aderdg.py

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# This file is part of the ExaHyPE2 project. For conditions of distribution and
# use, please see the copyright notice at www.peano-framework.org
import peano4
import exahype2
 
import scenarios
 
available_precisions = {
    "bf16", "fp16", "fp32", "fp64"
}
 
available_scenarios = {
    "AcousticPlanarWaves": scenarios.AcousticPlanarWaves(dimensions=2),
    "AdvectionLinear": scenarios.AdvectionLinear(),
    "ElasticPlanarWaves": scenarios.ElasticPlanarWaves(dimensions=2),
    "EulerGaussianBell": scenarios.EulerGaussianBell(),
    "EulerIsentropicVortex": scenarios.EulerIsentropicVortex(),
    "SWERadialDamBreak": scenarios.SWERadialDamBreak(),
    "SWERestingLake": scenarios.SWERestingLake(),
}
 
parser = exahype2.ArgumentParser("ExaHyPE 2 - ADER-DG Testing Script")
parser.add_argument("-pr", "--precision", default="fp64", help="|".join(available_precisions))
parser.add_argument("-s", "--scenario", default=None, help="|".join(available_scenarios.keys()))
parser.set_defaults(
    min_depth=3,
    degrees_of_freedom=4,
)
args = parser.parse_args()
 
if args.scenario is None:
    while True:
        try:
            s = input(
                "Which of the following scenarios would you like to test?\n"
                + " - ".join(available_scenarios.keys())
                + "\n"
            )
            scenario = available_scenarios[s]
        except KeyError:
            continue
        else:
            # User has specified a valid scenario
            break
else:
    scenario = available_scenarios[args.scenario]
 
order = args.degrees_of_freedom - 1
max_h = 1.1 * scenario._domain_size / (3.0**args.min_depth)
min_h = max_h * 3.0 ** (-args.amr_levels)
 
polynomials = exahype2.solvers.aderdg.Polynomials.Gauss_Legendre
 
project = exahype2.Project(
    namespace=["tests", "exahype2", "aderdg"],
    project_name=scenario.__class__.__name__,
    directory=".",
    executable="ADERDG",
)
 
solver = exahype2.solvers.aderdg.GlobalAdaptiveTimeStep(
    name="ADERDGSolver",
    order=order,
    min_cell_h=min_h,
    max_cell_h=max_h,
    time_step_relaxation=0.9,
    unknowns=scenario._equation.num_unknowns,
    auxiliary_variables=scenario._equation.num_auxiliary_variables,
)
 
solver.add_kernel_optimisations(
    polynomials=polynomials,
    is_linear=scenario._equation.is_linear,
    precision=args.precision
)
 
solver.set_implementation(
    initial_conditions=scenario.initial_conditions(),
    boundary_conditions=scenario.boundary_conditions(),
    max_eigenvalue=scenario._equation.eigenvalues(),
    flux=scenario._equation.flux(),
    ncp=scenario._equation.ncp(),
    riemann_solver=scenario._equation.riemann_solver(),
)
 
solver.set_plotter(args.plotter)
 
if scenario.analytical_solution() != exahype2.solvers.PDETerms.None_Implementation:
    exahype2.solvers.aderdg.ErrorMeasurement(
        solver,
        error_measurement_implementation=scenario.analytical_solution(),
        output_file_name="Error_" + scenario.__class__.__name__,
    )
 
project.add_solver(solver)
project.set_output_path("solutions")
scenario.set_global_simulation_parameters(project)
project.set_load_balancer("new ::exahype2::LoadBalancingConfiguration")
project.set_Peano4_installation("../../../", mode=peano4.output.string_to_mode(args.build_mode))
project = project.generate_Peano4_project(verbose=False)
project.set_fenv_handler(args.fpe)
project.build(make_clean_first=True)