def save_ebc(self, filename, force=True, default=0.0):
"""
Save essential boundary conditions as state variables.
"""
output('saving ebc...')
variables = self.get_variables(auto_create=True)
ebcs = Conditions.from_conf(self.conf.ebcs, self.domain.regions)
epbcs = Conditions.from_conf(self.conf.epbcs, self.domain.regions)
try:
variables.equation_mapping(ebcs, epbcs, self.ts, self.functions,
problem=self)
except:
output('cannot make equation mapping!')
raise
state = State(variables)
state.fill(default)
if force:
vals = dict_from_keys_init(variables.state)
for ii, key in enumerate(vals.iterkeys()):
vals[key] = ii + 1
state.apply_ebc(force_values=vals)
else:
state.apply_ebc()
out = state.create_output_dict(extend=True)
self.save_state(filename, out=out, fill_value=default)
output('...done')
def __call__(self, problem=None, data=None):
from sfepy.base.base import select_by_names
from sfepy.fem.variables import Variables
from sfepy.fem.state import State
from sfepy.fem.conditions import Conditions
problem = get_default(problem, self.problem)
conf_ebc = select_by_names(problem.conf.ebcs, self.ebcs)
conf_epbc = select_by_names(problem.conf.epbcs, self.epbcs)
ebcs = Conditions.from_conf(conf_ebc, problem.domain.regions)
epbcs = Conditions.from_conf(conf_epbc, problem.domain.regions)
conf_variables = select_by_names(problem.conf.variables, self.variable)
problem.set_variables(conf_variables)
variables = Variables.from_conf(conf_variables, problem.fields)
variables.equation_mapping(ebcs, epbcs, problem.ts, problem.functions)
state = State(variables)
state.fill(0.0)
state.apply_ebc()
corr_sol = CorrSolution(name=self.name, state=state.get_parts())
self.save(corr_sol, problem, variables)
return corr_sol
def solve(self, state0=None, nls_status=None,
ls_conf=None, nls_conf=None, force_values=None,
var_data=None):
"""Solve self.equations in current time step.
Parameters
----------
var_data : dict
A dictionary of {variable_name : data vector} used to initialize
parameter variables.
"""
solvers = self.get_solvers()
if solvers is None:
self.init_solvers(nls_status, ls_conf, nls_conf)
solvers = self.get_solvers()
if state0 is None:
state0 = State(self.equations.variables)
else:
if isinstance(state0, nm.ndarray):
state0 = State(self.equations.variables, vec=state0)
self.equations.set_data(var_data, ignore_unknown=True)
self.update_materials()
state0.apply_ebc(force_values=force_values)
vec0 = state0.get_reduced()
vec = solvers.nls(vec0)
state = state0.copy(preserve_caches=True)
state.set_reduced(vec, preserve_caches=True)
return state
def __call__(self, problem=None, data=None):
from sfepy.base.base import select_by_names
from sfepy.fem.variables import Variables
from sfepy.fem.state import State
from sfepy.fem.conditions import Conditions
problem = get_default(problem, self.problem)
conf_ebc = select_by_names(problem.conf.ebcs, self.ebcs)
conf_epbc = select_by_names(problem.conf.epbcs, self.epbcs)
ebcs = Conditions.from_conf(conf_ebc, problem.domain.regions)
epbcs = Conditions.from_conf(conf_epbc, problem.domain.regions)
conf_variables = select_by_names(problem.conf.variables, self.variable)
problem.set_variables(conf_variables)
variables = Variables.from_conf(conf_variables, problem.fields)
variables.equation_mapping(ebcs, epbcs, problem.ts, problem.functions)
state = State(variables)
state.fill(0.0)
state.apply_ebc()
corr_sol = CorrSolution(name=self.name,
state=state.get_parts())
self.save(corr_sol, problem, variables)
return corr_sol
def __init__(self, conf, **kwargs):
from sfepy.fem.state import State
ScipyDirect.__init__(self, conf, **kwargs)
equations = self.problem.equations
aux_state = State(equations.variables)
conf.idxs = {}
for bk, bv in conf.blocks.iteritems():
aux_state.fill(0.0)
for jj in bv:
idx = equations.variables.di.indx[jj]
aux_state.vec[idx] = nm.nan
aux_state.apply_ebc()
vec0 = aux_state.get_reduced()
conf.idxs[bk] = nm.where(nm.isnan(vec0))[0]
def solve(self,
state0=None,
nls_status=None,
ls_conf=None,
nls_conf=None,
force_values=None,
var_data=None):
"""Solve self.equations in current time step.
Parameters
----------
var_data : dict
A dictionary of {variable_name : data vector} used to initialize
parameter variables.
"""
solvers = self.get_solvers()
if solvers is None:
self.init_solvers(nls_status, ls_conf, nls_conf)
solvers = self.get_solvers()
if state0 is None:
state0 = State(self.equations.variables)
else:
if isinstance(state0, nm.ndarray):
state0 = State(self.equations.variables, vec=state0)
self.equations.set_data(var_data, ignore_unknown=True)
self.update_materials()
state0.apply_ebc(force_values=force_values)
vec0 = state0.get_reduced()
vec = solvers.nls(vec0)
state = state0.copy(preserve_caches=True)
state.set_reduced(vec, preserve_caches=True)
return state
def __init__(self, conf, **kwargs):
from sfepy.fem.state import State
ScipyDirect.__init__(self, conf, **kwargs)
equations = self.problem.equations
aux_state = State(equations.variables)
conf.idxs = {}
for bk, bv in conf.blocks.iteritems():
aux_state.fill(0.0)
for jj in bv:
idx = equations.variables.di.indx[jj]
aux_state.vec[idx] = nm.nan
aux_state.apply_ebc()
vec0 = aux_state.get_reduced()
conf.idxs[bk] = nm.where(nm.isnan(vec0))[0]
def __init__(self, conf, problem, **kwargs):
from sfepy.fem.state import State
from sfepy.fem import ProblemDefinition
from sfepy.base.conf import ProblemConf, get_standard_keywords
from scipy.spatial import cKDTree as KDTree
ScipyDirect.__init__(self, conf, **kwargs)
# init subproblems
pb_vars = problem.get_variables()
# get "master" DofInfo and last index
pb_adi_indx = problem.equations.variables.adi.indx
self.adi_indx = pb_adi_indx.copy()
last_indx = -1
for ii in self.adi_indx.itervalues():
last_indx = nm.max([last_indx, ii.stop])
# coupling variables
self.cvars_to_pb = {}
for jj in conf.coupling_variables:
self.cvars_to_pb[jj] = [None, None]
if jj in pb_vars.names:
if pb_vars[jj].dual_var_name is not None:
self.cvars_to_pb[jj][0] = -1
else:
self.cvars_to_pb[jj][1] = -1
# init subproblems
self.subpb = []
required, other = get_standard_keywords()
master_prefix = output.get_output_prefix()
for ii, ifname in enumerate(conf.others):
sub_prefix = master_prefix[:-1] + '-sub%d:' % (ii + 1)
output.set_output_prefix(sub_prefix)
confi = ProblemConf.from_file(ifname,
required,
other,
define_args=kwargs)
pbi = ProblemDefinition.from_conf(confi, init_equations=True)
sti = State(pbi.equations.variables)
pbi.equations.set_data(None, ignore_unknown=True)
pbi.time_update()
pbi.update_materials()
sti.apply_ebc()
pbi_vars = pbi.get_variables()
output.set_output_prefix(master_prefix)
self.subpb.append([pbi, sti, None])
# append "slave" DofInfo
for jj in pbi_vars.names:
if not (pbi_vars[jj].is_state()):
continue
didx = pbi.equations.variables.adi.indx[jj]
ndof = didx.stop - didx.start
if jj in self.adi_indx:
if ndof != \
(self.adi_indx[jj].stop - self.adi_indx[jj].start):
raise ValueError('DOFs do not match!')
else:
self.adi_indx.update(
{jj: slice(last_indx, last_indx + ndof, None)})
last_indx += ndof
for jj in conf.coupling_variables:
if jj in pbi_vars.names:
if pbi_vars[jj].dual_var_name is not None:
self.cvars_to_pb[jj][0] = ii
else:
self.cvars_to_pb[jj][1] = ii
self.subpb.append([problem, None, None])
self.cvars_to_pb_map = {}
for varname, pbs in self.cvars_to_pb.iteritems():
# match field nodes
coors = []
for ii in pbs:
pbi = self.subpb[ii][0]
pbi_vars = pbi.get_variables()
fcoors = pbi_vars[varname].field.coors
dc = nm.abs(nm.max(fcoors, axis=0)\
- nm.min(fcoors, axis=0))
ax = nm.where(dc > 1e-9)[0]
coors.append(fcoors[:, ax])
if len(coors[0]) != len(coors[1]):
raise ValueError('number of nodes does not match!')
