示例#1
0
    def linearize(self, dofs, min_level=0, max_level=1, eps=1e-4):
        """
        Linearize the solution for post-processing.

        Parameters
        ----------
        dofs : array, shape (n_nod, n_component)
            The array of DOFs reshaped so that each column corresponds
            to one component.
        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
        -------
        mesh : Mesh instance
            The adapted, nonconforming, mesh.
        vdofs : array
            The DOFs defined in vertices of `mesh`.
        levels : array of ints
            The refinement level used for each element group.
        """
        assert_(dofs.ndim == 2)

        n_nod, dpn = dofs.shape

        assert_(n_nod == self.n_nod)
        assert_(dpn == self.shape[0])

        vertex_coors = self.coors[:self.n_vertex_dof, :]

        coors = []
        vdofs = []
        conns = []
        mat_ids = []
        levels = []
        offset = 0
        for ig, ap in self.aps.iteritems():
            ps = ap.interp.poly_spaces['v']
            gps = ap.interp.gel.interp.poly_spaces['v']
            group = self.domain.groups[ig]
            vertex_conn = ap.econn[:, :group.shape.n_ep]

            eval_dofs = get_eval_dofs(dofs, ap.econn, ps, ori=ap.ori)
            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[:] = self.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,
                              self.domain.mesh.descs)

        return mesh, vdofs, levels
示例#2
0
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