def test_aamp_motifs_two_motifs():
# Fix seed, because in some case motifs can be off by an index resulting in test
# fails, which is caused since one of the motifs is not repeated perfectly in T.
np.random.seed(1234)
# The time series is random noise with two motifs for m=10:
# * (almost) identical step functions at indices 10, 110 and 210
# * identical linear slopes at indices 70 and 170
T = np.random.normal(size=300)
m = 20
T[10:30] = 1
T[12:28] = 2
# This is not part of the motif in the aamp case
T[110:130] = 3
T[112:128] = 6
T[120] = 6.6
T[210:230] = 1
T[212:228] = 2
T[220] = 1.9
# naive.distance(naive.z_norm(T[10:30]), naive.z_norm(T[110:130])) = 0.47
# naive.distance(naive.z_norm(T[10:30]), naive.z_norm(T[210:230])) = 0.24
# naive.distance(naive.z_norm(T[110:130]), naive.z_norm(T[210:230])) = 0.72
# Hence T[10:30] is the motif representative for this motif
T[70:90] = np.arange(m) * 0.1
T[170:190] = np.arange(m) * 0.1
# naive.distance(naive.z_norm(T[70:90]), naive.z_norm(T[170:190])) = 0.0
max_motifs = 2
mp = naive.aamp(T, m)
# left_indices = [[70, 170], [10, 210]]
left_profile_values = [
[0.0, 0.0],
[
0.0,
naive.distance(T[10:30], T[210:230]),
],
]
right_distance_values, right_indices = aamp_motifs(
T,
mp[:, 0],
max_motifs=max_motifs,
max_distance=0.5,
cutoff=np.inf,
)
# We ignore indices because of sorting ambiguities for equal distances.
# As long as the distances are correct, the indices will be too.
npt.assert_almost_equal(left_profile_values,
right_distance_values,
decimal=6)
# Reset seed
np.random.seed(None)
def test_aamp_motifs_one_motif():
# The top motif for m=3 is a [0 1 0] at indices 0 and 5, while the occurrence
# at index 9 is not a motif in the aamp case.
T = np.array(
[0.0, 1.0, 0.0, -1.0, -1.0, 0.0, 1.0, 0.0, -0.5, 2.0, 3.0, 2.0])
m = 3
max_motifs = 1
left_indices = [[0, 5]]
left_profile_values = [[0.0, 0.0]]
for p in [1.0, 2.0, 3.0]:
mp = naive.aamp(T, m, p=p)
right_distance_values, right_indices = aamp_motifs(
T,
mp[:, 0],
max_motifs=max_motifs,
max_distance=0.001,
cutoff=np.inf,
p=p,
)
npt.assert_array_equal(left_indices, right_indices)
npt.assert_almost_equal(left_profile_values,
right_distance_values,
decimal=4)
def test_motifs(T, m):
if T.ndim > 1:
T = T.copy()
T = T[0]
mp = stumpy.aamp(T, m)
ref = stumpy.aamp_motifs(T, mp[:, 0])
comp = stumpy.motifs(T, mp[:, 0], normalize=False)
npt.assert_almost_equal(ref, comp)