def _write_attrib(obj_list, k, v, hd):
#print('obj_list: ',dir(obj_list))
#print('k: ',k)
#print('v: ', v)
unit = False
if isinstance(v, YTQuantity):
data = [getattr(i, k).d for i in obj_list]
unit = True
elif isinstance(v, YTArray):
if np.shape(v)[0] == 3:
data = np.vstack([getattr(i, k).d for i in obj_list])
else:
data = [getattr(i, k).d for i in obj_list]
unit = True
elif isinstance(v, np.ndarray) and np.shape(v)[0] == 3 and 'list' not in k:
try:
data = np.vstack([getattr(i, k) for i in obj_list])
except:
mylog.warning('Saver unable to stack: %s %s %s', k, v, np.shape(v))
return
elif isinstance(v, (int, float, bool, np.number)):
data = [getattr(i, k) for i in obj_list]
else:
return
_write_dataset(k, data, hd)
if unit:
hd[k].attrs.create('unit', str(v.units).encode('utf8'))
def set_field(self, name, value):
"""
Set a field with name *name* to value *value*, which is a YTArray.
The array will be checked to make sure that it has the appropriate size.
"""
if not isinstance(value, YTArray):
raise TypeError("value needs to be a YTArray")
if len(value) == self.num_elements:
if name in self.fields:
mylog.warning("Overwriting field %s." % name)
self.fields[name] = value
else:
raise ValueError("The length of the array needs to be %d elements!"
% self.num_elements)
def setup_fluid_fields(self):
setup_magnetic_field_aliases(self, "amrvac",
[f"mag{ax}" for ax in "xyz"])
self._setup_velocity_fields() # gas velocities
self._setup_dust_fields() # dust derived fields (including velocities)
# fields with nested dependencies are defined thereafter
# by increasing level of complexity
us = self.ds.unit_system
def _kinetic_energy_density(field, data):
# devnote : have a look at issue 1301
return 0.5 * data["gas", "density"] * data["gas",
"velocity_magnitude"]**2
self.add_field(
("gas", "kinetic_energy_density"),
function=_kinetic_energy_density,
units=us["density"] * us["velocity"]**2,
dimensions=dimensions.density * dimensions.velocity**2,
sampling_type="cell",
)
# magnetic energy density
if ("amrvac", "b1") in self.field_list:
def _magnetic_energy_density(field, data):
emag = 0.5 * data["gas", "magnetic_1"]**2
for idim in "23":
if not ("amrvac", f"b{idim}") in self.field_list:
break
emag += 0.5 * data["gas", f"magnetic_{idim}"]**2
# in AMRVAC the magnetic field is defined in units where mu0 = 1,
# such that
# Emag = 0.5*B**2 instead of Emag = 0.5*B**2 / mu0
# To correctly transform the dimensionality from gauss**2 -> rho*v**2,
# we have to take mu0 into account. If we divide here, units when adding
# the field should be us["density"]*us["velocity"]**2.
# If not, they should be us["magnetic_field"]**2 and division should
# happen elsewhere.
emag /= 4 * np.pi
# divided by mu0 = 4pi in cgs,
# yt handles 'mks' and 'code' unit systems internally.
return emag
self.add_field(
("gas", "magnetic_energy_density"),
function=_magnetic_energy_density,
units=us["density"] * us["velocity"]**2,
dimensions=dimensions.density * dimensions.velocity**2,
sampling_type="cell",
)
# Adding the thermal pressure field.
# In AMRVAC we have multiple physics possibilities:
# - if HD/MHD + energy equation P = (gamma-1)*(e - ekin (- emag)) for (M)HD
# - if HD/MHD but solve_internal_e is true in parfile, P = (gamma-1)*e for both
# - if (m)hd_energy is false in parfile (isothermal), P = c_adiab * rho**gamma
def _full_thermal_pressure_HD(field, data):
# energy density and pressure are actually expressed in the same unit
pthermal = (data.ds.gamma -
1) * (data["gas", "energy_density"] -
data["gas", "kinetic_energy_density"])
return pthermal
def _full_thermal_pressure_MHD(field, data):
pthermal = (
_full_thermal_pressure_HD(field, data) -
(data.ds.gamma - 1) * data["gas", "magnetic_energy_density"])
return pthermal
def _polytropic_thermal_pressure(field, data):
return (data.ds.gamma - 1) * data["gas", "energy_density"]
def _adiabatic_thermal_pressure(field, data):
return data.ds._c_adiab * data["gas", "density"]**data.ds.gamma
pressure_recipe = None
if ("amrvac", "e") in self.field_list:
if self.ds._e_is_internal:
pressure_recipe = _polytropic_thermal_pressure
mylog.info("Using polytropic EoS for thermal pressure.")
elif ("amrvac", "b1") in self.field_list:
pressure_recipe = _full_thermal_pressure_MHD
mylog.info("Using full MHD energy for thermal pressure.")
