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Analysis pipeline to implement Bayesian inference in high-energy physics – using PCA, Gaussian Processes, and MCMC
Integration tests for each of the main module functions? Need to think a bit more, but would be important to add some testing functionality especially for those cases where we call external modules (e.g. sklearn) to do heavy-lifting.
If needed for the future, could use a pandas dataframe to select on data? Or could use a Label
class to identify one set of data, and then a Labels
class to make selections, similar to Axis
vs AxisTuple
? Not pressing at the moment though
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