From 5957c0d345a68046e738bf921009f764ec6b0f5a Mon Sep 17 00:00:00 2001 From: bnb32 Date: Fri, 1 May 2026 12:43:35 -0600 Subject: [PATCH] nrel -> nlr --- .github/ISSUE_TEMPLATE/bug_report.md | 2 +- .../documentation_improvement.yaml | 4 +- .github/ISSUE_TEMPLATE/feature_request.md | 2 +- .../ISSUE_TEMPLATE/installation_issue.yaml | 2 +- CITATION.cff | 16 ++-- LICENSE | 2 +- README.rst | 90 +++++++++---------- docs/source/conf.py | 4 +- examples/sup3rcc/README.rst | 16 ++-- examples/sup3rwind/README.rst | 14 +-- pyproject.toml | 14 +-- sup3r/__init__.py | 2 +- sup3r/cli.py | 10 +-- sup3r/pipeline/strategy.py | 2 +- sup3r/writers/base.py | 2 +- 15 files changed, 91 insertions(+), 91 deletions(-) diff --git a/.github/ISSUE_TEMPLATE/bug_report.md b/.github/ISSUE_TEMPLATE/bug_report.md index da8b023ac4..e687be2482 100644 --- a/.github/ISSUE_TEMPLATE/bug_report.md +++ b/.github/ISSUE_TEMPLATE/bug_report.md @@ -43,4 +43,4 @@ If applicable, add screenshots to help explain your problem. Add any other context about the problem here. **Charge code** -If you are at NREL and fixing this bug is urgent, please provide a charge code for our time. +If you are at NLR and fixing this bug is urgent, please provide a charge code for our time. diff --git a/.github/ISSUE_TEMPLATE/documentation_improvement.yaml b/.github/ISSUE_TEMPLATE/documentation_improvement.yaml index 887e0c9555..ebcb383290 100644 --- a/.github/ISSUE_TEMPLATE/documentation_improvement.yaml +++ b/.github/ISSUE_TEMPLATE/documentation_improvement.yaml @@ -10,7 +10,7 @@ body: options: - label: > I have checked that the issue still exists on the latest versions of the docs - on `main` [here](https://nrel.github.io/sup3r/) + on `main` [here](https://natlabrockies.github.io/sup3r/) required: true - type: textarea id: location @@ -18,7 +18,7 @@ body: label: Location of the documentation description: > Please provide the location of the documentation, - placeholder: https://nrel.github.io/sup3r/_autosummary/sup3r.cli.html#sup3r.cli + placeholder: https://natlabrockies.github.io/sup3r/_autosummary/sup3r.cli.html#sup3r.cli validations: required: true - type: textarea diff --git a/.github/ISSUE_TEMPLATE/feature_request.md b/.github/ISSUE_TEMPLATE/feature_request.md index 2302069a68..5c428324b4 100644 --- a/.github/ISSUE_TEMPLATE/feature_request.md +++ b/.github/ISSUE_TEMPLATE/feature_request.md @@ -20,7 +20,7 @@ A clear and concise description of any alternative solutions or features you've Add any other context or screenshots about the feature request here. **Charge code** -If you are at NREL, please provide a task number for the developers to implement this feature. +If you are at NLR, please provide a task number for the developers to implement this feature. **Urgency / Timeframe** When do you need this feature by? How urgent is it related to other feature requests you've made? diff --git a/.github/ISSUE_TEMPLATE/installation_issue.yaml b/.github/ISSUE_TEMPLATE/installation_issue.yaml index 3f11177cad..b940f4a1ad 100644 --- a/.github/ISSUE_TEMPLATE/installation_issue.yaml +++ b/.github/ISSUE_TEMPLATE/installation_issue.yaml @@ -8,7 +8,7 @@ body: label: Installation check options: - label: > - I have read the [installation guide](https://nrel.github.io/sup3r/misc/installation.html). + I have read the [installation guide](https://natlabrockies.github.io/sup3r/misc/installation.html). required: true - type: input id: platform diff --git a/CITATION.cff b/CITATION.cff index c0119d551e..e0a26ece1c 100644 --- a/CITATION.cff +++ b/CITATION.cff @@ -7,36 +7,36 @@ type: software authors: - family-names: Benton given-names: Brandon - affiliation: NREL + affiliation: NLR orcid: "https://orcid.org/0009-0008-9931-2050" - family-names: Buster given-names: Grant - affiliation: NREL + affiliation: NLR orcid: "https://orcid.org/0000-0001-8616-8100" - family-names: Hassanaly given-names: Malik - affiliation: NREL + affiliation: NLR orcid: "https://orcid.org/0000-0002-0425-9090" - family-names: Pinchuk given-names: Pavlo - affiliation: NREL + affiliation: NLR orcid: "https://orcid.org/0000-0003-4736-4728" - family-names: Podgorny given-names: Slater - affiliation: NREL + affiliation: NLR orcid: "https://orcid.org/0009-0008-4903-411X" - family-names: Glaws given-names: Andrew - affiliation: NREL + affiliation: NLR orcid: "https://orcid.org/0000-0002-7268-1883" - family-names: King given-names: Ryan - affiliation: NREL + affiliation: NLR orcid: "https://orcid.org/0000-0002-0591-7139" identifiers: - type: doi value: 10.5281/zenodo.6808547 -repository-code: 'https://github.com/NREL/sup3r' +repository-code: 'https://github.com/NatLabRockies/sup3r' abstract: >- The Super Resolution for Renewable Resource Data (sup3r) software uses generative adversarial networks to create diff --git a/LICENSE b/LICENSE index 75a9a8d4e4..23d5c52035 100644 --- a/LICENSE +++ b/LICENSE @@ -1,6 +1,6 @@ BSD 3-Clause License -Copyright (c) 2022, Alliance for Sustainable Energy LLC, All rights reserved. +Copyright (c) 2022, Alliance for Energy Innovation LLC, All rights reserved. Redistribution and use in source and binary forms, with or without modification, are permitted provided that the following conditions are met: diff --git a/README.rst b/README.rst index a61edab66c..d1c74d112e 100644 --- a/README.rst +++ b/README.rst @@ -1,32 +1,32 @@ -.. image:: https://raw.githubusercontent.com/NREL/sup3r/main/docs/source/_static/sup3r_github_banner.jpg +.. image:: https://raw.githubusercontent.com/NatLabRockies/sup3r/main/docs/source/_static/sup3r_github_banner.jpg :width: 750 :alt: sup3r banner |Docs| |Tests| |Linter| |PyPi| |PythonV| |Codecov| |Zenodo| -.. |Docs| image:: https://github.com/NREL/sup3r/workflows/Documentation/badge.svg - :target: https://nrel.github.io/sup3r/ +.. |Docs| image:: https://github.com/NatLabRockies/sup3r/workflows/Documentation/badge.svg + :target: https://natlabrockies.github.io/sup3r/ -.. |Tests| image:: https://github.com/NREL/sup3r/workflows/Pytests/badge.svg - :target: https://github.com/NREL/sup3r/actions?query=workflow%3A%22Pytests%22 +.. |Tests| image:: https://github.com/NatLabRockies/sup3r/workflows/Pytests/badge.svg + :target: https://github.com/NatLabRockies/sup3r/actions?query=workflow%3A%22Pytests%22 -.. |Linter| image:: https://github.com/NREL/sup3r/workflows/Lint%20Code%20Base/badge.svg - :target: https://github.com/NREL/sup3r/actions?query=workflow%3A%22Lint+Code+Base%22 +.. |Linter| image:: https://github.com/NatLabRockies/sup3r/workflows/Lint%20Code%20Base/badge.svg + :target: https://github.com/NatLabRockies/sup3r/actions?query=workflow%3A%22Lint+Code+Base%22 -.. |PyPi| image:: https://img.shields.io/pypi/pyversions/NREL-sup3r.svg - :target: https://pypi.org/project/NREL-sup3r/ +.. |PyPi| image:: https://img.shields.io/pypi/pyversions/NLR-sup3r.svg + :target: https://pypi.org/project/NLR-sup3r/ -.. |PythonV| image:: https://badge.fury.io/py/NREL-sup3r.svg - :target: https://badge.fury.io/py/NREL-sup3r +.. |PythonV| image:: https://badge.fury.io/py/NLR-sup3r.svg + :target: https://badge.fury.io/py/NLR-sup3r -.. |Codecov| image:: https://codecov.io/gh/nrel/sup3r/branch/main/graph/badge.svg - :target: https://codecov.io/gh/nrel/sup3r +.. |Codecov| image:: https://codecov.io/gh/NatLabRockies/sup3r/branch/main/graph/badge.svg + :target: https://codecov.io/gh/NatLabRockies/sup3r .. |Zenodo| image:: https://zenodo.org/badge/422324608.svg :target: https://zenodo.org/badge/latestdoi/422324608 -Developed by NREL, Sup3r is open-source software that transforms coarse, +Developed by NLR, Sup3r is open-source software that transforms coarse, low-resolution data into actionable and accessible hyper-local data at unprecedented speed and scale. @@ -43,17 +43,17 @@ Getting Started Here are some options to get started with sup3r: -#. Learn `how to install sup3r `_. -#. Learn `how sup3r works `_. -#. Learn about our `current applications of sup3r `_. -#. Learn about the methods and validation of sup3r from `our publications `_. -#. To access output datasets, see `our data records `_ from previous applications. -#. To get started running sup3r software, check out our `test suite `_ that uses the software on small pieces of test data. -#. To get started loading in data for training or inference, start with the `data handler object `_ that is our basic data structure that opens NREL .h5 and other .nc data files. -#. To get started with model training, check out our `training tests `_ that initialize and train a basic GAN on small test data. -#. To get started with model inference, check out our `forward pass tests `_ that run a simple inference on small test data. Alternatively, see the examples linked below. -#. To see previous examples of sup3r code, configs, pretrained models, and data, see our `published examples `_. -#. To setup full runs on an HPC environment, check out the sup3r command line interface `(CLI) `_. +#. Learn `how to install sup3r `_. +#. Learn `how sup3r works `_. +#. Learn about our `current applications of sup3r `_. +#. Learn about the methods and validation of sup3r from `our publications `_. +#. To access output datasets, see `our data records `_ from previous applications. +#. To get started running sup3r software, check out our `test suite `_ that uses the software on small pieces of test data. +#. To get started loading in data for training or inference, start with the `data handler object `_ that is our basic data