Source code for yt.frontends.enzo.fields

import numpy as np

from yt._typing import KnownFieldsT
from yt.fields.field_info_container import FieldInfoContainer
from yt.utilities.physical_constants import me, mp

b_units = "code_magnetic"
e_units = "code_magnetic/c"
ra_units = "code_length / code_time**2"
rho_units = "code_mass / code_length**3"
vel_units = "code_velocity"

known_species_names = {
    "HI": "H_p0",
    "HII": "H_p1",
    "HeI": "He_p0",
    "HeII": "He_p1",
    "HeIII": "He_p2",
    "H2I": "H2_p0",
    "H2II": "H2_p1",
    "HM": "H_m1",
    "HeH": "HeH_p0",
    "DI": "D_p0",
    "DII": "D_p1",
    "HDI": "HD_p0",
    "Electron": "El",
    "OI": "O_p0",
    "OII": "O_p1",
    "OIII": "O_p2",
    "OIV": "O_p3",
    "OV": "O_p4",
    "OVI": "O_p5",
    "OVII": "O_p6",
    "OVIII": "O_p7",
    "OIX": "O_p8",
}

NODAL_FLAGS = {
    "BxF": [1, 0, 0],
    "ByF": [0, 1, 0],
    "BzF": [0, 0, 1],
    "Ex": [0, 1, 1],
    "Ey": [1, 0, 1],
    "Ez": [1, 1, 0],
    "AvgElec0": [0, 1, 1],
    "AvgElec1": [1, 0, 1],
    "AvgElec2": [1, 1, 0],
}


