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Fix non-periodic cell construction in get_neighborhood #1395

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Fix non-periodic cell construction in get_neighborhood #1395

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13 changes: 6 additions & 7 deletions mace/data/neighborhood.py
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Original file line number Diff line number Diff line change
Expand Up @@ -24,16 +24,15 @@ def get_neighborhood(
pbc_y = pbc[1]
pbc_z = pbc[2]
identity = np.identity(3, dtype=float)
max_positions = np.max(np.absolute(positions)) + 1
# Extend cell in non-periodic directions
# For models with more than 5 layers, the multiplicative constant needs to be increased.
# temp_cell = np.copy(cell)
max_positions = np.max(positions, axis=0) - np.min(positions, axis=0)
padding = 1 # 1 angstrom padding

Copilot AI Mar 3, 2026

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padding is a hard-coded magic number and is currently an int while the rest of the computation is floating-point. Consider using 1.0 and/or factoring this into a named constant (or parameter) so it’s easier to tune/document and consistent with the cell’s float dtype.

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Comment on lines +27 to +28

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max_positions now stores the per-axis position span (max-min), not a maximum. Renaming it (e.g., position_span / extent) would avoid confusion and make the subsequent indexing (max_positions[0], etc.) clearer.

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Comment on lines +28 to +29

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padding = 1 is a new hard-coded magic number. Consider making this a module-level constant or a function parameter (and use 1.0 to keep everything explicitly float in Angstrom units) so callers/tests can tune it if needed.

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if not pbc_x:
cell[0, :] = max_positions * 5 * cutoff * identity[0, :]
cell[0, :] = (max_positions[0] + cutoff + padding) * identity[0, :]
if not pbc_y:
cell[1, :] = max_positions * 5 * cutoff * identity[1, :]
cell[1, :] = (max_positions[1] + cutoff + padding) * identity[1, :]
if not pbc_z:
cell[2, :] = max_positions * 5 * cutoff * identity[2, :]
cell[2, :] = (max_positions[2] + cutoff + padding) * identity[2, :]
Comment on lines +27 to +35

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The PR fixes a concrete failure mode for pbc=False, but there’s no regression test covering the “large absolute coordinates” example from the PR description. Adding a focused test that constructs a translated cluster (e.g., +5000 Å shift) and asserts get_neighborhood succeeds (and returns a reasonable non-pathological cell / neighbor list) would prevent reintroducing the oversized-cell behavior.

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sender, receiver, unit_shifts = neighbour_list(
quantities="ijS",
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