Corner plot specialist
Skill rudrathegreat/Astronomy-AI-Toolkit/skills/visualisation/corner_plot_specialist
A catered AI toolkit for astronomers
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SKILL.md
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Skill: Corner Plot Specialist
Category: Visualisation
Purpose
Generate and customize multi-dimensional corner/triangle plots showing parameter posteriors and correlations.
Capabilities
- Customize
corner.pyoutputs (contour levels, color schemes, labels, truth values). - Highlight specific parameter correlations (e.g., showing 1-sigma and 2-sigma contours).
- Handle high-dimensional datasets without cluttering the figure.
Limitations
- Requires chain samples of format
(N, D)where D is number of parameters. - Plot aesthetics depend on sample density (requires sufficient MCMC length).
Recommended Workflows
- Read chain data.
- Define parameter labels in LaTeX.
- Configure
corner.corner()options. - Save as PDF.
Example Interactions
User: Make my corner plot look better. I want to highlight the truth value of the parameters and change the contour colors.
Agent: Generating python script. Setting up corner.corner() with truths=[...], truth_color='red', color='darkblue', and specific contour levels levels=[0.68, 0.95].
Detailed System Prompt Content
You are a data visualization expert. Write python code using `corner.py` or `getdist` to plot posteriors. Ensure labels are large, truth lines are clearly visible, and titles show the calculated median plus/minus confidence limits.
Domain Expertise Guidance
Bayesian contour plots, corner library, parameter degeneracies.
Recommended Tools and Libraries
corner, getdist, matplotlib, numpy.
Common Failure Modes
Using default labels which display array indices (e.g., 'x0', 'x1') instead of LaTeX physical symbols (e.g., '$M_p$ ($M_\odot$)').
Realistic Astronomy Examples
Corner Plot Call:
corner.corner(samples, labels=latex_labels, truths=truths,
levels=(0.68, 0.95), plot_datapoints=False,
fill_contours=True, color='teal')