structure that opens NLR .h5 and other .nc data files. +#. To get started with model training, check out our `training tests `_ that initialize and train a basic GAN on small test data. +#. To get started with model inference, check out our `forward pass tests `_ that run a simple inference on small test data. Alternatively, see the examples linked below. +#. To see previous examples of sup3r code, configs, pretrained models, and data, see our `published examples `_. +#. To setup full runs on an HPC environment, check out the sup3r command line interface `(CLI) `_. How it Works @@ -62,7 +62,7 @@ Sup3r uses a generative machine learning approach to produce synthetic high-resolution spatiotemporal energy resource data from coarse, low-resolution inputs. The process is described step-by-step below. -.. image:: https://raw.githubusercontent.com/NREL/sup3r/main/docs/source/_static/Sup3rCC_Top_Graphic_v2.jpg +.. image:: https://raw.githubusercontent.com/NatLabRockies/sup3r/main/docs/source/_static/Sup3rCC_Top_Graphic_v2.jpg :width: 750 :alt: Sup3r climate downscaling overview graphic @@ -93,7 +93,7 @@ important for downstream applications such as power system operational modeling, where fine-scale spatial structure and high-frequency temporal dynamics matter as much as statistical accuracy. -.. image:: https://raw.githubusercontent.com/NREL/sup3r/main/docs/source/_static/Sup3r_training_flow_chart.jpg +.. image:: https://raw.githubusercontent.com/NatLabRockies/sup3r/main/docs/source/_static/Sup3r_training_flow_chart.jpg :width: 600 :alt: Sup3r training flow chart @@ -120,7 +120,7 @@ meteorological variables. Sup3r has been proven to generate output that reproduces the large-scale dynamics in the data from Step 2 while capturing realistic physics at the finest scales. -.. image:: https://raw.githubusercontent.com/NREL/sup3r/main/docs/source/_static/Sup3r_inference_flow_chart.jpg +.. image:: https://raw.githubusercontent.com/NatLabRockies/sup3r/main/docs/source/_static/Sup3r_inference_flow_chart.jpg :width: 600 :alt: Sup3r inference flow chart @@ -137,7 +137,7 @@ conditions. Notably, Sup3rCC does not represent real historical weather events, unlike Sup3rWind or Sup3rUHI (described below). To learn more about Sup3rCC, check out the publication list below or the -`Sup3rCC example `_. +`Sup3rCC example `_. Sup3rWind --------- @@ -151,7 +151,7 @@ developers worldwide. To learn more about Sup3rWind, check out the publication list below or the `Sup3rWind example -`_. +`_. Sup3rUHI -------- @@ -161,7 +161,7 @@ humidity time series. It supports both historical analysis and future scenario modeling, enabling precise, data-driven planning for high-risk heat events. To learn more about Sup3rUHI, check out the publication list below or the -`Sup3rUHI repo `_. +`Sup3rUHI repo `_. Installing sup3r @@ -178,7 +178,7 @@ Option 1: Install from PIP (recommended for analysts): 2. Activate environment: ``conda activate sup3r`` -3. Install sup3r: ``pip install NREL-sup3r`` +3. Install sup3r: ``pip install NLR-sup3r`` 4. Run this if you want to train models on GPUs: ``pip install tensorflow[and-cuda]`` @@ -187,7 +187,7 @@ Option 1: Install from PIP (recommended for analysts): Option 2: Clone repo (recommended for developers) ------------------------------------------------- -1. Run ``git clone git@github.com:NREL/sup3r.git`` +1. Run ``git clone git@github.com:NatLabRockies/sup3r.git`` 2. ``cd sup3r``. 3. Make sure the branch is correct (install from main!) 4. If you are using conda, create and activate a new environment: @@ -207,8 +207,8 @@ Update with current version and DOI: Brandon Benton, Grant Buster, Guilherme Pimenta Castelao, Malik Hassanaly, Pavlo Pinchuk, Slater Podgorny, Andrew Glaws, and Ryan King. Super Resolution -for Renewable Resource Data (sup3r). https://github.com/NREL/sup3r (version -v0.2.3), 2025. https://doi.org/10.5281/zenodo.15586596 +for Renewable Resource Data (sup3r). https://github.com/NatLabRockies/sup3r (version +v0.2.7), 2025. https://doi.org/10.5281/zenodo.15586596 Publications ============ @@ -234,21 +234,21 @@ https://doi.org/10.1073/pnas.1918964117 Data Records ============ Super-Resolution for Renewable Energy Resource Data with Climate Change Impacts -(Sup3rCC). [Data set]. Open Energy Data Initiative (OEDI). National Renewable -Energy Laboratory (NREL). https://doi.org/10.25984/1970814 +(Sup3rCC). [Data set]. Open Energy Data Initiative (OEDI). National Laboratory of the +Rockies (NLR). https://doi.org/10.25984/1970814 Super-Resolution for Renewable Energy Resource Data with Wind from Reanalysis -(Sup3rWind). [Data set]. Open Energy Data Initiative (OEDI). National Renewable -Energy Laboratory. https://data.openei.org/submissions/8455 +(Sup3rWind). [Data set]. Open Energy Data Initiative (OEDI). National Laboratory of +the Rockies. https://data.openei.org/submissions/8455 Super-Resolution for Renewable Resource Data and Urban Heat Islands (Sup3rUHI). -[Data set]. Open Energy Data Initiative (OEDI). National Renewable Energy Lab -(NREL). https://data.openei.org/submissions/6220 +[Data set]. Open Energy Data Initiative (OEDI). National Laboratory of the Rockies +(NLR). https://data.openei.org/submissions/6220 Acknowledgments =============== -This work was authored by the National Renewable Energy Laboratory, operated +This work was authored by the National Laboratory of the Rockies, operated for the U.S. Department of Energy (DOE) under Contract No. DE-AC36-08GO28308. This research was supported by the Grid Modernization Initiative of the U.S. Department of Energy (DOE) as part of its Grid Modernization Laboratory @@ -262,10 +262,10 @@ Energy Security, and Emergency Response (CESER), the DOE Advanced Scientific Computing Research (ASCR) program, the DOE Solar Energy Technologies Office (SETO), the DOE Wind Energy Technologies Office (WETO), the United States Agency for International Development (USAID), and the Laboratory Directed -Research and Development (LDRD) program at the National Renewable Energy -Laboratory. The research was performed using computational resources sponsored +Research and Development (LDRD) program at the National Laboratory of the Rockies. +The research was performed using computational resources sponsored by the Department of Energy's Office of Energy Efficiency and Renewable Energy -and located at the National Renewable Energy Laboratory. The views expressed in +and located at the National Laboratory of the Rockies. The views expressed in the article do not necessarily represent the views of the DOE or the U.S. Government. The U.S. Government retains and the publisher, by accepting the article for publication, acknowledges that the U.S. Government retains a diff --git a/docs/source/conf.py b/docs/source/conf.py index daf7f5477f..436b2c4cfa 100644 --- a/docs/source/conf.py +++ b/docs/source/conf.py @@ -24,7 +24,7 @@ # -- Project information ----------------------------------------------------- project = 'sup3r' -copyright = '2022, Alliance for Sustainable Energy, LLC' +copyright = '2022, Alliance for Energy Innovation, LLC' author = 'Brandon Benton, Grant Buster, Andrew Glaws, Ryan King' pkg = os.path.dirname(os.path.abspath(os.path.dirname(__file__))) @@ -122,7 +122,7 @@ html_context = { 'display_github': True, - 'github_user': 'nrel', + 'github_user': 'NatLabRockies', 'github_repo': 'sup3r', 'github_version': 'main', 'conf_py_path': '/docs/source/', diff --git a/examples/sup3rcc/README.rst b/examples/sup3rcc/README.rst index d7e4e64b2e..94dc821cd3 100644 --- a/examples/sup3rcc/README.rst +++ b/examples/sup3rcc/README.rst @@ -7,13 +7,13 @@ Super-Resolution for Renewable Energy Resource Data with Climate Change Impacts Sup3rCC Data Access -------------------- -For high level details on accessing the NREL renewable energy resource datasets including Sup3rCC, see the `rex docs pages `__ +For high level details on accessing the NLR renewable energy resource datasets including Sup3rCC, see the `rex docs pages `__ The Sup3rCC data and models are publicly available in a public AWS S3 bucket. The data files and models can be downloaded directly from there to your local machine or an EC2 instance using the `OEDI data explorer `__ or the `AWS CLI `__. A word of caution: there's a lot of data here. The smallest Sup3rCC file for just a single variable is ~20 GB, and a full year of data is ~200 GB. -The Sup3rCC data is also loaded into `HSDS `__ so that you may stream the data via the `NREL developer API `__ or your own HSDS server. This is the best option if you're not going to want the full annual dataset over the whole United States. See these `rex instructions `__ for more details on how to access this data with HSDS and rex. +The Sup3rCC data is also loaded into `HSDS `__ so that you may stream the data via the `NLR developer API `__ or your own HSDS server. This is the best option if you're not going to want the full annual dataset over the whole United States. See these `rex instructions `__ for more details on how to access this data with HSDS and rex. -The data can now be opened remotely with ``xarray`` and ``rex``. See the docs `here `__ for instructions. +The data can now be opened remotely with ``xarray`` and ``rex``. See the docs `here `__ for instructions. Directory Structure ------------------- @@ -25,7 +25,7 @@ Within the S3 bucket there is also a folder ``models`` providing pre-trained Sup Example Sup3rCC Data Usage -------------------------- -The jupyter notebook in this example shows some basic code to access and explore the data. You can walk through the `example notebook `__. You can clone this repo, setup a basic python environment with `rex `__, and run the notebook on your own. +The jupyter notebook in this example shows some basic code to access and explore the data. You can walk through the `example notebook `__. You can clone this repo, setup a basic python environment with `rex `__, and run the notebook on your own. Running Sup3rCC Models ---------------------- @@ -41,17 +41,17 @@ To run the Sup3rCC models, follow these instructions: #. Copy this examples directory to your hardware. You're going to be using the folder structure in ``/sup3r/examples/sup3rcc/run_configs`` as your project directories (``/sup3r/`` is a git clone of the sup3r software repo). #. Navigate to ``/sup3r/examples/sup3rcc/run_configs/nearsurf/`` and update all of the filepaths in the config files for the source GCM data, Sup3rCC models, and exogenous data sources (e.g. the ``nsrdb_clearsky.h5`` file downloaded from OEDI). #. Update the execution control parameters in the ``config_fwp.json`` file based on the hardware you're running on. -#. You can either run ``sup3r-batch`` to setup multiple run years, or ``sup3r-pipeline`` to run just one job. We recommend starting with ``sup3r-pipeline`` (more on the sup3r `CLI `__). +#. You can either run ``sup3r-batch`` to setup multiple run years, or ``sup3r-pipeline`` to run just one job. We recommend starting with ``sup3r-pipeline`` (more on the sup3r `CLI `__). #. To run ``sup3r-pipeline``, make sure you are in the directory with the ``config_pipeline.json`` and ``config_fwp.json`` files, and then run this command: ``python -m sup3r.cli -c config_pipeline.json pipeline`` #. If you're running on a slurm cluster, this will kick off a number of jobs that you can see with the ``squeue`` command. If you're running locally, your terminal should now be running the Sup3rCC models. The software will create a ``./logs/`` directory in which you can monitor the progress of your jobs. #. The ``sup3r-pipeline`` is designed to run several modules in serial, with each module running multiple chunks in parallel. Once the first module (forward-pass) finishes, you'll want to run ``python -m sup3r.cli -c config_pipeline.json pipeline`` again. This will clean up status files and kick off the next step in the pipeline (if the current step was successful). -Note that you can get significantly better performance by pre-loading the variable-by-variable and multi-year CMIP6 files using the `Sup3rCC data handler `__ and saving single files per year with all necessary variables for use in the generative runs. +Note that you can get significantly better performance by pre-loading the variable-by-variable and multi-year CMIP6 files using the `Sup3rCC data handler `__ and saving single files per year with all necessary variables for use in the generative runs. Nuances of Sup3rCC ------------------ -The Sup3rCC dataset is quite unlike the legacy NREL historical wind and solar datasets. As such, we expect there will be some confusion about how to use the data. There are some nuances of the data enumerated below. If you have any questions about how to apply the Sup3rCC data to your work, please reach out to Grant Buster (Grant.Buster@nrel.gov). +The Sup3rCC dataset is quite unlike the legacy NLR historical wind and solar datasets. As such, we expect there will be some confusion about how to use the data. There are some nuances of the data enumerated below. If you have any questions about how to apply the Sup3rCC data to your work, please reach out to Grant Buster (Grant.Buster@nlr.gov). #. Sup3rCC data is based on global climate model (GCM) data, which does not represent historical weather, only historical climate. So for example, Sup3rCC 2015 does not represent the actual historical weather in 2015, just the historical climate in 2015. #. Sup3rCC data represents just one possible future climate subject to deep uncertainties. Do not use the Sup3rCC data as an accurate prediction of future weather. Some uncertanties about our future climate can be quantified by exploring a large ensemble of GCM data across multiple climate scenarios and multiple models. @@ -91,4 +91,4 @@ Buster, Grant, Benton, Brandon, Glaws, Andrew, & King, Ryan. Super-Resolution fo Acknowledgements ---------------- -This work was authored by the National Renewable Energy Laboratory for the U.S. Department of Energy (DOE) under Contract No. DE-AC36-08GO28308. This research was supported by the Grid Modernization Initiative of the U.S. Department of Energy (DOE) as part of its Grid