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use numerical stability parameter for calculatiung d_ij #739

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40b3387
use numerical stability parameter for calculatiung d_ij
stefaanhessmann Jun 24, 2025
b114c2b
black
stefaanhessmann Jun 24, 2025
a656869
added: argument return_vector_representation in PaiNN
stefaanhessmann Jun 24, 2025
74940f3
fix bug
stefaanhessmann Jun 24, 2025
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85 changes: 47 additions & 38 deletions examples/howtos/howto_ensemble_calculation.ipynb
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -42,7 +42,11 @@
"from ase.md.velocitydistribution import MaxwellBoltzmannDistribution\n",
"from ase.md.langevin import Langevin\n",
"\n",
"from schnetpack.interfaces.ase_interface import SpkEnsembleCalculator, AbsoluteUncertainty, RelativeUncertainty\n",
"from schnetpack.interfaces.ase_interface import (\n",
" SpkEnsembleCalculator,\n",
" AbsoluteUncertainty,\n",
" RelativeUncertainty,\n",
")\n",
"import schnetpack.transform as trn\n",
"from schnetpack.datasets import MD17\n",
"import torch\n",
Expand Down Expand Up @@ -78,11 +82,13 @@
},
"outputs": [],
"source": [
"model_path_list = ['../trained_models/rmd17_ethanol/painn_1/best_model',\n",
" '../trained_models/rmd17_ethanol/painn_2/best_model',\n",
" '../trained_models/rmd17_ethanol/painn_3/best_model',\n",
" '../trained_models/rmd17_ethanol/painn_4/best_model',\n",
" '../trained_models/rmd17_ethanol/painn_5/best_model']"
"model_path_list = [\n",
" \"../trained_models/rmd17_ethanol/painn_1/best_model\",\n",
" \"../trained_models/rmd17_ethanol/painn_2/best_model\",\n",
" \"../trained_models/rmd17_ethanol/painn_3/best_model\",\n",
" \"../trained_models/rmd17_ethanol/painn_4/best_model\",\n",
" \"../trained_models/rmd17_ethanol/painn_5/best_model\",\n",
"]"
]
},
{
Expand Down Expand Up @@ -113,7 +119,7 @@
},
"outputs": [],
"source": [
"uncertainty_abs = AbsoluteUncertainty(energy_weight=0.5,force_weight=1.0)\n",
"uncertainty_abs = AbsoluteUncertainty(energy_weight=0.5, force_weight=1.0)\n",
"uncertainty_rel = RelativeUncertainty(energy_weight=1.0, force_weight=2.0)\n",
"\n",
"uncertainty = [uncertainty_abs, uncertainty_rel]\n",
Expand All @@ -125,7 +131,8 @@
" force_key=MD17.forces,\n",
" energy_unit=\"kcal/mol\",\n",
" position_unit=\"Ang\",\n",
" uncertainty_fn=uncertainty)"
" uncertainty_fn=uncertainty,\n",
")"
]
},
{
Expand All @@ -146,8 +153,8 @@
},
"outputs": [],
"source": [
"#load data into atoms object\n",
"atoms = read('../../tests/testdata/md_ethanol.xyz', index=0)\n",
"# load data into atoms object\n",
"atoms = read(\"../../tests/testdata/md_ethanol.xyz\", index=0)\n",
"# specify atoms calculator\n",
"atoms.calc = ensemble_calculator"
]
Expand Down Expand Up @@ -290,22 +297,22 @@
"fig, ax1 = plt.subplots(figsize=(8, 6))\n",
"\n",
"# Plot absolute uncertainty on left y-axis\n",
"ax1.plot(steps, abs_vals, label=\"Absolute Uncertainty\", marker='o', color='tab:blue')\n",
"ax1.plot(steps, abs_vals, label=\"Absolute Uncertainty\", marker=\"o\", color=\"tab:blue\")\n",
"ax1.set_xlabel(\"Optimization Step\")\n",
"ax1.set_ylabel(\"Absolute Uncertainty\", color='tab:blue')\n",
"ax1.tick_params(axis='y', labelcolor='tab:blue')\n",
"ax1.set_ylabel(\"Absolute Uncertainty\", color=\"tab:blue\")\n",
"ax1.tick_params(axis=\"y\", labelcolor=\"tab:blue\")\n",
"ax1.grid(True)\n",
"\n",
"# Create second y-axis for relative uncertainty\n",
"ax2 = ax1.twinx()\n",
"ax2.plot(steps, rel_vals, label=\"Relative Uncertainty\", marker='x', color='tab:red')\n",
"ax2.set_ylabel(\"Relative Uncertainty\", color='tab:red')\n",
"ax2.tick_params(axis='y', labelcolor='tab:red')\n",
"ax2.plot(steps, rel_vals, label=\"Relative Uncertainty\", marker=\"x\", color=\"tab:red\")\n",
"ax2.set_ylabel(\"Relative Uncertainty\", color=\"tab:red\")\n",
"ax2.tick_params(axis=\"y\", labelcolor=\"tab:red\")\n",
"\n",
"# Title and layout\n",
"plt.title(\"Uncertainty during Optimization\")\n",
"fig.tight_layout()\n",
"plt.show()\n"
"plt.show()"
]
},
{
Expand Down Expand Up @@ -344,7 +351,7 @@
},
"outputs": [],
"source": [
"uncertainty_abs = AbsoluteUncertainty(energy_weight=0.5,force_weight=1.0)\n",
"uncertainty_abs = AbsoluteUncertainty(energy_weight=0.5, force_weight=1.0)\n",
"\n",
"abs_ensemble_calculator = SpkEnsembleCalculator(\n",
" models=model_path_list,\n",
Expand All @@ -353,7 +360,8 @@
" force_key=MD17.forces,\n",
" energy_unit=\"kcal/mol\",\n",
" position_unit=\"Ang\",\n",
" uncertainty_fn=uncertainty_abs)"
" uncertainty_fn=uncertainty_abs,\n",
")"
]
},
{
Expand All @@ -367,13 +375,13 @@
},
"outputs": [],
"source": [
"target_temperatures = [_ for _ in range(50, 800, 100)] \n",
"n_steps = 1000 \n",
"sampling_interval = 10 \n",
"step_size = 0.5 \n",
"target_temperatures = [_ for _ in range(50, 800, 100)]\n",
"n_steps = 1000\n",
"sampling_interval = 10\n",
"step_size = 0.5\n",
"\n",
"# setting up initial atoms\n",
"atoms = read('../../tests/testdata/md_ethanol.xyz', index=0)\n",
"atoms = read(\"../../tests/testdata/md_ethanol.xyz\", index=0)\n",
"atoms.calc = abs_ensemble_calculator\n",
"\n",
"MaxwellBoltzmannDistribution(atoms, temperature_K=target_temperatures[0])\n",
Expand All @@ -385,19 +393,19 @@
"for target_temperature in target_temperatures:\n",
" print(f\"Temp: {target_temperature:.2f} K\")\n",
" for step in tqdm(range(n_steps // sampling_interval)):\n",
" \n",
"\n",
" dyn = Langevin(\n",
" atoms, \n",
" timestep=step_size * units.fs, \n",
" atoms,\n",
" timestep=step_size * units.fs,\n",
" temperature_K=target_temperature,\n",
" friction=0.01 / units.fs\n",
" friction=0.01 / units.fs,\n",
" )\n",
" \n",
"\n",
" dyn.run(sampling_interval)\n",
" \n",
"\n",
" temp.append(atoms.get_temperature())\n",
" uncertainties.append(abs_ensemble_calculator.get_uncertainty(atoms))\n",
" \n",
"\n",
" ats_traj.append(atoms.copy())"
]
},
Expand All @@ -409,22 +417,22 @@
"source": [
"fig, ax1 = plt.subplots(figsize=(8, 6))\n",
"\n",
"ax1.plot(uncertainties, marker='o', color='blue', label='Uncertainty')\n",
"ax1.plot(uncertainties, marker=\"o\", color=\"blue\", label=\"Uncertainty\")\n",
"ax1.set_xlabel(\"MD Step\")\n",
"ax1.set_ylabel(\"Uncertainty\", color='blue')\n",
"ax1.tick_params(axis='y', labelcolor='blue')\n",
"ax1.set_ylabel(\"Uncertainty\", color=\"blue\")\n",
"ax1.tick_params(axis=\"y\", labelcolor=\"blue\")\n",
"\n",
"ax2 = ax1.twinx()\n",
