mirror of
https://github.com/Richard-Sti/csiborgtools.git
synced 2024-10-19 00:15:06 +02:00
1d847cbd06
* Rename paths object * Remove redshift calculation * Explicit keywrod arg * Rename box units * Basic renaming * Little docs * Rename paths * add imports * Sort imports * Add Quijote cat * Split boxes * add Quijote path * Add origin argument * Update nbs
134 lines
4.3 KiB
Python
134 lines
4.3 KiB
Python
# 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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"""A script to calculate the KNN-CDF for a set of CSiBORG halo catalogues."""
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from argparse import ArgumentParser
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from datetime import datetime
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from itertools import combinations
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from warnings import warn
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import joblib
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import numpy
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import yaml
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from mpi4py import MPI
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from sklearn.neighbors import NearestNeighbors
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from taskmaster import master_process, worker_process
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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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###############################################################################
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# MPI and arguments #
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###############################################################################
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comm = MPI.COMM_WORLD
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rank = comm.Get_rank()
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nproc = comm.Get_size()
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parser = ArgumentParser()
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parser.add_argument("--runs", type=str, nargs="+")
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args = parser.parse_args()
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with open("../scripts/knn_cross.yml", "r") as file:
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config = yaml.safe_load(file)
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Rmax = 155 / 0.705 # Mpc (h = 0.705) high resolution region radius
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paths = csiborgtools.read.Paths(**csiborgtools.paths_glamdring)
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ics = paths.get_ics()
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knncdf = csiborgtools.clustering.kNN_CDF()
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###############################################################################
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# Analysis #
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###############################################################################
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def read_single(selection, cat):
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mmask = numpy.ones(len(cat), dtype=bool)
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pos = cat.positions(False)
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# Primary selection
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psel = selection["primary"]
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pmin, pmax = psel.get("min", None), psel.get("max", None)
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if pmin is not None:
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mmask &= cat[psel["name"]] >= pmin
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if pmax is not None:
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mmask &= cat[psel["name"]] < pmax
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return pos[mmask, ...]
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def do_cross(run, ics):
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_config = config.get(run, None)
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if _config is None:
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warn("No configuration for run {}.".format(run), stacklevel=1)
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return
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rvs_gen = csiborgtools.clustering.RVSinsphere(Rmax)
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knn1, knn2 = NearestNeighbors(), NearestNeighbors()
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cat1 = csiborgtools.read.ClumpsCatalogue(ics[0], paths, max_dist=Rmax)
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pos1 = read_single(_config, cat1)
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knn1.fit(pos1)
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cat2 = csiborgtools.read.ClumpsCatalogue(ics[1], paths, max_dist=Rmax)
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pos2 = read_single(_config, cat2)
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knn2.fit(pos2)
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rs, cdf0, cdf1, joint_cdf = knncdf.joint(
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knn1,
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knn2,
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rvs_gen=rvs_gen,
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nneighbours=int(config["nneighbours"]),
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rmin=config["rmin"],
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rmax=config["rmax"],
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nsamples=int(config["nsamples"]),
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neval=int(config["neval"]),
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batch_size=int(config["batch_size"]),
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random_state=config["seed"],
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)
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corr = knncdf.joint_to_corr(cdf0, cdf1, joint_cdf)
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joblib.dump({"rs": rs, "corr": corr}, paths.knncross_path(run, ics))
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def do_runs(ics):
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print(ics)
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for run in args.runs:
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do_cross(run, ics)
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###############################################################################
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# Crosscorrelation calculation #
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###############################################################################
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if nproc > 1:
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if rank == 0:
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tasks = list(combinations(ics, 2))
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master_process(tasks, comm, verbose=True)
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else:
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worker_process(do_runs, comm, verbose=False)
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else:
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tasks = list(combinations(ics, 2))
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for task in tasks:
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print("{}: completing task `{}`.".format(datetime.now(), task))
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do_runs(task)
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comm.Barrier()
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if rank == 0:
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print("{}: all finished.".format(datetime.now()))
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quit() # Force quit the script
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