/usr/share/pyshared/cclib/method/population.py is in python-cclib 1.1-1.
This file is owned by root:root, with mode 0o644.
The actual contents of the file can be viewed below.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 | # This file is part of cclib (http://cclib.sf.net), a library for parsing
# and interpreting the results of computational chemistry packages.
#
# Copyright (C) 2006, the cclib development team
#
# The library is free software, distributed under the terms of
# the GNU Lesser General Public version 2.1 or later. You should have
# received a copy of the license along with cclib. You can also access
# the full license online at http://www.gnu.org/copyleft/lgpl.html.
__revision__ = "$Revision: 960 $"
import logging
import numpy
from calculationmethod import Method
class Population(Method):
"""A base class for all population-type methods."""
def __init__(self, data, progress=None, \
loglevel=logging.INFO, logname="Log"):
# Call the __init__ method of the superclass.
super(Population, self).__init__(data, progress, loglevel, logname)
self.fragresults = None
def __str__(self):
"""Return a string representation of the object."""
return "Population"
def __repr__(self):
"""Return a representation of the object."""
return "Population"
def partition(self, indices=None):
if not hasattr(self, "aoresults"):
self.calculate()
if not indices:
# Build list of groups of orbitals in each atom for atomresults.
if hasattr(self.data, "aonames"):
names = self.data.aonames
elif hasattr(self.data, "fonames"):
names = self.data.fonames
atoms = []
indices = []
name = names[0].split('_')[0]
atoms.append(name)
indices.append([0])
for i in range(1, len(names)):
name = names[i].split('_')[0]
try:
index = atoms.index(name)
except ValueError: #not found in atom list
atoms.append(name)
indices.append([i])
else:
indices[index].append(i)
natoms = len(indices)
nmocoeffs = len(self.aoresults[0])
# Build results numpy array[3].
alpha = len(self.aoresults[0])
results = []
results.append(numpy.zeros([alpha, natoms], "d"))
if len(self.aoresults) == 2:
beta = len(self.aoresults[1])
results.append(numpy.zeros([beta, natoms], "d"))
# For each spin, splice numpy array at ao index,
# and add to correct result row.
for spin in range(len(results)):
for i in range(natoms): # Number of groups.
for j in range(len(indices[i])): # For each group.
temp = self.aoresults[spin][:, indices[i][j]]
results[spin][:, i] = numpy.add(results[spin][:, i], temp)
self.logger.info("Saving partitioned results in fragresults: [array[2]]")
self.fragresults = results
return True
if __name__ == "__main__":
import doctest, population
doctest.testmod(population, verbose=False)
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