def test_functions(self):
o = Observable('test_obs')
o.arguments = ['x']
def f(wc_obj, par_dict, x):
return x
pr = Prediction('test_obs', f )
wc_obj = None
self.assertEqual(flavio.sm_prediction('test_obs', 7), 7)
self.assertEqual(flavio.np_prediction('test_obs', x=7, wc_obj=wc_obj), 7)
self.assertEqual(flavio.sm_uncertainty('test_obs', 7), 0)
self.assertEqual(flavio.np_uncertainty('test_obs', x=7, wc_obj=wc_obj), 0)
self.assertEqual(flavio.sm_uncertainty('test_obs', 7, threads=2), 0)
self.assertEqual(flavio.np_uncertainty('test_obs', x=7, wc_obj=wc_obj, threads=2), 0)
# delete dummy instance
Observable.del_instance('test_obs')
def test_exp_combo(self):
o = Observable('test_obs')
o.arguments = ['x']
m = Measurement('test_obs measurement 1')
m.add_constraint([('test_obs', 1)], MultivariateNormalDistribution([1, 2], np.eye(2)))
# error: no measurement
with self.assertRaises(ValueError):
flavio.combine_measurements('test_obs', x=1, include_measurements=['bla'])
m.add_constraint([('test_obs', 1)], NormalDistribution(2, 3))
combo = flavio.combine_measurements('test_obs', x=1)
self.assertEqual(combo.central_value, 2)
self.assertEqual(combo.standard_deviation, 3)
m2 = Measurement('test_obs measurement 2')
m2.add_constraint([('test_obs', 1)], NormalDistribution(3, 3))
combo = flavio.combine_measurements('test_obs', x=1)
self.assertAlmostEqual(combo.central_value, 2.5)
self.assertAlmostEqual(combo.standard_deviation, sqrt(9 / 2))
Observable.del_instance('test_obs')
'decays': ['Bs->K*'],
},
}
_process_taxonomy = r'Process :: $b$ hadron decays :: Semi-leptonic tree-level decays :: $B\to V\ell\nu$ :: $'
for l in ['e', 'mu', 'tau', 'l']:
for br in ['dBR/dq2', 'BR', '<BR>']:
for M in _hadr.keys():
_process_tex = _hadr[M]['tex'] + _tex[l] + r"^+\nu_" + _tex[l]
_obs_name = br + "(" + M + l + "nu)"
_obs = Observable(_obs_name)
_obs.set_description(_desc[br] + r" branching ratio of $" +
_process_tex + "$")
_obs.tex = r'$' + _tex_br[br] + r"(" + _process_tex + ")$"
_obs.arguments = _args[br]
_obs.add_taxonomy(_process_taxonomy + _process_tex + r'$')
Prediction(_obs_name, _func[br](_hadr[M]['B'], _hadr[M]['V'], l))
# Lepton flavour ratios
for l in [('mu', 'e'), ('tau', 'mu'), ('tau', 'l')]:
for M in _hadr_l.keys():
# binned ratio of BRs
_obs_name = "<R" + l[0] + l[1] + ">(" + M + "lnu)"
_obs = Observable(name=_obs_name, arguments=['q2min', 'q2max'])
_obs.set_description(r"Ratio of partial branching ratios of $" +
_hadr_l[M]['tex'] + _tex[l[0]] + r"^+ \nu_" +
_tex[l[0]] + r"$" + " and " + r"$" +
_hadr_l[M]['tex'] + _tex[l[1]] + r"^+ \nu_" +
_tex[l[1]] + r"$")
_tex = {'emu': r'e^+\mu^-', 'mue': r'\mu^+e^-',
'taue': r'\tau^+e^-', 'etau': r'e^+\tau^-',
'taumu': r'\tau^+\mu^-', 'mutau': r'\mu^+\tau^-'}
_tex_lsum = {'emu': r'e^\pm\mu^\mp', 'etau': r'e^\pm\tau^\mp', 'mutau': r'\mu^\pm\tau^\mp'}
_func = {'BR': BR_tot_function, }
_desc = { 'BR': 'Total', }
_tex_br = {'BR': r'\text{BR}', }
_args = {'BR': None, }
_hadr = {
'B0->K*': {'tex': r"\bar B^0\to \bar K^{*0}", 'B': 'B0', 'V': 'K*0', },
'B+->K*': {'tex': r"B^-\to K^{*-}", 'B': 'B+', 'V': 'K*+', },
'B+->rho': {'tex': r"B^-\to \rho^{-}", 'B': 'B+', 'V': 'rho+', },
'B0->rho': {'tex': r"\bar B^0\to \rho^{0}", 'B': 'B0', 'V': 'rho0', },
'Bs->phi': {'tex': r"\bar B_s\to \phi", 'B': 'Bs', 'V': 'phi', },
}
for ll in [('e','mu'), ('mu','e'), ('e','tau'), ('tau','e'), ('mu','tau'), ('tau','mu')]:
for M in _hadr.keys():
_process_tex = _hadr[M]['tex']+' '+_tex[''.join(ll)]
_process_taxonomy = r'Process :: $b$ hadron decays :: FCNC decays :: $B\to V\ell^+\ell^-$ :: $' + _process_tex + r"$"
for br in ['BR',]:
_obs_name = br + "("+M+''.join(ll)+")"
_obs = Observable(_obs_name)
_obs.set_description(_desc[br] + r" branching ratio of $"+_process_tex+r"$")
_obs.tex = r'$' + _tex_br[br] + "(" + _process_tex+r")$"
_obs.arguments = _args[br]
_obs.add_taxonomy(_process_taxonomy)
Prediction(_obs_name, _func[br](_hadr[M]['B'], _hadr[M]['V'], ll[0], ll[1]))
