Source code for sfepy.discrete.problem

from __future__ import absolute_import
import os
import os.path as op
from copy import copy

import numpy as nm

from sfepy.base.base import (
    dict_from_keys_init, select_by_names, is_string, is_integer, is_sequence,
    output, get_default, Struct, IndexedStruct)
import sfepy.base.ioutils as io
from sfepy.base.conf import ProblemConf, get_standard_keywords
from sfepy.base.conf import transform_variables, transform_materials
from sfepy.base.timing import Timer
from .functions import Functions
from sfepy.discrete.fem.mesh import Mesh
from sfepy.discrete.fem.meshio import check_format_suffix
from sfepy.discrete.fem.fields_base import set_mesh_coors
from sfepy.discrete.common.fields import fields_from_conf
from .variables import Variables, Variable
from .materials import Materials, Material
from .equations import Equations
from .integrals import Integrals
from sfepy.discrete.state import State
from sfepy.discrete.conditions import Conditions
from sfepy.discrete.evaluate import create_evaluable, eval_equations
from sfepy.solvers.ts import TimeStepper
from sfepy.discrete.evaluate import Evaluator
from sfepy.solvers import Solver, NonlinearSolver
from sfepy.solvers.solvers import use_first_available
from sfepy.solvers.ts_solvers import StationarySolver
import six
from six.moves import range

[docs]def make_is_save(options): """ Given problem options, return a callable that determines whether to save results of a time step. """ class IsSave(Struct): def __init__(self, save_times): if is_sequence(save_times): save_times = nm.asarray(save_times) self.save_times0 = save_times self.reset() def reset(self, ts=None): self.ilast = 0 self.save_times = self.save_times0 if ts is not None: if is_integer(self.save_times0): self.save_times = nm.linspace(ts.t0, ts.t1, self.save_times0) def __call__(self, ts): if is_string(self.save_times) and self.save_times == 'all': return True elif isinstance(self.save_times, nm.ndarray): if (self.ilast < len(self.save_times) and (ts.time + (1e-14 * ts.dt) >= self.save_times[self.ilast])): self.ilast += 1 return True elif callable(self.save_times): return self.save_times(ts) return False save_times = options.get('save_times', 'all') is_save = IsSave(save_times) return is_save
[docs]def prepare_matrix(problem, state): """ Pre-assemble tangent system matrix. """ problem.update_materials() ev = problem.get_evaluator() try: mtx = ev.eval_tangent_matrix(state(), is_full=True) except ValueError: output('matrix evaluation failed, giving up...') raise return mtx
## # 29.01.2006, c
[docs]class Problem(Struct): """ Problem definition, the top-level class holding all data necessary to solve a problem. It can be constructed from a :class:`ProblemConf <sfepy.base.conf.ProblemConf>` instance using `Problem.from_conf()` or directly from a problem description file using `Problem.from_conf_file()` For interactive use, the constructor requires only the `equations`, `nls` and `ls` keyword arguments, see below. Parameters ---------- name : str The problem name. conf : ProblemConf instance, optional The :class:`ProblemConf <sfepy.base.conf.ProblemConf>` describing the problem. functions : Functions instance, optional The user functions for boundary conditions, materials, etc. domain : Domain instance, optional The solution :class:`Domain <sfepy.discrete.common.domain.Domain>`. fields : dict, optional The dictionary of :class:`Field <sfepy.discrete.common.fields.Field>` instances. equations : Equations instance, optional The :class:`Equations <sfepy.discrete.equations.Equations>` to solve. This argument is required when `auto_conf` is True. auto_conf : bool If True, fields and domain are determined by `equations`. active_only : bool If True, the (tangent) matrices and residual vectors (right-hand sides) contain only active DOFs, see below. Notes ----- The Problem is by default created with `active_only` set to True. Then the (tangent) matrices and residual vectors (right-hand sides) have reduced sizes and contain only the active DOFs, i.e., DOFs not constrained by EBCs or EPBCs. Setting `active_only` to False results in full-size vectors and matrices. Then the matrix size non-zeros structure does not depend on the actual E(P)BCs applied. It must be False when using parallel PETSc solvers. The active DOF connectivities contain all DOFs, with the E(P)BC-constrained ones stored as `-1 - <DOF number>`, so that the full connectivities can be reconstructed for the matrix graph creation. However, the negative entries mean that the assembled matrices/residuals have zero values at positions corresponding to constrained DOFs. The resulting linear system then provides a solution increment, that has to be added to the initial guess used to compute the residual, just like in the Newton iterations. The increment of the constrained DOFs is automatically zero. When solving with a direct solver, the diagonal entries of a matrix at positions corresponding to constrained DOFs has to be set to ones, so that the matrix is not singular, see :func:`sfepy.discrete.evaluate.apply_ebc_to_matrix()`, which is called automatically in :func:`sfepy.discrete.evaluate.Evaluator.eval_tangent_matrix()`. It is not called automatically in :func:`Problem.evaluate()`. Note that setting the diagonal entries to one might not be necessary with iterative solvers, as the zero matrix rows match the zero residual rows, i.e. if the reduced matrix would be regular, then the right-hand side (the residual) is orthogonal to the kernel of the matrix. """
[docs] @staticmethod def from_conf_file(conf_filename, required=None, other=None, init_fields=True, init_equations=True, init_solvers=True): _required, _other = get_standard_keywords() if required is None: required = _required if other is None: other = _other conf = ProblemConf.from_file(conf_filename, required, other) obj = Problem.from_conf(conf, init_fields=init_fields, init_equations=init_equations, init_solvers=init_solvers) return obj
[docs] @staticmethod def from_conf(conf, init_fields=True, init_equations=True, init_solvers=True): if conf.options.get('absolute_mesh_path', False): conf_dir = None else: conf_dir = op.dirname(conf.funmod.__file__) functions = Functions.from_conf(conf.functions) if conf.get('filename_mesh') is not None: from sfepy.discrete.fem.domain import FEDomain mesh = Mesh.from_file(conf.filename_mesh, prefix_dir=conf_dir) domain = FEDomain(, mesh) refine = conf.options.get('refinement_level', 0) if refine > 0: for ii in range(refine): output('refine %d...' % ii) domain = domain.refine() output('... %d nodes %d elements' % (domain.shape.n_nod, domain.shape.n_el)) if conf.options.get('ulf', False): domain.mesh.coors_act = domain.mesh.coors.copy() if conf.options.get('mesh_eps') is not None: import sfepy.discrete.fem.mesh as msh import sfepy.discrete.fem.periodic as per msh.set_accuracy(conf.options.mesh_eps) per.set_accuracy(conf.options.mesh_eps) elif conf.get('filename_domain') is not None: from sfepy.discrete.iga.domain import IGDomain domain = IGDomain.from_file(conf.filename_domain) else: raise ValueError('missing filename_mesh or filename_domain!') active_only = conf.options.get('active_only', True) obj = Problem('problem_from_conf', conf=conf, functions=functions, domain=domain, auto_conf=False, active_only=active_only) allow_empty = conf.options.get('allow_empty_regions', False) obj.set_regions(conf.regions, obj.functions, allow_empty=allow_empty) obj.clear_equations() if init_fields: obj.set_fields(conf.fields) if init_equations: obj.set_equations(conf.equations) if init_solvers: obj.set_conf_solvers(conf.solvers, conf.options) return obj
