upload parameter.py file for ITPA benchmark simulations

ITPA_benchmark/gc.py

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+from struphy.io.options import EnvironmentOptions, BaseUnits, Time
+from struphy.geometry import domains
+from struphy.fields_background import equils
+from struphy.topology import grids
+from struphy.io.options import DerhamOptions
+from struphy.io.options import FieldsBackground
+from struphy.initial import perturbations
+from struphy.kinetic_background import maxwellians
+from struphy.pic.utilities import (LoadingParameters,
+                                   WeightsParameters,
+                                   BoundaryParameters,
+                                   BinningPlot,
+                                   KernelDensityPlot,
+                                   )
+from struphy import main
+
+# import model, set verbosity
+from struphy.models.toy import GuidingCenter
+
+# environment options
+env = EnvironmentOptions(
+    out_folders='/tokp/work/bkna/tae', 
+    sim_folder='gc', 
+    save_step=8, max_runtime=1440)
+
+# units
+base_units = BaseUnits(n=0.2)
+
+# time stepping
+time_opts = Time(dt=0.25, Tend=200., split_algo='Strang')
+
+# geometry
+domain = domains.HollowTorus(a1=0.1, a2=1., R0=10., sfl=False, tor_period=6)
+
+# fluid equilibrium (can be used as part of initial conditions)
+equil = equils.AdhocTorus(
+    a=1.,
+    R0=10.,
+    B0=3.,
+    q_kind=0,
+    q0=1.71,
+    q1=1.87,
+    n1=0.,
+    n2=0.,
+    na=1.,
+    p_kind=1.,
+    p0=1.,
+    p1=0.95,
+    p2=0.05,
+    beta=0.0018,
+)
+
+# grid
+grid = grids.TensorProductGrid(
+    Nel=(24,96,16),
+    mpi_dims_mask=(True, True, False)
+)
+
+# derham options
+derham_opts = DerhamOptions(
+    p=(3, 3, 3),
+    spl_kind=(False, True, True),
+    dirichlet_bc=((True, True), (False, False), (False, False)),
+    nq_pr=(6, 6, 6),
+    nquads=(6, 6, 6),
+    polar_ck=-1,
+)
+
+# light-weight model instance
+model = GuidingCenter()
+
+# species parameters
+model.kinetic_ions.set_phys_params(
+    charge_number=2.,
+)
+
+loading_params = LoadingParameters(
+    ppc=100,
+    moments=(0., 0., 0.89740839, 0.89740839)
+    )
+weights_params = WeightsParameters(
+    control_variate=True,
+)
+boundary_params = BoundaryParameters(
+    bc=("remove", "periodic", "periodic"),
+    bc_refill=("outer", "inner"),
+)
+model.kinetic_ions.set_markers(loading_params=loading_params,
+                                 weights_params=weights_params,
+                                 boundary_params=boundary_params,
+                                 bufsize=1.,
+                                 n_cols_diag=3,
+                                 n_cols_aux=5,
+                                 )
+model.kinetic_ions.set_sorting_boxes(boxes_per_dim=None)
+binning_plots = (
+    BinningPlot(
+    slice="e1",
+    n_bins=128,
+    ranges=(0., 1.),
+    divide_by_jac=True),
+    BinningPlot(
+    slice="v1",
+    n_bins=128,
+    ranges=(-2.5, 2.5),
+    divide_by_jac=True),
+    )
+model.kinetic_ions.set_save_data(
+    binning_plots=binning_plots,
+)
+
+# propagator options
+model.propagators.push_bxe.options = model.propagators.push_bxe.Options(
+                        algo = 'explicit',)
+model.propagators.push_parallel.options = model.propagators.push_parallel.Options(
+                        algo = 'explicit',)
+# background, perturbations and initial conditions
+n_profile = perturbations.ITPA_density(
+    n0=0.00720652,
+    c=(0.47023, 0.20323, 0.13273, 0.521298)
+)
+maxwellian_1 = maxwellians.CanonicalMaxwellian2D(
+    equil=equil,
+    volume_form=True,
+    n=(0., n_profile),
+)
+
+background = maxwellian_1
+model.kinetic_ions.var.add_background(background, n_as_volume_form=False)
+
+if __name__ == "__main__":
+    # start run
+    verbose = True
+
+    main.run(model,
+             params_path=__file__,
+             env=env,
+             base_units=base_units,
+             time_opts=time_opts,
+             domain=domain,
+             equil=equil,
+             grid=grid,
+             derham_opts=derham_opts,
+             verbose=verbose,
+             )

