From d13c92fbef1a3c1e3a9ba21859b901ca7bfaaedb Mon Sep 17 00:00:00 2001 From: Thomas Bendall Date: Wed, 18 Dec 2024 12:09:00 +0000 Subject: [PATCH 1/7] Mixed velocity-vorticity transport (#574) --- .../compressible_euler/unsaturated_bubble.py | 9 +- gusto/core/configuration.py | 6 +- gusto/core/domain.py | 9 +- gusto/spatial_methods/__init__.py | 1 + gusto/spatial_methods/augmentation.py | 238 ++++++++++++++++++ .../explicit_runge_kutta.py | 54 +++- .../implicit_runge_kutta.py | 8 +- gusto/time_discretisation/sdc.py | 7 +- .../time_discretisation.py | 92 +++++-- integration-tests/conftest.py | 21 +- integration-tests/data/sw_fplane_chkpt.h5 | Bin 937363 -> 937363 bytes integration-tests/equations/test_sw_fplane.py | 10 +- .../transport/test_vector_recovered_space.py | 3 + .../transport/test_vorticity_transport.py | 111 ++++++++ 14 files changed, 508 insertions(+), 61 deletions(-) create mode 100644 gusto/spatial_methods/augmentation.py create mode 100644 integration-tests/transport/test_vorticity_transport.py diff --git a/examples/compressible_euler/unsaturated_bubble.py b/examples/compressible_euler/unsaturated_bubble.py index 394e15f97..59a911cb9 100644 --- a/examples/compressible_euler/unsaturated_bubble.py +++ b/examples/compressible_euler/unsaturated_bubble.py @@ -216,16 +216,11 @@ def unsaturated_bubble( R_v = eqns.parameters.R_v epsilon = R_d / R_v - # make expressions for determining water_v0 - exner = thermodynamics.exner_pressure(eqns.parameters, rho_averaged, theta0) - p = thermodynamics.p(eqns.parameters, exner) - T = thermodynamics.T(eqns.parameters, theta0, exner, water_v0) - r_v_expr = thermodynamics.r_v(eqns.parameters, rel_hum, T, p) - # make expressions to evaluate residual exner_expr = thermodynamics.exner_pressure(eqns.parameters, rho_averaged, theta0) p_expr = thermodynamics.p(eqns.parameters, exner_expr) T_expr = thermodynamics.T(eqns.parameters, theta0, exner_expr, water_v0) + water_v_expr = thermodynamics.r_v(eqns.parameters, rel_hum, T_expr, p_expr) rel_hum_expr = thermodynamics.RH(eqns.parameters, water_v0, T_expr, p_expr) rel_hum_eval = Function(Vt) @@ -247,7 +242,7 @@ def unsaturated_bubble( # first solve for r_v for _ in range(max_inner_solve_count): - water_v_eval.interpolate(r_v_expr) + water_v_eval.interpolate(water_v_expr) water_v0.assign(water_v0 * (1 - delta) + delta * water_v_eval) # compute theta_vd diff --git a/gusto/core/configuration.py b/gusto/core/configuration.py index f19ef0167..4f82a35f7 100644 --- a/gusto/core/configuration.py +++ b/gusto/core/configuration.py @@ -79,7 +79,11 @@ def __setattr__(self, name, value): # Almost all parameters should be Constants -- but there are some # specific exceptions which should be kept as integers - if type(value) in [float, int] and name not in ['dumpfreq', 'pddumpfreq', 'chkptfreq']: + non_constants = [ + 'dumpfreq', 'pddumpfreq', 'chkptfreq', + 'fixed_subcycles', 'max_subcycles', 'subcycle_by_courant' + ] + if type(value) in [float, int] and name not in non_constants: object.__setattr__(self, name, Constant(value)) else: object.__setattr__(self, name, value) diff --git a/gusto/core/domain.py b/gusto/core/domain.py index 5648c72e1..797f35e90 100644 --- a/gusto/core/domain.py +++ b/gusto/core/domain.py @@ -6,9 +6,10 @@ from gusto.core.coordinates import Coordinates from gusto.core.function_spaces import Spaces, check_degree_args -from firedrake import (Constant, SpatialCoordinate, sqrt, CellNormal, cross, - inner, grad, VectorFunctionSpace, Function, FunctionSpace, - perp) +from firedrake import ( + Constant, SpatialCoordinate, sqrt, CellNormal, cross, inner, grad, + VectorFunctionSpace, Function, FunctionSpace, perp, curl +) import numpy as np @@ -124,12 +125,14 @@ def __init__(self, mesh, dt, family, degree=None, V = VectorFunctionSpace(mesh, "DG", sphere_degree) self.outward_normals = Function(V).interpolate(CellNormal(mesh)) self.perp = lambda u: cross(self.outward_normals, u) + self.divperp = lambda u: inner(self.outward_normals, curl(u)) else: kvec = [0.0]*dim kvec[dim-1] = 1.0 self.k = Constant(kvec) if dim == 2: self.perp = perp + self.divperp = lambda u: -u[0].dx(1) + u[1].dx(0) # -------------------------------------------------------------------- # # Construct information relating to height/radius diff --git a/gusto/spatial_methods/__init__.py b/gusto/spatial_methods/__init__.py index baa1e0788..349094cdf 100644 --- a/gusto/spatial_methods/__init__.py +++ b/gusto/spatial_methods/__init__.py @@ -2,3 +2,4 @@ from gusto.spatial_methods.diffusion_methods import * # noqa from gusto.spatial_methods.transport_methods import * # noqa from gusto.spatial_methods.limiters import * # noqa +from gusto.spatial_methods.augmentation import * # noqa \ No newline at end of file diff --git a/gusto/spatial_methods/augmentation.py b/gusto/spatial_methods/augmentation.py new file mode 100644 index 000000000..42aedaa64 --- /dev/null +++ b/gusto/spatial_methods/augmentation.py @@ -0,0 +1,238 @@ +""" +A module defining objects for temporarily augmenting an equation with another. +""" + + +from abc import ABCMeta, abstractmethod +from firedrake import ( + MixedFunctionSpace, Function, TestFunctions, split, inner, dx, grad, + LinearVariationalProblem, LinearVariationalSolver, lhs, rhs, dot, + ds_b, ds_v, ds_t, ds, FacetNormal, TestFunction, TrialFunction, + transpose, nabla_grad, outer, dS, dS_h, dS_v, sign, jump, div, + Constant, sqrt, cross, curl, FunctionSpace, assemble, DirichletBC +) +from firedrake.fml import subject +from gusto import ( + time_derivative, transport, transporting_velocity, TransportEquationType, + logger +) + + +class Augmentation(object, metaclass=ABCMeta): + """ + Augments an equation with another equation to be solved simultaneously. + """ + + @abstractmethod + def pre_apply(self, x_in): + """ + Steps to take at the beginning of an apply method, for instance to + assign the input field to the internal mixed function. + """ + + pass + + @abstractmethod + def post_apply(self, x_out): + """ + Steps to take at the end of an apply method, for instance to assign the + internal mixed function to the output field. + """ + + pass + + @abstractmethod + def update(self, x_in_mixed): + """ + Any intermediate update steps, depending on the current mixed function. + """ + + pass + + +class VorticityTransport(Augmentation): + """ + Solves the transport of a vector field, simultaneously with the vorticity + as a mixed proble, as described in Bendall and Wimmer (2022). + + Note that this is most effective with implicit time discretisations. The + residual-based SUPG option provides a dissipation method. + + Args: + domain (:class:`Domain`): The domain object. + eqns (:class:`PrognosticEquationSet`): The overarching equation set. + transpose_commutator (bool, optional): Whether to include the commutator + of the transpose gradient terms. This is necessary for solving the + general vector transport equation, but is not necessary when the + transporting and transported fields are the same. Defaults to True. + supg (bool, optional): Whether to include dissipation through a + residual-based SUPG scheme. Defaults to False. + """ + + def __init__( + self, domain, eqns, transpose_commutator=True, supg=False + ): + + V_vel = domain.spaces('HDiv') + V_vort = domain.spaces('H1') + + self.fs = MixedFunctionSpace((V_vel, V_vort)) + self.X = Function(self.fs) + self.tests = TestFunctions(self.fs) + + u = Function(V_vel) + F, Z = split(self.X) + test_F, test_Z = self.tests + + if hasattr(domain.mesh, "_base_mesh"): + self.ds = ds_b + ds_t + ds_v + self.dS = dS_v + dS_h + else: + self.ds = ds + self.dS = dS + + # Add boundary conditions + self.bcs = [] + if 'u' in eqns.bcs.keys(): + for bc in eqns.bcs['u']: + self.bcs.append( + DirichletBC(self.fs.sub(0), bc.function_arg, bc.sub_domain) + ) + + # Set up test function and the vorticity term + n = FacetNormal(domain.mesh) + sign_u = 0.5*(sign(dot(u, n)) + 1) + upw = lambda f: (sign_u('+')*f('+') + sign_u('-')*f('-')) + + if domain.mesh.topological_dimension() == 2: + mix_test = test_F - domain.perp(grad(test_Z)) + F_cross_u = Z*domain.perp(u) + elif domain.mesh.topological_dimension == 3: + mix_test = test_F - curl(test_Z) + F_cross_u = cross(Z, u) + + time_deriv_form = inner(F, test_F)*dx + inner(Z, test_Z)*dx + + # Standard vector invariant transport form ----------------------------- + transport_form = ( + # vorticity term + inner(mix_test, F_cross_u)*dx + + inner(n, test_Z*Z*u)*self.ds + # 0.5*grad(v . F) + - 0.5 * div(mix_test) * inner(u, F)*dx + + 0.5 * inner(mix_test, n) * inner(u, F)*self.ds + ) + + # Communtator of tranpose gradient terms ------------------------------- + # This is needed for general vector transport + if transpose_commutator: + u_dot_nabla_F = dot(u, transpose(nabla_grad(F))) + transport_form += ( + - inner(n, test_Z*domain.perp(u_dot_nabla_F))*self.ds + # + 0.5*grad(F).v + - 0.5 * dot(F, div(outer(u, mix_test)))*dx + + 0.5 * inner(mix_test('+'), n('+'))*dot(jump(u), upw(F))*self.dS + # - 0.5*grad(v).F + + 0.5 * dot(u, div(outer(F, mix_test)))*dx + - 0.5 * inner(mix_test('+'), n('+'))*dot(jump(F), upw(u))*self.dS + ) + + # SUPG terms ----------------------------------------------------------- + # Add the vorticity residual to the transported vorticity, + # which damps enstrophy + if supg: + + # Determine SUPG coefficient --------------------------------------- + tau = 0.5*domain.dt + + # Find mean grid spacing to determine a Courant number + DG0 = FunctionSpace(domain.mesh, 'DG', 0) + ones = Function(DG0).interpolate(Constant(1.0)) + area = assemble(ones*dx) + mean_dx = (area/DG0.dof_count)**(1/domain.mesh.geometric_dimension()) + + # Divide by approximately (1 + c) + tau /= (1.0 + sqrt(dot(u, u))*domain.dt/Constant(mean_dx)) + + dxqp = dx(degree=3) + + if domain.mesh.topological_dimension() == 2: + time_deriv_form -= inner(mix_test, tau*Z*domain.perp(u)/domain.dt)*dxqp + transport_form -= inner( + mix_test, tau*domain.perp(u)*domain.divperp(Z*domain.perp(u)) + )*dxqp + if transpose_commutator: + transport_form -= inner( + mix_test, + tau*domain.perp(u)*domain.divperp(u_dot_nabla_F) + )*dxqp + elif domain.mesh.topological_dimension() == 3: + time_deriv_form -= inner(mix_test, tau*cross(Z, u)/domain.dt)*dxqp + transport_form -= inner( + mix_test, tau*cross(curl(Z*u), u) + )*dxqp + if transpose_commutator: + transport_form -= inner( + mix_test, + tau*cross(curl(u_dot_nabla_F), u) + )*dxqp + + # Assemble the residual ------------------------------------------------ + residual = ( + time_derivative(time_deriv_form) + + transport( + transport_form, TransportEquationType.vector_invariant + ) + ) + residual = transporting_velocity(residual, u) + + self.residual = subject(residual, self.X) + + self.x_in = Function(self.fs) + self.Z_in = Function(V_vort) + self.x_out = Function(self.fs) + + vort_test = TestFunction(V_vort) + vort_trial = TrialFunction(V_vort) + + F_in, _ = split(self.x_in) + + eqn = ( + inner(vort_trial, vort_test)*dx + + inner(domain.perp(grad(vort_test)), F_in)*dx + + vort_test*inner(n, domain.perp(F_in))*self.ds + ) + problem = LinearVariationalProblem( + lhs(eqn), rhs(eqn), self.Z_in, constant_jacobian=True + ) + self.solver = LinearVariationalSolver(problem) + + def pre_apply(self, x_in): + """ + Sets the velocity field for the local mixed function. + + Args: + x_in (:class:`Function`): The input velocity field + """ + self.x_in.subfunctions[0].assign(x_in) + + def post_apply(self, x_out): + """ + Sets the output velocity field from the local mixed function. + + Args: + x_out (:class:`Function`): the output velocity field. + """ + x_out.assign(self.x_out.subfunctions[0]) + + def update(self, x_in_mixed): + """ + Performs the solve to determine the vorticity function. + + Args: + x_in_mixed (:class:`Function`): The mixed function to update. + """ + self.x_in.subfunctions[0].assign(x_in_mixed.subfunctions[0]) + logger.debug('Vorticity solve') + self.solver.solve() + self.x_in.subfunctions[1].assign(self.Z_in) diff --git a/gusto/time_discretisation/explicit_runge_kutta.py b/gusto/time_discretisation/explicit_runge_kutta.py index 0055ddb89..b167cf80a 100644 --- a/gusto/time_discretisation/explicit_runge_kutta.py +++ b/gusto/time_discretisation/explicit_runge_kutta.py @@ -89,7 +89,8 @@ class ExplicitRungeKutta(ExplicitTimeDiscretisation): def __init__(self, domain, butcher_matrix, field_name=None, subcycling_options=None, rk_formulation=RungeKuttaFormulation.increment, - solver_parameters=None, limiter=None, options=None): + solver_parameters=None, limiter=None, options=None, + augmentation=None): """ Args: domain (:class:`Domain`): the model's domain object, containing the @@ -112,11 +113,15 @@ def __init__(self, domain, butcher_matrix, field_name=None, options to either be passed to the spatial discretisation, or to control the "wrapper" methods, such as Embedded DG or a recovery method. Defaults to None. + augmentation (:class:`Augmentation`): allows the equation solved in + this time discretisation to be augmented, for instances with + extra terms of another auxiliary variable. Defaults to None. """ super().__init__(domain, field_name=field_name, subcycling_options=subcycling_options, solver_parameters=solver_parameters, - limiter=limiter, options=options) + limiter=limiter, options=options, + augmentation=augmentation) self.butcher_matrix = butcher_matrix self.nbutcher = int(np.shape(self.butcher_matrix)[0]) self.rk_formulation = rk_formulation @@ -203,7 +208,7 @@ def lhs(self): if self.rk_formulation == RungeKuttaFormulation.increment: l = self.residual.label_map( lambda t: t.has_label(time_derivative), - map_if_true=replace_subject(self.x_out, self.idx), + map_if_true=replace_subject(self.x_out, old_idx=self.idx), map_if_false=drop) return l.form @@ -213,7 +218,7 @@ def lhs(self): for stage in range(self.nStages): l = self.residual.label_map( lambda t: t.has_label(time_derivative), - map_if_true=replace_subject(self.field_i[stage+1], self.idx), + map_if_true=replace_subject(self.field_i[stage+1], old_idx=self.idx), map_if_false=drop) lhs_list.append(l) @@ -222,7 +227,7 @@ def lhs(self): if self.rk_formulation == RungeKuttaFormulation.linear: l = self.residual.label_map( lambda t: t.has_label(time_derivative), - map_if_true=replace_subject(self.x1, self.idx), + map_if_true=replace_subject(self.x1, old_idx=self.idx), map_if_false=drop) return l.form @@ -461,6 +466,9 @@ def apply_cycle(self, x_out, x_in): x_out (:class:`Function`): the output field to be computed. """ + if self.augmentation is not None: + self.augmentation.update(x_in) + # TODO: is this limiter application necessary? if self.limiter is not None: self.limiter.apply(x_in) @@ -484,7 +492,8 @@ class ForwardEuler(ExplicitRungeKutta): def __init__( self, domain, field_name=None, subcycling_options=None, rk_formulation=RungeKuttaFormulation.increment, - solver_parameters=None, limiter=None, options=None + solver_parameters=None, limiter=None, options=None, + augmentation=None ): """ Args: @@ -506,6 +515,9 @@ def __init__( options to either be passed to the spatial discretisation, or to control the "wrapper" methods, such as Embedded DG or a recovery method. Defaults to None. + augmentation (:class:`Augmentation`): allows the equation solved in + this time discretisation to be augmented, for instances with + extra terms of another auxiliary variable. Defaults to None. """ butcher_matrix = np.array([1.]).reshape(1, 1) @@ -514,7 +526,8 @@ def __init__( subcycling_options=subcycling_options, rk_formulation=rk_formulation, solver_parameters=solver_parameters, - limiter=limiter, options=options) + limiter=limiter, options=options, + augmentation=augmentation) class SSPRK3(ExplicitRungeKutta): @@ -530,7 +543,8 @@ class SSPRK3(ExplicitRungeKutta): def __init__( self, domain, field_name=None, subcycling_options=None, rk_formulation=RungeKuttaFormulation.increment, - solver_parameters=None, limiter=None, options=None + solver_parameters=None, limiter=None, options=None, + augmentation=None ): """ Args: @@ -552,6 +566,9 @@ def __init__( options to either be passed to the spatial discretisation, or to control the "wrapper" methods, such as Embedded DG or a recovery method. Defaults to None. + augmentation (:class:`Augmentation`): allows the equation solved in + this time discretisation to be augmented, for instances with + extra terms of another auxiliary variable. Defaults to None. """ butcher_matrix = np.array([ @@ -563,7 +580,8 @@ def __init__( subcycling_options=subcycling_options, rk_formulation=rk_formulation, solver_parameters=solver_parameters, - limiter=limiter, options=options) + limiter=limiter, options=options, + augmentation=augmentation) class RK4(ExplicitRungeKutta): @@ -584,7 +602,8 @@ class RK4(ExplicitRungeKutta): def __init__( self, domain, field_name=None, subcycling_options=None, rk_formulation=RungeKuttaFormulation.increment, - solver_parameters=None, limiter=None, options=None + solver_parameters=None, limiter=None, options=None, + augmentation=None ): """ Args: @@ -606,6 +625,9 @@ def __init__( options to either be passed to the spatial discretisation, or to control the "wrapper" methods, such as Embedded DG or a recovery method. Defaults to None. + augmentation (:class:`Augmentation`): allows the equation solved in + this time discretisation to be augmented, for instances with + extra terms of another auxiliary variable. Defaults to None. """ butcher_matrix = np.array([ [0.5, 0., 0., 0.], @@ -617,7 +639,8 @@ def __init__( subcycling_options=subcycling_options, rk_formulation=rk_formulation, solver_parameters=solver_parameters, - limiter=limiter, options=options) + limiter=limiter, options=options, + augmentation=augmentation) class Heun(ExplicitRungeKutta): @@ -636,7 +659,8 @@ class Heun(ExplicitRungeKutta): def __init__( self, domain, field_name=None, subcycling_options=None, rk_formulation=RungeKuttaFormulation.increment, - solver_parameters=None, limiter=None, options=None + solver_parameters=None, limiter=None, options=None, + augmentation=None ): """ Args: @@ -658,6 +682,9 @@ def __init__( options to either be passed to the spatial discretisation, or to control the "wrapper" methods, such as Embedded DG or a recovery method. Defaults to None. + augmentation (:class:`Augmentation`): allows the equation solved in + this time discretisation to be augmented, for instances with + extra terms of another auxiliary variable. Defaults to None. """ butcher_matrix = np.array([ @@ -668,4 +695,5 @@ def __init__( subcycling_options=subcycling_options, rk_formulation=rk_formulation, solver_parameters=solver_parameters, - limiter=limiter, options=options) + limiter=limiter, options=options, + augmentation=augmentation) diff --git a/gusto/time_discretisation/implicit_runge_kutta.py b/gusto/time_discretisation/implicit_runge_kutta.py index 8eb1c75ab..b220ef0be 100644 --- a/gusto/time_discretisation/implicit_runge_kutta.py +++ b/gusto/time_discretisation/implicit_runge_kutta.py @@ -56,7 +56,7 @@ class ImplicitRungeKutta(TimeDiscretisation): # --------------------------------------------------------------------------- def __init__(self, domain, butcher_matrix, field_name=None, - solver_parameters=None, options=None,): + solver_parameters=None, options=None, augmentation=None): """ Args: domain (:class:`Domain`): the model's domain object, containing the @@ -75,7 +75,7 @@ def __init__(self, domain, butcher_matrix, field_name=None, """ super().__init__(domain, field_name=field_name, solver_parameters=solver_parameters, - options=options) + options=options, augmentation=augmentation) self.butcher_matrix = butcher_matrix self.nStages = int(np.shape(self.butcher_matrix)[1]) @@ -165,7 +165,7 @@ class ImplicitMidpoint(ImplicitRungeKutta): y^(n+1) = y^n + dt*k0 \n """ def __init__(self, domain, field_name=None, solver_parameters=None, - options=None): + options=None, augmentation=None): """ Args: domain (:class:`Domain`): the model's domain object, containing the @@ -182,7 +182,7 @@ def __init__(self, domain, field_name=None, solver_parameters=None, butcher_matrix = np.array([[0.5], [1.]]) super().__init__(domain, butcher_matrix, field_name, solver_parameters=solver_parameters, - options=options) + options=options, augmentation=augmentation) class QinZhang(ImplicitRungeKutta): diff --git a/gusto/time_discretisation/sdc.py b/gusto/time_discretisation/sdc.py index 0fe0c9f29..257cc7f89 100644 --- a/gusto/time_discretisation/sdc.py +++ b/gusto/time_discretisation/sdc.py @@ -119,6 +119,9 @@ def __init__(self, base_scheme, domain, M, maxk, quad_type, node_type, qdelta_im self.formulation = formulation self.limiter = limiter + # TODO: this is to avoid an error in the underlying wrapper_apply decorator + self.augmentation = None + # Initialise wrappers if options is not None: self.wrapper_name = options.name @@ -135,7 +138,7 @@ def __init__(self, base_scheme, domain, M, maxk, quad_type, node_type, qdelta_im 'SDC: suboption SUPG is currently not implemented within MixedOptions') else: raise RuntimeError( - f'SDC: suboption wrapper {wrapper_name} not implemented') + f'SDC: suboption wrapper {self.wrapper_name} not implemented') elif self.wrapper_name == "embedded_dg": self.wrapper = EmbeddedDGWrapper(self, options) elif self.wrapper_name == "recovered": @@ -234,7 +237,7 @@ def setup(self, equation, apply_bcs=True, *active_labels): raise ValueError(f"The option defined for {field} is for a field that does not exist in the equation set") field_idx = equation.field_names.index(field) - subwrapper.setup(equation.spaces[Wrappersfield_idx]) + subwrapper.setup(equation.spaces[field_idx]) # Update the function space to that needed by the wrapper self.wrapper.wrapper_spaces[field_idx] = subwrapper.function_space diff --git a/gusto/time_discretisation/time_discretisation.py b/gusto/time_discretisation/time_discretisation.py index d7b4d4aab..daa3e2ad9 100644 --- a/gusto/time_discretisation/time_discretisation.py +++ b/gusto/time_discretisation/time_discretisation.py @@ -30,7 +30,17 @@ def wrapper_apply(original_apply): """Decorator to add steps for using a wrapper around the apply method.""" def get_apply(self, x_out, x_in): - if self.wrapper is not None: + if self.augmentation is not None: + + def new_apply(self, x_out, x_in): + + self.augmentation.pre_apply(x_in) + original_apply(self, self.augmentation.x_out, self.augmentation.x_in) + self.augmentation.post_apply(x_out) + + return new_apply(self, x_out, x_in) + + elif self.wrapper is not None: def new_apply(self, x_out, x_in): @@ -51,13 +61,17 @@ class TimeDiscretisation(object, metaclass=ABCMeta): """Base class for time discretisation schemes.""" def __init__(self, domain, field_name=None, subcycling_options=None, - solver_parameters=None, limiter=None, options=None): + solver_parameters=None, limiter=None, options=None, + augmentation=None): """ Args: domain (:class:`Domain`): the model's domain object, containing the mesh and the compatible function spaces. field_name (str, optional): name of the field to be evolved. Defaults to None. + subcycling_options(:class:`SubcyclingOptions`, optional): an object + containing options for subcycling the time discretisation. + Defaults to None. solver_parameters (dict, optional): dictionary of parameters to pass to the underlying solver. Defaults to None. limiter (:class:`Limiter` object, optional): a limiter to apply to @@ -66,6 +80,9 @@ def __init__(self, domain, field_name=None, subcycling_options=None, options to either be passed to the spatial discretisation, or to control the "wrapper" methods, such as Embedded DG or a recovery method. Defaults to None. + augmentation (:class:`Augmentation`): allows the equation solved in + this time discretisation to be augmented, for instances with + extra terms of another auxiliary variable. Defaults to None. """ self.domain = domain self.field_name = field_name @@ -78,7 +95,8 @@ def __init__(self, domain, field_name=None, subcycling_options=None, self.options = options self.limiter = limiter self.courant_max = None - self.subcycling_options = None + self.augmentation = augmentation + self.subcycling_options = subcycling_options if self.subcycling_options is not None: self.subcycling_options.check_options() @@ -159,6 +177,11 @@ def setup(self, equation, apply_bcs=True, *active_labels): self.fs = equation.function_space self.idx = None + if self.augmentation is not None: + self.fs = self.augmentation.fs + self.residual = self.augmentation.residual + self.idx = None + if len(active_labels) > 0: if isinstance(self.field_name, list): # Multiple fields are being solved for simultaneously. @@ -179,6 +202,7 @@ def setup(self, equation, apply_bcs=True, *active_labels): map_if_false=drop) self.residual = residual + else: self.residual = self.residual.label_map( lambda t: any(t.has_label(time_derivative, *active_labels)), @@ -188,7 +212,11 @@ def setup(self, equation, apply_bcs=True, *active_labels): if isinstance(self.field_name, list): self.field_name = equation.field_name - bcs = equation.bcs[self.field_name] + if self.augmentation is not None: + # Transfer BCs from appropriate function space + bcs = self.augmentation.bcs if hasattr(self.augmentation, "bcs") else None + else: + bcs = equation.bcs[self.field_name] self.evaluate_source = [] self.physics_names = [] @@ -204,8 +232,16 @@ def setup(self, equation, apply_bcs=True, *active_labels): for field in equation.field_names: # Check if the mass term for this prognostic is mass-weighted - if len(self.residual.label_map(lambda t: t.get(prognostic) == field and t.has_label(time_derivative) and t.has_label(mass_weighted), map_if_false=drop)) == 1: - field_terms = self.residual.label_map(lambda t: t.get(prognostic) == field and not t.has_label(time_derivative), map_if_false=drop) + if len(self.residual.label_map(( + lambda t: t.get(prognostic) == field + and t.has_label(time_derivative) + and t.has_label(mass_weighted) + ), map_if_false=drop)) == 1: + + field_terms = self.residual.label_map( + lambda t: t.get(prognostic) == field and not t.has_label(time_derivative), + map_if_false=drop + ) # Check that the equation for this prognostic does not involve # both mass-weighted and non-mass-weighted terms; if so, a split @@ -407,7 +443,8 @@ class ExplicitTimeDiscretisation(TimeDiscretisation): """Base class for explicit time discretisations.""" def __init__(self, domain, field_name=None, subcycling_options=None, - solver_parameters=None, limiter=None, options=None): + solver_parameters=None, limiter=None, options=None, + augmentation=None): """ Args: domain (:class:`Domain`): the model's domain object, containing the @@ -425,11 +462,15 @@ def __init__(self, domain, field_name=None, subcycling_options=None, options to either be passed to the spatial discretisation, or to control the "wrapper" methods, such as Embedded DG or a recovery method. Defaults to None. + augmentation (:class:`Augmentation`): allows the equation solved in + this time discretisation to be augmented, for instances with + extra terms of another auxiliary variable. Defaults to None. """ super().__init__(domain, field_name, subcycling_options=subcycling_options, solver_parameters=solver_parameters, - limiter=limiter, options=options) + limiter=limiter, options=options, + augmentation=augmentation) # get default solver options if none passed in if solver_parameters is None: @@ -457,12 +498,11 @@ def setup(self, equation, apply_bcs=True, *active_labels): # and rescale dt accordingly; else perform just one cycle using dt if (self.subcycling_options is not None and self.subcycling_options.fixed_subcycles is not None): - fixed_subcycles = self.subcycling_options.fixed_subcycles - self.dt.assign(self.dt/fixed_subcycles) - self.ncycles = self.fixed_subcycles + self.ncycles = self.subcycling_options.fixed_subcycles + self.dt.assign(self.dt/self.ncycles) else: - self.dt = self.dt self.ncycles = 1 + self.dt = self.dt self.x0 = Function(self.fs) self.x1 = Function(self.fs) @@ -536,7 +576,8 @@ class BackwardEuler(TimeDiscretisation): y^(n+1) = y^n + dt*F[y^(n+1)]. \n """ def __init__(self, domain, field_name=None, subcycling_options=None, - solver_parameters=None, limiter=None, options=None): + solver_parameters=None, limiter=None, options=None, + augmentation=None): """ Args: domain (:class:`Domain`): the model's domain object, containing the @@ -553,7 +594,10 @@ def __init__(self, domain, field_name=None, subcycling_options=None, options (:class:`AdvectionOptions`, optional): an object containing options to either be passed to the spatial discretisation, or to control the "wrapper" methods. Defaults to None. - """ + augmentation (:class:`Augmentation`): allows the equation solved in + this time discretisation to be augmented, for instances with + extra terms of another auxiliary variable. Defaults to None. + """ if not solver_parameters: # default solver parameters solver_parameters = {'ksp_type': 'gmres', @@ -562,7 +606,8 @@ def __init__(self, domain, field_name=None, subcycling_options=None, super().__init__(domain=domain, field_name=field_name, subcycling_options=subcycling_options, solver_parameters=solver_parameters, - limiter=limiter, options=options) + limiter=limiter, options=options, + augmentation=augmentation) def setup(self, equation, apply_bcs=True, *active_labels): """ @@ -658,7 +703,7 @@ class ThetaMethod(TimeDiscretisation): """ def __init__(self, domain, theta, field_name=None, subcycling_options=None, - solver_parameters=None, options=None): + solver_parameters=None, options=None, augmentation=None): """ Args: domain (:class:`Domain`): the model's domain object, containing the @@ -676,6 +721,9 @@ def __init__(self, domain, theta, field_name=None, subcycling_options=None, options to either be passed to the spatial discretisation, or to control the "wrapper" methods, such as Embedded DG or a recovery method. Defaults to None. + augmentation (:class:`Augmentation`): allows the equation solved in + this time discretisation to be augmented, for instances with + extra terms of another auxiliary variable. Defaults to None. Raises: ValueError: if theta is not provided. @@ -694,7 +742,8 @@ def __init__(self, domain, theta, field_name=None, subcycling_options=None, super().__init__(domain, field_name, subcycling_options=subcycling_options, solver_parameters=solver_parameters, - options=options) + options=options, + augmentation=augmentation) self.theta = theta @@ -771,6 +820,8 @@ def apply(self, x_out, x_in): x_in (:class:`Function`): the input field. """ self.update_subcycling() + if self.augmentation is not None: + self.augmentation.update(x_in) self.x0.assign(x_in) for i in range(self.ncycles): @@ -791,7 +842,7 @@ class TrapeziumRule(ThetaMethod): """ def __init__(self, domain, field_name=None, subcycling_options=None, - solver_parameters=None, options=None): + solver_parameters=None, options=None, augmentation=None): """ Args: domain (:class:`Domain`): the model's domain object, containing the @@ -804,11 +855,14 @@ def __init__(self, domain, field_name=None, subcycling_options=None, options to either be passed to the spatial discretisation, or to control the "wrapper" methods, such as Embedded DG or a recovery method. Defaults to None. + augmentation (:class:`Augmentation`): allows the equation solved in + this time discretisation to be augmented, for instances with + extra terms of another auxiliary variable. Defaults to None. """ super().