v2.3.0 — Benchmark it. Regress it. Ship it.

v2.3.0 — Benchmark it. Regress it. Ship it.

AR6 plotting now has cross-library benchmarks, verified colour assets, collision-aware labels, and reference-figure contracts.

Highlights

• Native Figanos 0.7.0 cross-library benchmark on shared scenario and map inputs
• Collision-aware label_line_ends()
• Fixed-size map_panel_grid()
• add_uncertainty_legend() for agreement, missing data, and significance
• Reference width / height / panel-count / projection checks in Python and ar6plot
• IPCC-WG1/colormaps pinned to b7d3849d4fa521d2583b91360e875e38f191d209
• Git blob verification for all 43 official RGB assets
• Verified colormap source metadata used by strict map audit
• Structured contracts for AR6 WGI Chapter 3 Figure 3.2b, Chapter 6 Figure 6.18 source, and Chapter 10 Figure 10.20b
• PNG regression metrics: dimensions, mean absolute error, changed-pixel fraction, thumbnail error, SHA256
• Compact audit output with requested checks only
• Rebuilt GitHub README with benchmark and regression data front and center

Benchmark snapshot

Check	Figanos 0.7.0	ar6-sciplot 2.3.0
WGI-2022 SSP colours	exact	exact
SSP endpoint label collision	SSP1-1.9 / SSP1-2.6	none
3-panel controlled map	180 × 72 mm	180 × 72 mm
Xarray-native faceting	yes	explicit panel grid
Report-era SSP profile	—	yes
Reference geometry audit	—	yes

Reference regression

The committed AR6 source-data gallery reproduces at zero pixel error in CI.

Chapter 2 Figure 2.3      exact PNG regression
Chapter 3 Figure 3.2b     contract + exact PNG regression
Chapter 6 Figure 6.18     contract + exact PNG regression
Chapter 10 Figure 10.20b  contract + exact PNG regression

Install

python -m pip install -U ar6-sciplot

Climate extras:

python -m pip install -U "ar6-sciplot[climate]"