The Filter-Value analysis package

Caleb Fangmeier 8be6413ed7 Adds documentation deployment make target, additional values relating to 7 gadi atpakaļ
examples 9a4380809f Adds example code for filval and the beginnings of TMVA integration in filval_root 7 gadi atpakaļ
README.md c778e95685 Introduces the filval analysis fromwork wip 8 gadi atpakaļ
api.hpp 8be6413ed7 Adds documentation deployment make target, additional values relating to 7 gadi atpakaļ
argparse.hpp d050852cda Adds ability to save fv::root containers to root files. 7 gadi atpakaļ
container.hpp 4850bd64ac Adds calculation of Top(Tri-jet) invarient mass 7 gadi atpakaļ
dataset.hpp 4427df6a66 Finishes implementing TMVA integration 7 gadi atpakaļ
filter.hpp ba6411da77 Adds basic event selection 7 gadi atpakaļ
filval.hpp 7cee2c915b changes MapOver to no longer require template arguments to be wrapped in tuple 7 gadi atpakaļ
log.hpp d050852cda Adds ability to save fv::root containers to root files. 7 gadi atpakaļ
value.hpp 8be6413ed7 Adds documentation deployment make target, additional values relating to 7 gadi atpakaļ

README.md

A FILter-VALue System

This is a header-only, generic, data analysis system that allows for creating performant generation of Plots. Plots contain Values and can make use of Filters. Filters can also depend of Values, and Values can depend on other Values. A Dataset is a generic object that contains a series of observations. The individual observations consist of a series of Observed Values. One can also define Derived Values which are calculated from Observed Values or other Derived Values. Care is taken automatically so Derived Values are calculated at most once per observation.

MyDataSet myDataSet("somefile.root", "tree"); // MyDataSet subclasses DataSet
TTreeValue<int> countmyDataSet;
myDataSet.addValue

Hist1D myplot(count, myDataSet, ); // Hist1D subclasses Plot