Python dolfin.FunctionSpace方法代码示例

# 需要导入模块: import dolfin [as 别名]
# 或者: from dolfin import FunctionSpace [as 别名]
def __init__(self, init=None, val=0.0):
        """
        Initialization routine

        Args:
            init: can either be a FunctionSpace or another fenics_mesh object
            val: initial value (default: 0.0)
        Raises:
            DataError: if init is none of the types above
        """
        # if init is another fenic_mesh, do a deepcopy (init by copy)
        if isinstance(init, type(self)):
            self.values = init.values.copy(deepcopy=True)
        # if init is FunctionSpace, create mesh object with val as initial value
        elif isinstance(init, df.Function):
            self.values = init.copy(deepcopy=True)
        elif isinstance(init, df.FunctionSpace):
            self.values = df.Function(init)
            self.values.vector()[:] = val
        else:
            raise DataError('something went wrong during %s initialization' % type(init)) 

# 需要导入模块: import dolfin [as 别名]
# 或者: from dolfin import FunctionSpace [as 别名]
def __init__(self, problem_params, dtype_u=fenics_mesh, dtype_f=fenics_mesh):
        """
        Initialization routine

        Args:
            problem_params: custom parameters for the example
            dtype_u: FEniCS mesh data type (will be passed to parent class)
            dtype_f: FEniCS mesh data data type (will be passed to parent class)
        """

        # define the Dirichlet boundary
        def Boundary(x, on_boundary):
            return on_boundary

        # these parameters will be used later, so assert their existence
        essential_keys = ['c_nvars', 't0', 'family', 'order', 'refinements', 'Du', 'Dv', 'A', 'B']
        for key in essential_keys:
            if key not in problem_params:
                msg = 'need %s to instantiate problem, only got %s' % (key, str(problem_params.keys()))
                raise ParameterError(msg)

        # set logger level for FFC and dolfin
        df.set_log_level(df.WARNING)
        logging.getLogger('FFC').setLevel(logging.WARNING)

        # set solver and form parameters
        df.parameters["form_compiler"]["optimize"] = True
        df.parameters["form_compiler"]["cpp_optimize"] = True

        # set mesh and refinement (for multilevel)
        mesh = df.IntervalMesh(problem_params['c_nvars'], 0, 100)
        for i in range(problem_params['refinements']):
            mesh = df.refine(mesh)

        # define function space for future reference
        V = df.FunctionSpace(mesh, problem_params['family'], problem_params['order'])
        self.V = V * V

        # invoke super init, passing number of dofs, dtype_u and dtype_f
        super(fenics_grayscott, self).__init__(self.V, dtype_u, dtype_f, problem_params)

        # rhs in weak form
        self.w = df.Function(self.V)
        q1, q2 = df.TestFunctions(self.V)

        self.w1, self.w2 = df.split(self.w)

        self.F1 = (-self.params.Du * df.inner(df.nabla_grad(self.w1), df.nabla_grad(q1)) -
                   self.w1 * (self.w2 ** 2) * q1 + self.params.A * (1 - self.w1) * q1) * df.dx
        self.F2 = (-self.params.Dv * df.inner(df.nabla_grad(self.w2), df.nabla_grad(q2)) +
                   self.w1 * (self.w2 ** 2) * q2 - self.params.B * self.w2 * q2) * df.dx
        self.F = self.F1 + self.F2

        # mass matrix
        u1, u2 = df.TrialFunctions(self.V)
        a_M = u1 * q1 * df.dx
        M1 = df.assemble(a_M)
        a_M = u2 * q2 * df.dx
        M2 = df.assemble(a_M)
        self.M = M1 + M2 

# 需要导入模块: import dolfin [as 别名]
# 或者: from dolfin import FunctionSpace [as 别名]
def __init__(self, problem_params, dtype_u=fenics_mesh, dtype_f=fenics_mesh):
        """
        Initialization routine

        Args:
            problem_params (dict): custom parameters for the example
            dtype_u: FEniCS mesh data type (will be passed to parent class)
            dtype_f: FEniCS mesh data type (will be passed to parent class)
        """

        # define the Dirichlet boundary
        def Boundary(x, on_boundary):
            return on_boundary

        # these parameters will be used later, so assert their existence
        essential_keys = ['c_nvars', 't0', 'family', 'order', 'refinements', 'nu']
        for key in essential_keys:
            if key not in problem_params:
                msg = 'need %s to instantiate problem, only got %s' % (key, str(problem_params.keys()))
                raise ParameterError(msg)

        # set logger level for FFC and dolfin
        logging.getLogger('ULF').setLevel(logging.WARNING)
        logging.getLogger('FFC').setLevel(logging.WARNING)
        df.set_log_level(30)

        # set solver and form parameters
        df.parameters["form_compiler"]["optimize"] = True
        df.parameters["form_compiler"]["cpp_optimize"] = True

        # set mesh and refinement (for multilevel)
        mesh = df.UnitIntervalMesh(problem_params['c_nvars'])
        for i in range(problem_params['refinements']):
            mesh = df.refine(mesh)

        # define function space for future reference
        self.V = df.FunctionSpace(mesh, problem_params['family'], problem_params['order'])
        tmp = df.Function(self.V)
        print('DoFs on this level:', len(tmp.vector()[:]))

        # invoke super init, passing number of dofs, dtype_u and dtype_f
        super(fenics_heat_weak_fullyimplicit, self).__init__(self.V, dtype_u, dtype_f, problem_params)

        self.g = df.Expression('-sin(a*x[0]) * (sin(t) - b*a*a*cos(t))', a=np.pi, b=self.params.nu, t=self.params.t0,
                               degree=self.params.order)

        # rhs in weak form
        self.w = df.Function(self.V)
        v = df.TestFunction(self.V)
        self.a_K = -self.params.nu * df.inner(df.nabla_grad(self.w), df.nabla_grad(v)) * df.dx + self.g * v * df.dx

        # mass matrix
        u = df.TrialFunction(self.V)
        a_M = u * v * df.dx
        self.M = df.assemble(a_M)

        self.bc = df.DirichletBC(self.V, df.Constant(0.0), Boundary)