def test_scraamp_int_input():
with pytest.raises(TypeError):
scraamp(np.arange(10),
5,
ignore_trivial=True,
percentage=1.0,
pre_scraamp=False)
def test_scraamp_nan_zero_mean_self_join(percentages):
T = np.array([-1, 0, 1, np.inf, 1, 0, -1])
m = 3
zone = int(np.ceil(m / 4))
for percentage in percentages:
seed = np.random.randint(100000)
np.random.seed(seed)
ref_mp = naive.scraamp(T, m, T, percentage, zone, False, None)
ref_P = ref_mp[:, 0]
ref_I = ref_mp[:, 1]
ref_left_I = ref_mp[:, 2]
ref_right_I = ref_mp[:, 3]
np.random.seed(seed)
approx = scraamp(T, m, percentage=percentage, pre_scraamp=False)
approx.update()
comp_P = approx.P_
comp_I = approx.I_
comp_left_I = approx.left_I_
comp_right_I = approx.right_I_
naive.replace_inf(ref_P)
naive.replace_inf(comp_P)
npt.assert_almost_equal(ref_P, comp_P)
npt.assert_almost_equal(ref_I, comp_I)
npt.assert_almost_equal(ref_left_I, comp_left_I)
npt.assert_almost_equal(ref_right_I, comp_right_I)
def test_scraamp_identical_subsequence_self_join(percentages):
identical = np.random.rand(8)
T = np.random.rand(20)
T[1 : 1 + identical.shape[0]] = identical
T[11 : 11 + identical.shape[0]] = identical
m = 3
zone = int(np.ceil(m / 4))
for percentage in percentages:
seed = np.random.randint(100000)
np.random.seed(seed)
ref_mp = naive.scraamp(T, m, T, percentage, zone, False, None)
ref_P = ref_mp[:, 0]
# ref_I = ref_mp[:, 1]
# ref_left_I = ref_mp[:, 2]
# ref_right_I = ref_mp[:, 3]
np.random.seed(seed)
approx = scraamp(
T, m, ignore_trivial=True, percentage=percentage, pre_scraamp=False
)
approx.update()
comp_P = approx.P_
# comp_I = approx.I_
# comp_left_I = approx.left_I_
# comp_right_I = approx.right_I_
naive.replace_inf(ref_P)
naive.replace_inf(comp_P)
npt.assert_almost_equal(ref_P, comp_P, decimal=config.STUMPY_TEST_PRECISION)
def test_scraamp_constant_subsequence_self_join(percentages):
T = np.concatenate((np.zeros(20, dtype=np.float64), np.ones(5, dtype=np.float64)))
m = 3
zone = int(np.ceil(m / 4))
for percentage in percentages:
seed = np.random.randint(100000)
np.random.seed(seed)
ref_mp = naive.scraamp(T, m, T, percentage, zone, False, None)
ref_P = ref_mp[:, 0]
# ref_I = ref_mp[:, 1]
# ref_left_I = ref_mp[:, 2]
# ref_right_I = ref_mp[:, 3]
np.random.seed(seed)
approx = scraamp(
T, m, ignore_trivial=True, percentage=percentage, pre_scraamp=False
)
approx.update()
comp_P = approx.P_
# comp_I = approx.I_
# comp_left_I = approx.left_I_
# comp_right_I = approx.right_I_
naive.replace_inf(ref_P)
naive.replace_inf(comp_P)
npt.assert_almost_equal(ref_P, comp_P)
def test_scraamp_plus_plus_A_B_join_full_swap(T_A, T_B):
m = 3
zone = int(np.ceil(m / 4))
ref_mp = naive.aamp(T_B, m, T_B=T_A)
ref_P = ref_mp[:, 0]
ref_I = ref_mp[:, 1]
ref_left_I = ref_mp[:, 2]
ref_right_I = ref_mp[:, 3]
approx = scraamp(
T_B, m, T_B=T_A, ignore_trivial=False, percentage=1.0, pre_scraamp=True, s=zone
)
approx.update()
comp_P = approx.P_
comp_I = approx.I_
comp_left_I = approx.left_I_
comp_right_I = approx.right_I_
naive.replace_inf(ref_P)
naive.replace_inf(comp_P)
npt.assert_almost_equal(ref_P, comp_P)
npt.assert_almost_equal(ref_I, comp_I)
npt.assert_almost_equal(ref_left_I, comp_left_I)
npt.assert_almost_equal(ref_right_I, comp_right_I)
