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Add galaxy sampling (#88)

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* Improve calculations

* Improve flags

* Add smoothed options

* Remove some old comments

* Edit little things

* Save smoothed

* Move files

* Edit imports

* Edit imports

* Renaming imports

* Renaming imports

* Sort imports

* Sort files

* Sorting

* Optionally make copies of the field

* Add quijote backup check

* Add direct field smoothing

* Shorten stupid documentation

* Shorten stupid docs

* Update conversion

* Add particles to ASCII conversion

* Add a short comment

* Add SDSS uncorrected distance

* Adjust comment

* Add FITS index to galaxies

* Remove spare space

* Remove a stupid line

* Remove blank line

* Make space separated

* Add interpolated field path

* Add field sampling

* Sort imports

* Return density in cells

* Clear out observer velocity

* Add 170817 sampling

* Fix normalization

* Update plot
This commit is contained in:
Richard Stiskalek 2023-09-01 16:29:50 +01:00 • committed by GitHub
parent 0af925e26a
commit eccd8e3507
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GPG key ID: 4AEE18F83AFDEB23
26 changed files with 610 additions and 365 deletions
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16
scripts_plots/plot_1nn.py
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@ -62,7 +62,7 @@ def open_cats(nsims, simname):
def read_dist(simname, run, kind, kwargs):
paths = csiborgtools.read.Paths(**kwargs["paths_kind"])
reader = csiborgtools.read.NearestNeighbourReader(**kwargs, paths=paths)
reader = csiborgtools.summary.NearestNeighbourReader(**kwargs, paths=paths)
fpath = paths.cross_nearest(simname, run, "tot_counts", nsim=0, nobs=0)
counts = numpy.load(fpath)["tot_counts"]
@ -102,7 +102,7 @@ def plot_dist(run, kind, kwargs, runs_to_mass, pulled_cdf=False, r200=None):
"""
assert kind in ["pdf", "cdf"]
print(f"Plotting the {kind} for {run}...", flush=True)
reader = csiborgtools.read.NearestNeighbourReader(
reader = csiborgtools.summary.NearestNeighbourReader(
**kwargs, paths=csiborgtools.read.Paths(**kwargs["paths_kind"]))
raddist = reader.bin_centres("radial")
r = reader.bin_centres("neighbour")
@ -241,7 +241,7 @@ def plot_cdf_diff(runs, kwargs, pulled_cdf, runs_to_mass):
"""
print("Plotting the CDF difference...", flush=True)
paths = csiborgtools.read.Paths(**kwargs["paths_kind"])
reader = csiborgtools.read.NearestNeighbourReader(**kwargs, paths=paths)
reader = csiborgtools.summary.NearestNeighbourReader(**kwargs, paths=paths)
r = reader.bin_centres("neighbour")
runs_to_mass = [numpy.mean(runs_to_mass[run]) for run in runs]
@ -320,7 +320,7 @@ def make_kl(simname, run, nsim, nobs, kwargs):
of each halo in the reference simulation.
"""
paths = csiborgtools.read.Paths(**kwargs["paths_kind"])
reader = csiborgtools.read.NearestNeighbourReader(**kwargs, paths=paths)
reader = csiborgtools.summary.NearestNeighbourReader(**kwargs, paths=paths)
# This is the reference PDF. Must be Quijote!
pdf = read_dist("quijote", run, "pdf", kwargs)
return reader.kl_divergence(simname, run, nsim, pdf, nobs=nobs)
@ -352,7 +352,7 @@ def make_ks(simname, run, nsim, nobs, kwargs):
each halo in the reference simulation.
"""
paths = csiborgtools.read.Paths(**kwargs["paths_kind"])
reader = csiborgtools.read.NearestNeighbourReader(**kwargs, paths=paths)
reader = csiborgtools.summary.NearestNeighbourReader(**kwargs, paths=paths)
# This is the reference CDF. Must be Quijote!
cdf = read_dist("quijote", run, "cdf", kwargs)
return reader.ks_significance(simname, run, nsim, cdf, nobs=nobs)
@ -551,7 +551,7 @@ def plot_significance_vs_mass(simname, runs, nsim, nobs, kind, kwargs,
print(f"Plotting {kind} significance vs mass.")
assert kind in ["kl", "ks"]
paths = csiborgtools.read.Paths(**kwargs["paths_kind"])
reader = csiborgtools.read.NearestNeighbourReader(**kwargs, paths=paths)
reader = csiborgtools.summary.NearestNeighbourReader(**kwargs, paths=paths)
with plt.style.context(plt_utils.mplstyle):
plt.figure()
@ -627,7 +627,7 @@ def plot_kl_vs_ks(simname, runs, nsim, nobs, kwargs, runs_to_mass,
None
"""
paths = csiborgtools.read.Paths(**kwargs["paths_kind"])
reader = csiborgtools.read.NearestNeighbourReader(**kwargs, paths=paths)
reader = csiborgtools.summary.NearestNeighbourReader(**kwargs, paths=paths)
xs, ys, cs = [], [], []
for run in runs:
@ -697,7 +697,7 @@ def plot_kl_vs_overlap(runs, nsim, kwargs, runs_to_mass, plot_std=True,
None
"""
paths = csiborgtools.read.Paths(**kwargs["paths_kind"])
nn_reader = csiborgtools.read.NearestNeighbourReader(**kwargs, paths=paths)
nn_reader = csiborgtools.summary.NearestNeighbourReader(**kwargs, paths=paths)
xs, ys1, ys2, cs = [], [], [], []
for run in runs: