Пример #1
0
    def discretize_CircleDomain():
        ni = int(m.ceil(domain_description.width / diameter))
        grid = OnedGrid(domain=domain_description.domain,
                        num_intervals=ni,
                        identify_left_right=True)
        bi = EmptyBoundaryInfo(grid)

        return grid, bi
Пример #2
0
    def discretize_TorusDomain():
        if grid_type == RectGrid:
            x0i = int(m.ceil(domain_description.width * m.sqrt(2) / diameter))
            x1i = int(m.ceil(domain_description.height * m.sqrt(2) / diameter))
        elif grid_type == TriaGrid:
            x0i = int(m.ceil(domain_description.width / diameter))
            x1i = int(m.ceil(domain_description.height / diameter))
        else:
            raise NotImplementedError
        grid = grid_type(domain=domain_description.domain, num_intervals=(x0i, x1i),
                         identify_left_right=True, identify_bottom_top=True)

        bi = EmptyBoundaryInfo(grid)

        return grid, bi
Пример #3
0
def discretize_stationary_cg(analytical_problem,
                             diameter=None,
                             domain_discretizer=None,
                             grid_type=None,
                             grid=None,
                             boundary_info=None,
                             preassemble=True):
    """Discretizes a |StationaryProblem| using finite elements.

    Parameters
    ----------
    analytical_problem
        The |StationaryProblem| to discretize.
    diameter
        If not `None`, `diameter` is passed as an argument to the `domain_discretizer`.
    domain_discretizer
        Discretizer to be used for discretizing the analytical domain. This has
        to be a function `domain_discretizer(domain_description, diameter, ...)`.
        If `None`, |discretize_domain_default| is used.
    grid_type
        If not `None`, this parameter is forwarded to `domain_discretizer` to specify
        the type of the generated |Grid|.
    grid
        Instead of using a domain discretizer, the |Grid| can also be passed directly
        using this parameter.
    boundary_info
        A |BoundaryInfo| specifying the boundary types of the grid boundary entities.
        Must be provided if `grid` is specified.
    preassemble
        If `True`, preassemble all operators in the resulting |Model|.

    Returns
    -------
    m
        The |Model| that has been generated.
    data
        Dictionary with the following entries:

            :grid:           The generated |Grid|.
            :boundary_info:  The generated |BoundaryInfo|.
            :unassembled_m:  In case `preassemble` is `True`, the generated |Model|
                             before preassembling operators.
    """

    assert isinstance(analytical_problem, StationaryProblem)
    assert grid is None or boundary_info is not None
    assert boundary_info is None or grid is not None
    assert grid is None or domain_discretizer is None
    assert grid_type is None or grid is None

    p = analytical_problem

    if not (p.nonlinear_advection == p.nonlinear_advection_derivative ==
            p.nonlinear_reaction == p.nonlinear_reaction_derivative is None):
        raise NotImplementedError

    if grid is None:
        domain_discretizer = domain_discretizer or discretize_domain_default
        if grid_type:
            domain_discretizer = partial(domain_discretizer,
                                         grid_type=grid_type)
        if diameter is None:
            grid, boundary_info = domain_discretizer(p.domain)
        else:
            grid, boundary_info = domain_discretizer(p.domain,
                                                     diameter=diameter)

    assert grid.reference_element in (line, triangle, square)

    if grid.reference_element is square:
        DiffusionOperator = DiffusionOperatorQ1
        AdvectionOperator = AdvectionOperatorQ1
        ReactionOperator = L2ProductQ1
        L2Functional = L2ProductFunctionalQ1
        BoundaryL2Functional = BoundaryL2ProductFunctional
    else:
        DiffusionOperator = DiffusionOperatorP1
        AdvectionOperator = AdvectionOperatorP1
        ReactionOperator = L2ProductP1
        L2Functional = L2ProductFunctionalP1
        BoundaryL2Functional = BoundaryL2ProductFunctional

    Li = [
        DiffusionOperator(grid,
                          boundary_info,
                          diffusion_constant=0,
                          name='boundary_part')
    ]
    coefficients = [1.]

