semvec/pypi-packages huggingface dataset:
clement 0.3.0
GUI for Correlative Light and Electron Microscopy
Requires Python: >=3.6

# Clement
[![PyPI version](https://badge.fury.io/py/clement.svg)](https://badge.fury.io/py/clement)
## GUI for Correlative Light and Electron Microscopy
A graphical program to correlate electron microscopy and fluorescent optical images of the same sample.

## Installation
The package is pure python, and the easiest way to install it is through PyPi with the following command:
```
$ pip install clement
```
We recommend create a separate environment using either `conda` or `virtualenv` to manage dependencies.

Further instructions are available in the Wiki [here](https://github.com/kartikayyer/Clement/wiki/installation).

## Tutorial
A guide with screenshots for semi-automatic alignment of FM and EM images based on observable features is also described on the [wiki](https://github.com/kartikayyer/Clement/wiki/tutorial-2D).
eikosogram 0.0.5
A small package for drawing eikosograms
Requires Python: >=3.8

# Eikosogram

> WARNING: This package is no longer supported, it has been renamed to match the name in R. Check out the new one here: [PyPI](https://pypi.org/project/eikosograms), [GitHub](https://github.com/petro-zdebskyi/eikosograms).

Inspired by [R eikosograms](https://cran.r-project.org/web/packages/eikosograms/vignettes/Introduction.html), I decided to create a similar library for Python since there was no such library at the time (only a few crude implementations: [[1]](https://andrewtruong.com/data_visualization), [[2]](https://github.com/wtsi-hgi/spack-repo/blob/b5bd14ed3a34bae3ad4677be09af070f0f544293/packages/r-eikosograms/package.py#L9)). 

Also, I created [interactive visualization](https://www.desmos.com/calculator/81hy17u2bt) in Desmos.

## Install
```
pip install eikosogram
```

## Usage
```python
>>> from eikosogram import eikosogram
>>> eikosogram.draw_chart(.8, .3, .4, names=('Rain', 'Cloudy'), min_labels=False)
```
Check function docstring for more details.
sphinx-tsn-theme 2024.11.0
TiaC Systems Network (TSN) theme for Sphinx
Requires Python: >=3.9
Keywords: sphinx, theme, TiaC Systems Network, tiac, tiacsys, tsn

TiaC Systems Network (TSN) theme for Sphinx
===========================================

This repository contains the `Sphinx theme`_ for TiaC Systems Network (TSN)
documentation, based on `Read The Docs`_' default theme (sphinx_rtd_theme_).
This theme was forked from the Nordic Semiconductor NCS theme for Sphinx
(sphinx-ncs-theme_), which is also MIT licensed.
Copyright (c) 2021 Nordic Semiconductor ASA.

Installation
------------

This theme is distributed on PyPI as sphinx-tsn-theme_ and can be installed
with ``pip``:

.. code-block:: console

    pip install sphinx-tsn-theme

Usage
-----

To use the theme in your Sphinx project, you will need to add the following to
your ``conf.py`` file:

.. code-block:: python

    html_theme = "sphinx_tsn_theme"

Releasing
---------

1. Make sure you have a PyPI account and access to https://pypi.org/project/sphinx-tsn-theme/.
2. Make sure all your changes have been commited to the ``main`` branch.
3. Add a commit which updates the version number in ``sphinx_tsn_theme/__init__.py``.
4. Tag this commit with the version number, e.g. ``git tag -a 2020.4 -m "version 2020.4"``.
5. Push the commit and the tag to the ``main`` branch.
6. `Generate the source and binary distributions with setup.py <https://packaging.python.org/tutorials/packaging-projects/#generating-distribution-archives>`__.
7. `Upload the two files from step 6 to PyPI with twine <https://packaging.python.org/tutorials/packaging-projects/#uploading-the-distribution-archives>`__.

.. _Sphinx theme: https://www.sphinx-doc.org/en/master/usage/theming.html
.. _Read The Docs: https://readthedocs.org/
.. _sphinx_rtd_theme: https://github.com/readthedocs/sphinx_rtd_theme
.. _sphinx-ncs-theme: https://github.com/nrfconnect/doc-sphinx-ncs-theme
.. _sphinx-tsn-theme: https://pypi.org/project/sphinx-tsn-theme/
study-da 0.5.3
A tool to create and submit large-scale DA simulations.
Requires Python: <3.13,>=3.11

# Dynamics Aperture Study Package

<p align="center">
    <img src="https://img.shields.io/pypi/v/study-DA" alt="PyPI - Version">
    <img src="https://img.shields.io/github/commits-since/ColasDroin/study-DA/latest" alt="GitHub commits since latest release">
    <img src="https://img.shields.io/github/actions/workflow/status/ColasDroin/study-DA/ci_tests.yaml?label=Tests" alt="GitHub Actions Workflow Status">
    <img src="https://img.shields.io/github/actions/workflow/status/ColasDroin/study-DA/ci_docs.yaml?label=Doc" alt="GitHub Actions Workflow Status">
    <img src="https://img.shields.io/github/license/ColasDroin/study-DA" alt="GitHub License">
    <img src="https://img.shields.io/pypi/pyversions/study-DA" alt="PyPI - Python Version">
</p>

This package consists of a collection of tools to study the dynamics aperture of a particle accelerator built with [Xsuite](https://github.com/xsuite/xsuite). In a sense, it is a replacement of the [DA study template](https://github.com/xsuite/DA_study_template), but much more advanced. It also allows to configure colliders and do tracking without necessarily running parametric scans.

The whole project is described in details in the [full documentation](https://colasdroin.github.io/study-DA/), along with tutorials and description of the implemented functions.

## Installation

The package is available on PyPI and can be installed using `pip`.

```bash
pip install study-da
```

Proper installation might require additional instructions. Please refer to the [full documentation](https://colasdroin.github.io/study-DA/) for more details.

## Contributing

We welcome contributions to the Dynamics Aperture Study Package. If you have any ideas, suggestions, or bug reports, please open an issue or submit a pull request.

1. Fork the repository
2. Create a new branch (`git checkout -b feature/yourfeature`)
3. Make your changes
4. Commit your changes (`git commit -am 'Add your feature'`)
5. Push to the branch (`git push origin feature/yourfeature`)
6. Create a new Pull Request

## License

This project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details.