diff options
| -rwxr-xr-x | utils/chi2 | 12 |
1 files changed, 8 insertions, 4 deletions
@@ -112,7 +112,7 @@ def get_mc_hists_fast(ke_dict,x,bins,apply_norm=False): mc_hists = {} # FIXME: May need to increase number of bins here - bins2 = np.logspace(np.log10(20),np.log10(10e3),1000) + bins2 = np.logspace(np.log10(20),np.log10(10e3),100) bincenters2 = (bins2[1:] + bins2[:-1])/2 for id in (20,22,2020,2022,2222): @@ -236,7 +236,7 @@ def make_nll(data, muons, mc, bins): return nll return nll -def get_mc_hists_posterior(data,muon_hists,data_hists,x,bins): +def get_mc_hists_posterior(ke_dict,muon_hists,data_hists,x,bins): """ Returns the posterior on the Monte Carlo histograms. @@ -260,7 +260,7 @@ def get_mc_hists_posterior(data,muon_hists,data_hists,x,bins): Returns a dictionary mapping particle id combo -> histogram. """ - mc_hists = get_mc_hists(data,x,bins) + mc_hists = get_mc_hists_fast(ke_dict,x,bins) for id in (20,22,2020,2022,2222): mc_hists[id] = get_mc_hist_posterior(mc_hists[id],data_hists[id],norm=x[0]) # FIXME: does the orering of when we add the muons matter here? @@ -290,10 +290,14 @@ def get_multinomial_prob(data, data_muon, data_mc, id, x_samples, bins, percenti data_hists = get_data_hists(data,bins) muon_hists = get_data_hists(data_muon,bins) + ke_dict = {} + for id in (20,22,2020,2022,2222): + ke_dict[id] = data_mc[data_mc.id == id].ke.values + ps = [] for i in range(size): x = x_samples[np.random.randint(x_samples.shape[0])] - mc = get_mc_hists_posterior(data_mc,muon_hists,data_hists,x,bins)[id] + mc = get_mc_hists_posterior(ke_dict,muon_hists,data_hists,x,bins)[id] N = mc.sum() # Fix a bug in scipy(). See https://github.com/scipy/scipy/issues/8235 (I think). mc = mc + 1e-10 |