Update URLs

.github/ISSUE_TEMPLATE/config.yml

@@ -1,5 +1,5 @@
 blank_issues_enabled: false
 contact_links:
   - name: GitHub Discussions
-    url: https://github.com/NREL/flasc/discussions/new
+    url: https://github.com/NatLabRockies/flasc/discussions/new
     about: Discuss potential issues or ideas here prior to opening a GitHub Issue

.github/ISSUE_TEMPLATE/documentation.yaml

@@ -18,4 +18,4 @@ body:
       label: URL
       description: If this issue references online documentation, enter the complete url here.
       placeholder:
-        https://nrel.github.io/flasc//<full link here>.html
+        https://natlabrockies.github.io/flasc//<full link here>.html

README.md

@@ -1,34 +1,34 @@
 # FLORIS-Based Analysis for SCADA Data (FLASC)
 
 
-**Note:** Further documentation is available at **https://nrel.github.io/flasc/**
+**Note:** Further documentation is available at **https://natlabrockies.github.io/flasc/**
 
 ## Description
 
 FLASC provides a **rich suite of analysis tools** for SCADA data filtering, analysis,
 wind farm model validation, field experiment design, and field experiment monitoring.
 
 The repository is centrally built around NRELs in-house ``FLORIS`` wind farm model, available at
-**https://github.com/nrel/floris**. FLASC also largely relies on the ``energy ratio``, among others,
+**https://github.com/NatLabRockies/floris**. FLASC also largely relies on the ``energy ratio``, among others,
 to quantify wake losses in synthetic and historical data, to perform turbine northing calibrations,
 and model parameter estimation.
 
 For technical questions or concerns, please email [email protected].
 
 
-[![pages-build-deployment](https://github.com/NREL/flasc/actions/workflows/pages/pages-build-deployment/badge.svg)](https://github.com/NREL/flasc/actions/workflows/pages/pages-build-deployment)
+[![pages-build-deployment](https://github.com/NatLabRockies/flasc/actions/workflows/pages/pages-build-deployment/badge.svg)](https://github.com/NatLabRockies/flasc/actions/workflows/pages/pages-build-deployment)
 
-[![Automated tests & code coverage](https://github.com/NREL/flasc/actions/workflows/continuous-integration-workflow.yaml/badge.svg)](https://github.com/NREL/flasc/actions/workflows/continuous-integration-workflow.yaml)
+[![Automated tests & code coverage](https://github.com/NatLabRockies/flasc/actions/workflows/continuous-integration-workflow.yaml/badge.svg)](https://github.com/NatLabRockies/flasc/actions/workflows/continuous-integration-workflow.yaml)
 
 [![License](https://img.shields.io/badge/License-BSD_3--Clause-blue.svg)](https://opensource.org/licenses/BSD-3-Clause)
 
 
 ## WETO software
 
-FLASC is primarily developed with the support of the U.S. Department of Energy and is part of the [WETO Software Stack](https://nrel.github.io/WETOStack). For more information and other integrated modeling software, see:
-- [Portfolio Overview](https://nrel.github.io/WETOStack/portfolio_analysis/overview.html)
-- [Entry Guide](https://nrel.github.io/WETOStack/_static/entry_guide/index.html)
-- [Controls and Analysis Workshop](https://nrel.github.io/WETOStack/workshops/user_workshops_2024.html#wind-farm-controls-and-analysis)
+FLASC is primarily developed with the support of the U.S. Department of Energy and is part of the [WETO Software Stack](https://natlabrockies.github.io/WETOStack). For more information and other integrated modeling software, see:
+- [Portfolio Overview](https://natlabrockies.github.io/WETOStack/portfolio_analysis/overview.html)
+- [Entry Guide](https://natlabrockies.github.io/WETOStack/_static/entry_guide/index.html)
+- [Controls and Analysis Workshop](https://natlabrockies.github.io/WETOStack/workshops/user_workshops_2024.html#wind-farm-controls-and-analysis)
 
 
 ## Installation
@@ -37,28 +37,28 @@ We recommend installing this repository in a separate virtual environment.
 After creating a new virtual environment, clone this repository to your local
 system and install it locally using ``pip``. The command for this is ``pip install -e flasc``.
 
