Add Electrostatics using extensible extras

pyproject.toml

@@ -41,14 +41,12 @@ test = [
     "torch-sim-atomistic[io,symmetry,vesin]",
     "platformdirs>=4.0.0",
     "psutil>=7.0.0",
-    "pymatgen>=2025.6.14",
     "pytest-cov>=6",
     "pytest>=8",
     "spglib>=2.6",
-    "vesin[torch]>=0.5.3",
 ]
 vesin = ["vesin[torch]>=0.5.3"]
-io = ["ase>=3.26", "phonopy>=2.37.0", "pymatgen>=2025.6.14"]
+io = ["ase>=3.26", "phonopy>=2.37.0", "pymatgen>=2026.3.23"]
 symmetry = ["moyopy>=0.7.8"]
 mace = ["mace-torch>=0.3.15"]
 mattersim = ["mattersim>=1.2.2"]

tests/models/test_electrostatics.py

@@ -0,0 +1,115 @@
+"""Tests for the electrostatics ModelInterface wrappers."""
+
+import traceback  # noqa: I001
+
+import pytest
+import torch
+from ase.build import bulk
+
+import torch_sim as ts
+from tests.conftest import DEVICE, DTYPE
+from tests.models.conftest import make_validate_model_outputs_test
+
+try:
+    from torch_sim.models.electrostatics import DSFCoulombModel, EwaldModel, PMEModel
+except (ImportError, OSError, RuntimeError):
+    pytest.skip(
+        f"nvalchemiops not installed: {traceback.format_exc()}",
+        allow_module_level=True,
+    )
+
+
+def _make_charged_state(
+    device: torch.device = DEVICE,
+    dtype: torch.dtype = DTYPE,
+) -> ts.SimState:
+    """Build a small NaCl-like state with alternating +1/-1 site charges."""
+    atoms = bulk("NaCl", crystalstructure="rocksalt", a=5.64, cubic=True)
+    state = ts.io.atoms_to_state(atoms, device, dtype)
+    n = state.n_atoms
+    charges = torch.empty(n, dtype=dtype, device=device)
+    charges[::2] = 1.0
+    charges[1::2] = -1.0
+    state._atom_extras["partial_charges"] = charges  # noqa: SLF001
+    return state
+
+
+@pytest.fixture
+def dsf_model() -> DSFCoulombModel:
+    return DSFCoulombModel(cutoff=8.0, alpha=0.2, device=DEVICE, dtype=DTYPE)
+
+
+@pytest.fixture
+def ewald_model() -> EwaldModel:
+    return EwaldModel(cutoff=8.0, accuracy=1e-6, device=DEVICE, dtype=DTYPE)
+
+
+@pytest.fixture
+def pme_model() -> PMEModel:
+    return PMEModel(cutoff=8.0, accuracy=1e-6, device=DEVICE, dtype=DTYPE)
+
+
+def _add_partial_charges(state: ts.SimState) -> ts.SimState:
+    """Inject alternating +/-0.5 site charges into a state."""
+    n = state.n_atoms
+    charges = torch.zeros(n, dtype=state.positions.dtype, device=state.device)
+    charges[::2] = 0.5
+    charges[1::2] = -0.5
+    state._atom_extras["partial_charges"] = charges  # noqa: SLF001
+    return state
+
+
+test_dsf_model_outputs = make_validate_model_outputs_test(
+    model_fixture_name="dsf_model",
+    device=DEVICE,
+    dtype=DTYPE,
+    state_modifiers=[_add_partial_charges],
+)
+test_ewald_model_outputs = make_validate_model_outputs_test(
+    model_fixture_name="ewald_model",
+    device=DEVICE,
+    dtype=DTYPE,
+    state_modifiers=[_add_partial_charges],
+)
+test_pme_model_outputs = make_validate_model_outputs_test(
+    model_fixture_name="pme_model",
+    device=DEVICE,
+    dtype=DTYPE,
+    state_modifiers=[_add_partial_charges],
+)
+
+
+def test_dsf_nonzero_energy() -> None:
+    """Charged system should produce nonzero electrostatic energy."""
+    model = DSFCoulombModel(cutoff=8.0, alpha=0.2, device=DEVICE, dtype=DTYPE)
+    state = _make_charged_state()
+    out = model(state)
+    assert out["energy"].abs().item() > 0
+
+
+def test_ewald_pme_energy_agreement() -> None:
+    """Ewald and PME should give the same converged Coulomb energy."""
+    state = _make_charged_state()
+    ewald = EwaldModel(cutoff=8.0, accuracy=1e-6, device=DEVICE, dtype=DTYPE)
+    pme = PMEModel(cutoff=8.0, accuracy=1e-6, device=DEVICE, dtype=DTYPE)
+    torch.testing.assert_close(
+        ewald(state)["energy"], pme(state)["energy"], atol=1e-3, rtol=1e-3
+    )
+
+
+def test_sum_model_lj_plus_dsf() -> None:
+    """LJ + DSF should be additive through SumModel."""
+    from torch_sim.models.interface import SumModel
+    from torch_sim.models.lennard_jones import LennardJonesModel
+
+    lj = LennardJonesModel(
+        sigma=2.8, epsilon=0.01, cutoff=7.0, device=DEVICE, dtype=DTYPE
+    )
+    dsf = DSFCoulombModel(cutoff=8.0, alpha=0.2, device=DEVICE, dtype=DTYPE)
+    combined = SumModel(lj, dsf)
+    state = _make_charged_state()
+    lj_out = lj(state)
+    dsf_out = dsf(state)
+    sum_out = combined(state)
+    torch.testing.assert_close(sum_out["energy"], lj_out["energy"] + dsf_out["energy"])
+    torch.testing.assert_close(sum_out["forces"], lj_out["forces"] + dsf_out["forces"])