Next step is to write code that takes the flat trees output by the protonTRUTH DSelector and produces features files. Should give features that I didn't include in previous features files some type of tag that allows them to be removed from the dataframes prior to fitting.
Make sure to OBEY THE SAME FEATURE NAMES from previous scheme. Otherwise will have to change lots of NN code downstream.
A thing to worry about: these flat trees have no incorrect permutation events. Because proton/K+ separation is not good above a certain track momentum, this is unlikely to be true of actual data for which we can't cut on particle TRUTH id. Need to keep this in mind. Perhaps another NN that handles positive-track p/K+ id?
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