{"id":48082533,"url":"https://github.com/sandialabs/quends","last_synced_at":"2026-04-04T14:58:07.282Z","repository":{"id":278295639,"uuid":"934450757","full_name":"sandialabs/quends","owner":"sandialabs","description":"Quantification of Uncertainty in ENsembles of Data Streams","archived":false,"fork":false,"pushed_at":"2026-03-31T20:47:18.000Z","size":14759,"stargazers_count":6,"open_issues_count":15,"forks_count":0,"subscribers_count":2,"default_branch":"main","last_synced_at":"2026-03-31T22:26:20.453Z","etag":null,"topics":["data-analysis","ensembles","fusion-energy","scr-3155","snl-data-analysis","snl-other","snl-visualization","time-series-analysis","turbulent-gyro-kinetics-analysis","uncertainty"],"latest_commit_sha":null,"homepage":"https://sandialabs.github.io/quends/","language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"other","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/sandialabs.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":"CONTRIBUTING.rst","funding":null,"license":"LICENSE","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null,"zenodo":null,"notice":null,"maintainers":null,"copyright":null,"agents":null,"dco":null,"cla":null}},"created_at":"2025-02-17T21:21:15.000Z","updated_at":"2026-03-17T22:25:09.000Z","dependencies_parsed_at":"2025-03-26T00:26:41.688Z","dependency_job_id":null,"html_url":"https://github.com/sandialabs/quends","commit_stats":null,"previous_names":["sandialabs/quends"],"tags_count":1,"template":false,"template_full_name":null,"purl":"pkg:github/sandialabs/quends","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/sandialabs%2Fquends","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/sandialabs%2Fquends/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/sandialabs%2Fquends/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/sandialabs%2Fquends/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/sandialabs","download_url":"https://codeload.github.com/sandialabs/quends/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/sandialabs%2Fquends/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":31403942,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-04-04T10:20:44.708Z","status":"ssl_error","status_checked_at":"2026-04-04T10:20:06.846Z","response_time":60,"last_error":"SSL_read: unexpected eof while reading","robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":false,"can_crawl_api":true,"host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["data-analysis","ensembles","fusion-energy","scr-3155","snl-data-analysis","snl-other","snl-visualization","time-series-analysis","turbulent-gyro-kinetics-analysis","uncertainty"],"created_at":"2026-04-04T14:58:05.447Z","updated_at":"2026-04-04T14:58:07.277Z","avatar_url":"https://github.com/sandialabs.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Quantification of Uncertainty in ENsembles of Data Streams (QUENDS)\n\n#### Evans Etrue Howard, Abeyah Calpatura, Pieterjan Robbe, Bert Debusschere\n\n[![Coverage Status](https://coveralls.io/repos/github/sandialabs/quends/badge.svg?branch=main)](https://coveralls.io/github/sandialabs/quends?branch=main)\n[![Deploy to GitHub Pages](https://github.com/sandialabs/quends/actions/workflows/deployment.yml/badge.svg)](https://github.com/sandialabs/quends/actions/workflows/deployment.yml)\n[![Run Tests](https://github.com/sandialabs/quends/actions/workflows/python-tests.yml/badge.svg)](https://github.com/sandialabs/quends/actions/workflows/python-tests.yml)\n[![pages-build-deployment](https://github.com/sandialabs/quends/actions/workflows/pages/pages-build-deployment/badge.svg)](https://github.com/sandialabs/quends/actions/workflows/pages/pages-build-deployment)\n\n## Overview\nThis project focuses on uncertainty quantification in plasma turbulent simulations. It includes modules for loading and processing NetCDF and CSV datasets, estimating steady states, computing effective sample sizes, and running uncertainty quantification analyses. The project is structured into multiple Python scripts, each handling different aspects of the analysis. To see more information on documentation, etc... visit our website [here](https://sandialabs.github.io/quends/).