csiborgtools/notebooks/flow/process_upglade.ipynb
Richard Stiskalek 779f2e76ac
Calculate upglade redshifts (#128)
* Update redshift reading

* Add helio to CMB redshift

* Update imports

* Update nb

* Run for Quijote

* Add script

* Update

* Update .gitignore

* Update imports

* Add Peery estimator

* Add bulk flow scripts

* Update typs

* Add comment

* Add blank space

* Update submission script

* Update description

* Add barriers

* Update nb

* Update nb

* Rename script

* Move to old

* Update imports

* Add nb

* Update script

* Fix catalogue key

* Update script

* Update submit

* Update comment

* Update .gitignore

* Update nb

* Update for stationary obsrevers

* Update submission

* Add nb

* Add better verbose control

* Update nb

* Update submit

* Update nb

* Add SN errors

* Add draft of the script

* Update verbosity flags

* Add submission script

* Debug script

* Quickfix

* Remove comment

* Update nb

* Update submission

* Update nb

* Processed UPGLADE
2024-06-20 14:33:00 +01:00

1.1 MiB

In [1]:
import numpy as np
%matplotlib notebook
import matplotlib.pyplot as plt
# Local imports
try:
    import csiborgtools
except ModuleNotFoundError:
    import sys
    sys.path.append("../")
    import csiborgtools
import utils

%load_ext autoreload
%autoreload 2
In [28]:
Nsim = 9844
Nsnap = 1016


sim = utils.load_processed(Nsim, Nsnap)
sim = sim[sim["dist"] < 200]

gals = utils.load_2mpp()
gals = gals[gals["CDIST_CMB"] < 200]
planck = utils.load_planck2015()
In [101]:
dx = 40
dmin = 100
dmax = dmin + dx

mask_obs = (dmin < gals["CDIST_CMB"]) & (gals["CDIST_CMB"] < dmax)
mask_sim = (dmin < sim["dist"]) & (sim["dist"] < dmax) & (sim["m200"] > 1e12)
mask_planck = (dmin < planck["COMDIST"]) & (planck["COMDIST"] < dmax)

print(mask_planck.sum())

plt.figure()
plt.scatter(sim["ra"][mask_sim], sim["dec"][mask_sim], s=1, label="CSiBORG")
plt.scatter(gals["RA"][mask_obs], gals["DEC"][mask_obs], s=1, label="2M++")
plt.scatter(planck["RA"][mask_planck], planck["DEC"][mask_planck], s=50, label="Planck", c="m")
plt.legend()
plt.title(r"$M_{{200c}} > 10^{{12}} M_\odot$ and ${}~\mathrm{{Mpc}} < D_{{c}} < {}~\mathrm{{Mpc}}$"
          .format(dmin, dmax))
plt.xlabel(r"$\mathrm{RA}$")
plt.ylabel(r"$\delta$")
plt.savefig("../plots/sky_comparison.png", dpi=400)
plt.show()
9
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In [75]:
planck = utils.load_planck2015(1500)

plt.figure()
plt.scatter(planck["COMDIST"], planck["MSZ"], s=3)

plt.axvline(200, c="red", zorder=0)

plt.title("Planck clusters")
plt.xlabel(r"$D_{c}~[\mathrm{Mpc}]$")
plt.ylabel(r"$M_{500c}$")
plt.yscale("log")
plt.tight_layout()
plt.savefig("../plots/planck_mass_dist.png", dpi=450)
plt.show()
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In [77]:
planck = utils.load_planck2015(200)
In [103]:
mask_sim = sim["m500"] > 1e14
mask_planck = planck["MSZ"] > 1e14

plt.figure()
plt.scatter(planck["RA"], planck["DEC"], label="Planck", c=np.log10(planck["MSZ"]))
plt.colorbar()
plt.scatter(sim["ra"][mask_sim], sim["dec"][mask_sim], label="CSiBORG", c="red", s=3, zorder=1)

plt.legend(loc=2)

plt.title(r"Sky comparison of CSiBORG and Planck of $M_{500c} > 10^{14} M_\odot$")
plt.xlabel(r"$\mathrm{RA}$")
plt.ylabel(r"$\delta$")
plt.tight_layout()
plt.savefig("../plots/clusters_positions.png", dpi=450)

plt.show()
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In [ ]: