See the labels in OVITO or VMD¶
Counts tell you how much ice there is. Colouring each molecule by what the engine decided shows where it is. Three routes, from no Python at all to a live OVITO pipeline.
CLI: a dump with one extra column¶
seams cages traj.lammpstrj --frame 1 --last 200 --per-atom cages.lammpstrj
seams fingerprint traj.lammpstrj --hops 3 --library ic.keys --per-atom labels.lammpstrj
seams ions brine.lammpstrj --ion-types 3,4 --per-atom ions.lammpstrj
--per-atom FILE appends one LAMMPS dump frame per analysed frame with the columns id type x y z and one more: cage (0 water, 1 hexagonal cage, 2 double-diamond cage, 3 both) for cages, class (rank of the topology class by population, 1 the largest) or label (index into the library labels the summary line prints) for fingerprint, state (0 liquid water, 1 ice water, 2 liquid ion, 3 front ion, 4 ice ion) for ions. OVITO reads the extra column as a particle property; in VMD load it with the LAMMPS dump plugin and colour by user.
OVITO: a modifier function¶
from functools import partial
from ovito.io import import_file
from pydseams.adapters import ice_states
pipeline = import_file("traj.lammpstrj")
pipeline.modifiers.append(partial(ice_states, oxygen_type=1, cutoff=3.5))
data = pipeline.compute(10)
print(data.particles["Ice state"][...])
ice_states adds the Ice state particle property (0 water, 1 cubic, 2 hexagonal, 3 mixed, -1 outside the oxygen type) from the seeded cage assignment. Add a Color coding modifier on it and step through the trajectory.
MDAnalysis: an analysis class¶
import MDAnalysis as mda
from pydseams.adapters import IceStates
u = mda.Universe("brine.gro", "brine.xtc")
an = IceStates(u.select_atoms("name OW"), ions=u.select_atoms("name NA CL")).run()
an.results.states # frames x oxygens
an.results.ion_states # frames x ions
pip install pydseamslib[mdanalysis] pulls MDAnalysis. Boxes must be orthorhombic.