def test_custom_fn_impute(pos1, pos2, expected, mw_data):
mw_data[pos1, pos2] = np.nan
imputed = impy.moving_window(mw_data, func=lambda l: max(l) * 2)
return_na_check(imputed)
assert imputed[pos1, pos2] == expected
def test_custom_nindex_impute_1(pos1, pos2, expected, mw_data):
mw_data[pos1, pos2] = np.nan
imputed = impy.moving_window(mw_data, nindex=-1)
return_na_check(imputed)
assert imputed[pos1, pos2] == expected
def test_custom_nindex_impute_rightmost_index_valid(data):
data[2][-1] = np.nan
imputed = impy.moving_window(data, nindex=-1)
assert not np.isnan(imputed).any()
assert imputed[2][-1] == 11.5
def test_defaults_impute(pos1, pos2, expected, mw_data):
mw_data[pos1, pos2] = np.nan
imputed = impy.moving_window(mw_data)
return_na_check(imputed)
assert imputed[pos1, pos2] == expected
def test_custom_fn_impute_rightmost_index(data):
data[2][-1] = np.nan
imputed = impy.moving_window(data, func=lambda l: max(l) * 2)
assert not np.isnan(imputed).any()
assert imputed[2][-1] == 26
def test_custom_nindex_impute_leftmost_falls_off(data):
data[2][-1] = np.nan
imputed = impy.moving_window(data, nindex=0)
assert not np.isnan(imputed).any()
assert imputed[2][-1] == 12.5
def test_defaults_impute_middle_index(data):
data[2][2] = np.nan
imputed = impy.moving_window(data)
assert not np.isnan(imputed).any()
assert imputed[2][2] == 12
def test_defaults_impute_rightmost_index(data):
data[2][-1] = np.nan
imputed = impy.moving_window(data)
assert not np.isnan(imputed).any()
assert imputed[2][-1] == 12.5
def test_impute_rightmost_index(self):
self.data[2][-1] = np.nan
imputed = impy.moving_window(self.data, nindex=0)
self.assertFalse(np.isnan(imputed).any())
self.assertEqual(imputed[2][-1], 12.5)
def test_impute_leftmost_index(self):
self.data[2][0] = np.nan
imputed = impy.moving_window(self.data, nindex=-1)
self.assertFalse(np.isnan(imputed).any())
self.assertEqual(imputed[2][0], 11.5)
def test_impute_rightmost_index(self):
self.data[2][-1] = np.nan
imputed = impy.moving_window(self.data, func=lambda l: max(l) * 2)
self.assertFalse(np.isnan(imputed).any())
self.assertEqual(imputed[2][-1], 26)
def test_impute_middle_index(self):
self.data[2][2] = np.nan
imputed = impy.moving_window(self.data)
self.assertFalse(np.isnan(imputed).any())
self.assertEqual(imputed[2][2], 12)
df = DataFrame(data)
cols = list()
# input sequence (t-n, ... t-1)
for i in range(n_in, 0, -1):
cols.append(df.shift(i))
# forecast sequence (t, t+1, ... t+n)
for i in range(0, n_out):
cols.append(df.shift(-i))
# put it all together
agg = concat(cols, axis=1)
return agg.values
series = read_csv(
'../data/datasets/test_datasets/openstack_controller_server_final_week_nan.csv',
header=0,
index_col=0,
parse_dates=True,
squeeze=True)
A = series_to_supervised(series.values, n_in=3)
# A = series.values.reshape(-1, 1)
test_2 = impy.moving_window(A, wsize=5)
# print(test_2)
pc = PCA(data=A, ncomp=1, missing='fill-em')
# noinspection PyProtectedMember
B = pc._adjusted_data
print(B)
