def test_output_dimensions():
# test with univariate
X = _make_nested_from_array(np.ones(12), n_instances=10, n_columns=1)
p = PAA(num_intervals=5).fit(X)
res = p.transform(X)
# get the dimension of the generated dataframe.
corr_time_series_length = res.iloc[0, 0].shape[0]
num_rows = res.shape[0]
num_cols = res.shape[1]
assert corr_time_series_length == 5
assert num_rows == 10
assert num_cols == 1
# test with multivariate
X = _make_nested_from_array(np.ones(12), n_instances=10, n_columns=5)
p = PAA(num_intervals=5).fit(X)
res = p.transform(X)
# get the dimension of the generated dataframe.
corr_time_series_length = res.iloc[0, 0].shape[0]
num_rows = res.shape[0]
num_cols = res.shape[1]
assert corr_time_series_length == 5
assert num_rows == 10
assert num_cols == 5
def test_paa_performs_correcly_along_each_dim():
X = _make_nested_from_array(np.array([1, 2, 3, 4, 5, 6, 7, 8, 9, 10]),
n_instances=1,
n_columns=2)
p = PAA(num_intervals=3).fit(X)
res = p.transform(X)
orig = convert_list_to_dataframe([[2.2, 5.5, 8.8], [2.2, 5.5, 8.8]])
orig.columns = X.columns
assert check_if_dataframes_are_equal(res, orig)
def test_output_of_transformer():
X = _make_nested_from_array(np.array([1, 2, 3, 4, 5, 6, 7, 8, 9, 10]),
n_instances=1,
n_columns=1)
p = PAA(num_intervals=3).fit(X)
res = p.transform(X)
orig = convert_list_to_dataframe([[2.2, 5.5, 8.8]])
orig.columns = X.columns
assert check_if_dataframes_are_equal(res, orig)