diff options
Diffstat (limited to 'fig2.py')
| -rwxr-xr-x | fig2.py | 35 |
1 files changed, 5 insertions, 30 deletions
@@ -99,41 +99,16 @@ def main(): n_params = len(paramset) print n_params - # Data - data_path = '{0}/{1}/real'.format( - args.contour_dir, str_enum(args.likelihood).lower() - ) - prefix = '{0}/_{1}_REAL_mn_'.format(data_path, str_enum(args.likelihood)) - analyser = Analyzer( - outputfiles_basename=prefix, n_params=n_params - ) - print analyser - - pranges = paramset.ranges - - bf = analyser.get_best_fit()['parameters'] - for i in xrange(len(bf)): - bf[i] = (pranges[i][1]-pranges[i][0])*bf[i] + pranges[i][0] - print 'bestfit = ', bf - print 'bestfit log_likelihood', analyser.get_best_fit()['log_likelihood'] - - print - print '{0:50} = {1}'.format('global evidence', analyser.get_stats()['global evidence']) - print - - chains = analyser.get_data()[:,2:] - for x in chains: - for i in xrange(len(x)): - x[i] = (pranges[i][1]-pranges[i][0])*x[i] + pranges[i][0] - - llh = -0.5 * analyser.get_data()[:,1] + chains = np.load('/data/user/smandalia/flavour_ratio/data/contour_emcee/golemfit/real/_GOLEMFIT_REAL_emcee_.npy') + # chains = np.load('/data/user/smandalia/flavour_ratio/data/contour_emcee/golemfit/real/more_sys_flat/_GOLEMFIT_REAL_emcee_.npy') + print chains flavour_angles = chains[:,-2:] flavour_ratios = np.array( map(fr_utils.angles_to_fr, flavour_angles) ) - nbins = 25 + nbins = 15 fig = plt.figure(figsize=(8, 8)) ax = fig.add_subplot(111) @@ -168,7 +143,7 @@ def main(): ax.legend() - fig.savefig('test.png', bbox_inches='tight', dpi=150) + fig.savefig('test_emcee_moresys_flat.png', bbox_inches='tight', dpi=150) print "DONE!" |