-If installing for develop, follow the developer [install instructions](https://nrel.github.io/flasc/installation.html)
+If installing for develop, follow the developer [install instructions](https://natlabrockies.github.io/flasc/installation.html)
 
 ## Documentation
 
-Documentation is provided via the included examples folders as well as [online documentation](https://nrel.github.io/flasc/).
+Documentation is provided via the included examples folders as well as [online documentation](https://natlabrockies.github.io/flasc/).
 
 ## Engaging on GitHub
 
 FLASC leverages the following GitHub features to coordinate support and development efforts:
 
-- [Discussions](https://github.com/NREL/flasc/discussions): Collaborate to develop ideas for new use cases, features, and software designs, and get support for usage questions
-- [Issues](https://github.com/NREL/flasc/issues): Report potential bugs and well-developed feature requests
+- [Discussions](https://github.com/NatLabRockies/flasc/discussions): Collaborate to develop ideas for new use cases, features, and software designs, and get support for usage questions
+- [Issues](https://github.com/NatLabRockies/flasc/issues): Report potential bugs and well-developed feature requests
 - [Projects](https://github.com/orgs/NREL/projects/39): Include current and future work on a timeline and assign a person to "own" it
 
 Your feedback is crucial in this environment, as it helps identify areas for enhancement, resolve issues, and ensure the project meets the needs of its users. By sharing your insights and suggestions, you contribute to the project's evolution and success.
 
 Generally, the first entry point for the community will be within one of the
 categories in Discussions.
-[Ideas](https://github.com/NREL/flasc/discussions/categories/ideas) is a great spot to develop the
-details for a feature request. [Q&A](https://github.com/NREL/flasc/discussions/categories/q-a)
+[Ideas](https://github.com/NatLabRockies/flasc/discussions/categories/ideas) is a great spot to develop the
+details for a feature request. [Q&A](https://github.com/NatLabRockies/flasc/discussions/categories/q-a)
 is where to get usage support.
-[Show and tell](https://github.com/NREL/flasc/discussions/categories/show-and-tell) is a free-form
+[Show and tell](https://github.com/NatLabRockies/flasc/discussions/categories/show-and-tell) is a free-form
 space to show off the things you are doing with FLORIS.
 
 # License

docs/_config.yml

@@ -23,7 +23,7 @@ bibtex_bibfiles:
 
 # Information about where the book exists on the web
 repository:
-  url: https://github.com/NREL/flasc
+  url: https://github.com/NatLabRockies/flasc
   path_to_book: docs
   branch: main
 

docs/energy_change.md

@@ -8,15 +8,15 @@ FLASC now however includes three methods for quantifying the change in energy pr
 
 `total_uplift_power_ratio` uses a similar input as the [energy ratio](energy_ratio) methods but returns a single value representing the total uplift, rather than uplift binned by wind direction.  The method is named power_ratio because the change in energy production is computed using the mean per-wind-condition-bin power ratios.  The change in ratio per bin is then combined with the mean base power and frequency to estimate change in energy production.
 
-Currently the main example usage of the total uplift function is at the end of [smarteole example 06](https://github.com/NREL/flasc/blob/main/examples_smarteole/06_wake_steering_energy_ratio_analysis.ipynb).  Documentation of the function itself is available in the [API documentation](https://nrel.github.io/flasc/_autosummary/flasc.analysis.total_uplift_power_ratio.compute_total_uplift.html#flasc.analysis.total_uplift_power_ratio.compute_total_uplift).  Uncertainty of the results can be computed via bootstrapping.
+Currently the main example usage of the total uplift function is at the end of [smarteole example 06](https://github.com/NatLabRockies/flasc/blob/main/examples_smarteole/06_wake_steering_energy_ratio_analysis.ipynb).  Documentation of the function itself is available in the [API documentation](https://natlabrockies.github.io/flasc/_autosummary/flasc.analysis.total_uplift_power_ratio.compute_total_uplift.html#flasc.analysis.total_uplift_power_ratio.compute_total_uplift).  Uncertainty of the results can be computed via bootstrapping.
 
