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https://github.com/Richard-Sti/csiborgtools.git
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* Simplify smoothing support and looping over nonzero * Simplify comments * add now() * add cat length * add smoothed calculation * add smoothing * Add sorting * Edit what is ignored * Move notebooks * Add nonsymmetric smoothed overlap * Update NB * Add support for reading in the smoothed overlap * Switch to the true overlap definition * Reader of the true overlap * rem occups * Import moved to a class * Move definition * Edit submission script * Update to account for the new definition * backup nb * Switch back to properly initialising arrays * Fix addition bug * Update NB * Fix little bug * Update nb
1,001 KiB
1,001 KiB
In [1]:
from os.path import join
import csiborgtools
import healpy
import matplotlib.pyplot as plt
import numpy
import scienceplots
from cache_to_disk import cache_to_disk, delete_disk_caches_for_function
from h5py import File
import plt_utils
%load_ext autoreload
%autoreload 2
In [8]:
@cache_to_disk(30)
def _plot_sky_projected_density(nsim, simname, grid, nside, MAS, survey_name,
dmin, dmax):
paths = csiborgtools.read.Paths(**csiborgtools.paths_glamdring)
boxsize = csiborgtools.simname2boxsize(simname)
if simname == "csiborg1":
reader = csiborgtools.read.CSiBORG1Field(nsim, paths)
elif "csiborg2" in simname:
kind = simname.split("_")[-1]
reader = csiborgtools.read.CSiBORG2Field(nsim, kind, paths)
else:
raise ValueError(f"Unknown simname `{simname}`.")
field = reader.density_field(MAS, grid)
if survey_name == "2M++":
survey = csiborgtools.read.TwoMPPGalaxies()
dist = survey["ZCMB"] * 3e5 / 100
ra, dec = survey["RA"], survey["DEC"]
ra *= numpy.pi / 180
dec *= numpy.pi / 180
elif survey_name == "SDSS":
survey = csiborgtools.SDSS()()
dist = survey["DIST"]
ra, dec = survey["RA"], survey["DEC"]
ra *= numpy.pi / 180
dec *= numpy.pi / 180
elif survey_name == "csiborg2":
cat = csiborgtools.read.CSiBORG2Catalogue(
nsim, 99, "main", paths, bounds={"totmass": (1e12, None)})
coord = cat["spherical_pos"]
dist, ra, dec = coord[:, 0], coord[:, 1], coord[:, 2]
ra *= numpy.pi / 180
dec *= numpy.pi / 180
else:
raise ValueError(f"Unknown survey name `{survey_name}`.")
mask = (dist > dmin) & (dist < dmax)
ra = ra[mask]
dec = dec[mask]
angpos = csiborgtools.field.nside2radec(nside)
dist = numpy.linspace(dmin, dmax, 1000)
dmap = csiborgtools.field.make_sky(field, angpos=angpos, dist=dist,
boxsize=boxsize)
return dmap, ra, dec
In [9]:
def plot_sky_projected_density(nsim, simname, grid, nside, MAS="PCS",
dmin=0, dmax=220, survey_name="2M++",
ext="png", to_save=False):
dmap, ra, dec = _plot_sky_projected_density(
nsim, simname, grid, nside, MAS, survey_name, dmin, dmax)
with plt.style.context(plt_utils.mplstyle):
healpy.mollview(numpy.log10(dmap), fig=0, title="", unit="", rot=90)
healpy.projscatter(numpy.pi / 2 - dec, ra, s=0.05, c="red",
label="2M++ galaxies")
if to_save:
fout = join(plt_utils.fout, f"sky_density_{simname}_{nsim}_from_{dmin}_to_{dmax}.{ext}") # noqa
print(f"Saving to `{fout}`.")
plt.savefig(fout, dpi=plt_utils.dpi, bbox_inches="tight")
plt.show()
In [3]:
In [10]:
# delete_disk_caches_for_function("_plot_sky_projected_density")
plot_sky_projected_density(15517, "csiborg2_main", 1024, 128, "SPH", dmin=100,
dmax=125, survey_name="csiborg2", to_save=True)
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