__init__(domain, 0.5, field_name, subcycling_options=subcycling_options, solver_parameters=solver_parameters, - options=options) + options=options, augmentation=augmentation) class TR_BDF2(TimeDiscretisation): diff --git a/integration-tests/conftest.py b/integration-tests/conftest.py index b0508aae3..02b1addfc 100644 --- a/integration-tests/conftest.py +++ b/integration-tests/conftest.py @@ -25,7 +25,7 @@ def tracer_sphere(tmpdir, degree, small_dt): # Parameters chosen so that dt != 1 # Gaussian is translated from (lon=pi/2, lat=0) to (lon=0, lat=0) # to demonstrate that transport is working correctly - if (small_dt): + if small_dt: dt = pi/3. * 0.005 else: dt = pi/3. * 0.02 @@ -47,7 +47,7 @@ def tracer_sphere(tmpdir, degree, small_dt): uexpr, umax, radius, tol) -def tracer_slice(tmpdir, degree): +def tracer_slice(tmpdir, degree, small_dt): n = 30 if degree == 0 else 15 m = PeriodicIntervalMesh(n, 1.) mesh = ExtrudedMesh(m, layers=n, layer_height=1./n) @@ -56,7 +56,10 @@ def tracer_slice(tmpdir, degree): # Gaussian is translated by 1.5 times width of domain to demonstrate # that transport is working correctly - dt = 0.01 + if small_dt: + dt = 0.002 + else: + dt = 0.01 tmax = 0.75 output = OutputParameters(dirname=str(tmpdir), dumpfreq=25) domain = Domain(mesh, dt, family="CG", degree=degree) @@ -80,8 +83,11 @@ def tracer_slice(tmpdir, degree): return TracerSetup(domain, tmax, io, f_init, f_end, degree, uexpr, tol=tol) -def tracer_blob_slice(tmpdir, degree): - dt = 0.01 +def tracer_blob_slice(tmpdir, degree, small_dt): + if small_dt: + dt = 0.002 + else: + dt = 0.01 L = 10. m = PeriodicIntervalMesh(10, L) mesh = ExtrudedMesh(m, layers=10, layer_height=1.) @@ -105,10 +111,9 @@ def _tracer_setup(tmpdir, geometry, blob=False, degree=1, small_dt=False): assert not blob return tracer_sphere(tmpdir, degree, small_dt) elif geometry == "slice": - assert not small_dt if blob: - return tracer_blob_slice(tmpdir, degree) + return tracer_blob_slice(tmpdir, degree, small_dt) else: - return tracer_slice(tmpdir, degree) + return tracer_slice(tmpdir, degree, small_dt) return _tracer_setup diff --git a/integration-tests/data/sw_fplane_chkpt.h5 b/integration-tests/data/sw_fplane_chkpt.h5 index b752f0d70b6dd93f09b0d569d7c88e8fcb001525..7c41f9ebad6f45d77e1f4a22856c7b0edf54c780 100644 GIT binary patch delta 182943 zcmZs?cRbhM`#(-LQASCLLZQ-&Pa?Jqs3i*r|U zJqwZ5ec?hJ!+4?|6`FTTf9?r|7BU< zy>R9q>wjjgzsAq}uW3p3%W};BHlY5P4>R@rKO++BqkEYD@cd(v>QzSnKb=D)*VtVA z=js3ce74V;9I^jvtMAQN)4ccp%>Vws>s7ke6ifVHTfN7JHFq`tF-i3w_OkGu{f}Fl ze()A!Z(|+@pQwL(i)E7eUt_!iS=e>|^BCGA7NW@e^{h7MPH5?`k@~me`mdua3+Q2C z7SYdmVEZ2*r>FO_jI-`}U}jeD*~jvC)4yiiImR%>Zp7q~%aV3D&?0n3Zi{Iy6#x%~T++-1$U)o&>lI$auG;495twu3N zycv^IJZ1>*O3_?sWYPCY8=l**vSHv+9bQdjnygmuK*_gnLx(KMxMXD zX-^=KF=?Z>mvde#wz=u)C|sbS z9zIXY)hUM=1rgIUoecc?r|+l@fj1B8un&8H?CO~pmx!+RnLqacs&yxc*30r!fB=@)N6Fen2DEsmYxZm1`$kA;&h<@T;nky zl>$bbSLFlDDbPF@CUNz0ICvQSev)cQfhZfl?{AOT;)$}0!i3Q`L|{5AaduuU5jo!N 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zIjKOvebwUeer$IK^~?Ap38^y&1U|#S8hw6>H^_MSRq6BwsIHDs_vOam0^|3r6^G&5 zB+f*vHyRXJ+p9+f#2So4>E!o6bH5Mi%p>{qJoo5iqoNSiMXy}!*Qn3EA=i*nlje%c zp+bv&TAJiX>#XI?UX7uF+bMIN#ea{N`z|gM zSocHId>F~4>+Y5SA9>s$#LSO-Vn4UH&*L(nUg8&Z=RrKkRzJiD22$#5hchKO&Ra4! z+=2#})&5>JrG%GJm25S>p!}MI#{IDNUI++n(ES==jNfS;uM)}5>q^NjPtGGv zf3Y{F{U%%GlO_Cq72oM9_bTgR;Uvo+|NYGoHnt%DqrYUWzEjn$PZ2N|!S3<@`lDZX zCUk{PT%wrruP&XJptoM4g#FJsGYOO^dUrg_)n*qQC~aWdbGb|DD*&uRSii oiJmebC|@<5NYNAg(Ufhel%8!rnu7nX(H+(cQ>&^QDBYL-1MdUW2><{9 diff --git a/integration-tests/equations/test_sw_fplane.py b/integration-tests/equations/test_sw_fplane.py index 8e0779c2b..3d0acff5f 100644 --- a/integration-tests/equations/test_sw_fplane.py +++ b/integration-tests/equations/test_sw_fplane.py @@ -38,10 +38,12 @@ def run_sw_fplane(tmpdir): io = IO(domain, output, diagnostic_fields=[CourantNumber()]) # Transport schemes - transported_fields = [TrapeziumRule(domain, "u"), - SSPRK3(domain, "D")] - transport_methods = [DGUpwind(eqns, "u"), - DGUpwind(eqns, "D")] + vorticity_transport = VorticityTransport(domain, eqns, supg=True) + transported_fields = [ + TrapeziumRule(domain, "u", augmentation=vorticity_transport), + SSPRK3(domain, "D") + ] + transport_methods = [DGUpwind(eqns, "u"), DGUpwind(eqns, "D")] # Time stepper stepper = SemiImplicitQuasiNewton(eqns, io, transported_fields, diff --git a/integration-tests/transport/test_vector_recovered_space.py b/integration-tests/transport/test_vector_recovered_space.py index 54c951cd7..9f6dd773f 100644 --- a/integration-tests/transport/test_vector_recovered_space.py +++ b/integration-tests/transport/test_vector_recovered_space.py @@ -15,6 +15,9 @@ def run(timestepper, tmax, f_end): return norm(timestepper.fields("f") - f_end) / norm(f_end) +# NB: The default vector transport test is not valid on the sphere as it is +# designed for a 3-component vector function space, and not the space of tangent +# vectors on the sphere @pytest.mark.parametrize("geometry", ["slice"]) def test_vector_recovered_space_setup(tmpdir, geometry, tracer_setup): diff --git a/integration-tests/transport/test_vorticity_transport.py b/integration-tests/transport/test_vorticity_transport.py new file mode 100644 index 000000000..1cd9bdcbb --- /dev/null +++ b/integration-tests/transport/test_vorticity_transport.py @@ -0,0 +1,111 @@ +""" +This tests the transport of a vector-valued field using vorticity augmentation. +The computed solution is compared with a true one to check that the transport +is working correctly. +""" + +from gusto import * +from firedrake import ( + as_vector, norm, exp, PeriodicRectangleMesh, SpatialCoordinate, min_value +) +import pytest + + +def run(timestepper, tmax, f_end): + timestepper.run(0, tmax) + + return norm(timestepper.fields("f") - f_end) / norm(f_end) + + +@pytest.mark.parametrize("supg", [False, True]) +def test_vorticity_transport_setup(tmpdir, supg): + + # ------------------------------------------------------------------------ # + # Parameters for test case + # ------------------------------------------------------------------------ # + + Lx = 2000. # length of domain in x direction, in m + Ly = 2000. # width of domain in y direction, in m + ncells_1d = 20 # number of points in x and y directions + tmax = 500. + degree = 1 + + if supg: + # Smaller time steps for RK scheme + dt = 5.0 + dumpfreq = 50 + else: + dt = 25.0 + dumpfreq = 10 + + # ------------------------------------------------------------------------ # + # Set up model objects + # ------------------------------------------------------------------------ # + + mesh = PeriodicRectangleMesh(ncells_1d, ncells_1d, Lx, Ly, quadrilateral=True) + domain = Domain(mesh, dt, "RTCF", degree) + x, y = SpatialCoordinate(mesh) + + Vu = domain.spaces("HDiv") + + # Equation + eqn = AdvectionEquation(domain, Vu, "f") + + # I/O + dirname = f'{tmpdir}/vorticity_plane' + output = OutputParameters( + dirname=dirname, dumpfreq=dumpfreq, dump_nc=False, dump_vtus=True + ) + io = IO(domain, output) + + augmentation = VorticityTransport(domain, eqn, supg=supg) + + # Make equation + if supg: + transport_scheme = SSPRK3( + domain, augmentation=augmentation, + rk_formulation=RungeKuttaFormulation.predictor + ) + else: + transport_scheme = TrapeziumRule(domain, augmentation=augmentation) + transport_method = DGUpwind(eqn, "f") + + time_varying_velocity = False + timestepper = PrescribedTransport( + eqn, transport_scheme, io, time_varying_velocity, transport_method + ) + + # ------------------------------------------------------------------------ # + # Initial conditions + # ------------------------------------------------------------------------ # + + # Specify locations of the two Gaussians + xc = Lx/2. + xend = 3.*Lx/4. + yc = Ly/2. + + def l2_dist(xc, yc): + return min_value(abs(x - xc), Lx - abs(x - xc))**2 + (y - yc)**2 + + f0 = 1. + lc = 4.*Lx/25. + + init_scalar_expr = f0*exp(-l2_dist(xc, yc)/lc**2) + uexpr = as_vector([1.0, 0.0]) + + # Set fields + f = timestepper.fields("f") + f.project(as_vector([init_scalar_expr, init_scalar_expr])) + + u0 = timestepper.fields("u") + u0.project(uexpr) + + final_scalar_expr = f0*exp(-l2_dist(xend, yc)/lc**2) + final_vector_expr = as_vector([final_scalar_expr, final_scalar_expr]) + + # Run and check error + error = run(timestepper, tmax, final_vector_expr) + + tol = 1e-1 + assert error < tol, \ + 'The transport error is greater than the permitted tolerance' From c8527057315a5af50b730eb1c4bc1e340454fa76 Mon Sep 17 00:00:00 2001 From: Stephen Hughes <145994505+12shughes@users.noreply.github.com> Date: Wed, 18 Dec 2024 14:31:58 +0000 Subject: [PATCH 2/7] add cumulative sum diagnostic (#600) Co-authored-by: Dr Jemma Shipton --- gusto/diagnostics/diagnostics.py | 43 ++++++++++++++++- .../diagnostic_tests/test_cumulative_sum.py | 48 +++++++++++++++++++ 2 files changed, 90 insertions(+), 1 deletion(-) create mode 100644 unit-tests/diagnostic_tests/test_cumulative_sum.py diff --git a/gusto/diagnostics/diagnostics.py b/gusto/diagnostics/diagnostics.py index b287d6d36..69c053d45 100644 --- a/gusto/diagnostics/diagnostics.py +++ b/gusto/diagnostics/diagnostics.py @@ -21,7 +21,8 @@ "XComponent", "YComponent", "ZComponent", "MeridionalComponent", "ZonalComponent", "RadialComponent", "Energy", "KineticEnergy", "Sum", "Difference", "SteadyStateError", "Perturbation", - "Divergence", "TracerDensity", "IterativeDiagnosticField"] + "Divergence", "TracerDensity", "IterativeDiagnosticField", + "CumulativeSum"] class Diagnostics(object): @@ -1040,3 +1041,43 @@ def setup(self, domain, state_fields): else: super().setup(domain, state_fields) + + +class CumulativeSum(DiagnosticField): + """Base diagnostic for cumulatively summing a field in time.""" + def __init__(self, name): + """ + Args: + name (str): name of the field to take the cumulative sum of. + """ + self.field_name = name + self.integral_name = name+"_cumulative" + super().__init__(self, method='assign', required_fields=(self.field_name,)) + + def setup(self, domain, state_fields): + """ + Sets up the :class:`Function` for the diagnostic field. + + Args: + domain (:class:`Domain`): the model's domain object. + state_fields (:class:`StateFields`): the model's field container. + """ + + # Gather the field to be summed + self.integrand = state_fields(self.field_name) + self.space = self.integrand.function_space() + + # Create a new field to store the cumulative sum + self.field = state_fields(self.integral_name, space=self.space, dump=True, pick_up=True) + # Initialise the new field to zero, if picking up from a checkpoint + # file the original cumulative field will load and not be overwritten. + self.field.assign(0.0) + + def compute(self): + """Increment the cumulative sum diagnostic.""" + self.field.assign(self.field + self.integrand) + + @property + def name(self): + """Gives the name of this diagnostic field.""" + return self.integral_name diff --git a/unit-tests/diagnostic_tests/test_cumulative_sum.py b/unit-tests/diagnostic_tests/test_cumulative_sum.py new file mode 100644 index 000000000..295e522ca --- /dev/null +++ b/unit-tests/diagnostic_tests/test_cumulative_sum.py @@ -0,0 +1,48 @@ + +from gusto.diagnostics import CumulativeSum +from gusto.core.fields import StateFields, PrescribedFields, TimeLevelFields +from gusto import (Domain, CompressibleParameters, CompressibleEulerEquations, + WaterVapour) +from firedrake import PeriodicIntervalMesh, ExtrudedMesh +import numpy as np + + +def test_dewpoint(): + + L = 10 + H = 10 + ncol = 3 + nlayers = 3 + + m = PeriodicIntervalMesh(ncol, L) + mesh = ExtrudedMesh(m, layers=nlayers, layer_height=H/nlayers) + + domain = Domain(mesh, 0.1, 'CG', 1) + params = CompressibleParameters() + active_tracers = [WaterVapour()] + eqn = CompressibleEulerEquations(domain, params, active_tracers=active_tracers) + prog_fields = TimeLevelFields(eqn) + + Vtheta = domain.spaces('theta') + + # Setting up prognostic fields for the diagnostic to use + prescribed_fields = PrescribedFields() + state_fields = StateFields(prog_fields, prescribed_fields) + + theta = state_fields('theta', Vtheta) + + # Initial conditions + theta.interpolate(300.0) + + diagnostic = CumulativeSum(name='theta') + diagnostic.setup(domain, state_fields) + diagnostic.compute() + + assert np.allclose(diagnostic.field.dat.data, 300.0, atol=0.0), \ + 'The cumulative sum diagnostic does not seem to be correct after 1 iteration' + + theta.interpolate(250.0) + diagnostic.compute() + + assert np.allclose(diagnostic.field.dat.data, 550.0, atol=0.0), \ + 'The cumulative sum diagnostic does not seem to be correct after 2 iterations' From 3eaecc525e2fd097ea48a49eba32fac5ab81fc26 Mon Sep 17 00:00:00 2001 From: Alex Brown <81297297+atb1995@users.noreply.github.com> Date: Wed, 18 Dec 2024 15:50:39 +0000 Subject: [PATCH 3/7] SDC: Fix wrapper and augmentation + Add in MIN-SR-FLEX (#602) --- gusto/time_discretisation/sdc.py | 114 ++++++------------------------- 1 file changed, 21 insertions(+), 93 deletions(-) diff --git a/gusto/time_discretisation/sdc.py b/gusto/time_discretisation/sdc.py index 257cc7f89..234f0c7b9 100644 --- a/gusto/time_discretisation/sdc.py +++ b/gusto/time_discretisation/sdc.py @@ -46,14 +46,12 @@ from abc import ABCMeta import numpy as np from firedrake import ( - Function, NonlinearVariationalProblem, TestFunction, TestFunctions, - NonlinearVariationalSolver, Constant + Function, NonlinearVariationalProblem, NonlinearVariationalSolver, Constant ) from firedrake.fml import ( - replace_subject, replace_test_function, all_terms, drop + replace_subject, all_terms, drop ) from firedrake.utils import cached_property -from gusto.time_discretisation.wrappers import * from gusto.time_discretisation.time_discretisation import wrapper_apply from gusto.core.labels import (time_derivative, implicit, explicit) @@ -118,39 +116,8 @@ def __init__(self, base_scheme, domain, M, maxk, quad_type, node_type, qdelta_im self.final_update = final_update self.formulation = formulation self.limiter = limiter - - # TODO: this is to avoid an error in the underlying wrapper_apply decorator - self.augmentation = None - - # Initialise wrappers - if options is not None: - self.wrapper_name = options.name - if self.wrapper_name == "mixed_options": - self.wrapper = MixedFSWrapper() - - for field, suboption in options.suboptions.items(): - if suboption.name == 'embedded_dg': - self.wrapper.subwrappers.update({field: EmbeddedDGWrapper(self, suboption)}) - elif suboption.name == "recovered": - self.wrapper.subwrappers.update({field: RecoveryWrapper(self, suboption)}) - elif suboption.name == "supg": - raise RuntimeError( - 'SDC: suboption SUPG is currently not implemented within MixedOptions') - else: - raise RuntimeError( - f'SDC: suboption wrapper {self.wrapper_name} not implemented') - elif self.wrapper_name == "embedded_dg": - self.wrapper = EmbeddedDGWrapper(self, options) - elif self.wrapper_name == "recovered": - self.wrapper = RecoveryWrapper(self, options) - elif self.wrapper_name == "supg": - self.wrapper = SUPGWrapper(self, options) - else: - raise RuntimeError( - f'SDC: wrapper {self.wrapper_name} not implemented') - else: - self.wrapper = None - self.wrapper_name = None + self.augmentation = self.base.augmentation + self.wrapper = self.base.wrapper # Get quadrature nodes and weights self.nodes, self.weights, self.Q = genQCoeffs("Collocation", nNodes=M, @@ -163,6 +130,10 @@ def __init__(self, base_scheme, domain, M, maxk, quad_type, node_type, qdelta_im self.dtau = np.diff(np.append(0, self.nodes)) self.Q = float(self.dt_coarse)*self.Q self.Qfin = float(self.dt_coarse)*self.weights + self.qdelta_imp_type = qdelta_imp + self.formulation = formulation + self.node_type = node_type + self.quad_type = quad_type # Get Q_delta matrices self.Qdelta_imp = genQDeltaCoeffs(qdelta_imp, form=formulation, @@ -216,62 +187,6 @@ def setup(self, equation, apply_bcs=True, *active_labels): and (not t.has_label(time_derivative))): raise NotImplementedError("Non time-derivative terms must be labeled as implicit or explicit") - # Check we are not using wrappers for implicit schemes - if (t.has_label(implicit) and self.wrapper is not None): - raise NotImplementedError("Implicit terms not supported with wrappers") - - # Check we are not using limiters for implicit schemes - if (t.has_label(implicit) and self.limiter is not None): - raise NotImplementedError("Implicit terms not supported with limiters") - - # Set up Wrappers - if self.wrapper is not None: - if self.wrapper_name == "mixed_options": - - self.wrapper.wrapper_spaces = equation.spaces - self.wrapper.field_names = equation.field_names - - for field, subwrapper in self.wrapper.subwrappers.items(): - - if field not in equation.field_names: - raise ValueError(f"The option defined for {field} is for a field that does not exist in the equation set") - - field_idx = equation.field_names.index(field) - subwrapper.setup(equation.spaces[field_idx]) - - # Update the function space to that needed by the wrapper - self.wrapper.wrapper_spaces[field_idx] = subwrapper.function_space - - self.wrapper.setup() - self.fs = self.wrapper.function_space - new_test_mixed = TestFunctions(self.fs) - - # Replace the original test function with one from the new - # function space defined by the subwrappers - self.residual = self.residual.label_map( - all_terms, - map_if_true=replace_test_function(new_test_mixed)) - - else: - if self.wrapper_name == "supg": - self.wrapper.setup() - else: - self.wrapper.setup(self.fs) - self.fs = self.wrapper.function_space - if self.solver_parameters is None: - self.solver_parameters = self.wrapper.solver_parameters - new_test = TestFunction(self.wrapper.test_space) - # SUPG has a special wrapper - if self.wrapper_name == "supg": - new_test = self.wrapper.test - - # Replace the original test function with the one from the wrapper - self.residual = self.residual.label_map( - all_terms, - map_if_true=replace_test_function(new_test)) - - self.residual = self.wrapper.label_terms(self.residual) - # Set up bcs self.bcs = self.base.bcs @@ -483,6 +398,19 @@ def apply(self, x_out, x_in): while k < self.maxk: k += 1 + if self.qdelta_imp_type == "MIN-SR-FLEX": + # Recompute Implicit Q_delta matrix for each iteration k + self.Qdelta_imp = genQDeltaCoeffs( + self.qdelta_imp_type, + form=self.formulation, + nodes=self.nodes, + Q=self.Q, + nNodes=self.M, + nodeType=self.node_type, + quadType=self.quad_type, + k=k + ) + # Compute for N2N: sum(j=1,M) (s_mj*F(y_m^k) + s_mj*S(y_m^k)) # for Z2N: sum(j=1,M) (q_mj*F(y_m^k) + q_mj*S(y_m^k)) for m in range(1, self.M+1): From d573de5fd9c113d18f95ef5763e540172c99bcca Mon Sep 17 00:00:00 2001 From: Jack Betteridge <43041811+JDBetteridge@users.noreply.github.com> Date: Wed, 18 Dec 2024 16:53:17 +0000 Subject: [PATCH 4/7] Cancels jobs running if new commits are pushed (#605) --- .github/workflows/build.yml | 7 +++++++ 1 file changed, 7 insertions(+) diff --git a/.github/workflows/build.yml b/.github/workflows/build.yml index 110405818..fe0e49a28 100644 --- a/.github/workflows/build.yml +++ b/.github/workflows/build.yml @@ -11,6 +11,13 @@ on: # Scheduled build at 0330 UTC on Monday mornings to detect bitrot. - cron: '30 3 * * 1' +concurrency: + # Cancels jobs running if new commits are pushed + group: > + ${{ github.workflow }}- + ${{ github.event.pull_request.number || github.ref }} + cancel-in-progress: true + jobs: build: name: "Build Gusto" From a1d5959f2ec60a574882326c5fea92f7069e6db9 Mon Sep 17 00:00:00 2001 From: Josh Hope-Collins Date: Wed, 18 Dec 2024 19:13:07 +0000 Subject: [PATCH 5/7] Prevent unnecessary refactorisations when matrices haven't changed (#569) --- gusto/core/function_spaces.py | 156 ++++++++++++++---- .../compressible_euler_diagnostics.py | 9 +- gusto/diagnostics/diagnostics.py | 3 +- .../diagnostics/shallow_water_diagnostics.py | 5 +- gusto/solvers/__init__.py | 3 +- gusto/solvers/linear_solvers.py | 75 ++++++--- gusto/solvers/parameters.py | 99 +++++++++++ .../time_discretisation.py | 23 +-- gusto/time_discretisation/wrappers.py | 24 +-- .../semi_implicit_quasi_newton.py | 6 +- .../data/boussinesq_compressible_chkpt.h5 | Bin 240842 -> 240842 bytes .../data/boussinesq_incompressible_chkpt.h5 | Bin 240842 -> 240842 bytes .../data/dry_compressible_chkpt.h5 | Bin 241020 -> 241020 bytes .../data/linear_sw_wave_chkpt.h5 | Bin 580789 -> 580789 bytes .../data/moist_compressible_chkpt.h5 | Bin 269984 -> 269984 bytes .../data/simult_SIQN_order0_chkpt.h5 | Bin 312258 -> 312258 bytes .../data/simult_SIQN_order1_chkpt.h5 | Bin 279330 -> 279330 bytes integration-tests/data/sw_fplane_chkpt.h5 | Bin 937363 -> 937363 bytes unit-tests/test_function_spaces.py | 42 +++++ 19 files changed, 355 insertions(+), 90 deletions(-) create mode 100644 gusto/solvers/parameters.py diff --git a/gusto/core/function_spaces.py b/gusto/core/function_spaces.py index 97820d454..c83a15cd6 100644 --- a/gusto/core/function_spaces.py +++ b/gusto/core/function_spaces.py @@ -4,8 +4,8 @@ """ from gusto.core.logging import logger -from firedrake import (HCurl, HDiv, FunctionSpace, FiniteElement, - TensorProductElement, interval) +from firedrake import (HCurl, HDiv, FunctionSpace, FiniteElement, VectorElement, + TensorProductElement, BrokenElement, interval) __all__ = ["Spaces", "check_degree_args"] @@ -71,6 +71,7 @@ def __init__(self, mesh): self.mesh = mesh self.extruded_mesh = hasattr(mesh, "_base_mesh") self.de_rham_complex = {} + self.continuity = {} def __call__(self, name): """ @@ -89,7 +90,7 @@ def __call__(self, name): else: raise ValueError(f'The space container has no space {name}') - def add_space(self, name, space, overwrite_space=False): + def add_space(self, name, space, overwrite_space=False, continuity=None): """ Adds a function space to the container. @@ -100,6 +101,10 @@ def add_space(self, name, space, overwrite_space=False): overwrite_space (bool, optional): Logical to allow space existing in container to be overwritten by an incoming space. Defaults to False. + continuity: Whether the space is continuous or not. For spaces on + extruded meshes, must be a dictionary with entries for the + 'horizontal' and 'vertical' continuity. + If None, defaults to value of is_cg(space). """ if hasattr(self, name) and not overwrite_space: @@ -109,9 +114,28 @@ def add_space(self, name, space, overwrite_space=False): setattr(self, name, space) - def create_space(self, name, family, degree, overwrite_space=False): + # set the continuity of the space - for extruded meshes specify both directions + if continuity is None: + continuity = is_cg(space) + if self.extruded_mesh: + self.continuity[name] = { + 'horizontal': continuity, + 'vertical': continuity + } + else: + self.continuity[name] = continuity + else: + if self.extruded_mesh: + self.continuity[name] = { + 'horizontal': continuity['horizontal'], + 'vertical': continuity['vertical'] + } + else: + self.continuity[name] = continuity + + def create_space(self, name, family, degree, overwrite_space=False, continuity=None): """ - Creates a space and adds it to the container.. + Creates a space and adds it to the container. Args: name (str): the name to give to the space. @@ -120,18 +144,18 @@ def create_space(self, name, family, degree, overwrite_space=False): overwrite_space (bool, optional): Logical to allow space existing in container to be overwritten by an incoming space. Defaults to False. + continuity: Whether the space is continuous or not. For spaces on + extruded meshes, must be a tuple for the (horizontal, vertical) + continuity. If None, defaults to value of is_cg(space). Returns: :class:`FunctionSpace`: the desired function space. """ - - if hasattr(self, name) and not overwrite_space: - raise RuntimeError(f'Space {name} already exists. If you really ' - + 'to create it then set `overwrite_space` as ' - + 'to be True') - space = FunctionSpace(self.mesh, family, degree, name=name) - setattr(self, name, space) + + self.add_space(name, space, + overwrite_space=overwrite_space, + continuity=continuity) return space def build_compatible_spaces(self, family, horizontal_degree, @@ -181,9 +205,15 @@ def build_compatible_spaces(self, family, horizontal_degree, setattr(self, "L2"+complex_name, de_rham_complex.L2) # Register L2 space as DG also setattr(self, "DG"+complex_name, de_rham_complex.L2) - if hasattr(de_rham_complex, "theta"+complex_name): + if hasattr(de_rham_complex, "theta"): setattr(self, "theta"+complex_name, de_rham_complex.theta) + # Grab the continuity information from the complex + for space_type in ("H1, HCurl", "HDiv", "L2", "DG", "theta"): + space_name = space_type + complex_name + if hasattr(de_rham_complex, space_type): + self.continuity[space_name] = de_rham_complex.continuity[space_type] + def build_dg1_equispaced(self): """ Builds the equispaced variant of the DG1 function space, which is used in @@ -198,12 +228,15 @@ def build_dg1_equispaced(self): hori_elt = FiniteElement('DG', cell, 1, variant='equispaced') vert_elt = FiniteElement('DG', interval, 1, variant='equispaced') V_elt = TensorProductElement(hori_elt, vert_elt) + continuity = {'horizontal': False, 'vertical': False} else: cell = self.mesh.ufl_cell().cellname() V_elt = FiniteElement('DG', cell, 1, variant='equispaced') + continuity = False space = FunctionSpace(self.mesh, V_elt, name='DG1_equispaced') - setattr(self, 'DG1_equispaced', space) + + self.add_space('DG1_equispaced', space, continuity=continuity) return space @@ -234,6 +267,7 @@ def __init__(self, mesh, family, horizontal_degree, vertical_degree=None, self.extruded_mesh = hasattr(mesh, '_base_mesh') self.family = family self.complex_name = complex_name + self.continuity = {} self.build_base_spaces(family, horizontal_degree, vertical_degree) self.build_compatible_spaces() @@ -303,15 +337,24 @@ def build_compatible_spaces(self): if self.extruded_mesh: # Horizontal and vertical degrees # need specifying separately. Vtheta needs returning. - Vcg = self.build_h1_space() + Vcg, continuity = self.build_h1_space() + self.continuity["H1"] = continuity setattr(self, "H1", Vcg) - Vcurl = self.build_hcurl_space() + + Vcurl, continuity = self.build_hcurl_space() + self.continuity["HCurl"] = continuity setattr(self, "HCurl", Vcurl) - Vu = self.build_hdiv_space() + + Vu, continuity = self.build_hdiv_space() + self.continuity["HDiv"] = continuity setattr(self, "HDiv", Vu) - Vdg = self.build_l2_space() + + Vdg, continuity = self.build_l2_space() + self.continuity["L2"] = continuity setattr(self, "L2", Vdg) - Vth = self.build_theta_space() + + Vth, continuity = self.build_theta_space() + self.continuity["theta"] = continuity setattr(self, "theta", Vth) return Vcg, Vcurl, Vu, Vdg, Vth @@ -320,13 +363,20 @@ def build_compatible_spaces(self): # 2D: two de Rham complexes (hcurl or hdiv) with 3 spaces # 3D: one de Rham complexes with 4 spaces # either way, build all spaces - Vcg = self.build_h1_space() + Vcg, continuity = self.build_h1_space() + self.continuity["H1"] = continuity setattr(self, "H1", Vcg) - Vcurl = self.build_hcurl_space() + + Vcurl, continuity = self.build_hcurl_space() + self.continuity["HCurl"] = continuity setattr(self, "HCurl", Vcurl) - Vu = self.build_hdiv_space() + + Vu, continuity = self.build_hdiv_space() + self.continuity["HDiv"] = continuity setattr(self, "HDiv", Vu) - Vdg = self.build_l2_space() + + Vdg, continuity = self.build_l2_space() + self.continuity["L2"] = continuity setattr(self, "L2", Vdg) return Vcg, Vcurl, Vu, Vdg @@ -334,11 +384,18 @@ def build_compatible_spaces(self): else: # 1D domain, de Rham complex has 2 spaces # CG, hdiv and hcurl spaces should be the same - Vcg = self.build_h1_space() + Vcg, continuity = self.build_h1_space() + + self.continuity["H1"] = continuity setattr(self, "H1", Vcg) + setattr(self, "HCurl", None) + + self.continuity["HDiv"] = continuity setattr(self, "HDiv", Vcg) - Vdg = self.build_l2_space() + + Vdg, continuity = self.build_l2_space() + self.continuity["L2"] = continuity setattr(self, "L2", Vdg) return Vcg, Vdg @@ -360,7 +417,7 @@ def build_hcurl_space(self): """ if hdiv_hcurl_dict[self.family] is None: logger.warning('There is no HCurl space for this family. Not creating one') - return None + return None, None if self.extruded_mesh: Vh_elt = HCurl(TensorProductElement(self.base_elt_hori_hcurl, @@ -368,10 +425,13 @@ def build_hcurl_space(self): Vv_elt = HCurl(TensorProductElement(self.base_elt_hori_cg, self.base_elt_vert_dg)) V_elt = Vh_elt + Vv_elt + continuity = {'horizontal': True, 'vertical': True} else: V_elt = self.base_elt_hori_hcurl + continuity = True - return FunctionSpace(self.mesh, V_elt, name='HCurl'+self.complex_name) + space_name = 'HCurl'+self.complex_name + return FunctionSpace(self.mesh, V_elt, name=space_name), continuity def build_hdiv_space(self): """ @@ -387,9 +447,13 @@ def build_hdiv_space(self): self.base_elt_vert_cg) Vv_elt = HDiv(Vt_elt) V_elt = Vh_elt + Vv_elt + continuity = {'horizontal': True, 'vertical': True} else: V_elt = self.base_elt_hori_hdiv - return FunctionSpace(self.mesh, V_elt, name='HDiv'+self.complex_name) + continuity = True + + space_name = 'HDiv'+self.complex_name + return FunctionSpace(self.mesh, V_elt, name=space_name), continuity def build_l2_space(self): """ @@ -401,10 +465,13 @@ def build_l2_space(self): if self.extruded_mesh: V_elt = TensorProductElement(self.base_elt_hori_dg, self.base_elt_vert_dg) + continuity = {'horizontal': False, 'vertical': False} else: V_elt = self.base_elt_hori_dg + continuity = False - return FunctionSpace(self.mesh, V_elt, name='L2'+self.complex_name) + space_name = 'L2'+self.complex_name + return FunctionSpace(self.mesh, V_elt, name=space_name), continuity def build_theta_space(self): """ @@ -423,8 +490,10 @@ def build_theta_space(self): assert self.extruded_mesh, 'Cannot create theta space if mesh is not extruded' V_elt = TensorProductElement(self.base_elt_hori_dg, self.base_elt_vert_cg) + continuity = {'horizontal': False, 'vertical': True} - return FunctionSpace(self.mesh, V_elt, name='theta'+self.complex_name) + space_name = 'theta'+self.complex_name + return FunctionSpace(self.mesh, V_elt, name=space_name), continuity def build_h1_space(self): """ @@ -440,11 +509,13 @@ def build_h1_space(self): if self.extruded_mesh: V_elt = TensorProductElement(self.base_elt_hori_cg, self.base_elt_vert_cg) - + continuity = {'horizontal': True, 'vertical': True} else: V_elt = self.base_elt_hori_cg + continuity = True - return FunctionSpace(self.mesh, V_elt, name='H1'+self.complex_name) + space_name = 'H1'+self.complex_name + return FunctionSpace(self.mesh, V_elt, name=space_name), continuity def check_degree_args(name, mesh, degree, horizontal_degree, vertical_degree): @@ -476,3 +547,24 @@ def check_degree_args(name, mesh, degree, horizontal_degree, vertical_degree): raise ValueError(f'Cannot pass both "degree" and "vertical_degree" to {name}') if not extruded_mesh and vertical_degree is not None: raise ValueError(f'Cannot pass "vertical_degree" to {name} if mesh is not extruded') + + +def is_cg(V): + """ + Checks if a :class:`FunctionSpace` is continuous. + + Function to check if a given space, V, is CG. Broken elements are always + discontinuous; for vector elements we check the names of the Sobolev spaces + of the subelements and for all other elements we just check the Sobolev + space name. + + Args: + V (:class:`FunctionSpace`): the space to check. + """ + ele = V.ufl_element() + if isinstance(ele, BrokenElement): + return False + elif type(ele) == VectorElement: + return all([e.sobolev_space.name == "H1" for e in ele._sub_elements]) + else: + return V.ufl_element().sobolev_space.name == "H1" diff --git a/gusto/diagnostics/compressible_euler_diagnostics.py b/gusto/diagnostics/compressible_euler_diagnostics.py index ccb3a8595..bbacc549e 100644 --- a/gusto/diagnostics/compressible_euler_diagnostics.py +++ b/gusto/diagnostics/compressible_euler_diagnostics.py @@ -734,7 +734,8 @@ def setup(self, domain, state_fields): bcs = self.equations.bcs['u'] - imbalanceproblem = LinearVariationalProblem(a, L, imbalance, bcs=bcs) + imbalanceproblem = LinearVariationalProblem(a, L, imbalance, bcs=bcs, + constant_jacobian=True) self.imbalance_solver = LinearVariationalSolver(imbalanceproblem) self.expr = dot(imbalance, domain.k) super().setup(domain, state_fields) @@ -789,12 +790,14 @@ def setup(self, domain, state_fields): eqn_rhs = domain.dt * self.phi * (rain * dot(- v, domain.k) * rho / area) * ds_b # Compute area normalisation - area_prob = LinearVariationalProblem(eqn_lhs, area_rhs, area) + area_prob = LinearVariationalProblem(eqn_lhs, area_rhs, area, + constant_jacobian=True) area_solver = LinearVariationalSolver(area_prob) area_solver.solve() # setup solver - rain_prob = LinearVariationalProblem(eqn_lhs, eqn_rhs, self.flux) + rain_prob = LinearVariationalProblem(eqn_lhs, eqn_rhs, self.flux, + constant_jacobian=True) self.solver = LinearVariationalSolver(rain_prob) self.field = state_fields(self.name, space=DG0, dump=True, pick_up=True) # Initialise field to zero, if picking up this will be overridden diff --git a/gusto/diagnostics/diagnostics.py b/gusto/diagnostics/diagnostics.py index 69c053d45..90192f022 100644 --- a/gusto/diagnostics/diagnostics.py +++ b/gusto/diagnostics/diagnostics.py @@ -514,7 +514,8 @@ def setup(self, domain, state_fields): L = -inner(div(test), f)*dx if space.extruded: L += dot(dot(test, n), f)*(ds_t + ds_b) - prob = LinearVariationalProblem(a, L, self.field) + prob = LinearVariationalProblem(a, L, self.field, + constant_jacobian=True) self.evaluator = LinearVariationalSolver(prob) diff --git a/gusto/diagnostics/shallow_water_diagnostics.py b/gusto/diagnostics/shallow_water_diagnostics.py index 6484b2afe..eb2dc4a32 100644 --- a/gusto/diagnostics/shallow_water_diagnostics.py +++ b/gusto/diagnostics/shallow_water_diagnostics.py @@ -182,15 +182,18 @@ def setup(self, domain, state_fields, vorticity_type=None): if vorticity_type == "potential": a = q*gamma*D*dx + constant_jacobian = False else: a = q*gamma*dx + constant_jacobian = True L = (- inner(domain.perp(grad(gamma)), u))*dx if vorticity_type != "relative": f = state_fields("coriolis") L += gamma*f*dx - problem = LinearVariationalProblem(a, L, self.field) + problem = LinearVariationalProblem(a, L, self.field, + constant_jacobian=constant_jacobian) self.evaluator = LinearVariationalSolver(problem, solver_parameters={"ksp_type": "cg"}) diff --git a/gusto/solvers/__init__.py b/gusto/solvers/__init__.py index efb4a5af4..fc4c8a7d2 100644 --- a/gusto/solvers/__init__.py +++ b/gusto/solvers/__init__.py @@ -1,2 +1,3 @@ +from gusto.solvers.parameters import * # noqa from gusto.solvers.linear_solvers import * # noqa -from gusto.solvers.preconditioners import * # noqa \ No newline at end of file +from gusto.solvers.preconditioners import * # noqa diff --git a/gusto/solvers/linear_solvers.py b/gusto/solvers/linear_solvers.py index 52141d5dc..1f44cc950 100644 --- a/gusto/solvers/linear_solvers.py +++ b/gusto/solvers/linear_solvers.py @@ -84,6 +84,17 @@ def solver_parameters(self): def _setup_solver(self): pass + @abstractmethod + def update_reference_profiles(self): + """ + Update the solver when the reference profiles have changed. + + This typically includes forcing any Jacobians that depend on + the reference profiles to be reassembled, and recalculating + any values derived from the reference values. + """ + pass + @abstractmethod def solve(self): pass @@ -261,8 +272,10 @@ def L_tr(f): rhobar_avg = Function(Vtrace) exnerbar_avg = Function(Vtrace) - rho_avg_prb = LinearVariationalProblem(a_tr, L_tr(rhobar), rhobar_avg) - exner_avg_prb = LinearVariationalProblem(a_tr, L_tr(exnerbar), exnerbar_avg) + rho_avg_prb = LinearVariationalProblem(a_tr, L_tr(rhobar), rhobar_avg, + constant_jacobian=True) + exner_avg_prb = LinearVariationalProblem(a_tr, L_tr(exnerbar), exnerbar_avg, + constant_jacobian=True) self.rho_avg_solver = LinearVariationalSolver(rho_avg_prb, solver_parameters=cg_ilu_parameters, @@ -318,7 +331,8 @@ def L_tr(f): # Function for the hybridized solutions self.urhol0 = Function(M) - hybridized_prb = LinearVariationalProblem(aeqn, Leqn, self.urhol0) + hybridized_prb = LinearVariationalProblem(aeqn, Leqn, self.urhol0, + constant_jacobian=True) hybridized_solver = LinearVariationalSolver(hybridized_prb, solver_parameters=self.solver_parameters, options_prefix='ImplicitSolver') @@ -344,7 +358,8 @@ def L_tr(f): theta_eqn = gamma*(theta - theta_in + dot(k, self.u_hdiv)*dot(k, grad(thetabar))*beta_t)*dx - theta_problem = LinearVariationalProblem(lhs(theta_eqn), rhs(theta_eqn), self.theta) + theta_problem = LinearVariationalProblem(lhs(theta_eqn), rhs(theta_eqn), self.theta, + constant_jacobian=True) self.theta_solver = LinearVariationalSolver(theta_problem, solver_parameters=cg_ilu_parameters, options_prefix='thetabacksubstitution') @@ -361,10 +376,6 @@ def L_tr(f): @timed_function("Gusto:UpdateReferenceProfiles") def update_reference_profiles(self): - """ - Updates the reference profiles. - """ - with timed_region("Gusto:HybridProjectRhobar"): logger.info('Compressible linear solver: rho average solve') self.rho_avg_solver.solve() @@ -373,6 +384,13 @@ def update_reference_profiles(self): logger.info('Compressible linear solver: Exner average solve') self.exner_avg_solver.solve() + # Because the left hand side of the hybridised problem depends + # on the reference profile, the Jacobian matrix should change + # when the reference profiles are updated. This call will tell + # the hybridized_solver to reassemble the Jacobian next time + # `solve` is called. + self.hybridized_solver.invalidate_jacobian() + @timed_function("Gusto:LinearSolve") def solve(self, xrhs, dy): """ @@ -511,7 +529,8 @@ def V(u): bcs = [DirichletBC(M.sub(0), bc.function_arg, bc.sub_domain) for bc in self.equations.bcs['u']] # Solver for u, p - up_problem = LinearVariationalProblem(aeqn, Leqn, self.up, bcs=bcs) + up_problem = LinearVariationalProblem(aeqn, Leqn, self.up, bcs=bcs, + constant_jacobian=True) # Provide callback for the nullspace of the trace system def trace_nullsp(T): @@ -534,12 +553,17 @@ def trace_nullsp(T): b_problem = LinearVariationalProblem(lhs(b_eqn), rhs(b_eqn), - self.b) + self.b, + constant_jacobian=True) self.b_solver = LinearVariationalSolver(b_problem) # Log residuals on hybridized solver self.log_ksp_residuals(self.up_solver.snes.ksp) + @timed_function("Gusto:UpdateReferenceProfiles") + def update_reference_profiles(self): + self.up_solver.invalidate_jacobian() + @timed_function("Gusto:LinearSolve") def solve(self, xrhs, dy): """ @@ -673,7 +697,8 @@ def _setup_solver(self): bcs = [DirichletBC(M.sub(0), bc.function_arg, bc.sub_domain) for bc in self.equations.bcs['u']] # Solver for u, D - uD_problem = LinearVariationalProblem(aeqn, Leqn, self.uD, bcs=bcs) + uD_problem = LinearVariationalProblem(aeqn, Leqn, self.uD, bcs=bcs, + constant_jacobian=True) # Provide callback for the nullspace of the trace system def trace_nullsp(T): @@ -694,7 +719,8 @@ def trace_nullsp(T): b_problem = LinearVariationalProblem(lhs(b_eqn), rhs(b_eqn), - self.b) + self.b, + constant_jacobian=True) self.b_solver = LinearVariationalSolver(b_problem) # Log residuals on hybridized solver @@ -702,10 +728,6 @@ def trace_nullsp(T): @timed_function("Gusto:UpdateReferenceProfiles") def update_reference_profiles(self): - """ - Updates the reference profiles. - """ - if self.equations.equivalent_buoyancy: self.q_sat_expr_interpolator.interpolate() self.q_v_interpolator.interpolate() @@ -772,13 +794,17 @@ class LinearTimesteppingSolver(object): 'sub_pc_type': 'ilu'}} } - def __init__(self, equation, alpha): + def __init__(self, equation, alpha, reference_dependent=True): """ Args: equation (:class:`PrognosticEquation`): the model's equation object. alpha (float): the semi-implicit off-centring factor. A value of 1 is fully-implicit. + reference_dependent: this indicates that the solver Jacobian should + be rebuilt if the reference profiles have been updated. """ + self.reference_dependent = reference_dependent + residual = equation.residual.label_map( lambda t: t.has_label(linearisation), lambda t: Term(t.get(linearisation).form, t.labels), @@ -805,12 +831,18 @@ def __init__(self, equation, alpha): bcs = [DirichletBC(W.sub(0), bc.function_arg, bc.sub_domain) for bc in equation.bcs['u']] problem = LinearVariationalProblem(aeqn.form, action(Leqn.form, self.xrhs), - self.dy, bcs=bcs) + self.dy, bcs=bcs, + constant_jacobian=True) self.solver = LinearVariationalSolver(problem, solver_parameters=self.solver_parameters, options_prefix='linear_solver') + @timed_function("Gusto:UpdateReferenceProfiles") + def update_reference_profiles(self): + if self.reference_dependent: + self.solver.invalidate_jacobian() + @timed_function("Gusto:LinearSolve") def solve(self, xrhs, dy): """ @@ -895,7 +927,8 @@ def _setup_solver(self): bcs = [DirichletBC(M.sub(0), bc.function_arg, bc.sub_domain) for bc in self.equations.bcs['u']] # Solver for u, D - uD_problem = LinearVariationalProblem(aeqn, Leqn, self.uD, bcs=bcs) + uD_problem = LinearVariationalProblem(aeqn, Leqn, self.uD, bcs=bcs, + constant_jacobian=True) # Provide callback for the nullspace of the trace system def trace_nullsp(T): @@ -909,6 +942,10 @@ def trace_nullsp(T): # Log residuals on hybridized solver self.log_ksp_residuals(self.uD_solver.snes.ksp) + @timed_function("Gusto:UpdateReferenceProfiles") + def update_reference_profiles(self): + self.uD_solver.invalidate_jacobian() + @timed_function("Gusto:LinearSolve") def solve(self, xrhs, dy): """ diff --git a/gusto/solvers/parameters.py b/gusto/solvers/parameters.py new file mode 100644 index 000000000..a7f61edb0 --- /dev/null +++ b/gusto/solvers/parameters.py @@ -0,0 +1,99 @@ +""" +This module provides some parameters sets that are good defaults +for particular kinds of system. +""" +from gusto.core.function_spaces import is_cg + +__all__ = ['mass_parameters'] + + +def mass_parameters(V, spaces=None, ignore_vertical=True): + """ + PETSc solver parameters for mass matrices. + + Currently this sets to a monolithic CG+ILU. + + TODO: implement field-by-field parameters that choose + preonly for discontinuous fields and CG for continuous + fields - see docstring below. + + ================= FUTURE DOCSTRING ================= + Any fields which are discontinuous will have block diagonal + mass matrices, so are solved directly using: + 'ksp_type': 'preonly' + 'pc_type': 'ilu' + + All continuous fields are solved with CG, with the preconditioner + being ILU independently on each field. By solving all continuous fields + "monolithically", the total number of inner products is minimised, which + is beneficial for scaling to large core counts because it minimises the + total number of MPI_Allreduce calls. + 'ksp_type': 'cg' + 'pc_type': 'fieldsplit' + 'pc_fieldsplit_type': 'additive' + 'fieldsplit_ksp_type': 'preonly' + 'fieldsplit_pc_type': 'ilu' + + Args: + spaces: Optional `Spaces` object. If present, any subspace + of V that came from the `Spaces` object will use the + continuity information from `spaces`. + If not present, continuity is checked with `is_cg`. + + ignore_vertical: whether to include the vertical direction when checking + field continuity on extruded meshes. If True, only the horizontal + continuity will be considered, e.g. the standard theta space will + be treated as discontinuous. + """ + return { + 'ksp_type': 'cg', + 'pc_type': 'bjacobi', + 'sub_pc_type': 'ilu' + } + + extruded = hasattr(V.mesh, "_base_mesh") + + continuous_fields = set() + for i, Vsub in enumerate(V.subfunctions): + # field = Vsub.name or str(i) + field = str(i) + + if spaces is not None: + continuous = spaces.continuity.get(field, is_cg(Vsub)) + else: + continuous = is_cg(Vsub) + + # For extruded meshes the continuity is recorded + # separately for the horizontal and vertical directions. + if extruded and spaces is not None: + if ignore_vertical: + continuous = continuous['horizontal'] + else: + continuous = (continuous['horizontal'] + or continuous['vertical']) + + if continuous: + continuous_fields.add(field) + + if len(V.subfunctions) == 1: + parameters = { + 'ksp_type': 'cg' if all(continuous_fields) else 'preonly', + 'pc_type': 'bjacobi', + 'sub_pc_type': 'ilu', + } + else: + + parameters = { + 'ksp_type': 'preonly', + 'pc_type': 'fieldsplit', + 'pc_fieldsplit_type': 'additive', + 'pc_fieldsplit_0_fields': ','.join(continuous_fields), + 'fieldsplit': { + 'ksp_type': 'preonly', + 'pc_type': 'bjacobi', + 'sub_pc_type': 'ilu' + }, + 'fieldsplit_0_ksp_type': 'cg', + } + + return parameters diff --git a/gusto/time_discretisation/time_discretisation.py b/gusto/time_discretisation/time_discretisation.py index daa3e2ad9..d8e07bf86 100644 --- a/gusto/time_discretisation/time_discretisation.py +++ b/gusto/time_discretisation/time_discretisation.py @@ -21,6 +21,7 @@ mass_weighted, nonlinear_time_derivative) from gusto.core.logging import logger, DEBUG, logging_ksp_monitor_true_residual from gusto.time_discretisation.wrappers import * +from gusto.solvers import mass_parameters __all__ = ["TimeDiscretisation", "ExplicitTimeDiscretisation", "BackwardEuler", "ThetaMethod", "TrapeziumRule", "TR_BDF2"] @@ -472,15 +473,6 @@ def __init__(self, domain, field_name=None, subcycling_options=None, limiter=limiter, options=options, augmentation=augmentation) - # get default solver options if none passed in - if solver_parameters is None: - self.solver_parameters = {'snes_type': 'ksponly', - 'ksp_type': 'cg', - 'pc_type': 'bjacobi', - 'sub_pc_type': 'ilu'} - else: - self.solver_parameters = solver_parameters - def setup(self, equation, apply_bcs=True, *active_labels): """ Set up the time discretisation based