mirror of
https://github.com/Richard-Sti/csiborgtools.git
synced 2024-12-23 04:58:03 +00:00
66 lines
2.1 KiB
Python
66 lines
2.1 KiB
Python
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# Copyright (C) 2024 Richard Stiskalek
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# This program is free software; you can redistribute it and/or modify it
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# under the terms of the GNU General Public License as published by the
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# Free Software Foundation; either version 3 of the License, or (at your
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# option) any later version.
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#
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# This program is distributed in the hope that it will be useful, but
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# WITHOUT ANY WARRANTY; without even the implied warranty of
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# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General
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# Public License for more details.
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#
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# You should have received a copy of the GNU General Public License along
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# with this program; if not, write to the Free Software Foundation, Inc.,
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# 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301, USA.
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"""Script to help with plots in `flow_calibration.ipynb`."""
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from os.path import exists, join
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import csiborgtools
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import numpy as np
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from astropy import units as u
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from astropy.cosmology import FlatLambdaCDM
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FDIR = "/mnt/extraspace/rstiskalek/csiborg_postprocessing/field_shells"
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def read_enclosed_density(simname):
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fname = join(FDIR, f"enclosed_mass_{simname}.npz")
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if exists(fname):
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data = np.load(fname)
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else:
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raise FileNotFoundError(f"File `{fname}` not found.")
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Om0 = csiborgtools.simname2Omega_m(simname)
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cosmo = FlatLambdaCDM(H0=100, Om0=Om0)
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rho_matter = Om0 * cosmo.critical_density(0).to(u.M_sun / u.Mpc**3).value
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r = data["distances"]
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volume = 4 * np.pi / 3 * r**3
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overdensity = data["enclosed_mass"] / volume / rho_matter - 1
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return r, overdensity
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def read_enclosed_flow(simname):
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fname = join(FDIR, f"enclosed_mass_{simname}.npz")
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if exists(fname):
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data = np.load(fname)
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else:
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raise FileNotFoundError(f"File {fname} not found.")
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r = data["distances"]
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V = data["cumulative_velocity"]
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nsim, nbin = V.shape[:2]
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Vmag = np.linalg.norm(V, axis=-1)
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l = np.empty((nsim, nbin), dtype=V.dtype) # noqa
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b = np.empty_like(l)
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for n in range(nsim):
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V_n = csiborgtools.cartesian_to_radec(V[n])
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l[n], b[n] = csiborgtools.flow.radec_to_galactic(V_n[:, 1], V_n[:, 2])
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return r, Vmag, l, b
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