\n\n## Table of Contents\n\n- [Installation](#installation)\n- [Usage](#usage)\n- [For Developers](#for-developers)\n- [Documentation](#documentation)\n- [Examples](#examples)\n- [Summary](#summary)\n- [Contributing](#contributing)\n- [License](#license)\n\n## Installation\n\n1. **Clone the repository**:\n    - Using SSH:\n    ```bash\n    git clone git@github.com:sandialabs/quends.git\n    cd quends\n    ```\n    - Using HTTPS:\n    ```bash\n    git clone https://github.com/sandialabs/quends.git\n    cd quends\n    ```\n\n2. **Install the package and dependencies**:\n    You can install the package along with its dependencies using pip:\n    ```bash\n    pip install .\n    ```\n\n3. **Verify the installation**:\n    To ensure that the installation was successful, you can run a simple test:\n    ```bash\n    python -c \"import quends\"\n    ```\n\n\n## Usage\n\nExamples are shown in the `examples/notebooks` directories.\n- `cgyro`: Contains all CGYRO data\n- `gx`: Contains all gx data\n- `gx/ensemble`: Contains all ensemble data\n- `DataStream_Guide-CGRYO.ipynb`: DataStream guide for CGYRO data\n- `DataStream_Guide-GX.ipynb`: DataStream guide for GX data\n- `DataStream_Guide-Ensemble.ipynb`: DataStream guide for Ensembles\n- `DataStream_Guide.ipynb`: DataStream guide\n\n## For Developers\n\n1. **Clone the repository**:\n    - Using SSH:\n    ```bash\n    git clone git@github.com:sandialabs/quends.git\n    cd quends\n    ```\n    - Using HTTPS:\n    ```bash\n    git clone https://github.com/sandialabs/quends.git\n    cd quends\n    ```\n\n2. **Install the package and dependencies**:\n    You can install the package along with its dependencies using pip:\n    ```bash\n    pip install -e .\\[dev\\]\n    ```\n\n3. **Install pre-commit hooks**\n    To ensure code quality and consistency, install:\n    ```bash\n    pre-commit install\n    ```\n\n4. **Run Ruff**:\n    For linting and fixing issues:\n    ```bash\n    ruff check --fix\n    ```\n\n5. **Run isort**:\n    To format your code with Black:\n    ```bash\n    isort .\n    ```\n\n6. **Run Black**:\n    To format your code with Black:\n    ```bash\n    black .\n    ```\n\n## Documentation\nFor comprehensive information on how to use the QUENDS package, please refer to our [official documentation](https://sandialabs.github.io/quends/autoapi/quends/index.html). \n\n## Summary\nKey functionalities include:\n- **Data Handling**: Seamlessly load and preprocess data from various formats, including CSV, JSON, and NetCDF.\n- **Statistical Analysis**: Compute essential statistics and assess data quality with built-in methods for effective sample size estimation and confidence interval calculations.\n- **Visualization**: Create informative plots to visualize trends, correlations, and patterns in time series data.\n\n## Contributing\nFeel free to submit issues and merge requests. For major changes, please open an issue first to discuss what you would like to change.\n\n## License\nBSD 3-Clause License\n\nCopyright 2025 National Technology \u0026 Engineering Solutions of Sandia, LLC (NTESS).\nUnder the terms of Contract DE-NA0003525 with NTESS, the U.S. Government retains\ncertain rights in this software.\n\nRedistribution and use in source and binary forms, with or without\nmodification, are permitted provided that the following conditions are met:\n\n1. Redistributions of source code must retain the above copyright notice, this\n   list of conditions and the following disclaimer.\n\n2. Redistributions in binary form must reproduce the above copyright notice,\n   this list of conditions and the following disclaimer in the documentation\n   and/or other materials provided with the distribution.\n\n3. Neither the name of the copyright holder nor the names of its\n   contributors may be used to endorse or promote products derived from\n   this software without specific prior written permission.\n\nTHIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS \"AS IS\"\nAND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE\nIMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE\nDISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE\nFOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL\nDAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR\nSERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER\nCAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY,\nOR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE\nOF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.\n\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fsandialabs%2Fquends","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fsandialabs%2Fquends","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fsandialabs%2Fquends/lists"}