on the equation. @@ -494,6 +486,11 @@ def setup(self, equation, apply_bcs=True, *active_labels): """ super().setup(equation, apply_bcs, *active_labels) + # get default solver options if none passed in + self.solver_parameters.update(mass_parameters( + self.fs, equation.domain.spaces)) + self.solver_parameters['snes_type'] = 'ksponly' + # if user has specified a number of fixed subcycles, then save this # and rescale dt accordingly; else perform just one cycle using dt if (self.subcycling_options is not None @@ -506,7 +503,8 @@ def setup(self, equation, apply_bcs=True, *active_labels): self.x0 = Function(self.fs) self.x1 = Function(self.fs) - # If the time_derivative term is nonlinear, we must use a nonlinear solver + # If the time_derivative term is nonlinear, we must use a nonlinear solver, + # but if the time_derivative term is linear, we can reuse the factorisations. if ( len(self.residual.label_map( lambda t: t.has_label(nonlinear_time_derivative), @@ -518,6 +516,11 @@ def setup(self, equation, apply_bcs=True, *active_labels): + ' as the time derivative term is nonlinear') logger.warning(message) self.solver_parameters['snes_type'] = 'newtonls' + else: + self.solver_parameters.setdefault('snes_lag_jacobian', -2) + self.solver_parameters.setdefault('snes_lag_jacobian_persists', None) + self.solver_parameters.setdefault('snes_lag_preconditioner', -2) + self.solver_parameters.setdefault('snes_lag_preconditioner_persists', None) @cached_property def lhs(self): diff --git a/gusto/time_discretisation/wrappers.py b/gusto/time_discretisation/wrappers.py index 2d388e998..f0aae843e 100644 --- a/gusto/time_discretisation/wrappers.py +++ b/gusto/time_discretisation/wrappers.py @@ -7,13 +7,14 @@ from abc import ABCMeta, abstractmethod from firedrake import ( FunctionSpace, Function, BrokenElement, Projector, Interpolator, - VectorElement, Constant, as_ufl, dot, grad, TestFunction, MixedFunctionSpace + Constant, as_ufl, dot, grad, TestFunction, MixedFunctionSpace ) from firedrake.fml import Term from gusto.core.configuration import EmbeddedDGOptions, RecoveryOptions, SUPGOptions from gusto.recovery import Recoverer, ReversibleRecoverer, ConservativeRecoverer from gusto.core.labels import transporting_velocity from gusto.core.conservative_projection import ConservativeProjector +from gusto.core.function_spaces import is_cg import ufl __all__ = ["EmbeddedDGWrapper", "RecoveryWrapper", "SUPGWrapper", "MixedFSWrapper"] @@ -307,27 +308,6 @@ def post_apply(self, x_out): x_out.assign(self.x_projected) -def is_cg(V): - """ - Checks if a :class:`FunctionSpace` is continuous. - - Function to check if a given space, V, is CG. Broken elements are always - discontinuous; for vector elements we check the names of the Sobolev spaces - of the subelements and for all other elements we just check the Sobolev - space name. - - Args: - V (:class:`FunctionSpace`): the space to check. - """ - ele = V.ufl_element() - if isinstance(ele, BrokenElement): - return False - elif type(ele) == VectorElement: - return all([e.sobolev_space.name == "H1" for e in ele._sub_elements]) - else: - return V.ufl_element().sobolev_space.name == "H1" - - class SUPGWrapper(Wrapper): """ Wrapper for computing a time discretisation with SUPG, which adjusts the diff --git a/gusto/timestepping/semi_implicit_quasi_newton.py b/gusto/timestepping/semi_implicit_quasi_newton.py index 7c4de236b..c5f8a7ece 100644 --- a/gusto/timestepping/semi_implicit_quasi_newton.py +++ b/gusto/timestepping/semi_implicit_quasi_newton.py @@ -13,7 +13,7 @@ from gusto.core.labels import (transport, diffusion, time_derivative, linearisation, prognostic, hydrostatic, physics_label, sponge, incompressible) -from gusto.solvers import LinearTimesteppingSolver +from gusto.solvers import LinearTimesteppingSolver, mass_parameters from gusto.core.logging import logger, DEBUG, logging_ksp_monitor_true_residual from gusto.time_discretisation.time_discretisation import ExplicitTimeDiscretisation from gusto.timestepping.timestepper import BaseTimestepper @@ -571,13 +571,17 @@ def __init__(self, equation, alpha): constant_jacobian=True ) + self.solver_parameters = mass_parameters(W, equation.domain.spaces) + self.solvers = {} self.solvers["explicit"] = LinearVariationalSolver( explicit_forcing_problem, + solver_parameters=self.solver_parameters, options_prefix="ExplicitForcingSolver" ) self.solvers["implicit"] = LinearVariationalSolver( implicit_forcing_problem, + solver_parameters=self.solver_parameters, options_prefix="ImplicitForcingSolver" ) diff --git a/integration-tests/data/boussinesq_compressible_chkpt.h5 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z6AUF{DEL_q-f1>)+vE%$P+KtUFo6fi>c3&BHSeOhQI(Me|62Sk9HU>H|8+J!cR}ym9?A>Stc&1JFqCVVhHs)QT-%Qw53Q zw5pPefmlh)I^O_L_Se=o+U@0RC&TRHXvs=rLF!EBO#|=3iIe4LN)(tqy9#$F$-tqzd6cBXFzZ~JSg%1*$rILygVQRE()NiT3vZB+$Vc;2^?mE_|i8$S| zyCgXrnTqs9yFJFZaCU}QNi6D01qie9fWWDDrY0|Oe5ka7eiWg^{*G|yBP2AZxuu80 z^fFZ2x=C=dyxJT)Cfd_K*Q|IAO){QLbBR4oIPsny>w)kF?tGaS6esT8wt5aB|~+U9n6knNSs{o@$mV&e_$IDvIBPp{7N z7|4zaqwCJ#-@T24_s7wZ^Os601*$p~$S*hnrz2}e`ozO&AAje6WD&trGSDBDGVuo6 z)_KDVBZWQP)!mE%Twus}{Do*5<7T>L77uV`*%!;IDeju3 zc~)=2g)=p;;wbR)Tp2+p5{TnX~H<17U diff --git a/unit-tests/test_function_spaces.py b/unit-tests/test_function_spaces.py index b39aa8cc5..bcf105e35 100644 --- a/unit-tests/test_function_spaces.py +++ b/unit-tests/test_function_spaces.py @@ -100,6 +100,27 @@ def test_de_rham_spaces(domain, family): assert elt.degree() == degree, '"L2" space does not seem to be degree ' \ + f'{degree}. Found degree {elt.degree()}' + # Check that continuities have been recorded correctly + if hasattr(mesh, "_base_mesh"): + expected_continuity = { + "H1": {'horizontal': True, 'vertical': True}, + "L2": {'horizontal': False, 'vertical': False}, + "HDiv": {'horizontal': True, 'vertical': True}, + "HCurl": {'horizontal': True, 'vertical': True}, + "theta": {'horizontal': False, 'vertical': True} + } + else: + expected_continuity = { + "H1": True, + "L2": False, + "HDiv": True, + "HCurl": True + } + + for space, continuity in expected_continuity.items(): + if space in spaces.continuity: + assert spaces.continuity[space] == continuity + # ---------------------------------------------------------------------------- # # Test creation of DG1 equispaced @@ -118,6 +139,13 @@ def test_dg_equispaced(domain, family): assert elt.variant() == "equispaced", '"DG1 equispaced" does not seem to ' \ + f'be equispaced variant. Found variant {elt.variant()}' + if hasattr(mesh, "_base_mesh"): + expected_continuity = {'horizontal': False, 'vertical': False} + else: + expected_continuity = False + + assert spaces.continuity['DG1_equispaced'] == expected_continuity, "DG is discontinuous" + # ---------------------------------------------------------------------------- # # Test creation of DG0 space @@ -133,6 +161,13 @@ def test_dg0(domain, family): assert elt.degree() in [0, (0, 0)], '"DG0" space does not seem to be' \ + f'degree 0. Found degree {elt.degree()}' + if hasattr(mesh, "_base_mesh"): + expected_continuity = {'horizontal': False, 'vertical': False} + else: + expected_continuity = False + + assert spaces.continuity['DG0'] == expected_continuity, "DG is discontinuous" + # ---------------------------------------------------------------------------- # # Test creation of a general CG space @@ -150,3 +185,10 @@ def test_cg(domain, family): assert elt.degree() == degree or elt.degree() == (degree, degree), \ (f'"CG" space does not seem to be degree {degree}. ' + f'Found degree {elt.degree()}') + + if hasattr(mesh, "_base_mesh"): + expected_continuity = {'horizontal': True, 'vertical': True} + else: + expected_continuity = True + + assert spaces.continuity['CG'] == expected_continuity, "CG is continuous" From 0db493eaec1bfa32c489cbf77be929ac2159d095 Mon Sep 17 00:00:00 2001 From: Daniel Witt <91120222+Witt-D@users.noreply.github.com> Date: Wed, 18 Dec 2024 20:04:26 +0000 Subject: [PATCH 6/7] Relaxation physics (#540) Co-authored-by: Tom Bendall --- gusto/core/configuration.py | 13 ++ gusto/physics/__init__.py | 3 +- gusto/physics/held_suarez_forcing.py | 188 ++++++++++++++++++ .../physics/test_held_suarez_friction.py | 114 +++++++++++ .../physics/test_held_suarez_relaxation.py | 107 ++++++++++ 5 files changed, 424 insertions(+), 1 deletion(-) create mode 100644 gusto/physics/held_suarez_forcing.py create mode 100644 integration-tests/physics/test_held_suarez_friction.py create mode 100644 integration-tests/physics/test_held_suarez_relaxation.py diff --git a/gusto/core/configuration.py b/gusto/core/configuration.py index 4f82a35f7..40852033a 100644 --- a/gusto/core/configuration.py +++ b/gusto/core/configuration.py @@ -269,6 +269,19 @@ class BoundaryLayerParameters(Configuration): mu = 100. # Interior penalty coefficient for vertical diffusion +class HeldSuarezParameters(Configuration): + """ + Parameters used in the default configuration for the Held Suarez test case. + """ + T0stra = 200 # Stratosphere temp + T0surf = 315 # Surface temperature at equator + T0horiz = 60 # Equator to pole temperature difference + T0vert = 10 # Stability parameter + sigmab = 0.7 # Height of the boundary layer + tau_d = 40 * 24 * 60 * 60 # 40 day time scale + tau_u = 4 * 24 * 60 * 60 # 4 day timescale + + class SubcyclingOptions(Configuration): """ Describes the process of subcycling a time discretisation, by dividing the diff --git a/gusto/physics/__init__.py b/gusto/physics/__init__.py index 91f09c2ec..b1407a299 100644 --- a/gusto/physics/__init__.py +++ b/gusto/physics/__init__.py @@ -2,4 +2,5 @@ from gusto.physics.chemistry import * # noqa from gusto.physics.boundary_and_turbulence import * # noqa from gusto.physics.microphysics import * # noqa -from gusto.physics.shallow_water_microphysics import * # noqa \ No newline at end of file +from gusto.physics.shallow_water_microphysics import * # noqa +from gusto.physics.held_suarez_forcing import * # noqa diff --git a/gusto/physics/held_suarez_forcing.py b/gusto/physics/held_suarez_forcing.py new file mode 100644 index 000000000..d7573d009 --- /dev/null +++ b/gusto/physics/held_suarez_forcing.py @@ -0,0 +1,188 @@ +import numpy as np +from firedrake import (Interpolator, Function, dx, pi, SpatialCoordinate, + split, conditional, ge, sin, dot, ln, cos, inner, Projector) +from firedrake.fml import subject +from gusto.core.coord_transforms import lonlatr_from_xyz +from gusto.recovery import Recoverer, BoundaryMethod +from gusto.physics.physics_parametrisation import PhysicsParametrisation +from gusto.core.labels import prognostic +from gusto.equations import thermodynamics +from gusto.core.configuration import HeldSuarezParameters +from gusto.core import logger + + +class Relaxation(PhysicsParametrisation): + """ + Relaxation term for Held Suarez + """ + + def __init__(self, equation, variable_name, parameters, hs_parameters=None): + """ + Args: + equation (:class:`PrognosticEquationSet`): the model's equation. + variable_name (str): the name of the variable + hs_parameters (:class'Configuration'): contains the parameters for the Held-suariez test case + + """ + label_name = f'relaxation_{variable_name}' + if hs_parameters is None: + hs_parameters = HeldSuarezParameters() + logger.warning('Using default Held-Suarez parameters') + super().__init__(equation, label_name, hs_parameters) + + if equation.domain.on_sphere: + x, y, z = SpatialCoordinate(equation.domain.mesh) + _, lat, _ = lonlatr_from_xyz(x, y, z) + else: + # TODO: this could be determined some other way + # Take a mid-latitude + lat = pi / 4 + + self.X = Function(equation.X.function_space()) + X = self.X + self.domain = equation.domain + theta_idx = equation.field_names.index('theta') + self.theta = X.subfunctions[theta_idx] + Vt = equation.domain.spaces('theta') + rho_idx = equation.field_names.index('rho') + rho = split(X)[rho_idx] + + boundary_method = BoundaryMethod.extruded if equation.domain.vertical_degree == 0 else None + self.rho_averaged = Function(Vt) + self.rho_recoverer = Recoverer(rho, self.rho_averaged, boundary_method=boundary_method) + self.exner = Function(Vt) + self.exner_interpolator = Interpolator( + thermodynamics.exner_pressure(equation.parameters, + self.rho_averaged, self.theta), self.exner) + self.sigma = Function(Vt) + kappa = equation.parameters.kappa + + T0surf = hs_parameters.T0surf + T0horiz = hs_parameters.T0horiz + T0vert = hs_parameters.T0vert + T0stra = hs_parameters.T0stra + + sigma_b = hs_parameters.sigmab + tau_d = hs_parameters.tau_d + tau_u = hs_parameters.tau_u + + theta_condition = (T0surf - T0horiz * sin(lat)**2 - (T0vert * ln(self.exner) * cos(lat)**2)/kappa) + Theta_eq = conditional(T0stra/self.exner >= theta_condition, T0stra/self.exner, theta_condition) + + # timescale of temperature forcing + tau_cond = (self.sigma**(1/kappa) - sigma_b) / (1 - sigma_b) + newton_freq = 1 / tau_d + (1/tau_u - 1/tau_d) * conditional(0 >= tau_cond, 0, tau_cond) * cos(lat)**4 + forcing_expr = newton_freq * (self.theta - Theta_eq) + + # Create source for forcing + self.source_relaxation = Function(Vt) + self.source_interpolator = Interpolator(forcing_expr, self.source_relaxation) + + # Add relaxation term to residual + test = equation.tests[theta_idx] + dx_reduced = dx(degree=equation.domain.max_quad_degree) + forcing_form = test * self.source_relaxation * dx_reduced + equation.residual += self.label(subject(prognostic(forcing_form, 'theta'), X), self.evaluate) + + def evaluate(self, x_in, dt): + """ + Evalutes the source term generated by the physics. + + Args: + x_in: (:class:`Function`): the (mixed) field to be evolved. + dt: (:class:`Constant`): the timestep, which can be the time + interval for the scheme. + """ + self.X.assign(x_in) + self.rho_recoverer.project() + self.exner_interpolator.interpolate() + + # Determine sigma:= exner / exner_surf + exner_columnwise, index_data = self.domain.coords.get_column_data(self.exner, self.domain) + sigma_columnwise = np.zeros_like(exner_columnwise) + for col in range(len(exner_columnwise[:, 0])): + sigma_columnwise[col, :] = exner_columnwise[col, :] / exner_columnwise[col, 0] + self.domain.coords.set_field_from_column_data(self.sigma, sigma_columnwise, index_data) + + self.source_interpolator.interpolate() + + +class RayleighFriction(PhysicsParametrisation): + """ + Forcing term on the velocity of the form + F_u = -u / a, + where a is some friction factor + """ + def __init__(self, equation, hs_parameters=None): + """ + Args: + equation (:class:`PrognosticEquationSet`): the model's equation. + hs_parameters (:class'Configuration'): contains the parameters for the Held-suariez test case + """ + label_name = 'rayleigh_friction' + if hs_parameters is None: + hs_parameters = HeldSuarezParameters() + logger.warning('Using default Held-Suarez parameters') + super().