dlab-figure-style

name	dlab-figure-style
description	decision-lab house figure style for matplotlib. Use whenever creating, styling, or saving any matplotlib figure, chart, or plot. The environment is already styled — this skill covers only the rules the style config cannot enforce.

decision-lab figure style

The session environment already styles every matplotlib figure (palette color cycle, fonts, clean spines, marker edges, legend, figure size) via an rc file activated through the MATPLOTLIBRC environment variable. Your job is to NOT undo that, and to follow the few rules the rc cannot enforce.

Never override the house style

• NEVER call sns.set_theme(), sns.set(), sns.set_style(), or plt.style.use(...) — one such call silently destroys the entire house style. If you use seaborn, import it plainly (import seaborn as sns) and pass colors/axes explicitly; do not apply its themes.
• Do NOT set fonts, spine visibility, furniture colors, grid style, or rcParams in plotting scripts. The environment already did.
• Do NOT hard-code hex colors or CSS color names ("red", "tab:blue"). Colors come from the palette (below) or from the default cycle.

Use the palette by name

import dlab_plotstyle  # activates clean fill_between edges; always import it
from dlab_plotstyle import PALETTE, PALETTE_LIGHT, PALETTE_DARK

• For order-free multi-series plots, pass no colors at all — the default cycle assigns well-separated, colorblind-safe colors in a validated order.
• Set a color explicitly only when a series has fixed meaning across figures (the same channel/category in every exhibit), and take it from PALETTE.
• Use PALETTE_LIGHT for filled bands and backgrounds, PALETTE_DARK for emphasis and outlines.

The rules the rc cannot enforce

1. Scatter edge trap. ax.scatter(..., color=X) sets face AND edge to X, silently cancelling the thin white marker edge. For colored markers pass edgecolor="white", linewidth=0.6 explicitly; for white/open markers use facecolor="white", edgecolor=PALETTE_LIGHT["petrol"], linewidth=0.9.
2. Band/line layering. Draw each series' fill_between one z-layer below its own line (zorder=2*i for the fill, 2*i+1 for the line), reference lines (axhline/axvline) on top.
3. Grid OR reference lines — never both. A panel gets either a subtle grid (ax.grid(True)) or explicit reference lines (axhline/axvline for bounds, quartiles, thresholds), never the two together. If you draw reference lines, turn the grid off for that panel.
4. Legends are frameless and text is boxless. Never pass frameon=True to legend() and never wrap text/annotations in a bbox box (both are stripped by the environment anyway). Keep legends at their default size.
5. Axis limits. On continuous scatter/line panels, fit limits to the data (ax.set_xlim(x.min(), x.max())), then call dlab_plotstyle.add_axis_end_tick_caps(ax) so fitted spine ends read as bounded. Leave padding alone on categorical axes, bars, and distributions.
6. One legend per exhibit. In multi-panel figures, use one shared legend for the whole figure, not a repeated per-panel legend. Never label every data point — direct-label selectively.
7. Low-contrast series need labels. Coral, sky, and sand sit below 3:1 contrast on white — when one carries a key series, add a direct label or annotation so identity never rides on color alone.
8. Scatter with many categories. Only the first three cycle colors are mutually distinguishable in unordered point clouds. For scatter plots with more than 3 categories, add marker shapes or facet into small multiples.
9. Heatmaps and images. Use the registered house colormaps: dlab_seq (the default) for magnitudes, cmap="dlab_div" for signed data such as correlations or deltas. Never use jet, rainbow, or viridis.

Before finishing

Audit your plotting scripts programmatically — do not eyeball:

grep -nE "set_theme|set_style|plt\.style\.use|frameon=True|bbox=dict|color=[\"']#|color=[\"'](red|blue|green|orange|purple|tab:)" *.py

Any hit is a violation: replace with palette names or the default cycle.