Metadata-Version: 2.1
Name: NREL-farms
Version: 1.0.2
Summary: The Fast All-sky Radiation Model for Solar applications (FARMS)
Home-page: https://github.com/NREL/farms
Author: Grant Buster
Author-email: grant.buster@nrel.gov
License: BSD 3-Clause
Keywords: farms
Platform: UNKNOWN
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: BSD License
Classifier: Natural Language :: English
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Requires-Python: >=3.7
Requires-Dist: numpy (>=1.17)
Requires-Dist: pandas (>=0.25)
Provides-Extra: dev
Requires-Dist: pytest (>=5.2) ; extra == 'dev'
Requires-Dist: flake8 ; extra == 'dev'
Requires-Dist: pre-commit ; extra == 'dev'
Requires-Dist: pylint ; extra == 'dev'
Provides-Extra: test
Requires-Dist: pytest (>=5.2) ; extra == 'test'

***************************************************************************
Welcome to the Fast All-sky Radiation Model for Solar applications (FARMS)!
***************************************************************************

.. image:: https://github.com/NREL/farms/workflows/Documentation/badge.svg
    :target: https://nrel.github.io/farms/

.. image:: https://github.com/NREL/farms/workflows/Pytests/badge.svg
    :target: https://github.com/NREL/farms/actions?query=workflow%3A%22Pytests%22

.. image:: https://github.com/NREL/farms/workflows/Lint%20Code%20Base/badge.svg
    :target: https://github.com/NREL/farms/actions?query=workflow%3A%22Lint+Code+Base%22

.. image:: https://img.shields.io/pypi/pyversions/NREL-farms.svg
    :target: https://pypi.org/project/NREL-farms/

.. image:: https://badge.fury.io/py/NREL-farms.svg
    :target: https://badge.fury.io/py/NREL-farms

.. image:: https://anaconda.org/nrel/nrel-farms/badges/version.svg
    :target: https://anaconda.org/nrel/nrel-farms

.. image:: https://anaconda.org/nrel/nrel-farms/badges/license.svg
    :target: https://anaconda.org/nrel/nrel-farms

.. image:: https://codecov.io/gh/nrel/farms/branch/master/graph/badge.svg?token=WQ95L11SRS
    :target: https://codecov.io/gh/nrel/farms


The Fast All-sky Radiation Model for Solar applications (FARMS) is used to
compute cloudy irradiance.

.. inclusion-intro

Installing farms
================

Option 1: Install from PIP or Conda (recommended for analysts):
---------------------------------------------------------------

1. Create a new environment:
    ``conda create --name farms``

2. Activate directory:
    ``conda activate farms``

3. Install farms:
    1) ``pip install NREL-farms`` or
    2) ``conda install nrel-farms --channel=nrel``

Option 2: Clone repo (recommended for developers)
-------------------------------------------------

1. from home dir, ``git clone https://github.com/NREL/farms.git``
    1) enter github username
    2) enter github password

2. Create ``farms`` environment and install package
    1) Create a conda env: ``conda create -n farms``
    2) Run the command: ``conda activate farms``
    3) cd into the repo cloned in 1.
    4) prior to running ``pip`` below, make sure the branch is correct (install
       from master!)
    5) Install ``farms`` and its dependencies by running:
       ``pip install .`` (or ``pip install -e .`` if running a dev branch
       or working on the source code)

Recommended Citation
====================

Yu Xie, Manajit Sengupta, Jimy Dudhia, "A Fast All-sky Radiation Model
for Solar applications (FARMS): Algorithm and performance evaluation",
Solar Energy, Volume 135, 2016, Pages 435-445, ISSN 0038-092X,
https://doi.org/10.1016/j.solener.2016.06.003.
`Science Direct Link. <http://www.sciencedirect.com/science/article/pii/S0038092X16301827>`_

