https://github.com/aminnj/yahist

1D and 2D histogram objects
https://github.com/aminnj/yahist

histogram matplotlib numpy plotly plotting

Last synced: 10 months ago
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1D and 2D histogram objects

• Host: GitHub
• URL: https://github.com/aminnj/yahist
• Owner: aminnj
• Created: 2019-10-28T22:30:29.000Z (over 6 years ago)
• Default Branch: master
• Last Pushed: 2024-05-18T01:27:22.000Z (over 1 year ago)
• Last Synced: 2025-03-28T11:11:37.315Z (10 months ago)
• Topics: histogram, matplotlib, numpy, plotly, plotting
• Language: Python
• Homepage:
• Size: 9.08 MB
• Stars: 10
• Watchers: 1
• Forks: 3
• Open Issues: 3
• Metadata Files:
  • Readme: README.md

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README

          
## Yet another histogram

![Python application](https://github.com/aminnj/yahist/workflows/Python%20application/badge.svg)

[![PyPI](https://img.shields.io/pypi/v/yahist.svg)](https://pypi.python.org/pypi/yahist/)

[![Documentation Status](https://readthedocs.org/projects/pip/badge/?version=latest)](https://aminnj.github.io/yahist/)

[![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/aminnj/yahist/master?filepath=examples%2Fbasic.ipynb)

```bash

pip install yahist

```

### Examples ([API docs](https://aminnj.github.io/yahist/))

[![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/aminnj/yahist/master?filepath=examples%2Fbasic.ipynb)

(static [nbviewer](https://nbviewer.jupyter.org/url/github.com/aminnj/yahist/blob/master/examples/basic.ipynb) if Binder is slow)

### Overview

Histogram objects (1D and 2D) with easy manipulations (`numpy`), plotting (`matplotlib`), and fitting (`scipy`/`iminuit`).

```python

import numpy as np

from yahist import Hist1D

v = np.random.normal(0, 1, 1000)

h = Hist1D(v, bins=100, label="data").rebin(2).normalize()

h.plot(errors=True, ms=3)

h.fit("peak * np.exp(-(x-mu)**2 / (2*sigma**2))")

```



```python

import pandas as pd

df = pd.DataFrame(np.random.normal(0, 1, size=(10000, 2)), columns=["A", "B"])

h = Hist2D(df, bins="30,-3,3", threads=4)

h.plot(logz=True, cmap="cividis")

h.profile("x").plot(errors=True, color="C1", marker=".", label="x-profile")

```



Much more functionality is showcased in the example notebook, including

* fitting (chi2 or likelihood)

* interactive plots (via `bokeh`)

* datetime inputs/axes

* rebinning/subsetting

* profiling/projecting 2D histograms

* acceleration of 1D/2D histogram creation with [boost-histogram](https://github.com/scikit-hep/boost-histogram)

* using the histogram as a lookup function

* serialization to/from json

...and more.