def __init__(self, name, conf=None, functions=None, domain=None, fields=None, equations=None, auto_conf=True, active_only=True): self.active_only = active_only = name self.conf = conf self.functions = functions self.reset() self.ls_conf = self.nls_conf = self.ts_conf = None self.conf_variables = self.conf_materials = None if auto_conf: if equations is None: raise ValueError('missing equations in auto_conf mode!') if fields is None: variables = equations.variables fields = {} for field in [var.get_field() for var in variables]: fields[] = field if domain is None: domain = list(fields.values())[0].domain if conf is None: self.conf = Struct(options={}, ics={}, ebcs={}, epbcs={}, lcbcs={}, materials={}) self.equations = equations self.fields = fields self.domain = domain self.setup_output()
[docs] def reset(self): if hasattr(self.conf, 'options'): self.setup_hooks(self.conf.options) else: self.setup_hooks() self.mtx_a = None self.solver = None self.ts = self.get_default_ts() self.clear_equations() self._restart_filenames = []
[docs] def setup_hooks(self, options=None): """ Setup various hooks (user-defined functions), as given in `options`. Supported hooks: - `matrix_hook` - check/modify tangent matrix in each nonlinear solver iteration - `nls_iter_hook` - called prior to every iteration of nonlinear solver, if the solver supports that - takes the Problem instance (`self`) as the first argument """ hook_names = ['nls_iter_hook', 'matrix_hook'] for hook_name in hook_names: setattr(self, hook_name, None) if options is not None: hook = options.get(hook_name, None) if hook is not None: hook = self.conf.get_function(hook) setattr(self, hook_name, hook)
[docs] def copy(self, name=None): """ Make a copy of Problem. """ if name is None: name = + '_copy' obj = self.__class__(name, conf=self.conf, functions=self.functions, domain=self.domain, fields=self.fields, equations=self.equations, auto_conf=False, active_only=self.active_only) obj.ebcs = self.ebcs obj.epbcs = self.epbcs obj.lcbcs = self.lcbcs obj.ics = self.ics obj.set_conf_solvers(self.conf.solvers, self.conf.options) obj.setup_output(output_filename_trunk=self.ofn_trunk, output_dir=self.output_dir, output_format=self.output_format, file_format=self.file_format, file_per_var=self.file_per_var, linearization=self.linearization) return obj
[docs] def create_subproblem(self, var_names, known_var_names): """ Create a sub-problem with equations containing only terms with the given virtual variables. Parameters ---------- var_names : list The list of names of virtual variables. known_var_names : list The list of names of (already) known state variables. Returns ------- subpb : Problem instance The sub-problem. """ subpb = Problem( + '_' + '_'.join(var_names), conf=self.conf, functions=self.functions, domain=self.domain, fields=self.fields, auto_conf=False, active_only=self.active_only) subpb.set_conf_solvers(self.conf.solvers, self.conf.options) subeqs = self.equations.create_subequations(var_names, known_var_names) subpb.set_equations_instance(subeqs, keep_solvers=True) return subpb
[docs] def setup_default_output(self, conf=None, options=None): """ Provide default values to `Problem.setup_output()` from `conf.options` and `options`. """ conf = get_default(conf, self.conf) if options and getattr(options, 'output_filename_trunk', None): default_output_dir, of = op.split(options.output_filename_trunk) default_trunk = io.get_trunk(of) else: default_trunk = None default_output_dir = conf.options.get('output_dir', None) if options and getattr(options, 'output_format', None): default_output_format = options.output_format else: default_output_format = conf.options.get('output_format', None) default_file_format = conf.options.get('file_format', None) default_file_per_var = conf.options.get('file_per_var', None) default_float_format = conf.options.get('float_format', None) default_linearization = Struct(kind='strip') self.setup_output(output_filename_trunk=default_trunk, output_dir=default_output_dir, output_format=default_output_format, file_format=default_file_format, float_format=default_float_format, file_per_var=default_file_per_var, linearization=default_linearization)
[docs] def setup_output(self, output_filename_trunk=None, output_dir=None, output_format=None, file_format=None, float_format=None, file_per_var=None, linearization=None): """ Sets output options to given values, or uses the defaults for each argument that is None. """ self.output_modes = {'vtk' : 'sequence', 'h5' : 'single', 'msh' : 'sequence'} self.ofn_trunk = get_default(output_filename_trunk, op.basename( self.set_output_dir(output_dir) self.output_format = get_default(output_format, 'vtk') self.file_format = file_format if self.file_format is not None: check_format_suffix(self.file_format, self.output_format) self.float_format = get_default(float_format, None) self.file_per_var = get_default(file_per_var, False) self.linearization = get_default(linearization, Struct(kind='strip')) if ((self.output_format == 'h5') and (self.linearization.kind == 'adaptive')): self.linearization.kind = None
[docs] def set_output_dir(self, output_dir=None): """ Set the directory for output files. The directory is created if it does not exist. """ self.output_dir = get_default(output_dir, os.curdir) if self.output_dir and not op.exists(self.output_dir): os.makedirs(self.output_dir)
[docs] def set_regions(self, conf_regions=None, conf_materials=None, functions=None, allow_empty=False): conf_regions = get_default(conf_regions, self.conf.regions) functions = get_default(functions, self.functions) self.domain.create_regions(conf_regions, functions, allow_empty=allow_empty)
[docs] def set_materials(self, conf_materials=None): """ Set definition of materials. """ self.conf_materials = get_default(conf_materials, self.conf.materials)
[docs] def select_materials(self, material_names, only_conf=False): if type(material_names) == dict: conf_materials = transform_materials(material_names) else: conf_materials = select_by_names(self.conf.materials, material_names) if not only_conf: self.set_materials(conf_materials) return conf_materials
[docs] def set_fields(self, conf_fields=None): conf_fields = get_default(conf_fields, self.conf.fields) self.fields = fields_from_conf(conf_fields, self.domain.regions)