__init__(equation, label_name, hs_parameters) + + self.domain = equation.domain + self.X = Function(equation.X.function_space()) + X = self.X + k = equation.domain.k + u_idx = equation.field_names.index('u') + u = split(X)[u_idx] + theta_idx = equation.field_names.index('theta') + self.theta = X.subfunctions[theta_idx] + rho_idx = equation.field_names.index('rho') + rho = split(X)[rho_idx] + Vt = equation.domain.spaces('theta') + Vu = equation.domain.spaces('HDiv') + u_hori = u - k*dot(u, k) + + boundary_method = BoundaryMethod.extruded if self.domain == 0 else None + self.rho_averaged = Function(Vt) + self.exner = Function(Vt) + self.rho_recoverer = Recoverer(rho, self.rho_averaged, boundary_method=boundary_method) + self.exner_interpolator = Interpolator( + thermodynamics.exner_pressure(equation.parameters, + self.rho_averaged, self.theta), self.exner) + + self.sigma = Function(Vt) + sigmab = hs_parameters.sigmab + kappa = equation.parameters.kappa + tau_fric = 24 * 60 * 60 + + tau_cond = (self.sigma**(1/kappa) - sigmab) / (1 - sigmab) + wind_timescale = conditional(ge(0, tau_cond), 0, tau_cond) / tau_fric + forcing_expr = u_hori * wind_timescale + + self.source_friction = Function(Vu) + self.source_projector = Projector(forcing_expr, self.source_friction) + + tests = equation.tests + test = tests[u_idx] + dx_reduced = dx(degree=equation.domain.max_quad_degree) + source_form = inner(test, self.source_friction) * dx_reduced + equation.residual += self.label(subject(prognostic(source_form, 'u'), X), self.evaluate) + + def evaluate(self, x_in, dt): + """ + Evaluates the source term generated by the physics. This does nothing if + the implicit formulation is not used. + + Args: + x_in: (:class: 'Function'): the (mixed) field to be evolved. + dt: (:class: 'Constant'): the timestep, which can be the time + interval for the scheme. + """ + self.X.assign(x_in) + self.rho_recoverer.project() + self.exner_interpolator.interpolate() + # Determine sigma:= exner / exner_surf + exner_columnwise, index_data = self.domain.coords.get_column_data(self.exner, self.domain) + sigma_columnwise = np.zeros_like(exner_columnwise) + for col in range(len(exner_columnwise[:, 0])): + sigma_columnwise[col, :] = exner_columnwise[col, :] / exner_columnwise[col, 0] + self.domain.coords.set_field_from_column_data(self.sigma, sigma_columnwise, index_data) + + self.source_projector.project() diff --git a/integration-tests/physics/test_held_suarez_friction.py b/integration-tests/physics/test_held_suarez_friction.py new file mode 100644 index 000000000..dfe7e34f9 --- /dev/null +++ b/integration-tests/physics/test_held_suarez_friction.py @@ -0,0 +1,114 @@ +""" +This tests the Rayleigh friction term used in the Held Suarez test case. +""" + +from gusto import * +import gusto.equations.thermodynamics as td +from gusto.core.labels import physics_label +from firedrake import (Constant, PeriodicIntervalMesh, as_vector, norm, + ExtrudedMesh, Function, dot) +from firedrake.fml import identity, drop + + +def run_apply_rayleigh_friction(dirname): + # ------------------------------------------------------------------------ # + # Set up model objects + # ------------------------------------------------------------------------ # + + dt = 3600.0 + + # declare grid shape, with length L and height H + L = 500. + H = 500. + nlayers = int(H / 5.) + ncolumns = int(L / 5.) + + # make mesh and domain + m = PeriodicIntervalMesh(ncolumns, L) + mesh = ExtrudedMesh(m, layers=nlayers, layer_height=(H / nlayers)) + domain = Domain(mesh, dt, "CG", 0) + + # Set up equation + parameters = CompressibleParameters() + eqn = CompressibleEulerEquations(domain, parameters) + + # I/O + output = OutputParameters(dirname=dirname+"/held_suarez_friction", + dumpfreq=1, + dumplist=['u']) + io = IO(domain, output) + + # Physics scheme + physics_parametrisation = RayleighFriction(eqn) + + time_discretisation = BackwardEuler(domain) + + # time_discretisation = ForwardEuler(domain) + physics_schemes = [(physics_parametrisation, time_discretisation)] + + # Only want time derivatives and physics terms in equation, so drop the rest + eqn.residual = eqn.residual.label_map(lambda t: any(t.has_label(time_derivative, physics_label)), + map_if_true=identity, map_if_false=drop) + + # Time stepper + scheme = ForwardEuler(domain) + stepper = SplitPhysicsTimestepper(eqn, scheme, io, + physics_schemes=physics_schemes) + + # ------------------------------------------------------------------------ # + # Initial conditions + # ------------------------------------------------------------------------ # + + Vu = domain.spaces("HDiv") + Vt = domain.spaces("theta") + Vr = domain.spaces("DG") + + # Declare prognostic fields + u0 = stepper.fields("u") + rho0 = stepper.fields("rho") + theta0 = stepper.fields("theta") + + # Set a background state with constant pressure and temperature + pressure = Function(Vr).interpolate(Constant(100000.)) + temperature = Function(Vt).interpolate(Constant(295.)) + theta_d = td.theta(parameters, temperature, pressure) + + theta0.project(theta_d) + rho0.interpolate(pressure / (temperature*parameters.R_d)) + + # Constant horizontal wind + u0.project(as_vector([864, 0.0])) + + # Answer: slower winds than initially + u_true = Function(Vu) + u_true.project(as_vector([828, 0.0])) + + # ------------------------------------------------------------------------ # + # Run + # ------------------------------------------------------------------------ # + + stepper.run(t=0, tmax=dt) + + return mesh, stepper, u_true + + +def test_rayleigh_friction(tmpdir): + + dirname = str(tmpdir) + mesh, stepper, u_true = run_apply_rayleigh_friction(dirname) + + u_final = stepper.fields('u') + + # Project into CG1 to get sensible values + e_x = as_vector([1.0, 0.0]) + e_z = as_vector([0.0, 1.0]) + + DG0 = FunctionSpace(mesh, "DG", 0) + u_x_final = Function(DG0).project(dot(u_final, e_x)) + u_x_true = Function(DG0).project(dot(u_true, e_x)) + u_z_final = Function(DG0).project(dot(u_final, e_z)) + u_z_true = Function(DG0).project(dot(u_true, e_z)) + + denom = norm(u_x_true) + assert norm(u_x_final - u_x_true) / denom < 0.0001, 'Final horizontal wind is incorrect' + assert norm(u_z_final - u_z_true) < 1e-12, 'Final vertical wind is incorrect' diff --git a/integration-tests/physics/test_held_suarez_relaxation.py b/integration-tests/physics/test_held_suarez_relaxation.py new file mode 100644 index 000000000..615ba8d29 --- /dev/null +++ b/integration-tests/physics/test_held_suarez_relaxation.py @@ -0,0 +1,107 @@ +""" +This tests the Held-Suarez physics routine to apply Rayleigh friction. +""" +from gusto import * +import gusto.equations.thermodynamics as td +from gusto.core.labels import physics_label +from firedrake import (Constant, PeriodicIntervalMesh, as_vector, + ExtrudedMesh, Function) +from firedrake.fml import identity, drop +import pytest + + +def run_held_suarez_relaxation(dirname, temp): + + # ------------------------------------------------------------------------ # + # Set up model objects + # ------------------------------------------------------------------------ # + + dt = 3600.0 + + # declare grid shape, with length L and height H + L = 500. + H = 500. + nlayers = int(H / 5.) + ncolumns = int(L / 5.) + + # make mesh and domain + m = PeriodicIntervalMesh(ncolumns, L) + mesh = ExtrudedMesh(m, layers=nlayers, layer_height=(H / nlayers)) + domain = Domain(mesh, dt, "CG", 0) + + # Set up equation + parameters = CompressibleParameters() + eqn = CompressibleEulerEquations(domain, parameters) + + # I/O + output = OutputParameters(dirname=dirname+"/held_suarez_friction", + dumpfreq=1, + dumplist=['u']) + io = IO(domain, output) + + # Physics scheme + physics_parametrisation = Relaxation(eqn, 'theta', parameters) + + time_discretisation = ForwardEuler(domain) + + # time_discretisation = ForwardEuler(domain) + physics_schemes = [(physics_parametrisation, time_discretisation)] + + # Only want time derivatives and physics terms in equation, so drop the rest + eqn.residual = eqn.residual.label_map(lambda t: any(t.has_label(time_derivative, physics_label)), + map_if_true=identity, map_if_false=drop) + + # Time stepper + scheme = ForwardEuler(domain) + stepper = SplitPhysicsTimestepper(eqn, scheme, io, + physics_schemes=physics_schemes) + + # ------------------------------------------------------------------------ # + # Initial conditions + # ------------------------------------------------------------------------ # + + Vt = domain.spaces("theta") + Vr = domain.spaces("DG") + + # Declare prognostic fields + u0 = stepper.fields("u") + rho0 = stepper.fields("rho") + theta0 = stepper.fields("theta") + + # Set a background state with constant pressure and temperature + p0 = 100000. + pressure = Function(Vr).interpolate(Constant(p0)) + temperature = Function(Vt).interpolate(Constant(temp)) + theta_d = td.theta(parameters, temperature, pressure) + + theta0.project(theta_d) + rho0.interpolate(p0 / (theta_d*parameters.R_d)) # This ensures that exner = 1 + + # Constant horizontal wind + u0.project(as_vector([1.0, 1.0])) + theta_initial = Function(Vt) + theta_initial.interpolate(theta_d) + + # ------------------------------------------------------------------------ # + # Run + # ------------------------------------------------------------------------ # + + stepper.run(t=0, tmax=dt) + + return stepper, theta_initial + + +@pytest.mark.parametrize('temp', [280, 290]) +def test_held_suarez_relaxation(tmpdir, temp): + # By configuring the fields we have set the equilibrium temperature to 285K + # We test a temperature value eith side to check it moves in the right direction + dirname = str(tmpdir) + stepper, theta_initial = run_held_suarez_relaxation(dirname, temp) + + theta_final = stepper.fields('theta') + final_data = theta_final.dat.data + initial_data = theta_initial.dat.data + if temp == 280: + assert np.mean(final_data) > np.mean(initial_data) + if temp == 290: + assert np.mean(final_data) < np.mean(initial_data) From e3055892c6b1fe8cd775291b841b0e27025c0395 Mon Sep 17 00:00:00 2001 From: Daiane Iglesia Dolci <63597005+Ig-dolci@users.noreply.github.com> Date: Thu, 19 Dec 2024 16:03:31 +0000 Subject: [PATCH 7/7] Dolci/fix interpolate warnings (#603) Co-authored-by: Thomas Bendall --- gusto/diagnostics/diagnostics.py | 11 +++++---- .../diagnostics/shallow_water_diagnostics.py | 11 +++++---- gusto/physics/microphysics.py | 23 +++++++++---------- gusto/physics/physics_parametrisation.py | 9 ++++---- gusto/physics/shallow_water_microphysics.py | 15 ++++++------ gusto/recovery/recovery.py | 11 +++++---- gusto/recovery/reversible_recovery.py | 15 ++++++------ gusto/solvers/linear_solvers.py | 15 ++++++------ gusto/time_discretisation/wrappers.py | 9 ++++---- .../semi_implicit_quasi_newton.py | 10 ++++---- 10 files changed, 68 insertions(+), 61 deletions(-) diff --git a/gusto/diagnostics/diagnostics.py b/gusto/diagnostics/diagnostics.py index 90192f022..00272edac 100644 --- a/gusto/diagnostics/diagnostics.py +++ b/gusto/diagnostics/diagnostics.py @@ -1,14 +1,15 @@ """Common diagnostic fields.""" -from firedrake import (assemble, dot, dx, Function, sqrt, TestFunction, +from firedrake import (dot, dx, Function, sqrt, TestFunction, TrialFunction, Constant, grad, inner, FacetNormal, LinearVariationalProblem, LinearVariationalSolver, ds_b, ds_v, ds_t, dS_h, dS_v, ds, dS, div, avg, pi, TensorFunctionSpace, SpatialCoordinate, as_vector, - Projector, Interpolator, FunctionSpace, FiniteElement, + Projector, assemble, FunctionSpace, FiniteElement, TensorProductElement) from firedrake.assign import Assigner +from firedrake.__future__ import interpolate from ufl.domain import extract_unique_domain from abc import ABCMeta, abstractmethod, abstractproperty @@ -193,7 +194,7 @@ def setup(self, domain, state_fields, space=None): # Solve method must be declared in diagnostic's own setup routine if self.method == 'interpolate': - self.evaluator = Interpolator(self.expr, self.field) + self.evaluator = interpolate(self.expr, self.space) elif self.method == 'project': self.evaluator = Projector(self.expr, self.field) elif self.method == 'assign': @@ -207,7 +208,7 @@ def compute(self): logger.debug(f'Computing diagnostic {self.name} with {self.method} method') if self.method == 'interpolate': - self.evaluator.interpolate() + self.field.assign(assemble(self.evaluator)) elif self.method == 'assign': self.evaluator.assign() elif self.method == 'project': @@ -294,7 +295,7 @@ def setup(self, domain, state_fields, space=None): # Solve method must be declared in diagnostic's own setup routine if self.method == 'interpolate': - self.evaluator = Interpolator(self.expr, self.field) + self.evaluator = interpolate(self.expr, self.space) elif self.method == 'project': self.evaluator = Projector(self.expr, self.field) elif self.method == 'assign': diff --git a/gusto/diagnostics/shallow_water_diagnostics.py b/gusto/diagnostics/shallow_water_diagnostics.py index eb2dc4a32..024e58ecf 100644 --- a/gusto/diagnostics/shallow_water_diagnostics.py +++ b/gusto/diagnostics/shallow_water_diagnostics.py @@ -2,9 +2,10 @@ from firedrake import ( - dx, TestFunction, TrialFunction, grad, inner, curl, Function, Interpolator, + dx, TestFunction, TrialFunction, grad, inner, curl, Function, assemble, LinearVariationalProblem, LinearVariationalSolver, conditional ) +from firedrake.__future__ import interpolate from gusto.diagnostics.diagnostics import DiagnosticField, Energy __all__ = ["ShallowWaterKineticEnergy", "ShallowWaterPotentialEnergy", @@ -321,14 +322,14 @@ def setup(self, domain, state_fields): qsat_expr = self.equation.compute_saturation(state_fields.X( self.equation.field_name)) - self.qsat_interpolator = Interpolator(qsat_expr, self.qsat_func) + self.qsat_interpolate = interpolate(qsat_expr, space) self.expr = conditional(q_t < self.qsat_func, q_t, self.qsat_func) super().setup(domain, state_fields, space=space) def compute(self): """Performs the computation of the diagnostic field.""" - self.qsat_interpolator.interpolate() + self.qsat_func.assign(assemble(self.qsat_interpolate)) super().compute() @@ -371,7 +372,7 @@ def setup(self, domain, state_fields): qsat_expr = self.equation.compute_saturation(state_fields.X( self.equation.field_name)) - self.qsat_interpolator = Interpolator(qsat_expr, self.qsat_func) + self.qsat_interpolate = interpolate(qsat_expr, space) vapour = conditional(q_t < self.qsat_func, q_t, self.qsat_func) self.expr = q_t - vapour @@ -379,5 +380,5 @@ def setup(self, domain, state_fields): def compute(self): """Performs the computation of the diagnostic field.""" - self.qsat_interpolator.interpolate() + self.qsat_func.assign(assemble(self.qsat_interpolate)) super().compute() diff --git a/gusto/physics/microphysics.py b/gusto/physics/microphysics.py index e8313ab11..a5cbe3da5 100644 --- a/gusto/physics/microphysics.py +++ b/gusto/physics/microphysics.py @@ -4,9 +4,10 @@ """ from firedrake import ( - Interpolator, conditional, Function, dx, min_value, max_value, Constant, pi, - Projector + conditional, Function, dx, min_value, max_value, Constant, pi, + Projector, assemble ) +from firedrake.