# This file is a part of library for computing Photon Asymmetry (A_phot)

# parameter for morphological classification of cluster.

# This parameter is described in detail in the following publication:

#

# xxxxxxxx

#

# This program is free software: you can redistribute it, modify

# it or unclude parts of it in your free or proprietary software, provided

# that you reference the aforementioned scientific publication.

#

# Copyright (C) 2013 Daniyar Nurgaliev

from numpy.random import RandomState

from scipy.stats import scoreatpercentile

from sys import stdout

from common import sdict, find_core, kpc2pix

from get_args import get_args

from chandra import process_multiple_obs

from libaphot import aphot

# Default parameters

p = sdict(

)

# Get parameters from the command line and configuration file

p.update(get_args())

kpc2px = kpc2pix(p.H, p.Om, p.z) # kpc to pixels conversion factor

R500px = p.R500 * kpc2px # R500 in pixels

# Convert multiple observations, exposure maps, and region files into

# internal representation of X-ray events (evt) and exposure map (expm)

evt, expm = process_multiple_obs(p.ra, p.dec, int(1.5*R500px),

p.Eband, [x*R500px for x in p.R_bkgr],

p.path, p.evt_files.split(), p.exp_files.split(), p.reg_files.split(),

p.inspect)

print ('Calculating Aphot ...')

stdout.flush()

# Find cluster core as the brightest point after convolution with

# sigma = 40 Mpc Gaussian, within 400 Mpc from cluster center coordinates

center = find_core(evt, 40*kpc2px, 400*kpc2px)

# Calculate A_phot

annuli_px = [x*R500px for x in p.annuli]

ap0 = aphot(evt, center, annuli_px, expm=expm)

# Calculate uncertainty ###########################################3

def sample_half_counts(evt0, seed=0):

return evt

if p.Nresamplings > 0:

print ('\nCalculating uncertainty ...')

ap = []

for r in range(p.Nresamplings):

stdout.flush()

evt1 = sample_half_counts(evt, seed=r)

center = find_core(evt1, 40*kpc2px, 400*kpc2px)

ap.append( aphot(evt, center, annuli_px, expm=expm).aphot )

lo = scoreatpercentile(ap, 16)

mid = scoreatpercentile(ap, 50)

hi = scoreatpercentile(ap, 84)

print ('\nAphot =', ap0.aphot, '+', (mid-lo)/1.4142, '-', (hi-mid)/1.4142 )

else:

print ('\nAphot =', ap0.aphot)