A package for analysis of rare particle decays with machine-learning algorithms
This package consists of several tools for the event selection of particle decays, mostly built on machine learning techniques. It contains:
- a data-container holding data, weights, labels and more and implemented root-to-python data conversion as well as plots and KFold-data splitting
- reweighting tools from the hep_ml-repository wrapped in a KFolding structure and with metrics to evaluate the reweighting quality
- classifier optimization tools for hyper-parameters as well as feature selection involving a backward-elimination
- an output handler which makes it easy to add text as well as figures into your code and automatically save them to a file
- … and more
Want to test whether your reweighting did overfit? Use train_similar:
import raredecay as rd mc_data = rd.data.HEPDataStorage(df, weights=*pd.Series weights*, target=0) real_data = rd.data.HEPDataStorage(df, weights=*pd.Series weights*, target=1) score = rd.score.train_similar(mc_data, real_data, old_mc_weights=1 *or whatever weights the mc had before*)
Getting started right now
If you want it the easy, fast way, have a look at the Ready-to-use scripts. All you need to do is to have a look at every “TODO” task and probably change them. Then you can run the script without the need of coding at all.
Documentation and API
The API as well as the documentation: Documentation
Setup and installation
Easiest way: use conda to install everything (except of the rep, which has to be upgraded with pip for some functionalities)
conda install raredecay -c mayou36
The package with all extras requires root_numpy as well as rootpy (and therefore a ROOT installation with python-bindings) to be installed on your system. If that is not the case, some functions won’t work.
If you want to install all the extra, first install the very newest version of REP (may also needed with conda install) (the -U can be omitted, but is recommended to have the newest dependencies):
pip install -U https://github.com/yandex/rep/archive/stratifiedkfold.zip
Then, install the raredecay package (without ROOT-support) via
pip install raredecay
To make sure you can convert ROOT-NTuples, use
pip install raredecay[root] # *use raredecay\[root\] in a zsh-console*
or, instead of root/additionally (comma separated) reweight or reweight for the specific functionalities.
In order to have all functionalities, use
pip install raredecay[all]
As it is a young package still under developement, it may receive regular updates and improvements and it is probably a good idea to regularly download the newest package.
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
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|–||Source||Nov 5, 2017|