feat(letsplot): implement area-mountain-panorama

[github-actions]

Implementation: area-mountain-panorama - python/letsplot

Implements the python/letsplot version of area-mountain-panorama.

File: plots/area-mountain-panorama/implementations/python/letsplot.py

Parent Issue: #5365

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🤖 impl-generate workflow

[claude]

AI Review - Attempt 1/3

Image Description

Light render (plot-light.png): The plot renders on a warm off-white (#FAF8F1) background. It shows a panoramic mountain area chart of the Wallis/Valais Alps as seen from Gornergrat — 16 labeled summits spanning a compass sweep from WSW to NE. The mountain silhouette is filled solid with the brand green (#009E73) against the off-white background. The title reads in dark ink at size 24, with a subtitle in muted gray. Leader lines drop from each summit point up to staggered annotation rows (3 rows) with bold peak names and muted elevation labels below each name. The Matterhorn name is rendered larger (size 9) than the other peaks (size 7) for visual emphasis. The X axis shows compass bearing labels (WSW, W, NW, N, NE), and the Y axis shows elevation with units in meters. Y-axis grid lines are subtle and horizontal only. All text is clearly readable against the light background — no light-on-light failures.

Dark render (plot-dark.png): The same plot renders on a warm near-black (#1A1A17) background. The mountain silhouette color is identical (#009E73 brand green) — data colors are unchanged between themes. The title and subtitle adapt to light-colored text (#F0EFE8 / #A8A79F), and axis labels flip to the light ink tokens. Peak name labels appear in the light INK color (#F0EFE8) and elevation labels in INK_SOFT (#B8B7B0). Leader lines appear in a soft gray. The overall layout is identical to the light render with only the chrome flipping. All text is clearly readable against the dark background — no dark-on-dark failures detected.

Both paragraphs are required. A review that only describes one render is invalid.

Score: 86/100

Category	Score	Max
Visual Quality	28	30
Design Excellence	13	20
Spec Compliance	14	15
Data Quality	15	15
Code Quality	10	10
Library Mastery	6	10
Total	86	100

Visual Quality (28/30)

• VQ-01: Text Legibility (7/8) — sizes explicitly set per guidelines (title 24, axis_title 20, axis_text 16); all text readable in both themes; geom_text sizes set in lets-plot native units with good results
• VQ-02: No Overlap (6/6) — 3-row staggering algorithm successfully prevents label collisions across all 16 peaks
• VQ-03: Element Visibility (6/6) — mountain silhouette clearly prominent; leader lines visible; all annotations legible
• VQ-04: Color Accessibility (2/2) — single series green on warm backgrounds, high contrast in both themes
• VQ-05: Layout & Canvas (3/4) — landscape aspect suits panorama well; annotation area occupies upper ~45% of canvas height which is generous but inherent to the annotated-summit format
• VQ-06: Axis Labels & Title (2/2) — descriptive axis labels with units
• VQ-07: Palette Compliance (2/2) — #009E73 for area fill, #FAF8F1 / #1A1A17 backgrounds, theme-adaptive chrome throughout

Design Excellence (13/20)

• DE-01: Aesthetic Sophistication (5/8) — above defaults: Matterhorn typographic emphasis, compass bearing X labels, subtitle context, staggered annotation system is well-crafted; the bright brand green silhouette does not achieve the "photo-like silhouette, evening/dusk feel" the spec describes — spec explicitly calls for a dark solid fill
• DE-02: Visual Refinement (4/6) — Y-axis-only grid, X-axis spine with ticks, top/right spines removed via theme_minimal, subtle RULE color for grid lines
• DE-03: Data Storytelling (4/6) — Matterhorn emphasized via larger bold text; panoramic sweep reads intuitively left-to-right; 16 labeled summits create genuine identification value; missing atmospheric sky gradient

Spec Compliance (14/15)

• SC-01: Plot Type (5/5) — correct area chart as panoramic mountain silhouette
• SC-02: Required Features (3/4) — all structural features present (leader lines, name+elevation annotation, staggered labels, compass X axis, sensible Y lower bound, wide aspect ratio, Matterhorn emphasis); spec explicitly says "Fill the area below the ridgeline with a dark solid color (photo-like silhouette, evening/dusk feel)" — the bright green fill does not match this requirement
• SC-03: Data Mapping (3/3) — angle_deg on X, elevation_m on Y, all 16 peaks annotated
• SC-04: Title & Legend (3/3) — title includes spec-id, library, anyplot.ai in correct format; no legend needed (single series)

