Does it support specific SDO/AIA telescope settings?

Yes, it includes built-in support for all standard SDO/AIA wavelengths (171A, 193A, 211A, 304A, etc.) and automatically applies the correct color scales.

How does it handle high dynamic range solar data?

It provides various normalization stretches such as AsinhStretch and LogStretch, which are essential for revealing faint coronal features alongside bright active regions.

What data formats are compatible with SSW-Viz?

SSW-Viz is designed to work with FITS (Flexible Image Transport System) files, the standard format for solar physics, using the SunPy and Astropy libraries.

Can I use this skill to evaluate AI models?

Absolutely. It contains specific patterns for side-by-side comparisons of model predictions versus ground truth, including the generation of difference/error maps.

Can I create video files of solar activity?

Yes, the skill includes a pattern for generating MP4 time-lapse animations from a sequence of FITS files using Matplotlib's animation module.

Solar Data Visualization (SSW-Viz)

Name: Solar Data Visualization (SSW-Viz)
Author: tykimos

bytykimos

0•

数据科学与机器学习

Visualizes solar observation data, EUV imagery, and machine learning model outputs using SunPy and Matplotlib.

SSW-Viz is a specialized visualization suite for Claude Code tailored for solar physics and space weather research. It provides standardized implementation patterns for rendering FITS files, applying wavelength-specific SDO/AIA colormaps, and performing advanced image normalization like Asinh and Log stretches. The skill excels at comparative analysis, allowing users to generate multi-wavelength panels, before-and-after preprocessing views, and detailed ML model evaluation maps. Whether you are generating publication-quality solar plots or creating time-lapse animations of solar events, SSW-Viz streamlines the complex workflow of solar data representation.

主要功能

01ML model output evaluation with automated error and difference mapping

02Automatic SDO/AIA wavelength-specific colormap mapping

03Multi-wavelength comparison panels and preprocessing benchmarks

040 GitHub stars

05FITS-based time-lapse animation generation for solar event tracking

06Advanced image normalization including Asinh, Log, and Histogram Equalization

使用场景

01Visualizing pixel intensity distributions and data quality during preprocessing

02Validating solar image enhancement or translation ML models against ground truth

03Comparing solar atmospheric features across different EUV wavelengths

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add tykimos/ssw-plugin ssw-viz

For use in Claude.ai and ChatGPT

Download Skill