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https://github.com/Richard-Sti/csiborgtools.git
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53a0629d90
* add recarray manipulations * add cart to radec * add behav so x can be a list * add import * create empty files * ignore plots file * add planck data * add read_mmain file * add cols_to_structured import * use cols_to_structured * add cols_to_structued * add read_mmain import * add reading planck * add mass conversion * add brute force separation calculation * update nb * rename & int dtype * add func to get csiborg ids * add list to nd array conversion * add utils * rename file * add 2M++ * add read 2mpp * add 2mpp shortcut * add randoms generator * Change range of RA [0, 360] * fix ang wrapping * add code for sphere 2pcf * rm wrapping * optionally load only a few borgs * update nb
1.3 MiB
1.3 MiB
In [1]:
import numpy as np
%matplotlib notebook
import matplotlib.pyplot as plt
try:
import csiborgtools
except ModuleNotFoundError:
import sys
sys.path.append("../")
import csiborgtools
import utils
%load_ext autoreload
%autoreload 2
import joblib
from os.path import join
from glob import glob
In [2]:
Nsim = 9844
simpath = csiborgtools.io.get_sim_path(Nsim)
Nsnap = 1016
outfname = join(utils.dumpdir, "ramses_out_{}_{}.npy".format(str(Nsim).zfill(5), str(Nsnap).zfill(5)))
mmain = csiborgtools.io.read_mmain(Nsim, "/mnt/zfsusers/hdesmond/Mmain")
data = np.load(outfname)
data = csiborgtools.io.merge_mmain_to_clumps(data, mmain)
data = data[(data["npart"] > 100) & np.isfinite(data["m200"])]
CSiBORGBox = csiborgtools.units.CSiBORGBox(Nsnap, simpath)
In [22]:
R = np.sqrt((data["peak_x"] - 0.5)**2 + (data["peak_y"] - 0.5)**2 + (data["peak_z"] - 0.5)**2)
In [29]:
CSiBORGBox.box2kpc(0.21) * 1e-3
Out[29]:
In [30]:
plt.figure()
plt.hist(R, bins="auto")
plt.axvline(0.22, c="red")
plt.show()
In [34]:
mass = CSiBORGBox.box2solarmass(data["m200"])
Out[34]:
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In [3]:
# Nsplit = 0
# loaddir = join(utils.dumpdir, "temp")
# parts, part_clumps, clumps = csiborgtools.fits.load_split_particles(
# Nsplit, loaddir, Nsim, Nsnap, remove_split=False)
In [43]:
# n = 584
# xs = csiborgtools.fits.pick_single_clump(n, parts, part_clumps, clumps)
# halo = csiborgtools.fits.Clump.from_arrays(*xs, rhoc=CSiBORGBox.box_rhoc)
# print(halo.Npart)
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