 The method was developed by Eric Simley and implemented by Paul Fleming and Misha Sinner of NREL.  
 
 ## Wind-Up
 
 FLASC further includes methods for calculating change in energy production using the [wind-up](https://github.com/resgroup/wind-up) module.   [wind-up](https://github.com/resgroup/wind-up) is a tool to assess yield uplift of wind turbines developed by Alex Clerc of RES and available open-source on GitHub.  Using translation methods in the [FlascDataFrame](flasc_data_format), the methods and analysis of wind-up can be invoked from FLASC.
 
-[smarteole example 09](https://github.com/NREL/flasc/blob/main/examples_smarteole/09_wind-up_wake_steering_uplift_analysis.ipynb), calculates the change in energy production (as in [smarteole example 06](https://github.com/NREL/flasc/blob/main/examples_smarteole/06_wake_steering_energy_ratio_analysis.ipynb)) using wind-up.
+[smarteole example 09](https://github.com/NatLabRockies/flasc/blob/main/examples_smarteole/09_wind-up_wake_steering_uplift_analysis.ipynb), calculates the change in energy production (as in [smarteole example 06](https://github.com/NatLabRockies/flasc/blob/main/examples_smarteole/06_wake_steering_energy_ratio_analysis.ipynb)) using wind-up.
 
 ## Expected Power Analysis
 
@@ -28,5 +28,5 @@ The module provides two approaches for quantifying uncertainty in the total upli
 
 The approach is different from the above approaches in several ways (refer to [AWC validation methodology](https://publications.tno.nl/publication/34637216/LWOb3s/TNO-2020-R11300.pdf) for full description).  First, as mentioned above, the uncertainty of the result can be computed directly from the variance and co-variances of the turbine powers instead of relying on the more computationally expensive bootstrapping approach.  Additionally, the method does not normalize the power of the test turbines by reference powers.  Therefore, the method may be more sensitive to wind speed variations within bins and other atmospheric conditions that would otherwise be partially controlled for through normalization by reference powers. To account for this sensitivity we suggest using smaller wind speed bins and wind speed estimates based on measured turbine performance (rather than nacelle anemometry) when calculating the expected power.  However, by avoiding normalization by a reference power signal, this method does not require all test turbines to be operating normally at each sample, increasing the amount of usable data, especially when large wind farms are being analyzed.
 
-Similar to above, an example using the smarteole data provides usage example, see [smarteole example 10](https://github.com/NREL/flasc/blob/main/examples_smarteole/examples_smarteole/10_uplift_with_expected_power.ipynb)
+Similar to above, an example using the smarteole data provides usage example, see [smarteole example 10](https://github.com/NatLabRockies/flasc/blob/main/examples_smarteole/examples_smarteole/10_uplift_with_expected_power.ipynb)
 

docs/energy_ratio.md

@@ -21,5 +21,5 @@ Key syntax for computing energy ratios is provided in the examples:
 
  Within the set of analysis of the smarteole dataset are also examples of using flasc's energy ratio calculations.  See for example:
 
- - [Baseline Energy Ratio Analysis](https://github.com/NREL/flasc/blob/main/examples_smarteole/05_baseline_energy_ratio_analysis.ipynb)
- - [Wake Steering Energy Ratio Analysis](https://github.com/NREL/flasc/blob/main/examples_smarteole/06_wake_steering_energy_ratio_analysis.ipynb)
+ - [Baseline Energy Ratio Analysis](https://github.com/NatLabRockies/flasc/blob/main/examples_smarteole/05_baseline_energy_ratio_analysis.ipynb)
+ - [Wake Steering Energy Ratio Analysis](https://github.com/NatLabRockies/flasc/blob/main/examples_smarteole/06_wake_steering_energy_ratio_analysis.ipynb)

