https://github.com/scikit-hep/hist
Histogramming for analysis powered by boost-histogram
https://github.com/scikit-hep/hist
histogram python scikit-hep
Last synced: 3 months ago
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Histogramming for analysis powered by boost-histogram
- Host: GitHub
- URL: https://github.com/scikit-hep/hist
- Owner: scikit-hep
- License: bsd-3-clause
- Created: 2020-02-10T20:24:52.000Z (over 6 years ago)
- Default Branch: main
- Last Pushed: 2025-03-28T21:40:25.000Z (about 1 year ago)
- Last Synced: 2025-03-31T21:47:44.521Z (about 1 year ago)
- Topics: histogram, python, scikit-hep
- Language: Python
- Homepage: https://hist.readthedocs.io
- Size: 4.36 MB
- Stars: 128
- Watchers: 7
- Forks: 26
- Open Issues: 86
-
Metadata Files:
- Readme: README.md
- Contributing: .github/CONTRIBUTING.md
- License: LICENSE
- Citation: CITATION.cff
- Support: docs/support.rst
Awesome Lists containing this project
- awesome-hep - Hist - histogram with analysis shortcuts and plotting. (Python / Aggregation/histogram filling)
README
# Hist
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Hist is an analyst-friendly front-end for
[boost-histogram](https://github.com/scikit-hep/boost-histogram), designed for
Python 3.10+ (3.6-3.9 users get older versions). See [what's new](https://hist.readthedocs.io/en/latest/changelog.html).
## Installation
You can install this library from [PyPI](https://pypi.org/project/hist/) with pip:
```bash
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:
- 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.
- `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.
- `.fill_flattened(...)` will flatten and fill, including support for AwkwardArray.
- `.integrate(...)`, which takes the opposite arguments as `.project`.
- 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=[0.3, 0.5, 0.2])
# 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](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
📖
Angus Hollands
💻 📖
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.
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