[docs] class EnzoFieldInfo(FieldInfoContainer): known_other_fields: KnownFieldsT = ( ("Cooling_Time", ("s", ["cooling_time"], None)), ("Dengo_Cooling_Rate", ("erg/g/s", [], None)), ("Grackle_Cooling_Rate", ("erg/s/cm**3", [], None)), ("HI_kph", ("1/code_time", ["H_p0_ionization_rate"], None)), ("HeI_kph", ("1/code_time", ["He_p0_ionization_rate"], None)), ("HeII_kph", ("1/code_time", ["He_p1_ionization_rate"], None)), ("H2I_kdiss", ("1/code_time", ["H2_p0_dissociation_rate"], None)), ("HM_kph", ("1/code_time", ["H_m1_ionization_rate"], None)), ("H2II_kdiss", ("1/code_time", ["H2_p1_dissociation_rate"], None)), ("Bx", (b_units, [], None)), ("By", (b_units, [], None)), ("Bz", (b_units, [], None)), ("BxF", (b_units, [], None)), ("ByF", (b_units, [], None)), ("BzF", (b_units, [], None)), ("Ex", (e_units, [], None)), ("Ey", (e_units, [], None)), ("Ez", (e_units, [], None)), ("AvgElec0", (e_units, [], None)), ("AvgElec1", (e_units, [], None)), ("AvgElec2", (e_units, [], None)), ("RadAccel1", (ra_units, ["radiation_acceleration_x"], None)), ("RadAccel2", (ra_units, ["radiation_acceleration_y"], None)), ("RadAccel3", (ra_units, ["radiation_acceleration_z"], None)), ("Dark_Matter_Density", (rho_units, ["dark_matter_density"], None)), ("Temperature", ("K", ["temperature"], None)), ("Dust_Temperature", ("K", ["dust_temperature"], None)), ("x-velocity", (vel_units, ["velocity_x"], None)), ("y-velocity", (vel_units, ["velocity_y"], None)), ("z-velocity", (vel_units, ["velocity_z"], None)), ("RaySegments", ("", ["ray_segments"], None)), ("PhotoGamma", ("eV/code_time", ["photo_gamma"], None)), ("PotentialField", ("code_velocity**2", ["gravitational_potential"], None)), ("Density", (rho_units, ["density"], None)), ("Metal_Density", (rho_units, ["metal_density"], None)), ("SN_Colour", (rho_units, [], None)), # Note: we do not alias Electron_Density to anything ("Electron_Density", (rho_units, [], None)), ) known_particle_fields: KnownFieldsT = ( ("particle_position_x", ("code_length", [], None)), ("particle_position_y", ("code_length", [], None)), ("particle_position_z", ("code_length", [], None)), ("particle_velocity_x", (vel_units, [], None)), ("particle_velocity_y", (vel_units, [], None)), ("particle_velocity_z", (vel_units, [], None)), ("creation_time", ("code_time", [], None)), ("dynamical_time", ("code_time", [], None)), ("metallicity_fraction", ("code_metallicity", [], None)), ("metallicity", ("", [], None)), ("particle_type", ("", [], None)), ("particle_index", ("", [], None)), ("particle_mass", ("code_mass", [], None)), ("GridID", ("", [], None)), ("identifier", ("", ["particle_index"], None)), ("level", ("", [], None)), ("AccretionRate", ("code_mass/code_time", [], None)), ("AccretionRateTime", ("code_time", [], None)), ("AccretionRadius", ("code_length", [], None)), ("RadiationLifetime", ("code_time", [], None)), ) def __init__(self, ds, field_list): hydro_method = ds.parameters.get("HydroMethod", None) if hydro_method is None: hydro_method = ds.parameters["Physics"]["Hydro"]["HydroMethod"] if hydro_method == 2: sl_left = slice(None, -2, None) sl_right = slice(1, -1, None) div_fac = 1.0 else: sl_left = slice(None, -2, None) sl_right = slice(2, None, None) div_fac = 2.0 slice_info = (sl_left, sl_right, div_fac) super().__init__(ds, field_list, slice_info) # setup nodal flag information for field in NODAL_FLAGS: if ("enzo", field) in self: finfo = self["enzo", field] finfo.nodal_flag = np.array(NODAL_FLAGS[field])
[docs] def add_species_field(self, species): # This is currently specific to Enzo. Hopefully in the future we will # have deeper integration with other systems, such as Dengo, to provide # better understanding of ionization and molecular states. # # We have several fields to add based on a given species field. First # off, we add the species field itself. Then we'll add a few more # items... # self.add_output_field( ("enzo", f"{species}_Density"), sampling_type="cell", take_log=True, units="code_mass/code_length**3", ) yt_name = known_species_names[species] # don't alias electron density since mass is wrong if species != "Electron": self.alias(("gas", f"{yt_name}_density"), ("enzo", f"{species}_Density"))
[docs] def setup_species_fields(self): species_names = [ fn.rsplit("_Density")[0] for ft, fn in self.field_list if fn.endswith("_Density") ] species_names = [sp for sp in species_names if sp in known_species_names] def _electron_density(field, data): return data["enzo", "Electron_Density"] * (me / mp) self.add_field( ("gas", "El_density"), sampling_type="cell", function=_electron_density, units=self.ds.unit_system["density"], ) for sp in species_names: self.add_species_field(sp) self.species_names.append(known_species_names[sp]) self.species_names.sort() # bb #1059
