def test_ARFModelPHA(self):
from sherpa.astro import ui
ui.load_pha(self.make_path("3c120_meg_1.pha"))
# remove the RMF to ensure this is an ARF-only analysis
# (which is what is needed to trigger the bug that lead to #699)
ui.get_data().set_rmf(None)
ui.group_counts(20)
ui.notice(0.5, 6)
ui.subtract()
ui.set_model(ui.xsphabs.abs1 * (ui.xsapec.bubble + ui.powlaw1d.p1))
ui.set_xsabund('angr')
ui.set_xsxsect('vern')
abs1.nh = 0.163
abs1.nh.freeze()
p1.ampl = 0.017
p1.gamma = 1.9
bubble.kt = 0.5
bubble.norm = 4.2e-5
tol = 1.0e-2
ui.set_method_opt('ftol', tol)
ui.fit()
result = ui.get_fit_results()
assert result.numpoints == self._fit_using_ARFModelPHA['numpoints']
assert result.dof == self._fit_using_ARFModelPHA['dof']
def test_eqwith_err1(make_data_path, restore_xspec_settings):
def check1(e0, e1, e2):
assert e0 == approx(0.028335201547206704, rel=1.0e-3)
assert e1 == approx(-0.00744118799274448756, rel=1.0e-3)
assert e2 == approx(0.0706249544851336, rel=1.0e-3)
ui.set_xsabund('angr')
ui.set_xsxsect('bcmc')
ui.load_pha(make_data_path('3c273.pi'))
ui.notice(0.5, 7.0)
ui.set_stat("chi2datavar")
ui.set_method("simplex")
ui.set_model('powlaw1d.p1+gauss1d.g1')
g1.fwhm = 0.1
g1.pos = 2.0
ui.freeze(g1.pos, g1.fwhm)
ui.fit()
numpy.random.seed(2345)
e = ui.eqwidth(p1, p1 + g1, error=True, niter=100)
check1(e[0], e[1], e[2])
params = e[3]
numpy.random.seed(2345)
e = ui.eqwidth(p1, p1 + g1, error=True, params=params, niter=100)
check1(e[0], e[1], e[2])
parvals = ui.get_fit_results().parvals
assert parvals[0] == approx(1.9055272902160334, rel=1.0e-3)
assert parvals[1] == approx(0.00017387966749772638, rel=1.0e-3)
assert parvals[2] == approx(1.279415076070516e-05, rel=1.0e-3)
def test_eqwith_err1(make_data_path, restore_xspec_settings):
def check1(e0, e1, e2):
assert e0 == pytest.approx(0.028335201547206704, rel=1.0e-3)
assert e1 == pytest.approx(-0.00744118799274448756, rel=1.0e-3)
assert e2 == pytest.approx(0.0706249544851336, rel=1.0e-3)
ui.set_xsabund('angr')
ui.set_xsxsect('bcmc')
ui.load_pha(make_data_path('3c273.pi'))
ui.notice(0.5, 7.0)
ui.set_stat("chi2datavar")
ui.set_method("simplex")
ui.set_model('powlaw1d.p1+gauss1d.g1')
g1.fwhm = 0.1
g1.pos = 2.0
ui.freeze(g1.pos, g1.fwhm)
ui.fit()
np.random.seed(2345)
e = ui.eqwidth(p1, p1 + g1, error=True, niter=100)
check1(e[0], e[1], e[2])
params = e[3]
np.random.seed(2345)
e = ui.eqwidth(p1, p1 + g1, error=True, params=params, niter=100)
check1(e[0], e[1], e[2])
parvals = ui.get_fit_results().parvals
assert parvals[0] == pytest.approx(1.9055272902160334, rel=1.0e-3)
assert parvals[1] == pytest.approx(0.00017387966749772638, rel=1.0e-3)
assert parvals[2] == pytest.approx(1.279415076070516e-05, rel=1.0e-3)
def test_eqwith_err(make_data_path, restore_xspec_settings):
def check(a0, a1, a2):
assert a0 == approx(0.16443033244310976, rel=1e-3)
assert a1 == approx(0.09205564216156815, rel=1e-3)
assert a2 == approx(0.23933118287470895, rel=1e-3)
ui.set_method('neldermead')
ui.set_stat('cstat')
ui.set_xsabund('angr')
ui.set_xsxsect('bcmc')
ui.load_data(make_data_path('12845.pi'))
ui.notice(0.5, 7)
ui.set_model("xsphabs.gal*xszphabs.zabs*(powlaw1d.p1+xszgauss.g1)")
ui.set_par(gal.nh, 0.08)
ui.freeze(gal)
ui.set_par(zabs.redshift, 0.518)
ui.set_par(g1.redshift, 0.518)
ui.set_par(g1.Sigma, 0.01)
ui.freeze(g1.Sigma)
ui.set_par(g1.LineE, min=6.0, max=7.0)
ui.fit()
numpy.random.seed(12345)
result = ui.eqwidth(p1, p1 + g1, error=True, niter=100)
check(result[0], result[1], result[2])
params = result[3]
numpy.random.seed(12345)
result = ui.eqwidth(p1, p1 + g1, error=True, params=params, niter=100)
check(result[0], result[1], result[2])
parvals = ui.get_fit_results().parvals
assert parvals[0] == approx(0.6111340686157877, rel=1.0e-3)
assert parvals[1] == approx(1.6409785803466297, rel=1.0e-3)
assert parvals[2] == approx(8.960926761312153e-05, rel=1.0e-3)
assert parvals[3] == approx(6.620017726014523, rel=1.0e-3)
