def test_proj_bubble(self):
self.run_thread('proj_bubble')
# Fit -- Results from reminimize
self.assertEqualWithinTol(self.locals['mek1'].kt.val, 17.8849, 1e-2)
self.assertEqualWithinTol(self.locals['mek1'].norm.val, 4.15418e-06,
1e-2)
# Covar
self.assertEqualWithinTol(ui.get_covar_results().parmins[0], -0.328832,
1e-2)
self.assertEqualWithinTol(ui.get_covar_results().parmins[1],
-8.847916e-07, 1e-2)
self.assertEqualWithinTol(ui.get_covar_results().parmaxes[0], 0.328832,
1e-2)
self.assertEqualWithinTol(ui.get_covar_results().parmaxes[1],
8.847916e-07, 1e-2)
# Proj -- Upper bound of kT can't be found
self.assertEqualWithinTol(ui.get_proj_results().parmins[0], -12.048069,
1e-2)
self.assertEqualWithinTol(ui.get_proj_results().parmins[1],
-9.510913e-07, 1e-2)
self.assertEqual(ui.get_proj_results().parmaxes[0], None)
self.assertEqualWithinTol(ui.get_proj_results().parmaxes[1],
2.403640e-06, 1e-2)
def test_proj_bubble(self):
self.run_thread('proj_bubble')
# Fit -- Results from reminimize
self.assertEqualWithinTol(self.locals['mek1'].kt.val, 17.8849, 1e-2)
self.assertEqualWithinTol(self.locals['mek1'].norm.val, 4.15418e-06,
1e-2)
# Covar
self.assertEqualWithinTol(ui.get_covar_results().parmins[0],
-0.328832, 1e-2)
self.assertEqualWithinTol(ui.get_covar_results().parmins[1],
-8.847916e-07, 1e-2)
self.assertEqualWithinTol(ui.get_covar_results().parmaxes[0],
0.328832, 1e-2)
self.assertEqualWithinTol(ui.get_covar_results().parmaxes[1],
8.847916e-07, 1e-2)
# Proj -- Upper bound of kT can't be found
self.assertEqualWithinTol(ui.get_proj_results().parmins[0],
-12.048069, 1e-2)
self.assertEqualWithinTol(ui.get_proj_results().parmins[1],
-9.510913e-07, 1e-2)
self.assertEqual(ui.get_proj_results().parmaxes[0], None)
self.assertEqualWithinTol(ui.get_proj_results().parmaxes[1],
2.403640e-06, 1e-2)
def test_proj_bubble(self):
def cmp_proj_bubble(mylocals, convarerr, proj, conf):
mek1 = mylocals['mek1']
assert covarerr[0] == approx(0, rel=1e-4)
assert covarerr[1] == approx(8.74608e-07, rel=1e-3)
assert mek1.kt.val == approx(17.8849, rel=1e-2)
assert mek1.norm.val == approx(4.15418e-06, rel=1e-2)
# Proj -- Upper bound of kT can't be found
#
assert proj.parmins[0] == approx(-12.048069, rel=0.01)
assert proj.parmins[1] == approx(-9.510913e-07, rel=0.01)
assert proj.parmaxes[1] == approx(2.403640e-06, rel=0.01)
assert proj.parmaxes[0] is None
assert conf.parmins[0] == approx(-12.1073, rel=0.01)
assert conf.parmaxes[0] == approx(62.0585, rel=0.01)
assert conf.parmins[1] == approx(-9.5568e-07, rel=0.01)
assert conf.parmaxes[1] == approx(2.39937e-06, rel=0.01)
self.run_thread('proj_bubble')
fit_results = ui.get_fit_results()
covarerr = sqrt(fit_results.extra_output['covar'].diagonal())
proj = ui.get_proj_results()
conf = ui.get_conf_results()
cmp_proj_bubble(self.locals, covarerr, proj, conf)
self.run_thread('proj_bubble_ncpus')
fit_results = ui.get_fit_results()
covarerr = sqrt(fit_results.extra_output['covar'].diagonal())
proj = ui.get_proj_results()
conf = ui.get_conf_results()
cmp_proj_bubble(self.locals, covarerr, proj, conf)
def test_proj_bubble(parallel, clean_astro_ui, fix_xspec, run_thread):
