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Changes for new trained regression for UL 2016 - 110X #28466
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The code-checks are being triggered in jenkins. |
+code-checks Logs: https://cmssdt.cern.ch/SDT/code-checks/cms-sw-PR-28466/12902
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A new Pull Request was created by @jainshilpi for master. It involves the following packages: Configuration/Eras @perrotta, @kpedro88, @cmsbuild, @franzoni, @slava77, @fabiocos, @davidlange6 can you please review it and eventually sign? Thanks. cms-bot commands are listed here |
@cmsbuild please test |
The tests are being triggered in jenkins. |
Comparison job queued. |
recHitsEBLabel = "reducedEcalRecHitsEB", | ||
recHitsEELabel = "reducedEcalRecHitsEE" | ||
particleFlowClusterOOTECAL, | ||
energyCorrector = dict(applyMVACorrections = True, maxPtForMVAEvaluation = 90., srfAwareCorrection = False, recHitsEBLabel = "reducedEcalRecHitsEB", recHitsEELabel = "reducedEcalRecHitsEE") |
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please add linebreak for readability to keep the length within/below 100 chars.
Also, It looks like applyMVACorrections = True
is redundant
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Hi Slava, yes that is right - removed applyMVACorrections = True.
Comparison is ready Comparison Summary:
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@cmsbuild please test |
The tests are being triggered in jenkins. |
Comparison job queued. |
Comparison is ready Comparison Summary:
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+1
Based on the discussion in the Nov 26 ORP, this PR is only introducing the configuration changes. There should be a follow up update to the GT to properly complete the update for the 2016 ecal/egamma regressions. |
+operations the update of Eras and modifier is coherent with the purpose of the PR |
This pull request is fully signed and it will be integrated in one of the next master IBs (tests are also fine). This pull request will now be reviewed by the release team before it's merged. @davidlange6, @slava77, @smuzaffar, @fabiocos (and backports should be raised in the release meeting by the corresponding L2) |
+1 |
This is exactly the same as #28422. A new PR is created instead of continuing from there since the there were problems with the history and hence further merging
These changes are essential for making the 2016 UL regression work. After discussion with Sam, I have made these changes (since 2016 uses the old PF cluster regression strategy and old ele/pho regressions codes).
We had to create Modifier_run2_ECAL_2016_cff.py so that the training strategy of 2017 and 2018 could be used here as well.