semvec/pypi-packages huggingface dataset:
foliume 0.0.1
Make beautiful maps with Leaflet.js & Python
License: MIT
Requires Python: >=3.5
Keywords: data visualization

foliume
=======

基于folium添加基本无偏移国内图源，包名及所有用法与folium相同，但安装需要使用如下方式（结尾有个
``e`` ）

.. code:: shell

   pip install foliume

添加：

-  GeoQ (tiles=“GeoQ China Community / Street”)
-  高德地图 (tiles=“AMAP China”)
-  腾讯地图 (tiles=“TencentMap China”)
-  百度地图 (tiles=“BaiduMaps China”)

简单案例参考：\ `test.ipynb <test.ipynb>`__

======

|PyPI| |Test| |Gitter| |DOI| |binder|

.. |PyPI| image:: https://img.shields.io/pypi/v/folium.svg
    :target: https://pypi.org/project/folium
    :alt: PyPI Package

.. |Test| image:: https://github.com/python-visualization/folium/actions/workflows/test_code.yml/badge.svg
    :target: https://github.com/python-visualization/folium/actions/workflows/test_code.yml
    :alt: Code tests

.. |Gitter| image:: https://badges.gitter.im/python-visualization/folium.svg
    :target: https://gitter.im/python-visualization/folium
    :alt: Gitter

.. |DOI| image:: https://zenodo.org/badge/18669/python-visualization/folium.svg
   :target: https://zenodo.org/badge/latestdoi/18669/python-visualization/folium
   :alt: DOI
   
.. |binder| image:: https://mybinder.org/badge_logo.svg
 :target: https://mybinder.org/v2/gh/python-visualization/folium/main?filepath=examples

folium
======

|folium|

Python Data, Leaflet.js Maps
~~~~~~~~~~~~~~~~~~~~~~~~~~~~

`folium` builds on the data wrangling strengths of the Python ecosystem and the
mapping strengths of the Leaflet.js library. Manipulate your data in Python, 
then visualize it in a Leaflet map via `folium`.

Installation
------------

.. code:: bash

    $ pip install folium

or

.. code:: bash

    $ conda install -c conda-forge folium

Documentation
-------------

https://python-visualization.github.io/folium/


Gallery
-------

There are two galleries of Jupyter notebooks with examples, which you can see
using Jupyter's nbviewer:

https://nbviewer.jupyter.org/github/python-visualization/folium/tree/main/examples/

https://nbviewer.jupyter.org/github/python-visualization/folium_contrib/tree/master/notebooks/

Contributing
------------

We love contributions!  folium is open source, built on open source,
and we'd love to have you hang out in our community.

See `our complete contributor's guide <https://github.com/python-visualization/folium/blob/main/.github/CONTRIBUTING.md>`_ for more info.


.. |folium| image:: http://python-visualization.github.io/folium/_images/folium_logo.jpg


Changelog
---------

Check the `changelog <https://raw.githubusercontent.com/python-visualization/folium/main/CHANGES.txt>`_ for a detailed list of the latest changes.
safely 0.2.1
Capture side effects, safely.
License: MIT
Requires Python: >=3.8.0,<3.11.0

<h1 align="center">Safely</h1>
<p align="center">Capture side effects, safely ⚔️</p>
<p align="center">
<a href="https://github.com/lukemiloszewski/safely/actions/workflows/ci.yml/badge.svg" target="_blank">
    <img src="https://github.com/lukemiloszewski/safely/actions/workflows/ci.yml/badge.svg" alt="Continuous Integration">
</a>
<a href="https://pypi.org/project/safely" target="_blank">
    <img src="https://img.shields.io/pypi/v/safely?color=%2334D058&label=pypi%20package" alt="Package Version">
</a>
<a href="https://pypi.org/project/safely" target="_blank">
    <img src="https://img.shields.io/pypi/pyversions/safely.svg?color=%2334D058" alt="Supported Python Versions">
</a>
</p>

## Installation

```shell
pip install safely
```

## Usage

As a function (without second-order arguments):

```python
def f(...): ...

result = safely(f)(...)
```

As a function (with second-order arguments):

```python
def f(...): ...

result = safely(f, logger=logger.error, message="{exc_type}: {exc_value}")(...)
```

As a decorator (without second-order arguments):

```python
@safely
def f(...): ...

result = f(...)
```

As a decorator (with second-order arguments):

```python
@safely(logger=logger.error, message="{exc_type}: {exc_value}")
def f(...): ...

result = f(...)
```
raw2fits 1.0.2
Convert raw images to fits
License: MIT
Requires Python: >=3.6

# raw2fits
A Python package to convert camera raw images to astronomical fits files.

## Installation
```bash
pip install raw2fits
```

## Usage

### To convert a raw image to a fits file.

```python
from raw2fits.image import Image
img = Image(path='path/to/raw/image', debayer_method="VNG")
img.save_fits(image_type="LIGHT", path='path/to/save/fits/image')
```
where `debayer_method` can be one of the following: "VNG", "Bilinear". We recommend using "VNG" for better results.

### Comparsion between different debayer methods
  
The following images are the result of converting a raw image to a fits file using different debayer methods.

|     Debayer Method      |                             Image                             |
| :---------------------: | :-----------------------------------------------------------: |
|      **Bilinear**       |   <img width=250px  src=tests/debayer_examples/full/BL.jpg>   |
|         **VNG**         |  <img width=250px  src=tests/debayer_examples/full/VNG.jpg>   |
| **VNG (by Pixinsight)** | <img width=250px  src=tests/debayer_examples/full/VNG_PI.jpg> |

---

|     Debayer Method      |                              Image                               |
| :---------------------: | :--------------------------------------------------------------: |
|      **Bilinear**       |   <img width=250px  src=tests/debayer_examples/cropped/BL.png>   |
|         **VNG**         |  <img width=250px  src=tests/debayer_examples/cropped/VNG.png>   |
| **VNG (by Pixinsight)** | <img width=250px  src=tests/debayer_examples/cropped/VNG_PI.png> |
---

## Contributing
Pull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.

Please make sure to update tests as appropriate.

## License
[MIT](https://choosealicense.com/licenses/mit/)

## Acknowledgements
This extraction of the bayer image is based on the [rawpy](https://github.com/letmaik/rawpy).