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gtssongchi

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专业: 凝聚态物性 II ：电子结构

[求助] ovito中打开python脚本错误已有3人参与

大家好，用ovito计算voronoi多面体时，按照手册采用的python脚本计算。手册上脚本如下
# Import OVITO modules.
from ovito.io import *
from ovito.modifiers import *

# Import NumPy module.
import numpy

# Load a simulation snapshot of a Cu-Zr metallic glass.
node = import_file("../data/CuZr_metallic_glass.dump.gz"

# Set atomic radii (required for polydisperse Voronoi tessellation).
atypes = node.source.particle_properties.particle_type.type_list
atypes[0].radius = 1.35       # Cu atomic radius (atom type 1 in input file)
atypes[1].radius = 1.55       # Zr atomic radius (atom type 2 in input file)

# Set up the Voronoi analysis modifier.
voro = VoronoiAnalysisModifier(
compute_indices = True,
use_radii = True,
edge_count = 6, # Length after which Voronoi index vectors are truncated
edge_threshold = 0.1
)
node.modifiers.append(voro)

# Let OVITO compute the results.
node.compute()

# Make sure we did not lose information due to truncated Voronoi index vectors.
if voro.max_face_order > voro.edge_count:
print("Warning: Maximum face order in Voronoi tessellation is {0}, "
      "but computed Voronoi indices are truncated after {1} entries. "
      "You should consider increasing the 'edge_count' parameter to {0}."
      .format(voro.max_face_order, voro.edge_count))
# Note that it would be possible to automatically increase the 'edge_count'
# parameter to 'max_face_order' here and recompute the Voronoi tessellation:
# voro.edge_count = voro.max_face_order
# node.compute()

# Access computed Voronoi indices as NumPy array.
# This is an (N)x(edge_count) array.
voro_indices = node.output.particle_properties['Voronoi Index'].array

# This helper function takes a two-dimensional array and computes a frequency
# histogram of the data rows using some NumPy magic.
# It returns two arrays (of equal length):
# 1. The list of unique data rows from the input array
# 2. The number of occurences of each unique row
# Both arrays are sorted in descending order such that the most frequent rows
# are listed first.
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)
sort_indices = numpy.argsort(counts)[::-1]
return (a[indices[sort_indices]], counts[sort_indices])

# Compute frequency histogram.
unique_indices, counts = row_histogram(voro_indices)

# Print the ten most frequent histogram entries.
for i in range(10):
print("%s\t%i\t(%.1f %%)" % (tuple(unique_indices),
                              counts,
                              100.0*float(counts)/len(voro_indices)))

我只是将其中的文件路径改变了。在运行时却提示如下错误：
Traceback (most recent call last):
  File "/home/csong/ovito.py", line 2, in <module>
from ovito.io import *
ImportError: No module named 'ovito.io'; 'ovito' is not a package
ERROR: Failed to initialize Python interpreter.

请问这是什么原因呢？