10 <= r1_max, snap.tezine_S10 >= r1_min))
snap11_elem_r1 = np.average(
np.logical_and(snap.tezine_S11 <= r1_max, snap.tezine_S11 >= r1_min))
snap12_elem_r1 = np.average(
np.logical_and(snap.tezine_S12 <= r1_max, snap.tezine_S12 >= r1_min))
r2_min = (min_anp - 0.05).clip(
min=0) # ako razlika daje rezultat ispod nule, postavi na nulu
r2_max = max_anp + 0.05
snap_elem_r2 = np.average(
np.logical_and(snap.tezine_S1 <= r2_max, snap.tezine_S1 >= r2_min))
snap2_elem_r2 = np.average(
np.logical_and(snap.tezine_S2 <= r2_max, snap.tezine_S2 >= r2_min))
snap3_elem_r2 = np.average(
np.logical_and(snap.tezine_S3 <= r2_max, snap.tezine_S3 >= r2_min))
snap4_elem_r2 = np.average(
np.logical_and(snap.tezine_S4 <= r2_max, snap.tezine_S4 >= r2_min))
snap5_elem_r2 = np.average(
np.logical_and(snap.tezine_S5 <= r2_max, snap.tezine_S5 >= r2_min))
snap6_elem_r2 = np.average(
np.logical_and(snap.tezine_S6 <= r2_max, snap.tezine_S6 >= r2_min))
snap7_elem_r2 = np.average(
np.logical_and(snap.tezine_S7 <= r2_max, snap.tezine_S7 >= r2_min))
snap8_elem_r2 = np.average(
np.logical_and(snap.tezine_S8 <= r2_max, snap.tezine_S8 >= r2_min))
snap9_elem_r2 = np.average(
np.logical_and(snap.tezine_S9 <= r2_max, snap.tezine_S9 >= r2_min))
snap10_elem_r2 = np.average(
np.logical_and(snap.tezine_S10 <= r2_max, snap.tezine_S10 >= r2_min))
snap11_elem_r2 = np.average(
np.logical_and(snap.tezine_S11 <= r2_max, snap.tezine_S11 >= r2_min))
snap12_elem_r2 = np.average(
np.logical_and(snap.tezine_S12 <= r2_max, snap.tezine_S12 >= r2_min))
r3_min = (min_anp - 0.1).clip(
min=0) # ako razlika daje rezultat ispod nule, postavi na nulu
r3_max = max_anp + 0.1
snap_elem_r3 = np.average(
np.logical_and(snap.tezine_S1 <= r3_max, snap.tezine_S1 >= r3_min))
snap2_elem_r3 = np.average(
np.logical_and(snap.tezine_S2 <= r3_max, snap.tezine_S2 >= r3_min))
snap3_elem_r3 = np.average(
np.logical_and(snap.tezine_S3 <= r3_max, snap.tezine_S3 >= r3_min))
snap4_elem_r3 = np.average(
np.logical_and(snap.tezine_S4 <= r3_max, snap.tezine_S4 >= r3_min))
snap5_elem_r3 = np.average(
np.logical_and(snap.tezine_S5 <= r3_max, snap.tezine_S5 >= r3_min))
snap6_elem_r3 = np.average(
np.logical_and(snap.tezine_S6 <= r3_max, snap.tezine_S6 >= r3_min))
snap7_elem_r3 = np.average(
np.logical_and(snap.tezine_S7 <= r3_max, snap.tezine_S7 >= r3_min))
snap8_elem_r3 = np.average(
np.logical_and(snap.tezine_S8 <= r3_max, snap.tezine_S8 >= r3_min))
snap9_elem_r3 = np.average(
np.logical_and(snap.tezine_S9 <= r3_max, snap.tezine_S9 >= r3_min))
snap10_elem_r3 = np.average(
np.logical_and(snap.tezine_S10 <= r3_max, snap.tezine_S10 >= r3_min))
snap11_elem_r3 = np.average(
np.logical_and(snap.tezine_S11 <= r3_max, snap.tezine_S11 >= r3_min))
snap12_elem_r3 = np.average(
np.logical_and(snap.tezine_S12 <= r3_max, snap.tezine_S12 >= r3_min))
# Zaokruziti tezine na 5 decimala jer rangiranje zna bit osjetljivo
rank_anp1 = rankdata(np.round(anp1.tezine, 5), method='ordinal')
rank_anp2 = rankdata(np.round(anp2.tezine, 5), method='ordinal')
rank_anp3 = rankdata(np.round(anp3.tezine, 5), method='ordinal')
