def save_eigenvectors(filename, svecs, wmag, wdir, pb):
if svecs is None: return
variables = pb.get_variables()
# Make full eigenvectors (add DOFs fixed by boundary conditions).
vecs = nm.empty((variables.di.ptr[-1], svecs.shape[1]),
dtype=svecs.dtype)
for ii in range(svecs.shape[1]):
vecs[:, ii] = variables.make_full_vec(svecs[:, ii])
# Save the eigenvectors.
out = {}
state = pb.create_state()
pp_name = pb.conf.options.get('post_process_hook')
pp = getattr(pb.conf.funmod, pp_name if pp_name is not None else '',
lambda out, *args, **kwargs: out)
for ii in range(svecs.shape[1]):
state.set_full(vecs[:, ii])
aux = state.create_output_dict()
aux2 = {}
pp(aux2, pb, state, wmag=wmag, wdir=wdir)
aux.update(convert_complex_output(aux2))
out.update({key + '%03d' % ii : aux[key] for key in aux})
pb.save_state(filename, out=out)
def save_eigenvectors(filename, svecs, wmag, wdir, pb):
if svecs is None: return
variables = pb.get_variables()
# Make full eigenvectors (add DOFs fixed by boundary conditions).
vecs = nm.empty((variables.di.ptr[-1], svecs.shape[1]),
dtype=svecs.dtype)
for ii in range(svecs.shape[1]):
vecs[:, ii] = variables.make_full_vec(svecs[:, ii])
# Save the eigenvectors.
out = {}
state = pb.create_state()
pp_name = pb.conf.options.get('post_process_hook')
pp = getattr(pb.conf.funmod, pp_name if pp_name is not None else '',
lambda out, *args, **kwargs: out)
for ii in range(svecs.shape[1]):
state.set_full(vecs[:, ii])
aux = state.create_output_dict()
aux2 = {}
pp(aux2, pb, state, wmag=wmag, wdir=wdir)
aux.update(convert_complex_output(aux2))
out.update({key + '%03d' % ii : aux[key] for key in aux})
pb.save_state(filename, out=out)
def save_results(self,
eigs,
vecs,
out=None,
mesh_results_name=None,
eig_results_name=None):
if vecs is not None:
mesh_results_name = get_default(mesh_results_name,
self.mesh_results_name)
pb = self.problem
pp_name = pb.conf.options.get('post_process_hook')
pp = getattr(pb.conf.funmod,
pp_name if pp_name is not None else '',
lambda out, *args, **kwargs: out)
out = get_default(out, {})
state = pb.create_state()
for ii in range(eigs.shape[0]):
state.set_full(vecs[:, ii])
aux = state.create_output_dict()
aux2 = {}
pp(aux2, pb, state)
aux.update(convert_complex_output(aux2))
out.update({key + '%03d' % ii: aux[key] for key in aux})
if aux.get('__mesh__') is not None:
out['__mesh__'] = aux['__mesh__']
pb.save_state(mesh_results_name, out=out)
output('solution saved to %s' % mesh_results_name)
eig_results_name = get_default(eig_results_name, self.eig_results_name)
with open(eig_results_name, 'w') as fd:
if nm.iscomplexobj(eigs):
nm.savetxt(fd, eigs, '% .18e % .18e')
else:
nm.savetxt(fd, eigs, '% .18e')
output('eigenvalues saved to %s' % eig_results_name)
def save_results(self, eigs, vecs, out=None,
mesh_results_name=None, eig_results_name=None):
if vecs is not None:
mesh_results_name = get_default(mesh_results_name,
self.mesh_results_name)
pb = self.problem
pp_name = pb.conf.options.get('post_process_hook')
pp = getattr(pb.conf.funmod,
pp_name if pp_name is not None else '',
lambda out, *args, **kwargs: out)
out = get_default(out, {})
state = pb.create_state()
for ii in range(eigs.shape[0]):
state.set_full(vecs[:, ii])
aux = state.create_output_dict()
aux2 = {}
pp(aux2, pb, state)
aux.update(convert_complex_output(aux2))
out.update({key + '%03d' % ii : aux[key] for key in aux})
if aux.get('__mesh__') is not None:
out['__mesh__'] = aux['__mesh__']
pb.save_state(mesh_results_name, out=out)
output('solution saved to %s' % mesh_results_name)
eig_results_name = get_default(eig_results_name,
self.eig_results_name)
with open(eig_results_name, 'w') as fd:
if nm.iscomplexobj(eigs):
nm.savetxt(fd, eigs, '% .18e % .18e')
else:
nm.savetxt(fd, eigs, '% .18e')
output('eigenvalues saved to %s' % eig_results_name)
def create_output(self, dofs, var_name, dof_names=None,
key=None, extend=True, fill_value=None,
linearization=None):
"""
Convert the DOFs corresponding to the field to a dictionary of
output data usable by Mesh.write().
