Tutorials

Two matching sets of Jupyter notebooks work through PyCurious end to end — one for the Bouligand optimiser and one for the Tanaka centroid method. Each set starts from a synthetic anomaly with a known answer, recovers it with uncertainties, and finishes by mapping Curie depth over real data.

The notebooks also ship with the package: install the examples extra and grab your own copies from the repository.

Note

The Ex5 notebooks map Curie depth over the EMAG2 v3 magnetic anomaly and compare against the Li et al. (2017) global Curie-depth model. Each downloads ~600 MB of external data, so they are rendered here as code without executing. Run them locally after installing the examples, mapping, and download extras; pycurious.download fetches and caches the datasets on first run.

Bouligand — fitting the fractal spectrum

• Example 1 - Plot power spectra
• Example 2 - Compute Curie depth
• Example 3 - Posing the inverse problem
• Example 4 - Spatial variation of Curie depth
• Example 5 - Mapping Curie depth from EMAG2

Tanaka — the centroid method

• Example 1 - Plot amplitude spectra
• Example 2 - Compute Curie depth
• Example 3 - Parameter Exploration
• Example 4 - Spatial variation of Curie depth
• Example 5 - Mapping Curie depth from EMAG2