Developments

• Tested behaviour when setting / removing split flags for all clusters
• Ongoing: PR in O2 for GPU cluster finder
• Unknown status: PR in alidist for ONNX update (?)

Setting the split flags

(Setting the split flags for the NN exactly in the same way as the CF deconvolution kernel does)

• Also percentiles look better when regression model is used, even for 2D regression models (best one is still 3D CNN with (5,11,11) input) 

• The network clearly improves all distributions, but let's make sure that this is not a fluke:

Removing the split flags (for both algorithms)

• The network is clearly better

What happens when many clusters are rejected?

• (Setting the flags again)
• Rejecting about 13.4% of clusters and about 4.5% of tracks
• Keeping CF deconvolution flags for direct comparability

• Most tracks rejected are with NCL < 40 and hence not relevant for physics (typical analysis cut: 60 NCl / track)
• Do we loose any physics-relevant tracks? No -> see plot below

• Still need to understand where we loose some tracks with high NCL (or better: shift them to lower NCL due to "false" cluster rejection)

Update

• Using patch from David to calculate Chi2 without cluster flags (note the different axis scaling. Chi2/NCL is now a lot bigger)

• Network is still better