feat(letsplot): implement rug-basic

[github-actions]

Implementation: rug-basic - python/letsplot

Implements the python/letsplot version of rug-basic.

File: plots/rug-basic/implementations/python/letsplot.py

Parent Issue: #978

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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). The plot shows a brand-green (#009E73) density curve with semi-transparent fill (alpha=0.25) over a multimodal distribution of response times, with three visible peaks at approximately 120ms, 250ms, and 400ms. Rug marks appear as short vertical segments along the x-axis bottom (alpha=0.7), clearly showing three dense clusters and sparse outliers extending to ~780ms. Title "rug-basic · letsplot · anyplot.ai" in dark ink, axis labels "Response Time (ms)" and "Density" readable. Grid lines visible on both axes (subtle). All text is clearly readable against the light background.

Dark render (plot-dark.png): Warm near-black background (#1A1A17). The same brand-green data colors are identical to the light render — density curve, fill, and rug marks all remain #009E73. Chrome correctly inverts: title, axis labels, and tick labels display in light near-white ink with no dark-on-dark failures. Grid lines remain subtle and visible. The density fill is slightly less prominent on the dark surface but present. All text is clearly readable against the dark background.

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

Score: 83/100

Category	Score	Max
Visual Quality	26	30
Design Excellence	11	20
Spec Compliance	15	15
Data Quality	15	15
Code Quality	10	10
Library Mastery	6	10
Total	83	100

Visual Quality (26/30)

• VQ-01: Text Legibility (7/8) — Font sizes explicitly set (title=24, axis=20, tick=16); all text readable in both renders
• VQ-02: No Overlap (5/6) — Rug marks overlap in dense clusters, inherent to plot type; no text collisions
• VQ-03: Element Visibility (5/6) — Density curve and rug marks clearly visible; alpha=0.7 on rug marks appropriate
• VQ-04: Color Accessibility (2/2) — Single CVD-safe brand green; no red-green sole signal
• VQ-05: Layout & Canvas (3/4) — Good 16:9 proportions, nothing cut off; grid on both axes slightly busy for a density plot
• VQ-06: Axis Labels & Title (2/2) — X: "Response Time (ms)" with units; Y: "Density"; title correct
• VQ-07: Palette Compliance (2/2) — First series #009E73; light #FAF8F1, dark #1A1A17; both renders theme-correct

Design Excellence (11/20)

• DE-01: Aesthetic Sophistication (5/8) — Good use of alpha-blended density + rug layer composition; theme tokens applied throughout; above default but no standout design decisions
• DE-02: Visual Refinement (3/6) — theme_minimal() base used and minor grid removed; grid remains on both axes, suboptimal for a density plot (style guide recommends y-axis-only for non-scatter)
• DE-03: Data Storytelling (3/6) — The multimodal distribution story is visible but not actively guided; three performance clusters are present without any annotations or visual emphasis on peaks

Spec Compliance (15/15)

• SC-01: Plot Type (5/5) — Correct rug plot implementation with density complement as suggested in spec
• SC-02: Required Features (4/4) — Semi-transparency, consistent tick height, x-axis positioning, density complement all present
• SC-03: Data Mapping (3/3) — Response time on x-axis, density on y-axis, all 99 observations shown
• SC-04: Title & Legend (3/3) — Title rug-basic · letsplot · anyplot.ai; no legend for single series (correct)

Data Quality (15/15)

• DQ-01: Feature Coverage (6/6) — Shows clustering, gaps, outliers, and distribution shape — all key rug plot aspects demonstrated
• DQ-02: Realistic Context (5/5) — Server response times with three latency classes (fast/medium/slow) is domain-realistic and neutral
• DQ-03: Appropriate Scale (4/4) — 80–780ms range with natural cluster centers; realistic for web application latency

Code Quality (10/10)

• CQ-01: KISS Structure (3/3) — No functions or classes; clean linear procedural structure
• CQ-02: Reproducibility (2/2) — np.random.seed(42) set before all random calls
• CQ-03: Clean Imports (2/2) — All imports (os, numpy, pandas, lets_plot) are used
• CQ-04: Code Elegance (2/2) — Clean structure, appropriate complexity, no fake UI
• CQ-05: Output & API (1/1) — Saves plot-{THEME}.png (scale=3) and plot-{THEME}.html; ggsave used correctly

Library Mastery (6/10)

• LM-01: Idiomatic Usage (4/5) — Correct ggplot grammar; geom_segment for rug is the idiomatic lets-plot approach (no native geom_rug); proper theme() overrides
• LM-02: Distinctive Features (2/5) — HTML export present; interactive features (tooltips, hover info on rug marks) not leveraged