[docs] def set_variables(self, conf_variables=None): """ Set definition of variables. """ self.conf_variables = get_default(conf_variables, self.conf.variables) self.reset()
[docs] def select_variables(self, variable_names, only_conf=False): if type(variable_names) == dict: conf_variables = transform_variables(variable_names) else: conf_variables = select_by_names(self.conf.variables, variable_names) if not only_conf: self.set_variables(conf_variables) return conf_variables
[docs] def clear_equations(self): self.integrals = None self.equations = None self.ebcs = None self.epbcs = None self.lcbcs = None self.ics = None
[docs] def set_equations(self, conf_equations=None, user=None, keep_solvers=False, make_virtual=False): """ Set equations of the problem using the `equations` problem description entry. Fields and Regions have to be already set. """ conf_equations = get_default(conf_equations, self.conf.get('equations', None)) self.set_variables(self.conf_variables) variables = Variables.from_conf(self.conf_variables, self.fields) self.set_materials(self.conf_materials) materials = Materials.from_conf(self.conf_materials, self.functions) self.integrals = self.get_integrals() default_user = vars(self.conf) if user is not None: default_user.update(user) user = default_user eterm_options = self.conf.options.get('eterm', {}) equations = Equations.from_conf(conf_equations, variables, self.domain.regions, materials, self.integrals, user=user, eterm_options=eterm_options) self.equations = equations if not keep_solvers: self.solver = None
[docs] def set_equations_instance(self, equations, keep_solvers=False): """ Set equations of the problem to `equations`. """ self.mtx_a = None self.clear_equations() self.equations = equations if not keep_solvers: self.solver = None
[docs] def get_integrals(self, names=None): """ Get integrals, initialized from problem configuration if available. Parameters ---------- names : list, optional If given, only the named integrals are returned. Returns ------- integrals : Integrals instance The requested integrals. """ conf_integrals = self.conf.get('integrals', {}) integrals = Integrals.from_conf(conf_integrals) if names is not None: integrals.update([integrals[ii] for ii in names if ii in integrals.names]) return integrals
[docs] def update_materials(self, ts=None, mode='normal', verbose=True): """ Update materials used in equations. Parameters ---------- ts : TimeStepper instance The time stepper. mode : 'normal', 'update' or 'force' The update mode, see :func:`Material.time_update() <sfepy.discrete.materials.Material.time_update()>`. verbose : bool If False, reduce verbosity. """ if self.equations is not None: self.update_time_stepper(ts) self.equations.time_update_materials(self.ts, mode=mode, problem=self, verbose=verbose)
[docs] def update_equations(self, ts=None, ebcs=None, epbcs=None, lcbcs=None, functions=None, create_matrix=False, is_matrix=True): """ Update equations for current time step. The tangent matrix graph is automatically recomputed if the set of active essential or periodic boundary conditions changed w.r.t. the previous time step. Parameters ---------- ts : TimeStepper instance, optional The time stepper. If not given, `self.ts` is used. ebcs : Conditions instance, optional The essential (Dirichlet) boundary conditions. If not given, `self.ebcs` are used. epbcs : Conditions instance, optional The periodic boundary conditions. If not given, `self.epbcs` are used. lcbcs : Conditions instance, optional The linear combination boundary conditions. If not given, `self.lcbcs` are used. functions : Functions instance, optional The user functions for boundary conditions, materials, etc. If not given, `self.functions` are used. create_matrix : bool If True, force the matrix graph computation. is_matrix : bool If False, the matrix is not created. Has precedence over `create_matrix`. """ self.update_time_stepper(ts) functions = get_default(functions, self.functions) ac = self.active_only graph_changed = self.equations.time_update( self.ts, ebcs, epbcs, lcbcs, functions, self, active_only=ac, verbose=self.conf.get('verbose', True)) self.graph_changed = graph_changed if (is_matrix and ((self.active_only and graph_changed) or (self.mtx_a is None) or create_matrix)): self.mtx_a = self.equations.create_matrix_graph(active_only=ac)
## import sfepy.base.plotutils as plu ## plu.spy(self.mtx_a) ##
[docs] def set_bcs(self, ebcs=None, epbcs=None, lcbcs=None): """ Update boundary conditions. """ if isinstance(ebcs, Conditions): self.ebcs = ebcs else: conf_ebc = get_default(ebcs, self.conf.ebcs) self.ebcs = Conditions.from_conf(conf_ebc, self.domain.regions) conf_dgebc = self.conf.get("dgebcs", {}) self.ebcs.extend(Conditions.from_conf(conf_dgebc, self.domain.regions)) if isinstance(epbcs, Conditions): self.epbcs = epbcs else: conf_epbc = get_default(epbcs, self.conf.epbcs) self.epbcs = Conditions.from_conf(conf_epbc, self.domain.regions) conf_dgepbc = self.conf.get("dgepbcs", {}) self.ebcs.extend(Conditions.from_conf(conf_dgepbc, self.domain.regions)) if isinstance(lcbcs, Conditions): self.lcbcs = lcbcs else: conf_lcbc = get_default(lcbcs, self.conf.lcbcs) self.lcbcs = Conditions.from_conf(conf_lcbc, self.domain.regions)
[docs] def time_update(self, ts=None, ebcs=None, epbcs=None, lcbcs=None, functions=None, create_matrix=False, is_matrix=True): self.set_bcs(get_default(ebcs, self.ebcs), get_default(epbcs, self.epbcs), get_default(lcbcs, self.lcbcs)) self.update_equations(ts, self.ebcs, self.epbcs, self.lcbcs, functions, create_matrix, is_matrix)
[docs] def set_ics(self, ics=None): """ Set the initial conditions to use. """ if isinstance(ics, Conditions): self.ics = ics else: conf_ics = get_default(ics, self.conf.ics) self.ics = Conditions.from_conf(conf_ics, self.domain.regions)
[docs] def setup_ics(self, ics=None, functions=None): """ Setup the initial conditions for use. """ self.set_ics(get_default(ics, self.ics)) functions = get_default(functions, self.functions) self.equations.setup_initial_conditions(self.ics, functions)
[docs] def select_bcs(self, ebc_names=None, epbc_names=None, lcbc_names=None, create_matrix=False): if ebc_names is not None: conf_ebc = select_by_names(self.conf.ebcs, ebc_names) else: conf_ebc = None if epbc_names is not None: conf_epbc = select_by_names(self.conf.epbcs, epbc_names) else: conf_epbc = None if lcbc_names is not None: conf_lcbc = select_by_names(self.conf.lcbcs, lcbc_names) else: conf_lcbc = None self.set_bcs(conf_ebc, conf_epbc, conf_lcbc) self.update_equations(self.ts, self.ebcs, self.epbcs, self.lcbcs, self.functions, create_matrix)
[docs] def create_state(self): return State(self.equations.variables)
[docs] def get_mesh_coors(self, actual=False): return self.domain.get_mesh_coors(actual=actual)
