Ideas for benchmarks from Gordon

[masonproffitt]

Suggestions from one of Gordon's emails:

• Focus: Demonstrating Language Ability:
  1. Plotting the Jet pT for jets that have an jet pT > 20 GeV and abs(jet eta) < 1.0
  2. Plotting the Missing ET for jets with at least 2 jets with Jet pT > 40 and abs(jet Eta) < 1.0
  3. Plot the opposite-sign muon pair mass for all combinations of muons
  4. Create a group of plots (jet pT, eta, phi, N_jets). Now make it for all events, for events with missing et > 20 GeV, and for events with missing et > 20 GeV and 2 jets with 40 GeV and abs(eta) < 1.0. Demonstrate making "groups" of plots, and a graphical cut flow
  5. Create a new ntuple/TTree/numpy/awkward array (whatever!) that contains one jet per row with (jet pT, jet eta, run number, event number).
  6. Create a new ntuple/TTree/numpy/awkward array (whatever!) that contains one event per row with (jet pT's jet eta's, run number, event number) for jets with pt > 40 and abs(eta) < 1.0
• Focus: Benchmark:
  • Make ~100 plots, running over ~50 files (e.g. use all cores).
  • Make ~100 plots, running over 1 very large file (e.g. use all cores).
• Focus: Getting To Physics Fast:
  • With code that makes 200 plots, how hard is it to add one more? How is the performance of making the N+1 plot vs making just the 1 plot?
  • How amenable to using Jupyter notebooks for exploration and tutorials? Show a few of the samples from Demonstrating Language Ability in a notebook.
• Other (super advanced, but we'll have to get there eventually):
  • A Z peak analysis with systematics

Note that (i) just adds a pt requirement on the current third benchmark, (ii) just adds an eta requirement on the current fourth benchmark, and (iii) is an intermediate step for the current fifth benchmark.