Score Caps Applied

• None

Strengths

• Excellent spec compliance — density + rug segment combination correctly displays both distribution shape and individual observation positions, with three clusters and outliers clearly visible
• Perfect data quality — realistic response-time scenario with natural multimodal clusters and edge outliers, neutral and domain-plausible
• Correct theme-adaptive chrome — all INK/INK_SOFT/PAGE_BG tokens wired through; both renders fully readable with no dark-on-dark or light-on-light failures
• Clean KISS code — deterministic seed, no functions/classes, proper lets-plot export pattern

Weaknesses

• Grid lines shown on both axes; for a density plot, y-axis-only grid (panel_grid_major_x=element_blank()) would be cleaner and match style-guide guidance
• No visual emphasis on the three distribution peaks — the multimodal story is visible but not highlighted; annotations at cluster centers would strengthen storytelling (DE-03)
• Minimal use of lets-plot's distinctive interactive features — HTML export present but tooltips/hover on rug marks not leveraged (LM-02)

Issues Found

1. DE-02 GRID: Both horizontal and vertical grid lines are shown. Density plots benefit from y-axis-only grid.
   • Fix: Add panel_grid_major_x=element_blank() to the theme() call
2. DE-03 LOW: Three latency cluster peaks are visible but not emphasized.
   • Fix: Add geom_text or annotate() labels at the three cluster peak positions to guide the viewer

AI Feedback for Next Attempt

The implementation is solid and correct. To elevate design: (1) remove x-axis major grid with panel_grid_major_x=element_blank() for a cleaner density plot; (2) add subtle geom_vline or geom_text annotations at the three cluster centers (~120ms, ~250ms, ~400ms) to tell the performance-tier story; (3) consider adding geom_point with tooltips=layer_tooltips() to the rug marks to leverage lets-plot's interactive HTML output.

Verdict: APPROVED

[github-actions]

🔧 Repair Attempt 1/4

Applied fixes based on AI review feedback.

Status: Repair completed, re-triggering review...

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🤖 impl-repair

[claude]

AI Review - Attempt 2/3

Image Description

Light render (plot-light.png): The plot renders on a warm off-white background (~#FAF8F1). It shows a filled density curve in brand green (#009E73) with 25% opacity, revealing a trimodal distribution of API response times peaking around 120ms, 250ms, and a smaller shoulder near 400ms, with a long right tail. Along the x-axis bottom, short green vertical tick marks (the rug) are densely clustered at 100–150ms and 200–280ms, sparse at 380–450ms, and isolated at 550–780ms (outliers). Subtle horizontal and vertical major gridlines are visible. Title "rug-basic · letsplot · anyplot.ai" in dark ink is clearly readable. Axis labels "Response Time (ms)" and "Density" are descriptive with units. All text is readable against the light background. Legibility verdict: PASS.

Dark render (plot-dark.png): The same plot renders on a near-black background (~#1A1A17). The density curve and rug marks use the exact same brand green (#009E73) as the light render — data colors are identical. Title and all axis labels/tick labels appear in light-colored text that is clearly readable against the dark background. No dark-on-dark issues detected. Grid lines are subtle. Brand green is well-visible against the dark surface. Legibility verdict: PASS.

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

Score: 87/100

Category	Score	Max
Visual Quality	29	30
Design Excellence	13	20
Spec Compliance	15	15
Data Quality	15	15
Code Quality	9	10
Library Mastery	6	10
Total	87	100

Visual Quality (29/30)

• VQ-01: Text Legibility (8/8) — Title=24, axis_title=20, axis_text=16, all explicitly set; readable in both renders
• VQ-02: No Overlap (6/6) — Axis labels, tick labels, title all well-spaced
• VQ-03: Element Visibility (6/6) — Density curve prominent; rug marks clearly visible with appropriate height and alpha=0.7
• VQ-04: Color Accessibility (2/2) — Single series Okabe-Ito #009E73, CVD-safe
• VQ-05: Layout & Canvas (3/4) — Good proportions; some inherent empty space in upper-right due to right-skewed distribution
• VQ-06: Axis Labels & Title (2/2) — "Response Time (ms)" with units, "Density"; correct title format
• VQ-07: Palette Compliance (2/2) — #009E73 for single series; #FAF8F1 light background; #1A1A17 dark background; chrome adapts correctly in both renders

Design Excellence (13/20)

• DE-01: Aesthetic Sophistication (5/8) — Clean, professional density+rug composition with semi-transparent fill (alpha=0.25) and properly themed chrome. Clearly above defaults but not FiveThirtyEight-level polish.
• DE-02: Visual Refinement (4/6) — Minor grid removed, major grid subtly styled (size=0.2), transparent density fill adds visual layering. Both x/y gridlines still visible; spines could be pruned further.
• DE-03: Data Storytelling (4/6) — The trimodal distribution and gap between fast/medium/slow clusters is immediately legible from both the KDE and the rug density patterns. Outliers at 550–780ms are visually distinct as isolated rug marks.