__future__ import interpolate from firedrake.fml import identity, Term, subject from gusto.equations import Phases, TracerVariableType from gusto.recovery import Recoverer, BoundaryMethod @@ -170,8 +171,7 @@ def __init__(self, equation, vapour_name='water_vapour', # Add terms to equations and make interpolators # -------------------------------------------------------------------- # self.source = [Function(V) for factor in factors] - self.source_interpolators = [Interpolator(sat_adj_expr*factor, source) - for factor, source in zip(factors, self.source)] + self.source_interpolate = [interpolate(sat_adj_expr*factor, V) for factor in factors] tests = [equation.tests[idx] for idx in V_idxs] @@ -195,8 +195,8 @@ def evaluate(self, x_in, dt): if isinstance(self.equation, CompressibleEulerEquations): self.rho_recoverer.project() # Evaluate the source - for interpolator in self.source_interpolators: - interpolator.interpolate() + for interpolator, src in zip(self.source_interpolate, self.source): + src.assign(assemble(interpolator)) class AdvectedMoments(Enum): @@ -440,7 +440,7 @@ def __init__(self, equation, cloud_name='cloud_water', rain_name='rain', min_value(accu_rate, self.cloud_water / self.dt), min_value(accr_rate + accu_rate, self.cloud_water / self.dt)))) - self.source_interpolator = Interpolator(rain_expr, self.source) + self.source_interpolate = interpolate(rain_expr, Vt) # Add term to equation's residual test_cl = equation.tests[self.cloud_idx] @@ -464,7 +464,7 @@ def evaluate(self, x_in, dt): self.rain.assign(x_in.subfunctions[self.rain_idx]) self.cloud_water.assign(x_in.subfunctions[self.cloud_idx]) # Evaluate the source - self.source.assign(self.source_interpolator.interpolate()) + self.source.assign(assemble(self.source_interpolate)) class EvaporationOfRain(PhysicsParametrisation): @@ -609,8 +609,7 @@ def __init__(self, equation, rain_name='rain', vapour_name='water_vapour', # Add terms to equations and make interpolators # -------------------------------------------------------------------- # self.source = [Function(V) for factor in factors] - self.source_interpolators = [Interpolator(evap_rate*factor, source) - for factor, source in zip(factors, self.source)] + self.source_interpolate = [interpolate(evap_rate*factor, V) for factor in factors] tests = [equation.tests[idx] for idx in V_idxs] @@ -634,5 +633,5 @@ def evaluate(self, x_in, dt): if isinstance(self.equation, CompressibleEulerEquations): self.rho_recoverer.project() # Evaluate the source - for interpolator in self.source_interpolators: - interpolator.interpolate() + for interpolator, src in zip(self.source_interpolate, self.source): + src.assign(assemble(interpolator)) diff --git a/gusto/physics/physics_parametrisation.py b/gusto/physics/physics_parametrisation.py index 2d43dae48..c304c23f6 100644 --- a/gusto/physics/physics_parametrisation.py +++ b/gusto/physics/physics_parametrisation.py @@ -8,7 +8,8 @@ """ from abc import ABCMeta, abstractmethod -from firedrake import Interpolator, Function, dx, Projector +from firedrake import Function, dx, Projector, assemble +from firedrake.__future__ import interpolate from firedrake.fml import subject from gusto.core.labels import PhysicsLabel from gusto.core.logging import logger @@ -117,14 +118,14 @@ def __init__(self, equation, variable_name, rate_expression, # Handle method of evaluating source/sink if self.method == 'interpolate': - self.source_interpolator = Interpolator(expression, V) + self.source_interpolate = interpolate(expression, V) else: self.source_projector = Projector(expression, V) # If not time-varying, evaluate for the first time here if not self.time_varying: if self.method == 'interpolate': - self.source.assign(self.source_interpolator.interpolate()) + self.source.assign(assemble(self.source_interpolate)) else: self.source.assign(self.source_projector.project()) @@ -140,7 +141,7 @@ def evaluate(self, x_in, dt): if self.time_varying: logger.info(f'Evaluating physics parametrisation {self.label.label}') if self.method == 'interpolate': - self.source.assign(self.source_interpolator.interpolate()) + self.source.assign(assemble(self.source_interpolate)) else: self.source.assign(self.source_projector.project()) else: diff --git a/gusto/physics/shallow_water_microphysics.py b/gusto/physics/shallow_water_microphysics.py index bd3f8a02e..7f1b91227 100644 --- a/gusto/physics/shallow_water_microphysics.py +++ b/gusto/physics/shallow_water_microphysics.py @@ -3,8 +3,9 @@ """ from firedrake import ( - Interpolator, conditional, Function, dx, min_value, max_value, Constant + conditional, Function, dx, min_value, max_value, Constant, assemble ) +from firedrake.__future__ import interpolate from firedrake.fml import subject from gusto.core.logging import logger from gusto.physics.physics_parametrisation import PhysicsParametrisation @@ -134,7 +135,7 @@ def __init__(self, equation, saturation_curve, self.evaluate) # interpolator does the conversion of vapour to rain - self.source_interpolator = Interpolator(conditional( + self.source_interpolate = interpolate(conditional( self.water_v > self.saturation_curve, (1/self.tau)*gamma_r*(self.water_v - self.saturation_curve), 0), Vv) @@ -159,7 +160,7 @@ def evaluate(self, x_in, dt): if self.set_tau_to_dt: self.tau.assign(dt) self.water_v.assign(x_in.subfunctions[self.Vv_idx]) - self.source.assign(self.source_interpolator.interpolate()) + self.source.assign(assemble(self.source_interpolate)) class SWSaturationAdjustment(PhysicsParametrisation): @@ -321,8 +322,8 @@ def __init__(self, equation, saturation_curve, # Add terms to equations and make interpolators # sources have the same order as V_idxs and factors self.source = [Function(Vc) for factor in factors] - self.source_interpolators = [Interpolator(sat_adj_expr*factor, source) - for factor, source in zip(factors, self.source)] + self.source_interpolate = [interpolate(sat_adj_expr*factor, Vc) + for factor in factors] # test functions have the same order as factors and sources (vapour, # cloud, depth, buoyancy) so that the correct test function multiplies @@ -359,5 +360,5 @@ def evaluate(self, x_in, dt): self.cloud.assign(x_in.subfunctions[self.Vc_idx]) if self.time_varying_gamma_v: self.gamma_v.interpolate(self.gamma_v_computation(x_in)) - for interpolator in self.source_interpolators: - interpolator.interpolate() + for interpolator, src in zip(self.source_interpolate, self.source): + src.assign(assemble(interpolator)) diff --git a/gusto/recovery/recovery.py b/gusto/recovery/recovery.py index b88c6ad6a..9d186dd48 100644 --- a/gusto/recovery/recovery.py +++ b/gusto/recovery/recovery.py @@ -13,7 +13,8 @@ Function, FunctionSpace, Interpolator, Projector, SpatialCoordinate, TensorProductElement, VectorFunctionSpace, as_vector, function, interval, - VectorElement) + VectorElement, assemble) +from firedrake.__future__ import interpolate from gusto.recovery import Averager from .recovery_kernels import (BoundaryRecoveryExtruded, BoundaryRecoveryHCurl, BoundaryGaussianElimination) @@ -144,14 +145,14 @@ def __init__(self, x_inout, method=BoundaryMethod.extruded, eff_coords=None): V_broken = FunctionSpace(mesh, BrokenElement(V_inout.ufl_element())) self.x_DG1_wrong = Function(V_broken) self.x_DG1_correct = Function(V_broken) - self.interpolator = Interpolator(self.x_inout, self.x_DG1_wrong) + self.interpolate = interpolate(self.x_inout, V_broken) self.averager = Averager(self.x_DG1_correct, self.x_inout) self.kernel = BoundaryGaussianElimination(V_broken) def apply(self): """Applies the boundary recovery process.""" if self.method == BoundaryMethod.taylor: - self.interpolator.interpolate() + self.x_DG1_wrong.assign(assemble(self.interpolate)) self.kernel.apply(self.x_DG1_wrong, self.x_DG1_correct, self.act_coords, self.eff_coords, self.num_ext) self.averager.project() @@ -275,7 +276,7 @@ def __init__(self, x_in, x_out, method='interpolate', boundary_method=None): self.boundary_recoverers.append(BoundaryRecoverer(x_out_scalars[i], method=BoundaryMethod.taylor, eff_coords=eff_coords[i])) - self.interpolate_to_vector = Interpolator(as_vector(x_out_scalars), self.x_out) + self.interpolate_to_vector = interpolate(as_vector(x_out_scalars), V_out) def project(self): """Perform the whole recovery step.""" @@ -294,7 +295,7 @@ def project(self): # Correct at boundaries boundary_recoverer.apply() # Combine the components to obtain the vector field - self.interpolate_to_vector.interpolate() + self.x_out.assign(assemble(self.interpolate_to_vector)) else: # Extrapolate at boundaries self.boundary_recoverer.apply() diff --git a/gusto/recovery/reversible_recovery.py b/gusto/recovery/reversible_recovery.py index fc8fbd332..d87449817 100644 --- a/gusto/recovery/reversible_recovery.py +++ b/gusto/recovery/reversible_recovery.py @@ -4,7 +4,8 @@ """ from gusto.core.conservative_projection import ConservativeProjector -from firedrake import (Projector, Function, Interpolator) +from firedrake import (Projector, Function, assemble) +from firedrake.__future__ import interpolate from .recovery import Recoverer __all__ = ["ReversibleRecoverer", "ConservativeRecoverer"] @@ -52,7 +53,7 @@ def __init__(self, source_field, target_field, reconstruct_opts): elif self.opts.project_high_method == 'project': self.projector_high = Projector(self.q_recovered, self.q_rec_high) elif self.opts.project_high_method == 'interpolate': - self.projector_high = Interpolator(self.q_recovered, self.q_rec_high) + self.projector_high = interpolate(self.q_recovered, target_field.function_space()) self.interp_high = True else: raise ValueError(f'Method {self.opts.project_high_method} ' @@ -68,7 +69,7 @@ def __init__(self, source_field, target_field, reconstruct_opts): elif self.opts.project_low_method == 'project': self.projector_low = Projector(self.q_rec_high, self.q_corr_low) elif self.opts.project_low_method == 'interpolate': - self.projector_low = Interpolator(self.q_rec_high, self.q_corr_low) + self.projector_low = interpolate(self.q_rec_high, source_field.function_space()) self.interp_low = True else: raise ValueError(f'Method {self.opts.project_low_method} ' @@ -84,17 +85,17 @@ def __init__(self, source_field, target_field, reconstruct_opts): elif self.opts.injection_method == 'project': self.injector = Projector(self.q_corr_low, self.q_corr_high) elif self.opts.injection_method == 'interpolate': - self.injector = Interpolator(self.q_corr_low, self.q_corr_high) + self.injector = interpolate(self.q_corr_low, target_field.function_space()) self.interp_inj = True else: raise ValueError(f'Method {self.opts.injection_method} for injection not valid') def project(self): self.recoverer.project() - self.projector_high.interpolate() if self.interp_high else self.projector_high.project() - self.projector_low.interpolate() if self.interp_low else self.projector_low.project() + self.q_rec_high.assign(assemble(self.projector_high)) if self.interp_high else self.projector_high.project() + self.q_corr_low.assign(assemble(self.projector_low)) if self.interp_low else self.projector_low.project() self.q_corr_low.assign(self.q_low - self.q_corr_low) - self.injector.interpolate() if self.interp_inj else self.injector.project() + self.q_corr_high.assign(assemble(self.injector)) if self.interp_inj else self.injector.project() self.q_high.assign(self.q_corr_high + self.q_rec_high) diff --git a/gusto/solvers/linear_solvers.py b/gusto/solvers/linear_solvers.py index 1f44cc950..ca684c6af 100644 --- a/gusto/solvers/linear_solvers.py +++ b/gusto/solvers/linear_solvers.py @@ -11,10 +11,11 @@ rhs, FacetNormal, div, dx, jump, avg, dS, dS_v, dS_h, ds_v, ds_t, ds_b, ds_tb, inner, action, dot, grad, Function, VectorSpaceBasis, cross, BrokenElement, FunctionSpace, MixedFunctionSpace, DirichletBC, as_vector, - Interpolator, conditional + assemble, conditional ) from firedrake.fml import Term, drop from firedrake.petsc import flatten_parameters +from firedrake.__future__ import interpolate from pyop2.profiling import timed_function, timed_region from gusto.equations.active_tracers import TracerVariableType @@ -660,11 +661,11 @@ def _setup_solver(self): qtbar = split(equation.X_ref)[3] # set up interpolators that use the X_ref values for D and b_e - self.q_sat_expr_interpolator = Interpolator( - equation.compute_saturation(equation.X_ref), self.q_sat_func) - self.q_v_interpolator = Interpolator( + self.q_sat_expr_interpolate = interpolate( + equation.compute_saturation(equation.X_ref), VD) + self.q_v_interpolate = interpolate( conditional(qtbar < self.q_sat_func, qtbar, self.q_sat_func), - self.qvbar) + VD) # bbar was be_bar and here we correct to become bbar bbar += equation.parameters.beta2 * self.qvbar @@ -729,8 +730,8 @@ def trace_nullsp(T): @timed_function("Gusto:UpdateReferenceProfiles") def update_reference_profiles(self): if self.equations.equivalent_buoyancy: - self.q_sat_expr_interpolator.interpolate() - self.q_v_interpolator.interpolate() + self.q_sat_func.assign(assemble(self.q_sat_expr_interpolate)) + self.qvbar.assign(assemble(self.q_v_interpolate)) @timed_function("Gusto:LinearSolve") def solve(self, xrhs, dy): diff --git a/gusto/time_discretisation/wrappers.py b/gusto/time_discretisation/wrappers.py index f0aae843e..18381bc1f 100644 --- a/gusto/time_discretisation/wrappers.py +++ b/gusto/time_discretisation/wrappers.py @@ -6,9 +6,10 @@ from abc import ABCMeta, abstractmethod from firedrake import ( - FunctionSpace, Function, BrokenElement, Projector, Interpolator, - Constant, as_ufl, dot, grad, TestFunction, MixedFunctionSpace + FunctionSpace, Function, BrokenElement, Projector, Constant, as_ufl, dot, grad, + TestFunction, MixedFunctionSpace, assemble ) +from firedrake.__future__ import interpolate from firedrake.fml import Term from gusto.core.configuration import EmbeddedDGOptions, RecoveryOptions, SUPGOptions from gusto.recovery import Recoverer, ReversibleRecoverer, ConservativeRecoverer @@ -264,7 +265,7 @@ def setup(self, original_space, post_apply_bcs): # Operators for projecting back self.interp_back = (self.options.project_low_method == 'interpolate') if self.options.project_low_method == 'interpolate': - self.x_out_projector = Interpolator(self.x_out, self.x_projected) + self.x_out_projector = interpolate(self.x_out, self.original_space) elif self.options.project_low_method == 'project': self.x_out_projector = Projector(self.x_out, self.x_projected, bcs=post_apply_bcs) @@ -302,7 +303,7 @@ def post_apply(self, x_out): """ if self.interp_back: - self.x_out_projector.interpolate() + self.x_projected.assign(assemble(self.x_out_projector)) else: self.x_out_projector.project() x_out.assign(self.x_projected) diff --git a/gusto/timestepping/semi_implicit_quasi_newton.py b/gusto/timestepping/semi_implicit_quasi_newton.py index c5f8a7ece..19142dbaa 100644 --- a/gusto/timestepping/semi_implicit_quasi_newton.py +++ b/gusto/timestepping/semi_implicit_quasi_newton.py @@ -4,10 +4,11 @@ """ from firedrake import ( - Function, Constant, TrialFunctions, DirichletBC, div, Interpolator, + Function, Constant, TrialFunctions, DirichletBC, div, assemble, LinearVariationalProblem, LinearVariationalSolver ) from firedrake.fml import drop, replace_subject +from firedrake.__future__ import interpolate from pyop2.profiling import timed_stage from gusto.core import TimeLevelFields, StateFields from gusto.core.labels import (transport, diffusion, time_derivative, @@ -234,9 +235,8 @@ def __init__(self, equation_set, io, transport_schemes, spatial_methods, V_DG = equation_set.domain.spaces('DG') self.predictor_field_in = Function(V_DG) div_factor = Constant(1.0) - (Constant(1.0) - self.alpha)*self.dt*div(self.x.n('u')) - self.predictor_interpolator = Interpolator( - self.x.star(predictor)*div_factor, self.predictor_field_in - ) + self.predictor_interpolate = interpolate( + self.x.star(predictor)*div_factor, V_DG) def _apply_bcs(self): """ @@ -334,7 +334,7 @@ def transport_fields(self, outer, xstar, xp): # Pre-multiply this variable by (1 - dt*beta*div(u)) V = xstar(name).function_space() field_out = Function(V) - self.predictor_interpolator.interpolate() + self.predictor_field_in.assign(assemble(self.predictor_interpolate)) scheme.apply(field_out, self.predictor_field_in) # xp is xstar plus the increment from the transported predictor