Generic system to perform streaming transformations on histograms

Features:

• core does not depend on any histogram library or input/output format; plugins can be written (and these need not live in this package). Probably most useful if histograms live in a hierarchical namespace but this is not necessary. Example implementation to read/write ROOT files provided.
• intended for streaming, e.g. for online environments where histograms are updated asynchronously.
• pattern matching makes it easy to apply the same transformation to multiple histograms
• no code needed to configure

This is still very much early-release software, you can test it as follows (e.g. should work on lxplus, if you have a CERN account):

• set up ROOT and Python (>=3.7) in a way that you like. For ATLAS people you can set up a master nightly. (The code may run on Python 3.6 but we no longer test it there.)
• install (not needed if you are on ATLAS and using master,2020-10-20T2101 or later): python3 -m pip install -U --user histgrinder==0.1.6
• prepare a sample ROOT file: python3 -m histgrinder.make_sample_file
• download an example YAML configuration from https://raw.githubusercontent.com/ponyisi/histogram_postprocessing/master/resources/example.yaml
• run. The following will postprocess example.root, created above, according to the example.yaml configuration, ignoring the top-level path "prefix", then add the outputs to example.root:

python3 -m histgrinder.engine example.root example.root -c example.yaml --prefix prefix

• the transformation above will perform a number of operations on the histograms of the input file. For example, 20 different histogram divisions are configured with the first config block.

Command line arguments:

This work was supported by the US Department of Energy, Office of Science, Office of High Energy Physics, under Award Number DE-SC0007890.