Metadata-Version: 2.1
Name: geoca
Version: 0.0.10
Summary: A Python module for CA models based on geo-raster data
Author-email: Haorui Jiang <jianghr0321@163.com>
License: MIT License
Project-URL: Homepage, https://github.com/Haorui-Jiang/geoca
Keywords: geoca
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved :: MIT License
Classifier: Natural Language :: English
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
Requires-Python: >=3.8
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: numpy
Requires-Dist: rasterio
Requires-Dist: tqdm
Provides-Extra: all
Requires-Dist: geoca[extra]; extra == "all"
Provides-Extra: extra
Requires-Dist: pandas; extra == "extra"

# geoca

[![image](https://img.shields.io/pypi/v/geoca.svg)](https://pypi.python.org/pypi/geoca)
[![image](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT)

English [简体中文](README.zh.md)

**A Python module for CA models based on geo-raster data**

- Free software: MIT License
- Documentation: [https://Haorui-Jiang.github.io/geoca](https://Haorui-Jiang.github.io/geoca)

## Features

- Read raster data from a file and convert the data to a format such as a Python list.
- Creates a raster template from the input raster data and uniformly replaces the data in the corresponding position of that raster template.
- Running CA models based on raster data to analyze population and other resource migration.

## File Template

- [cookiecutter-pypackage](https://github.com/opengeos/cookiecutter-pypackage): Cookiecutter template creating a Python package with mkdocs.

## Acknowledgement

Special thanks to [Dr. Qiusheng Wu](https://github.com/giswqs) from the University of Tennessee for his generous sharing. Dr. Wu has greatly enriched my knowledge of Python with his great tutorials on [YouTube](https://youtube.com/playlist?list=PLAxJ4-o7ZoPcD-6wZ2xY5bXuu48Scu8kq&si=dq_x-xUJZvoflVqy). It is with the help of his instructional videos that I have been able to develop geoca for Python. Once again, I express my deepest gratitude to Dr. Wu.