docs/flasc_data_format.ipynb

@@ -329,7 +329,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "Another use case for `FlascDataFrame` is to export the data into the \"wind-up\" format.  [Wind-up](https://github.com/resgroup/wind-up) is an open source tool for assessing uplift provided by RES.  This conversion  provides a convenient way to assess the data, in the case of uplift assessment, using the wind-up tool, which is imported by FLASC.  A full demonstration of the usage of the wind-up tool in FLASC is provided within the [Smarteole](https://github.com/NREL/flasc/tree/main/examples_smarteole) example set."
+    "Another use case for `FlascDataFrame` is to export the data into the \"wind-up\" format.  [Wind-up](https://github.com/resgroup/wind-up) is an open source tool for assessing uplift provided by RES.  This conversion  provides a convenient way to assess the data, in the case of uplift assessment, using the wind-up tool, which is imported by FLASC.  A full demonstration of the usage of the wind-up tool in FLASC is provided within the [Smarteole](https://github.com/NatLabRockies/flasc/tree/main/examples_smarteole) example set."
    ]
   },
   {

docs/index.md

@@ -7,11 +7,11 @@ Welcome to the documentation of the NREL FLASC repository!
 As of FLASC v2.3, FLASC requires `numpy` version 2, following the update in FLORIS v4.3. See the [numpy documentation for details](https://numpy.org/doc/stable/numpy_2_0_migration_guide.html).
 ```
 
-FLASC provides a comprehensive toolkit for wind farm analysis, combining SCADA data processing with advanced wake modeling capabilities. The repository is intended as a community-driven toolbox, available on its [GitHub Repository](https://github.com/NREL/flasc).
+FLASC provides a comprehensive toolkit for wind farm analysis, combining SCADA data processing with advanced wake modeling capabilities. The repository is intended as a community-driven toolbox, available on its [GitHub Repository](https://github.com/NatLabRockies/flasc).
 
 ## What is FLASC?
 
-FLASC offers analysis tools for SCADA data filtering & analysis, wind farm model validation, field experiment design, and field experiment monitoring. Built around NREL's [FLORIS](https://github.com/NREL/floris/discussions/) wake modeling utility, FLASC enables researchers and practitioners to:
+FLASC offers analysis tools for SCADA data filtering & analysis, wind farm model validation, field experiment design, and field experiment monitoring. Built around NREL's [FLORIS](https://github.com/NatLabRockies/floris/discussions/) wake modeling utility, FLASC enables researchers and practitioners to:
 
 - **Process and filter SCADA data** with robust outlier detection and quality control
 - **Analyze energy production patterns** using energy ratio methodology for wake quantification  
@@ -45,11 +45,11 @@ FLASC's modular design supports the complete wind farm analysis workflow:
 - **Experiment Analysis**: Evaluate control strategies and technology impacts with statistical rigor
 
 The FLASC repository is intended as a community driven toolbox, available on
-its [GitHub Repository](https://github.com/NREL/flasc).
+its [GitHub Repository](https://github.com/NatLabRockies/flasc).
 
 ### WETO software
 
-FLASC is primarily developed with the support of the U.S. Department of Energy and is part of the [WETO Software Stack](https://nrel.github.io/WETOStack). For more information and other integrated modeling software, see:
-- [Portfolio Overview](https://nrel.github.io/WETOStack/portfolio_analysis/overview.html)
-- [Entry Guide](https://nrel.github.io/WETOStack/_static/entry_guide/index.html)
-- [Controls and Analysis Workshop](https://nrel.github.io/WETOStack/workshops/user_workshops_2024.html#wind-farm-controls-and-analysis)
+FLASC is primarily developed with the support of the U.S. Department of Energy and is part of the [WETO Software Stack](https://natlabrockies.github.io/WETOStack). For more information and other integrated modeling software, see:
+- [Portfolio Overview](https://natlabrockies.github.io/WETOStack/portfolio_analysis/overview.html)
+- [Entry Guide](https://natlabrockies.github.io/WETOStack/_static/entry_guide/index.html)
+- [Controls and Analysis Workshop](https://natlabrockies.github.io/WETOStack/workshops/user_workshops_2024.html#wind-farm-controls-and-analysis)

docs/installation.md

@@ -20,7 +20,7 @@ use `git clone`. Then, add it to your Python path with the "local editable insta
 
