mirror of
https://github.com/Richard-Sti/csiborgtools.git
synced 2024-12-22 18:28:02 +00:00
f48eb6dcb0
* add radial position path * pep8 * Add basic fit profile dumping * pep8 * pep8 * pep8 * pep8 * pep8 * pep8 * Update TODO * Fix parts is None bug * Update nb
133 lines
4.3 KiB
Python
133 lines
4.3 KiB
Python
# Copyright (C) 2022 Richard Stiskalek
|
|
# 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 the KNN-CDF for a set of CSiBORG halo catalogues."""
|
|
from argparse import ArgumentParser
|
|
from datetime import datetime
|
|
from itertools import combinations
|
|
from warnings import warn
|
|
|
|
import joblib
|
|
import numpy
|
|
import yaml
|
|
from mpi4py import MPI
|
|
from sklearn.neighbors import NearestNeighbors
|
|
from taskmaster import master_process, worker_process
|
|
|
|
try:
|
|
import csiborgtools
|
|
except ModuleNotFoundError:
|
|
import sys
|
|
|
|
sys.path.append("../")
|
|
import csiborgtools
|
|
|
|
|
|
###############################################################################
|
|
# MPI and arguments #
|
|
###############################################################################
|
|
comm = MPI.COMM_WORLD
|
|
rank = comm.Get_rank()
|
|
nproc = comm.Get_size()
|
|
|
|
parser = ArgumentParser()
|
|
parser.add_argument("--runs", type=str, nargs="+")
|
|
args = parser.parse_args()
|
|
with open("../scripts/knn_cross.yml", "r") as file:
|
|
config = yaml.safe_load(file)
|
|
|
|
Rmax = 155 / 0.705 # Mpc (h = 0.705) high resolution region radius
|
|
paths = csiborgtools.read.CSiBORGPaths(**csiborgtools.paths_glamdring)
|
|
ics = paths.get_ics(False)
|
|
knncdf = csiborgtools.clustering.kNN_CDF()
|
|
|
|
###############################################################################
|
|
# Analysis #
|
|
###############################################################################
|
|
|
|
|
|
def read_single(selection, cat):
|
|
mmask = numpy.ones(len(cat), dtype=bool)
|
|
pos = cat.positions(False)
|
|
# Primary selection
|
|
psel = selection["primary"]
|
|
pmin, pmax = psel.get("min", None), psel.get("max", None)
|
|
if pmin is not None:
|
|
mmask &= cat[psel["name"]] >= pmin
|
|
if pmax is not None:
|
|
mmask &= cat[psel["name"]] < pmax
|
|
return pos[mmask, ...]
|
|
|
|
|
|
def do_cross(run, ics):
|
|
_config = config.get(run, None)
|
|
if _config is None:
|
|
warn("No configuration for run {}.".format(run), stacklevel=1)
|
|
return
|
|
rvs_gen = csiborgtools.clustering.RVSinsphere(Rmax)
|
|
knn1, knn2 = NearestNeighbors(), NearestNeighbors()
|
|
|
|
cat1 = csiborgtools.read.ClumpsCatalogue(ics[0], paths, max_dist=Rmax)
|
|
pos1 = read_single(_config, cat1)
|
|
knn1.fit(pos1)
|
|
|
|
cat2 = csiborgtools.read.ClumpsCatalogue(ics[1], paths, max_dist=Rmax)
|
|
pos2 = read_single(_config, cat2)
|
|
knn2.fit(pos2)
|
|
|
|
rs, cdf0, cdf1, joint_cdf = knncdf.joint(
|
|
knn1,
|
|
knn2,
|
|
rvs_gen=rvs_gen,
|
|
nneighbours=int(config["nneighbours"]),
|
|
rmin=config["rmin"],
|
|
rmax=config["rmax"],
|
|
nsamples=int(config["nsamples"]),
|
|
neval=int(config["neval"]),
|
|
batch_size=int(config["batch_size"]),
|
|
random_state=config["seed"],
|
|
)
|
|
|
|
corr = knncdf.joint_to_corr(cdf0, cdf1, joint_cdf)
|
|
joblib.dump({"rs": rs, "corr": corr}, paths.knncross_path(run, ics))
|
|
|
|
|
|
def do_runs(ics):
|
|
print(ics)
|
|
for run in args.runs:
|
|
do_cross(run, ics)
|
|
|
|
|
|
###############################################################################
|
|
# Crosscorrelation calculation #
|
|
###############################################################################
|
|
|
|
|
|
if nproc > 1:
|
|
if rank == 0:
|
|
tasks = list(combinations(ics, 2))
|
|
master_process(tasks, comm, verbose=True)
|
|
else:
|
|
worker_process(do_runs, comm, verbose=False)
|
|
else:
|
|
tasks = list(combinations(ics, 2))
|
|
for task in tasks:
|
|
print("{}: completing task `{}`.".format(datetime.now(), task))
|
|
do_runs(task)
|
|
comm.Barrier()
|
|
|
|
|
|
if rank == 0:
|
|
print("{}: all finished.".format(datetime.now()))
|
|
quit() # Force quit the script
|