[docs] def set_mesh_coors(self, coors, update_fields=False, actual=False, clear_all=True, extra_dofs=False): """ Set mesh coordinates. Parameters ---------- coors : array The new coordinates. update_fields : bool If True, update also coordinates of fields. actual : bool If True, update the actual configuration coordinates, otherwise the undeformed configuration ones. """ set_mesh_coors(self.domain, self.fields, coors, update_fields=update_fields, actual=actual, clear_all=clear_all, extra_dofs=extra_dofs)
[docs] def refine_uniformly(self, level): """ Refine the mesh uniformly `level`-times. Notes ----- This operation resets almost everything (fields, equations, ...) - it is roughly equivalent to creating a new Problem instance with the refined mesh. """ if level == 0: return domain = self.domain for ii in range(level): domain = domain.refine() self.domain = domain self.set_regions(self.conf.regions, self.functions) self.clear_equations() self.set_fields(self.conf.fields) self.set_equations(self.conf.equations, user={'ts' : self.ts})
[docs] def get_dim(self, get_sym=False): """Returns mesh dimension, symmetric tensor dimension (if `get_sym` is True). """ dim = self.domain.mesh.dim if get_sym: return dim, (dim + 1) * dim // 2 else: return dim
[docs] def init_time(self, ts): self.update_time_stepper(ts) self.equations.init_time(ts) self.update_materials(mode='force', verbose=self.conf.get('verbose', True)) self._restart_filenames = []
[docs] def advance(self, ts=None): self.update_time_stepper(ts) self.equations.advance(self.ts)
[docs] def save_state(self, filename, state=None, out=None, fill_value=None, post_process_hook=None, linearization=None, file_per_var=False, **kwargs): """ Parameters ---------- file_per_var : bool or None If True, data of each variable are stored in a separate file. If None, it is set to the application option value. linearization : Struct or None The linearization configuration for higher order approximations. If its kind is 'adaptive', `file_per_var` is assumed True. """ linearization = get_default(linearization, self.linearization) if linearization.kind != 'adaptive': file_per_var = get_default(file_per_var, self.file_per_var) else: file_per_var = True extend = not file_per_var if (out is None) and (state is not None): out = state.create_output_dict(fill_value=fill_value, extend=extend, linearization=linearization) if post_process_hook is not None: out = post_process_hook(out, self, state, extend=extend) if linearization.kind == 'adaptive': for key, val in six.iteritems(out): mesh = val.get('mesh', self.domain.mesh) aux = io.edit_filename(filename, suffix='_' + val.var_name) mesh.write(aux, io='auto', out={key : val}, float_format=self.float_format, **kwargs) if hasattr(val, 'levels'): output('max. refinement per group:', val.levels) elif file_per_var: meshes = {} if self.equations is None: varnames = {} for key, val in six.iteritems(out): varnames[val.var_name] = 1 varnames = list(varnames.keys()) outvars = self.create_variables(varnames) itervars = outvars.__iter__ else: itervars = self.equations.variables.iter_state for var in itervars(): rname = if rname in meshes: mesh = meshes[rname] else: mesh = Mesh.from_region(var.field.region, self.domain.mesh, localize=True, is_surface=var.is_surface) meshes[rname] = mesh vout = {} for key, val in six.iteritems(out): try: if val.var_name == vout[key] = val except AttributeError: msg = 'missing var_name attribute in output!' raise ValueError(msg) aux = io.edit_filename(filename, suffix='_' + mesh.write(aux, io='auto', out=vout, float_format=self.float_format, **kwargs) else: mesh = out.pop('__mesh__', self.domain.mesh) mesh.write(filename, io='auto', out=out, float_format=self.float_format, **kwargs)
[docs] def save_ebc(self, filename, ebcs=None, epbcs=None, force=True, default=0.0): """ Save essential boundary conditions as state variables. Parameters ---------- filename : str The output file name. ebcs : Conditions instance, optional The essential (Dirichlet) boundary conditions. If not given, `self.conf.ebcs` are used. epbcs : Conditions instance, optional The periodic boundary conditions. If not given, `self.conf.epbcs` are used. force : bool If True, sequential nonzero values are forced to individual `ebcs` so that the conditions are visible even when zero. default : float The default constant value of state vector. """ output('saving ebc...') variables = self.get_variables(auto_create=True) if ebcs is None: ebcs = Conditions.from_conf(self.conf.ebcs, self.domain.regions) if epbcs is None: 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(six.iterkeys(vals)): 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')
[docs] def save_regions(self, filename_trunk, region_names=None): """ Save regions as meshes. Parameters ---------- filename_trunk : str The output filename without suffix. region_names : list, optional If given, only the listed regions are saved. """ filename = '%s.mesh' % filename_trunk self.domain.save_regions(filename, region_names=region_names)
[docs] def save_regions_as_groups(self, filename_trunk, region_names=None): """ Save regions in a single mesh but mark them by using different element/node group numbers. See :func:`Domain.save_regions_as_groups() <sfepy.discrete.fem.domain.Domain.save_regions_as_groups()>` for more details. Parameters ---------- filename_trunk : str The output filename without suffix. region_names : list, optional If given, only the listed regions are saved. """ filename = '%s.%s' % (filename_trunk, self.output_format) self.domain.save_regions_as_groups(filename, region_names=region_names)
[docs] def save_field_meshes(self, filename_trunk): output('saving field meshes...') for field in self.fields: output( field.write_mesh(filename_trunk + '_%s') output('...done')
[docs] def get_evaluator(self, reuse=False): """ Either create a new Evaluator instance (reuse == False), or return an existing instance, created in a preceding call to Problem.init_solvers(). """ if reuse: try: ev = self.evaluator except AttributeError: raise AttributeError('call Problem.init_solvers() or'\ ' set reuse to False!') else: UserEvaluator = self.conf.options.get('user_evaluator', None) Eval = UserEvaluator if UserEvaluator is not None else Evaluator ev = self.evaluator = Eval(self, matrix_hook=self.matrix_hook) return ev
[docs] def get_ebc_indices(self): """ Get indices of E(P)BC-constrained DOFs in the full global state vector. """ variables = self.get_variables() ebc_indx = [] epbc_indx = [] for ii, variable in enumerate(variables.iter_state(ordered=True)): eq_map = variable.eq_map ebc_indx.append(eq_map.eq_ebc + variables.di.ptr[ii]) epbc_indx.append((eq_map.master + variables.di.ptr[ii], eq_map.slave + variables.di.ptr[ii])) ebc_indx = nm.concatenate(ebc_indx) epbc_indx = nm.concatenate(epbc_indx, axis=1) return ebc_indx, epbc_indx
