The Filter-Value analysis package

Caleb Fangmeier 7166060f01 begins re-implementing old ipynb analysis/plots using new framework		8 yıl önce
README.md	c778e95685 Introduces the filval analysis fromwork wip	8 yıl önce
argparse.hpp	d050852cda Adds ability to save fv::root containers to root files.	8 yıl önce
container.hpp	c79b608374 Adds histogram containers to be filled with arrays, rather than singular	8 yıl önce
dataset.hpp	7166060f01 begins re-implementing old ipynb analysis/plots using new framework	8 yıl önce
filter.hpp	cbfd3422eb Adds Mean and Range Reduce classes. Integrates Function type into	8 yıl önce
filval.hpp	6cc0f0d55e Changes to CMake build system and adds additional logging functionality	8 yıl önce
log.hpp	d050852cda Adds ability to save fv::root containers to root files.	8 yıl önce
value.hpp	7166060f01 begins re-implementing old ipynb analysis/plots using new framework	8 yıl önce

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

README.md

A FILter-VALue System