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National Renewable Energy Laboratory's (NREL's) Geospatial Analysis Pipelines (GAPs) framework

Project description

================================================ Welcome to Geospatial Analysis Pipelines (GAPs)!

.. inclusion-intro

Geospatial Analysis Pipelines (GAPs) is a framework designed to assist users in scaling their geospatial models to a High-Performance Computing (HPC) environment. In particular, GAPs automatically distributes the execution of a single-location model (such as the System Advisor Model <https://sam.nrel.gov>) over a large geospatial extent (e.g. CONUS) across many parallel HPC nodes. Born from the open-source reV <https://github.com/NREL/reV> model, GAPs is a robust and easy-to-use engine that provides a rich set of features such as configuration file generation, job status monitoring, CLI Documentation, and more.

Installing gaps

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.

  1. Clone the gaps repository.

    • Using ssh: :code:git clone git@github.com:NREL/gaps.git
    • Using https: :code:git clone https://github.com/NREL/gaps.git
  2. Create and activate the gaps environment and install the package:

    1. Create a conda env: conda create -n gaps python=3.10
    2. Activate the newly-created conda env: conda activate gaps
    3. Change directories into the repository: cd gaps
    4. Prior to running pip below, make sure the branch is correct (install from main!): git branch -vv
    5. Install gaps and its dependencies by running: pip install -e . (or pip install -e .[dev] if running a dev branch or working on the source code)

Development

This repository uses pylint <https://pylint.pycqa.org/en/latest/>_ to lint the code and black <https://black.readthedocs.io/en/stable/index.html>_ to format it (check out the black formatting style <https://black.readthedocs.io/en/stable/the_black_code_style/current_style.html>_). If you wish to contribute to this repository, your code will have to adhere to both of these guidelines and pass all existing tests.

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