def test_osm_cellids(self): init_('../datipisa/segments_osm_cellids_1M_uint64.csv', "../datipisa/osm_cellids_1M_uint64") pgm = pgm_index(neuroni, init, slope, intercept, False) y = pgm.predict(chiavi).reshape(-1, 1) index = [0] for i in range(1, len(chiavi)): if chiavi[i] == chiavi[i - 1]: index.append(index[i - 1]) else: index.append(i) err = [] for i in range(len(chiavi)): diff = abs(y[i, 0] - index[i]) err.append(diff) x = all(i <= 64.1 for i in err) self.assertEqual(True, x)
def test_pgm(self): model = pgm_index(2, w, slope, intercept, False) x = model.predict([10]) y = np.array([[2]]) self.assertTrue((x == y).all())
x_train = np.fromfile("datipisa/wiki_ts_1M_uint64", dtype=np.uint64) x_train = x_train.reshape(len(x_train), 1) index = [0] for i in range(1, len(x_train)): if x_train[i] == x_train[i - 1]: index.append(index[i-1]) else: index.append(i) init = indice['key'].to_numpy().reshape(1, len(indice)) slope = indice['slope'].to_numpy().reshape(1, len(indice)) intercept = indice['intercept'].to_numpy().reshape(1, len(indice)) neuroni = len(indice) pgm = pgm_index(neuroni, init, slope, intercept, True, dati) # calcolo media con valori presi dai dati y = pgm.predict(x_train) err = [] for i in range(len(x_train)): diff = abs(y[i, 0] - index[i]) err.append(diff) err_max_init = np.amax(err) err_medio_init = np.average(err) init_custom = input("init pesi random? Y/N ") if init_custom == 'Y': dati = False