mirror of
https://github.com/Richard-Sti/csiborgtools.git
synced 2024-10-19 00:15:06 +02:00
56e39a8b1d
* Store indices as f32 * Fix init sorting * Organise imports * Rename pathing * Add particle loading * Improve particle reading * Add h5py reader * edit particle path * Update particles loading * update particles loading * Fix particle dumping * Add init fitting * Fix bug due to insufficient precision * Add commnet * Add comment * Add clumps catalogue to halo cat * Add comment * Make sure PIDS never forced to float32 * fix pid reading * fix pid reading * Update matching to work with new arrays * Stop using cubical sub boxes, turn off nshift if no smoothing * Improve caching * Move function definitions * Simplify calculation * Add import * Small updates to the halo * Simplify calculation * Simplify looping calculation * fix tonew * Add initial data * Add skip condition * Add unit conversion * Add loading background in batches * Rename mmain index * Switch overlaps to h5 * Add finite lagpatch check * fix column name * Add verbosity flags * Save halo IDs instead. * Switch back to npz * Delte nbs * Reduce size of the box * Load correct bckg of halos being matched * Remove verbosity * verbosity edits * Change lower thresholds
83 lines
3.0 KiB
Python
83 lines
3.0 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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"""
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Script to sort the initial snapshot particles according to their final
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snapshot ordering, which is sorted by the clump IDs.
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"""
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from argparse import ArgumentParser
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from datetime import datetime
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import h5py
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from gc import collect
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import numpy
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from mpi4py import MPI
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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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# Get MPI things
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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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verbose = nproc == 1
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# Argument parser
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parser = ArgumentParser()
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parser.add_argument("--ics", type=int, nargs="+", default=None,
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help="IC realisations. If `-1` processes all simulations.")
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args = parser.parse_args()
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paths = csiborgtools.read.CSiBORGPaths(**csiborgtools.paths_glamdring)
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partreader = csiborgtools.read.ParticleReader(paths)
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# NOTE: ID has to be the last column.
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pars_extract = ["x", "y", "z", "M", "ID"]
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if args.ics is None or args.ics[0] == -1:
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ics = paths.get_ics(tonew=True)
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else:
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ics = args.ics
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# We loop over simulations. Each simulation is then procesed with MPI, rank 0
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# loads the data and broadcasts it to other ranks.
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jobs = csiborgtools.fits.split_jobs(len(ics), nproc)[rank]
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for i in jobs:
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nsim = ics[i]
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nsnap = max(paths.get_snapshots(nsim))
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print(f"{datetime.now()}: reading and processing simulation {nsim}.",
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flush=True)
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# We first load the particle IDs in the final snapshot.
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pidf = csiborgtools.read.read_h5(paths.particles_path(nsim))
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pidf = pidf["particle_ids"]
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# Then we load the particles in the initil snapshot and make sure that
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# their particle IDs are sorted as in the final snapshot.
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# Again, because of precision this must be read as structured.
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part0, pid0 = partreader.read_particle(
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1, nsim, pars_extract, return_structured=False, verbose=verbose)
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# First enforce them to already be sorted and then apply reverse
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# sorting from the final snapshot.
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part0 = part0[numpy.argsort(pid0)]
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del pid0
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collect()
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part0 = part0[numpy.argsort(numpy.argsort(pidf))]
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print(f"{datetime.now()}: dumping particles for {nsim}.", flush=True)
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with h5py.File(paths.initmatch_path(nsim, "particles"), "w") as f:
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f.create_dataset("particles", data=part0)
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