[docs] def set_conf_solvers(self, conf_solvers=None, options=None): """ Choose which solvers should be used. If solvers are not set in `options`, use the ones named `ls`, `nls` or `ts`. If such solver names do not exist, use the first of each required solver kind listed in `conf_solvers`. """ conf_solvers = get_default(conf_solvers, self.conf.solvers) self.solver_confs = {} for key, val in six.iteritems(conf_solvers): self.solver_confs[] = val def _find_suitable(prefix): cands = [] for key, val in six.iteritems(self.solver_confs): if val.kind.find(prefix) == 0: if == prefix[:-1]: return val else: cands.append(val) if len(cands) > 0: return cands[0] else: return None def _get_solver_conf(kind): try: key = options[kind] if key is None: conf = None else: conf = self.solver_confs[key] except: conf = _find_suitable(kind + '.') return conf self.ts_conf = _get_solver_conf('ts') if self.ts_conf is None: self.ts_conf = Struct(name='no ts', kind='ts.stationary') self.nls_conf = _get_solver_conf('nls') self.ls_conf = _get_solver_conf('ls') info = 'using solvers:' if self.ts_conf: info += '\n ts: %s' % if self.nls_conf: info += '\n nls: %s' % if self.ls_conf: info += '\n ls: %s' % if info != 'using solvers:': output(info)
[docs] def get_solver_conf(self, name): return self.solver_confs[name]
[docs] def init_solvers(self, status=None, ls_conf=None, nls_conf=None, ts_conf=None, force=False): """ Create and initialize solver instances. Parameters ---------- status : dict-like, IndexedStruct, optional The user-supplied object to hold the time-stepping/nonlinear solver convergence statistics. ls_conf : Struct, optional The linear solver options. nls_conf : Struct, optional The nonlinear solver options. force : bool If True, re-create the solver instances even if they already exist in `self.nls` attribute. """ if (self.solver is None) or force: ls_conf = get_default(ls_conf, self.ls_conf, 'you must set linear solver!') nls_conf = get_default(nls_conf, self.nls_conf, 'you must set nonlinear solver!') fb_list = [] for ii in range(100): fb_list.append((ls_conf.kind, ls_conf)) if hasattr(ls_conf, 'fallback'): ls_conf = self.solver_confs[ls_conf.fallback] else: break if len(fb_list) > 1: ls = use_first_available(fb_list, context=self) else: ls = Solver.any_from_conf(ls_conf, context=self) ev = self.get_evaluator() if self.conf.options.get('ulf', False): self.nls_iter_hook = ev.new_ulf_iteration if status is None: status = IndexedStruct() status.set_default('nls_status', IndexedStruct()) nls = Solver.any_from_conf(nls_conf, fun=ev.eval_residual, fun_grad=ev.eval_tangent_matrix, lin_solver=ls, iter_hook=self.nls_iter_hook, status=status.nls_status, context=self) ts_conf = get_default(ts_conf, self.ts_conf) if ts_conf is None: self.set_solver(nls, status=status) else: tss = Solver.any_from_conf(ts_conf, nls=nls, context=self, status=status) self.set_solver(tss)
[docs] def get_default_ts(self, t0=None, t1=None, dt=None, n_step=None, step=None): t0 = get_default(t0, 0.0) t1 = get_default(t1, 1.0) dt = get_default(dt, 1.0) n_step = get_default(n_step, 1) ts = TimeStepper(t0, t1, dt, n_step, step=step) return ts
[docs] def update_time_stepper(self, ts): if ts is not None: self.ts = ts
[docs] def get_timestepper(self): return self.ts
[docs] def set_solver(self, solver, status=None): """ Set a time-stepping or nonlinear solver to be used in :func:`Problem.solve()` call. Parameters ---------- solver : NonlinearSolver or TimeSteppingSolver instance The nonlinear or time-stepping solver. Notes ----- A copy of the solver is used, and the nonlinear solver functions are set to those returned by :func:`Problem.get_nls_functions()`, if not set already. If a nonlinear solver is set, a default StationarySolver instance is created automatically as the time-stepping solver. Also sets `self.ts` attribute. """ if isinstance(solver, NonlinearSolver): solver = StationarySolver({}, nls=solver.copy(), ts=self.get_default_ts(), status=status) self.solver = solver.copy() self.ts = solver.ts self.status = get_default(solver.status, IndexedStruct()) # Assign the nonlinear solver functions. nls = self.get_nls() if is None: fun, fun_grag, iter_hook = self.get_nls_functions() = fun nls.fun_grad = fun_grag nls.iter_hook = iter_hook
[docs] def try_presolve(self, mtx): ls = self.get_ls() timer = Timer(start=True) ls.presolve(mtx) tt = timer.stop() output('presolve: %.2f [s]' % tt)
[docs] def get_solver(self): return self.get_tss()
[docs] def get_tss(self): tss = get_default(None, self.solver, 'solver is not set!') return tss
[docs] def get_tss_functions(self, state0, update_bcs=True, update_materials=True, save_results=True, step_hook=None, post_process_hook=None): """ Get the problem-dependent functions required by the time-stepping solver during the solution process. Parameters ---------- state0 : State The state holding the problem variables. update_bcs : bool, optional If True, update the boundary conditions in each `prestep_fun` call. update_materials : bool, optional If True, update the values of material parameters in each `prestep_fun` call. save_results : bool, optional If True, save the results in each `poststep_fun` call. step_hook : callable, optional The optional user-defined function that is called in each `poststep_fun` call before saving the results. post_process_hook : callable, optional The optional user-defined function that is passed in each `poststep_fun` to :func:`Problem.save_state()`. Returns ------- init_fun : callable The initialization function called before the actual time-stepping. prestep_fun : callable The function called in each time (sub-)step prior to the nonlinear solver call. poststep_fun : callable The function called at the end of each time step. """ is_save = make_is_save(self.conf.options) def init_fun(ts, vec0): if not ts.is_quasistatic: self.init_time(ts) is_save.reset(ts) restart_filename = self.conf.options.get('load_restart', None) if restart_filename is not None: self.load_restart(restart_filename, state=state0, ts=ts) self.advance(ts) ts.advance() state = self.create_state() vec0 = state.get_vec(self.active_only) return vec0 def prestep_fun(ts, vec): if update_bcs: self.time_update(ts) state = state0.copy() state.set_vec(vec, self.active_only) state.apply_ebc() if update_materials: self.update_materials(verbose=self.conf.get('verbose', True)) def poststep_fun(ts, vec): state = state0.copy(preserve_caches=True) state.set_vec(vec, self.active_only) if step_hook is not None: step_hook(self, ts, state) restart_filename = self.get_restart_filename(ts=ts) if restart_filename is not None: self.save_restart(restart_filename, state, ts=ts) if save_results and is_save(ts): if not isinstance(self.get_solver(), StationarySolver): suffix = ts.suffix % ts.step else: suffix = None filename = self.get_output_name(suffix=suffix) self.save_state(filename, state, post_process_hook=post_process_hook, file_per_var=None, ts=ts, file_format=self.file_format) self.advance(ts) return init_fun, prestep_fun, poststep_fun
[docs] def get_nls_functions(self): """ Returns functions to be used by a nonlinear solver to evaluate the nonlinear function value (the residual) and its gradient (the tangent matrix) corresponding to the problem equations. Returns ------- fun : function The function ``fun(x)`` for computing the residual. fun_grad : function The function ``fun_grad(x)`` for computing the tangent matrix. iter_hook : function The optional (user-defined) function to be called before each nonlinear solver iteration iteration. """ ev = self.get_evaluator() return ev.eval_residual, ev.eval_tangent_matrix, self.nls_iter_hook
