def test_loop_apertures(i):
# Create a cluster object
cluster = Cluster(simulation_name='ceagle', clusterID=i, redshift='z000p000')
apertures = cluster.generate_apertures()
for aperture in apertures:
# Create a PhaseDiagram object and link it to the cluster object
t_rho_diagram = PhaseDiagram(cluster, aperture=aperture)
t_rho_diagram.info()
# Test the map output
t_rho_diagram.setup_plot()
def make_simstats(self,
save2hdf5: bool = True) -> Union[pd.DataFrame, None]:
if not self.is_metadata():
print('[+] Metadata file not found.')
self.make_metadata()
df = pd.DataFrame(columns=self.cols)
iterator = itertools.product(self.simulation.clusterIDAllowed,
self.simulation.redshiftAllowed)
print(
f"{'':<30s} {' process ID ':^25s} | {' halo ID ':^15s} | {' halo redshift ':^20s}\n"
)
for process_n, (halo_id, halo_z) in enumerate(list(iterator)):
if self.simulation.sample_completeness[
halo_id,
self.simulation.redshiftAllowed.index(halo_z)]:
print(
f"{'Processing...':<30s} {process_n:^25d} | {halo_id:^15d} | {halo_z:^20s}"
)
cluster = Cluster(
simulation_name=self.simulation.simulation_name,
clusterID=halo_id,
redshift=halo_z)
read = pull.FOFRead(cluster)
df = df.append(
{
'cluster_id':
cluster.clusterID,
'redshift_float':
cluster.z,
'R_2500_crit':
cluster.r2500,
'R_500_crit':
cluster.r500,
'R_200_crit':
cluster.r200,
'R_aperture':
cluster.generate_apertures()[self.aperture_id],
'M_2500_crit':
cluster.mass_units(cluster.M2500, unit_system='astro'),
'M_500_crit':
cluster.mass_units(cluster.M500, unit_system='astro'),
'M_200_crit':
cluster.mass_units(cluster.M200, unit_system='astro'),
'M_aperture_T':
cluster.mass_units(read.pull_mass_aperture(
'Total_mass')[self.aperture_id],
unit_system='astro'),
'M_aperture_0':
cluster.mass_units(read.pull_mass_aperture(
'ParType0_mass')[self.aperture_id],
unit_system='astro'),
'M_aperture_1':
cluster.mass_units(read.pull_mass_aperture(
'ParType1_mass')[self.aperture_id],
unit_system='astro'),
'M_aperture_4':
cluster.mass_units(read.pull_mass_aperture(
'ParType4_mass')[self.aperture_id],
unit_system='astro'),
'rotTvelT':
read.pull_rot_vel_angle_between(
'Total_angmom', 'Total_ZMF')[self.aperture_id],
'rot0rot4':
read.pull_rot_vel_angle_between(
'ParType0_angmom',
'ParType4_angmom')[self.aperture_id],
'rot1rot4':
read.pull_rot_vel_angle_between(
'ParType1_angmom',
'ParType4_angmom')[self.aperture_id],
'vel0vel1':
read.pull_rot_vel_angle_between(
'ParType0_ZMF', 'ParType1_ZMF')[self.aperture_id],
'peculiar_velocity_T_magnitude':
read.pull_peculiar_velocity_magnitude('Total_ZMF')[
self.aperture_id],
'peculiar_velocity_0_magnitude':
read.pull_peculiar_velocity_magnitude('ParType0_ZMF')[
self.aperture_id],
'peculiar_velocity_1_magnitude':
read.pull_peculiar_velocity_magnitude('ParType1_ZMF')[
self.aperture_id],
'peculiar_velocity_4_magnitude':
read.pull_peculiar_velocity_magnitude('ParType4_ZMF')[
self.aperture_id],
'angular_momentum_T_magnitude':
cluster.momentum_units(
read.pull_angular_momentum_magnitude(
'Total_angmom')[self.aperture_id],
unit_system='astro'),
'angular_momentum_0_magnitude':
cluster.momentum_units(
read.pull_angular_momentum_magnitude(
'ParType0_angmom')[self.aperture_id],
unit_system='astro'),
'angular_momentum_1_magnitude':
cluster.momentum_units(
read.pull_angular_momentum_magnitude(
'ParType1_angmom')[self.aperture_id],
unit_system='astro'),
'angular_momentum_4_magnitude':
cluster.momentum_units(
read.pull_angular_momentum_magnitude(
'ParType4_angmom')[self.aperture_id],
unit_system='astro'),
'kinetic_energy_T':
cluster.energy_units(read.pull_kinetic_energy(
'Total_kin_energy')[self.aperture_id],
unit_system='SI'),
'kinetic_energy_0':
cluster.energy_units(read.pull_kinetic_energy(
'ParType0_kin_energy')[self.aperture_id],
unit_system='SI'),
'kinetic_energy_1':
cluster.energy_units(read.pull_kinetic_energy(
'ParType1_kin_energy')[self.aperture_id],
unit_system='SI'),
'thermal_energy':
cluster.energy_units(read.pull_thermal_energy(
'Total_th_energy')[self.aperture_id],
unit_system='SI'),
'substructure_mass_T':
cluster.mass_units(read.pull_substructure_mass(
'Total_substructure_mass')[self.aperture_id],
unit_system='astro'),
'dynamical_merging_index_T':
read.pull_dynamical_merging_index(
'Total_dyn_mergindex')[self.aperture_id],
'thermodynamic_merging_index_T':
read.pull_thermodynamic_merging_index(
'Total_therm_mergindex')[self.aperture_id],
'substructure_fraction_T':
read.pull_substructure_merging_index(
'Total_substructure_fraction')[self.aperture_id]
},
ignore_index=True)
else:
print(
f"{'Skip - sample_completeness':<30s} {process_n:^25d} | {halo_id:^15d} | {halo_z:^20s}"
)
print(df.info())
if save2hdf5:
self.h5store(os.path.join(self.path, self.filename),
df,
key=f'aperture{self.aperture_id}')
if os.path.isfile(os.path.join(self.path, self.filename)):
print(
f"[+] Saved\n[+]\tPath: {self.path}\n[+]\tFile: {self.filename}"
)
else:
return df
