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**4)** Assuming the evaluation sample vertex category weights have been produced (look at procedures for Evaluation Samples), add the normalization and category weight branches to the flat ntuples with **addWeightBranch.py**. The combination of these weights will remove the training sample vertex category information and match it with that of the evaluation sample. | **4)** Assuming the evaluation sample vertex category weights have been produced (look at procedures for Evaluation Samples), add the normalization and category weight branches to the flat ntuples with **addWeightBranch.py**. The combination of these weights will remove the training sample vertex category information and match it with that of the evaluation sample. | ||
- | **5)** Create 2D Pt/Eta Histograms for the weighted ntuples with **createEtaPtWeightHists.py** (make sure " | + | **5)** Create 2D Pt/Eta Histograms for the weighted ntuples with **createEtaPtWeightHists.py** (make sure " |
+ | |||
+ | **6)** Make the final weighted ntuples making sure that the new Pt/Eta histogram files are pointed to in **addWeightBranch.py**. There should be six new branches created: | ||
+ | -**weight_etaPt** | ||
+ | -**weight_etaPtInc**: | ||
+ | -**weight_category**: | ||
+ | -**weight_norm** | ||
+ | -**weight_flavour** : the ratio of the flavour prevalences in the evaluation process\\ | ||
+ | -**weight** | ||