    # diffusion part
    if isinstance(p.diffusion, LincombFunction):
        Li += [
            DiffusionOperator(grid,
                              boundary_info,
                              diffusion_function=df,
                              dirichlet_clear_diag=True,
                              name=f'diffusion_{i}')
            for i, df in enumerate(p.diffusion.functions)
        ]
        coefficients += list(p.diffusion.coefficients)
    elif p.diffusion is not None:
        Li += [
            DiffusionOperator(grid,
                              boundary_info,
                              diffusion_function=p.diffusion,
                              dirichlet_clear_diag=True,
                              name='diffusion')
        ]
        coefficients.append(1.)

    # advection part
    if isinstance(p.advection, LincombFunction):
        Li += [
            AdvectionOperator(grid,
                              boundary_info,
                              advection_function=af,
                              dirichlet_clear_diag=True,
                              name=f'advection_{i}')
            for i, af in enumerate(p.advection.functions)
        ]
        coefficients += list(p.advection.coefficients)
    elif p.advection is not None:
        Li += [
            AdvectionOperator(grid,
                              boundary_info,
                              advection_function=p.advection,
                              dirichlet_clear_diag=True,
                              name='advection')
        ]
        coefficients.append(1.)

    # reaction part
    if isinstance(p.reaction, LincombFunction):
        Li += [
            ReactionOperator(grid,
                             boundary_info,
                             coefficient_function=rf,
                             dirichlet_clear_diag=True,
                             name=f'reaction_{i}')
            for i, rf in enumerate(p.reaction.functions)
        ]
        coefficients += list(p.reaction.coefficients)
    elif p.reaction is not None:
        Li += [
            ReactionOperator(grid,
                             boundary_info,
                             coefficient_function=p.reaction,
                             dirichlet_clear_diag=True,
                             name='reaction')
        ]
        coefficients.append(1.)

    # robin boundaries
    if p.robin_data is not None:
        assert isinstance(p.robin_data, tuple) and len(p.robin_data) == 2
        if isinstance(p.robin_data[0], LincombFunction):
            for i, rd in enumerate(p.robin_data[0].functions):
                robin_tuple = (rd, p.robin_data[1])
                Li += [
                    RobinBoundaryOperator(grid,
                                          boundary_info,
                                          robin_data=robin_tuple,
                                          name=f'robin_{i}')
                ]
            coefficients += list(p.robin_data[0].coefficients)
        else:
            Li += [
                RobinBoundaryOperator(grid,
                                      boundary_info,
                                      robin_data=p.robin_data,
                                      name=f'robin')
            ]
            coefficients.append(1.)

    L = LincombOperator(operators=Li,
                        coefficients=coefficients,
                        name='ellipticOperator')

    # right-hand side
    rhs = p.rhs or ConstantFunction(0., dim_domain=p.domain.dim)
    Fi = []
    coefficients_F = []
    if isinstance(p.rhs, LincombFunction):
        Fi += [
            L2Functional(grid,
                         rh,
                         dirichlet_clear_dofs=True,
                         boundary_info=boundary_info,
                         name=f'rhs_{i}')
            for i, rh in enumerate(p.rhs.functions)
        ]
        coefficients_F += list(p.rhs.coefficients)
    else:
        Fi += [
            L2Functional(grid,
                         rhs,
                         dirichlet_clear_dofs=True,
                         boundary_info=boundary_info,
                         name='rhs')
        ]
        coefficients_F.append(1.)

