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https://github.com/Richard-Sti/csiborgtools.git
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5dd8c668fa
* 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
1.1 MiB
1.1 MiB
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 [ ]: