feat(seaborn): implement cartogram-area-distortion

[github-actions]

Implementation: cartogram-area-distortion - python/seaborn

Implements the python/seaborn version of cartogram-area-distortion.

File: plots/cartogram-area-distortion/implementations/python/seaborn.py

Parent Issue: #4671

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🤖 impl-generate workflow

[claude]

AI Review - Attempt 1/3

Image Description

Light render (plot-light.png): The plot shows a US states grid cartogram on a warm off-white (#FAF8F1) background. States are rendered as square tiles sized proportionally to population, colored by geographic region (West=brand green #009E73, Midwest=lavender #C475FD, South=blue #4467A3, Northeast=ochre #BD8233). Larger states like CA, TX, FL, NY have clearly larger tiles. State abbreviations appear in white text on colored tiles; population values (e.g. 39M, 30M) appear below the abbreviation for higher-population states. An equal-area reference inset is shown top-right, and a regional totals bar chart occupies the lower-right panel. CRITICAL ISSUE (AR-09): The title "US States by Population · cartogram-area-distortion · python · seaborn · anyplot.ai" is clipped at the LEFT canvas edge — the leading character "U" is cut off, rendering the title as "S States by Population · …". This is a confirmed AR-09 violation in the light render. Other text (state labels, legend, bar chart labels) is readable against the light background.

Dark render (plot-dark.png): The same layout is shown on a warm near-black (#1A1A17) background. Data colors are identical to the light render (Imprint palette positions 1–4). Chrome elements (title, subtitles, bar labels) are rendered in light-valued tokens, and white state labels on colored tiles remain clearly visible. CRITICAL ISSUE (AR-09): The same title clipping persists in the dark render — the "U" in "US" is cut off at the left canvas edge, identical to the light render failure. No dark-on-dark text issues observed for non-title elements. The "126M" South bar-chart label and regional tick labels are all legible against the dark surface.

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

Score: 0/100

AR-09 Auto-Reject — title clipped at canvas edge (both renders).

Category	Score	Max
Visual Quality	15	30
Design Excellence	13	20
Spec Compliance	13	15
Data Quality	14	15
Code Quality	10	10
Library Mastery	6	10
Total	0	100

Note: Category scores reflect honest evaluation for repair purposes. Final total is 0 due to AR-09 auto-reject rule.

Visual Quality (15/30)

• VQ-01: Text Legibility (0/8) — Title clipped at left canvas edge (AR-09). All other text (state abbreviations, population labels, bar labels, legend) is readable in both themes.
• VQ-02: No Overlap (5/6) — No significant collisions. Very small tiles for low-population states (AK, WY, SD, VT) have tiny but just-readable labels; minor deduction.
• VQ-03: Element Visibility (5/6) — Size encoding of population is clear. CA and TX tiles are prominently large; small states have small but visible tiles. Minor deduction for the very smallest tiles.
• VQ-04: Color Accessibility (2/2) — Four Imprint colors used with white text labels. Redundant text encoding supplements color. CVD-safe.
• VQ-05: Layout & Canvas (0/4) — Title overflows the left canvas boundary (AR-09 violation). The gridspec left=0.01 margin is insufficient to contain the title starting position.
• VQ-06: Axis Labels & Title (1/2) — No axis labels on cartogram (appropriate). Title format is correct but physically clipped.
• VQ-07: Palette Compliance (2/2) — West→#009E73 (slot 1), Midwest→#C475FD (slot 2), South→#4467A3 (slot 3), Northeast→#BD8233 (slot 4). Both theme backgrounds correct (#FAF8F1 / #1A1A17). Chrome tokens applied correctly.

Design Excellence (13/20)

• DE-01: Aesthetic Sophistication (5/8) — Multi-panel layout (main cartogram + equal-area reference + regional bar chart) shows genuine design thought. Color-coded regions with size encoding is intentional. Slight deduction for overall density and small-tile crowding.
• DE-02: Visual Refinement (4/6) — All axes cleanly despiked via sns.despine. No ticks on cartogram. Alpha-blended tiles with edge colors. Good use of ELEVATED_BG for legend. Deduction for the crowded reference inset where labels are barely readable.
• DE-03: Data Storytelling (4/6) — The reference inset for equal-area comparison is excellent storytelling. Regional totals bar chart summarizes the size data well. The subtitle "Tile area ∝ state population" is a helpful annotation.

Spec Compliance (13/15)

• SC-01: Plot Type (4/5) — Tile cartogram (Dorling-style) is a valid cartogram form with area proportional to population. Minor deduction: tiles do not maintain contiguity when sizes vary (gaps appear between tiles of different sizes, breaking the adjacency requirement mentioned in the spec).
• SC-02: Required Features (4/4) — Reference map inset included. State abbreviation labels present. Color scale for region encoding. Legend clarifying area and color.
• SC-03: Data Mapping (3/3) — Population maps to tile area, region maps to color, grid positions approximate US geographic layout.
• SC-04: Title & Legend (2/3) — Title format is correct ("US States by Population · cartogram-area-distortion · python · seaborn · anyplot.ai") but clipped at the left edge. Legend labels are correct.

Data Quality (14/15)

• DQ-01: Feature Coverage (5/6) — Shows area distortion, reference comparison, regional grouping, and population values for large states. Slight deduction: the cartogram doesn't demonstrate contiguous border-sharing behavior described in the spec.
• DQ-02: Realistic Context (5/5) — US states by population is realistic, neutral, and uses plausible real-world population values (CA=39M, TX=29.5M, FL=22.2M, NY=19.5M).
• DQ-03: Appropriate Scale (4/4) — Population in millions, sensible ranges, all 50 states represented.

Code Quality (10/10)

• CQ-01: KISS Structure (3/3) — No functions or classes; linear procedural script.
• CQ-02: Reproducibility (2/2) — np.random.seed(42) present; data is hardcoded so fully deterministic.
• CQ-03: Clean Imports (2/2) — Only os, matplotlib, numpy, pandas, seaborn — all used.
• CQ-04: Code Elegance (2/2) — Clean layout logic, proper legend construction, good use of theme tokens throughout.
• CQ-05: Output & API (1/1) — plt.savefig with no bbox_inches='tight'. Correct API.

Library Mastery (6/10)

• LM-01: Idiomatic Usage (4/5) — sns.set_theme() for theming, sns.scatterplot with proper hue/size/style encoding, sns.barplot for summary, sns.despine for cleanup.
• LM-02: Distinctive Features (2/5) — Uses seaborn's combined size+hue+style encoding in a single call, which is a distinctive seaborn feature. Limited use of seaborn-specific statistical features.

Score Caps Applied

• AR-09 (title clipped at canvas edge): total score overridden to 0, verdict REJECTED.

Strengths

• Multi-panel layout (cartogram + reference inset + bar chart) is a sophisticated, spec-compliant design with strong data storytelling
• Correct Imprint palette: West→#009E73, Midwest→#C475FD, South→#4467A3, Northeast→#BD8233 (canonical order 1–4)
• Theme tokens applied consistently — both renders pass the theme-readability check for all non-title elements
• State abbreviation labels scale with tile size; population values shown for large states only — clean information hierarchy
• No bbox_inches='tight' violation; canvas spec (8x4.5 @ dpi=400 = 3200x1800) is correct

Weaknesses

• AR-09 CRITICAL: Title is clipped at the left canvas edge in both renders. The gridspec sets left=0.01, placing the main axes nearly flush with the canvas left border. The title (fontsize ~10 on the main axes) extends beyond the left canvas boundary. Fix: increase left in the gridspec from 0.01 to at least 0.04–0.05, OR reduce the title fontsize floor further so the title fits within the axes bounds, OR use fig.suptitle() instead of ax_main.set_title() with a figure-level horizontal alignment that stays within the canvas.
• Equal-area reference inset has very small labels (3.5pt) that are barely legible; consider 4.5–5pt minimum for the inset state abbreviations.
• Tile sizes for small-population states (AK, WY, VT, RI) are very small, making their labels nearly invisible at 3.5–4pt.

Issues Found

1. AR-09 CRITICAL: Title clipped at left canvas edge (both renders — "U" in "US" is missing)
   • Root cause: left=0.01 in gridspec places ax_main flush with canvas; title overflows left boundary
   • Fix: change left=0.01 to left=0.04 or left=0.05 in fig.add_gridspec(...), then adjust layout accordingly
2. VQ-01 MINOR: Reference inset state labels at fontsize=3.5 are at the edge of readability
   • Fix: increase to fontsize=4.5 or 5 in the reference inset label loop

AI Feedback for Next Attempt

The implementation is otherwise high-quality — fix the single AR-09 clipping issue by increasing the left margin in the gridspec. Change left=0.01 to left=0.04 or left=0.05 in the fig.add_gridspec(...) call. This will shift the main axes right, giving the title room to render without clipping. Also consider increasing the reference inset state label fontsize from 3.5pt to 4.5pt for better legibility. All other aspects (palette, theme tokens, multi-panel layout, data content) are correct and should be preserved.

Verdict: REJECTED

[github-actions]

🔧 AI Review Produced No Score — Auto-Retrying

The Claude Code Action ran but didn't write quality_score.txt. Auto-retrying review once...

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🤖 impl-review

[claude]

AI Review - Attempt 1/3

Image Description

Light render (plot-light.png): Background is warm off-white (#FAF8F1) — correct. The plot is a three-panel layout: a tile-grid cartogram on the left (US states as scaled squares, area ∝ population), an equal-area reference tile map (top right), and a regional totals bar chart (bottom right). State abbreviations appear in white text inside colored tiles; CA and TX are the largest squares. The Imprint palette is correctly applied in canonical order: West=#009E73 (green), Midwest=#C475FD (lavender), South=#4467A3 (blue), Northeast=#BD8233 (ochre). A region legend is visible inside the cartogram panel. However, the title is clipped at the left canvas edge — only "S States by Population · cartogram-area-distortion · python · seaborn · anyplot.ai" is visible; the leading "U" in "US" is missing. All other text is readable.

Dark render (plot-dark.png): Background is warm near-black (#1A1A17) — correct. Same three-panel layout. Data colors are identical to the light render (same Imprint palette, same order — only chrome flips). Title text is light-colored against the dark surface and readable where present, but the same AR-09 title clipping occurs — "U" is cut off at the left canvas edge. No dark-on-dark failure: tick labels, axis labels, legend text, and state labels all use light tokens and are clearly legible against the dark background.

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

Score: 0/100

Category	Score	Max
Visual Quality	0	30
Design Excellence	14	20
Spec Compliance	12	15
Data Quality	14	15
Code Quality	10	10
Library Mastery	6	10
Total	0	100

⚠️ Score forced to 0 by AR-09 auto-reject. Without the title clipping the estimated score would be ~77/100.

Visual Quality (19/30)

• VQ-01: Text Legibility (4/8) — Title clipped at left edge (AR-09); other text readable
• VQ-02: No Overlap (5/6) — No severe collisions; reference map dense but legible
• VQ-03: Element Visibility (5/6) — Population scaling is clear; small states still visible
• VQ-04: Color Accessibility (2/2) — Imprint palette is CVD-safe; white-on-color tile labels pass contrast
• VQ-05: Layout & Canvas (1/4) — Title overflows left boundary; canvas size is correct
• VQ-06: Axis Labels & Title (2/2) — Bar chart labelled correctly; cartogram rightly has no axis labels
• VQ-07: Palette Compliance (2/2) — #FAF8F1/#1A1A17 backgrounds correct; canonical Imprint order

Design Excellence (14/20)

• DE-01: Aesthetic Sophistication (5/8) — Multi-panel design with intentional hierarchy and custom palette
• DE-02: Visual Refinement (4/6) — All spines removed; clean bg; "Tile area ∝ state population" annotation
• DE-03: Data Storytelling (5/6) — Cartogram vs equal-area reference comparison is strong storytelling

Spec Compliance (12/15)

• SC-01: Plot Type (4/5) — Tile-grid cartogram is a valid cartogram variant; lacks true geographic polygon distortion
• SC-02: Required Features (3/4) — Size, labels, legend, reference map all present; color encodes region categorically rather than a continuous secondary variable
• SC-03: Data Mapping (3/3) — State labels, population→size, region→color all correctly mapped
• SC-04: Title & Legend (2/3) — Title format is correct but clipped (AR-09)

Data Quality (14/15)

• DQ-01: Feature Coverage (5/6) — Cartogram, equal-area reference, regional bar chart — comprehensive
• DQ-02: Realistic Context (5/5) — Approximate real US state population data; neutral subject
• DQ-03: Appropriate Scale (4/4) — Population 0.6M–39M is realistic

Code Quality (10/10)

• CQ-01: KISS Structure (3/3) — Flat script, no functions or classes
• CQ-02: Reproducibility (2/2) — np.random.seed(42) + hardcoded data = fully deterministic
• CQ-03: Clean Imports (2/2) — All five imports are used
• CQ-04: Code Elegance (2/2) — Appropriate complexity, no fake UI
• CQ-05: Output & API (1/1) — plt.savefig(f'plot-{THEME}.png', dpi=400, facecolor=PAGE_BG) correct; no bbox_inches='tight'

Library Mastery (6/10)

• LM-01: Idiomatic Usage (4/5) — sns.scatterplot with size=, sns.barplot, sns.set_theme, sns.despine used well
• LM-02: Distinctive Features (2/5) — sizes=(min, max) size-encoding is seaborn-distinctive; multi-panel layout is mostly matplotlib-level

Score Caps Applied

• AR-09 auto-reject: Score forced to 0, verdict = REJECTED. Title pixels clipped at left canvas edge in both renders.

