diff options
Diffstat (limited to 'utils')
| -rw-r--r-- | utils/fr.py | 14 | ||||
| -rw-r--r-- | utils/gf.py | 3 | ||||
| -rw-r--r-- | utils/likelihood.py | 9 | ||||
| -rw-r--r-- | utils/plot.py | 11 |
4 files changed, 25 insertions, 12 deletions
diff --git a/utils/fr.py b/utils/fr.py index 81ba3b2..80a26e1 100644 --- a/utils/fr.py +++ b/utils/fr.py @@ -248,10 +248,12 @@ def estimate_scale(args): """Estimate the scale at which new physics will enter.""" try: m_eign = args.m3x_2 except: m_eign = MASS_EIGENVALUES[1] - if args.scale is not None: - scale = args.scale - scale_region = (scale/args.scale_region, scale*args.scale_region) - elif args.energy_dependance is EnergyDependance.MONO: + if hasattr(args, 'scale'): + if args.scale != 0: + scale = args.scale + scale_region = (scale/args.scale_region, scale*args.scale_region) + return scale, scale_region + if args.energy_dependance is EnergyDependance.MONO: scale = np.power( 10, np.round(np.log10(m_eign/args.energy)) - \ np.log10(args.energy**(args.dimension-3)) @@ -319,7 +321,7 @@ def fr_argparse(parser): help='Fix the new physics scale' ) parser.add_argument( - '--scale', type=float, default=None, + '--scale', type=float, default=0, help='Set the new physics scale' ) parser.add_argument( @@ -418,7 +420,7 @@ def params_to_BSMu(theta, dim, energy, mass_eigenvalues=MASS_EIGENVALUES, '--fix-mixing and --fix-mixing-almost cannot be used together' ) - if not isinstance(theta, list): + if not isinstance(theta, (list, tuple)): theta = [theta] if fix_mixing is MixingScenario.T12: diff --git a/utils/gf.py b/utils/gf.py index ddf3fdd..6ce7863 100644 --- a/utils/gf.py +++ b/utils/gf.py @@ -69,7 +69,8 @@ def steering_params(args): # For Tianlu # params.years = [999] - params.minFitEnergy = args.binning[0] # GeV + params.minFitEnergy = args.binning[0] # GeV + params.maxFitEnergy = args.binning[-1] # GeV params.load_data_from_text_file = False return params diff --git a/utils/likelihood.py b/utils/likelihood.py index 93f3aea..7079d52 100644 --- a/utils/likelihood.py +++ b/utils/likelihood.py @@ -72,6 +72,8 @@ def lnprior(theta, paramset): prior += Gaussian().logpdf( param.nominal_value, param.value, param.std ) + print 'prioring param', param.name, '=', param.value + print 'prior', prior elif param.prior is PriorsCateg.HALFGAUSS: prior += Gaussian().logpdf( param.nominal_value, param.value, param.std @@ -177,7 +179,8 @@ def triangle_llh(theta, args, asimov_paramset, llh_paramset, fitter): n = gen_identifier(args) + '.txt' with open(args.output_measured_fr + n, 'a') as f: f.write(r'{0:.3f} {1:.3f} {2:.3f} {3:.1f}'.format( - fr[0], fr[1], fr[2], llh_paramset['logLam'].value + float(fr[0]), float(fr[1]), float(fr[2]), + llh_paramset['logLam'].value )) f.write('\n') @@ -202,6 +205,10 @@ def ln_prob(theta, args, asimov_paramset, llh_paramset, fitter): lp = lnprior(theta, paramset=llh_paramset) if not np.isfinite(lp): return -np.inf + llh = triangle_llh( + theta, args=args, asimov_paramset=asimov_paramset, + llh_paramset=llh_paramset, fitter=fitter + ) return lp + triangle_llh( theta, args=args, asimov_paramset=asimov_paramset, llh_paramset=llh_paramset, fitter=fitter diff --git a/utils/plot.py b/utils/plot.py index a73235b..53a4a84 100644 --- a/utils/plot.py +++ b/utils/plot.py @@ -196,10 +196,10 @@ def chainer_plot(infile, outfile, outformat, args, llh_paramset): # ) if args.data is DataType.REAL: - fig.text(0.8, 0.7, 'IceCube Preliminary', color='red', fontsize=15, + plt.text(0.8, 0.7, 'IceCube Preliminary', color='red', fontsize=15, ha='center', va='center') elif args.data in [DataType.ASIMOV, DataType.REALISATION]: - fig.text(0.8, 0.7, 'IceCube Simulation', color='red', fontsize=15, + plt.text(0.8, 0.7, 'IceCube Simulation', color='red', fontsize=15, ha='center', va='center') for of in outformat: @@ -247,14 +247,15 @@ def chainer_plot(infile, outfile, outformat, args, llh_paramset): g = plot_Tchain(Tchain, trns_axes_labels, trns_ranges) if args.data is DataType.REAL: - fig.text(0.8, 0.7, 'IceCube Preliminary', color='red', fontsize=15, + plt.text(0.8, 0.7, 'IceCube Preliminary', color='red', fontsize=15, ha='center', va='center') elif args.data in [DataType.ASIMOV, DataType.REALISATION]: - fig.text(0.8, 0.7, 'IceCube Simulation', color='red', fontsize=15, + plt.text(0.8, 0.7, 'IceCube Simulation', color='red', fontsize=15, ha='center', va='center') mpl.pyplot.figtext(0.5, 0.7, fig_text, fontsize=15) for of in outformat: + print 'Saving', outfile+'_elements'+of g.export(outfile+'_elements.'+of) @@ -281,6 +282,8 @@ def plot_statistic(data, outfile, outformat, args, scale_param, label=None): min_idx = np.argmin(scales) null = statistic[min_idx] + fig_text += '\nnull lnZ = {0:.2f}'.format(null) + if args.stat_method is StatCateg.BAYESIAN: reduced_ev = -(statistic - null) elif args.stat_method is StatCateg.FREQUENTIST: |