---

name: trend-radar-heatmap-figures description: "Build publication-ready trend panels, event-annotated cumulative time series, normalized radar comparisons, heatmaps, matrix panels, and shared legends." disable-model-invocation: true metadata: disco-role: operating license: NO_LICENSE

Trend, Radar, and Heatmap Figures

Use this sub-skill when a figures4papers task asks for publication-ready matplotlib figures involving line or sweep curves, cumulative time series, event annotations, radar/polar benchmark comparisons, seaborn or matplotlib heatmaps, matrix-style comparison panels, colorbars, per-cell labels, or shared/legend-only layouts.

Route here for

• Line, sweep, post-training, or ablation curves with 2-4 readable series per axis.
• Cumulative time-series panels with parsed month/date labels, filled areas, hatch overlays, and event arrows.
• Radar or polar benchmark comparisons where each spoke has its own natural score scale and tick labels.
• Heatmaps with row/column totals, colorbars, annotations, per-cell text contrast, or summary/improvement rows.
• Wide comparison panels that mix trends, heatmaps, matrix blocks, and a dedicated shared-legend axis.

Route elsewhere

• Grouped bars, horizontal ablation bars, log bars, or print-safe bar comparisons: use bar-comparison-figures.
• Conceptual manifolds, spheres, scatter clouds, KDE contours, Swiss-roll diagrams, or schematic arrows: use concept-manifold-diagrams.
• Cross-cutting palette, font, export, and environment helpers: use the root figures4papers references/scripts when they are available; this sub-skill does not require them.

Read or run

• Read references/trend-radar-heatmap-recipes.md before implementing any trend, radar, heatmap, matrix, colorbar, or shared-legend figure. It contains the data contracts, normalization formulas, date/event handling, layout recipes, and output validation checklist.
• Read references/troubleshooting.md when the figure has shape mismatches, date/event problems, malformed radar polygons, bad tick labels, unreadable heatmap text, colorbar issues, optional TeX/seaborn failures, or missing output files.
• Run scripts/trend_radar_heatmap_template.py to create safe built-in examples for --example trend, --example radar, or --example heatmap. Use it as a self-contained starting point when no project-specific plotting code exists.

Operating checklist

1. Identify the figure family: trend/event, radar, heatmap, matrix panel, or mixed layout.
2. Validate the data contract from the recipes before plotting: array rank, label counts, method/order alignment, finite numeric values, and date coverage.
3. Keep figures self-contained and headless-friendly: no network, credentials, hidden global state, or dependence on external source checkouts.
4. Prefer non-TeX defaults. Enable TeX only when the runtime explicitly has a LaTeX installation and the target venue requires TeX-rendered labels.
5. Save with deterministic output names and verify that every requested file exists, is non-empty, and can be opened by matplotlib/Pillow or a simple file-size check.