kdtree = KDTree(coors[0])
map_12 = kdtree.query(coors[1])[1]
pbi1 = self.subpb[pbs[0]][0]
pbi1_vars = pbi1.get_variables()
eq_map_1 = pbi1_vars[varname].eq_map
pbi2 = self.subpb[pbs[1]][0]
pbi2_vars = pbi2.get_variables()
eq_map_2 = pbi2_vars[varname].eq_map
dpn = eq_map_2.dpn
nnd = map_12.shape[0]
map_12_nd = nm.zeros((nnd * dpn, ), dtype=nm.int32)
if dpn > 1:
for ii in range(dpn):
map_12_nd[ii::dpn] = map_12 * dpn + ii
else:
map_12_nd = map_12
idx = nm.where(eq_map_2.eq >= 0)[0]
self.cvars_to_pb_map[varname] = eq_map_1.eq[map_12[idx]]
def __init__(self, conf, problem, **kwargs):
from sfepy.fem.state import State
from sfepy.fem import ProblemDefinition
from sfepy.base.conf import ProblemConf, get_standard_keywords
from scipy.spatial import cKDTree as KDTree
ScipyDirect.__init__(self, conf, **kwargs)
# init subproblems
pb_vars = problem.get_variables()
# get "master" DofInfo and last index
pb_adi_indx = problem.equations.variables.adi.indx
self.adi_indx = pb_adi_indx.copy()
last_indx = -1
for ii in self.adi_indx.itervalues():
last_indx = nm.max([last_indx, ii.stop])
# coupling variables
self.cvars_to_pb = {}
for jj in conf.coupling_variables:
self.cvars_to_pb[jj] = [None, None]
if jj in pb_vars.names:
if pb_vars[jj].dual_var_name is not None:
self.cvars_to_pb[jj][0] = -1
else:
self.cvars_to_pb[jj][1] = -1
# init subproblems
self.subpb = []
required, other = get_standard_keywords()
master_prefix = output.get_output_prefix()
for ii, ifname in enumerate(conf.others):
sub_prefix = master_prefix[:-1] + "-sub%d:" % (ii + 1)
output.set_output_prefix(sub_prefix)
confi = ProblemConf.from_file(ifname, required, other, define_args=kwargs)
pbi = ProblemDefinition.from_conf(confi, init_equations=True)
sti = State(pbi.equations.variables)
pbi.equations.set_data(None, ignore_unknown=True)
pbi.time_update()
pbi.update_materials()
sti.apply_ebc()
pbi_vars = pbi.get_variables()
output.set_output_prefix(master_prefix)
self.subpb.append([pbi, sti, None])
# append "slave" DofInfo
for jj in pbi_vars.names:
if not (pbi_vars[jj].is_state()):
continue
didx = pbi.equations.variables.adi.indx[jj]
ndof = didx.stop - didx.start
if jj in self.adi_indx:
if ndof != (self.adi_indx[jj].stop - self.adi_indx[jj].start):
raise ValueError("DOFs do not match!")
else:
self.adi_indx.update({jj: slice(last_indx, last_indx + ndof, None)})
last_indx += ndof
for jj in conf.coupling_variables:
if jj in pbi_vars.names:
if pbi_vars[jj].dual_var_name is not None:
self.cvars_to_pb[jj][0] = ii
else:
self.cvars_to_pb[jj][1] = ii
self.subpb.append([problem, None, None])
self.cvars_to_pb_map = {}
for varname, pbs in self.cvars_to_pb.iteritems():
# match field nodes
coors = []
for ii in pbs:
pbi = self.subpb[ii][0]
pbi_vars = pbi.get_variables()
fcoors = pbi_vars[varname].field.coors
dc = nm.abs(nm.max(fcoors, axis=0) - nm.min(fcoors, axis=0))
ax = nm.where(dc > 1e-9)[0]
coors.append(fcoors[:, ax])
if len(coors[0]) != len(coors[1]):
raise ValueError("number of nodes does not match!")
kdtree = KDTree(coors[0])
map_12 = kdtree.query(coors[1])[1]
pbi1 = self.subpb[pbs[0]][0]
pbi1_vars = pbi1.get_variables()
eq_map_1 = pbi1_vars[varname].eq_map
pbi2 = self.subpb[pbs[1]][0]
pbi2_vars = pbi2.get_variables()
eq_map_2 = pbi2_vars[varname].eq_map
dpn = eq_map_2.dpn
nnd = map_12.shape[0]
map_12_nd = nm.zeros((nnd * dpn,), dtype=nm.int32)
if dpn > 1:
for ii in range(dpn):
map_12_nd[ii::dpn] = map_12 * dpn + ii
else:
map_12_nd = map_12
idx = nm.where(eq_map_2.eq >= 0)[0]
self.cvars_to_pb_map[varname] = eq_map_1.eq[map_12[idx]]
def create_state(self):
return State(self.equations.variables)
