mirror of
https://github.com/Richard-Sti/csiborgtools.git
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67 lines
2.2 KiB
Python
67 lines
2.2 KiB
Python
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# Copyright (C) 2022 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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"""
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Script to test running the CSiBORG realisations matcher.
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"""
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import numpy
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from argparse import ArgumentParser
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from distutils.util import strtobool
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from datetime import datetime
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from os.path import join
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try:
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import csiborgtools
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except ModuleNotFoundError:
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import sys
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sys.path.append("../")
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import csiborgtools
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import utils
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# Argument parser
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parser = ArgumentParser()
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parser.add_argument("--nmult", type=float)
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parser.add_argument("--overlap", type=lambda x: bool(strtobool(x)))
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parser.add_argument("--select_initial", type=lambda x: bool(strtobool(x)))
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parser.add_argument("--fast_neighbours", type=lambda x: bool(strtobool(x)))
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args = parser.parse_args()
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# File paths
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ic = 7468
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fperm = join(utils.dumpdir, "overlap", "cross_{}.npy")
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paths = csiborgtools.read.CSiBORGPaths(to_new=False)
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paths.set_info(ic, paths.get_maximum_snapshot(ic))
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print("{}: loading catalogues.".format(datetime.now()), flush=True)
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cat = csiborgtools.read.CombinedHaloCatalogue(paths)
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matcher = csiborgtools.match.RealisationsMatcher(cat)
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nsim0 = cat.n_sims[0]
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nsimx = cat.n_sims[1]
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print("{}: crossing the simulations.".format(datetime.now()), flush=True)
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out = matcher.cross_knn_position_single(
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0, nmult=args.nmult, dlogmass=2., overlap=args.overlap,
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select_initial=args.select_initial, fast_neighbours=args.fast_neighbours)
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# Dump the result
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fout = fperm.format(nsim0)
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print("Saving results to `{}`.".format(fout), flush=True)
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with open(fout, "wb") as f:
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numpy.save(fout, out)
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print("All finished.", flush=True)
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