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779f2e76ac
* 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
41 KiB
41 KiB
In [2]:
import sys
import numpy as np
import matplotlib.pyplot as plt
import scienceplots
import astroquery
from tqdm import trange, tqdm
sys.path.append("../")
import csiborgtools
%matplotlib widget
%load_ext autoreload
%autoreload 2
In [38]:
# # Norma
cluster = {"RA": (16 + 15 / 60 + 32.8 / 60**2) * 15,
"DEC": -60 + 54 / 60 + 30 / 60**2,
"DIST": 67.8}
Xclust = np.array([cluster["DIST"], cluster["RA"], cluster["DEC"]]).reshape(1, -1)
In [39]:
paths = csiborgtools.read.Paths(**csiborgtools.paths_glamdring)
nsims = paths.get_ics(False)
In [29]:
Xclust = np.array([cluster["DIST"], cluster["RA"], cluster["DEC"]]).reshape(1, -1)
In [33]:
matches = np.full(len(nsims), np.nan)
for ii in trange(101):
cat = csiborgtools.read.HaloCatalogue(nsims[ii], paths, minmass=('M', 1e13))
dist, ind = cat.angular_neighbours(Xclust, ang_radius=5, rad_tolerance=10)
dist = dist[0]
ind = ind[0]
if ind.size > 0:
matches[ii] = np.max(cat['M'][ind])
In [37]:
x = np.log10(matches[~np.isnan(matches)])
plt.figure()
plt.hist(x, bins=10)
plt.show()
In [ ]: