eofs-cookbook
Cookbook covering empirical orthogonal function (EOF) analysis and examples of its application to climate data
Science Score: 67.0%
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✓CITATION.cff file
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✓codemeta.json file
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✓.zenodo.json file
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✓DOI references
Found 3 DOI reference(s) in README -
✓Academic publication links
Links to: zenodo.org -
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○Scientific vocabulary similarity
Low similarity (15.3%) to scientific vocabulary
Repository
Cookbook covering empirical orthogonal function (EOF) analysis and examples of its application to climate data
Basic Info
- Host: GitHub
- Owner: ProjectPythia
- License: apache-2.0
- Language: Jupyter Notebook
- Default Branch: main
- Homepage: https://projectpythia.org/eofs-cookbook/
- Size: 131 MB
Statistics
- Stars: 8
- Watchers: 2
- Forks: 3
- Open Issues: 3
- Releases: 4
Metadata Files
README.md
EOFs Cookbook
This Project Pythia Cookbook covers empirical orthogonal function analysis and its application to climate data.
Motivation
Empirical orthogonal function (EOF) analysis is an essential tool for studying the variability of the atmosphere–ocean system. Meteorological and oceanographic data is noisy and multidimensional, but an EOF analysis allows us to pull out patterns from the data that might otherwise be difficult to find. The goal of this cookbook is to provide background and context to the analysis alongside practical examples of carrying out the analysis using Python packages.
Authors
Contributors
Structure
This cookbook currently has one section that covers the basics of EOF analysis.
Foundations
This section includes three notebooks: - Introduction to EOFs - EOFs with NumPy - Finding Climate Modes with EOFs
Running the Notebooks
You can either run the notebook using Binder or on your local machine.
Running on Binder
The simplest way to interact with a Jupyter Notebook is through
Binder, which enables the execution of a
Jupyter Book in the cloud. The details of how this works are not
important for now. All you need to know is how to launch a Pythia
Cookbooks chapter via Binder. Simply navigate your mouse to
the top right corner of the book chapter you are viewing and click
on the rocket ship icon, (see figure below), and be sure to select
“launch Binder”. After a moment you should be presented with a
notebook that you can interact with. I.e. you’ll be able to execute
and even change the example programs. You’ll see that the code cells
have no output at first, until you execute them by pressing
{kbd}Shift+{kbd}Enter. Complete details on how to interact with
a live Jupyter notebook are described in Getting Started with
Jupyter.
Running on Your Own Machine
If you are interested in running this material locally on your computer, you will need to follow this workflow:
- Clone the
https://github.com/ProjectPythia/eofs-cookbookrepository:
bash
git clone https://github.com/ProjectPythia/eofs-cookbook.git
- Move into the
eofs-cookbookdirectorybash cd eofs-cookbook - Create and activate your conda environment from the
environment.ymlfilebash conda env create -f environment.yml conda activate eofs-cookbook-dev - Move into the
notebooksdirectory and start up Jupyterlabbash cd notebooks/ jupyter lab
Owner
- Name: Project Pythia
- Login: ProjectPythia
- Kind: organization
- Email: projectpythia@ucar.edu
- Location: United States of America
- Website: projectpythia.org
- Twitter: Project_Pythia
- Repositories: 21
- Profile: https://github.com/ProjectPythia
Community learning resource for Python-based computing in the geosciences
Citation (CITATION.cff)
cff-version: 1.2.0
message: "If you use this cookbook, please cite it as below."
authors:
# add additional entries for each author -- see https://github.com/citation-file-format/citation-file-format/blob/main/schema-guide.md
- family-names: Ford
given-names: Robert R.
orcid: https://orcid.org/0000-0001-5483-4965
website: https://github.com/r-ford
affiliation: University at Albany (State University of New York)
- name: "EOFs Cookbook contributors" # use the 'name' field to acknowledge organizations
website: "https://github.com/ProjectPythia/eofs-cookbook/graphs/contributors"
title: "EOFs Cookbook"
abstract: "Description of empirical orthogonal function (EOF) analysis and examples of its application to climate data."
GitHub Events
Total
- Issues event: 7
- Watch event: 2
- Delete event: 1
- Issue comment event: 12
- Push event: 77
- Pull request event: 7
- Create event: 4
Last Year
- Issues event: 7
- Watch event: 2
- Delete event: 1
- Issue comment event: 12
- Push event: 77
- Pull request event: 7
- Create event: 4
Issues and Pull Requests
Last synced: 6 months ago
All Time
- Total issues: 2
- Total pull requests: 5
- Average time to close issues: 10 months
- Average time to close pull requests: about 1 hour
- Total issue authors: 1
- Total pull request authors: 4
- Average comments per issue: 0.5
- Average comments per pull request: 1.0
- Merged pull requests: 3
- Bot issues: 0
- Bot pull requests: 1
Past Year
- Issues: 2
- Pull requests: 5
- Average time to close issues: 10 months
- Average time to close pull requests: about 1 hour
- Issue authors: 1
- Pull request authors: 4
- Average comments per issue: 0.5
- Average comments per pull request: 1.0
- Merged pull requests: 3
- Bot issues: 0
- Bot pull requests: 1
Top Authors
Issue Authors
- r-ford (4)
- erogluorhan (1)
Pull Request Authors
- brian-rose (3)
- jukent (3)
- r-ford (3)
- nicrie (1)
- dependabot[bot] (1)