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#!/usr/bin/env python3
#
# Copyright (c) 2016 Weitian LI <liweitianux@live.com>
# MIT license
"""
Retrieve the galaxy cluster catalog simulated by the *Hubble Volume Project*:
http://wwwmpa.mpa-garching.mpg.de/galform/virgo/hubble/
The data used by this package is the *cluster catalog* of the *deep wedge*
assuming the *ΛCMD* lightcone geometry,
and can be downloaded from:
http://www.mpa-garching.mpg.de/galform/virgo/hubble/lcdm.DW.tar.gz
The catalog data is downloaded, extracted, transformed, and finally saved
to a CSV file.
Catalog Description
-------------------
The Hubble Volume Project is a joint effort of the Virgo Consortium and
Collaborators in U.S., Canada, U.K., and Germany. To study the formation
of clusters of galaxies, filaments and void-structures, a significant
fraction of the entire observable Universe is modeled and simulated by
employing one billion (1e9) mass particles. [Evard2002]_
The ΛCDM cosmological model, one of the two models adopted by the Project,
has the following parameters:
Ω_m = 0.3, Ω_Λ = 0.7, h = 0.7, σ_8 = 0.9
Cube side length: 3000 h^-1 Mpc
Main slice: 3000 x 3000 x 30 h^-3 Mpc^3
P^3M: z_init = 35, s = 100 h^-1 kpc
1000^3 particles, 1024^3 mesh
M_particle = 2.25e12 h^-1 M_⊙
The retrieved catalog of the galaxy clusters is derived from a *spherical
overdensity* method applied to the *deep wedge* light-cone particle data,
with overdensity threshold Δ=200. The deep wedge lightcone covers
10x10 deg^2, with a maximum LoS distance of 5100 h^-1 Mpc, and a redshift
coverage limit of 4.37. The coordinates used in the catalog are mapped
to 0-1 unit, and as for the deep wedge catalog, the origin is at (0, 0, 0),
and is directed toward (1, 1, 1).
References
----------
.. [Evard2002]
Evard, A. E. et al.,
"Galaxy Clusters in Hubble Volume Simulations: Cosmological Constraints
from Sky Survey Populations",
2002, ApJ, 573, 7-36,
http://adsabs.harvard.edu/abs/2002ApJ...573....7E
"""
import os
import sys
import re
import argparse
import logging
import csv
import urllib.request
import tarfile
from fg21sim.configs import configs
from fg21sim.utils import setup_logging
# URL to the simulated galaxy cluster catalog data
DATA_URL = "http://www.mpa-garching.mpg.de/galform/virgo/hubble/lcdm.DW.tar.gz"
def main():
outfile_default = "HVP_LCDM_DeepWedge_Catalog.csv"
parser = argparse.ArgumentParser(
description="Retrieve Simulated galaxy cluster catalog data")
parser.add_argument("outfile", nargs="?", default=outfile_default,
help="output CSV file to save the catalog data " +
"(default: %s)" % outfile_default)
parser.add_argument("-U", "--url", default=DATA_URL,
help="URL to Green's SNRs catalog summary page " +
"or a local HTML file (default: %s)" % DATA_URL)
parser.add_argument("-C", "--clobber", action="store_true",
help="overwrite the existing output file")
parser.add_argument("-l", "--log", dest="loglevel", default=None,
choices=["DEBUG", "INFO", "WARNING",
"ERROR", "CRITICAL"],
help="set the log level")
parser.add_argument("-L", "--logfile", default=None,
help="filename where to save the log messages")
parser.add_argument("-Q", "--quiet", action="store_true",
help="be quiet so do not log messages to screen")
args = parser.parse_args()
if args.quiet:
log_stream = ""
else:
log_stream = None
tool = os.path.basename(sys.argv[0])
setup_logging(dict_config=configs.logging,
level=args.loglevel,
stream=log_stream,
logfile=args.logfile)
logger = logging.getLogger(tool)
logger.info("COMMAND: {0}".format(" ".join(sys.argv)))
if os.path.exists(args.outfile) and (not args.clobber):
raise IOError("output file already exists: %s" % args.outfile)
basename = os.path.splitext(args.outfile)[0]
fn_catalog = basename + ".tar.gz"
fn_catalogtxt = basename + ".txt"
logger.info("Downloading the catalog data from: {0}".format(args.url))
urllib.request.urlretrieve(args.url, fn_catalog)
logger.info("Done download the catalog as file: {0}".format(fn_catalog))
logger.info("Extract the catalog data from the downloaded archive ...")
tf = tarfile.open(fn_catalog)
members = tf.getmembers()
if len(members) != 1:
raise ValueError("Catalog should contain only 1 file, but got %d" %
len(members))
m0 = members[0]
tf.extract(m0)
tf.close()
os.rename(m0.name, fn_catalogtxt)
logger.info("Done extract catalog data to file: %s" % fn_catalogtxt)
# Data column names
header = ["m", "redshift", "sigma", "ip", "x", "y", "z", "vx", "vy", "vz"]
with open(args.outfile, "w") as csvfile:
csvwriter = csv.writer(csvfile)
csvwriter.writerow(header)
i = 0
for line in open(fn_catalogtxt):
if re.match(r"^\s*#|^\s*$", line):
# Ignore comment and blank line
continue
values = line.split()
if len(header) != len(values):
raise ValueError("Invalid line: '{0}'".format(line))
values = [
int(values[0]), # m: number of particles
float(values[1]), # redshift
float(values[2]), # sigma: measured 1D velocity dispersion
int(values[3]), # ip: parent flag
float(values[4]), # x: cluster X location in 0-1 units
float(values[5]), # y: cluster Y location in 0-1 units
float(values[6]), # z: cluster Z location in 0-1 units
float(values[7]), # vx: physical peculiar velocity [km/s]
float(values[8]), # vy: physical peculiar velocity [km/s]
float(values[9]), # vz: physical peculiar velocity [km/s]
]
i += 1
csvwriter.writerow(values)
logger.info("Catalog data contains %d clusters" % i)
logger.info("Cluster catalog data write to: %s" % args.outfile)
if __name__ == "__main__":
main()
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