Super Resolving Renewable Resource Data (sup3r)
Project description
The Super Resolution for Renewable Resource Data (sup3r) software uses generative adversarial networks to create synthetic high-resolution wind and solar spatiotemporal data from coarse low-resolution inputs. To get started, check out the sup3r command line interface (CLI) here.
Installing sup3r
NOTE: The installation instruction below assume that you have python installed on your machine and are using conda as your package/environment manager.
Option 1: Install from PIP (recommended for analysts):
Create a new environment: conda create --name sup3r python=3.9
Activate environment: conda activate sup3r
Run this if you want to train models on GPUs: conda install -c anaconda tensorflow-gpu
Install sup3r: pip install NREL-sup3r
Option 2: Clone repo (recommended for developers)
from home dir, git clone git@github.com:NREL/sup3r.git
- Create sup3r environment and install package
Create a conda env: conda create -n sup3r
Run the command: conda activate sup3r
cd into the repo cloned in 1.
Run this if you want to train models on GPUs: conda install -c anaconda tensorflow-gpu
Prior to running pip below, make sure the branch is correct (install from main!)
Install sup3r and its dependencies by running: pip install . (or pip install -e . if running a dev branch or working on the source code)
Recommended Citation
Update with current version and DOI:
Brandon Benton, Grant Buster, Andrew Glaws, Ryan King. Super Resolution for Renewable Resource Data (sup3r). https://github.com/NREL/sup3r (version v0.0.2), 2022. DOI: 10.5281/zenodo.6808547
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