[docs] def get_nls(self): tss = self.get_tss() return tss.nls
[docs] def get_ls(self): nls = self.get_nls() return nls.lin_solver
[docs] def is_linear(self): nls = self.get_nls() return nls.conf.get('is_linear', False)
[docs] def set_linear(self, is_linear): nls = self.get_nls() nls.conf.is_linear = is_linear
[docs] def get_initial_state(self): """ Create a zero state vector and apply initial conditions. """ state = self.create_state() self.setup_ics() state.apply_ic() # Initialize variables with history. state.init_history() return state
[docs] def solve(self, state0=None, status=None, force_values=None, var_data=None, update_bcs=True, update_materials=True, save_results=True, step_hook=None, post_process_hook=None, post_process_hook_final=None, verbose=True): """ Solve the problem equations by calling the top-level solver. Before calling this function the top-level solver has to be set, see :func:`Problem.set_solver()`. Also, the boundary conditions and the initial conditions (for time-dependent problems) has to be set, see :func:`Problem.set_bcs()`, :func:`Problem.set_ics()`. Parameters ---------- state0 : State or array, optional If given, the initial state satisfying the initial conditions. By default, it is created and the initial conditions are applied automatically. status : dict-like, optional The user-supplied object to hold the solver convergence statistics. force_values : dict of floats or float, optional If given, the supplied values override the values of the essential boundary conditions. var_data : dict, optional A dictionary of {variable_name : data vector} used to initialize parameter variables. update_bcs : bool, optional If True, update the boundary conditions in each `prestep_fun` call. See :func:`Problem.get_tss_functions()`. update_materials : bool, optional If True, update the values of material parameters in each `prestep_fun` call. See :func:`Problem.get_tss_functions()`. save_results : bool, optional If True, save the results in each `poststep_fun` call. See :func:`Problem.get_tss_functions()`. step_hook : callable, optional The optional user-defined function that is called in each `poststep_fun` call before saving the results. See :func:`Problem.get_tss_functions()`. post_process_hook : callable, optional The optional user-defined function that is passed in each `poststep_fun` to :func:`Problem.save_state()`. See :func:`Problem.get_tss_functions()`. post_process_hook_final : callable, optional The optional user-defined function that is called after the top-level solver returns. Returns ------- state : State The final state. """ if status is None: status = IndexedStruct() if self.solver is None: self.init_solvers(status=status) tss = self.get_solver() self.equations.set_data(var_data, ignore_unknown=True) if state0 is None: state0 = self.get_initial_state() else: if isinstance(state0, nm.ndarray): state0 = State(self.equations.variables, vec=state0) if self.conf.options.get('block_solve', False): state = self.block_solve(state0, status=status, save_results=save_results, step_hook=step_hook, post_process_hook=post_process_hook, verbose=verbose) else: self.time_update(tss.ts) # Only having adi is required here(?) state0.apply_ebc(force_values=force_values) if self.is_linear(): mtx = prepare_matrix(self, state0) self.try_presolve(mtx) init_fun, prestep_fun, poststep_fun = self.get_tss_functions( state0, update_bcs=update_bcs, update_materials=update_materials, save_results=save_results, step_hook=step_hook, post_process_hook=post_process_hook) vec = tss(state0.get_vec(self.active_only), init_fun=init_fun, prestep_fun=prestep_fun, poststep_fun=poststep_fun, status=status) output('solved in %d steps in %.2f seconds' % (status['n_step'], status['time']), verbose=verbose) state = state0.copy() state.set_vec(vec, self.active_only) if post_process_hook_final is not None: # User postprocessing. post_process_hook_final(self, state) return state
[docs] def block_solve(self, state0=None, status=None, save_results=True, step_hook=None, post_process_hook=None, verbose=True): """ Call :func:`Problem.solve()` sequentially for the individual matrix blocks of a block-triangular matrix. It is called by :func:`Problem.solve()` if the `'block_solve'` option is set to True. """ from sfepy.base.base import invert_dict, get_subdict from sfepy.base.resolve_deps import resolve if not isinstance(self.get_solver(), StationarySolver): msg = 'The block solve can be used only for stationary problems!' raise ValueError(msg) def replace_virtuals(deps, pairs): out = {} for key, val in six.iteritems(deps): out[pairs[key]] = val return out if state0 is None: state0 = self.get_initial_state() variables = self.get_variables() vtos = variables.get_dual_names() vdeps = self.equations.get_variable_dependencies() sdeps = replace_virtuals(vdeps, vtos) sorder = resolve(sdeps) stov = invert_dict(vtos) vorder = [[stov[ii] for ii in block] for block in sorder] parts0 = state0.get_parts() state = state0.copy() solved = [] for ib, block in enumerate(vorder): output('solving for %s...' % sorder[ib], verbose=verbose) subpb = self.create_subproblem(block, solved) subpb.conf.options.block_solve = False subpb.equations.print_terms() substate0 = subpb.create_state() vals = get_subdict(parts0, block) substate0.set_parts(vals) substate = subpb.solve(state0=substate0, status=status, save_results=False, step_hook=step_hook, post_process_hook=post_process_hook, verbose=verbose) state.set_parts(substate.get_parts()) solved.extend(sorder[ib]) output('...done', verbose=verbose) if step_hook is not None: step_hook(self, None, state) if save_results: self.save_state(self.get_output_name(), state, post_process_hook=post_process_hook, file_per_var=None) return state
