icarus-figures

# Icarus Figures Turn a dataset + a claim into a **publication-grade figure** — one a top-journal editor accepts with no revision request. Default stack: **matplotlib/seaborn for data figures, original TikZ for hero/method figures**, both reproducible (script + data file), exported as PDF + PNG + SVG. ## First read Open `references/figure-cookbook.md` and work in this order: 1. **§0b (the quality bar)** — the four axes (Depth · Elegance · Unimpeachable · Visible gap). Internalize this *before* plotting; it is the acceptance test, not an afterthought. 2. **§0a (Figure Contract)** — write the one-line `core_claim` + hero panel + what stats go on the figure, before any code. 3. **§0 style preset** — `from _style import paper_style, save` (the preset lives in `scripts/_style.py`). Never hand-edit rcParams per figure. 4. **§A archetypes A1–A13** — pick the matching template (time series+CI, sorted bar, grouped bar, residual, heatmap, scatter+fit, Pareto, tornado, confusion, phase, network), paste, swap the data path + labels, run. ## For a hero / method / framework figure (the one that carries the paper) **Read `references/framework-figures.md`** — the deep-dive, with **five** compilable heroes to paste from (P1 pipeline, P2 paradigm-swimlanes, + T4 graphical-model / data-tensor / matrix-fit), the borrowable TikZ techniques, and curated journal-grade resources. The rule to internalize first: **never a generic boxes-and-arrows flowchart** — embed the *real method object* (a distribution, a before/after scatter, a decision region), not a text label. Route through the cookbook: **§I** composition paradigms P1–P6 → **§J** craft spec → **§K** original standalone TikZ (compiled to PDF, `\includegraphics`, zero compile risk). framework-figures.md walks all three with worked examples. ## Hard rules (non-negotiable) - **Reproducible only**: every figure is generated by a committed script that reads data from a file path. **No inline data > 20 rows. No AI-generated images** (unreproducible). - **Three-format vector**: `save()` writes PDF + PNG + SVG (text stays editable in SVG/PDF). Never ship a 72-dpi PNG. - **Style preset, once**: call `paper_style(...)` at the top; do not tweak rcParams per script. - **Colorblind + grayscale safe**: use the palette + redundant marker/linestyle so every series survives a B&W print and deuteranopia. - **Units + N + uncertainty on the figure**: axis labels carry units; N annotated; CI band / error bars shown (§0b axis 3). - **Acceptance test (run it, don't eyeball it)**: before declaring done, run the gate `python scripts/critique.py scripts/figN_<name>.py` — it enforces the §F checklist + §G anti-patterns mechanically (must report **no FAIL**) and prints the four judgment prompts. Then answer the four §0b axes by hand using `references/figure-critique.md` (the mechanical floor is defense; the four judgment ticks are the offense). A figure that merely "plots correctly" — or merely passes the script — is not done. ## Optional front-ends / references - **§M Origin** — allowed only behind the M1–M6 guardrails (same-source CSV, journal .otp template, vector three-format, reproducible matplotlib fallback for key figures). Hero figures never go through Origin. - **§L external template library** — if `<TEMPLATE_LIB>` is set in `CLAUDE.md`, use it as a *design reference* (imitate composition/palette/chart-type, redraw original); never paste foreign output into the paper. ## Captions After the figure passes the critique gate (`references/figure-critique.md`), write the caption with `references/caption-and-quality.md` — the caption states the **conclusion**, not "Figure shows X"; reference figures in text as "as in Fig. 3", never "the figure below". ## Output locations - scripts → `scripts/figN_<short-name>.py` (or `.tex` for TikZ) - figures → `outputs/figures/figN_<short-name>.{pdf,png,svg}` - register each in `outputs/figures/figure_manifest.csv` (id, path, claim, source data, generation script).