# How sensitive are the results to the change from bcmc to vern
# made in XSPEC 12.10.1? It looks like the mekal best-fit
# temperature can jump from ~17.9 to 18.6, so require bcmc
# in this test (handled by fix_xspec).
#
# Note that the error on kT is large, so we can expect that
# changes to the system could change these results. In particular,
# the covariance errors on kt are < 1 but from other error
# analysis they are > 10 or even unbound, so it is likely that the
# covariance error results can change significantly.
#
# The fit results change in XSPEC 12.10.0 since the mekal model
# was changed (FORTRAN to C++). A 1% difference is used for the
# parameter ranges from covar and proj (matches the tolerance for
# the fit results). Note that this tolerance has been relaced to
# 10% for the kT errors, as there is a significant change seen
# with different XSPEC versions for the covariance results.
#
# fit_results is unused
def cmp_thread(fit_results, mek1, covarerr):
assert covarerr[0] == approx(0, rel=1e-4)
assert covarerr[1] == approx(8.74608e-07, rel=1e-3)
assert mek1.kt.val == approx(17.8849, rel=1e-2)
assert mek1.norm.val == approx(4.15418e-06, rel=1e-2)
check_thread(run_thread, 'proj_bubble', parallel, cmp_thread, ['mek1'])
# Covar
#
# TODO: should this check that parmaxes is -1 * parmins instead?
covar = ui.get_covar_results()
assert covar.parmins[0] == approx(-0.653884, rel=0.1)
assert covar.parmins[1] == approx(-8.94436e-07, rel=0.01)
assert covar.parmaxes[0] == approx(0.653884, rel=0.1)
assert covar.parmaxes[1] == approx(8.94436e-07, rel=0.01)
# Proj -- Upper bound of kT can't be found
#
proj = ui.get_proj_results()
assert proj.parmins[0] == approx(-12.048069, rel=0.01)
assert proj.parmins[1] == approx(-9.510913e-07, rel=0.01)
assert proj.parmaxes[0] is None
assert proj.parmaxes[1] == approx(2.403640e-06, rel=0.01)
# Conf
#
conf = ui.get_conf_results()
assert conf.parmins[0] == approx(-12.1073, rel=0.01)
assert conf.parmins[1] == approx(-9.5568e-07, rel=0.01)
assert conf.parmaxes[0] is None
assert conf.parmaxes[1] == approx(2.39937e-06, rel=0.01)
def test_proj_bubble(run_thread):
# How sensitive are the results to the change from bcmc to vern
# made in XSPEC 12.10.1? It looks like the mekal best-fit
# temperature can jump from ~17.9 to 18.6, so require bcmc
# in this test.
#
xspec.set_xsxsect('bcmc')
models = run_thread('proj_bubble')
fit_results = ui.get_fit_results()
covarerr = sqrt(fit_results.extra_output['covar'].diagonal())
assert covarerr[0] == approx(0, rel=1e-4)
assert covarerr[1] == approx(8.74608e-07, rel=1e-2)
# Fit -- Results from reminimize
assert models['mek1'].kt.val == approx(17.8849, rel=1e-2)
assert models['mek1'].norm.val == approx(4.15418e-06, rel=1e-2)
# Fit -- Results from reminimize
# The fit results change in XSPEC 12.10.0 since the mekal model
# was changed (FORTRAN to C++). A 1% difference is used for the
# parameter ranges from covar and proj (matches the tolerance for
# the fit results). Note that this tolerance has been relaced to
# 10% for the kT errors, as there is a significant change seen
# with different XSPEC versions for the covariance results.
#
# Covar
#
# TODO: should this check that parmaxes is -1 * parmins instead?
covar = ui.get_covar_results()
assert covar.parmins[0] == approx(-0.328832, rel=0.1)
assert covar.parmins[1] == approx(-8.847916e-7, rel=0.01)
assert covar.parmaxes[0] == approx(0.328832, rel=0.1)
assert covar.parmaxes[1] == approx(8.847916e-7, rel=0.01)
# Proj -- Upper bound of kT can't be found
#
proj = ui.get_proj_results()
assert proj.parmins[0] == approx(-12.048069, rel=0.01)
assert proj.parmins[1] == approx(-9.510913e-07, rel=0.01)
assert proj.parmaxes[1] == approx(2.403640e-06, rel=0.01)
assert proj.parmaxes[0] is None