Modernization Laboratory Consortium, a strategic partnership between DOE and the national laboratories to bring together leading experts, technologies, and resources to collaborate on the goal of modernizing the nation’s grid. Funding provided by the DOE Office of Energy Efficiency and Renewable Energy (EERE), the DOE Office of Electricity (OE), DOE Grid Deployment Office (GDO), the DOE Advanced Scientific Computing Research (ASCR) program, the DOE Solar Energy Technologies Office (SETO), and the Laboratory Directed Research and Development (LDRD) program at the National Renewable Energy Laboratory. The research was performed using computational resources sponsored by the DOE Office of Energy Efficiency and Renewable Energy and located at the National Renewable Energy Laboratory. The views expressed in the article do not necessarily represent the views of the DOE or the U.S. Government. The U.S. Government retains and the publisher, by accepting the article for publication, acknowledges that the U.S. Government retains a nonexclusive, paid-up, irrevocable, worldwide license to publish or reproduce the published form of this work, or allow others to do so, for U.S. Government purposes. +This work was authored by the National Laboratory of the Rockies for the U.S. Department of Energy (DOE) under Contract No. DE-AC36-08GO28308. This research was supported by the Grid Modernization Initiative of the U.S. Department of Energy (DOE) as part of its Grid Modernization Laboratory Consortium, a strategic partnership between DOE and the national laboratories to bring together leading experts, technologies, and resources to collaborate on the goal of modernizing the nation’s grid. Funding provided by the DOE Office of Energy Efficiency and Renewable Energy (EERE), the DOE Office of Electricity (OE), DOE Grid Deployment Office (GDO), the DOE Advanced Scientific Computing Research (ASCR) program, the DOE Solar Energy Technologies Office (SETO), and the Laboratory Directed Research and Development (LDRD) program at the National Lab of the Rockies. The research was performed using computational resources sponsored by the DOE Office of Energy Efficiency and Renewable Energy and located at the National Lab of the Rockies. The views expressed in the article do not necessarily represent the views of the DOE or the U.S. Government. The U.S. Government retains and the publisher, by accepting the article for publication, acknowledges that the U.S. Government retains a nonexclusive, paid-up, irrevocable, worldwide license to publish or reproduce the published form of this work, or allow others to do so, for U.S. Government purposes. diff --git a/examples/sup3rwind/README.rst b/examples/sup3rwind/README.rst index b65c8ceb19..d4eea9a730 100644 --- a/examples/sup3rwind/README.rst +++ b/examples/sup3rwind/README.rst @@ -9,30 +9,30 @@ Sup3rWind Data Access The Sup3rWind data and models are publicly available in a public AWS S3 bucket. The data files can be downloaded directly from there to your local machine or an EC2 instance using the `OEDI data explorer `__ or the `AWS CLI `__. A word of caution: there's a lot of data here. The smallest Sup3rWind file for just a single variable at 2-km 5-minute resolution is 130 GB. -The Sup3rWind data is also loaded into `HSDS `__ so that you may stream the data via the `NREL developer API `__ or your own HSDS server. This is the best option if you're not going to want a full annual dataset. See these `rex instructions `__ for more details on how to access this data with HSDS and rex. +The Sup3rWind data is also loaded into `HSDS `__ so that you may stream the data via the `NLR developer API `__ or your own HSDS server. This is the best option if you're not going to want a full annual dataset. See these `rex instructions `__ for more details on how to access this data with HSDS and rex. Sup3rWind Data Usage --------------------- -Sup3rWind data can be used in generally the same way as `Sup3rCC `__ data, with the condition that Sup3rWind includes only wind data and ancillary variables for modeling wind energy generation. Refer to the Sup3rCC `example notebook `__ for usage patterns. +Sup3rWind data can be used in generally the same way as `Sup3rCC `__ data, with the condition that Sup3rWind includes only wind data and ancillary variables for modeling wind energy generation. Refer to the Sup3rCC `example notebook `__ for usage patterns. Running Sup3rWind Models ------------------------- -The process for running the Sup3rWind models is much the same as for `Sup3rCC `__. +The process for running the Sup3rWind models is much the same as for `Sup3rCC `__. #. Download the Sup3rWind models to your hardware using the AWS CLI: ``$ aws s3 cp s3://nrel-pds-wtk/sup3rwind/models/`` #. Setup the Sup3rWind software. We recommend using `miniconda `__ to manage your python environments. You can create a sup3r environment with the conda file in this example directory: ``$ conda env create -n sup3rwind --file env.yml`` -#. Download the ERA5 data that you want to downscale from `ERA5-single-levels `__ and/or `ERA5-pressure-levels `__ using the `EraDownloader `__. +#. Download the ERA5 data that you want to downscale from `ERA5-single-levels `__ and/or `ERA5-pressure-levels `__ using the `EraDownloader `__. #. Copy this examples directory to your hardware. You're going to be using the folder structure in ``/sup3r/examples/sup3rwind/run_configs`` as your project directories (``/sup3r/`` is a git clone of the sup3r software repo). #. Navigate to ``/sup3r/examples/sup3rwind/run_configs/wind/`` and/or ``sup3r/examples/sup3rwind/run_configs/trhp`` and update all of the filepaths in the config files for the source ERA5 data, Sup3rWind models, and exogenous data sources (e.g. the ``topography`` source file). #. Update the execution control parameters in the ``config_fwp_spatial.json`` file based on the hardware you're running on. -#. Run ``sup3r-pipeline`` to run just one job. There are also batch options for running multiple jobs, but we recommend starting with ``sup3r-pipeline`` (more on the sup3r `CLI `__). +#. Run ``sup3r-pipeline`` to run just one job. There are also batch options for running multiple jobs, but we recommend starting with ``sup3r-pipeline`` (more on the sup3r `CLI `__). #. To run ``sup3r-pipeline``, make sure you are in the directory with the ``config_pipeline.json`` and ``config_fwp_spatial.json`` files, and then run this command: ``python -m sup3r.cli -c config_pipeline.json pipeline`` #. If you're running on a slurm cluster, this will kick off a number of jobs that you can see with the ``squeue`` command. If you're running locally, your terminal should now be running the Sup3rWind models. The software will create a ``./logs/`` directory in which you can monitor the progress of your jobs. #. The ``sup3r-pipeline`` is designed to run several modules in serial, with each module running multiple chunks in parallel. Once the first module (forward-pass) finishes, you'll want to run ``python -m sup3r.cli -c config_pipeline.json pipeline`` again. This will clean up status files and kick off the next step in the pipeline (if the current step was successful). -You can also checkout the `example notebook `__ for how to run models without config files. +You can also checkout the `example notebook `__ for how to run models without config files. Training from scratch --------------------- @@ -95,4 +95,4 @@ Benton, B. N., Buster, G., Pinchuk, P., Glaws, A., King, R. N., Maclaurin, G., & Acknowledgements ----------------- -This work was authored by the National Renewable Energy Laboratory, for the U.S. Department of Energy (DOE) under Contract No. DE-AC36-08GO28308. Funding provided by the DOE Grid Deployment Office (GDO), the DOE Advanced Scientific Computing Research (ASCR) program, the DOE Solar Energy Technologies Office (SETO), and the Laboratory Directed Research and Development (LDRD) program at the National Renewable Energy Laboratory. The research was performed using computational resources sponsored by the DOE Office of Energy Efficiency and Renewable Energy and located at the National Renewable Energy Laboratory. The views expressed in the article do not necessarily represent the views of the DOE or the U.S. Government. The U.S. Government retains and the publisher, by accepting the article for publication, acknowledges that the U.S. Government retains a nonexclusive, paid-up, irrevocable, worldwide license to publish or reproduce the published form of this work, or allow others to do so, for U.S. Government purposes. +This work was authored by the National Laboratory of the Rockies, for the U.S. Department of Energy (DOE) under Contract No. DE-AC36-08GO28308. Funding provided by the DOE Grid Deployment Office (GDO), the DOE Advanced Scientific Computing Research (ASCR) program, the DOE Solar Energy Technologies Office (SETO), and the Laboratory Directed Research and Development (LDRD) program at the National Laboratory of the Rockies. The research was performed using computational resources sponsored by the DOE Office of Energy Efficiency and Renewable Energy and located at the National Laboratory of the Rockies. The views expressed in the article do not necessarily represent the views of the DOE or the U.S. Government. The U.S. Government retains and the publisher, by accepting the article for publication, acknowledges that the U.S. Government retains