National Renewable Energy Laboratory's (NREL's) Geospatial Analysis Pipelines (GAPs) framework
Project description
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) over a large geospatial extent (e.g. CONUS) across many parallel HPC nodes. Born from the open-source 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.
To get started, take a look at the documentation (examples coming soon!)
Installing gaps
NOTE: The installation instruction below assume that you have python installed on your machine and are using conda as your package/environment manager.
- Clone the gaps repository.
Using ssh:
git clone git@github.com:NREL/gaps.git
Using https:
git clone https://github.com/NREL/gaps.git
- Create and activate the gaps environment and install the package:
Create a conda env: conda create -n gaps python=3.10
Activate the newly-created conda env: conda activate gaps
Change directories into the repository: cd gaps
Prior to running pip below, make sure the branch is correct (install from main!): git branch -vv
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 to lint the code and black to format it (check out the black formatting style). If you wish to contribute to this repository, your code will have to adhere to both of these guidelines and pass all existing tests.
Acknowledgments
Paul Pinchuk and Grant Buster. Geospatial Analysis Pipelines. 2023. https://doi.org/10.11578/dc.20230426.7
The authors of this code would like to thank ExxonMobil Corporation for their contributions to this effort.
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