How does it help with parameter sensitivity?

It automates the iterative process of testing state variables against a range of control parameters, allowing you to see exactly where a system becomes unstable.

What types of bifurcations can this skill handle?

The skill is designed to visualize various types of transitions including Hopf, pitchfork, saddle-node, and transcritical bifurcations.

Can I use this for the logistic map?

Yes, it is highly effective at visualizing period-doubling routes to chaos and attractor maps for the logistic map and similar iterative functions.

What Python libraries are required for the output?

The skill typically generates code that utilizes standard scientific libraries such as NumPy for computation and Matplotlib for high-quality plotting.

Does it provide mathematical analysis or just visualization?

This skill primarily focuses on generating the visual diagrams (Generator role), though it is designed to work alongside classification skills to provide a complete analysis.

Bifurcation Diagram Generator

Name: Bifurcation Diagram Generator
Author: plurigrid

byplurigrid

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데이터 과학 및 ML

Generates visual bifurcation diagrams to track stability transitions and behavior changes in dynamical systems.

소개

The Bifurcation Generator is a specialized tool for Claude Code designed to help researchers and developers visualize how the qualitative behavior of a dynamical system changes as parameters vary. It automates the complex process of performing parameter sweeps and plotting attractors, making it easy to identify critical transitions such as Hopf, pitchfork, and saddle-node bifurcations. By translating mathematical models into clear visual representations, this skill enables a deeper understanding of stability boundaries and chaotic regimes in everything from ecological models to chemical oscillators.

주요 기능

Identifies stability boundaries in complex systems
Automates parameter sweeps across defined ranges
Generates optimized Python code using NumPy and Matplotlib
2 GitHub stars
Supports visualization of attractor states and chaotic transitions
Visualizes Hopf, pitchfork, and saddle-node bifurcations

사용 사례

Analyzing stability transitions in chemical reaction-diffusion systems
Mapping chaotic behavior and period-doubling in the logistic map
Identifying phase transitions in physical and engineering simulations

소개

주요 기능

Identifies stability boundaries in complex systems
Automates parameter sweeps across defined ranges
Generates optimized Python code using NumPy and Matplotlib
2 GitHub stars
Supports visualization of attractor states and chaotic transitions
Visualizes Hopf, pitchfork, and saddle-node bifurcations

사용 사례

Analyzing stability transitions in chemical reaction-diffusion systems
Mapping chaotic behavior and period-doubling in the logistic map
Identifying phase transitions in physical and engineering simulations