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[BUGFIX] Fixes CI + other tests #76

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merged 5 commits into from
Sep 23, 2024
Merged

[BUGFIX] Fixes CI + other tests #76

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f80b5c2
Convert coarse plan to np
pbarbarant Sep 19, 2024
f76fef8
Refactor test_fugw_barycenter to use normalized geometry embedding
pbarbarant Sep 19, 2024
f387a09
Add oneline docstring to barycenter test
pbarbarant Sep 23, 2024
36464eb
Add callback testing to sparse barycenter
pbarbarant Sep 23, 2024
37476c2
Add assertions to test_barycenter
pbarbarant Sep 23, 2024
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11 changes: 7 additions & 4 deletions src/fugw/scripts/coarse_to_fine.py
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Original file line number Diff line number Diff line change
Expand Up @@ -316,10 +316,13 @@ def compute_sparsity_mask(
device = torch.device("cuda", 0)
else:
device = torch.device("cpu")

# Convert coarse plan to numpy
coarse_plan = coarse_mapping.pi.to("cpu").numpy()
if method == "quantile":
# Method 1: keep first percentile
threshold = np.percentile(coarse_mapping.pi, 99.95)
rows, cols = np.nonzero(coarse_mapping.pi > threshold)
threshold = np.percentile(coarse_plan, 99.95)
rows, cols = np.nonzero(coarse_plan > threshold)

elif method == "topk":
# Method 2: keep topk indices per line and per column
Expand All @@ -328,12 +331,12 @@ def compute_sparsity_mask(
rows = np.concatenate(
[
np.arange(source_sample.shape[0]),
np.argmax(coarse_mapping.pi, axis=0),
np.argmax(coarse_plan, axis=0),
]
)
cols = np.concatenate(
[
np.argmax(coarse_mapping.pi, axis=1),
np.argmax(coarse_plan, axis=1),
np.arange(target_sample.shape[0]),
]
)
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11 changes: 7 additions & 4 deletions tests/mappings/test_sparse_barycenter.py
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Original file line number Diff line number Diff line change
Expand Up @@ -19,7 +19,7 @@
"device, callback",
product(devices, callbacks),
)
def test_fugw_barycenter(device, callback):
def test_fugw_sparse_barycenter(device, callback):
np.random.seed(0)
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n_subjects = 4
n_voxels = 100
Expand All @@ -39,18 +39,21 @@ def test_fugw_barycenter(device, callback):
weights_list.append(weights)
features_list.append(features)

fugw_barycenter = FUGWSparseBarycenter()
geometry_embedding_normalized = (
geometry_embedding / geometry_embedding.norm()
)
fugw_sparse_barycenter = FUGWSparseBarycenter()

# Fit the barycenter
(
barycenter_weights,
barycenter_features,
plans,
losses_each_bar_step,
) = fugw_barycenter.fit(
) = fugw_sparse_barycenter.fit(
weights_list,
features_list,
geometry_embedding,
geometry_embedding_normalized,
mesh_sample=mesh_sample,
coarse_mapping_solver_params={"nits_bcd": 2, "nits_uot": 5},
fine_mapping_solver_params={"nits_bcd": 2, "nits_uot": 5},
Expand Down