else:
pressure_recipe = _full_thermal_pressure_HD
mylog.info("Using full HD energy for thermal pressure.")
elif self.ds._c_adiab is not None:
pressure_recipe = _adiabatic_thermal_pressure
mylog.info(
"Using adiabatic EoS for thermal pressure (isothermal).")
mylog.warning("If you used usr_set_pthermal you should "
"redefine the thermal_pressure field.")
if pressure_recipe is not None:
self.add_field(
("gas", "thermal_pressure"),
function=pressure_recipe,
units=us["density"] * us["velocity"]**2,
dimensions=dimensions.density * dimensions.velocity**2,
sampling_type="cell",
)
# sound speed and temperature depend on thermal pressure
def _sound_speed(field, data):
return np.sqrt(data.ds.gamma *
data["gas", "thermal_pressure"] /
data["gas", "density"])
self.add_field(
("gas", "sound_speed"),
function=_sound_speed,
units=us["velocity"],
dimensions=dimensions.velocity,
sampling_type="cell",
)
else:
mylog.warning(
"e not found and no parfile passed, can not set thermal_pressure."
)
def save(obj, filename='test.hdf5'):
"""Function to save a CAESAR file to disk.
Parameters
----------
obj : :class:`main.CAESAR`
Main caesar object to save.
filename : str, optional
Filename of the output file.
Examples
--------
>>> obj.save('output.hdf5')
"""
from yt.funcs import mylog
if os.path.isfile(filename):
mylog.warning('%s already present, overwriting!' % filename)
os.remove(filename)
mylog.info('Writing %s' % filename)
outfile = h5py.File(filename, 'w')
outfile.attrs.create('caesar', 315)
unit_registry = obj.yt_dataset.unit_registry.to_json()
outfile.attrs.create('unit_registry_json', unit_registry.encode('utf8'))
serialize_global_attribs(obj, outfile)
obj.simulation._serialize(obj, outfile)
if hasattr(obj, 'halos') and obj.nhalos > 0:
hd = outfile.create_group('halo_data')
hdd = hd.create_group('lists')
hddd = hd.create_group('dicts')
# gather
index_lists = ['dmlist']
if 'gas' in obj.data_manager.ptypes: index_lists.append('glist')
if 'star' in obj.data_manager.ptypes:
index_lists.extend(['slist', 'galaxy_index_list'])
if 'dm2' in obj.data_manager.ptypes: index_lists.append('dm2list')
if 'dm3' in obj.data_manager.ptypes: index_lists.append('dm3list')
if obj.data_manager.blackholes:
index_lists.append('bhlist')
if obj.data_manager.dust:
index_lists.append('dlist')
#write
for vals in index_lists:
serialize_list(obj.halos, vals, hdd)
serialize_attributes(obj.halos, hd, hddd)
if hasattr(obj, 'galaxies') and obj.ngalaxies > 0:
hd = outfile.create_group('galaxy_data')
hdd = hd.create_group('lists')
hddd = hd.create_group('dicts')
# gather
index_lists = ['glist', 'slist', 'cloud_index_list']
if obj.data_manager.blackholes:
index_lists.append('bhlist')
if obj.data_manager.dust:
index_lists.append('dlist')
# write
for vals in index_lists:
serialize_list(obj.galaxies, vals, hdd)
serialize_attributes(obj.galaxies, hd, hddd)
if hasattr(obj, 'clouds') and obj.nclouds > 0:
hd = outfile.create_group('cloud_data')
hdd = hd.create_group('lists')
hddd = hd.create_group('dicts')
# gather
index_lists = ['glist']
# write
for vals in index_lists:
serialize_list(obj.clouds, vals, hdd)
serialize_attributes(obj.clouds, hd, hddd)
if hasattr(obj, 'global_particle_lists'):
hd = outfile.create_group('global_lists')
# gather
global_index_lists = [
'halo_dmlist', 'halo_glist', 'halo_slist', 'galaxy_glist',
'galaxy_slist', 'cloud_glist'
]
if obj.data_manager.blackholes:
global_index_lists.extend(['halo_bhlist', 'galaxy_bhlist'])
if obj.data_manager.dust:
global_index_lists.extend(['halo_dlist', 'galaxy_dlist'])
# write
for vals in global_index_lists:
check_and_write_dataset(obj.global_particle_lists, vals, hd)
outfile.close()
def setup_fluid_fields(self):
def _v1(field, data):
return data["gas", "moment_1"] / data["gas", "density"]
def _v2(field, data):
return data["gas", "moment_2"] / data["gas", "density"]
def _v3(field, data):
return data["gas", "moment_3"] / data["gas", "density"]
us = self.ds.unit_system
aliases = direction_aliases[self.ds.geometry]
for idir, alias, func in zip("123", aliases, (_v1, _v2, _v3)):
if not ("amrvac", "m%s" % idir) in self.field_list:
break
self.add_field(("gas", "velocity_%s" % alias),
function=func,
units=us['velocity'],
dimensions=dimensions.velocity,
sampling_type="cell")
self.alias(("gas", "velocity_%s" % idir),
("gas", "velocity_%s" % alias),
units=us["velocity"])
self.alias(("gas", "moment_%s" % alias),
("gas", "moment_%s" % idir),
units=us["density"] * us["velocity"])
setup_magnetic_field_aliases(self, "amrvac",
["mag%s" % ax for ax in "xyz"])
# fields with nested dependencies are defined thereafter by increasing level of complexity
# kinetic pressure is given by 0.5 * rho * v**2
def _kinetic_energy_density(field, data):
# devnote : have a look at issue 1301
return 0.5 * data['gas', 'density'] * data['gas',
'velocity_magnitude']**2
self.add_field(("gas", "kinetic_energy_density"),
function=_kinetic_energy_density,
units=us["density"] * us["velocity"]**2,
dimensions=dimensions.density * dimensions.velocity**2,
sampling_type="cell")
# magnetic energy density
if ('amrvac', 'b1') in self.field_list:
def _magnetic_energy_density(field, data):
emag = 0.5 * data['gas', 'magnetic_1']**2
for idim in '23':
if not ('amrvac', 'b%s' % idim) in self.field_list:
break
emag += 0.5 * data['gas', 'magnetic_%s' % idim]**2
# important note: in AMRVAC the magnetic field is defined in units where mu0 = 1, such that
# Emag = 0.5*B**2 instead of Emag = 0.5*B**2 / mu0
# To correctly transform the dimensionality from gauss**2 -> rho*v**2, we have to take mu0 into account.
# If we divide here, units when adding the field should be us["density"]*us["velocity"]**2
# If not, they should be us["magnetic_field"]**2 and division should happen elsewhere.
emag /= 4 * np.pi
# divided by mu0 = 4pi in cgs, yt handles 'mks' and 'code' unit systems internally.
return emag
self.add_field(
('gas', 'magnetic_energy_density'),
function=_magnetic_energy_density,
units=us["density"] * us["velocity"]**2,
dimensions=dimensions.density * dimensions.velocity**2,
sampling_type='cell')
# Adding the thermal pressure field.
# In AMRVAC we have multiple physics possibilities:
# - if HD/MHD + energy equation, pressure is (gamma-1)*(e - ekin (- emag)) for (M)HD
# - if HD/MHD but solve_internal_e is true in parfile, pressure is (gamma-1)*e for both
# - if (m)hd_energy is false in parfile (isothermal), pressure is c_adiab * rho**gamma
def _full_thermal_pressure_HD(field, data):
# important note : energy density and pressure are actually expressed in the same unit
pthermal = (data.ds.gamma -
1) * (data['gas', 'energy_density'] -
data['gas', 'kinetic_energy_density'])
return pthermal
def _full_thermal_pressure_MHD(field, data):
pthermal = _full_thermal_pressure_HD(field, data) \
- (data.ds.gamma - 1) * data["gas", "magnetic_energy_density"]
return pthermal
def _polytropic_thermal_pressure(field, data):
return (data.ds.gamma - 1) * data['gas', 'energy_density']
def _adiabatic_thermal_pressure(field, data):
return data.ds._c_adiab * data["gas", "density"]**data.ds.gamma
pressure_recipe = None
if ("amrvac", "e") in self.field_list:
if self.ds._e_is_internal:
pressure_recipe = _polytropic_thermal_pressure
mylog.info('Using polytropic EoS for thermal pressure.')
elif ('amrvac', 'b1') in self.field_list:
pressure_recipe = _full_thermal_pressure_MHD
mylog.info('Using full MHD energy for thermal pressure.')
else:
pressure_recipe = _full_thermal_pressure_HD
mylog.info('Using full HD energy for thermal pressure.')
elif self.ds._c_adiab is not None:
pressure_recipe = _adiabatic_thermal_pressure
mylog.info(
'Using adiabatic EoS for thermal pressure (isothermal).')
mylog.warning(
'If you used usr_set_pthermal you should redefine the thermal_pressure field.'
)
if pressure_recipe is not None:
self.add_field(
('gas', 'thermal_pressure'),
function=pressure_recipe,
units=us['density'] * us['velocity']**2,
dimensions=dimensions.density * dimensions.velocity**2,
sampling_type='cell')
# sound speed and temperature depend on thermal pressure
def _sound_speed(field, data):
return np.sqrt(data.ds.gamma *
data["gas", "thermal_pressure"] /
data["gas", "density"])
self.add_field(("gas", "sound_speed"),
function=_sound_speed,
units=us["velocity"],
dimensions=dimensions.velocity,
sampling_type="cell")
else:
mylog.warning(
"e not found and no parfile passed, can not set thermal_pressure."
)