Fake factor using ML #34
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… PNet scores using MoE6 model presented in weekly meeting
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hh_bbtatautau.pyto calculate the FF combined weight (ff_comb_weight) using the output from the ONNX model (two files required: ONNX model file and JSON file where feature order is written for robustness). Model file is for the one discussed in my last presentation (MoE6)weight_MLshape_Central(data:ff_comb_weight, for MC:ff_comb_weight * final_weight) along withweight_central.HistProducerFromNTuple.pyto save two hists in OS_Iso, one nominal and one ML weighted OS_AntiIso (e.g., $var$_MLshape_Central) to be used as a template during QCD estimation.HistMergerFromHists.pyproduces two sample-wise merged histograms (nominal and *_ML_shape).QCD_estimation_MLFF.pyuses nominal and _ML_shape for ML, ML+ABCD, and ABCD (based on args in CLI) methods of BG estimation.