correctionlib


Namecorrectionlib JSON
Version 2.5.0 PyPI version JSON
download
home_pagehttps://github.com/cms-nanoAOD/correctionlib
SummaryA generic correction library
upload_time2024-02-02 21:23:31
maintainerNick Smith
docs_urlNone
authorNick Smith
requires_python>=3.7
licenseBSD 3-Clause License
keywords
VCS
bugtrack_url
requirements No requirements were recorded.
Travis-CI No Travis.
coveralls test coverage No coveralls.
            # correctionlib

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[![Documentation Status][rtd-badge]][rtd-link]
[![Code style: black][black-badge]][black-link]

[![conda version][conda-badge]][conda-link]
[![PyPI version][pypi-version]][pypi-link]
[![PyPI platforms][pypi-platforms]][pypi-link]

[![GitHub Discussion][github-discussions-badge]][github-discussions-link]

## Introduction
The purpose of this library is to provide a well-structured JSON data format for a
wide variety of ad-hoc correction factors encountered in a typical HEP analysis and
a companion evaluation tool suitable for use in C++ and python programs.
Here we restrict our definition of correction factors to a class of functions with
scalar inputs that produce a scalar output.

In python, the function signature is:

```python
def f(*args: str | int | float) -> float:
    return ...
```

In C++, the evaluator implements this currently as:
```cpp
double Correction::evaluate(const std::vector<std::variant<int, double, std::string>>& values) const;
```

The supported function classes include:

  * multi-dimensional binned lookups;
  * binned lookups pointing to multi-argument formulas with a restricted
    math function set (`exp`, `sqrt`, etc.);
  * categorical (string or integer enumeration) maps;
  * input transforms (updating one input value in place); and
  * compositions of the above.

Each function type is represented by a "node" in a call graph and holds all
of its parameters in a JSON structure, described by the JSON schema.
Possible future extension nodes might include weigted sums (which, when composed with
the others, could represent a BDT) and perhaps simple MLPs.

The tool should provide:

  * standardized, versioned [JSON schemas](https://json-schema.org/);
  * forward-porting tools (to migrate data written in older schema versions); and
  * a well-optimized C++ evaluator and python bindings (with numpy vectorization support).

This tool will definitely not provide:

  * support for `TLorentzVector` or other object-type inputs (such tools should be written
    as a higher-level tool depending on this library as a low-level tool)

Formula support currently includes a mostly-complete subset of the ROOT library `TFormula` class,
and is implemented in a threadsafe standalone manner. The parsing grammar is formally defined
and parsed through the use of a header-only [PEG parser library](https://github.com/yhirose/cpp-peglib).
The supported features mirror CMSSW's [reco::formulaEvaluator](https://github.com/cms-sw/cmssw/pull/11516)
and fully passes the test suite for that utility with the purposeful exception of the `TMath::` namespace.
The python bindings may be able to call into [numexpr](https://numexpr.readthedocs.io/en/latest/user_guide.html),
though, due to the tree-like structure of the corrections, it may prove difficult to exploit vectorization
at levels other than the entrypoint.

Detailed instructions for installing and using this package are provided in the [documentation][rtd-link].

## Creating new corrections

A demo/tutorial of the features is available in the [documentation][rtd-link] and also available interactively
on [binder](https://mybinder.org/v2/gh/cms-nanoAOD/correctionlib/HEAD?labpath=binder%2Fcorrectionlib_tutorial.ipynb)

The `correctionlib.schemav2` module provides a helpful framework for defining correction objects
and `correctionlib.convert` includes select conversion routines for common types. Nodes can be type-checked as they are
constructed using the [parse_obj](https://pydantic-docs.helpmanual.io/usage/models/#helper-functions)
class method or by directly constructing them using keyword arguments.

## Developing
See CONTRIBUTING.md

[actions-badge]:            https://github.com/cms-nanoAOD/correctionlib/workflows/CI/badge.svg
[actions-link]:             https://github.com/cms-nanoAOD/correctionlib/actions
[black-badge]:              https://img.shields.io/badge/code%20style-black-000000.svg
[black-link]:               https://github.com/psf/black
[conda-badge]:              https://img.shields.io/conda/vn/conda-forge/correctionlib.svg
[conda-link]:               https://github.com/conda-forge/correctionlib-feedstock
[github-discussions-badge]: https://img.shields.io/static/v1?label=Discussions&message=Ask&color=blue&logo=github
[github-discussions-link]:  https://github.com/cms-nanoAOD/correctionlib/discussions
[gitter-badge]:             https://badges.gitter.im/https://github.com/cms-nanoAOD/correctionlib/community.svg
[gitter-link]:              https://gitter.im/https://github.com/cms-nanoAOD/correctionlib/community?utm_source=badge&utm_medium=badge&utm_campaign=pr-badge
[pypi-link]:                https://pypi.org/project/correctionlib/
[pypi-platforms]:           https://img.shields.io/pypi/pyversions/correctionlib
[pypi-version]:             https://badge.fury.io/py/correctionlib.svg
[rtd-badge]:                https://github.com/cms-nanoAOD/correctionlib/actions/workflows/docs.yml/badge.svg
[rtd-link]:                 https://cms-nanoAOD.github.io/correctionlib/

            

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