semvec/pypi-packages huggingface dataset:
shml 0.1
lightweight pdata cleaning/processing/plotting/ML training library for use with an ATLAS BSM dihiggs search
License: BSD-3-Clause
Requires Python: >=3.7



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# `shml`: routines to automate machine learning experiments for a X -> SH -> bbyy search

This module aims to provide a set of functions that, when composed, can run a pipeline capable of:
- going from `.root` files to `parquet` files via `uproot` and `awkward`
- constructing useful kinematic quantites for training
- applying a chosen or manual preselection
- configuring any additional processing, e.g. weight normalization, feature scaling
- access event data that's prepared for `pytorch` using `shml.torch_dataset.EventDataset`

still to do:
- infra to run ml experiments in a GPU or CPU environment via `pytorch-lightining`

## Usage
To see currently usable implemented functionality, check the [`examples`](examples) folder.

## Install
For preprocessing only:
```
python3 -m pip install shml
```
For ML extras (`pytorch`, plotting):
```
python3 -m pip install shml[ml]
```
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