/usr/lib/python2.7/dist-packages/ffc/restrictedelement.py is in python-ffc 1.4.0-1.
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 | # Copyright (C) 2010 Anders Logg
#
# This file is part of FFC.
#
# FFC is free software: you can redistribute it and/or modify
# it under the terms of the GNU Lesser General Public License as published by
# the Free Software Foundation, either version 3 of the License, or
# (at your option) any later version.
#
# FFC is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU Lesser General Public License for more details.
#
# You should have received a copy of the GNU Lesser General Public License
# along with FFC. If not, see <http://www.gnu.org/licenses/>.
#
# Modified by Marie Rognes, 2010.
#
# Last changed: 2010-04-07
from ffc.log import error
import numpy
class RestrictedElement:
"Create a restriction of a given FIAT element."
def __init__(self, element, indices, domain):
if len(indices) == 0:
error("No point in creating empty RestrictedElement.")
self._element = element
self._indices = indices
self._entity_dofs = _extract_entity_dofs(element, indices)
self._domain = domain
def space_dimension(self):
return len(self._indices)
def value_shape(self):
return self._element.value_shape()
def degree(self):
return self._element.degree()
def entity_dofs(self):
return self._entity_dofs
def mapping(self):
mappings = self._element.mapping()
return [mappings[i] for i in self._indices]
def dual_basis(self):
dual = self._element.dual_basis()
return [dual[i] for i in self._indices]
def tabulate(self, order, points):
result = self._element.tabulate(order, points)
extracted = {}
for (dtuple, values) in result.iteritems():
extracted[dtuple] = numpy.array([values[i] for i in self._indices])
return extracted
# Used in evaluate_basis:
def get_coeffs(self):
coefficients = self._element.get_coeffs()
return numpy.array([coefficients[i] for i in self._indices])
def dmats(self):
return self._element.dmats()
def get_num_members(self, arg):
return self._element.get_num_members(arg)
def domain(self):
return self._domain
def _extract_entity_dofs(element, indices):
# FIXME: Readability counts
entity_dofs = element.entity_dofs()
dofs = {}
for (dim, entities) in entity_dofs.iteritems():
dofs[dim] = {}
for (entity, all_dofs) in entities.iteritems():
dofs[dim][entity] = []
for index in all_dofs:
if index in indices:
# print "index = ", index
i = indices.index(index)
dofs[dim][entity] += [i]
return dofs
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