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kdlong
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Apr 18, 2024
| axis_ewPtll = hist.axis.Variable(common.ptV_binning, underflow=False, name = "ewPTll") | ||
| axis_ewAbsYll = hist.axis.Regular(50, 0, 5, name = "ewAbsYll") | ||
| df = theory_tools.define_dressed_vars(df, mode="wmass" if isW else "dilepton") | ||
| df = theory_tools.define_dressed_vars(df, mode="wmass" if isW else "wlike") |
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Most of the time when people run the gen histmaker I would expect them to want dilepton observables.
kdlong
reviewed
Apr 18, 2024
| axis_eta = hist.axis.Regular(25, 0, 2.5, name = "postfsrLep_absEta", overflow=True, underflow=False) | ||
| axis_pt = hist.axis.Regular(50, 20, 70, name = "postfsrLep_pt", overflow=True, underflow=True) | ||
| results.append(df_fiducial.HistoBoost("nominal_postfsr", [axis_eta, axis_pt], ["postfsrLep_absEta", "postfsrLep_pt", "nominal_weight"], storage=hist.storage.Weight())) | ||
| if args.applySelection: |
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I think it's probably easier to just set the lepton type in the gen script and then make one or the other.
kdlong
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Jul 4, 2025
add flag for physics model of the fitresult used as input
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