Parameters
----------
dofs : array, shape (n_nod, n_component)
The array of DOFs reshaped so that each column corresponds
to one component.
var_name : str
The variable name corresponding to `dofs`.
dof_names : tuple of str
The names of DOF components.
key : str, optional
The key to be used in the output dictionary instead of the
variable name.
extend : bool
Extend the DOF values to cover the whole domain.
fill_value : float or complex
The value used to fill the missing DOF values if `extend` is True.
linearization : Struct or None
The linearization configuration for higher order approximations.
Returns
-------
out : dict
The output dictionary.
"""
linearization = get_default(linearization, Struct(kind='strip'))
out = {}
if linearization.kind is None:
out[key] = Struct(name='output_data', mode='full',
data=dofs, var_name=var_name,
dofs=dof_names, field_name=self.name)
elif ((not self.is_higher_order())
or (linearization.kind == 'strip')):
if extend:
ext = self.extend_dofs(dofs, fill_value)
else:
ext = self.remove_extra_dofs(dofs)
if ext is not None:
approx_order = self.get_output_approx_order()
if approx_order != 0:
# Has vertex data.
out[key] = Struct(name='output_data', mode='vertex',
data=ext, var_name=var_name,
dofs=dof_names)
else:
ext.shape = (ext.shape[0], 1, ext.shape[1], 1)
out[key] = Struct(name='output_data', mode='cell',
data=ext, var_name=var_name,
dofs=dof_names)
else:
mesh, vdofs, levels = self.linearize(dofs,
linearization.min_level,
linearization.max_level,
linearization.eps)
out[key] = Struct(name='output_data', mode='vertex',
data=vdofs, var_name=var_name, dofs=dof_names,
mesh=mesh, levels=levels)
out = convert_complex_output(out)
return out
def create_expression_output(expression, name, primary_field_name,
fields, materials, variables,
functions=None, mode='eval', term_mode=None,
extra_args=None, verbose=True, kwargs=None,
min_level=0, max_level=1, eps=1e-4):
"""
Create output mesh and data for the expression using the adaptive
linearizer.
Parameters
----------
expression : str
The expression to evaluate.
name : str
The name of the data.
primary_field_name : str
The name of field that defines the element groups and polynomial
spaces.
fields : dict
The dictionary of fields used in `variables`.
materials : Materials instance
The materials used in the expression.
variables : Variables instance
The variables used in the expression.
functions : Functions instance, optional
The user functions for materials etc.
mode : one of 'eval', 'el_avg', 'qp'
The evaluation mode - 'qp' requests the values in quadrature points,
'el_avg' element averages and 'eval' means integration over
each term region.
term_mode : str
The term call mode - some terms support different call modes
and depending on the call mode different values are
returned.
extra_args : dict, optional
Extra arguments to be passed to terms in the expression.
verbose : bool
If False, reduce verbosity.
kwargs : dict, optional
The variables (dictionary of (variable name) : (Variable
instance)) to be used in the expression.
min_level : int
The minimum required level of mesh refinement.
max_level : int
The maximum level of mesh refinement.
eps : float
The relative tolerance parameter of mesh adaptivity.
Returns
-------
out : dict
The output dictionary.