[docs] def create_evaluable(self, expression, try_equations=True, auto_init=False, preserve_caches=False, copy_materials=True, integrals=None, ebcs=None, epbcs=None, lcbcs=None, ts=None, functions=None, mode='eval', var_dict=None, strip_variables=True, extra_args=None, active_only=True, verbose=True, **kwargs): """ Create evaluable object (equations and corresponding variables) from the `expression` string. Convenience function calling :func:`create_evaluable() <sfepy.discrete.evaluate.create_evaluable()>` with defaults provided by the Problem instance `self`. The evaluable can be repeatedly evaluated by calling :func:`eval_equations() <sfepy.discrete.evaluate.eval_equations()>`, e.g. for different values of variables. Parameters ---------- expression : str The expression to evaluate. try_equations : bool Try to get variables from `self.equations`. If this fails, variables can either be provided in `var_dict`, as keyword arguments, or are created automatically according to the expression. auto_init : bool Set values of all variables to all zeros. preserve_caches : bool If True, do not invalidate evaluate caches of variables. copy_materials : bool Work with a copy of `self.equations.materials` instead of reusing them. Safe but can be slow. integrals : Integrals instance, optional The integrals to be used. Automatically created as needed if not given. ebcs : Conditions instance, optional The essential (Dirichlet) boundary conditions for 'weak' mode. If not given, `self.ebcs` are used. epbcs : Conditions instance, optional The periodic boundary conditions for 'weak' mode. If not given, `self.epbcs` are used. lcbcs : Conditions instance, optional The linear combination boundary conditions for 'weak' mode. If not given, `self.lcbcs` are used. ts : TimeStepper instance, optional The time stepper. If not given, `self.ts` is used. functions : Functions instance, optional The user functions for boundary conditions, materials etc. If not given, `self.functions` are used. mode : one of 'eval', 'el_avg', 'qp', 'weak' The evaluation mode - 'weak' means the finite element assembling, 'qp' requests the values in quadrature points, 'el_avg' element averages and 'eval' means integration over each term region. var_dict : dict, optional The variables (dictionary of (variable name) : (Variable instance)) to be used in the expression. Use this if the name of a variable conflicts with one of the parameters of this method. strip_variables : bool If False, the variables in `var_dict` or `kwargs` not present in the expression are added to the actual variables as a context. extra_args : dict, optional Extra arguments to be passed to terms in the expression. active_only : bool If True, in 'weak' mode, the (tangent) matrices and residual vectors (right-hand sides) contain only active DOFs. verbose : bool If False, reduce verbosity. **kwargs : keyword arguments Additional variables can be passed as keyword arguments, see `var_dict`. Returns ------- equations : Equations instance The equations that can be evaluated. variables : Variables instance The corresponding variables. Set their values and use :func:`eval_equations() <sfepy.discrete.evaluate.eval_equations()>`. Examples -------- `problem` is Problem instance. >>> out = problem.create_evaluable('ev_volume_integrate.i1.Omega(u)') >>> equations, variables = out `vec` is a vector of coefficients compatible with the field of 'u' - let's use all ones. >>> vec = nm.ones((variables['u'].n_dof,), dtype=nm.float64) >>> variables['u'].set_data(vec) >>> vec_qp = eval_equations(equations, variables, mode='qp') Try another vector: >>> vec = 3 * nm.ones((variables['u'].n_dof,), dtype=nm.float64) >>> variables['u'].set_data(vec) >>> vec_qp = eval_equations(equations, variables, mode='qp') """ from sfepy.discrete.equations import get_expression_arg_names variables = Variables(six.itervalues(get_default(var_dict, {}))) var_context = get_default(var_dict, {}) if try_equations and self.equations is not None: # Make a copy, so that possible variable caches are preserved. for key, var in six.iteritems(self.equations.variables.as_dict()): if key in variables: continue var = var.copy(name=key) if not preserve_caches: var.clear_evaluate_cache() variables[key] = var elif var_dict is None: possible_var_names = get_expression_arg_names(expression) variables = self.create_variables(possible_var_names) materials = self.get_materials() if copy_materials or (materials is None): possible_mat_names = get_expression_arg_names(expression) materials = self.create_materials(possible_mat_names) else: materials = Materials(objs=materials._objs) _kwargs = copy(kwargs) for key, val in six.iteritems(kwargs): if isinstance(val, Variable): if != key: msg = 'inconsistent variable name! (%s == %s)' \ % (, key) raise ValueError(msg) var_context[key] = variables[key] = val.copy(name=key) _kwargs.pop(key) elif isinstance(val, Material): if != key: msg = 'inconsistent material name! (%s == %s)' \ % (, key) raise ValueError(msg) materials[] = val _kwargs.pop(key) kwargs = _kwargs ebcs = get_default(ebcs, self.ebcs) epbcs = get_default(epbcs, self.epbcs) lcbcs = get_default(lcbcs, self.lcbcs) ts = get_default(ts, self.get_timestepper()) functions = get_default(functions, self.functions) integrals = get_default(integrals, self.get_integrals()) out = create_evaluable(expression, self.fields, materials, variables, integrals, ebcs=ebcs, epbcs=epbcs, lcbcs=lcbcs, ts=ts, functions=functions, auto_init=auto_init, mode=mode, extra_args=extra_args, active_only=active_only, verbose=verbose, kwargs=kwargs) if not strip_variables: variables = out[1] variables.extend([var for var in six.itervalues(var_context) if var not in variables]) equations = out[0] mode = 'update' if not copy_materials else 'normal' equations.time_update_materials(self.ts, mode=mode, problem=self, verbose=verbose) return out
[docs] def evaluate(self, expression, try_equations=True, auto_init=False, preserve_caches=False, copy_materials=True, integrals=None, ebcs=None, epbcs=None, lcbcs=None, ts=None, functions=None, mode='eval', dw_mode='vector', term_mode=None, var_dict=None, strip_variables=True, ret_variables=False, active_only=True, verbose=True, extra_args=None, **kwargs): """ Evaluate an expression, convenience wrapper of :func:`Problem.create_evaluable` and :func:`eval_equations() <sfepy.discrete.evaluate.eval_equations>`. Parameters ---------- dw_mode : 'vector' or 'matrix' The assembling mode for 'weak' evaluation mode. term_mode : str The term call mode - some terms support different call modes and depending on the call mode different values are returned. ret_variables : bool If True, return the variables that were created to evaluate the expression. other : arguments See docstrings of :func:`Problem.create_evaluable()`. Returns ------- out : array The result of the evaluation. variables : Variables instance The variables that were created to evaluate the expression. Only provided if `ret_variables` is True. """ aux = self.create_evaluable(expression, try_equations=try_equations, auto_init=auto_init, preserve_caches=preserve_caches, copy_materials=copy_materials, integrals=integrals, ebcs=ebcs, epbcs=epbcs, lcbcs=lcbcs, ts=ts, functions=functions, mode=mode, var_dict=var_dict, strip_variables=strip_variables, extra_args=extra_args, active_only=active_only, verbose=verbose, **kwargs) equations, variables = aux out = eval_equations(equations, variables, preserve_caches=preserve_caches, mode=mode, dw_mode=dw_mode, term_mode=term_mode, active_only=active_only, verbose=verbose) if ret_variables: out = (out, variables) return out
