# This program is free software; you can redistribute it and/or modify it # under the terms of the GNU General Public License as published by the # Free Software Foundation; either version 3 of the License, or (at your # option) any later version. # # This program is distributed in the hope that it will be useful, but # WITHOUT ANY WARRANTY; without even the implied warranty of # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General # Public License for more details. # # You should have received a copy of the GNU General Public License along # with this program; if not, write to the Free Software Foundation, Inc., # 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301, USA. """A script to calculate overlap between two CSiBORG realisations.""" from argparse import ArgumentParser from copy import deepcopy from datetime import datetime from distutils.util import strtobool import numpy from scipy.ndimage import gaussian_filter try: import csiborgtools except ModuleNotFoundError: import sys sys.path.append("../") import csiborgtools def pair_match(nsim0, nsimx, sigma, smoothen, verbose): from csiborgtools.read import HaloCatalogue, read_h5 paths = csiborgtools.read.Paths(**csiborgtools.paths_glamdring) smooth_kwargs = {"sigma": sigma, "mode": "constant", "cval": 0.0} overlapper = csiborgtools.match.ParticleOverlap() matcher = csiborgtools.match.RealisationsMatcher() # Load the raw catalogues (i.e. no selection) including the initial CM # positions and the particle archives. bounds = {"totpartmass": (1e12, None)} cat0 = HaloCatalogue(nsim0, paths, load_initial=True, bounds=bounds, with_lagpatch=True, load_clumps_cat=True) catx = HaloCatalogue(nsimx, paths, load_initial=True, bounds=bounds, with_lagpatch=True, load_clumps_cat=True) clumpmap0 = read_h5(paths.particles(nsim0))["clumpmap"] parts0 = read_h5(paths.initmatch(nsim0, "particles"))["particles"] clid2map0 = {clid: i for i, clid in enumerate(clumpmap0[:, 0])} clumpmapx = read_h5(paths.particles(nsimx))["clumpmap"] partsx = read_h5(paths.initmatch(nsimx, "particles"))["particles"] clid2mapx = {clid: i for i, clid in enumerate(clumpmapx[:, 0])} # We generate the background density fields. Loads halos's particles one by # one from the archive, concatenates them and calculates the NGP density # field. if verbose: print(f"{datetime.now()}: generating the background density fields.", flush=True) delta_bckg = overlapper.make_bckg_delta(parts0, clumpmap0, clid2map0, cat0, verbose=verbose) delta_bckg = overlapper.make_bckg_delta(partsx, clumpmapx, clid2mapx, catx, delta=delta_bckg, verbose=verbose) # We calculate the overlap between the NGP fields. if verbose: print(f"{datetime.now()}: crossing the simulations.", flush=True) match_indxs, ngp_overlap = matcher.cross(cat0, catx, parts0, partsx, clumpmap0, clumpmapx, delta_bckg, verbose=verbose) # We wish to store the halo IDs of the matches, not their array positions # in the catalogues match_hids = deepcopy(match_indxs) for i, matches in enumerate(match_indxs): for j, match in enumerate(matches): match_hids[i][j] = catx["index"][match] fout = paths.overlap(nsim0, nsimx, smoothed=False) numpy.savez(fout, ref_hids=cat0["index"], match_hids=match_hids, ngp_overlap=ngp_overlap) if verbose: print(f"{datetime.now()}: calculated NGP overlap, saved to {fout}.", flush=True) if not smoothen: quit() # We now smoothen up the background density field for the smoothed overlap # calculation. if verbose: print(f"{datetime.now()}: smoothing the background field.", flush=True) gaussian_filter(delta_bckg, output=delta_bckg, **smooth_kwargs) # We calculate the smoothed overlap for the pairs whose NGP overlap is > 0. smoothed_overlap = matcher.smoothed_cross(cat0, catx, parts0, partsx, clumpmap0, clumpmapx, delta_bckg, match_indxs, smooth_kwargs, verbose=verbose) fout = paths.overlap(nsim0, nsimx, smoothed=True) numpy.savez(fout, smoothed_overlap=smoothed_overlap, sigma=sigma) if verbose: print(f"{datetime.now()}: calculated smoothing, saved to {fout}.", flush=True) if __name__ == "__main__": parser = ArgumentParser() parser.add_argument("--nsim0", type=int) parser.add_argument("--nsimx", type=int) parser.add_argument("--sigma", type=float, default=None) parser.add_argument("--smoothen", type=lambda x: bool(strtobool(x)), default=None) parser.add_argument("--verbose", type=lambda x: bool(strtobool(x)), default=False) args = parser.parse_args() pair_match(args.nsim0, args.nsimx, args.sigma, args.smoothen, args.verbose)