mirror of
https://github.com/Richard-Sti/csiborgtools_public.git
synced 2025-07-02 20:41:11 +00:00
fdb0df8d4c
* Move paths to a separate file * Add mmain reader * Add a verbosity flag * Fix imports * Fix bug * Rename files * Return ultimate parents * Add script to generate mmain * Remove mmain path * edit path * Add mmain path * Change function name * Rename function * Turn off verbose * Fix list requirement * Edit init match paths * Fix init pathing * Edit paths docs * Edit dumpdir name * Rename path * Fix split paths * Remove unused import * Add comment * Update readme * remove read mmain * Rename haloatalogue * Fix minor bugs * Update nbs * Add create directory option * Move split jobs * Move spliot jobs * Remove splitting * Add import * Edit script * Deeper split folder * Fix paths bug * Rename catalogue * Rename Catalogue * Add new clumpread * Edit paths * add knn paths * Update commenting * Update imports * Add more conversions * Update temp file * Add a note * Add catalogue * Cooment * Update TODO * Update script * add nb * Update * pep8 * edit paths & pep8 * Fix knn auto paths * add paths docs * Add auto and cross knn paths * Add new paths * Simplify tpcf reading * pep8 patch * update readme * Update progress * pep8 * pep8 * pep8 * pep8 * pep8 * pep8 * pep8 * pep8 * pep8 * pep8 * pep8 * pep8 * pep8 * pep8 * pep8 * Pep 8 and restructure * add lambda spin * add clump and halo * add checks * Edit halo profile fit * Update gitignore * backup script
6 KiB
6 KiB
In [1]:
import matplotlib.pyplot as plt
import numpy
import scienceplots
from h5py import File
import plt_utils
%load_ext autoreload
%autoreload 2
In [12]:
with File("/mnt/extraspace/rstiskalek/csiborg_postprocessing/ACL/BORG2_0.25.hdf5", 'r') as f:
voxel_acl = f['voxel_acl'][...].flatten()
voxel_dist = f['voxel_dist'][...].flatten()
In [28]:
bins = numpy.linspace(0, 100, 10)
plt.figure()
mask = voxel_dist < 20
plt.hist(voxel_acl[mask], bins="auto", histtype='step', density=1, label=r"$0 < R / (\mathrm{Mpc} / h) < 20$")
mask = (voxel_dist > 20) & (voxel_dist < 40)
plt.hist(voxel_acl[mask], bins="auto", histtype='step', density=1, label=r"$20 < R / (\mathrm{Mpc} / h) < 40$")
mask = (voxel_dist > 40) & (voxel_dist < 60)
plt.hist(voxel_acl[mask], bins="auto", histtype='step', density=1, label=r"$40 < R / (\mathrm{Mpc} / h) < 60$")
# plt.scatter(voxel_dist.flatten(), voxel_acl.flatten(), s=0.1)
plt.legend()
plt.title("ACL of individual voxels")
plt.xlabel(r"$\mathrm{ACL}$")
plt.ylabel(r"Normalized bin counts")
plt.tight_layout()
plt.savefig("../plots/BORG_Stephen_ACL.png", dpi=450)
plt.show()
In [ ]: