#!/usr/bin/env python3 # # Copyright (c) 2016 Weitian LI # 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()