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Migrate tests/test_gpu_aamp_ostinato.py to npt.assert_allclose #1191

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Merged
seanlaw merged 1 commit into from
Aug 18, 2026
+24 −20
Merged

Migrate tests/test_gpu_aamp_ostinato.py to npt.assert_allclose #1191

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44 changes: 24 additions & 20 deletions tests/test_gpu_aamp_ostinato.py
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Original file line number Diff line number Diff line change
Expand Up @@ -36,11 +36,11 @@ def test_random_gpu_aamp_ostinato(runs):
Ts = [rng.RNG.rand(n) for n in [64, 128, 256]]

ref_radius, ref_Ts_idx, ref_subseq_idx = naive.aamp_ostinato(Ts, m)
comp_radius, comp_Ts_idx, comp_subseq_idx = gpu_aamp_ostinato(Ts, m)
cmp_radius, cmp_Ts_idx, cmp_subseq_idx = gpu_aamp_ostinato(Ts, m)

npt.assert_almost_equal(ref_radius, comp_radius)
npt.assert_almost_equal(ref_Ts_idx, comp_Ts_idx)
npt.assert_almost_equal(ref_subseq_idx, comp_subseq_idx)
npt.assert_allclose(cmp_radius, ref_radius, atol=1.5e-07)
npt.assert_allclose(cmp_Ts_idx, ref_Ts_idx, atol=1.5e-07)
npt.assert_allclose(cmp_subseq_idx, ref_subseq_idx, atol=1.5e-07)


@pytest.mark.filterwarnings("ignore", category=NumbaPerformanceWarning)
Expand All @@ -54,11 +54,11 @@ def test_deterministic_gpu_aamp_ostinato(seed):

for p in [1.0, 2.0, 3.0]:
ref_radius, ref_Ts_idx, ref_subseq_idx = naive.aamp_ostinato(Ts, m, p=p)
comp_radius, comp_Ts_idx, comp_subseq_idx = gpu_aamp_ostinato(Ts, m, p=p)
cmp_radius, cmp_Ts_idx, cmp_subseq_idx = gpu_aamp_ostinato(Ts, m, p=p)

npt.assert_almost_equal(ref_radius, comp_radius)
npt.assert_almost_equal(ref_Ts_idx, comp_Ts_idx)
npt.assert_almost_equal(ref_subseq_idx, comp_subseq_idx)
npt.assert_allclose(cmp_radius, ref_radius, atol=1.5e-07)
npt.assert_allclose(cmp_Ts_idx, ref_Ts_idx, atol=1.5e-07)
npt.assert_allclose(cmp_subseq_idx, ref_subseq_idx, atol=1.5e-07)


@pytest.mark.filterwarnings("ignore", category=NumbaPerformanceWarning)
Expand All @@ -77,8 +77,10 @@ def test_input_not_overwritten():
gpu_aamp_ostinato(Ts_input, m)
for i in range(len(Ts)):
T_ref = Ts[i]
T_comp = Ts_input[i]
npt.assert_almost_equal(T_ref[np.isfinite(T_ref)], T_comp[np.isfinite(T_comp)])
T_cmp = Ts_input[i]
npt.assert_allclose(
T_cmp[np.isfinite(T_cmp)], T_ref[np.isfinite(T_ref)], atol=1.5e-07
)


@pytest.mark.filterwarnings("ignore", category=NumbaPerformanceWarning)
Expand All @@ -88,31 +90,33 @@ def test_extract_several_consensus():
# does not tamper with the original data.
Ts = [rng.RNG.rand(n) for n in [64, 128]]
Ts_ref = [T.copy() for T in Ts]
Ts_comp = [T.copy() for T in Ts]
Ts_cmp = [T.copy() for T in Ts]

m = 20

k = 2 # Get the first `k` consensus motifs
for _ in range(k):
# Find consensus motif and its NN in each time series in Ts_comp
# Remove them from Ts_comp as well as Ts_ref, and assert that the
# Find consensus motif and its NN in each time series in Ts_cmp
# Remove them from Ts_cmp as well as Ts_ref, and assert that the
# two time series are the same
radius, Ts_idx, subseq_idx = gpu_aamp_ostinato(Ts_comp, m)
consensus_motif = Ts_comp[Ts_idx][subseq_idx : subseq_idx + m].copy()
for i in range(len(Ts_comp)):
radius, Ts_idx, subseq_idx = gpu_aamp_ostinato(Ts_cmp, m)
consensus_motif = Ts_cmp[Ts_idx][subseq_idx : subseq_idx + m].copy()
for i in range(len(Ts_cmp)):
if i == Ts_idx:
query_idx = subseq_idx
else:
query_idx = None

idx = np.argmin(
core.mass(
consensus_motif, Ts_comp[i], normalize=False, query_idx=query_idx
consensus_motif, Ts_cmp[i], normalize=False, query_idx=query_idx
)
)
Ts_comp[i][idx : idx + m] = np.nan
Ts_cmp[i][idx : idx + m] = np.nan
Ts_ref[i][idx : idx + m] = np.nan

npt.assert_almost_equal(
Ts_ref[i][np.isfinite(Ts_ref[i])], Ts_comp[i][np.isfinite(Ts_comp[i])]
npt.assert_allclose(
Ts_cmp[i][np.isfinite(Ts_cmp[i])],
Ts_ref[i][np.isfinite(Ts_ref[i])],
atol=1.5e-07,
)
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