def test_scraamp_self_join_larger_window(T_A, T_B, m, percentages):
if len(T_B) > m:
zone = int(np.ceil(m / 4))
for percentage in percentages:
seed = np.random.randint(100000)
np.random.seed(seed)
ref_mp = naive.scraamp(T_B, m, T_B, percentage, zone, False, None)
ref_P = ref_mp[:, 0]
ref_I = ref_mp[:, 1]
ref_left_I = ref_mp[:, 2]
ref_right_I = ref_mp[:, 3]
np.random.seed(seed)
approx = scraamp(
T_B, m, ignore_trivial=True, percentage=percentage, pre_scraamp=False
)
approx.update()
comp_P = approx.P_
comp_I = approx.I_
comp_left_I = approx.left_I_
comp_right_I = approx.right_I_
naive.replace_inf(ref_P)
naive.replace_inf(comp_P)
npt.assert_almost_equal(ref_P, comp_P)
npt.assert_almost_equal(ref_I, comp_I)
npt.assert_almost_equal(ref_left_I, comp_left_I)
npt.assert_almost_equal(ref_right_I, comp_right_I)
def test_scraamp_A_B_join_swap(T_A, T_B, percentages):
m = 3
for percentage in percentages:
seed = np.random.randint(100000)
np.random.seed(seed)
ref_mp = naive.scraamp(T_B, m, T_A, percentage, None, False, None)
ref_P = ref_mp[:, 0]
# ref_I = ref_mp[:, 1]
ref_left_I = ref_mp[:, 2]
ref_right_I = ref_mp[:, 3]
np.random.seed(seed)
approx = scraamp(
T_B, m, T_A, ignore_trivial=False, percentage=percentage, pre_scraamp=False
)
approx.update()
comp_P = approx.P_
# comp_I = approx.I_
comp_left_I = approx.left_I_
comp_right_I = approx.right_I_
naive.replace_inf(ref_P)
naive.replace_inf(comp_P)
npt.assert_almost_equal(ref_P, comp_P)
npt.assert_almost_equal(ref_P, comp_P)
npt.assert_almost_equal(ref_left_I, comp_left_I)
npt.assert_almost_equal(ref_right_I, comp_right_I)
def test_scraamp_self_join_full_larger_window(T_A, T_B, m):
if len(T_B) > m:
zone = int(np.ceil(m / 4))
ref_mp = naive.aamp(T_B, m, exclusion_zone=zone)
ref_P = ref_mp[:, 0]
ref_I = ref_mp[:, 1]
ref_left_I = ref_mp[:, 2]
ref_right_I = ref_mp[:, 3]
approx = scraamp(T_B,
m,
ignore_trivial=True,
percentage=1.0,
pre_scraamp=False)
approx.update()
comp_P = approx.P_
comp_I = approx.I_
comp_left_I = approx.left_I_
comp_right_I = approx.right_I_
naive.replace_inf(ref_P)
naive.replace_inf(comp_P)
npt.assert_almost_equal(ref_P, comp_P)
npt.assert_almost_equal(ref_I, comp_I)
npt.assert_almost_equal(ref_left_I, comp_left_I)
npt.assert_almost_equal(ref_right_I, comp_right_I)
def test_scrump_plus_plus(T, m):
if T.ndim > 1:
T = T.copy()
T = T[0]
seed = np.random.randint(100000)
np.random.seed(seed)
ref = stumpy.scraamp(T, m, pre_scraamp=True)
np.random.seed(seed)
comp = stumpy.scrump(T, m, pre_scrump=True, normalize=False)
npt.assert_almost_equal(ref.P_, comp.P_)
for i in range(10):
ref.update()
comp.update()
npt.assert_almost_equal(ref.P_, comp.P_)
def test_scraamp_plus_plus_A_B_join(T_A, T_B, percentages):
m = 3
zone = int(np.ceil(m / 4))
for p in [1.0, 2.0, 3.0]:
for s in range(1, zone + 1):
for percentage in percentages:
seed = np.random.randint(100000)
np.random.seed(seed)
ref_P, ref_I = naive.prescraamp(T_A, m, T_B, s=s, p=p)
ref_mp = naive.scraamp(T_A, m, T_B, percentage, None, False, None, p=p)
for i in range(ref_mp.shape[0]):
if ref_P[i] < ref_mp[i, 0]:
ref_mp[i, 0] = ref_P[i]
ref_mp[i, 1] = ref_I[i]
ref_P = ref_mp[:, 0]
ref_I = ref_mp[:, 1]
ref_left_I = ref_mp[:, 2]
ref_right_I = ref_mp[:, 3]
approx = scraamp(
T_A,
m,
T_B,
