Metadata-Version: 2.4
Name: leaflux
Version: 0.1.4
Summary: Core algorithms for the Leaflux project
Home-page: https://github.com/silvxlabs/leaflux-core
License: MIT
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
Classifier: Topic :: Scientific/Engineering
Requires-Python: >=3.9
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: numpy
Requires-Dist: datetime
Requires-Dist: pvlib
Requires-Dist: scipy
Requires-Dist: sparse
Requires-Dist: numba
Dynamic: classifier
Dynamic: description
Dynamic: description-content-type
Dynamic: home-page
Dynamic: license
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# LeafLux

## About
LeafLux is a process based light dynamics model for forested environments. The goal 
of LeafLux is to provide relative irradiance information for a user provided
canopy and terrain at a finer resolution than is 
typically available. It is a Python package that aims to be easy to use and is
compatible with standard numpy data types.

## Links
[Documentation home](https://silvxlabs.github.io/leaflux-core/)

[PyPi package](https://pypi.org/project/leaflux/)

## Installation

Leaflux can be installed using pip:

`pip install leaflux`

## Quick start guide

Install LeafLux as shown above, then include it in your project like:

`import leaflux`

You can then follow a [how to guide](https://silvxlabs.github.io/leaflux-core/how-to-guides/) to learn how 
to use LeafLux to generate irradiance information. 

## Issues

If you encounter any issues, please submit an issue to this project's [issue page](https://github.com/silvxlabs/leaflux-core/issues).