[docs] def setup_fluid_fields(self): from yt.fields.magnetic_field import setup_magnetic_field_aliases # Now we conditionally load a few other things. params = self.ds.parameters multi_species = params.get("MultiSpecies", None) dengo = params.get("DengoChemistryModel", 0) if multi_species is None: multi_species = params["Physics"]["AtomicPhysics"]["MultiSpecies"] if multi_species > 0 or dengo == 1: self.setup_species_fields() self.setup_energy_field() setup_magnetic_field_aliases(self, "enzo", [f"B{ax}" for ax in "xyz"])
[docs] def setup_energy_field(self): unit_system = self.ds.unit_system # We check which type of field we need, and then we add it. ge_name = None te_name = None params = self.ds.parameters multi_species = params.get("MultiSpecies", None) if multi_species is None: multi_species = params["Physics"]["AtomicPhysics"]["MultiSpecies"] hydro_method = params.get("HydroMethod", None) if hydro_method is None: hydro_method = params["Physics"]["Hydro"]["HydroMethod"] dual_energy = params.get("DualEnergyFormalism", None) if dual_energy is None: dual_energy = params["Physics"]["Hydro"]["DualEnergyFormalism"] if ("enzo", "Gas_Energy") in self.field_list: ge_name = "Gas_Energy" elif ("enzo", "GasEnergy") in self.field_list: ge_name = "GasEnergy" if ("enzo", "Total_Energy") in self.field_list: te_name = "Total_Energy" elif ("enzo", "TotalEnergy") in self.field_list: te_name = "TotalEnergy" if hydro_method == 2 and te_name is not None: self.add_output_field( ("enzo", te_name), sampling_type="cell", units="code_velocity**2" ) self.alias(("gas", "specific_thermal_energy"), ("enzo", te_name)) def _ge_plus_kin(field, data): ret = data["enzo", te_name] + 0.5 * data["gas", "velocity_x"] ** 2.0 if data.ds.dimensionality > 1: ret += 0.5 * data["gas", "velocity_y"] ** 2.0 if data.ds.dimensionality > 2: ret += 0.5 * data["gas", "velocity_z"] ** 2.0 return ret self.add_field( ("gas", "specific_total_energy"), sampling_type="cell", function=_ge_plus_kin, units=unit_system["specific_energy"], ) elif dual_energy == 1: if te_name is not None: self.add_output_field( ("enzo", te_name), sampling_type="cell", units="code_velocity**2" ) self.alias( ("gas", "specific_total_energy"), ("enzo", te_name), units=unit_system["specific_energy"], ) if ge_name is not None: self.add_output_field( ("enzo", ge_name), sampling_type="cell", units="code_velocity**2" ) self.alias( ("gas", "specific_thermal_energy"), ("enzo", ge_name), units=unit_system["specific_energy"], ) elif hydro_method in (4, 6) and te_name is not None: self.add_output_field( ("enzo", te_name), sampling_type="cell", units="code_velocity**2" ) # Subtract off B-field energy def _sub_b(field, data): ret = data["enzo", te_name] - 0.5 * data["gas", "velocity_x"] ** 2.0 if data.ds.dimensionality > 1: ret -= 0.5 * data["gas", "velocity_y"] ** 2.0 if data.ds.dimensionality > 2: ret -= 0.5 * data["gas", "velocity_z"] ** 2.0 ret -= data["gas", "magnetic_energy_density"] / data["gas", "density"] return ret self.add_field( ("gas", "specific_thermal_energy"), sampling_type="cell", function=_sub_b, units=unit_system["specific_energy"], ) elif te_name is not None: # Otherwise, we assume TotalEnergy is kinetic+thermal self.add_output_field( ("enzo", te_name), sampling_type="cell", units="code_velocity**2" ) self.alias( ("gas", "specific_total_energy"), ("enzo", te_name), units=unit_system["specific_energy"], ) def _tot_minus_kin(field, data): ret = data["enzo", te_name] - 0.5 * data["gas", "velocity_x"] ** 2.0 if data.ds.dimensionality > 1: ret -= 0.5 * data["gas", "velocity_y"] ** 2.0 if data.ds.dimensionality > 2: ret -= 0.5 * data["gas", "velocity_z"] ** 2.0 return ret self.add_field( ("gas", "specific_thermal_energy"), sampling_type="cell", function=_tot_minus_kin, units=unit_system["specific_energy"], ) if multi_species == 0 and "Mu" in params: def _mean_molecular_weight(field, data): return params["Mu"] * data["index", "ones"] self.add_field( ("gas", "mean_molecular_weight"), sampling_type="cell", function=_mean_molecular_weight, units="", ) def _number_density(field, data): return data["gas", "density"] / (mp * params["Mu"]) self.add_field( ("gas", "number_density"), sampling_type="cell", function=_number_density, units=unit_system["number_density"], )
[docs] def setup_particle_fields(self, ptype): def _age(field, data): return data.ds.current_time - data["all", "creation_time"] self.add_field( (ptype, "age"), sampling_type="particle", function=_age, units="yr" ) super().setup_particle_fields(ptype)