"ax2.plot(temp, marker='x', color='red', label='Temperature')\n",
"ax2.set_ylabel(\"Temperature (K)\", color='red')\n",
"ax2.tick_params(axis='y', labelcolor='red')\n",
"ax2.plot(temp, marker=\"x\", color=\"red\", label=\"Temperature\")\n",
"ax2.set_ylabel(\"Temperature (K)\", color=\"red\")\n",
"ax2.tick_params(axis=\"y\", labelcolor=\"red\")\n",
"\n",
"plt.title(\"Molecular Dynamics: Uncertainty and Temperature Profile\")\n",
"ax1.grid(True)\n",
"\n",
"lines_1, labels_1 = ax1.get_legend_handles_labels()\n",
"lines_2, labels_2 = ax2.get_legend_handles_labels()\n",
"ax1.legend(lines_1 + lines_2, labels_1 + labels_2, loc='upper right')\n",
"ax1.legend(lines_1 + lines_2, labels_1 + labels_2, loc=\"upper right\")\n",
"\n",
"plt.tight_layout()\n",
"plt.show()"
Expand All @@ -444,6 +452,7 @@
"outputs": [],
"source": [
"from ase.visualize import view\n",
"\n",
"view(ats_traj)"
]
}
Expand Down
4 changes: 1 addition & 3 deletions examples/tutorials/tutorial_02_qm9.ipynb
View file
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Original file line number Diff line number Diff line change
Expand Up @@ -377,9 +377,7 @@
"from ase import Atoms\n",
"from schnetpack.utils.compatibility import load_model\n",
"\n",
"best_model = load_model(\n",
" os.path.join(qm9tut, \"best_inference_model\"), device=\"cpu\"\n",
")"
"best_model = load_model(os.path.join(qm9tut, \"best_inference_model\"), device=\"cpu\")"
]
},
{
Expand Down
10 changes: 7 additions & 3 deletions src/schnetpack/representation/painn.py
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Original file line number Diff line number Diff line change
Expand Up @@ -136,6 +136,7 @@ def __init__(
cutoff_fn: Optional[Callable] = None,
activation: Optional[Callable] = F.silu,
shared_interactions: bool = False,
return_vector_representation: bool = False,
shared_filters: bool = False,
epsilon: float = 1e-8,
nuclear_embedding: Optional[nn.Module] = None,
Expand Down Expand Up @@ -165,6 +166,8 @@ def __init__(
self.cutoff_fn = cutoff_fn
self.cutoff = cutoff_fn.cutoff
self.radial_basis = radial_basis
self.return_vector_representation = return_vector_representation
self.epsilon = epsilon

# initialize embeddings
if nuclear_embedding is None:
Expand Down Expand Up @@ -198,7 +201,7 @@ def __init__(
)
self.mixing = snn.replicate_module(
lambda: PaiNNMixing(
n_atom_basis=self.n_atom_basis, activation=activation, epsilon=epsilon
n_atom_basis=self.n_atom_basis, activation=activation, epsilon=self.epsilon
),
self.n_interactions,
shared_interactions,
Expand All @@ -224,7 +227,7 @@ def forward(self, inputs: Dict[str, torch.Tensor]):
n_atoms = atomic_numbers.shape[0]

# compute atom and pair features
d_ij = torch.norm(r_ij, dim=1, keepdim=True)
d_ij = torch.sqrt(torch.sum(r_ij**2, dim=-1, keepdim=True) + self.epsilon)
dir_ij = r_ij / d_ij
phi_ij = self.radial_basis(d_ij)
fcut = self.cutoff_fn(d_ij)
Expand All @@ -251,6 +254,7 @@ def forward(self, inputs: Dict[str, torch.Tensor]):

# collect results
inputs["scalar_representation"] = q
inputs["vector_representation"] = mu
if self.return_vector_representation:
inputs["vector_representation"] = mu

return inputs
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