Added neighborlist from MatScipy package

setup.py

@@ -35,6 +35,7 @@ def read(fname):
         "rich",
         "fasteners",
         "dirsync",
+        "matscipy @ git+https://github.com/libAtoms/matscipy.git",
     ],
     include_package_data=True,
     extras_require={"test": ["pytest", "pytest-datadir", "pytest-benchmark"]},

src/schnetpack/configs/experiment/md17.yaml

@@ -22,7 +22,7 @@ data:
     - _target_: schnetpack.transform.RemoveOffsets
       property: energy
       remove_mean: True
-    - _target_: schnetpack.transform.ASENeighborList
+    - _target_: schnetpack.transform.MatScipyNeighborList
       cutoff: ${globals.cutoff}
     - _target_: schnetpack.transform.CastTo32
 

src/schnetpack/configs/experiment/qm9.yaml

@@ -18,7 +18,7 @@ data:
       property: ${globals.property}
       remove_atomrefs: True
       remove_mean: True
-    - _target_: schnetpack.transform.ASENeighborList
+    - _target_: schnetpack.transform.MatScipyNeighborList
       cutoff: ${globals.cutoff}
     - _target_: schnetpack.transform.CastTo32
 

src/schnetpack/configs/predict.yaml

@@ -15,7 +15,7 @@ data:
   datapath: ${datapath}
   transforms:
     - _target_: schnetpack.transform.SubtractCenterOfMass
-    - _target_: schnetpack.transform.ASENeighborList
+    - _target_: schnetpack.transform.MatScipyNeighborList
       cutoff: ${cutoff}
     - _target_: schnetpack.transform.CastTo32
 

src/schnetpack/md/md_configs/calculator/lj.yaml

@@ -9,4 +9,4 @@ stress_key: stress
 healing_length: 4.0 #0.3405
 
 defaults:
-  - neighbor_list: ase
+  - neighbor_list: matscipy

src/schnetpack/md/md_configs/calculator/neighbor_list/matscipy.yaml

@@ -0,0 +1,6 @@
+_target_: schnetpack.md.neighborlist_md.NeighborListMD
+cutoff: ???
+cutoff_shell: 2.0
+requires_triples: false
+base_nbl: schnetpack.transform.MatScipyNeighborList
+collate_fn: schnetpack.data.loader._atoms_collate_fn

src/schnetpack/md/md_configs/calculator/spk.yaml

@@ -11,4 +11,4 @@ stress_key: null
 script_model: false
 
 defaults:
-  - neighbor_list: ase
+  - neighbor_list: matscipy

src/schnetpack/md/md_configs/calculator/spk_ensemble.yaml

@@ -12,4 +12,4 @@ stress_key: null
 script_model: false
 
 defaults:
-  - neighbor_list: ase
+  - neighbor_list: matscipy

src/schnetpack/transform/neighborlist.py

@@ -2,15 +2,16 @@
 import torch
 import shutil
 from ase import Atoms
-from ase.neighborlist import neighbor_list
+from ase.neighborlist import neighbor_list as ase_neighbor_list
+from matscipy.neighbours import neighbour_list as msp_neighbor_list
 from .base import Transform
 from dirsync import sync
 import numpy as np
 from typing import Optional, Dict, List, Type, Any, Union
 
-
 __all__ = [
     "ASENeighborList",
+    "MatScipyNeighborList",
     "TorchNeighborList",
     "CountNeighbors",
     "CollectAtomTriples",
@@ -55,7 +56,6 @@ def forward(
         self,
         inputs: Dict[str, torch.Tensor],
     ) -> Dict[str, torch.Tensor]:
-
         inputs = self.neighbor_list(inputs)
         for postprocess in self.nbh_postprocessing:
             inputs = postprocess(inputs)
@@ -229,14 +229,43 @@ class ASENeighborList(NeighborListTransform):
     def _build_neighbor_list(self, Z, positions, cell, pbc, cutoff):
         at = Atoms(numbers=Z, positions=positions, cell=cell, pbc=pbc)
 
-        idx_i, idx_j, S = neighbor_list("ijS", at, cutoff, self_interaction=False)
+        idx_i, idx_j, S = ase_neighbor_list("ijS", at, cutoff, self_interaction=False)
         idx_i = torch.from_numpy(idx_i)
         idx_j = torch.from_numpy(idx_j)
         S = torch.from_numpy(S).to(dtype=positions.dtype)
         offset = torch.mm(S, cell)
         return idx_i, idx_j, offset
 
 
+class MatScipyNeighborList(NeighborListTransform):
+    """
+    Neighborlist using the efficient implementation of the Matscipy package
+    (https://github.com/libAtoms/matscipy).
+    """
+
+    def _build_neighbor_list(
+        self, Z, positions, cell, pbc, cutoff, eps=1e-6, buffer=1.0
+    ):
+        at = Atoms(numbers=Z, positions=positions, cell=cell, pbc=pbc)
+
+        # Add cell if none is present (volume = 0)
+        if at.cell.volume < eps:
+            # max values - min values along xyz augmented by small buffer for stability
+            new_cell = np.ptp(at.positions, axis=0) + buffer
+            # Set cell and center
+            at.set_cell(new_cell, scale_atoms=False)
+            at.center()
+
+        # Compute neighborhood
+        idx_i, idx_j, S = msp_neighbor_list("ijS", at, cutoff)
+        idx_i = torch.from_numpy(idx_i).long()
+        idx_j = torch.from_numpy(idx_j).long()
+        S = torch.from_numpy(S).to(dtype=positions.dtype)
+        offset = torch.mm(S, cell)
+
+        return idx_i, idx_j, offset
+
+
 class SkinNeighborList(Transform):
     """
     Neighbor list provider utilizing a cutoff skin for computational efficiency. Wrapper around neighbor list classes