def load_halos(ds,location):
#Merely loads an already saved halocatalog
#Calls a fn to gather positions and radii of halos over a mass threshold
halo_ds = yt.load(location)
hc = HaloCatalog(data_ds=ds,halos_ds=halo_ds)
hc.add_filter('quantity_value','particle_mass','>',1E12,'Msun')
halo_ds = hc.halos_ds.all_data()
radii, positions = get_halo_pos(ds,halo_ds)
return hc, radii, positions
def generate_halos(ds,dsname):
#function to find the halos for the given dataset, using the HOP finder
#Calls a fn to gather positions and radii of halos over a mass threshold
#Autosaves the HC
hc = HaloCatalog(data_ds=ds,finder_method='hop',finder_kwargs={'threshold':300,'padding':0.04},output_dir="".join(['~/',dsname]))
hc.add_filter('quantity_value','particle_mass','>',1E12,'Msun')
hc.create()
hc = hc.halos_ds.all_data()
radii, positions = get_halo_pos(ds,hc)
return hc, radii, positions
import yt
from yt.analysis_modules.halo_analysis.api import HaloCatalog
# Load the data set with the full simulation information
# and rockstar halos
data_ds = yt.load('Enzo_64/RD0006/RedshiftOutput0006')
halos_ds = yt.load('rockstar_halos/halos_0.0.bin')
# Instantiate a catalog using those two paramter files
hc = HaloCatalog(data_ds=data_ds, halos_ds=halos_ds)
# Filter out less massive halos
hc.add_filter("quantity_value", "particle_mass", ">", 1e14, "Msun")
# attach a sphere object to each halo whose radius extends
# to twice the radius of the halo
hc.add_callback("sphere", factor=2.0)
# use the sphere to calculate radial profiles of gas density
# weighted by cell volume in terms of the virial radius
hc.add_callback("profile",
x_field="radius",
y_fields=[("gas", "overdensity")],
weight_field="cell_volume",
accumulation=False,
storage="virial_quantities_profiles")
hc.add_callback("virial_quantities", ["radius"],
profile_storage="virial_quantities_profiles")
hc.add_callback('delete_attribute', 'virial_quantities_profiles')
x = halo.quantities['particle_position_x']
y = halo.quantities['particle_position_y']
z = halo.quantities['particle_position_z']
return (lower_bound < x < upper_bound) and (lower_bound < y < upper_bound) and (lower_bound < z < upper_bound)
def filter_particles(halo):
"""
Checks to see if there are more than a certain number of particles within a sphere.
"""
minimum_particles = 50000
x = halo.quantities['particle_position_x']
y = halo.quantities['particle_position_y']
z = halo.quantities['particle_position_z']
sphere = halo.halo_catalog.data_ds.sphere([x, y, z], (30, 'kpc'))
n_particles = len(sphere['x'])
return n_particles > minimum_particles
# Add to the filter registry.
add_filter('position', filter_position)
add_filter('particles', filter_particles)
# Run the analysis.
hc.add_filter('quantity_value', 'particle_mass', '<', 1e13, 'Msun')
hc.add_callback('iterative_center_of_mass')
hc.add_filter('position')
hc.add_filter('particles')
hc.create()
import yt
from yt.analysis_modules.halo_analysis.api import HaloCatalog
# Load the data set with the full simulation information
# and rockstar halos
data_ds = yt.load('Enzo_64/RD0006/RedshiftOutput0006')
halos_ds = yt.load('rockstar_halos/halos_0.0.bin')
# Instantiate a catalog using those two paramter files
hc = HaloCatalog(data_ds=data_ds, halos_ds=halos_ds)
# Filter out less massive halos
hc.add_filter("quantity_value", "particle_mass", ">", 1e14, "Msun")
# attach a sphere object to each halo whose radius extends
# to twice the radius of the halo
hc.add_callback("sphere", factor=2.0)
# use the sphere to calculate radial profiles of gas density
# weighted by cell volume in terms of the virial radius
hc.add_callback("profile", ["radius"],
[("gas", "overdensity")],
weight_field="cell_volume",
accumulation=True,
storage="virial_quantities_profiles")
hc.add_callback("virial_quantities", ["radius"],
profile_storage="virial_quantities_profiles")
hc.add_callback('delete_attribute', 'virial_quantities_profiles')
