https://github.com/agoose77/hist

Histogramming for analysis powered by boost-histogram

https://github.com/agoose77/hist

Repository

Histogramming for analysis powered by boost-histogram

https://github.com/agoose77/hist/blob/main/

# Hist

[![Actions Status][actions-badge]][actions-link]
[![Documentation Status][rtd-badge]][rtd-link]
[![pre-commit.ci status][pre-commit-badge]][pre-commit-link]
[![Code style: black][black-badge]][black-link]

[![PyPI version][pypi-version]][pypi-link]
[![Conda-Forge][conda-badge]][conda-link]
[![PyPI platforms][pypi-platforms]][pypi-link]
[![DOI][doi-badge]][doi-link]
[![License][license-badge]][license-link]

[![GitHub Discussion][github-discussions-badge]][github-discussions-link]
[![Gitter][gitter-badge]][gitter-link]
[![Binder][binder-badge]][binder-link]
[![Scikit-HEP][sk-badge]][sk-link]

Hist is an analyst-friendly front-end for
[boost-histogram](https://github.com/scikit-hep/boost-histogram), designed for
Python 3.7+ (3.6 users get version 2.4). See [what's new](https://hist.readthedocs.io/en/latest/changelog.html).

![Slideshow of features. See docs/banner_slides.md for text if the image is not readable.](https://github.com/scikit-hep/hist/raw/main/docs/_images/banner.gif)

## Installation

You can install this library from [PyPI](https://pypi.org/project/hist/) with pip:

```bash
python3 -m pip install "hist[plot]"
```

If you do not need the plotting features, you can skip the `[plot]` extra.

## Features

Hist currently provides everything boost-histogram provides, and the following enhancements:

- Hist augments axes with names:
  - `name=` is a unique label describing each axis.
  - `label=` is an optional string that is used in plotting (defaults to `name`
    if not provided).
  - Indexing, projection, and more support named axes.
  - Experimental `NamedHist` is a `Hist` that disables most forms of positional access, forcing users to use only names.

- The `Hist` class augments `bh.Histogram` with simpler construction:
  - `flow=False` is a fast way to turn off flow for the axes on construction.
  - Storages can be given by string.
  - `storage=` can be omitted, strings and storages can be positional.
  - `data=` can initialize a histogram with existing data.
  - `Hist.from_columns` can be used to initialize with a DataFrame or dict.
  - You can cast back and forth with boost-histogram (or any other extensions).

- Hist support QuickConstruct, an import-free construction system that does not require extra imports:
  - Use `Hist.new.().().()`.
  - Axes names can be full (`Regular`) or short (`Reg`).
  - Histogram arguments (like `data=`) can go in the storage.

- Extended Histogram features:
  - Direct support for `.name` and `.label`, like axes.
  - `.density()` computes the density as an array.
  - `.profile(remove_ax)` can convert a ND COUNT histogram into a (N-1)D MEAN histogram.
  - `.sort(axis)` supports sorting a histogram by a categorical axis. Optionally takes a function to sort by.

- Hist implements UHI+; an extension to the UHI (Unified Histogram Indexing) system designed for import-free interactivity:
  - Uses `j` suffix to switch to data coordinates in access or slices.
  - Uses `j` suffix on slices to rebin.
  - Strings can be used directly to index into string category axes.

- Quick plotting routines encourage exploration:
  - `.plot()` provides 1D and 2D plots (or use `plot1d()`, `plot2d()`)
  - `.plot2d_full()` shows 1D projects around a 2D plot.
  - `.plot_ratio(...)` make a ratio plot between the histogram and another histogram or callable.
  - `.plot_pull(...)` performs a pull plot.
  - `.plot_pie()` makes a pie plot.
  - `.show()` provides a nice str printout using Histoprint.

- Stacks: work with groups of histograms with identical axes
  - Stacks can be created with `h.stack(axis)`, using index or name of an axis (`StrCategory` axes ideal).
  - You can also create with `hist.stacks.Stack(h1, h2, ...)`, or use `from_iter` or `from_dict`.
  - You can index a stack, and set an entry with a matching histogram.
  - Stacks support `.plot()` and `.show()`, with names (plot labels default to original axes info).
  - Stacks pass through `.project`, `*`, `+`, and `-`.

- New modules
  - `intervals` supports frequentist coverage intervals.

