Metadata-Version: 2.1
Name: NREL-reV
Version: 0.6.0
Summary: National Renewable Energy Laboratory's (NREL's) Renewable Energy Potential(V) Model: reV
Home-page: https://nrel.github.io/reV/
Author: Galen Maclaurin
Author-email: galen.maclaurin@nrel.gov
License: BSD 3-Clause
Keywords: reV
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: NREL-NRWAL (>=0.0.7)
Requires-Dist: NREL-PySAM (<3.0.0,>=2.2.4)
Requires-Dist: NREL-rex (>=0.2.69)
Requires-Dist: packaging (>=20.3)
Requires-Dist: plotly (>=4.7.1)
Requires-Dist: plotting (>=0.0.6)
Requires-Dist: shapely
Requires-Dist: rasterio ; sys_platform == "darwin" or sys_platform == "linux"
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 Renewable Energy Potential (reV) Model!
******************************************************

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

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

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

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

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

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

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

.. image:: https://codecov.io/gh/nrel/reV/branch/main/graph/badge.svg?token=U4ZU9F0K0Z
    :target: https://codecov.io/gh/nrel/reV

.. image:: https://zenodo.org/badge/201343076.svg
   :target: https://zenodo.org/badge/latestdoi/201343076

.. image:: https://mybinder.org/badge_logo.svg
    :target: https://mybinder.org/v2/gh/nrel/reV/HEAD

.. inclusion-intro


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

Please cite both the technical paper and the software with the version and
DOI you used:

Maclaurin, Galen J., Nicholas W. Grue, Anthony J. Lopez, Donna M. Heimiller,
Michael Rossol, Grant Buster, and Travis Williams. 2019. “The Renewable Energy
Potential (reV) Model: A Geospatial Platform for Technical Potential and Supply
Curve Modeling.” Golden, Colorado, United States: National Renewable Energy
Laboratory. NREL/TP-6A20-73067. https://doi.org/10.2172/1563140.

Michael Rossol, Grant Buster, Mike Bannister, Robert Spencer, and Travis
Williams. The Renewable Energy Potential Model (reV).
https://github.com/NREL/reV (version v0.5.0), 2021.
https://doi.org/10.5281/zenodo.4711470.


reV command line tools
======================

- `reV <https://nrel.github.io/reV/_cli/reV.html#reV>`_
- `reV-project-points <https://nrel.github.io/reV/_cli/reV-project-points.html#reV-project-points>`_
- `reV-gen <https://nrel.github.io/reV/_cli/reV-gen.html#rev-gen>`_
- `reV-econ <https://nrel.github.io/reV/_cli/reV-econ.html#rev-econ>`_
- `reV-offshore <https://nrel.github.io/reV/_cli/reV-offshore.html#rev-offshore>`_
- `reV-collect <https://nrel.github.io/reV/_cli/reV-collect.html#rev-collect>`_
- `reV-multiyear <https://nrel.github.io/reV/_cli/reV-multiyear.html#rev-multiyear>`_
- `reV-supply-curve-aggregation <https://nrel.github.io/reV/_cli/reV-supply-curve-aggregation.html#rev-supply-curve-aggregation>`_
- `reV-supply-curve <https://nrel.github.io/reV/_cli/reV-supply-curve.html#rev-supply-curve>`_
- `reV-rep-profiles <https://nrel.github.io/reV/_cli/reV-rep-profiles.html#rev-rep-profiles>`_
- `reV-pipeline <https://nrel.github.io/reV/_cli/reV-pipeline.html#rev-pipeline>`_
- `reV-batch <https://nrel.github.io/reV/_cli/reV-batch.html#rev-batch>`_
- `reV-QA-QC <https://nrel.github.io/reV/_cli/reV-QA-QC.html#rev-qa-qc>`_

Using Eagle Env
===============

If you would like to run reV on Eagle (NREL's HPC) you can use a pre-compiled
conda env:

.. code-block:: bash

    conda activate /shared-projects/rev/modulefiles/conda/envs/rev/

or

.. code-block:: bash

    source activate /shared-projects/rev/modulefiles/conda/envs/rev/


Launching a run
---------------

Tips

- Only use a screen session if running the pipeline module: `screen -S rev`
- `Full pipeline execution <https://nrel.github.io/reV/misc/examples.full_pipeline_execution.html>`_

.. code-block:: bash

    reV -c "/scratch/user/rev/config_pipeline.json" pipeline

- Running simply generation or econ can just be done from the console:

.. code-block:: bash

    reV -c "/scratch/user/rev/config_gen.json" generation

General Run times and Node configuration on Eagle
-------------------------------------------------

- WTK Conus: 10-20 nodes per year walltime 1-4 hours
- NSRDB Conus: 5 nodes walltime 2 hours

`Eagle node requests <https://nrel.github.io/reV/misc/examples.eagle_node_requests.html>`_

Installing reV
==============

NOTE: The installation instruction below assume that you have python installed
on your machine and are using `conda <https://docs.conda.io/en/latest/index.html>`_
as your package/environment manager.

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

1. Create a new environment:
    ``conda create --name rev python=3.7``

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

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

       - NOTE: If you install using conda and want to use `HSDS <https://github.com/NREL/hsds-examples>`_
         you will also need to install h5pyd manually: ``pip install h5pyd``

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

1. from home dir, ``git clone git@github.com:NREL/reV.git``

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

3. Check that ``reV`` was installed successfully
    1) From any directory, run the following commands. This should return the
       help pages for the CLI's.

        - ``reV``


