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#!/usr/bin/env python3
#
# Copyright (c) 2016 Aaron LI
# MIT license
#
# Calculate the surface brightness concentration (i.e., C_{SB}), which
# is an index/indicator of the cool core, and may be defined as:
# (1) brightness(<=40kpc) / brightness(<=400kpc)
# (2) brightness(<=0.048R500) / brightness(<=0.45R500)
#
# References:
# [1] Santos, J. S., Rosati, P., Tozi, P., et al. 2008, A&A, 483, 35
#
# Created: 2016-04-28
#
# Change log:
# 2016-06-07:
# * Update function `calc_csb()`
# 2016-05-16:
# * Add some background subtraction support
# * Use `subprocess.run` instead of `subprocess.call`
# * PEP8 fixes
# 2016-04-29:
# * Fix order of executing ds9 and print message
# * Fix C_SB calculation
# * Add reference
# * Fix "cuspiness" to "concentration"
# * Add "name" and "obsid" to results
# 2016-04-28:
# * Add "csb_type" to results
#
# TODO/XXX:
# whether the background should be subtracted for C_SB calculation??
#
import sys
import os
import glob
import json
import argparse
import subprocess
from collections import OrderedDict
from astropy.io import fits
from make_r500_regions import get_r500, get_center
def make_csb_region(regfile, center, r1, r2):
"""
Make the regions for C_SB and save.
"""
regions = [
"pie(%.2f,%.2f,0,%.2f,0,360)" % (center[0], center[1], r1),
"pie(%.2f,%.2f,0,%.2f,0,360)" % (center[0], center[1], r2),
]
open(regfile, "w").write("\n".join(regions) + "\n")
def calc_csb(infile, expmap, regfile, r1, r2, bkg=None):
"""
Calculate the C_SB
If `bkg` is provided, then background subtraction is considered
for `dmextract` to calculate the *net* counts and surface brightness.
"""
csbfile = os.path.splitext(regfile)[0] + ".fits"
cmd_args = [
"dmextract",
"infile=%s[bin sky=@%s]" % (infile, regfile),
"outfile=%s" % csbfile,
"exp=%s" % expmap,
"opt=generic", "clobber=yes"
]
if bkg is not None:
# consider background subtraction
subprocess.run(["punlearn", "dmkeypar"])
ret = subprocess.run(args=["dmkeypar", infile, "EXPOSURE", "echo=yes"],
check=True, stdout=subprocess.PIPE)
exposure_evt = float(ret.stdout.decode("utf-8"))
ret = subprocess.run(args=["dmkeypar", bkg, "EXPOSURE", "echo=yes"],
check=True, stdout=subprocess.PIPE)
exposure_bkg = float(ret.stdout.decode("utf-8"))
bkg_norm = exposure_evt / exposure_bkg
cmd_args += [
"bkg=%s[bin sky=@%s]" % (bkg, regfile),
"bkgnorm=%s" % bkg_norm,
"bkgexp=)exp"
]
subprocess.run(["punlearn", "dmextract"])
subprocess.run(args=cmd_args)
# read calculate C_SB data from output FITS
with fits.open(csbfile) as csb_fits:
csb_s_val = csb_fits["HISTOGRAM"].data["SUR_BRI"]
csb_s_err = csb_fits["HISTOGRAM"].data["SUR_BRI_ERR"]
# if bkg is not None:
# bkg_csb_s_val = csb_fits["HISTOGRAM"].data["BG_SUR_BRI"]
# bkg_csb_s_err = csb_fits["HISTOGRAM"].data["BG_SUR_BRI_ERR"]
# calculate C_SB and error
area_ratio = (r2 / r1) ** 2
csb = csb_s_val[0] / csb_s_val[1] / area_ratio
csb_err = csb * ((csb_s_err[0] / csb_s_val[0])**2 +
(csb_s_err[1] / csb_s_val[1])**2) ** 0.5
results = OrderedDict([
("csb_s1", csb_s_val[0]),
("csb_s1_err", csb_s_err[0]),
("csb_s2", csb_s_val[1]),
("csb_s2_err", csb_s_err[1]),
("csb", csb),
("csb_err", csb_err),
])
return results
def main():
parser = argparse.ArgumentParser(
