feat(altair): implement ridgeline-basic

[github-actions]

Implementation: ridgeline-basic - python/altair

Implements the python/altair version of ridgeline-basic.

File: plots/ridgeline-basic/implementations/python/altair.py

Parent Issue: #923

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🤖 impl-generate workflow

[claude]

AI Review - Attempt 1/3

Image Description

Light render (plot-light.png): Warm off-white background (#FAF8F1). Bold dark title "Monthly Temperature Distribution · ridgeline-basic · altair · anyplot.ai" centered at top. Twelve row labels (Jan–Dec) in soft-dark ink, right-aligned left of each ridge. X-axis "Temperature (°C)" with tick labels −15 to 40 in dark/soft-dark ink at the bottom. All text confirmed legible with generous, unclipped margins on every edge (verified via pixel crops of all four borders). Twelve stacked, partially-overlapping KDE density curves (one per month, chronological top-to-bottom), filled with a smooth Imprint-sequential gradient from brand green #009E73 (Jan) to blue #4467A3 (Dec), each with a thin soft-ink stroke outline. Ridge shapes track the seasonal cycle realistically (cold/left-shifted in Jan/Dec, warm/right-shifted in Jul/Aug).

Dark render (plot-dark.png): Warm near-black background (#1A1A17). Same layout; title, row labels, and axis text now render in light ink (#F0EFE8 primary / #B8B7B0 secondary) — clearly legible against the dark surface, no dark-on-dark failures. Data colors are pixel-identical to the light render (green→blue gradient unchanged); only chrome (background, text, baseline strokes) flipped for the theme, as required.

Both renders pass the theme-readability checklist — no light-on-light or dark-on-dark issues, no edge clipping (AR-09 clear).

Score: 93/100

Category	Score	Max
Visual Quality	29	30
Design Excellence	15	20
Spec Compliance	15	15
Data Quality	14	15
Code Quality	10	10
Library Mastery	10	10
Total	93	100

Visual Quality (29/30)

• VQ-01: Text Legibility (7/8) — all sizes explicitly set, matches style-guide defaults, legible in both themes, no overflow
• VQ-02: No Overlap (6/6) — no collisions in either render
• VQ-03: Element Visibility (6/6) — density curves clearly visible, fillOpacity + stroke give good definition
• VQ-04: Color Accessibility (2/2) — CVD-safe gradient, ink stroke around each fill
• VQ-05: Layout & Canvas (4/4) — balanced margins, verified no cut-off content on any edge
• VQ-06: Axis Labels & Title (2/2) — "Temperature (°C)" with units; Y-axis correctly shows group labels per spec
• VQ-07: Palette Compliance (2/2) — first ridge exactly #009E73, gradient is the canonical imprint_seq two-stop range, theme-correct chrome in both renders

Design Excellence (15/20)

• DE-01: Aesthetic Sophistication (6/8) - Thoughtful gradient encoding of month order, clean typography, clearly above a configured default
• DE-02: Visual Refinement (5/6) - No grid, minimal chrome, generous whitespace; per-row baseline stroke is the only un-refined touch
• DE-03: Data Storytelling (4/6) - Row order + color gradient make the seasonal cycle immediately visible, but no explicit annotation of peak/insight

Spec Compliance (15/15)

• SC-01: Plot Type (5/5) — correct ridgeline/joy plot via row-faceted density curves
• SC-02: Required Features (4/4) — stacked partial-overlap curves, Y-axis group labels, chronological order, color differentiation
• SC-03: Data Mapping (3/3) — X=temperature, Y=density→row position, all 12 groups fully visible
• SC-04: Title & Legend (3/3) — title matches this spec's established convention; no legend needed since row labels already identify groups

Data Quality (14/15)

• DQ-01: Feature Coverage (5/6) — 12 distributions vary in both mean and spread
• DQ-02: Realistic Context (5/5) — neutral, comprehensible monthly-climate scenario
• DQ-03: Appropriate Scale (4/4) — values realistic for a temperate seasonal cycle

Code Quality (10/10)

• CQ-01: KISS Structure (3/3)
• CQ-02: Reproducibility (2/2) — np.random.seed(42)
• CQ-03: Clean Imports (2/2)
• CQ-04: Code Elegance (2/2)
• CQ-05: Output & API (1/1) — plot-{THEME}.png + .html via current API

Library Mastery (10/10)

• LM-01: Idiomatic Usage (5/5) — expert use of transform_density + alt.Row faceting + negative configure_facet(spacing=...), Altair's recommended ridgeline pattern
• LM-02: Distinctive Features (5/5) — transform_density is a Vega-Lite-native declarative KDE transform unique to Altair's grammar

Score Caps Applied

• None

Strengths

• Idiomatic Altair technique: transform_density (declarative KDE) + alt.Row faceting + negative configure_facet(spacing=-13) is the canonical, distinctive way to build a ridgeline in this library
• Imprint sequential gradient (#009E73 → #4467A3) correctly applied across the 12 chronologically-ordered ridges, first ridge exactly #009E73
• Canvas gate passes exactly at 3200×1800; all four edges verified clipping-free
• Theme-adaptive chrome threaded consistently through axis/header/title/view config — both renders fully legible
• Realistic monthly temperature data with per-month variation in mean and spread

Weaknesses

• Ridge overlap (~46%, spacing=-13 vs row height=28) sits slightly below the spec's "typically 50-70%" guidance — a bit more negative spacing (e.g. -16 to -18) would give a more classic joy-plot silhouette
• The green-to-blue gradient is decorative/redundant with row order — no caption or label ties it to "month progression"
• Design stays fairly minimal/flat; a small refinement (subtle alternating row shading, mean-value tick per ridge) would push Aesthetic Sophistication closer to publication-ready

Issues Found

1. DE-03 MEDIUM: No explicit call-out of the seasonal insight beyond the implicit visual pattern
   • Fix: Not required for approval — optional polish for a future pass could add a subtle annotation on the warmest/coldest month

AI Feedback for Next Attempt

Implementation approved on first review. Optional future polish: tighten ridge overlap slightly (spacing ≈ -16 to -18) for a more dramatic joy-plot silhouette, and consider a subtle design touch (alternating row shading or a mean-tick per ridge) to push Design Excellence further.

Verdict: APPROVED