rank_anp4 = rankdata(np.round(anp4.tezine, 5), method='ordinal')
mean_anp_rank = (rank_anp1 + rank_anp2 + rank_anp3 + rank_anp4) / 4
rank_snap1 = rankdata(np.round(snap.tezine_S1, 5), method='ordinal')
rank_snap2 = rankdata(np.round(snap.tezine_S2, 5), method='ordinal')
rank_snap3 = rankdata(np.round(snap.tezine_S3, 5), method='ordinal')
rank_snap4 = rankdata(np.round(snap.tezine_S4, 5), method='ordinal')
rank_snap5 = rankdata(np.round(snap.tezine_S5, 5), method='ordinal')
rank_snap6 = rankdata(np.round(snap.tezine_S6, 5), method='ordinal')
rank_snap7 = rankdata(np.round(snap.tezine_S7, 5), method='ordinal')
rank_snap8 = rankdata(np.round(snap.tezine_S8, 5), method='ordinal')
rank_snap9 = rankdata(np.round(snap.tezine_S9, 5), method='ordinal')
rank_snap10 = rankdata(np.round(snap.tezine_S10, 5), method='ordinal')
rank_snap11 = rankdata(np.round(snap.tezine_S11, 5), method='ordinal')
rank_snap12 = rankdata(np.round(snap.tezine_S12, 5), method='ordinal')
anp_array = calculate_diff_array(rank_anp1, rank_anp2, rank_anp3,
rank_anp4, rank_snap1)
sk1_snap1 = spearman_difference(np.amin(anp_array, axis=1))
anp_array = calculate_diff_array(rank_anp1, rank_anp2, rank_anp3,
rank_anp4, rank_snap2)
sk1_snap2 = spearman_difference(np.amin(anp_array, axis=1))
anp_array = calculate_diff_array(rank_anp1, rank_anp2, rank_anp3,
rank_anp4, rank_snap3)
sk1_snap3 = spearman_difference(np.amin(anp_array, axis=1))
anp_array = calculate_diff_array(rank_anp1, rank_anp2, rank_anp3,
rank_anp4, rank_snap4)
sk1_snap4 = spearman_difference(np.amin(anp_array, axis=1))
anp_array = calculate_diff_array(rank_anp1, rank_anp2, rank_anp3,
rank_anp4, rank_snap5)
sk1_snap5 = spearman_difference(np.amin(anp_array, axis=1))
anp_array = calculate_diff_array(rank_anp1, rank_anp2, rank_anp3,
rank_anp4, rank_snap6)
sk1_snap6 = spearman_difference(np.amin(anp_array, axis=1))
anp_array = calculate_diff_array(rank_anp1, rank_anp2, rank_anp3,
rank_anp4, rank_snap7)
sk1_snap7 = spearman_difference(np.amin(anp_array, axis=1))
anp_array = calculate_diff_array(rank_anp1, rank_anp2, rank_anp3,
rank_anp4, rank_snap8)
sk1_snap8 = spearman_difference(np.amin(anp_array, axis=1))
anp_array = calculate_diff_array(rank_anp1, rank_anp2, rank_anp3,
rank_anp4, rank_snap9)
sk1_snap9 = spearman_difference(np.amin(anp_array, axis=1))
anp_array = calculate_diff_array(rank_anp1, rank_anp2, rank_anp3,
rank_anp4, rank_snap10)
sk1_snap10 = spearman_difference(np.amin(anp_array, axis=1))
anp_array = calculate_diff_array(rank_anp1, rank_anp2, rank_anp3,
rank_anp4, rank_snap11)
sk1_snap11 = spearman_difference(np.amin(anp_array, axis=1))
anp_array = calculate_diff_array(rank_anp1, rank_anp2, rank_anp3,
rank_anp4, rank_snap12)
sk1_snap12 = spearman_difference(np.amin(anp_array, axis=1))
sk2_snap1 = spearman_difference(mean_anp_rank - rank_snap1)
sk2_snap2 = spearman_difference(mean_anp_rank - rank_snap2)
sk2_snap3 = spearman_difference(mean_anp_rank - rank_snap3)
sk2_snap4 = spearman_difference(mean_anp_rank - rank_snap4)