[docs] def eval_equations(self, names=None, preserve_caches=False, mode='eval', dw_mode='vector', term_mode=None, active_only=True, verbose=True): """ Evaluate (some of) the problem's equations, convenience wrapper of :func:`eval_equations() <sfepy.discrete.evaluate.eval_equations>`. Parameters ---------- names : str or sequence of str, optional Evaluate only equations of the given name(s). preserve_caches : bool If True, do not invalidate evaluate caches of variables. mode : one of 'eval', 'el_avg', 'qp', 'weak' The evaluation mode - 'weak' means the finite element assembling, 'qp' requests the values in quadrature points, 'el_avg' element averages and 'eval' means integration over each term region. dw_mode : 'vector' or 'matrix' The assembling mode for 'weak' evaluation mode. term_mode : str The term call mode - some terms support different call modes and depending on the call mode different values are returned. verbose : bool If False, reduce verbosity. Returns ------- out : dict or result The evaluation result. In 'weak' mode it is the vector or sparse matrix, depending on `dw_mode`. Otherwise, it is a dict of results with equation names as keys or a single result for a single equation. """ return eval_equations(self.equations, self.equations.variables, names=names, preserve_caches=preserve_caches, mode=mode, dw_mode=dw_mode, term_mode=term_mode, active_only=active_only, verbose=verbose)
[docs] def get_materials(self): if self.equations is not None: materials = self.equations.materials else: materials = None return materials
[docs] def create_materials(self, mat_names=None): """ Create materials with names in `mat_names`. Their definitions have to be present in `self.conf.materials`. Notes ----- This method does not change `self.equations`, so it should not have any side effects. """ if mat_names is not None: conf_materials = self.select_materials(mat_names, only_conf=True) else: conf_materials = self.conf.materials materials = Materials.from_conf(conf_materials, self.functions) return materials
[docs] def get_variables(self, auto_create=False): if self.equations is not None: variables = self.equations.variables elif auto_create: variables = self.create_variables() else: variables = None return variables
[docs] def create_variables(self, var_names=None): """ Create variables with names in `var_names`. Their definitions have to be present in `self.conf.variables`. Notes ----- This method does not change `self.equations`, so it should not have any side effects. """ if var_names is not None: conf_variables = self.select_variables(var_names, only_conf=True) else: conf_variables = self.conf.variables variables = Variables.from_conf(conf_variables, self.fields) return variables
[docs] def get_output_name(self, suffix=None, extra=None, mode=None): """ Return default output file name, based on the output directory, output format, step suffix and mode. If present, the extra string is put just before the output format suffix. """ out = op.join(self.output_dir, self.ofn_trunk) if suffix is not None: if mode is None: mode = self.output_modes[self.output_format] if mode == 'sequence': out = '.'.join((out, suffix)) if extra is not None: out = '.'.join((out, extra, self.output_format)) else: out = '.'.join((out, self.output_format)) return out
[docs] def remove_bcs(self): """ Convenience function to remove boundary conditions. """ self.time_update(ebcs={}, epbcs={}, lcbcs={})
[docs] def get_restart_filename(self, ts=None): """ If restarts are allowed in problem definition options, return the restart file name, based on the output directory and time step. """ if self.conf.options.get('save_restart', None) is None: return suffix = 'restart' if ts is not None: suffix += '-' + ts.suffix % ts.step aux = self.get_output_name(extra=suffix) iext = len(aux) - len('.' + self.output_format) restart_filename = aux[:iext] + '.h5' return restart_filename
[docs] def save_restart(self, filename, state=None, ts=None): """ Save the current state and time step to a restart file. Parameters ---------- filename : str The restart file name. state : State instance, optional The state instance. If not given, a new state is created using the variables in problem equations. ts : TimeStepper instance, optional The time stepper. If not given, a default one is created. Notes ----- Does not support terms with internal state. """ import tables as pt if state is None: state = self.create_state() if ts is None: ts = self.get_default_ts() fd = pt.open_file(filename, mode='w', title='SfePy restart file') tgroup = fd.create_group('/', 'ts', 'ts') for key, val in six.iteritems(ts.get_state()): fd.create_array(tgroup, key, val, key) if state.r_vec is not None: fd.create_array('/', 'r_vec', state.r_vec, 'reduced state vector') variables = state.variables for var in variables.iter_state(): vgroup = fd.create_group('/',, history_length = len( fd.create_array(vgroup, 'history_length', history_length, 'history length') for ii in range(history_length): data = var(step=-ii) fd.create_array(vgroup, 'data_%d' % ii, data, 'data') fd.close() mode = self.conf.options.get('save_restart', None) if (mode == -1) and len(self._restart_filenames): last_filename = self._restart_filenames.pop() try: os.remove(last_filename) except OSError: pass self._restart_filenames.append(filename)
[docs] def load_restart(self, filename, state=None, ts=None): """ Load the current state and time step from a restart file. Alternatively, a regular output file in the HDF5 format can be used in place of the restart file. In that case the restart is only approximate, because higher order field DOFs (if any) were stripped out. Files with the adaptive linearization are not supported. Use with caution! Parameters ---------- filename : str The restart file name. state : State instance, optional The state instance. If not given, a new state is created using the variables in problem equations. Otherwise, its variables are modified in place. ts : TimeStepper instance, optional The time stepper. If not given, a default one is created. Otherwise, it is modified in place. Returns ------- new_state : State instance The loaded state. """ import tables as pt if state is None: state = self.create_state() if ts is None: ts = self.get_default_ts() variables = state.variables output('loading restart file "%s"...' % filename) fd = pt.open_file(filename, mode='r') if fd.title == 'SfePy restart file': ts_state = {} for val in fd.root.ts._f_walknodes(): ts_state[] = ts.set_state(**ts_state) for var in variables.iter_state(): vgroup = fd.root._f_get_child( history_length = for ii in range(0, history_length): data = vgroup._f_get_child('data_%d' % ii).read() var.set_data(data, step=-ii) new_state = State.from_variables(variables) if '/r_vec' in fd: r_vec = state.r_vec = r_vec fd.close() elif fd.title == 'SfePy output file': from sfepy.discrete.fem.meshio import MeshIO output('WARNING: using a SfePy output file in place of a restart' ' file discards higher order DOFs! Use with caution!') fd.close() io = MeshIO.any_from_filename(filename) out = io.read_data(step=ts.step) for var in variables.iter_state(): val = out[] var.set_from_mesh_vertices( new_state = State.from_variables(variables) else: raise IOError('unknown file type! ("%s" in ("%s", "%s"))' % (fd.title, 'SfePy restart file', 'SfePy output file')) output('...done') return new_state