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https://github.com/Richard-Sti/csiborgtools_public.git
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2b938c112c
* Add more comments * Add flow paths * Simplify paths * Update default arguemnts * Update paths * Update param names * Update some of scipts for reading files * Add the Mike method option * Update plotting * Update fnames * Simplify things * Make more default options * Add print * Update * Downsample CF4 * Update numpyro selection * Add selection fitting nb * Add coeffs * Update script * Add nb * Add label * Increase number of steps * Update default params * Add more labels * Improve file name * Update nb * Fix little bug * Remove import * Update scales * Update labels * Add script * Update script * Add more * Add more labels * Add script * Add submit * Update spacing * Update submit scrips * Update script * Update defaults * Update defaults * Update nb * Update test * Update imports * Add script * Add support for Indranil void * Add a dipole * Update nb * Update submit * Update Om0 * Add final * Update default params * Fix bug * Add option to fix to LG frame * Add Vext label * Add Vext label * Update script * Rm fixed LG * rm LG stuff * Update script * Update bulk flow plotting * Update nb * Add no field option * Update defaults * Update nb * Update script * Update nb * Update nb * Add names to plots * Update nb * Update plot * Add more latex names * Update default * Update nb * Update np * Add plane slicing * Add nb with slices * Update nb * Update script * Upddate nb * Update nb
14 KiB
14 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 [ ]: