Cosmological Analysis

These scripts demonstrate some basic and more advanced analysis that can be performed on cosmological simulation datasets.

Plotting Halos

This is a mechanism for plotting circles representing identified particle halos on an image. See Halo Analysis and Overplotting Halo Annotations for more information.

import yt
from yt.extensions.astro_analysis.halo_analysis.halo_catalog import HaloCatalog

# Load the dataset
ds = yt.load("Enzo_64/RD0006/RedshiftOutput0006")

# Load the halo list from a rockstar output for this dataset
halos = yt.load("rockstar_halos/halos_0.0.bin")

# Create the halo catalog from this halo list
hc = HaloCatalog(halos_ds=halos)

# Create a projection with the halos overplot on top
p = yt.ProjectionPlot(ds, "x", "density")

Light Cone Projection

This script creates a light cone projection, a synthetic observation that stacks together projections from multiple datasets to extend over a given redshift interval. See Light Cone Generator for more information.

import glob
import shutil

from yt.extensions.astro_analysis.cosmological_observation.api import LightCone

# Create a LightCone object extending from z = 0 to z = 0.1.

# We have already set up the redshift dumps to be
# used for this, so we will not use any of the time
# data dumps.
lc = LightCone(

# Calculate a randomization of the solution.
lc.calculate_light_cone_solution(seed=123456789, filename="LC/solution.txt")

# Choose the field to be projected.
field = "szy"

# Use the LightCone object to make a projection with a 600 arcminute
# field of view and a resolution of 60 arcseconds.
# Set njobs to -1 to have one core work on each projection
# in parallel.
    (600.0, "arcmin"),
    (60.0, "arcsec"),

# By default, the light cone projections are kept in the LC directory,
# but this moves them back to the current directory so that they're rendered
# in our cookbook.

for file in glob.glob("LC/*png"):
    shutil.move(file, ".")