ITPA_benchmark/linearmhd.py

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+from struphy.io.options import EnvironmentOptions, BaseUnits, Time
+from struphy.geometry import domains
+from struphy.fields_background import equils
+from struphy.topology import grids
+from struphy.io.options import DerhamOptions
+from struphy.io.options import FieldsBackground
+from struphy.initial import perturbations
+from struphy.kinetic_background import maxwellians
+from struphy.pic.utilities import (LoadingParameters,
+                                   WeightsParameters,
+                                   BoundaryParameters,
+                                   BinningPlot,
+                                   KernelDensityPlot,
+                                   )
+from struphy import main
+
+# import model, set verbosity
+from struphy.models.fluid import LinearMHD
+
+# environment options
+env = EnvironmentOptions(
+    out_folders='/tokp/work/bkna/tae', 
+    sim_folder='linearmhd', 
+    save_step=8, max_runtime=1440)
+
+
+# units
+base_units = BaseUnits(n=0.2)
+
+# time stepping
+time_opts = Time(dt=0.25, Tend=200., split_algo='Strang')
+
+# geometry
+domain = domains.HollowTorus(a1=0.1, a2=1., R0=10., sfl=False, tor_period=6)
+
+# fluid equilibrium (can be used as part of initial conditions)
+equil = equils.AdhocTorus(
+    a=1.,
+    R0=10.,
+    B0=3.,
+    q_kind=0,
+    q0=1.71,
+    q1=1.87,
+    n1=0.,
+    n2=0.,
+    na=1.,
+    p_kind=1.,
+    p0=1.,
+    p1=0.95,
+    p2=0.05,
+    beta=0.0018,
+)
+
+# grid
+grid = grids.TensorProductGrid(
+    Nel=(24,96,16), 
+    mpi_dims_mask=(True, True, False)
+)
+
+# derham options
+derham_opts = DerhamOptions(
+    p=(3, 3, 3),
+    spl_kind=(False, True, True),
+    dirichlet_bc=((True, True), (False, False), (False, False)),
+    nq_pr=(6, 6, 6),
+    nquads=(6, 6, 6),
+    polar_ck=-1,
+)
+
+# light-weight model instance
+model = LinearMHD()
+
+# species parameters
+model.mhd.set_phys_params()
+
+# propagator options
+model.propagators.shear_alf.options = model.propagators.shear_alf.Options(
+    algo='implicit',
+    precond='MassMatrixDiagonalPreconditioner',
+)
+model.propagators.mag_sonic.options = model.propagators.mag_sonic.Options(b_field=model.em_fields.b_field)
+
+# background, perturbations and initial conditions
+model.mhd.velocity.add_background(FieldsBackground(
+    type="LogicalConst",
+    values=(0., 0., 0.)
+))
+model.mhd.velocity.add_perturbation(
+    perturbations.TorusModesSin(
+        given_in_basis="2",
+        amps=(0.01,0.01),
+        ms=(10,11),
+        ns=(-1,-1),
+        pfuns=('exp','exp'),
+        pfun_params=((0.44444444,0.1),(0.44444444,0.1)),
+        comp=0)
+)
+model.mhd.velocity.add_perturbation(
+     perturbations.TorusModesCos(
+        given_in_basis="2",
+        amps=(0.00015915,0.00015915),
+        ms=(10,11),
+        ns=(-1,-1),
+        pfuns=('d_exp','d_exp'),
+        pfun_params=((0.44444444,0.1),(0.44444444,0.1)),
+        comp=1),
+)
+
+# optional: exclude variables from saving
+# model.mhd.pressure.save_data = False
+
+if __name__ == "__main__":
+    # start run
+    verbose = True
+
+    main.run(model,
+             params_path=__file__,
+             env=env,
+             base_units=base_units,
+             time_opts=time_opts,
+             domain=domain,
+             equil=equil,
+             grid=grid,
+             derham_opts=derham_opts,
+             verbose=verbose,
+             )