How does this skill help with fold analysis?

It can plot poles to bedding, fit a best-fit great circle (girdle) to those poles, and automatically calculate the fold axis as the pole to that girdle.

Which geological measurement formats are supported?

The skill supports Strike/Dip (Right-Hand Rule), Dip Direction/Dip, and Trend/Plunge formats for linear and planar data.

Is the output compatible with standard Matplotlib functions?

Yes, mplstereonet acts as an extension to Matplotlib, meaning you can use standard commands for titles, legends, and saving figures (PNG, PDF, SVG).

Can I generate density contours for large datasets?

Yes, it provides functions for Kamb, Schmidt, and exponential Kamb contouring to visualize point density across a stereonet.

Structural Geology Stereonets

Name: Structural Geology Stereonets
Author: SteadfastAsArt

bySteadfastAsArt

•

Data Science & ML

Generates professional stereographic projections and performs structural geology analysis using Matplotlib and mplstereonet.

This skill enables Claude to perform specialized structural geology tasks by leveraging the mplstereonet library. It allows for the creation of lower-hemisphere stereographic projections to visualize orientation data, including planes (as great circles or poles) and lineations (trend/plunge). Beyond visualization, the skill supports advanced structural analysis such as density contouring (Kamb or Schmidt methods), calculating mean orientations, and performing fold axis analysis via pi-diagrams, making it a powerful tool for geoscientists automating geological data processing and figure generation.

Key Features

01Plot planes and lineations using strike/dip, dip direction, or trend/plunge formats

02Create lower-hemisphere stereographic projections integrated with Matplotlib

0312 GitHub stars

04Perform automated fold analysis by fitting best-fit great circles (girdles) to orientation data

05Convert between various geological coordinate systems and measurement conventions

06Generate statistical density contours using Kamb, Schmidt, or exponential methods

Use Cases

01Batch processing large datasets of orientation data into publication-quality density plots

02Analyzing field bedding measurements to determine regional fold axes and orientations

03Visualizing joint sets, fault planes, and slip vectors for geotechnical or structural reports

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add steadfastasart/geoscience-skills mplstereonet

For use in Claude.ai and ChatGPT

Download Skill