    if p.neumann_data is not None and boundary_info.has_neumann:
        if isinstance(p.neumann_data, LincombFunction):
            Fi += [
                BoundaryL2Functional(grid,
                                     -ne,
                                     boundary_info=boundary_info,
                                     boundary_type='neumann',
                                     dirichlet_clear_dofs=True,
                                     name=f'neumann_{i}')
                for i, ne in enumerate(p.neumann_data.functions)
            ]
            coefficients_F += list(p.neumann_data.coefficients)
        else:
            Fi += [
                BoundaryL2Functional(grid,
                                     -p.neumann_data,
                                     boundary_info=boundary_info,
                                     boundary_type='neumann',
                                     dirichlet_clear_dofs=True)
            ]
            coefficients_F.append(1.)

    if p.robin_data is not None and boundary_info.has_robin:
        if isinstance(p.robin_data[0], LincombFunction):
            Fi += [
                BoundaryL2Functional(grid,
                                     rob * p.robin_data[1],
                                     boundary_info=boundary_info,
                                     boundary_type='robin',
                                     dirichlet_clear_dofs=True,
                                     name=f'robin_{i}')
                for i, rob in enumerate(p.robin_data[0].functions)
            ]
            coefficients_F += list(p.robin_data[0].coefficients)
        else:
            Fi += [
                BoundaryL2Functional(grid,
                                     p.robin_data[0] * p.robin_data[1],
                                     boundary_info=boundary_info,
                                     boundary_type='robin',
                                     dirichlet_clear_dofs=True)
            ]
            coefficients_F.append(1.)

    if p.dirichlet_data is not None and boundary_info.has_dirichlet:
        if isinstance(p.dirichlet_data, LincombFunction):
            Fi += [
                BoundaryDirichletFunctional(grid,
                                            di,
                                            boundary_info,
                                            name=f'dirichlet{i}')
                for i, di in enumerate(p.dirichlet_data.functions)
            ]
            coefficients_F += list(p.dirichlet_data.coefficients)
        else:
            Fi += [
                BoundaryDirichletFunctional(grid, p.dirichlet_data,
                                            boundary_info)
            ]
            coefficients_F.append(1.)

    F = LincombOperator(operators=Fi,
                        coefficients=coefficients_F,
                        name='rhsOperator')

    if grid.reference_element in (triangle, square):
        visualizer = PatchVisualizer(grid=grid,
                                     bounding_box=grid.bounding_box(),
                                     codim=2)
    elif grid.reference_element is line:
        visualizer = OnedVisualizer(grid=grid, codim=1)
    else:
        visualizer = None

    Prod = L2ProductQ1 if grid.reference_element is square else L2ProductP1
    empty_bi = EmptyBoundaryInfo(grid)
    l2_product = Prod(grid, empty_bi, name='l2')
    l2_0_product = Prod(grid,
                        boundary_info,
                        dirichlet_clear_columns=True,
                        name='l2_0')
    h1_semi_product = DiffusionOperator(grid, empty_bi, name='h1_semi')
    h1_0_semi_product = DiffusionOperator(grid,
                                          boundary_info,
                                          dirichlet_clear_columns=True,
                                          name='h1_0_semi')
    products = {
        'h1': l2_product + h1_semi_product,
        'h1_semi': h1_semi_product,
        'l2': l2_product,
        'h1_0': l2_0_product + h1_0_semi_product,
        'h1_0_semi': h1_0_semi_product,
        'l2_0': l2_0_product
    }

    # assemble additionals output functionals
    if p.outputs:
        if any(v[0] not in ('l2', 'l2_boundary') for v in p.outputs):
            raise NotImplementedError
        outputs = [
            L2Functional(grid, v[1], dirichlet_clear_dofs=False).H
            if v[0] == 'l2' else BoundaryL2Functional(
                grid, v[1], dirichlet_clear_dofs=False).H for v in p.outputs
        ]
        if len(outputs) > 1:
            from pymor.operators.block import BlockColumnOperator
            output_functional = BlockColumnOperator(outputs)
        else:
            output_functional = outputs[0]
    else:
        output_functional = None

    parameter_space = p.parameter_space if hasattr(p,
                                                   'parameter_space') else None

    m = StationaryModel(L,
                        F,
                        output_functional=output_functional,
                        products=products,
                        visualizer=visualizer,
                        parameter_space=parameter_space,
                        name=f'{p.name}_CG')

    data = {'grid': grid, 'boundary_info': boundary_info}

    if preassemble:
        data['unassembled_m'] = m
        m = preassemble_(m)

    return m, data
Пример #4
0
def discretize_elliptic_cg(analytical_problem,
                           diameter=None,
                           domain_discretizer=None,
                           grid=None,
                           boundary_info=None):
    """Discretizes an |EllipticProblem| using finite elements.

    Parameters
    ----------
    analytical_problem
        The |EllipticProblem| to discretize.
    diameter
        If not `None`, `diameter` is passed to the `domain_discretizer`.
    domain_discretizer
        Discretizer to be used for discretizing the analytical domain. This has
        to be a function `domain_discretizer(domain_description, diameter, ...)`.
        If further arguments should be passed to the discretizer, use
        :func:`functools.partial`. If `None`, |discretize_domain_default| is used.
    grid
        Instead of using a domain discretizer, the |Grid| can also be passed directly
        using this parameter.
    boundary_info
        A |BoundaryInfo| specifying the boundary types of the grid boundary entities.
        Must be provided if `grid` is specified.

    Returns
    -------
    discretization
        The |Discretization| that has been generated.
    data
        Dictionary with the following entries:

            :grid:           The generated |Grid|.
            :boundary_info:  The generated |BoundaryInfo|.
    """

    assert isinstance(analytical_problem, EllipticProblem)
    assert grid is None or boundary_info is not None
    assert boundary_info is None or grid is not None
    assert grid is None or domain_discretizer is None

    if grid is None:
        domain_discretizer = domain_discretizer or discretize_domain_default
        if diameter is None:
            grid, boundary_info = domain_discretizer(analytical_problem.domain)
        else:
            grid, boundary_info = domain_discretizer(analytical_problem.domain,
                                                     diameter=diameter)

    assert isinstance(grid, (OnedGrid, TriaGrid, RectGrid))

    if isinstance(grid, RectGrid):
        Operator = cg.DiffusionOperatorQ1
        Functional = cg.L2ProductFunctionalQ1
    else:
        Operator = cg.DiffusionOperatorP1
        Functional = cg.L2ProductFunctionalP1

    p = analytical_problem

    if p.diffusion_functionals is not None:
        L0 = Operator(grid,
                      boundary_info,
                      diffusion_constant=0,
                      name='diffusion_boundary_part')

        Li = [
            Operator(grid,
                     boundary_info,
                     diffusion_function=df,
                     dirichlet_clear_diag=True,
                     name='diffusion_{}'.format(i))
            for i, df in enumerate(p.diffusion_functions)
        ]

        L = LincombOperator(operators=[L0] + Li,
                            coefficients=[1.] + list(p.diffusion_functionals),
                            name='diffusion')
    else:
        assert len(p.diffusion_functions) == 1
        L = Operator(grid,
                     boundary_info,
                     diffusion_function=p.diffusion_functions[0],
                     name='diffusion')

    F = Functional(grid,
                   p.rhs,
                   boundary_info,
                   dirichlet_data=p.dirichlet_data,
                   neumann_data=p.neumann_data)

    if isinstance(grid, (TriaGrid, RectGrid)):
        visualizer = PatchVisualizer(grid=grid,
                                     bounding_box=grid.domain,
                                     codim=2)
    else:
        visualizer = Matplotlib1DVisualizer(grid=grid, codim=1)

    empty_bi = EmptyBoundaryInfo(grid)
    l2_product = cg.L2ProductQ1(grid, empty_bi) if isinstance(
        grid, RectGrid) else cg.L2ProductP1(grid, empty_bi)
    h1_semi_product = Operator(grid, empty_bi)
    products = {
        'h1': l2_product + h1_semi_product,
        'h1_semi': h1_semi_product,
        'l2': l2_product
    }

    parameter_space = p.parameter_space if hasattr(p,
                                                   'parameter_space') else None

    discretization = StationaryDiscretization(L,
                                              F,
                                              products=products,
                                              visualizer=visualizer,
                                              parameter_space=parameter_space,
                                              name='{}_CG'.format(p.name))

    return discretization, {'grid': grid, 'boundary_info': boundary_info}
Пример #5
0
def discretize_stationary_cg(analytical_problem,
                             diameter=None,
                             domain_discretizer=None,
                             grid_type=None,
                             grid=None,
                             boundary_info=None,
                             preassemble=True):
    """Discretizes an |StationaryProblem| using finite elements.

