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Topics - eason1021

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1
Support Forum / Order of neighbors from NearestNeighborFinder
« on: July 09, 2018, 07:02:26 PM »
And I still want to ask a question.
Now I stored 6 nearest neighbors around the central atom.
The neigh index in NearestNeighborFinder is sorted list of nearest neighbors.
But I want to sort these 6 atoms is array by +x +y +z -x -y -z direction to central atom.
Has any function to re-array the neigh index list?

2
When I update my ovito to the latest version.
My older script can't work
It will said:AttributeError: type object 'BondsView' has no attribute 'Enumerator'

Below is my code:

Code: [Select]
from ovito.io import *
from ovito.modifiers import *
from ovito.data import Bonds

# Import standard Python and NumPy modules.
import sys
import numpy

# Load the simulation dataset to be analyzed.
node = import_file("input.dump")

#create a output file
file = open('output_file.txt' , 'w')

# Create bonds.
node.modifiers.append(CreateBondsModifier(cutoff = 3.5))

# Compute CNA indices on the basis of the created bonds.
node.modifiers.append(
        CommonNeighborAnalysisModifier(mode = CommonNeighborAnalysisModifier.Mode.BondBased))
                     
# 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.
cna_indices = node.output.bond_properties['CNA Indices'].array

# This helper function takes a two-dimensional array and computes the frequency
# histogram of the data rows using some NumPy magic.
# It returns two arrays (of same length):
#    1. The list of unique data rows from the input array
#    2. The number of occurences of each unique row
def row_histogram(a):
    ca = numpy.ascontiguousarray(a).view([('', a.dtype)] * a.shape[1])
    unique, indices, inverse = numpy.unique(ca, return_index=True, return_inverse=True)
    counts = numpy.bincount(inverse)
    return (a[indices], counts)

# Used below for enumerating the bonds of each particle:
bond_enumerator = Bonds.Enumerator(node.output.bonds)

# Loop over atoms.
bonds_array = node.output.bonds.array
# Loop over particles and print their CNA indices.
for particle_index in range(node.output.number_of_particles):
   
    # Print particle index (1-based).
    sys.stdout.write("%i " % (particle_index+1))
    # Create local list with CNA indices of the bonds of the current particle.
    bond_index_list = list(bond_enumerator.bonds_of_particle(particle_index))
    local_cna_indices = cna_indices[bond_index_list]

    # Count how often each type of CNA triplet occurred.
    unique_triplets, triplet_counts = row_histogram(local_cna_indices)
   
    # Print list of triplets with their respective counts.
    for triplet, count in zip(unique_triplets, triplet_counts):
        sys.stdout.write("%s:%i " % (triplet, count))
        file.write("\n%i %s:%i " % (particle_index+1, triplet, count))

# Loop over half-bonds of current atom.
    for bond_index in bond_enumerator.bonds_of_particle(particle_index):
        atomA = bonds_array[bond_index][0]
        atomB = bonds_array[bond_index][1]
        assert(atomA == particle_index)
        print("\nAtom %i has a bond to atom %i" % (atomA, atomB))
        file.write("\nAtom %i has a bond to atom %i" % (atomA, atomB))

    # End of particle line
sys.stdout.write("\n")
file.close()

3
Support Forum / How to export custom variables by python scripts?
« on: January 23, 2018, 05:26:42 AM »
I want to export the atomA & atomB as a imd(or txt)

the code is below


# Import OVITO modules.
from ovito.io import *
from ovito.modifiers import *
from ovito.data import *
from ovito.data import Bonds
from ovito.modifiers import PythonScriptModifier

# Import standard Python and NumPy modules.
import sys
import numpy

# Load the simulation dataset to be analyzed.
node = import_file('/Users/eason851021/Documents/1635/dump.tensile_200.dump')
# Create bonds.
node.modifiers.append(CreateBondsModifier(cutoff = 3.5))

# Compute CNA indices on the basis of the created bonds.
node.modifiers.append(
        CommonNeighborAnalysisModifier(mode = CommonNeighborAnalysisModifier.Mode.BondBased))
                     
# 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.
cna_indices = node.output.bond_properties['CNA Indices'].array

# This helper function takes a two-dimensional array and computes the frequency
# histogram of the data rows using some NumPy magic.
# It returns two arrays (of same length):
#    1. The list of unique data rows from the input array
#    2. The number of occurences of each unique row
def row_histogram(a):
    ca = numpy.ascontiguousarray(a).view([('', a.dtype)] * a.shape[1])
    unique, indices, inverse = numpy.unique(ca, return_index=True, return_inverse=True)
    counts = numpy.bincount(inverse)
    return (a[indices], counts)

# Used below for enumerating the bonds of each particle:
bond_enumerator = Bonds.Enumerator(node.output.bonds)

# Loop over atoms.
bonds_array = node.output.bonds.array
# Loop over particles and print their CNA indices.
for particle_index in range(node.output.number_of_particles):
   
    # Print particle index (1-based).
    sys.stdout.write("%i " % (particle_index+1))
   
    # Create local list with CNA indices of the bonds of the current particle.
    bond_index_list = list(bond_enumerator.bonds_of_particle(particle_index))
    local_cna_indices = cna_indices[bond_index_list]

    # Count how often each type of CNA triplet occurred.
    unique_triplets, triplet_counts = row_histogram(local_cna_indices)
   
    # Print list of triplets with their respective counts.
    for triplet, count in zip(unique_triplets, triplet_counts):
        sys.stdout.write("%s:%i " % (triplet, count))
   # Loop over half-bonds of current atom.
    for bond_index in bond_enumerator.bonds_of_particle(particle_index):
        atomA = bonds_array[bond_index][0]
        atomB = bonds_array[bond_index][1]
        assert(atomA == particle_index)
        print("\nAtom %i has a bond to atom %i" % (atomA, atomB))
   
    export_file(node, "/Users/eason851021/Documents/1635/output.imd",
   format = "imd",
   columns = ["Particle Identifier", "Particle Type", "%i"%(atomA), "%i" % (atomB)])
   
   # End of particle line
    sys.stdout.write("\n")



But it display an error ´╝ÜRuntimeError: The set of output data columns is invalid (column 3). The property '0' does not exist.

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