/scientific-visualization

name: scientific-visualization
description: Publication-quality chart patterns for agentsociety-analysis Stage 4 refine — Okabe-Ito palettes, seaborn CI bands, small multiples, error bars, grayscale-safe encoding. Use when writing run-code chart scripts or reviewing chart QA failures.

Scientific Visualization (bundled support)

Active only during **agentsociety-analysis** explore/refine/produce. Does not replace figure contracts or harness gates.

When to read

• Writing `charts/chart_NN_*.py` via `run-code`
• Chart failed squint test or `validate-chart`
• User asks for better-looking or clearer plots

Read order

1. `references/charts.md` 2. `references/chart-recipes.md` 3. `assets/chart_scaffold.reference.py` 4. `references/api.md`

Absorbed sources (patterns only — no external deps required)

| Source | Absorbed | | -------------------------------- | --------------------------------------------------------------------------- | | K-Dense scientific-visualization | Okabe-Ito, CI/error bars, multi-panel labels, grayscale test | | seaborn | `set_theme(ticks, paper, colorblind)`, `lineplot` CI, `boxplot`+`stripplot` | | Observable Plot | Defaults-first workflow, faceting, shared scales | | Tufte | Small multiples, chart junk removal | | Cursor canvas | Mandatory metric titles, axis units, source in caption |

AgentSociety overrides

• English-only legend text
• matplotlib `Agg` required
• Simulation caveats — no overstated significance
• Semantic palette locked per condition across report
• PNG in `assets/` required; interactive HTML optional

Quick invoke

Copy scaffold → pick recipe letter (A–G) → fill SQL/pandas → `save_chart_bundle` → rubric → `compose-figure` if needed.