def test_pha_intro(self):
self.run_thread('pha_intro')
# astro.ui imported as ui, instead of
# being in global namespace
self.assertEqualWithinTol(ui.get_fit_results().statval, 37.9079, 1e-4)
self.assertEqualWithinTol(ui.get_fit_results().rstat, 0.902569, 1e-4)
self.assertEqualWithinTol(ui.get_fit_results().qval, 0.651155, 1e-4)
self.assertEqualWithinTol(self.locals['p1'].gamma.val, 2.15852, 1e-4)
self.assertEqualWithinTol(self.locals['p1'].ampl.val, 0.00022484, 1e-4)
self.assertEqualWithinTol(ui.calc_photon_flux(), 0.000469964, 1e-4)
self.assertEqualWithinTol(ui.calc_energy_flux(), 9.614847e-13, 1e-4)
self.assertEqualWithinTol(ui.calc_data_sum(), 706.85714092, 1e-4)
self.assertEqualWithinTol(ui.calc_model_sum(), 638.45693377, 1e-4)
self.assertEqualWithinTol(ui.calc_source_sum(), 0.046996409, 1e-4)
self.assertEqualWithinTol(
ui.eqwidth(self.locals['p1'], ui.get_source()), -0.57731725, 1e-4)
self.assertEqualWithinTol(
ui.calc_kcorr([1, 1.2, 1.4, 1.6, 1.8, 2], 0.5, 2), [
0.93341286, 0.93752836, 0.94325233, 0.94990140, 0.95678054,
0.96393515
], 1e-4)
self.assertEqual(ui.get_fit_results().nfev, 22)
self.assertEqual(ui.get_fit_results().numpoints, 44)
self.assertEqual(ui.get_fit_results().dof, 42)
def cmp_pha_intro(fit_result, p1, covarerr):
assert fit_result.statval == approx(37.9079, rel=1e-4)
assert fit_result.rstat == approx(0.902569, rel=1e-4)
assert fit_result.qval == approx(0.651155, rel=1e-4)
self.assertEqual(fit_result.nfev, 22)
self.assertEqual(fit_result.numpoints, 44)
self.assertEqual(fit_result.dof, 42)
p1.gamma.val == approx(2.15852, rel=1e-4)
p1.ampl.val == approx(0.00022484, rel=1e-4)
assert ui.calc_photon_flux() == approx(0.000469964, rel=1e-4)
assert ui.calc_energy_flux() == approx(9.614847e-13, rel=1e-4)
assert ui.calc_data_sum() == approx(706.85714092, rel=1e-4)
assert ui.calc_model_sum() == approx(638.45693377, rel=1e-4)
assert ui.calc_source_sum() == approx(0.046996409, rel=1e-4)
calc = ui.eqwidth(self.locals['p1'], ui.get_source())
assert calc == approx(-0.57731725, rel=1e-4)
calc = ui.calc_kcorr([1, 1.2, 1.4, 1.6, 1.8, 2], 0.5, 2)
# Prior to fixing #619 the expected values were
# expected = [0.93341286, 0.93752836, 0.94325233,
# 0.94990140, 0.95678054, 0.96393515]
expected = [0.93132747, 0.9352768, 0.94085917,
0.94738472, 0.95415463, 0.96121113]
assert calc == approx(expected, rel=1e-4)
def test_pha_intro(self):
self.run_thread("pha_intro")
# astro.ui imported as ui, instead of
# being in global namespace
self.assertEqualWithinTol(ui.get_fit_results().statval, 37.9079, 1e-4)
self.assertEqualWithinTol(ui.get_fit_results().rstat, 0.902569, 1e-4)
self.assertEqualWithinTol(ui.get_fit_results().qval, 0.651155, 1e-4)
self.assertEqualWithinTol(self.locals["p1"].gamma.val, 2.15852, 1e-4)
self.assertEqualWithinTol(self.locals["p1"].ampl.val, 0.00022484, 1e-4)
self.assertEqualWithinTol(ui.calc_photon_flux(), 0.000469964, 1e-4)
self.assertEqualWithinTol(ui.calc_energy_flux(), 9.614847e-13, 1e-4)
self.assertEqualWithinTol(ui.calc_data_sum(), 706.85714092, 1e-4)
self.assertEqualWithinTol(ui.calc_model_sum(), 638.45693377, 1e-4)
self.assertEqualWithinTol(ui.calc_source_sum(), 0.046996409, 1e-4)
self.assertEqualWithinTol(ui.eqwidth(self.locals["p1"], ui.get_source()), -0.57731725, 1e-4)
self.assertEqualWithinTol(
ui.calc_kcorr([1, 1.2, 1.4, 1.6, 1.8, 2], 0.5, 2),
[0.93341286, 0.93752836, 0.94325233, 0.94990140, 0.95678054, 0.96393515],
1e-4,
)
self.assertEqual(ui.get_fit_results().nfev, 22)
self.assertEqual(ui.get_fit_results().numpoints, 44)
self.assertEqual(ui.get_fit_results().dof, 42)
def cmp_thread(fit_result, p1, covarerr):
assert fit_result.statval == approx(37.9079, rel=1e-4)
assert fit_result.rstat == approx(0.902569, rel=1e-4)
assert fit_result.qval == approx(0.651155, rel=1e-4)
assert fit_result.nfev == 22