Strengths

• Multi-panel design (cartogram + equal-area reference + bar chart) tells a complete story and directly satisfies the spec requirement for a reference map inset
• Imprint palette applied in correct canonical order; all theme-adaptive chrome tokens (PAGE_BG, INK, INK_SOFT, ELEVATED_BG) correctly propagated to every element
• No bbox_inches='tight' on savefig — canvas size is correct per the seaborn canvas rule
• White state abbreviation labels inside colored tiles are readable; population annotations on major states add useful detail
• Code is clean, flat, reproducible, and uses the full seaborn API idiomatically

Weaknesses

• Title clipped at left canvas edge (AR-09): ax_main.set_title(...) centers the title on ax_main, whose center X sits at ~36% of figure width. The 83-character title at 10pt extends ~218 px past the left canvas boundary, cutting off the leading "U" in "US States". Fix: replace ax_main.set_title(title, ...) with fig.suptitle(title, x=0.50, ha='center', fontsize=title_fontsize, fontweight='medium', color=INK, y=0.95) to center the title on the full figure — and remove the pad= from the old call. Alternatively, increase left= margin substantially so ax_main's center shifts right.
• Bar chart x-axis tick labels at the very bottom (below "0") may be partially cut — bottom=0.04 leaves very little room; consider increasing to bottom=0.08.
• Tile cartogram does not use actual geographic geometry — uses a synthetic grid. For seaborn this is an acceptable creative interpretation, but noting it for context.

Issues Found

1. AR-09 CRITICAL: Title "US States by Population · cartogram-area-distortion · python · seaborn · anyplot.ai" clipped at left canvas edge — the "U" is cut off in both light and dark renders.
   • Fix: Change ax_main.set_title(title, ...) to fig.suptitle(title, x=0.50, ha='center', fontsize=title_fontsize, fontweight='medium', color=INK, y=0.95) and adjust top= in gridspec to leave room (e.g. top=0.85). This centers the title on the full 3200 px canvas width.

AI Feedback for Next Attempt

The implementation is strong overall — the multi-panel design, palette application, theme tokens, and code quality are all correct. The single blocking issue is the title placement: ax_main.set_title() centers on the axis column, not the figure, and the long title overflows the left canvas boundary. Replace with fig.suptitle(title, x=0.50, ha='center', fontsize=title_fontsize, fontweight='medium', color=INK) and shrink top= in fig.add_gridspec(...) to make room (e.g. top=0.85). Do not change anything else — the design, palette, and canvas size are all correct.

Verdict: REJECTED

[github-actions]

❌ AI Review Failed (auto-retry exhausted)

The AI review action completed but did not produce valid output files. Auto-retry already tried once.

What happened:

• The Claude Code Action ran
• No quality_score.txt file was created

Manual rerun:

gh workflow run impl-review.yml -f pr_number=8457

---

🤖 impl-review

[claude]

AI Review - Attempt 1/3

Image Description

Light render (plot-light.png): The plot renders on a warm off-white (#FAF8F1) background. The main cartogram is a tile/bubble grid where square marker size represents US state population — California (CA) is the largest green tile, Texas (TX) and Florida (FL) are large blue tiles, and New York (NY) is a large ochre tile. Region colors follow the Imprint palette: West=#009E73 (green), Midwest=#C475FD (lavender), South=#4467A3 (blue), Northeast=#BD8233 (ochre). A 4-column Region legend sits above the main chart. A reference equal-area inset is shown top-right, and a Regional Totals horizontal bar chart is in the bottom-right. Most text is readable against the light background. However, the title "US States by Population · cartogram-area-distortion · python · seaborn · anyplot.ai" is visibly clipped at the LEFT canvas edge — the "U" from "US" is missing, rendering as "S States by Population…" This is a hard AR-09 violation (pixels removed at canvas border).

Dark render (plot-dark.png): The same plot on a warm near-black (#1A1A17) background. Data colors are identical to the light render (West=green, Midwest=lavender, South=blue, Northeast=ochre ✓). Text is rendered in light tones and is readable against the dark background — no dark-on-dark failures in body text or tick labels. Legend and bar chart text are legible. The same title clipping is present in the dark render — "U" from "US States" is cut off at the left canvas edge. Legibility verdict: FAIL (title AR-09 clipping in both renders).

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

Score: 0/100

Category	Score	Max
Visual Quality	0	30
Design Excellence	0	20
Spec Compliance	0	15
Data Quality	0	15
Code Quality	0	10
Library Mastery	0	10
Total	0	100

Visual Quality (0/30)

• VQ-01: Text Legibility (0/8) — AR-09 override: title clipped
• VQ-02: No Overlap (0/6) — AR-09 override
• VQ-03: Element Visibility (0/6) — AR-09 override
• VQ-04: Color Accessibility (0/2) — AR-09 override
• VQ-05: Layout & Canvas (0/4) — AR-09 override
• VQ-06: Axis Labels & Title (0/2) — AR-09 override
• VQ-07: Palette Compliance (0/2) — AR-09 override

Design Excellence (0/20)

• DE-01: Aesthetic Sophistication (0/8) — AR-09 override
• DE-02: Visual Refinement (0/6) — AR-09 override
• DE-03: Data Storytelling (0/6) — AR-09 override

Spec Compliance (0/15)

• SC-01: Plot Type (0/5) — AR-09 override
• SC-02: Required Features (0/4) — AR-09 override
• SC-03: Data Mapping (0/3) — AR-09 override
• SC-04: Title & Legend (0/3) — AR-09 override

Data Quality (0/15)

• DQ-01: Feature Coverage (0/6) — AR-09 override
• DQ-02: Realistic Context (0/5) — AR-09 override
• DQ-03: Appropriate Scale (0/4) — AR-09 override

Code Quality (0/10)

• CQ-01: KISS Structure (0/3) — AR-09 override
• CQ-02: Reproducibility (0/2) — AR-09 override
• CQ-03: Clean Imports (0/2) — AR-09 override
• CQ-04: Code Elegance (0/2) — AR-09 override
• CQ-05: Output & API (0/1) — AR-09 override

Library Mastery (0/10)

• LM-01: Idiomatic Usage (0/5) — AR-09 override
• LM-02: Distinctive Features (0/5) — AR-09 override

Score Caps Applied

• AR-09 edge clipping: Score = 0, Verdict = REJECTED

Strengths

• Strong multi-panel layout concept: main cartogram + equal-area reference inset + regional totals bar chart — exactly what the spec called for
• Correct Imprint palette usage: West=#009E73, Midwest=#C475FD, South=#4467A3, Northeast=#BD8233 in canonical order
• Theme chrome adapts correctly in dark render — no dark-on-dark failures in body text
• Population-scaled bubble/tile sizes are clearly distinguishable (CA >> TX >> FL >> NY etc.)
• Regional Totals bar chart adds quantitative anchoring alongside the visual cartogram

Weaknesses

• AR-09 VIOLATION: Title "US States by Population · cartogram-area-distortion · python · seaborn · anyplot.ai" is clipped at the LEFT canvas edge in both renders — the leading "U" from "US" is cut off. Root cause: left=0.01 in fig.add_gridspec(...) places ax_main almost flush with the left canvas edge, and the long centered title of ax_main overflows past the left canvas boundary. Fix: increase left= to at least 0.05, or switch to fig.suptitle(title, ...) which spans the full figure width with proper margins, or reduce title_fontsize further so the title fits within the left-constrained axis.

Issues Found

1. AR-09 TITLE CLIPPED AT LEFT EDGE: In both light and dark renders, the title begins with "S States by Population…" — the "U" is clipped off at the canvas left boundary. The gridspec parameter left=0.01 is too tight; ax_main.set_title() centers over the axis, causing the long title string to overflow left of the axis origin and past the canvas edge. Fix options (in order of preference): (a) Use fig.suptitle(title, fontsize=title_fontsize, fontweight='medium', color=INK, y=0.96) instead of ax_main.set_title(), and remove the top=0.89 constraint or raise it to 0.92; (b) increase gridspec left=0.05; (c) reduce title_fontsize floor so the title fits within the existing left=0.01 bounds.

AI Feedback for Next Attempt

AR-09 fix is mandatory: the title is clipped at the left canvas edge in both renders. Switch from ax_main.set_title(title, ...) to fig.suptitle(title, fontsize=title_fontsize, fontweight='medium', color=INK, y=0.96) and remove top=0.89 from the gridspec (set to ~0.91 to leave room for the suptitle). Alternatively, increase gridspec left= from 0.01 to 0.05. Once the title is fully visible, the implementation is otherwise quite good: palette is correct, dual-panel layout is appropriate, and the tile-area cartogram concept is well-executed.

Verdict: REJECTED

[github-actions]

❌ AI Review Failed (auto-retry exhausted)

The AI review action completed but did not produce valid output files. Auto-retry already tried once.

What happened:

• The Claude Code Action ran
• No quality_score.txt file was created

Manual rerun:

gh workflow run impl-review.yml -f pr_number=8457

---

🤖 impl-review