scikit-hep / hist

Histogramming for analysis powered by boost-histogram
https://hist.readthedocs.io
BSD 3-Clause "New" or "Revised" License
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histogram python scikit-hep
histogram

Hist

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PyPI version Conda-Forge PyPI platforms DOI License

GitHub Discussion Gitter Binder Scikit-HEP

Hist is an analyst-friendly front-end for boost-histogram, designed for Python 3.8+ (3.6-3.7 users get older versions). See what's new.

Slideshow of features. See docs/banner_slides.md for text if the image is not readable.

Installation

You can install this library from PyPI with pip:

python3 -m pip install "hist[plot,fit]"

If you do not need the plotting features, you can skip the [plot] and/or [fit] extras. [fit] is not currently supported in WebAssembly.

Features

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

Usage

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[0.3j:, ::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, or run:

python -m pip install -e .[dev]

See Contributing guidelines for information on setting up a development environment.

Contributors

We would like to acknowledge the contributors that made this project possible (emoji key):


Henry Schreiner

🚧 πŸ’» πŸ“–

Nino Lau

🚧 πŸ’» πŸ“–

Chris Burr

πŸ’»

Nick Amin

πŸ’»

Eduardo Rodrigues

πŸ’»

Andrzej Novak

πŸ’»

Matthew Feickert

πŸ’»

Kyle Cranmer

πŸ“–

Daniel Antrim

πŸ’»

Nicholas Smith

πŸ’»

Michael Eliachevitch

πŸ’»

Jonas Eschle

πŸ“–

This project follows the all-contributors specification.

Talks


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.