    Parameters
    ----------
    analytical_problem
        The |StationaryProblem| to discretize.
    diameter
        If not `None`, `diameter` is passed as an argument to the `domain_discretizer`.
    domain_discretizer
        Discretizer to be used for discretizing the analytical domain. This has
        to be a function `domain_discretizer(domain_description, diameter, ...)`.
        If `None`, |discretize_domain_default| is used.
    grid_type
        If not `None`, this parameter is forwarded to `domain_discretizer` to specify
        the type of the generated |Grid|.
    grid
        Instead of using a domain discretizer, the |Grid| can also be passed directly
        using this parameter.
    boundary_info
        A |BoundaryInfo| specifying the boundary types of the grid boundary entities.
        Must be provided if `grid` is specified.
    preassemble
        If `True`, preassemble all operators in the resulting |Discretization|.

    Returns
    -------
    d
        The |Discretization| that has been generated.
    data
        Dictionary with the following entries:

            :grid:           The generated |Grid|.
            :boundary_info:  The generated |BoundaryInfo|.
    """

    assert isinstance(analytical_problem, StationaryProblem)
    assert grid is None or boundary_info is not None
    assert boundary_info is None or grid is not None
    assert grid is None or domain_discretizer is None
    assert grid_type is None or grid is None

    p = analytical_problem

    if not (p.nonlinear_advection == p.nonlinear_advection_derivative ==
            p.nonlinear_reaction == p.nonlinear_reaction_derivative == None):
        raise NotImplementedError

    if grid is None:
        domain_discretizer = domain_discretizer or discretize_domain_default
        if grid_type:
            domain_discretizer = partial(domain_discretizer,
                                         grid_type=grid_type)
        if diameter is None:
            grid, boundary_info = domain_discretizer(p.domain)
        else:
            grid, boundary_info = domain_discretizer(p.domain,
                                                     diameter=diameter)

    assert grid.reference_element in (line, triangle, square)

    if grid.reference_element is square:
        DiffusionOperator = DiffusionOperatorQ1
        AdvectionOperator = AdvectionOperatorQ1
        ReactionOperator = L2ProductQ1
        Functional = L2ProductFunctionalQ1
    else:
        DiffusionOperator = DiffusionOperatorP1
        AdvectionOperator = AdvectionOperatorP1
        ReactionOperator = L2ProductP1
        Functional = L2ProductFunctionalP1

    Li = [
        DiffusionOperator(grid,
                          boundary_info,
                          diffusion_constant=0,
                          name='boundary_part')
    ]
    coefficients = [1.]

    # diffusion part
    if isinstance(p.diffusion, LincombFunction):
        Li += [
            DiffusionOperator(grid,
                              boundary_info,
                              diffusion_function=df,
                              dirichlet_clear_diag=True,
                              name='diffusion_{}'.format(i))
            for i, df in enumerate(p.diffusion.functions)
        ]
        coefficients += list(p.diffusion.coefficients)
    elif p.diffusion is not None:
        Li += [
            DiffusionOperator(grid,
                              boundary_info,
                              diffusion_function=p.diffusion,
                              dirichlet_clear_diag=True,
                              name='diffusion')
        ]
        coefficients.append(1.)

