Merge pull request #79 from chrisjonesBSU/freud3.0

Update to freud 3.0, use `get_molecule_cluster` from cmeutils

environment.yml

@@ -2,19 +2,18 @@ name: grits
 channels:
   - conda-forge
 dependencies:
-  - cmeutils >= 1.2.0
+  - cmeutils >=1.3.0
   - ele
-  - freud = 2.13.2
-  - gsd >= 3.0
+  - freud >=3.0
+  - gsd >=3.0
   - jupyterlab
-  - mbuild
+  - mbuild >=0.17.1
   - ele
-  - freud
   - numpy
   - openbabel
   - pip
   - pre-commit
   - py3Dmol
   - pytest
   - pytest-cov
-  - python = 3.10
+  - python >=3.10

grits/coarsegrain.py

@@ -10,7 +10,7 @@
 import freud
 import gsd.hoomd
 import numpy as np
-from cmeutils.gsd_utils import identify_snapshot_connections
+from cmeutils.gsd_utils import get_molecule_cluster, identify_snapshot_connections
 from ele import element_from_symbol
 from mbuild import Compound, clone
 from mbuild.utils.io import run_from_ipython
@@ -24,7 +24,6 @@
     get_quaternion,
     has_common_member,
     has_number,
-    snap_molecules,
 )
 
 __all__ = ["CG_Compound", "CG_System", "Bead"]
@@ -574,7 +573,7 @@ def _get_compounds(
                 conversion_dict[i].symbol for i in snap.particles.types
             ]
         # Break apart the snapshot into separate molecules
-        molecules = snap_molecules(snap)
+        molecules = get_molecule_cluster(snap=snap)
         mol_inds = []
         for i in range(max(molecules) + 1):
             mol_inds.append(np.where(molecules == i)[0])

grits/utils.py

@@ -82,23 +82,6 @@ def comp_from_snapshot(snapshot, indices, length_scale=1.0, mass_scale=1.0):
     return comp
 
 
-def snap_molecules(snap):
-    """Get the molecule indices based on bonding in a gsd.hoomd.Frame."""
-    system = freud.AABBQuery.from_system(snap)
-    n_query_points = n_points = snap.particles.N
-    query_point_indices = snap.bonds.group[:, 0]
-    point_indices = snap.bonds.group[:, 1]
-    distances = system.box.compute_distances(
-        system.points[query_point_indices], system.points[point_indices]
-    )
-    nlist = freud.NeighborList.from_arrays(
-        n_query_points, n_points, query_point_indices, point_indices, distances
-    )
-    cluster = freud.cluster.Cluster()
-    cluster.compute(system=system, neighbors=nlist)
-    return cluster.cluster_idx
-
-
 def align(compound, particle, towards_compound, around=None):
     """Spin a compound such that particle points at towards_compound.