assert parvals[4] == approx(1.9279114810359657e-06, rel=1.0e-3)
def test_eqwith_err(make_data_path, restore_xspec_settings):
def check(a0, a1, a2):
assert a0 == pytest.approx(0.16443033244310976, rel=1e-3)
assert a1 == pytest.approx(0.09205564216156815, rel=1e-3)
assert a2 == pytest.approx(0.23933118287470895, rel=1e-3)
ui.set_method('neldermead')
ui.set_stat('cstat')
ui.set_xsabund('angr')
ui.set_xsxsect('bcmc')
ui.load_data(make_data_path('12845.pi'))
ui.notice(0.5, 7)
ui.set_model("xsphabs.gal*xszphabs.zabs*(powlaw1d.p1+xszgauss.g1)")
ui.set_par(gal.nh, 0.08)
ui.freeze(gal)
ui.set_par(zabs.redshift, 0.518)
ui.set_par(g1.redshift, 0.518)
ui.set_par(g1.Sigma, 0.01)
ui.freeze(g1.Sigma)
ui.set_par(g1.LineE, min=6.0, max=7.0)
ui.fit()
np.random.seed(12345)
result = ui.eqwidth(p1, p1 + g1, error=True, niter=100)
check(result[0], result[1], result[2])
params = result[3]
np.random.seed(12345)
result = ui.eqwidth(p1, p1 + g1, error=True, params=params, niter=100)
check(result[0], result[1], result[2])
parvals = ui.get_fit_results().parvals
assert parvals[0] == pytest.approx(0.6111340686157877, rel=1.0e-3)
assert parvals[1] == pytest.approx(1.6409785803466297, rel=1.0e-3)
assert parvals[2] == pytest.approx(8.960926761312153e-05, rel=1.0e-3)
assert parvals[3] == pytest.approx(6.620017726014523, rel=1.0e-3)
assert parvals[4] == pytest.approx(1.9279114810359657e-06, rel=1.0e-3)
def test_xspec_con_ui_cflux(make_data_path, clean_astro_ui, restore_xspec_settings):
"""Check cflux from the UI layer with a response."""
from sherpa.astro import xspec
infile = make_data_path('3c273.pi')
ui.load_pha('random', infile)
ui.subtract('random')
ui.ignore(None, 0.5)
ui.ignore(7, None)
ui.set_source('random', 'xsphabs.gal * xscflux.sflux(powlaw1d.pl)')
mdl = ui.get_source('random')
assert mdl.name == '(xsphabs.gal * xscflux.sflux(powlaw1d.pl))'
assert len(mdl.pars) == 7
assert mdl.pars[0].fullname == 'gal.nH'
assert mdl.pars[1].fullname == 'sflux.Emin'
assert mdl.pars[2].fullname == 'sflux.Emax'
assert mdl.pars[3].fullname == 'sflux.lg10Flux'
assert mdl.pars[4].fullname == 'pl.gamma'
assert mdl.pars[5].fullname == 'pl.ref'
assert mdl.pars[6].fullname == 'pl.ampl'
assert isinstance(mdl.lhs, xspec.XSphabs)
assert isinstance(mdl.rhs, xspec.XSConvolutionModel)
gal = ui.get_model_component('gal')
sflux = ui.get_model_component('sflux')
pl = ui.get_model_component('pl')
assert isinstance(gal, xspec.XSphabs)
assert isinstance(sflux, xspec.XScflux)
assert isinstance(pl, PowLaw1D)
# the convolution model needs the normalization to be fixed
# (not for this example, as we are not fitting, but do this
# anyway for reference)
pl.ampl.frozen = True
sflux.emin = 1
sflux.emax = 5
sflux.lg10Flux = -12.3027
pl.gamma = 2.03
gal.nh = 0.039
ui.set_xsabund('angr')
ui.set_xsxsect('vern')
# check we get the "expected" statistic (so this is a regression
# test).
#
ui.set_stat('chi2gehrels')
sinfo = ui.get_stat_info()
assert len(sinfo) == 1
sinfo = sinfo[0]
assert sinfo.numpoints == 40
assert sinfo.dof == 37
assert sinfo.statval == pytest.approx(21.25762265234619)
# Do we get the same flux from Sherpa's calc_energy_flux?
#
cflux = ui.calc_energy_flux(id='random', model=sflux(pl), lo=1, hi=5)
lcflux = np.log10(cflux)
assert lcflux == pytest.approx(sflux.lg10Flux.val)
elo, ehi = args.energyrange.split(':')
elo, ehi = float(elo), float(ehi)
load_pha(id, filename)
try:
assert get_rmf(id).energ_lo[0] > 0
assert get_arf(id).energ_lo[0] > 0
assert (get_bkg(id).counts > 0).sum() > 0
except:
traceback.print_exc()
sys.exit(0)
set_xlog()
set_ylog()
set_stat('cstat')
set_xsabund('wilm')
set_xsxsect('vern')
set_analysis(id, 'ener', 'counts')
ignore(None, elo)
ignore(ehi, None)
notice(elo, ehi)
prefix = filename + '_xagnfitter_out_'
#import json
#z = float(open(filename + '.z').read())
#galnh_value = float(open(filename + '.nh').read())
galabso = auto_galactic_absorption()
galabso.nH.freeze()
if args.backgroundmodel == 'chandra':