    # advection part
    if isinstance(p.advection, LincombFunction):
        Li += [
            AdvectionOperator(grid,
                              boundary_info,
                              advection_function=af,
                              dirichlet_clear_diag=True,
                              name='advection_{}'.format(i))
            for i, af in enumerate(p.advection.functions)
        ]
        coefficients += list(p.advection.coefficients)
    elif p.advection is not None:
        Li += [
            AdvectionOperator(grid,
                              boundary_info,
                              advection_function=p.advection,
                              dirichlet_clear_diag=True,
                              name='advection')
        ]
        coefficients.append(1.)

    # reaction part
    if isinstance(p.reaction, LincombFunction):
        Li += [
            ReactionOperator(grid,
                             boundary_info,
                             coefficient_function=rf,
                             dirichlet_clear_diag=True,
                             name='reaction_{}'.format(i))
            for i, rf in enumerate(p.reaction.functions)
        ]
        coefficients += list(p.reaction.coefficients)
    elif p.reaction is not None:
        Li += [
            ReactionOperator(grid,
                             boundary_info,
                             coefficient_function=p.reaction,
                             dirichlet_clear_diag=True,
                             name='reaction')
        ]
        coefficients.append(1.)

    # robin boundaries
    if p.robin_data is not None:
        if grid.reference_element is square:
            raise NotImplementedError
        Li += [
            RobinBoundaryOperator(grid,
                                  boundary_info,
                                  robin_data=p.robin_data,
                                  order=2,
                                  name='robin')
        ]
        coefficients.append(1.)

    L = LincombOperator(operators=Li,
                        coefficients=coefficients,
                        name='ellipticOperator')

    rhs = p.rhs or ConstantFunction(0., dim_domain=p.domain.dim)
    F = Functional(grid,
                   rhs,
                   boundary_info,
                   dirichlet_data=p.dirichlet_data,
                   neumann_data=p.neumann_data)

    if grid.reference_element in (triangle, square):
        visualizer = PatchVisualizer(grid=grid,
                                     bounding_box=grid.bounding_box(),
                                     codim=2)
    elif grid.reference_element is line:
        visualizer = OnedVisualizer(grid=grid, codim=1)
    else:
        visualizer = None

    Prod = L2ProductQ1 if grid.reference_element is square else L2ProductP1
    empty_bi = EmptyBoundaryInfo(grid)
    l2_product = Prod(grid, empty_bi, name='l2')
    l2_0_product = Prod(grid,
                        boundary_info,
                        dirichlet_clear_columns=True,
                        name='l2_0')
    h1_semi_product = DiffusionOperator(grid, empty_bi, name='h1_semi')
    h1_0_semi_product = DiffusionOperator(grid,
                                          boundary_info,
                                          dirichlet_clear_columns=True,
                                          name='h1_0_semi')
    products = {
        'h1': l2_product + h1_semi_product,
        'h1_semi': h1_semi_product,
        'l2': l2_product,
        'h1_0': l2_0_product + h1_0_semi_product,
        'h1_0_semi': h1_0_semi_product,
        'l2_0': l2_0_product
    }

    parameter_space = p.parameter_space if hasattr(p,
                                                   'parameter_space') else None

    d = StationaryDiscretization(L,
                                 F,
                                 products=products,
                                 visualizer=visualizer,
                                 parameter_space=parameter_space,
                                 name='{}_CG'.format(p.name))

    data = {'grid': grid, 'boundary_info': boundary_info}

    if preassemble:
        data['unassembled_d'] = d
        d = preassemble_(d)

    return d, data
Пример #6
0
def discretize_elliptic_cg(analytical_problem,
                           diameter=None,
                           domain_discretizer=None,
                           grid=None,
                           boundary_info=None):
    """Discretizes an |EllipticProblem| using finite elements.