sk2_snap5 = spearman_difference(mean_anp_rank - rank_snap5)
sk2_snap6 = spearman_difference(mean_anp_rank - rank_snap6)
sk2_snap7 = spearman_difference(mean_anp_rank - rank_snap7)
sk2_snap8 = spearman_difference(mean_anp_rank - rank_snap8)
sk2_snap9 = spearman_difference(mean_anp_rank - rank_snap9)
sk2_snap10 = spearman_difference(mean_anp_rank - rank_snap10)
sk2_snap11 = spearman_difference(mean_anp_rank - rank_snap11)
sk2_snap12 = spearman_difference(mean_anp_rank - rank_snap12)
counter += 1
res = (
(zavisnost, usporedba),
{
'ANP1': anp1.tezine.flatten(),
'ANP2': anp2.tezine.flatten(),
'ANP3': anp3.tezine.flatten(),
'ANP4': anp4.tezine.flatten(),
'SNAP1': snap.tezine_S1.flatten(),
'min_ANP': min_anp,
'max_ANP': max_anp,
'R1_min': r1_min,
'R1_max': r1_max,
'SNAP1_elem_R1': snap_elem_r1,
'SNAP2_elem_R1': snap2_elem_r1,
'SNAP3_elem_R1': snap3_elem_r1,
'SNAP4_elem_R1': snap4_elem_r1,
'SNAP5_elem_R1': snap5_elem_r1,
'SNAP6_elem_R1': snap6_elem_r1,
'SNAP7_elem_R1': snap7_elem_r1,
'SNAP8_elem_R1': snap8_elem_r1,
'SNAP9_elem_R1': snap9_elem_r1,
'SNAP10_elem_R1': snap10_elem_r1,
'SNAP11_elem_R1': snap11_elem_r1,
'SNAP12_elem_R1': snap12_elem_r1,
'R2_min': r2_min,
'R2_max': r2_max,
'SNAP1_elem_R2': snap_elem_r2,
'SNAP2_elem_R2': snap2_elem_r2,
'SNAP3_elem_R2': snap3_elem_r2,
'SNAP4_elem_R2': snap4_elem_r2,
'SNAP5_elem_R2': snap5_elem_r2,
'SNAP6_elem_R2': snap6_elem_r2,
'SNAP7_elem_R2': snap7_elem_r2,
'SNAP8_elem_R2': snap8_elem_r2,
'SNAP9_elem_R2': snap9_elem_r2,
'SNAP10_elem_R2': snap10_elem_r2,
'SNAP11_elem_R2': snap11_elem_r2,
'SNAP12_elem_R2': snap12_elem_r2,
'R3_min': r3_min,
'R3_max': r3_max,
'SNAP1_elem_R3': snap_elem_r3,
'SNAP2_elem_R3': snap2_elem_r3,
'SNAP3_elem_R3': snap3_elem_r3,
'SNAP4_elem_R3': snap4_elem_r3,
'SNAP5_elem_R3': snap5_elem_r3,
'SNAP6_elem_R3': snap6_elem_r3,
'SNAP7_elem_R3': snap7_elem_r3,
'SNAP8_elem_R3': snap8_elem_r3,
'SNAP9_elem_R3': snap9_elem_r3,
'SNAP10_elem_R3': snap10_elem_r3,
'SNAP11_elem_R3': snap11_elem_r3,
'SNAP12_elem_R3': snap12_elem_r3,
# 'rank_ANP1': rank_anp1, 'rank_ANP2': rank_anp2, 'rank_ANP3': rank_anp3,
# 'rank_ANP4': rank_anp4, 'rank_SNAP1': rank_snap1, 'rank_SNAP2': rank_snap2,
# 'rank_SNAP3': rank_snap3, 'rank_SNAP4': rank_snap4, 'rank_SNAP5': rank_snap5,
# 'rank_SNAP6': rank_snap6, 'rank_SNAP7': rank_snap7, 'rank_SNAP8': rank_snap8,
# 'rank_SNAP9': rank_snap9, 'rank_SNAP10': rank_snap10, 'rank_SNAP11': rank_snap11,
# 'rank_SNAP12': rank_snap12,
'sk1_snap1': sk1_snap1,
'sk2_snap1': sk2_snap1,
'sk1_snap2': sk1_snap2,
'sk2_snap2': sk2_snap2,
'sk1_snap3': sk1_snap3,
'sk2_snap3': sk2_snap3,
'sk1_snap4': sk1_snap4,
'sk2_snap4': sk2_snap4,
'sk1_snap5': sk1_snap5,
'sk2_snap5': sk2_snap5,
'sk1_snap6': sk1_snap6,
'sk2_snap6': sk2_snap6,
'sk1_snap7': sk1_snap7,
'sk2_snap7': sk2_snap7,
'sk1_snap8': sk1_snap8,
'sk2_snap8': sk2_snap8,
'sk1_snap9': sk1_snap9,
'sk2_snap9': sk2_snap9,
'sk1_snap10': sk1_snap10,
'sk2_snap10': sk2_snap10,
'sk1_snap11': sk1_snap11,
'sk2_snap11': sk2_snap11,
'sk1_snap12': sk1_snap12,
'sk2_snap12': sk2_snap12
})
return res