"""
field = fields[primary_field_name]
vertex_coors = field.coors[:field.n_vertex_dof, :]
coors = []
vdofs = []
conns = []
mat_ids = []
levels = []
offset = 0
for ig, ap in field.aps.iteritems():
ps = ap.interp.poly_spaces['v']
gps = ap.interp.gel.interp.poly_spaces['v']
group = field.domain.groups[ig]
vertex_conn = ap.econn[:, :group.shape.n_ep]
eval_dofs = get_eval_expression(expression, ig,
fields, materials, variables,
functions=functions,
mode=mode, extra_args=extra_args,
verbose=verbose, kwargs=kwargs)
eval_coors = get_eval_coors(vertex_coors, vertex_conn, gps)
(level, _coors, conn,
_vdofs, _mat_ids) = create_output(eval_dofs, eval_coors,
group.shape.n_el, ps,
min_level=min_level,
max_level=max_level, eps=eps)
_mat_ids[:] = field.domain.mesh.mat_ids[ig][0]
coors.append(_coors)
vdofs.append(_vdofs)
conns.append(conn + offset)
mat_ids.append(_mat_ids)
levels.append(level)
offset += _coors.shape[0]
coors = nm.concatenate(coors, axis=0)
vdofs = nm.concatenate(vdofs, axis=0)
mesh = Mesh.from_data('linearized_mesh', coors, None, conns, mat_ids,
field.domain.mesh.descs)
out = {}
out[name] = Struct(name='output_data', mode='vertex',
data=vdofs, var_name=name, dofs=None,
mesh=mesh, levels=levels)
out = convert_complex_output(out)
return out
def create_output(self, dofs, var_name, dof_names=None,
key=None, extend=True, fill_value=None,
linearization=None):
"""
Convert the DOFs corresponding to the field to a dictionary of
output data usable by Mesh.write().
Parameters
----------
dofs : array, shape (n_nod, n_component)
The array of DOFs reshaped so that each column corresponds
to one component.
var_name : str
The variable name corresponding to `dofs`.
dof_names : tuple of str
The names of DOF components.
key : str, optional
The key to be used in the output dictionary instead of the
variable name.
extend : bool
Extend the DOF values to cover the whole domain.
fill_value : float or complex
The value used to fill the missing DOF values if `extend` is True.
linearization : Struct or None
The linearization configuration for higher order approximations.
Returns
-------
out : dict
The output dictionary.
"""
linearization = get_default(linearization, Struct(kind='strip'))
out = {}
if linearization.kind is None:
out[key] = Struct(name='output_data', mode='full',
data=dofs, var_name=var_name,
dofs=dof_names, field_name=self.name)
elif linearization.kind == 'strip':
if extend:
ext = self.extend_dofs(dofs, fill_value)
else:
ext = self.remove_extra_dofs(dofs)
if ext is not None:
approx_order = self.get_output_approx_order()
if approx_order != 0:
# Has vertex data.
out[key] = Struct(name='output_data', mode='vertex',
data=ext, var_name=var_name,
dofs=dof_names)
else:
ext.shape = (ext.shape[0], 1, ext.shape[1], 1)
out[key] = Struct(name='output_data', mode='cell',
data=ext, var_name=var_name,
dofs=dof_names)
else:
mesh, vdofs, levels = self.linearize(dofs,
linearization.min_level,
linearization.max_level,
linearization.eps)
out[key] = Struct(name='output_data', mode='vertex',
data=vdofs, var_name=var_name, dofs=dof_names,
mesh=mesh, levels=levels)
out = convert_complex_output(out)
return out
def create_expression_output(expression, name, primary_field_name,
fields, materials, variables,
functions=None, mode='eval', term_mode=None,
extra_args=None, verbose=True, kwargs=None,
min_level=0, max_level=1, eps=1e-4):
"""
Create output mesh and data for the expression using the adaptive
linearizer.
Parameters
----------
expression : str
The expression to evaluate.
name : str
The name of the data.
primary_field_name : str
The name of field that defines the element groups and polynomial
spaces.
fields : dict
The dictionary of fields used in `variables`.
materials : Materials instance
The materials used in the expression.
variables : Variables instance
The variables used in the expression.
functions : Functions instance, optional
The user functions for materials etc.
mode : one of 'eval', 'el_avg', 'qp'
The evaluation mode - 'qp' requests the values in quadrature points,
'el_avg' element averages and 'eval' means integration over
each term region.
term_mode : str
The term call mode - some terms support different call modes
and depending on the call mode different values are
returned.
extra_args : dict, optional
Extra arguments to be passed to terms in the expression.
verbose : bool
If False, reduce verbosity.
kwargs : dict, optional
The variables (dictionary of (variable name) : (Variable
instance)) to be used in the expression.
min_level : int
The minimum required level of mesh refinement.
max_level : int
The maximum level of mesh refinement.
eps : float
The relative tolerance parameter of mesh adaptivity.
