Looking ahead to generating a large MC set that includes both ppim and sl_mu events in roughly physical proportion. Here are some thoughts:
0. This will likely have to be done at the raw generator level. Should see if it will be easy to add mixing... suspect yes, but might take some reworking of the generator and some vetting of the re-toolchain.
1. One could simply make proportional mixture of signal and background at the post-reconstruction stage, but this would assume that detector and reconstruction acceptance is the same for signal and background, which might not be true. Similarly, weighting events post-recon would produce similar results.
2. Need to include which decay mechanism (truth) each event is in the data stream. This can be done with the "mech" tag in the hddm format. Need to add to the raw files, and to the post-recon code.
3. Additionally, we want this mixed data set to be events that the signal-separation models were NOT trained on. Right now, it looks like the models are over-training (more below), so this will be a problem.
A note on model training. With the increased number of input features (many of which are technically redundant) overtraining seems to be more prevalent. This is probably because the drop-out rate (previously 0.1) is no longer as effective at regularization because there are redundant features (for example, I'm now supplying cylindrical coord components for p4's and x4's in addition to the cartesian components). Will have to try increasing the dropout rate!
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