def test_naive_mstump():
T = np.random.uniform(-1000, 1000, [1, 1000]).astype(np.float64)
m = 20
excl_zone = int(np.ceil(m / 4))
left = np.array(
[
utils.naive_mass(Q,
T[0],
m,
trivial_idx=i,
ignore_trivial=True,
excl_zone=excl_zone)
for i, Q in enumerate(core.rolling_window(T[0], m))
],
dtype=object,
)
left_P = left[np.newaxis, :, 0].T
left_I = left[np.newaxis, :, 1].T
right_P, right_I = utils.naive_mstump(T, m, excl_zone)
npt.assert_almost_equal(left_P, right_P)
npt.assert_almost_equal(left_I, right_I)
def test_mstump(T, m):
excl_zone = int(np.ceil(m / 4))
left_P, left_I = utils.naive_mstump(T, m, excl_zone)
right_P, right_I = mstump(T, m)
npt.assert_almost_equal(left_P, right_P)
npt.assert_almost_equal(left_I, right_I)
def test_mstumped_discords(T, m, dask_cluster):
with Client(dask_cluster) as dask_client:
excl_zone = int(np.ceil(m / 4))
left_P, left_I = utils.naive_mstump(T, m, excl_zone, discords=True)
right_P, right_I = mstumped(dask_client, T, m, discords=True)
npt.assert_almost_equal(left_P, right_P)
npt.assert_almost_equal(left_I, right_I)
def test_mstumped_df(T, m, dask_client):
excl_zone = int(np.ceil(m / 4))
left_P, left_I = utils.naive_mstump(T, m, excl_zone)
df = pd.DataFrame(T.T)
right_P, right_I = mstumped(dask_client, df, m)
npt.assert_almost_equal(left_P, right_P)
npt.assert_almost_equal(left_I, right_I)
def test_mstump_include(T, m):
for i in range(T.shape[0]):
include = np.asarray([i])
excl_zone = int(np.ceil(m / 4))
left_P, left_I = utils.naive_mstump(T, m, excl_zone, include)
right_P, right_I = mstump(T, m, include)
npt.assert_almost_equal(left_P, right_P)
npt.assert_almost_equal(left_I, right_I)
def test_mstumped_include(T, m, dask_cluster):
with Client(dask_cluster) as dask_client:
for i in range(T.shape[0]):
include = np.asarray([i])
excl_zone = int(np.ceil(m / 4))
left_P, left_I = utils.naive_mstump(T, m, excl_zone, include)
right_P, right_I = mstumped(dask_client, T, m, include)
npt.assert_almost_equal(left_P, right_P)
npt.assert_almost_equal(left_I, right_I)
def test_constant_subsequence_self_join():
T_A = np.concatenate((np.zeros(20, dtype=np.float64), np.ones(5, dtype=np.float64)))
T = np.array([T_A, T_A, np.random.rand(T_A.shape[0])])
m = 3
excl_zone = int(np.ceil(m / 4))
left_P, left_I = utils.naive_mstump(T, m, excl_zone)
right_P, right_I = mstump(T, m)
npt.assert_almost_equal(left_P, right_P) # ignore indices
def test_mstumped_one_subsequence_nan_self_join_all_dimensions(
T, m, substitution_location, dask_client):
excl_zone = int(np.ceil(m / 4))
T_sub = T.copy()
T_sub[:, substitution_location] = np.nan
left_P, left_I = utils.naive_mstump(T_sub, m, excl_zone)
right_P, right_I = mstumped(dask_client, T_sub, m)
npt.assert_almost_equal(left_P, right_P)
npt.assert_almost_equal(left_I, right_I)
def test_mstumped_one_subsequence_inf_self_join_first_dimension(
T, m, substitution_location, dask_cluster):
with Client(dask_cluster) as dask_client:
excl_zone = int(np.ceil(m / 4))
T_sub = T.copy()
T_sub[0, substitution_location] = np.inf
left_P, left_I = utils.naive_mstump(T_sub, m, excl_zone)
right_P, right_I = mstumped(dask_client, T_sub, m)
npt.assert_almost_equal(left_P, right_P)
npt.assert_almost_equal(left_I, right_I)
def test_get_first_mstump_profile(T, m):
excl_zone = int(np.ceil(m / 4))
start = 0
left_P, left_I = utils.naive_mstump(T, m, excl_zone)
left_P = left_P[start, :]
left_I = left_I[start, :]
M_T, Σ_T = core.compute_mean_std(T, m)
right_P, right_I = _get_first_mstump_profile(start, T, T, m, excl_zone, M_T, Σ_T)
npt.assert_almost_equal(left_P, right_P)
npt.assert_equal(left_I, right_I)
def test_naive_mstump():
T = np.random.uniform(-1000, 1000, [1, 1000]).astype(np.float64)
m = 20
zone = int(np.ceil(m / 4))
left = utils.naive_stamp(T[0], m, exclusion_zone=zone)
left_P = left[np.newaxis, :, 0].T
left_I = left[np.newaxis, :, 1].T
right_P, right_I = utils.naive_mstump(T, m, zone)
npt.assert_almost_equal(left_P, right_P)
npt.assert_almost_equal(left_I, right_I)
def test_mstump_wrapper(T, m):
excl_zone = int(np.ceil(m / 4))
left_P, left_I = utils.naive_mstump(T, m, excl_zone)
right_P, right_I = mstump(T, m)
npt.assert_almost_equal(left_P, right_P)
npt.assert_almost_equal(left_I, right_I)
df = pd.DataFrame(T.T)
right_P, right_I = mstump(df, m)
npt.assert_almost_equal(left_P, right_P)
npt.assert_almost_equal(left_I, right_I)
def test_mstump_nan_self_join_all_dimensions(T, m, substitute, substitution_locations):
excl_zone = int(np.ceil(m / 4))
T_sub = T.copy()
for substitution_location in substitution_locations:
T_sub[:] = T[:]
T_sub[:, substitution_location] = substitute
left_P, left_I = utils.naive_mstump(T_sub, m, excl_zone)
right_P, right_I = mstump(T_sub, m)
npt.assert_almost_equal(left_P, right_P)
npt.assert_almost_equal(left_I, right_I)