a nonexclusive, paid-up, irrevocable, worldwide license to publish or reproduce the published form of this work, or allow others to do so, for U.S. Government purposes. diff --git a/pyproject.toml b/pyproject.toml index a1281dcee9..398f6661c0 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -6,13 +6,13 @@ requires = [ build-backend = "setuptools.build_meta" [project] -name = "NREL-sup3r" +name = "NLR-sup3r" dynamic = ["version"] description = "Super Resolving Renewable Resource Data (sup3r)" -keywords = ["sup3r", "NREL"] +keywords = ["sup3r", "NLR"] readme = "README.rst" authors = [ - {name = "Brandon Benton", email = "brandon.benton@nrel.gov"}, + {name = "Brandon Benton", email = "brandon.benton@nlr.gov"}, ] license = {text = "BSD-3-Clause"} requires-python = ">= 3.9,<3.13" @@ -93,9 +93,9 @@ sup3r-forward-pass = "sup3r.pipeline.forward_pass_cli:main" sup3r-collect = "sup3r.postprocessing.data_collect_cli:main" [project.urls] -homepage = "https://github.com/NREL/sup3r" -documentation = "https://nrel.github.io/sup3r/" -repository = "https://github.com/NREL/sup3r" +homepage = "https://github.com/NatLabRockies/sup3r" +documentation = "https://natlabrockies.github.io/sup3r/" +repository = "https://github.com/NatLabRockies/sup3r" [tool.ruff] line-length = 79 @@ -303,7 +303,7 @@ scipy = ">=1.0.0" xarray = ">=2023.0" [tool.pixi.pypi-dependencies] -NREL-sup3r = { path = ".", editable = true } +NLR-sup3r = { path = ".", editable = true } [tool.pixi.environments] default = { solve-group = "default" } diff --git a/sup3r/__init__.py b/sup3r/__init__.py index f683bacef1..d20ce4180b 100644 --- a/sup3r/__init__.py +++ b/sup3r/__init__.py @@ -20,7 +20,7 @@ from .cli import main __author__ = """Brandon Benton""" -__email__ = 'brandon.benton@nrel.gov' +__email__ = 'brandon.benton@nlr.gov' SUP3R_DIR = os.path.dirname(os.path.realpath(__file__)) CONFIG_DIR = os.path.join(SUP3R_DIR, 'configs') diff --git a/sup3r/cli.py b/sup3r/cli.py index 5bc3bef06c..d38d13cedb 100644 --- a/sup3r/cli.py +++ b/sup3r/cli.py @@ -116,7 +116,7 @@ def forward_pass(ctx, verbose): } Note that the ``execution_control`` block contains kwargs that would - be required to distribute the job on multiple nodes on the NREL HPC. + be required to distribute the job on multiple nodes on the NLR HPC. To run the job locally, use ``execution_control: {"option": "local"}``. """ # noqa : D301 config_file = ctx.obj['CONFIG_FILE'] @@ -165,7 +165,7 @@ def solar(ctx, verbose): } Note that the ``execution_control`` block contains kwargs that would - be required to distribute the job on multiple nodes on the NREL HPC. + be required to distribute the job on multiple nodes on the NLR HPC. To run the job locally, use ``execution_control: {"option": "local"}``. """ # noqa : D301 config_file = ctx.obj['CONFIG_FILE'] @@ -228,7 +228,7 @@ def bias_calc(ctx, verbose): } Note that the ``execution_control`` block contains kwargs that would - be required to distribute the job on multiple nodes on the NREL HPC. + be required to distribute the job on multiple nodes on the NLR HPC. To run the job locally, use ``execution_control: {"option": "local"}``. """ # noqa : D301 config_file = ctx.obj['CONFIG_FILE'] @@ -271,7 +271,7 @@ def data_collect(ctx, verbose): } Note that the ``execution_control`` has the same options as forward-pass - and you can set ``"option": "kestrel"`` to run on the NREL HPC. + and you can set ``"option": "kestrel"`` to run on the NLR HPC. """ # noqa : D301 config_file = ctx.obj['CONFIG_FILE'] verbose = any([verbose, ctx.obj['VERBOSE']]) @@ -314,7 +314,7 @@ def qa(ctx, verbose): } Note that the ``execution_control`` has the same options as forward-pass - and you can set ``"option": "kestrel"`` to run on the NREL HPC. + and you can set ``"option": "kestrel"`` to run on the NLR HPC. """ # noqa : D301 config_file = ctx.obj['CONFIG_FILE'] verbose = any([verbose, ctx.obj['VERBOSE']]) diff --git a/sup3r/pipeline/strategy.py b/sup3r/pipeline/strategy.py index a7a122a02a..c4f67a467a 100644 --- a/sup3r/pipeline/strategy.py +++ b/sup3r/pipeline/strategy.py @@ -206,7 +206,7 @@ class ForwardPassStrategy: use_cpu : bool Flag to only use CPUs or to also use GPUs if available. Default is to use CPUs because they have more memory and GPUs are expensive on the - NREL HPC. + NLR HPC. """ file_paths: Union[str, list, pathlib.Path] diff --git a/sup3r/writers/base.py b/sup3r/writers/base.py index 3d808aac4c..38247f9804 100644 --- a/sup3r/writers/base.py +++ b/sup3r/writers/base.py @@ -168,7 +168,7 @@ def write_data( class RexOutputs(BaseRexOutputs): - """Base class to handle NREL h5 formatted output data""" + """Base class to handle NLR h5 formatted output data""" @property def full_version_record(self):