semvec/pypi-packages huggingface dataset:
poissonregime 0.1.0
Poisson error bars for low count statistics, detection significances.
License: MIT
Requires Python: >=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*
Keywords: poissonregime

=============
poissonregime
=============

Poisson error bars for low count statistics, detection significances.

.. image:: https://img.shields.io/pypi/v/poissonregime.svg
        :target: https://pypi.python.org/pypi/poissonregime

.. image:: https://api.travis-ci.com/JohannesBuchner/poissonregime.svg?branch=master&status=started
        :target: https://travis-ci.com/github/JohannesBuchner/poissonregime

.. image:: https://img.shields.io/badge/docs-published-ok.svg
        :target: https://johannesbuchner.github.io/poissonregime/
        :alt: Documentation Status

About
-----

Low count statistics is not that hard. It's just not Gaussian.

This package can answer the following questions:

* Given k detected objects, what are the uncertainties on the true number of objects? (`poissonregime.uncertainties_rate`)
* Given k "hits" out of a sample of n tries, what is the fraction and its uncertainty? (`poissonregime.uncertainties_fraction`)
* What is the significance of k detections, given that I expect B background events? (`poissonregime.significance`)
  * what if I measure the background events from counts in a "off" region?
  * what if I have additional systematic uncertainty?
* What is the probability distribution on the event rate, given a measured background rate? (`poissonregime.posterior`)

You can help by testing poissonregime and reporting issues. Code contributions are welcome.
See the `Contributing page <https://johannesbuchner.github.io/poissonregime/contributing.html>`_.

Usage
^^^^^

Read the full documentation at:

https://johannesbuchner.github.io/poissonregime/


Licence
^^^^^^^

MIT.


Other projects
^^^^^^^^^^^^^^

See also:

 * https://github.com/giacomov/gv_significance
 * https://github.com/mahnen/gamma_limits_sensitivity


==============
Release Notes
==============

0.1.0 (2021-06-11)
------------------

* First version
reqsit 0.28.0
A CLI tool for converting requirements.txt entries to a form accepted by pyproject.toml.
License: MIT
Keywords: packaging,wheel


# Reqsit

[![Code style: black](https://img.shields.io/badge/code%20style-black-000000.svg)](https://github.com/psf/black)
![example workflow](https://github.com/mattyWuh/reqsit/actions/workflows/ci.yml/badge.svg)

A CLI tool for converting requirements.txt entries to a form accepted by pyproject.toml.
Pronounced "RECKS-IT".

## Getting started.

Install `reqsit` with `pip`,

```
pip install --user reqsit
```

Run by executing the command from the root folder of your project,

```
reqsit
```

If you prefer to use a name other than `requirements.txt` for your requirements file, then add a `--filename` argument.
For example, to use the file `foo.bar`, enter

```
reqsit --filename=foo.bar
```

## How to contribute.