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| author | tlatorre <tlatorre@uchicago.edu> | 2020-12-09 08:13:22 -0600 |
|---|---|---|
| committer | tlatorre <tlatorre@uchicago.edu> | 2020-12-09 08:13:22 -0600 |
| commit | 7b0afb866daeeaeced1bdd624db2e2dfb09232d4 (patch) | |
| tree | 144883ae117f328be183654e83e88c869160177d | |
| parent | 256ed092dc42d34e03cbd43f39c98e27680aec7a (diff) | |
| download | sddm-7b0afb866daeeaeced1bdd624db2e2dfb09232d4.tar.gz sddm-7b0afb866daeeaeced1bdd624db2e2dfb09232d4.tar.bz2 sddm-7b0afb866daeeaeced1bdd624db2e2dfb09232d4.zip | |
don't delete mc data from runs not in data when running chi2 --coverage
| -rwxr-xr-x | utils/chi2 | 16 | ||||
| -rwxr-xr-x | utils/dm-search | 19 |
2 files changed, 14 insertions, 21 deletions
@@ -560,18 +560,9 @@ if __name__ == '__main__': #muon = ev[ev.muon & ev.prompt & ~ev.atm] #muon_atm = ev[ev.muon & ev.prompt & ev.atm] - if (~rhdr.run.isin(ev_mc.run)).any(): - print_warning("Error! The following runs have no Monte Carlo: %s" % \ - rhdr.run[~rhdr.run.isin(ev_mc.run)].values) - sys.exit(1) - - ev_mc = ev_mc[ev_mc.run.isin(rhdr.run)] - data_mc = ev_mc[ev_mc.signal & ev_mc.prompt & ~ev_mc.atm] data_atm_mc = ev_mc[ev_mc.signal & ev_mc.prompt & ev_mc.atm] - data_mc = ev_mc[ev_mc.signal & ev_mc.prompt & ~ev_mc.atm] - bins = np.logspace(np.log10(20),np.log10(10e3),21) atmo_scale_factor = 100.0 @@ -751,6 +742,13 @@ if __name__ == '__main__': sys.exit(0) + if (~rhdr.run.isin(ev_mc.run)).any(): + print_warning("Error! The following runs have no Monte Carlo: %s" % \ + rhdr.run[~rhdr.run.isin(ev_mc.run)].values) + sys.exit(1) + + data_mc = data_mc[data_mc.run.isin(rhdr.run)] + xopt, universe, samples = do_fit(data,muon,data_mc,weights,atmo_scale_factor,muon_scale_factor,bins,args.steps,args.print_nll,args.walkers,args.thin) data_mc_with_weights = pd.merge(data_mc,weights[weights.universe == universe],how='left',on=['run','evn']) diff --git a/utils/dm-search b/utils/dm-search index 45c60c7..cbc4f8c 100755 --- a/utils/dm-search +++ b/utils/dm-search @@ -57,9 +57,6 @@ DM_MASSES = {2020: np.logspace(np.log10(22),np.log10(10e3 - 500),101), DISCOVERY_P_VALUE = 0.05 -# Energy resolution as a fraction of energy for dark matter signal -DM_ENERGY_RESOLUTION = 0.1 - FIT_PARS = [ 'Atmospheric Neutrino Flux Scale', 'Electron energy bias', @@ -634,18 +631,9 @@ if __name__ == '__main__': #muon = ev[ev.muon & ev.prompt & ~ev.atm] #muon_atm = ev[ev.muon & ev.prompt & ev.atm] - if (~rhdr.run.isin(ev_mc.run)).any(): - print_warning("Error! The following runs have no Monte Carlo: %s" % \ - rhdr.run[~rhdr.run.isin(ev_mc.run)].values) - sys.exit(1) - - ev_mc = ev_mc[ev_mc.run.isin(rhdr.run)] - data_mc = ev_mc[ev_mc.signal & ev_mc.prompt & ~ev_mc.atm] data_atm_mc = ev_mc[ev_mc.signal & ev_mc.prompt & ev_mc.atm] - data_mc = ev_mc[ev_mc.signal & ev_mc.prompt & ~ev_mc.atm] - bins = np.logspace(np.log10(20),np.log10(10e3),21) atmo_scale_factor = 100.0 @@ -778,6 +766,13 @@ if __name__ == '__main__': sys.exit(0) + if (~rhdr.run.isin(ev_mc.run)).any(): + print_warning("Error! The following runs have no Monte Carlo: %s" % \ + rhdr.run[~rhdr.run.isin(ev_mc.run)].values) + sys.exit(1) + + data_mc = data_mc[data_mc.run.isin(rhdr.run)] + limits, best_fit, discovery_array = get_limits(DM_MASSES,data,muon,data_mc,atmo_scale_factor,muon_scale_factor,bins,args.steps,args.print_nll,args.walkers,args.thin) fig = plt.figure() |