def wrap_cc(cell1, pts):
"""
Function finds the indices of atoms making tetrahedrons
Parameters
-------------
cell1 :
The simulation cell ( a 3*4 numpy array where the first 3 columns are the
cell vectors and the last column is the box origin)
pts :
Position of atoms in initial cell, the atoms within an rCut of the initial cell.
Returns
------------
pts1 :
Position of atoms in initial cell, the atoms within an rCut of the initial cell,
and the Voronoi coordinates as the new set of atoms.
"""
data = ovd.DataCollection()
data.objects.append(cell1)
particles = ovd.Particles()
particles.create_property('Position', data=pts)
data.objects.append(particles)
# Create a new Pipeline with a StaticSource as data source:
pipeline = Pipeline(source=StaticSource(data=data))
pipeline.modifiers.append(ovm.WrapPeriodicImagesModifier())
data1 = pipeline.compute()
pts1 = np.array(data1.particle_properties['Position'][...])
return pts1
def ovito_dxa(atoms, replicate_z=3):
from ovito.io.ase import ase_to_ovito
from ovito.modifiers import ReplicateModifier, DislocationAnalysisModifier
from ovito.pipeline import StaticSource, Pipeline
data = ase_to_ovito(atoms)
pipeline = Pipeline(source=StaticSource(data=data))
pipeline.modifiers.append(ReplicateModifier(num_z=replicate_z))
dxa = DislocationAnalysisModifier(
input_crystal_structure=DislocationAnalysisModifier.Lattice.BCC)
pipeline.modifiers.append(dxa)
data = pipeline.compute()
return (np.array(data.dislocations.segments[0].true_burgers_vector),
data.dislocations.segments[0].length / replicate_z,
data.dislocations.segments[0])
def write_lammps_data(ftxt, atoms, **kwargs):
# FAIL: use ase.io.write(ftxt, atoms, format='lammps-data', atom_style='charge')
from ovito.io import export_file
from ovito.pipeline import StaticSource, Pipeline
from ovito.io.ase import ase_to_ovito
atoms.set_initial_charges(atoms.get_initial_charges())
dc = ase_to_ovito(atoms)
#dc.particles.masses = np.ones(len(atoms))
#dc.particles_.create_property('masses', data=atoms.get_masses())
pl = Pipeline(source=StaticSource(data=dc))
export_file(pl, ftxt, 'lammps/data', atom_style='charge')#**kwargs)
replica = 0
min_nb_atoms = 100
while (atoms*(replica,replica,replica)).get_number_of_atoms()<min_nb_atoms:
replica+=1
atoms *= (replica, replica, replica)
# if str(atoms.info['target']) == '227':
"""
if str(atoms.info['target']) == '227' or str(atoms.info['target']) == '221':
pass
"""
#if False:
# pass
#else:
# atoms = atoms*(2, 2, 2)
data = ase_to_ovito(atoms)
node = Pipeline(source=StaticSource(data=data))
node.modifiers.append(modifier)
#node.modifiers.append(CommonNeighborAnalysisModifier(mode=CommonNeighborAnalysisModifier.Mode.FixedCutoff))
# node.modifiers.append(CommonNeighborAnalysisModifier(mode=CommonNeighborAnalysisModifier.Mode.AdaptiveCutoff))
#node.modifiers.append(AcklandJonesModifier())
# node.modifiers.append(BondAngleAnalysisModifier())
# node.modifiers.append(PolyhedralTemplateMatchingModifier(rmsd_cutoff=0.0))
# Let OVITO's data pipeline do the heavy work.
node.compute()
# A two-dimensional array containing the three CNA indices
# computed for each bond in the system.
atom_classes = list(node.output.particle_properties['Structure Type'].array)
# Skip execution of this example script during testing if ASE is not installed.
import sys
try:
import ase
except:
sys.exit()
# >>>>>>>>>>>>>>>>>>>>>>> begin example snippet >>>>>>>>>>>>>>>>>>
from ovito.pipeline import StaticSource, Pipeline
from ovito.io.ase import ase_to_ovito
from ase.atoms import Atoms
# The ASE Atoms object to convert:
ase_atoms = Atoms('CO', positions=[(0, 0, 0), (0, 0, 1.1)])
# Create a new Pipeline with a StaticSource as data source:
pipeline = Pipeline(source=StaticSource())
# Convert the ASE object; use the StaticSource as destination container:
ase_to_ovito(ase_atoms, pipeline.source)
from ovito.pipeline import TrajectoryLineGenerator, Pipeline
from ovito.io import import_file
from ovito.vis import TrajectoryLineDisplay
# Load a particle simulation sequence:
pipeline = import_file('simulation.*.dump')
# Create a second pipeline for the trajectory lines:
traj_pipeline = Pipeline()
# Create data source and assign it to the second pipeline.
# The first pipeline provides the particle positions.
traj_pipeline.source = TrajectoryLineGenerator(source_pipeline=pipeline,
only_selected=False)
# Generate the trajectory lines by sampling the
# particle positions over the entire animation interval.
traj_object = traj_pipeline.source.generate()
# Configure trajectory line display:
traj_object.display.width = 0.4
traj_object.display.color = (1, 0, 0)
traj_object.display.shading = TrajectoryLineDisplay.Shading.Flat
# Insert both pipelines into the scene to make both the particles and
# the trajectory lines visible in rendered images:
pipeline.add_to_scene()
traj_pipeline.add_to_scene()