- Notebook ready: Hist has gorgeous in-notebook representation.
  - No dependencies required

## Usage

```python
from hist import Hist

# Quick construction, no other imports needed:
h = (
  Hist.new
  .Reg(10, 0 ,1, name="x", label="x-axis")
  .Var(range(10), name="y", label="y-axis")
  .Int64()
)

# Filling by names is allowed:
h.fill(y=[1, 4, 6], x=[3, 5, 2])

# Names can be used to manipulate the histogram:
h.project("x")
h[{"y": 0.5j + 3, "x": 5j}]

# You can access data coordinates or rebin with a `j` suffix:
h[.3j:, ::2j] # x from .3 to the end, y is rebinned by 2

# Elegant plotting functions:
h.plot()
h.plot2d_full()
h.plot_pull(Callable)
```

## Development

From a git checkout, either use [nox](https://nox.thea.codes), or run:

```bash
python -m pip install -e .[dev]
```

See [Contributing](https://hist.readthedocs.io/en/latest/contributing.html) guidelines for information on setting up a development environment.

## Contributors

We would like to acknowledge the contributors that made this project possible ([emoji key](https://allcontributors.org/docs/en/emoji-key)):




  

    

Henry Schreiner
  
    

Nino Lau
  
    

Chris Burr

    

Nick Amin

    

Eduardo Rodrigues

    

Andrzej Novak

    

Matthew Feickert

  
  

    

Kyle Cranmer

    

Daniel Antrim

    

Nicholas Smith

    

Michael Eliachevitch

    

Jonas Eschle

  







This project follows the [all-contributors](https://github.com/all-contributors/all-contributors) specification.

## Talks

- [2021-07-07 PyHEP 2021 -- High-Performance Histogramming for HEP Analysis](https://indico.cern.ch/event/1019958/contributions/4430375/) [](https://youtu.be/jewb5q6_Rpk)
- [2020-09-08 IRIS-HEP/GSOC -- Hist: histogramming for analysis powered by boost-histogram](https://indico.cern.ch/event/950229/#3-hist-histogramming-for-analy) [](https://www.youtube.com/watch?v=hIiEu7XFu5Y)
- [2020-07-07 SciPy Proceedings](https://www.youtube.com/watch?v=ERraTfHkPd0&list=PLYx7XA2nY5GfY4WWJjG5cQZDc7DIUmn6Z&index=4) [](https://youtu.be/ERraTfHkPd0)
- [2020-07-17 PyHEP 2020](https://indico.cern.ch/event/882824/contributions/3931299/) [](https://youtu.be/-g0mxopCJT8)

---

## Acknowledgements

This library was primarily developed by Henry Schreiner and Nino Lau.

Support for this work was provided by the National Science Foundation cooperative agreement OAC-1836650 (IRIS-HEP) and OAC-1450377 (DIANA/HEP). Any opinions, findings, conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the National Science Foundation.

[actions-badge]:            https://github.com/scikit-hep/hist/workflows/CI/badge.svg
[actions-link]:             https://github.com/scikit-hep/hist/actions
[binder-badge]:             https://mybinder.org/badge_logo.svg
[binder-link]:              https://mybinder.org/v2/gh/scikit-hep/hist/HEAD
[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/hist
[conda-link]:               https://github.com/conda-forge/hist-feedstock
[doi-badge]:                https://zenodo.org/badge/239605861.svg
[doi-link]:                 https://zenodo.org/badge/latestdoi/239605861
[github-discussions-badge]: https://img.shields.io/static/v1?label=Discussions&message=Ask&color=blue&logo=github
[github-discussions-link]:  https://github.com/scikit-hep/hist/discussions
[gitter-badge]:             https://badges.gitter.im/HSF/PyHEP-histogramming.svg
[gitter-link]:              https://gitter.im/HSF/PyHEP-histogramming?utm_source=badge&utm_medium=badge&utm_campaign=pr-badge
[license-badge]:            https://img.shields.io/badge/License-BSD_3--Clause-blue.svg
[license-link]:             https://opensource.org/licenses/BSD-3-Clause
[pre-commit-badge]:         https://results.pre-commit.ci/badge/github/scikit-hep/hist/main.svg
[pre-commit-link]:          https://results.pre-commit.ci/repo/github/scikit-hep/hist
[pypi-link]:                https://pypi.org/project/hist/
[pypi-platforms]:           https://img.shields.io/pypi/pyversions/hist
[pypi-version]:             https://badge.fury.io/py/hist.svg
[rtd-badge]:                https://readthedocs.org/projects/hist/badge/?version=latest
[rtd-link]:                 https://hist.readthedocs.io/en/latest/?badge=latest
[sk-badge]:                 https://scikit-hep.org/assets/images/Scikit--HEP-Project-blue.svg
[sk-link]:                  https://scikit-hep.org/

Owner

GitHub Events