assert fit_result.numpoints == 44
assert fit_result.dof == 42
p1.gamma.val == approx(2.15852, rel=1e-4)
p1.ampl.val == approx(0.00022484, rel=1e-4)
assert ui.calc_photon_flux() == approx(0.000469964, rel=1e-4)
assert ui.calc_energy_flux() == approx(9.614847e-13, rel=1e-4)
assert ui.calc_data_sum() == approx(706.85714092, rel=1e-4)
assert ui.calc_model_sum() == approx(638.45693377, rel=1e-4)
assert ui.calc_source_sum() == approx(0.046996409, rel=1e-4)
calc = ui.eqwidth(p1, ui.get_source())
assert calc == approx(-0.57731725, rel=1e-4)
calc = ui.calc_kcorr([1, 1.2, 1.4, 1.6, 1.8, 2], 0.5, 2)
expected = [
0.93132747, 0.9352768, 0.94085917, 0.94738472, 0.95415463,
0.96121113
]
assert calc == approx(expected, rel=1e-4)
def test_pha_intro(self):
self.run_thread('pha_intro')
# astro.ui imported as ui, instead of
# being in global namespace
fit_results = ui.get_fit_results()
covarerr = sqrt(fit_results.extra_output['covar'].diagonal())
assert covarerr[0] == approx(0.0790393, rel=1e-4)
assert covarerr[1] == approx(1.4564e-05, rel=1e-4)
assert fit_results.statval == approx(37.9079, rel=1e-4)
assert fit_results.rstat == approx(0.902569, rel=1e-4)
assert fit_results.qval == approx(0.651155, rel=1e-4)
assert self.locals['p1'].gamma.val == approx(2.15852, rel=1e-4)
assert self.locals['p1'].ampl.val == approx(0.00022484, rel=1e-4)
assert ui.calc_photon_flux() == approx(0.000469964, rel=1e-4)
assert ui.calc_energy_flux() == approx(9.614847e-13, rel=1e-4)
assert ui.calc_data_sum() == approx(706.85714092, rel=1e-4)
assert ui.calc_model_sum() == approx(638.45693377, rel=1e-4)
assert ui.calc_source_sum() == approx(0.046996409, rel=1e-4)
calc = ui.eqwidth(self.locals['p1'], ui.get_source())
assert calc == approx(-0.57731725, rel=1e-4)
calc = ui.calc_kcorr([1, 1.2, 1.4, 1.6, 1.8, 2], 0.5, 2)
expected = [0.93341286, 0.93752836, 0.94325233,
0.94990140, 0.95678054, 0.96393515]
assert calc == approx(expected, rel=1e-4)
self.assertEqual(ui.get_fit_results().nfev, 22)
self.assertEqual(ui.get_fit_results().numpoints, 44)
self.assertEqual(ui.get_fit_results().dof, 42)
def fit_multiplets(multipletlist, id = None, outpath = None, plot = False, delta_lam = .2):
#
n_lines = np.sum([len(mult['wave']) for mult in multipletlist])
result = np.zeros(n_lines, dtype = {'names': ['multname', 'linename', 'wave', 'flux', 'errup', 'errdown', 'photons', 'photonflux'], 'formats': ['S30', 'S30', 'f4', 'f4', 'f4', 'f4', 'f4', 'f4']})
currentline = 0
#
for mult in multipletlist:
if outpath is not None:
outfile = os.path.join(outpath, filter(lambda x: x.isalnum(), mult['name']))
else:
outfile = None
fit_lines(mult, id, delta_lam = delta_lam, plot = plot, outfile = outfile)
#
ui.conf(id)
conf_res = ui.get_conf_results()
source = ui.get_source(id)
#set all ampl to 0 and only for 1 line to real value
set_all_val('c0', 0., id)
for lname, lfili, lwave in zip(mult['linename'], mult['fililiname'], mult['wave']):
print 'Fitting line '+str(currentline+1)+'/'+str(n_lines)
par = ui.get_model_component(lfili)
indconf_res = ( np.array(conf_res.parnames) == lfili+'.ampl').nonzero()[0]
set_all_val('ampl', 0., id)
par.ampl.val = conf_res.parvals[indconf_res]
counts = ui.calc_model_sum(None, None, id)
#
print(lname, counts)
photonflux = ui.calc_photon_flux(None, None, id)
# determine scaling between ampl and flux
par.ampl.val = 1
amp2flux = ui.calc_energy_flux(None, None, id)
par.ampl.val = conf_res.parvals[indconf_res]
#
val = conf_res.parvals[indconf_res] * amp2flux
errdown = conf_res.parmins[indconf_res] * amp2flux if conf_res.parmins[indconf_res] else np.nan
errup = conf_res.parmaxes[indconf_res] * amp2flux if conf_res.parmaxes[indconf_res] else np.nan
#
result[currentline] = (mult['name'], lname, lwave, val, errup, errdown, counts, photonflux)
#
currentline +=1
return result
