Saved in:
| Main Authors: | , |
|---|---|
| Format: | Recurso digital |
| Language: | |
| Published: |
Zenodo
2025
|
| Online Access: | https://doi.org/10.5281/zenodo.15495546 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1866901688685690880 |
|---|---|
| author | Steiner, Matthias Flores Orozco, Adrian |
| author_facet | Steiner, Matthias Flores Orozco, Adrian |
| contents | <p><strong>Description:</strong></p> <p>This repository provides datasets, mesh configuration files, and Python scripts used for 3D complex resistivity inversion (electrical resistivity tomography with induced polarization) as presented in the accompanying manuscript. The inversion was performed using the pyGIMLi framework.</p> <p><strong>Contents:</strong></p> <ul> <li> <p><code>01_data/</code>: Field ERT datasets (<code>.ohm</code> files) at a single frequency, containing apparent resistivity and phase (IP) measurements.</p> </li> <li> <p><code>02_mesh/</code>: Mesh configuration files (<code>.cfg</code>) and a mesh generation script (<code>get_paradomain.py</code>). Meshes and parameter domains are created using the functionalities of BERT (Boundless Electrical Resistivity Tomography), a high-level module within pyGIMLi.</p> </li> <li> <p><code>03_inversion/</code>: Main inversion script (<code>inversion_3d.py</code>) for resistivity and phase angle inversions. Outputs include VTK files for visualization.</p> </li> </ul> <p><strong>Usage Notes:</strong></p> <ul> <li> <p>File paths in scripts may need adjustment to match local directory structures.</p> </li> <li> <p>Phase data are expected in milliradians and are internally converted to radians.</p> </li> <li> <p>Inversion parameters (e.g., regularization, error assumptions) are configurable in the script.</p> </li> </ul> <p><strong>Requirements:</strong></p> <ul> <li> <p>Python 3.x</p> </li> <li> <p><a href="https://www.pygimli.org" target="_new" rel="noopener">pyGIMLi</a>, including BERT</p> </li> <li> <p>numpy</p> </li> <li> <p>matplotlib</p> </li> </ul> |
| format | Recurso digital |
| id | zenodo_https___doi_org_10_5281_zenodo_15495546 |
| institution | Zenodo |
| language | |
| publishDate | 2025 |
| publisher | Zenodo |
| record_format | zenodo |
| spellingShingle | 3D Complex Resistivity Survey of a Known Burial Site at an Inactive Cemetery Steiner, Matthias Flores Orozco, Adrian <p><strong>Description:</strong></p> <p>This repository provides datasets, mesh configuration files, and Python scripts used for 3D complex resistivity inversion (electrical resistivity tomography with induced polarization) as presented in the accompanying manuscript. The inversion was performed using the pyGIMLi framework.</p> <p><strong>Contents:</strong></p> <ul> <li> <p><code>01_data/</code>: Field ERT datasets (<code>.ohm</code> files) at a single frequency, containing apparent resistivity and phase (IP) measurements.</p> </li> <li> <p><code>02_mesh/</code>: Mesh configuration files (<code>.cfg</code>) and a mesh generation script (<code>get_paradomain.py</code>). Meshes and parameter domains are created using the functionalities of BERT (Boundless Electrical Resistivity Tomography), a high-level module within pyGIMLi.</p> </li> <li> <p><code>03_inversion/</code>: Main inversion script (<code>inversion_3d.py</code>) for resistivity and phase angle inversions. Outputs include VTK files for visualization.</p> </li> </ul> <p><strong>Usage Notes:</strong></p> <ul> <li> <p>File paths in scripts may need adjustment to match local directory structures.</p> </li> <li> <p>Phase data are expected in milliradians and are internally converted to radians.</p> </li> <li> <p>Inversion parameters (e.g., regularization, error assumptions) are configurable in the script.</p> </li> </ul> <p><strong>Requirements:</strong></p> <ul> <li> <p>Python 3.x</p> </li> <li> <p><a href="https://www.pygimli.org" target="_new" rel="noopener">pyGIMLi</a>, including BERT</p> </li> <li> <p>numpy</p> </li> <li> <p>matplotlib</p> </li> </ul> |
| title | 3D Complex Resistivity Survey of a Known Burial Site at an Inactive Cemetery |
| url | https://doi.org/10.5281/zenodo.15495546 |