ignore_trivial=False,
percentage=percentage,
pre_scraamp=True,
s=s,
p=p,
)
approx.update()
comp_P = approx.P_
comp_I = approx.I_
comp_left_I = approx.left_I_
comp_right_I = approx.right_I_
naive.replace_inf(ref_P)
naive.replace_inf(comp_P)
npt.assert_almost_equal(ref_P, comp_P)
npt.assert_almost_equal(ref_I, comp_I)
npt.assert_almost_equal(ref_left_I, comp_left_I)
npt.assert_almost_equal(ref_right_I, comp_right_I)
def test_scraamp_plus_plus_self_join(T_A, T_B, percentages):
m = 3
zone = int(np.ceil(m / 4))
for s in range(1, zone + 1):
for percentage in percentages:
seed = np.random.randint(100000)
np.random.seed(seed)
ref_P, ref_I = naive_prescraamp(T_B,
m,
T_B,
s=s,
exclusion_zone=zone)
ref_mp = naive_scraamp(T_B, m, T_B, percentage, zone, True, s)
for i in range(ref_mp.shape[0]):
if ref_P[i] < ref_mp[i, 0]:
ref_mp[i, 0] = ref_P[i]
ref_mp[i, 1] = ref_I[i]
ref_P = ref_mp[:, 0]
ref_I = ref_mp[:, 1]
# ref_left_I = ref_mp[:, 2]
# ref_right_I = ref_mp[:, 3]
np.random.seed(seed)
approx = scraamp(
T_B,
m,
ignore_trivial=True,
percentage=percentage,
pre_scraamp=True,
s=s,
)
approx.update()
comp_P = approx.P_
comp_I = approx.I_
# comp_left_I = approx.left_I_
# comp_right_I = approx.right_I_
naive.replace_inf(ref_P)
naive.replace_inf(comp_I)
npt.assert_almost_equal(ref_P, comp_P)
npt.assert_almost_equal(ref_I, comp_I)
def test_scraamp_nan_inf_self_join(T_A, T_B, substitute,
substitution_locations, percentages):
m = 3
T_B_sub = T_B.copy()
for substitution_location in substitution_locations:
T_B_sub[:] = T_B[:]
T_B_sub[substitution_location] = substitute
zone = int(np.ceil(m / 4))
for percentage in percentages:
seed = np.random.randint(100000)
np.random.seed(seed)
ref_mp = naive_scraamp(T_B_sub, m, T_B_sub, percentage, zone,
False, None)
ref_P = ref_mp[:, 0]
ref_I = ref_mp[:, 1]
ref_left_I = ref_mp[:, 2]
ref_right_I = ref_mp[:, 3]
np.random.seed(seed)
approx = scraamp(T_B_sub,
m,
percentage=percentage,
pre_scraamp=False)
approx.update()
comp_P = approx.P_
comp_I = approx.I_
comp_left_I = approx.left_I_
comp_right_I = approx.right_I_
naive.replace_inf(ref_P)
naive.replace_inf(comp_P)
npt.assert_almost_equal(ref_P, comp_P)
npt.assert_almost_equal(ref_I, comp_I)
npt.assert_almost_equal(ref_left_I, comp_left_I)
npt.assert_almost_equal(ref_right_I, comp_right_I)
def test_scraamp_A_B_join_full(T_A, T_B):
m = 3
ref_mp = naive.aamp(T_A, m, T_B=T_B)
ref_P = ref_mp[:, 0]
ref_I = ref_mp[:, 1]
ref_left_I = ref_mp[:, 2]
ref_right_I = ref_mp[:, 3]
approx = scraamp(T_A,
m,
T_B,
ignore_trivial=False,
percentage=1.0,
pre_scraamp=False)
approx.update()
comp_P = approx.P_
comp_I = approx.I_
comp_left_I = approx.left_I_
comp_right_I = approx.right_I_
naive.replace_inf(ref_P)
naive.replace_inf(comp_P)
npt.assert_almost_equal(ref_P, comp_P)
npt.assert_almost_equal(ref_I, comp_I)
npt.assert_almost_equal(ref_left_I, comp_left_I)
npt.assert_almost_equal(ref_right_I, comp_right_I)
ref_mp = aamp(T_A, m, T_B=T_B, ignore_trivial=False)
ref_P = ref_mp[:, 0]
ref_I = ref_mp[:, 1]
ref_left_I = ref_mp[:, 2]
ref_right_I = ref_mp[:, 3]
npt.assert_almost_equal(ref_P, comp_P)
npt.assert_almost_equal(ref_I, comp_I)
npt.assert_almost_equal(ref_left_I, comp_left_I)
npt.assert_almost_equal(ref_right_I, comp_right_I)