    Parameters
    ----------
    analytical_problem
        The |EllipticProblem| to discretize.
    diameter
        If not `None`, `diameter` is passed to the `domain_discretizer`.
    domain_discretizer
        Discretizer to be used for discretizing the analytical domain. This has
        to be a function `domain_discretizer(domain_description, diameter, ...)`.
        If further arguments should be passed to the discretizer, use
        :func:`functools.partial`. If `None`, |discretize_domain_default| is used.
    grid
        Instead of using a domain discretizer, the |Grid| can also be passed directly
        using this parameter.
    boundary_info
        A |BoundaryInfo| specifying the boundary types of the grid boundary entities.
        Must be provided if `grid` is specified.

    Returns
    -------
    discretization
        The |Discretization| that has been generated.
    data
        Dictionary with the following entries:

            :grid:           The generated |Grid|.
            :boundary_info:  The generated |BoundaryInfo|.
    """

    assert isinstance(analytical_problem, EllipticProblem)
    assert grid is None or boundary_info is not None
    assert boundary_info is None or grid is not None
    assert grid is None or domain_discretizer is None

    if grid is None:
        domain_discretizer = domain_discretizer or discretize_domain_default
        if diameter is None:
            grid, boundary_info = domain_discretizer(analytical_problem.domain)
        else:
            grid, boundary_info = domain_discretizer(analytical_problem.domain,
                                                     diameter=diameter)

    assert grid.reference_element in (line, triangle, square)

    if grid.reference_element is square:
        DiffusionOperator = cg.DiffusionOperatorQ1
        AdvectionOperator = cg.AdvectionOperatorQ1
        ReactionOperator = cg.L2ProductQ1
        Functional = cg.L2ProductFunctionalQ1
    else:
        DiffusionOperator = cg.DiffusionOperatorP1
        AdvectionOperator = cg.AdvectionOperatorP1
        ReactionOperator = cg.L2ProductP1
        Functional = cg.L2ProductFunctionalP1

    p = analytical_problem

    if p.diffusion_functionals is not None or p.advection_functionals is not None or p.reaction_functionals is not None:
        # parametric case
        Li = [
            DiffusionOperator(grid,
                              boundary_info,
                              diffusion_constant=0,
                              name='boundary_part')
        ]
        coefficients = [1.]

        # diffusion part
        if p.diffusion_functionals is not None:
            Li += [
                DiffusionOperator(grid,
                                  boundary_info,
                                  diffusion_function=df,
                                  dirichlet_clear_diag=True,
                                  name='diffusion_{}'.format(i))
                for i, df in enumerate(p.diffusion_functions)
            ]
            coefficients += list(p.diffusion_functionals)
        elif p.diffusion_functions is not None:
            assert len(p.diffusion_functions) == 1
            Li += [
                DiffusionOperator(grid,
                                  boundary_info,
                                  diffusion_function=p.diffusion_functions[0],
                                  dirichlet_clear_diag=True,
                                  name='diffusion')
            ]
            coefficients.append(1.)

        # advection part
        if p.advection_functionals is not None:
            Li += [
                AdvectionOperator(grid,
                                  boundary_info,
                                  advection_function=af,
                                  dirichlet_clear_diag=True,
                                  name='advection_{}'.format(i))
                for i, af in enumerate(p.advection_functions)
            ]
            coefficients += list(p.advection_functionals)
        elif p.advection_functions is not None:
            assert len(p.advection_functions) == 1
            Li += [
                AdvectionOperator(grid,
                                  boundary_info,
                                  advection_function=p.advection_functions[0],
                                  dirichlet_clear_diag=True,
                                  name='advection')
            ]
            coefficients.append(1.)

        # reaction part
        if p.reaction_functionals is not None:
            Li += [
                ReactionOperator(grid,
                                 boundary_info,
                                 coefficient_function=rf,
                                 dirichlet_clear_diag=True,
                                 name='reaction_{}'.format(i))
                for i, rf in enumerate(p.reaction_functions)
            ]
            coefficients += list(p.reaction_functionals)
        elif p.reaction_functions is not None:
            assert len(p.reaction_functions) == 1
            Li += [
                ReactionOperator(grid,
                                 boundary_info,
                                 coefficient_function=p.reaction_functions[0],
                                 dirichlet_clear_diag=True,
                                 name='reaction')
            ]
            coefficients.append(1.)

