def test_aamp_mmotifs_default_parameters():
motif_distances_ref = np.array(
[[0.0, 0.06315749, 0.25275899, 0.34087884, 0.3452315]])
motif_indices_ref = np.array([[19, 77, 63, 52, 71]])
motif_subspaces_ref = [np.array([2])]
motif_mdls_ref = [
np.array([
411.60964047, 423.69925001, 449.11032383, 476.95855027,
506.62406252
])
]
np.random.seed(0)
T = np.random.rand(500).reshape(5, 100)
m = 5
excl_zone = int(np.ceil(m / config.STUMPY_EXCL_ZONE_DENOM))
P, I = naive.maamp(T, m, excl_zone)
(
motif_distances_cmp,
motif_indices_cmp,
motif_subspaces_cmp,
motif_mdls_cmp,
) = aamp_mmotifs(T, P, I)
npt.assert_array_almost_equal(motif_distances_ref, motif_distances_cmp)
npt.assert_array_almost_equal(motif_indices_ref, motif_indices_cmp)
npt.assert_array_almost_equal(motif_subspaces_ref, motif_subspaces_cmp)
npt.assert_array_almost_equal(motif_mdls_ref, motif_mdls_cmp)
def test_aamp_mmotifs_more_motif_pairs_cutoffs_as_list(T):
motif_distances_ref = np.array([[0.0, 1.41421356]])
motif_indices_ref = np.array([[2, 9]])
motif_subspaces_ref = [np.array([3])]
motif_mdls_ref = [
np.array([244.0, 260.67970001, 279.86313714, 281.35940001])
]
m = 4
cutoffs = [2, 3, 4, 5]
excl_zone = int(np.ceil(m / config.STUMPY_EXCL_ZONE_DENOM))
P, I = naive.maamp(T, m, excl_zone)
(
motif_distances_cmp,
motif_indices_cmp,
motif_subspaces_cmp,
motif_mdls_cmp,
) = aamp_mmotifs(T,
P,
I,
max_distance=np.inf,
cutoffs=cutoffs,
max_matches=2,
max_motifs=10)
npt.assert_array_almost_equal(motif_distances_ref, motif_distances_cmp)
npt.assert_array_almost_equal(motif_indices_ref, motif_indices_cmp)
npt.assert_array_almost_equal(motif_subspaces_ref, motif_subspaces_cmp)
npt.assert_array_almost_equal(motif_mdls_ref, motif_mdls_cmp)
def test_aamp_mmotifs_two_motif_pairs_max_motifs_2(T):
motif_distances_ref = np.array([[0.0, 1.41421356], [0.0, 2.06639783]])
motif_indices_ref = np.array([[2, 9], [0, 5]])
motif_subspaces_ref = [np.array([3]), np.array([2])]
motif_mdls_ref = [
np.array([244.0, 260.67970001, 279.86313714, 281.35940001]),
np.array([254.33985, 260.67970001, 279.86313714, 291.20703549]),
]
m = 4
excl_zone = int(np.ceil(m / config.STUMPY_EXCL_ZONE_DENOM))
P, I = naive.maamp(T, m, excl_zone)
(
motif_distances_cmp,
motif_indices_cmp,
motif_subspaces_cmp,
motif_mdls_cmp,
) = aamp_mmotifs(
T,
P,
I,
max_distance=np.inf,
cutoffs=np.inf,
max_matches=2,
max_motifs=2,
)
npt.assert_array_almost_equal(motif_distances_ref, motif_distances_cmp)
npt.assert_array_almost_equal(motif_indices_ref, motif_indices_cmp)
npt.assert_array_almost_equal(motif_subspaces_ref, motif_subspaces_cmp)
npt.assert_array_almost_equal(motif_mdls_ref, motif_mdls_cmp)
def test_maamp_discords(T, m):
excl_zone = int(np.ceil(m / 4))
ref_P, ref_I = naive.maamp(T, m, excl_zone, discords=True)
comp_P, comp_I = maamp(T, m, discords=True)
npt.assert_almost_equal(ref_P, comp_P)
npt.assert_almost_equal(ref_I, comp_I)
def test_maamp(T, m):
excl_zone = int(np.ceil(m / 4))
for p in [1.0, 2.0, 3.0]:
ref_P, ref_I = naive.maamp(T, m, excl_zone, p=p)
comp_P, comp_I = maamp(T, m, p=p)
npt.assert_almost_equal(ref_P, comp_P)
npt.assert_almost_equal(ref_I, comp_I)
def test_maamp_include(T, m):
for width in range(T.shape[0]):
for i in range(T.shape[0] - width):
include = np.asarray(range(i, i + width + 1))
excl_zone = int(np.ceil(m / 4))
ref_P, ref_I = naive.maamp(T, m, excl_zone, include)
comp_P, comp_I = maamp(T, m, include)
npt.assert_almost_equal(ref_P, comp_P)
npt.assert_almost_equal(ref_I, comp_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))
ref_P, ref_I = naive.maamp(T, m, excl_zone)
comp_P, comp_I = maamp(T, m)
npt.assert_almost_equal(ref_P, comp_P) # ignore indices
def test_query_maamp_profile(T, m):
_T, T_subseq_isfinite = core.preprocess_non_normalized(T, m)
