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convert cell_to_cellpar from ase's numpy implementation to pytorch #306

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convert cell_to_cellpar from ase's numpy implementation to pytorch #306

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560c617
convert to pytorch
wwymak Oct 25, 2025
9f1c2de
changing function back to the same row convention as ase, plus use a …
wwymak Nov 4, 2025
6bd4a36
Merge branch 'main' into chore/304-cellpar-reimplementation
wwymak Nov 4, 2025
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17 changes: 17 additions & 0 deletions tests/models/test_orb.py
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Original file line number Diff line number Diff line change
@@ -1,13 +1,17 @@
import traceback

import numpy as np
import pytest
from ase.geometry.cell import cell_to_cellpar as ase_c2p

from tests.conftest import DEVICE
from tests.models.conftest import (
consistency_test_simstate_fixtures,
make_model_calculator_consistency_test,
make_validate_model_outputs_test,
)
from torch_sim import SimState
from torch_sim.models.orb import cell_to_cellpar


try:
Expand Down Expand Up @@ -74,3 +78,16 @@ def orbv3_direct_20_omat_calculator() -> ORBCalculator:
test_validate_direct_model_outputs = make_validate_model_outputs_test(
model_fixture_name="orbv3_direct_20_omat_model",
)


def test_cell_to_cellpar(ti_sim_state: SimState) -> None:
assert np.allclose(
ase_c2p(ti_sim_state.row_vector_cell.squeeze()),
cell_to_cellpar(ti_sim_state.row_vector_cell.squeeze(0)).cpu().numpy(),
)
assert np.allclose(
ase_c2p(ti_sim_state.row_vector_cell.squeeze(), radians=True),
cell_to_cellpar(ti_sim_state.row_vector_cell.squeeze(0), radians=True)
.cpu()
.numpy(),
)
38 changes: 34 additions & 4 deletions torch_sim/models/orb.py
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Original file line number Diff line number Diff line change
Expand Up @@ -29,7 +29,6 @@


try:
from ase.geometry import cell_to_cellpar
from orb_models.forcefield import featurization_utilities as feat_util
from orb_models.forcefield.atomic_system import SystemConfig
from orb_models.forcefield.base import AtomGraphs, _map_concat
Expand Down Expand Up @@ -59,6 +58,39 @@ def __init__(self, err: ImportError = exc, *_args: Any, **_kwargs: Any) -> None:
from torch_sim.typing import StateDict


def cell_to_cellpar(
cell: torch.Tensor,
radians: bool = False, # noqa: FBT001, FBT002
) -> torch.Tensor:
"""Returns the cell parameters [a, b, c, alpha, beta, gamma].
torch version of ase's cell_to_cellpar.

Args:
cell: lattice vector in row vector convention, same as ase
radians: If True, return angles in radians. Otherwise, return degrees (default).

Returns:
Tensor with [a, b, c, alpha, beta, gamma].
"""
lengths = torch.linalg.norm(cell, dim=1).squeeze()
angles = []
for i in range(3):
j = i - 1
k = i - 2
ll = lengths[j] * lengths[k]
if ll.item() > 1e-16:
cell_j = cell[j].squeeze()
cell_k = cell[k].squeeze()
x = torch.dot(cell_j, cell_k) / ll
angle = 180.0 / torch.pi * torch.arccos(x)
else:
angle = 90.0
angles.append(angle)
if radians:
angles = [angle * torch.pi / 180 for angle in angles]
return torch.concat((torch.tensor(lengths), torch.tensor(angles)))


def state_to_atom_graphs( # noqa: PLR0915
state: ts.SimState,
*,
Expand Down Expand Up @@ -181,9 +213,7 @@ def state_to_atom_graphs( # noqa: PLR0915
num_edges.append(len(edges[0]))

# Calculate lattice parameters
lattice_per_system = torch.from_numpy(
cell_to_cellpar(cell_per_system.squeeze(0).cpu().numpy())
)
lattice_per_system = cell_to_cellpar(cell_per_system.squeeze(0))
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@thomasloux thomasloux Oct 27, 2025

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Ok I didn't see that the cell was extracted explicitly with the convention row_vector. When I say that the convention is not the same is that if A=Ase.atoms.cell[:] and B=SimState.cell, then A=B.T (transpose form). So in here, either you assume that the input is row and then you should have the same behaviour as ASE.cell_to_cellpar or you change that and then you have to change the input.
Given the current state of code, I suggest to use the same cell_to_cellpar convention as ASE, which is to assume that the input cell is a row_vector. Then modify the test accordingly

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@wwymak wwymak Nov 4, 2025

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Hi, I have changed the function to use the row convention and also updated the test.


# Create features dictionaries
node_feats = {
Expand Down