This repository provides a suite of geostatistical tools, including functions to compute the ground-motion correlation structure according to the relations by Bodenmann et al. (2023), and to do Kriging interpolation.
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Example 1 (Python backend): Ordinary Kriging using the
$\rho_{E}$ correlation model. -
Example 1 (Cython backend): Ordinary Kriging using the
$\rho_{E}$ correlation model. -
Example 2 (Python backend): Ordinary Kriging using the
$\rho_{EA}$ correlation model. -
Example 2 (Cython backend): Ordinary Kriging using the
$\rho_{EA}$ correlation model. - Example 3 (Python backend): Ordinary Kriging using a user-defined correlation model.
- Example 3 (Cython backend): Ordinary Kriging using a user-defined correlation model.
- Example 4 (Python backend): Krige a map using a user-defined correlation model.
- Example 4 (Cython backend): Krige a map using a user-defined correlation model.
- Implementation of the Kriging code benefited from Scott Brandenberg's random field python package.
- The cython implementations for spatial correlation are based on Lukas Bodenmann's python functions.
Pretell, R. (2026). geostats: A suite of geostatistical tools (v1.0.2). Zenodo. https://doi.org/10.5281/zenodo.10253690
For any questions or comments, contact Renmin Pretell (rpretell at unr dot edu).