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extractor.py
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extractor.py
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#!/usr/bin/env python
"""
Examples
--------
$ ./extractor.py -e "p e 0 1999" bone.h5
$ ./extractor.py -e "p e 0 1999" bone.h5 -a
$ ./extractor.py -e "p e 0 1999" bone.h5 -o extracted.h5
$ ./extractor.py -e "p e 0 1999" bone.h5 -o extracted.h5 -a
"""
import os
from optparse import OptionParser
import sfepy
from sfepy.base.base import nm, dict_to_struct, get_default, Struct
from sfepy.base.ioutils import get_trunk
import sfepy.postprocess.time_history as th
def create_problem(filename):
from sfepy.fem import ProblemDefinition
problem = ProblemDefinition.from_conf_file(filename,
init_equations=False,
init_solvers=False)
return problem
def parse_linearization(linearization):
out = {}
for item in linearization.split(','):
key, val = item.split(':')
if key == 'eps':
val = float(val)
elif key in ('min_level', 'max_level'):
val = int(val)
elif key == 'kind':
pass
else:
raise ValueError('wrong linearization option key! (%s)'
% key)
out[key] = val
return dict_to_struct(out)
usage = """%prog [options] [<input file>] <results file>
Extract information from a SfePy multi-time-step results file (HDF5
format) and/or linearize results with stored higher order DOFs.
For the linearization, the original input (problem description) file must
be specified as the first argument. Use the option --linearization below
to override linearization parameters defined in the input file. The
linearization forces --dump option, i.e., output to VTK files.
"""
help = {
'filename' :
'basename of output file(s) [default: <basename of input file>]',
'dump' :
'dump to sequence of VTK files',
'same_dir' :
'store the dumped VTK files in the directory of filename_in',
'linearization' :
'linearization options. Default values apply if neither command'
' line nor input file options are set.'
" [default: 'kind:adaptive,min_level:0,max_level:2,eps:1e-2']",
'times' :
'extract and print times of individual time steps',
'from' :
'start dumping from time step ii [default: %default]',
'to' :
'stop dumping at time step ii [default: <last step>]',
'step' :
'use every ii-th step for dumping [default: %default]',
'extract' :
'extract variables according to extraction list.'
" Example: 'u n 10 15, p e 0' means variable 'u' in nodes 10, 15"
" and variable 'p' in element 0",
'average' :
'average vertex variable into cells ("e" extraction mode)'
}
def main():
parser = OptionParser(usage=usage, version="%prog " + sfepy.__version__)
parser.add_option('-o', '', metavar='filename',
action='store', dest='output_filename_trunk',
default=None, help=help['filename'])
parser.add_option('-d', '--dump', action='store_true', dest='dump',
default=False, help=help['dump'])
parser.add_option('', '--same-dir', action='store_true', dest='same_dir',
default=False, help=help['same_dir'])
parser.add_option('-l', '--linearization', metavar='options',
action='store', dest='linearization',
default=None, help=help['linearization'])
parser.add_option('', '--times', action='store_true', dest='times',
default=False, help=help['times'])
parser.add_option('-f', '--from', type=int, metavar='ii',
action='store', dest='step_from',
default=0, help=help['from'])
parser.add_option('-t', '--to', type=int, metavar='ii',
action='store', dest='step_to',
default=None, help=help['to'])
parser.add_option('-s', '--step', type=int, metavar='ii',
action='store', dest='step_by',
default=1, help=help['step'])
parser.add_option('-e', '--extract', metavar='list',
action='store', dest='extract',
default=None, help=help['extract'])
parser.add_option('-a', '--average', action='store_true', dest='average',
default=False, help=help['average'])
(options, args) = parser.parse_args()
nargs = len(args)
if nargs == 1:
filename_results = args[0]
linearize = False
elif nargs == 2:
filename_in, filename_results = args
linearize = True
options.dump = True
else:
parser.print_help()
return
if options.times:
steps, times, nts, dts = th.extract_times(filename_results)
for ii, time in enumerate(times):
step = steps[ii]
print '%d %e %e %e' % (step, time, nts[ii], dts[ii])
if options.dump:
trunk = get_default(options.output_filename_trunk,
get_trunk(filename_results))
if options.same_dir:
trunk = os.path.join(os.path.dirname(filename_results),
os.path.basename(trunk))
args = {}
if linearize:
problem = create_problem(filename_in)
linearization = Struct(kind='adaptive', min_level=0,
max_level=2, eps=1e-2)
aux = problem.conf.options.get('linearization', None)
linearization.update(aux)
if options.linearization is not None:
aux = parse_linearization(options.linearization)
linearization.update(aux)
args.update({'fields' : problem.fields,
'linearization' : linearization})
if options.step_to is None:
args.update({'step0' : options.step_from})
else:
args.update({'steps' : nm.arange(options.step_from,
options.step_to + 1,
options.step_by, dtype=nm.int)})
th.dump_to_vtk(filename_results, output_filename_trunk=trunk, **args)
if options.extract:
ths, ts = th.extract_time_history(filename_results, options.extract)
if options.average:
ths = th.average_vertex_var_in_cells(ths)
if options.output_filename_trunk:
th.save_time_history(ths, ts, options.output_filename_trunk + '.h5')
else:
print dict_to_struct(ths, flag=(1, 1, 1)).str_all()
if __name__ == '__main__':
main()