---

name: visualization description: "Plot, animate, and export HyperTools figures." disable-model-invocation: true metadata: disco-role: operating license: MIT

Visualization

Use this sub-skill when the request is about plotting, rendering, animating, or exporting HyperTools figures rather than choosing the analysis pipeline.

Owns

• hypertools.plot(...) for static matplotlib plots, plotly renders, and animations
• hypertools.set_interactive_backend(...) plus backend='auto', 'matplotlib', and 'plotly'
• styling, fmt, markers, line styles, palette, hue, legend, names, labels, colorbar, title, and axis-label kwargs
• surface, density, and save_path
• row-MultiIndex plotting behavior in hyp.plot
• streaming plot parameters: stream_init, stream_chunk, stream_max, and stream_window
• predict= as a visual overlay only; model selection stays in ../forecasting/SKILL.md
• return_model=True plot bundles when the caller wants the fitted plotting bundle back

Route away

• Choose reduction / alignment / clustering / manipulation stages in ../pipeline/SKILL.md
• Resolve loaders, save/load source details, and hyp.io.lsl_stream in ../io/SKILL.md
• Choose forecast or imputation models in ../forecasting/SKILL.md

Read first

• ./references/plot-reference.md
• ./references/workflows.md
• ./references/troubleshooting.md

Quick smoke

Run:

python ./scripts/smoke_plot.py --feature static --backend auto

For streaming plots, remember that the backend is always matplotlib. For animation, plotly returns a Figure with frames; matplotlib returns a HyperAnimation or (fig, ani)-style result.