        # robin boundaries
        if p.robin_data is not None:
            Li += [
                cg.RobinBoundaryOperator(grid,
                                         boundary_info,
                                         robin_data=p.robin_data,
                                         order=2,
                                         name='robin')
            ]
            coefficients.append(1.)

        L = LincombOperator(operators=Li,
                            coefficients=coefficients,
                            name='ellipticOperator')
    else:
        # unparametric case, not operator for boundary treatment
        Li = []

        # only one operator has diagonal values, all subsequent operators have clear_diag
        dirichlet_clear_diag = False
        # diffusion part
        if p.diffusion_functions is not None:
            assert len(p.diffusion_functions) == 1
            Li += [
                DiffusionOperator(grid,
                                  boundary_info,
                                  diffusion_function=p.diffusion_functions[0],
                                  dirichlet_clear_diag=dirichlet_clear_diag,
                                  name='diffusion')
            ]
            dirichlet_clear_diag = True

        # advection part
        if p.advection_functions is not None:
            assert len(p.advection_functions) == 1
            Li += [
                AdvectionOperator(grid,
                                  boundary_info,
                                  advection_function=p.advection_functions[0],
                                  dirichlet_clear_diag=dirichlet_clear_diag,
                                  name='advection')
            ]
            dirichlet_clear_diag = True

        # reaction part
        if p.reaction_functions is not None:
            assert len(p.reaction_functions) == 1
            Li += [
                ReactionOperator(grid,
                                 boundary_info,
                                 coefficient_function=p.reaction_functions[0],
                                 dirichlet_clear_diag=dirichlet_clear_diag,
                                 name='reaction')
            ]
            dirichlet_clear_diag = True

        # robin boundaries
        if p.robin_data is not None:
            Li += [
                cg.RobinBoundaryOperator(grid,
                                         boundary_info,
                                         robin_data=p.robin_data,
                                         order=2,
                                         name='robin')
            ]

        if len(Li) == 1:
            L = Li[0]
        else:
            L = LincombOperator(operators=Li,
                                coefficients=[1.] * len(Li),
                                name='ellipticOperator')

    F = Functional(grid,
                   p.rhs,
                   boundary_info,
                   dirichlet_data=p.dirichlet_data,
                   neumann_data=p.neumann_data)

    if grid.reference_element in (triangle, square):
        visualizer = PatchVisualizer(grid=grid,
                                     bounding_box=grid.bounding_box(),
                                     codim=2)
    elif grid.reference_element is line:
        visualizer = Matplotlib1DVisualizer(grid=grid, codim=1)
    else:
        visualizer = None

    Prod = cg.L2ProductQ1 if grid.reference_element is square else cg.L2ProductP1
    empty_bi = EmptyBoundaryInfo(grid)
    l2_product = Prod(grid, empty_bi, name='l2')
    l2_0_product = Prod(grid,
                        boundary_info,
                        dirichlet_clear_columns=True,
                        name='l2_0')
    h1_semi_product = DiffusionOperator(grid, empty_bi, name='h1_semi')
    h1_0_semi_product = DiffusionOperator(grid,
                                          boundary_info,
                                          dirichlet_clear_columns=True,
                                          name='h1_0_semi')
    products = {
        'h1': l2_product + h1_semi_product,
        'h1_semi': h1_semi_product,
        'l2': l2_product,
        'h1_0': l2_0_product + h1_0_semi_product,
        'h1_0_semi': h1_0_semi_product,
        'l2_0': l2_0_product
    }

    parameter_space = p.parameter_space if hasattr(p,
                                                   'parameter_space') else None

    discretization = StationaryDiscretization(L,
                                              F,
                                              products=products,
                                              visualizer=visualizer,
                                              parameter_space=parameter_space,
                                              name='{}_CG'.format(p.name))

    return discretization, {'grid': grid, 'boundary_info': boundary_info}