Esempio n. 1
0
    elo, ehi = float(elo), float(ehi)
    load_pha(id, filename)
    ignore_id(id, None, None)
    notice_id(id, elo, ehi)
    ids.append(id)

    set_analysis(id, 'ener', 'counts')

set_xlog()
set_ylog()
set_stat('cstat')
set_xsabund('wilm')
set_xsxsect('vern')

id = ids[0]
galabso = bxa.auto_galactic_absorption(id)
galabso.nH.freeze()

# Models available at https://doi.org/10.5281/zenodo.602282
load_table_model("torus",
                 '/home/user/Downloads/specmodels/uxclumpy-cutoff.fits')
load_table_model("scat",
                 '/home/user/Downloads/specmodels/uxclumpy-cutoff-omni.fits')
# the limits correspond to fluxes between Sco X-1 and CDFS7Ms faintest fluxes
srclevel = Parameter('src', 'level', 0, -8, 3, -20, 20)
print('combining components')
model = torus + scat
print('linking parameters')
torus.norm = 10**srclevel
srcnh = Parameter('src', 'nH', 22, 20, 26, 20, 26)
torus.nh = 10**(srcnh - 22)
Esempio n. 2
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	print('loading background fitting module...')
	from bxa.sherpa.background.pca import auto_background

	# BXA fully supports fitting multiple ids with the usual id=2, otherids=(3,4,5) 
	#     parameters
	id = 2
	load_pha(id, 'interval0pc.pi')
	if get_rmf(id).energ_lo[0] == 0: get_rmf(id).energ_lo[0] = 0.001
	if get_arf(id).energ_lo[0] == 0: get_arf(id).energ_lo[0] = 0.001
	set_stat('cstat')
	set_xsabund('wilm')
	set_xsxsect('vern')

	# next we set up a source model.
	#    with automatic milky way absorption
	model = xszpowerlw.src * xszwabs.abso * bxa.auto_galactic_absorption(id)
	src.norm.val = 1e-5

	#    with automatic background from PCA
	set_model(id, model)
	convmodel = get_model(id)
	bkg_model = auto_background(id)
	#set_bkg_full_model(id, bkg_model)
	set_full_model(id, convmodel + bkg_model*get_bkg_scale(id))

	id2 = None
	if os.path.exists('interval0wt.pi'):
		id2 = 3
		load_pha(id2, 'interval0wt.pi')
		if get_rmf(id2).energ_lo[0] == 0: get_rmf(id2).energ_lo[0] = 0.001
		if get_arf(id2).energ_lo[0] == 0: get_arf(id2).energ_lo[0] = 0.001