 ```bash
 # Download the source code.
-git clone https://github.com/NREL/flasc.git
+git clone https://github.com/NatLabRockies/flasc.git
 
 # Install into your Python environment
 pip install -e flasc
@@ -38,12 +38,12 @@ Recommended approach is to:
 
 1. Declare a new directory to be the root folder, for example FLASC/
 2. Setup a new virtual environement with venv or conda and activate
-3. Clone and install FLORIS into this root directory and environment, following the [developer install](https://nrel.github.io/floris/dev_guide.html)
+3. Clone and install FLORIS into this root directory and environment, following the [developer install](https://natlabrockies.github.io/floris/dev_guide.html)
 4. Clone and install flasc with developer options:
 
     ```bash
     # Download the source code.
-    git clone https://github.com/NREL/flasc.git
+    git clone https://github.com/NatLabRockies/flasc.git
 
     # Install into your Python environment
     pip install -e flasc ".[develop, docs]"

docs/introduction.md

@@ -1,6 +1,6 @@
 # Introduction to FLASC
 
-FLASC provides a rich suite of analysis tools for SCADA data filtering & analysis, wind farm model validation, field experiment design, and field experiment monitoring. The repository is centrally built around NREL's in-house [FLORIS](https://github.com/nrel/floris) wake modeling utility. FLASC also largely relies on the "energy ratio" to quantify wake losses in synthetic and historical data, perform turbine northing calibrations, and for model parameter estimation.
+FLASC provides a rich suite of analysis tools for SCADA data filtering & analysis, wind farm model validation, field experiment design, and field experiment monitoring. The repository is centrally built around NREL's in-house [FLORIS](https://github.com/NatLabRockies/floris) wake modeling utility. FLASC also largely relies on the "energy ratio" to quantify wake losses in synthetic and historical data, perform turbine northing calibrations, and for model parameter estimation.
 
 ## Getting Started
 
@@ -59,7 +59,7 @@ See {cite:p}`Doekemeijer2022a` and {cite:p}`Bay2022a` for practical examples of
 
 If FLASC played a role in your research, please cite it. This software can be cited as:
 
-   FLASC. Version 2.0.1 (2024). Available at https://github.com/NREL/flasc.
+   FLASC. Version 2.0.1 (2024). Available at https://github.com/NatLabRockies/flasc.
 
 For LaTeX users:
 
@@ -69,9 +69,9 @@ For LaTeX users:
       year = {2024},
       publisher = {GitHub},
       journal = {GitHub repository},
-      url = {https://github.com/NREL/flasc},
+      url = {https://github.com/NatLabRockies/flasc},
     }
 
 ## Questions
 
-For technical questions regarding FLASC usage, please post your questions to [GitHub Discussions](https://github.com/NREL/flasc/discussions) on the FLASC repository. Alternatively, email the NREL FLASC team at `[email protected] <mailto:[email protected]>`_ or `[email protected] <mailto:[email protected]>`_.
+For technical questions regarding FLASC usage, please post your questions to [GitHub Discussions](https://github.com/NatLabRockies/flasc/discussions) on the FLASC repository. Alternatively, email the NREL FLASC team at `[email protected] <mailto:[email protected]>`_ or `[email protected] <mailto:[email protected]>`_.

examples_artificial_data/04_floris_tuning/README.txt

@@ -1,6 +1,6 @@
 Calibrating FLORIS models using the floris_tuning package is deprecated as of FLASC v2.4.
 If you are looking for these examples, please see FLASC v2.3
-(https://github.com/NREL/flasc/releases/tag/v2.3)
+(https://github.com/NatLabRockies/flasc/releases/tag/v2.3)
 
 We strongly recommend instead using the replacement ModelFit package, demonstrated in
 examples_artificial_data/05_model_fit/