| _version_ | 1866901723151335424 |
|---|---|
| author | Okazaki, Tomohisa |
| author_facet | Okazaki, Tomohisa |
| contents | <p><span lang="EN-US">This repository provides tools for estimating crustal strain rate fields from discrete horizontal velocity data using Bayesian linear regression with basis function expansion. A key feature is objective determination of the regularization strength. Users can choose from three types of regularization: mathematical (</span><span lang="EN-US">math</span><span lang="EN-US">), physical (</span><span lang="EN-US">phys</span><span lang="EN-US">), and their hybrid (</span><span lang="EN-US">hyb</span><span lang="EN-US">).</span></p> <p><span lang="EN-US">The programs are written in <em>Python</em> using the following libraries: <em>Numpy, Scipy, Pickle, </em>and<em> Matplotlib</em>. They are organized into four functional components:</span></p> <p><span lang="EN-US"><span>1.<span> </span></span></span><span lang="EN-US">Data organization</span></p> <p><span lang="EN-US"><span>2.<span> </span></span></span><span lang="EN-US">Hyperparameter optimization</span></p> <p><span lang="EN-US"><span>3.<span> </span></span></span><span lang="EN-US">Strain rate estimation</span></p> <p><span lang="EN-US"><span>4.<span> </span></span></span><span lang="EN-US">Visualization</span></p> <p><span lang="EN-US">Component 1 handles the preprocessing of velocity data. Components 2 and 3 form the core of the method. Component 4 generates figures of the results.</span></p> |
| format | Recurso digital |
| id | zenodo_https___doi_org_10_5281_zenodo_16014772 |
| institution | Zenodo |
| language | |
| publishDate | 2025 |
| publisher | Zenodo |
| record_format | zenodo |
| spellingShingle | Program Codes for Crustal Strain Rate Estimation Using Basis Function Expansion Okazaki, Tomohisa <p><span lang="EN-US">This repository provides tools for estimating crustal strain rate fields from discrete horizontal velocity data using Bayesian linear regression with basis function expansion. A key feature is objective determination of the regularization strength. Users can choose from three types of regularization: mathematical (</span><span lang="EN-US">math</span><span lang="EN-US">), physical (</span><span lang="EN-US">phys</span><span lang="EN-US">), and their hybrid (</span><span lang="EN-US">hyb</span><span lang="EN-US">).</span></p> <p><span lang="EN-US">The programs are written in <em>Python</em> using the following libraries: <em>Numpy, Scipy, Pickle, </em>and<em> Matplotlib</em>. They are organized into four functional components:</span></p> <p><span lang="EN-US"><span>1.<span> </span></span></span><span lang="EN-US">Data organization</span></p> <p><span lang="EN-US"><span>2.<span> </span></span></span><span lang="EN-US">Hyperparameter optimization</span></p> <p><span lang="EN-US"><span>3.<span> </span></span></span><span lang="EN-US">Strain rate estimation</span></p> <p><span lang="EN-US"><span>4.<span> </span></span></span><span lang="EN-US">Visualization</span></p> <p><span lang="EN-US">Component 1 handles the preprocessing of velocity data. Components 2 and 3 form the core of the method. Component 4 generates figures of the results.</span></p> |
| title | Program Codes for Crustal Strain Rate Estimation Using Basis Function Expansion |
| url | https://doi.org/10.5281/zenodo.16014772 |