Returns
-------
out : dict
The output dictionary.
"""
field = fields[primary_field_name]
vertex_coors = field.coors[:field.n_vertex_dof, :]
ps = field.poly_space
gps = field.gel.poly_space
vertex_conn = field.econn[:, :field.gel.n_vertex]
eval_dofs = get_eval_expression(expression,
fields, materials, variables,
functions=functions,
mode=mode, extra_args=extra_args,
verbose=verbose, kwargs=kwargs)
eval_coors = get_eval_coors(vertex_coors, vertex_conn, gps)
(level, coors, conn,
vdofs, mat_ids) = create_output(eval_dofs, eval_coors,
vertex_conn.shape[0], ps,
min_level=min_level,
max_level=max_level, eps=eps)
mesh = Mesh.from_data('linearized_mesh', coors, None, [conn], [mat_ids],
field.domain.mesh.descs)
out = {}
out[name] = Struct(name='output_data', mode='vertex',
data=vdofs, var_name=name, dofs=None,
mesh=mesh, level=level)
out = convert_complex_output(out)
return out
def create_expression_output(
expression,
name,
primary_field_name,
fields,
materials,
variables,
functions=None,
mode="eval",
term_mode=None,
extra_args=None,
verbose=True,
kwargs=None,
min_level=0,
max_level=1,
eps=1e-4,
):
"""
Create output mesh and data for the expression using the adaptive
linearizer.
Parameters
----------
expression : str
The expression to evaluate.
name : str
The name of the data.
primary_field_name : str
The name of field that defines the element groups and polynomial
spaces.
fields : dict
The dictionary of fields used in `variables`.
materials : Materials instance
The materials used in the expression.
variables : Variables instance
The variables used in the expression.
functions : Functions instance, optional
The user functions for materials etc.
mode : one of 'eval', 'el_avg', 'qp'
The evaluation mode - 'qp' requests the values in quadrature points,
'el_avg' element averages and 'eval' means integration over
each term region.
term_mode : str
The term call mode - some terms support different call modes
and depending on the call mode different values are
returned.
extra_args : dict, optional
Extra arguments to be passed to terms in the expression.
verbose : bool
If False, reduce verbosity.
kwargs : dict, optional
The variables (dictionary of (variable name) : (Variable
instance)) to be used in the expression.
min_level : int
The minimum required level of mesh refinement.
max_level : int
The maximum level of mesh refinement.
eps : float
The relative tolerance parameter of mesh adaptivity.
Returns
-------
out : dict
The output dictionary.
"""
field = fields[primary_field_name]
vertex_coors = field.coors[: field.n_vertex_dof, :]
coors = []
vdofs = []
conns = []
mat_ids = []
levels = []
offset = 0
for ig, ap in field.aps.iteritems():
ps = ap.interp.poly_spaces["v"]
gps = ap.interp.gel.interp.poly_spaces["v"]
group = field.domain.groups[ig]
vertex_conn = ap.econn[:, : group.shape.n_ep]
eval_dofs = get_eval_expression(
expression,
ig,
fields,
materials,
variables,
functions=functions,
mode=mode,
extra_args=extra_args,
verbose=verbose,
kwargs=kwargs,
)
eval_coors = get_eval_coors(vertex_coors, vertex_conn, gps)
(level, _coors, conn, _vdofs, _mat_ids) = create_output(
eval_dofs, eval_coors, group.shape.n_el, ps, min_level=min_level, max_level=max_level, eps=eps
)
_mat_ids[:] = field.domain.mesh.mat_ids[ig][0]
coors.append(_coors)
vdofs.append(_vdofs)
conns.append(conn + offset)
mat_ids.append(_mat_ids)
levels.append(level)
offset += _coors.shape[0]
coors = nm.concatenate(coors, axis=0)
vdofs = nm.concatenate(vdofs, axis=0)
mesh = Mesh.from_data("linearized_mesh", coors, None, conns, mat_ids, field.domain.mesh.descs)
out = {}
out[name] = Struct(
name="output_data", mode="vertex", data=vdofs, var_name=name, dofs=None, mesh=mesh, levels=levels
)
out = convert_complex_output(out)
return out
