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@@ -134,9 +134,9 @@ def plot_event_obs(rss, dataset):
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@decl_plot
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-def plot_fake_taus(rss):
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+def plot_tau_purity(rss):
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_, ((ax_ft, ax_ttw), (ax_ttz, ax_tth)) = plt.subplots(2, 2)
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- ft, ttw, ttz, tth = list(map(lambda rs: hist(rs.tau_fakes_v_pt), rss))
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+ ft, ttw, ttz, tth = list(map(lambda rs: hist(rs.tau_purity_v_pt), rss))
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def _plot(ax, dataset):
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plt.sca(ax)
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@@ -145,6 +145,8 @@ def plot_fake_taus(rss):
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'TTZ': ttz,
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'TTH': tth}[dataset]
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hist_plot(h, stats=False, label=dataset)
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+ plt.text(200, 0.05, dataset)
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+ plt.xlabel(r"$P_T$(GeV)")
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_plot(ax_ft, 'TTTT')
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_plot(ax_ttw, 'TTW')
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@@ -185,7 +187,7 @@ if __name__ == '__main__':
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ttz_event_obs = (plot_event_obs, (rss, 'TTZ'), {})
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tth_event_obs = (plot_event_obs, (rss, 'TTH'), {})
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- fake_taus = (plot_fake_taus, (rss,), {})
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+ tau_purity = (plot_tau_purity, (rss,), {})
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# Now assemble the plots into figures.
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plots = [
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@@ -219,8 +221,8 @@ if __name__ == '__main__':
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'TTZ - Event Observables'),
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Plot([[tth_event_obs]],
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'TTH - Event Observables'),
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- Plot([[fake_taus]],
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- 'Hadronic Tau fake-rate'),
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+ Plot([[tau_purity]],
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+ 'Tau Purity'),
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]
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# Finally, render and save the plots and generate the html+bootstrap
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