description="Calculate the surface brightness concentration")
# exclusive argument group for C_SB definition
grp_csb = parser.add_mutually_exclusive_group(required=True)
grp_csb.add_argument("-K", "--kpc", dest="kpc", action="store_true",
help="C_SB = brightness(<=0.048R500) " +
"/ brightness(<=0.45R500)")
grp_csb.add_argument("-R", "--r500", dest="r500", action="store_true",
help="C_SB = brightness(<=40kpc) " +
"/ brightness(<=400kpc)")
#
parser.add_argument("-A", "--no-ask", dest="no_ask",
required=False, action="store_true",
help="do NOT check region and ask")
parser.add_argument("-j", "--json", dest="json", required=False,
help="the *_INFO.json file " +
"(default: find ../*_INFO.json)")
parser.add_argument("-r", "--region", dest="region",
required=False, default="sbprofile.reg",
help="region from which to extract the center " +
"coordinate (default: sbprofile.reg)")
parser.add_argument("-i", "--infile", dest="infile", required=True,
help="binned image used to calculate the C_SB")
parser.add_argument("-e", "--expmap", dest="expmap", required=True,
help="exposure map of the input image")
parser.add_argument("-b", "--bkg", dest="bkg", default=None,
help="background image with respect to the input file")
parser.add_argument("-o", "--outfile", dest="outfile", required=True,
help="output json file to store the C_SB results")
#
args = parser.parse_args()
# default "*_INFO.json"
info_json = glob.glob("../*_INFO.json")[0]
if args.json:
info_json = args.json
json_str = open(info_json).read().rstrip().rstrip(",")
info = json.loads(json_str)
name = info["Source Name"]
obsid = int(info["Obs. ID"])
r500 = get_r500(info)
r500_kpc = r500["r500_kpc"]
r500_pix = r500["r500_pix"]
kpc_per_pix = r500["kpc_per_pix"]
print("R500: %.2f (kpc), %.2f (pixel)" % (r500_kpc, r500_pix))
# get center coordinate
xc, yc = get_center(args.region)
if args.r500:
csb_type = "r500"
r1 = 0.048 * r500_pix
r2 = 0.450 * r500_pix
elif args.kpc:
csb_type = "kpc"
r1 = 40.0 / kpc_per_pix
r2 = 400.0 / kpc_per_pix
else:
raise ValueError("Unknown C_SB definition")
# make regions for C_SB
regfile = os.path.splitext(args.outfile)[0] + ".reg"
make_csb_region(regfile, center=(xc, yc), r1=r1, r2=r2)
# check region with DS9
if not args.no_ask:
print("Check the C_SB regions; overwrite the region file " +
"'%s' if modified" % regfile, flush=True, file=sys.stderr)
cmd = "ds9 %s -cmap he " % args.infile + \
"-regions format ciao -regions %s" % regfile
subprocess.call(cmd, shell=True)
ans = input("C_SB regions exceed CCD (No/yes/modified)? ")
if ans == "" or ans[0] in "nN":
csb_region_note = "OK"
elif ans[0] in "yY":
csb_region_note = "EXCESS"
elif ans[0] in "mM":
csb_region_note = "MODIFIED"
else:
csb_region_note = "???"
else:
csb_region_note = None
# calculate the C_SB
csb = calc_csb(args.infile, expmap=args.expmap,
regfile=regfile, r1=r1, r2=r2, bkg=args.bkg)
csb_data = OrderedDict([
("name", name),
("obsid", obsid),
("csb_type", csb_type),
("csb_r1", r1),
("csb_r2", r2),
])
csb_data.update(csb)
csb_data["csb_region"] = csb_region_note
csb_data_json = json.dumps(csb_data, indent=2)
print(csb_data_json)
open(args.outfile, "w").write(csb_data_json + "\n")
if __name__ == "__main__":
main()
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