phase-portrait-generator

Generate phase portraits for 2D dynamical systems. Use when visualizing vector fields, nullclines, and trajectories.

16 stars

Best use case

phase-portrait-generator is best used when you need a repeatable AI agent workflow instead of a one-off prompt.

Generate phase portraits for 2D dynamical systems. Use when visualizing vector fields, nullclines, and trajectories.

Teams using phase-portrait-generator should expect a more consistent output, faster repeated execution, less prompt rewriting.

When to use this skill

You want a reusable workflow that can be run more than once with consistent structure.

When not to use this skill

You only need a quick one-off answer and do not need a reusable workflow.
You cannot install or maintain the underlying files, dependencies, or repository context.

Installation

Claude Code / Cursor / Codex

$curl -o ~/.claude/skills/phase-portrait-generator/SKILL.md --create-dirs "https://raw.githubusercontent.com/plurigrid/asi/main/plugins/asi/skills/phase-portrait-generator/SKILL.md"

Manual Installation

Download SKILL.md from GitHub
Place it in .claude/skills/phase-portrait-generator/SKILL.md inside your project
Restart your AI agent — it will auto-discover the skill

How phase-portrait-generator Compares

Feature / Agent	phase-portrait-generator	Standard Approach
Platform Support	Not specified	Limited / Varies
Context Awareness	High	Baseline
Installation Complexity	Unknown	N/A

Frequently Asked Questions

What does this skill do?

Generate phase portraits for 2D dynamical systems. Use when visualizing vector fields, nullclines, and trajectories.

Where can I find the source code?

You can find the source code on GitHub using the link provided at the top of the page.

SKILL.md Source

# Phase Portrait Generator

Generates phase portraits showing vector fields and trajectories in 2D state space.

## When to Use
- Visualizing 2D autonomous systems
- Plotting nullclines and equilibria
- Trajectory analysis in phase space

## GF(3) Role
PLUS (+1) Generator - creates visual outputs from differential equations.

## Quick Example

```python
import numpy as np
import matplotlib.pyplot as plt

def phase_portrait(f, xlim=(-3,3), ylim=(-3,3), density=20):
    x = np.linspace(*xlim, density)
    y = np.linspace(*ylim, density)
    X, Y = np.meshgrid(x, y)
    U, V = f(X, Y)
    plt.streamplot(X, Y, U, V, density=1.5)
    plt.xlabel('x'); plt.ylabel('y')

# Van der Pol oscillator
phase_portrait(lambda x, y: (y, -x + (1 - x**2) * y))
```

## Integration with bifurcation skills

Forms triad with:
- `bifurcation` (0): detects transitions
- `bifurcation-generator` (+1): parameter space
- `phase-portrait-generator` (+1): state space