Spec Compliance (15/15)

• SC-01: Plot Type (5/5) — Correct: rug marks displayed as short tick marks along x-axis, complemented by density curve per spec guidance
• SC-02: Required Features (4/4) — Semi-transparency on rug (alpha=0.7) ✓; consistent tick height ✓; x-axis position ✓; paired with density as complement ✓
• SC-03: Data Mapping (3/3) — Continuous variable mapped to x-axis; density on y-axis; all 99 observations represented
• SC-04: Title & Legend (3/3) — "rug-basic · letsplot · anyplot.ai" exact format; no legend (single-series, correct omission)

Data Quality (15/15)

• DQ-01: Feature Coverage (6/6) — Shows ALL rug plot features: clustering (dense rug regions), gaps in data, exact observation positions, and outliers at the tail
• DQ-02: Realistic Context (5/5) — API/server response time is a real, neutral, comprehensible scenario with meaningful clusters (fast/medium/slow responses)
• DQ-03: Appropriate Scale (4/4) — 100–800ms response times are realistic for web service latency; cluster proportions (fast=45, medium=35, slow=15, outliers=4) are factually plausible

Code Quality (9/10)

• CQ-01: KISS Structure (3/3) — Linear imports → data → 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; from lets_plot import * is idiomatic for the library
• CQ-04: Code Elegance (1/2) — Repeated # noqa: F405 on every geom/theme call clutters the code; named imports would eliminate the noise
• CQ-05: Output & API (1/1) — Saves plot-{THEME}.png (scale=3 for 4800×2700) and plot-{THEME}.html correctly

Library Mastery (6/10)

• LM-01: Idiomatic Usage (4/5) — Correct ggplot grammar with layered geoms, proper theme() override pattern, ggsize() for canvas control
• LM-02: Distinctive Features (2/5) — Uses lets-plot's ggsize + scale=3 export (distinctive for high-res output); multi-layer ggplot composition. Does not use native geom_rug() if available in lets-plot, choosing manual geom_segment instead.

Score Caps Applied

• None — no caps triggered (DE-01=5>2, DE-02=4>2, VQ-02=6, VQ-03=6, CQ-04=1>0)

Strengths

• Full theme-adaptive chrome — PAGE_BG, INK, INK_SOFT tokens applied to all chrome elements; both renders pass legibility check
• All three rug plot features demonstrated effectively: clustering, gaps, and outliers are immediately visible
• Realistic, neutral data scenario with plausible multimodal response-time distribution
• All font sizes explicitly set to spec-required values (24/20/16pt)
• Correct output filenames with proper scale=3 for 4800×2700px

Weaknesses

• Repeated # noqa: F405 comments on every lets_plot function call; use explicit named imports to avoid this noise
• Missing native geom_rug() (if available in lets-plot version used); geom_segment works but is less idiomatic than the dedicated geom
• Both x and y major gridlines visible; removing vertical gridlines would give a cleaner look for a density/rug chart

Issues Found

1. CQ-04 MINOR: Repeated # noqa: F405 on every plot function call makes code verbose
   • Fix: Use from lets_plot import ggplot, aes, geom_density, geom_segment, labs, theme_minimal, theme, ggsize, element_rect, element_text, element_line, element_blank to avoid wildcard-import lint noise
2. DE-02 MINOR: Both x and y axis gridlines visible
   • Fix: Remove vertical (x-axis) gridlines with panel_grid_major_x=element_blank() for a cleaner density+rug composition
3. LM-02: geom_segment used for rug marks instead of native geom_rug() if available
   • Fix: Check if lets-plot version supports geom_rug() and use it instead

AI Feedback for Next Attempt

The core implementation is solid. Focus on: (1) Replace wildcard import with named imports to eliminate repeated noqa comments. (2) Remove x-axis gridlines (panel_grid_major_x=element_blank()) — vertical gridlines add noise to a density+rug chart. (3) Investigate whether geom_rug() is available in the installed lets-plot version and use it for cleaner, more idiomatic rug mark code.

Verdict: APPROVED