mirror of
https://github.com/Richard-Sti/csiborgtools.git
synced 2024-12-22 07:18:03 +00:00
66 lines
2.4 KiB
Python
66 lines
2.4 KiB
Python
# 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 `hmf.py`."""
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import csiborgtools
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import numpy as np
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from tqdm import tqdm
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from h5py import File
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def calculate_hmf(simname, bin_edges, halofinder="FOF", max_distance=135):
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"""
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Calculate the halo mass function for a given simulation from catalogues.
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"""
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paths = csiborgtools.read.Paths(**csiborgtools.paths_glamdring)
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nsims = paths.get_ics(simname)
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bounds = {"dist": (0, max_distance)}
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hmf = np.full((len(nsims), len(bin_edges) - 1), np.nan)
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volume = 4 / 3 * np.pi * max_distance**3
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for i, nsim in enumerate(tqdm(nsims)):
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if "csiborg2_" in simname:
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kind = simname.split("_")[-1]
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if halofinder == "FOF":
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cat = csiborgtools.read.CSiBORG2Catalogue(
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nsim, 99, kind, bounds=bounds)
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elif halofinder == "SUBFIND":
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cat = csiborgtools.read.CSiBORG2SUBFINDCatalogue(
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nsim, 99, kind, kind, bounds=bounds)
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else:
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raise ValueError(f"Unknown halofinder: {halofinder}")
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else:
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raise ValueError(f"Unknown simname: {simname}")
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hmf[i] = cat.halo_mass_function(bin_edges, volume, "totmass")[1]
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return hmf
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def MDPL2_HMF(bin_edges):
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"""MDPL2 FoF halo mass function."""
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fname = "/mnt/extraspace/rstiskalek/catalogs/MDPL2_FOF_125.hdf5"
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with File(fname, "r") as f:
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mass = f["mass"][:]
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dx = np.diff(np.log10(bin_edges))
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if not np.all(np.isclose(dx, dx[0])):
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raise ValueError("Bin edges must be logarithmically spaced.")
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dx = dx[0]
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hmf = csiborgtools.number_counts(mass, bin_edges)
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hmf /= 1000**3 * dx
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return hmf
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