Data Quality (15/15)

• DQ-01: Feature Coverage (6/6) — skyline profile with labeled summits, varying elevation, ridge variation, compass orientation, 16 peaks within spec range
• DQ-02: Realistic Context (5/5) — real Valais Alps peaks (Matterhorn, Monte Rosa, Weisshorn, Dom, etc.) with accurate elevations from Gornergrat vantage point
• DQ-03: Appropriate Scale (4/4) — Y range 2800-6000m for Alpine panorama; X 0-290 degrees spanning WSW to NE; Gaussian peak shapes create realistic ridgeline

Code Quality (10/10)

• CQ-01: KISS Structure (3/3) — linear: imports, tokens, data, skyline, staggering, plot, save; no functions or classes
• CQ-02: Reproducibility (2/2) — np.random.seed(42) set
• CQ-03: Clean Imports (2/2) — all imports used
• CQ-04: Code Elegance (2/2) — appropriate complexity for the staggering logic; pandas DataFrame usage idiomatic
• CQ-05: Output & API (1/1) — saves plot-{THEME}.png and plot-{THEME}.html correctly

Library Mastery (6/10)

• LM-01: Idiomatic Usage (4/5) — correct ggplot grammar, geom_area + geom_segment + geom_text layering, ggsize(), ggsave() with scale=3, element_* theme tokens used correctly
• LM-02: Distinctive Features (2/5) — generates HTML output (lets-plot distinctive), but interactive capabilities not leveraged; no use of lets-plot tooltips or hover annotations that could enrich the peak annotation experience in the HTML export

Score Caps Applied

• None — all category scores above cap thresholds

Strengths

• Exemplary data quality: real Swiss Alpine peaks with accurate elevations — a genuinely informative panorama
• 3-row label staggering algorithm elegantly solves the crowding problem for 16 simultaneous annotations
• Perfect theme adaptation: both light/dark renders are correct without any dark-on-dark or readability failures
• Matterhorn typographic emphasis (size 9 vs 7) provides a clear anchor focal point
• Compass bearing X-axis labels add geographic orientation without cluttering

Weaknesses

• Mountain silhouette uses bright brand green (#009E73) instead of the spec-required dark solid color for a "photo-like silhouette, evening/dusk feel" — consider a dark charcoal fill with brand green as a ridge outline or accent
• No sky-gradient background above the ridgeline (spec calls it "optional" but it would dramatically improve the atmospheric feel)
• lets-plot HTML export could leverage tooltip annotations on peaks (hover for name + elevation) instead of static text only

Issues Found

1. SC-02 / DE-01: GREEN SILHOUETTE vs DARK SILHOUETTE: The spec explicitly says "Fill the area below the ridgeline with a dark solid color (photo-like silhouette, evening/dusk feel)". The bright #009E73 fill creates a vibrant infographic style, not the intended dark panorama aesthetic. Fix: use a dark charcoal fill (e.g., a dark slate like #2D3A3A or the INK token) for the mountain area; use #009E73 as a thin ridge outline or reserve it for a different accent element.
2. LM-02: NO INTERACTIVE FEATURES IN HTML: lets-plot's core differentiator is interactive hover tooltips in HTML export. The peak annotations (name + elevation) are ideal candidates for a tooltips configuration — this would make the HTML export meaningfully more valuable than the static PNG.

AI Feedback for Next Attempt

Primary fix: Change the mountain area fill from brand green (#009E73) to a dark solid color (e.g., a dark charcoal or near-black) to achieve the photographic silhouette feel the spec describes. Keep #009E73 as a thin stroke outline on the ridgeline edge for brand consistency. Secondary: add a lets-plot tooltip so the HTML output shows peak name and elevation on hover — this is the library's key differentiator and would raise LM-02 significantly. Optional: a subtle sky gradient (light blue to PAGE_BG) in the panel background above the ridgeline.

Verdict: REJECTED