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center scale for spatial normalization callback #697

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ed00ac4
center scale
giovp May 22, 2024
fe37d7b
update
giovp Jun 17, 2024
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giovp Jun 17, 2024
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giovp Jun 17, 2024
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Merge branch 'main' into giovp/spatial_callback
giovp Jun 17, 2024
778b534
Merge branch 'main' into giovp/spatial_callback
giovp Jul 9, 2024
7b566fc
Merge branch 'main' into giovp/spatial_callback
giovp Jul 23, 2024
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2 changes: 1 addition & 1 deletion src/moscot/base/problems/problem.py
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Original file line number Diff line number Diff line change
Expand Up @@ -635,7 +635,7 @@ def _spatial_norm_callback(
spatial = TaggedArray._extract_data(adata, attr=attr, key=key)

logger.info(f"Normalizing spatial coordinates of `{term}`.")
spatial = (spatial - spatial.mean()) / spatial.std()
spatial = (spatial - spatial.mean(axis=0)) / spatial.std()
return TaggedArray(spatial, tag=Tag.POINT_CLOUD)

@staticmethod
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7 changes: 2 additions & 5 deletions tests/problems/space/test_alignment_problem.py
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Expand Up @@ -51,8 +51,7 @@ def test_prepare_sequential(
ap = ap.prepare(batch_key="batch", joint_attr=joint_attr, normalize_spatial=normalize_spatial)
assert len(ap) == 2
if normalize_spatial:
np.testing.assert_allclose(ap[("1", "2")].x.data_src.std(), ap[("0", "1")].x.data_src.std(), atol=1e-15)
np.testing.assert_allclose(ap[("1", "2")].x.data_src.std(), 1.0, atol=1e-15)
np.testing.assert_allclose(ap[("1", "2")].x.data_src.std(), ap[("0", "1")].y.data_src.std(), atol=1e-15)
np.testing.assert_allclose(ap[("1", "2")].x.data_src.mean(), 0, atol=1e-15)
np.testing.assert_allclose(ap[("0", "1")].x.data_src.mean(), 0, atol=1e-15)

Expand All @@ -75,7 +74,6 @@ def test_prepare_star(self, adata_space_rotate: AnnData, reference: str):
assert ref == reference
assert isinstance(ap[prob_key], ap._base_problem_type)

@pytest.mark.skip(reason="See https://github.com/theislab/moscot/issues/678")
@pytest.mark.parametrize(
("epsilon", "alpha", "rank", "initializer"),
[(1, 0.9, -1, None), (1, 0.5, 10, "random"), (1, 0.5, 10, "rank2"), (0.1, 0.1, -1, None)],
Expand All @@ -102,8 +100,7 @@ def test_solve_balanced(
)
for prob_key in ap:
assert ap[prob_key].solution.rank == rank
if initializer != "random": # TODO: is this valid?
assert ap[prob_key].solution.converged
assert ap[prob_key].solution.converged

# TODO(michalk8): use np.testing
assert np.allclose(*(sol.cost for sol in ap.solutions.values()))
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1 change: 0 additions & 1 deletion tests/problems/space/test_mapping_problem.py
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Expand Up @@ -96,7 +96,6 @@ def test_prepare_varnames(self, adata_mapping: AnnData, var_names: Optional[List
assert prob.x.data_src.shape == (n_obs, x_n_var)
assert prob.y.data_src.shape == (n_obs, y_n_var)

@pytest.mark.skip(reason="See https://github.com/theislab/moscot/issues/678")
@pytest.mark.parametrize(
("epsilon", "alpha", "rank", "initializer"),
[(1e-2, 0.9, -1, None), (2, 0.5, 10, "random"), (2, 0.5, 10, "rank2"), (2, 0.1, -1, None)],
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5 changes: 2 additions & 3 deletions tests/problems/spatio_temporal/test_spatio_temporal_problem.py
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Expand Up @@ -60,7 +60,6 @@ def test_solve_balanced(self, adata_spatio_temporal: AnnData):
assert isinstance(subsol, BaseSolverOutput)
assert key in expected_keys

@pytest.mark.skip(reason="unbalanced does not work yet")
def test_solve_unbalanced(self, adata_spatio_temporal: AnnData):
taus = [9e-1, 1e-2]
problem1 = SpatioTemporalProblem(adata=adata_spatio_temporal)
Expand All @@ -76,8 +75,8 @@ def test_solve_unbalanced(self, adata_spatio_temporal: AnnData):
assert problem2[0, 1].a is not None
assert problem2[0, 1].b is not None

problem1 = problem1.solve(epsilon=1, tau_a=taus[0], tau_b=taus[0], max_iterations=10000)
problem2 = problem2.solve(epsilon=1, tau_a=taus[1], tau_b=taus[1], max_iterations=10000)
problem1 = problem1.solve(epsilon=1, tau_a=taus[0], tau_b=taus[0])
problem2 = problem2.solve(epsilon=1, tau_a=taus[1], tau_b=taus[1])

assert problem1[0, 1].solution.a is not None
assert problem1[0, 1].solution.b is not None
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4 changes: 2 additions & 2 deletions tests/problems/time/test_temporal_problem.py
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Expand Up @@ -78,8 +78,8 @@ def test_solve_unbalanced(self, adata_time: AnnData):
assert problem2[0, 1].a is not None
assert problem2[0, 1].b is not None

problem1 = problem1.solve(epsilon=1, tau_a=taus[0], tau_b=taus[0], max_iterations=10000)
problem2 = problem2.solve(epsilon=1, tau_a=taus[1], tau_b=taus[1], max_iterations=10000)
problem1 = problem1.solve(epsilon=1, tau_a=taus[0], tau_b=taus[0])
problem2 = problem2.solve(epsilon=1, tau_a=taus[1], tau_b=taus[1])

assert problem1[0, 1].solution.a is not None
assert problem1[0, 1].solution.b is not None
Expand Down