excl_zone = int(np.ceil(m / 4))
for query_idx in range(_T.shape[0] - m + 1):
ref_P, ref_I = naive.maamp(T, m, excl_zone)
ref_P = ref_P[:, query_idx]
ref_I = ref_I[:, query_idx]
comp_P, comp_I = _query_maamp_profile(query_idx, _T, _T, m, excl_zone,
T_subseq_isfinite)
npt.assert_almost_equal(ref_P, comp_P)
npt.assert_equal(ref_I, comp_I)
def test_get_first_maamp_profile(T, m):
excl_zone = int(np.ceil(m / 4))
start = 0
ref_P, ref_I = naive.maamp(T, m, excl_zone)
ref_P = ref_P[:, start]
ref_I = ref_I[:, start]
_T, T_subseq_isfinite = core.preprocess_non_normalized(T, m)
comp_P, comp_I = _get_first_maamp_profile(start, _T, _T, m, excl_zone,
T_subseq_isfinite)
npt.assert_almost_equal(ref_P, comp_P)
npt.assert_equal(ref_I, comp_I)
def test_maamp_wrapper(T, m):
excl_zone = int(np.ceil(m / 4))
ref_P, ref_I = naive.maamp(T, m, excl_zone)
comp_P, comp_I = maamp(T, m)
npt.assert_almost_equal(ref_P, comp_P)
npt.assert_almost_equal(ref_I, comp_I)
df = pd.DataFrame(T.T)
comp_P, comp_I = maamp(df, m)
npt.assert_almost_equal(ref_P, comp_P)
npt.assert_almost_equal(ref_I, comp_I)
def test_naive_maamp():
T = np.random.uniform(-1000, 1000, [1, 1000]).astype(np.float64)
m = 20
zone = int(np.ceil(m / 4))
ref_mp = naive.aamp(T[0], m, exclusion_zone=zone)
ref_P = ref_mp[np.newaxis, :, 0]
ref_I = ref_mp[np.newaxis, :, 1]
comp_P, comp_I = naive.maamp(T, m, zone)
npt.assert_almost_equal(ref_P, comp_P)
npt.assert_almost_equal(ref_I, comp_I)
def test_maamp_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
ref_P, ref_I = naive.maamp(T_sub, m, excl_zone)
comp_P, comp_I = maamp(T_sub, m)
npt.assert_almost_equal(ref_P, comp_P)
npt.assert_almost_equal(ref_I, comp_I)
def test_identical_subsequence_self_join():
identical = np.random.rand(8)
T_A = np.random.rand(20)
T_A[1:1 + identical.shape[0]] = identical
T_A[11:11 + identical.shape[0]] = identical
T = np.array([T_A, T_A, np.random.rand(T_A.shape[0])])
m = 3
excl_zone = int(np.ceil(m / 4))
ref_P, ref_I = naive.maamp(T, m, excl_zone)
comp_P, comp_I = maamp(T, m)
npt.assert_almost_equal(
ref_P, comp_P, decimal=config.STUMPY_TEST_PRECISION) # ignore indices
def test_aamp_mmotifs_max_motifs_1_max_matches_2_k_1(T):
motif_distances_ref = np.array([[0.0, 2.87778559]])
motif_indices_ref = np.array([[0, 5]])
motif_subspaces_ref = [np.array([2, 1])]
motif_mdls_ref = [
np.array([244.0, 260.67970001, 279.86313714, 281.35940001])
]
m = 4
excl_zone = int(np.ceil(m / config.STUMPY_EXCL_ZONE_DENOM))
P, I = naive.maamp(T, m, excl_zone)
(
motif_distances_cmp,
motif_indices_cmp,
motif_subspaces_cmp,
motif_mdls_cmp,
) = aamp_mmotifs(T, P, I, max_distance=np.inf, max_matches=2, k=1)
npt.assert_array_almost_equal(motif_distances_ref, motif_distances_cmp)
npt.assert_array_almost_equal(motif_indices_ref, motif_indices_cmp)
npt.assert_array_almost_equal(motif_subspaces_ref, motif_subspaces_cmp)
npt.assert_array_almost_equal(motif_mdls_ref, motif_mdls_cmp)
def test_aamp_mmotifs_max_distance(T):
motif_distances_ref = np.array(
[[0.0, 1.41421356, 4.46430286, 6.85346628, 8.207923, 8.50529247]])
motif_indices_ref = np.array([[2, 9, 0, 11, 7, 5]])
motif_subspaces_ref = [np.array([3])]
motif_mdls_ref = [
np.array([244.0, 260.67970001, 279.86313714, 281.35940001])
]
m = 4
excl_zone = int(np.ceil(m / config.STUMPY_EXCL_ZONE_DENOM))
P, I = naive.maamp(T, m, excl_zone)
(
motif_distances_cmp,
motif_indices_cmp,
motif_subspaces_cmp,
motif_mdls_cmp,
) = aamp_mmotifs(T, P, I, max_distance=np.inf)
npt.assert_array_almost_equal(motif_distances_ref, motif_distances_cmp)
npt.assert_array_almost_equal(motif_indices_ref, motif_indices_cmp)
npt.assert_array_almost_equal(motif_subspaces_ref, motif_subspaces_cmp)
npt.assert_array_almost_equal(motif_mdls_ref, motif_mdls_cmp)
