feat(letsplot): implement contour-density

[github-actions]

Implementation: contour-density - letsplot

Implements the letsplot version of contour-density.

File: plots/contour-density/implementations/letsplot.py

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🤖 impl-generate workflow

[claude]

AI Review - Attempt 1/3

Image Description

The plot displays a density contour visualization on a light gray background with subtle grid lines. Three distinct clusters are visible through concentric blue contour lines (#306998 color): one in the upper-left area centered around ~15°C/80% humidity (small, dense cluster), one in the lower-center area around ~22°C/55% humidity (large, dense cluster with many contour levels), and one on the right side around ~32°C/75% humidity (more diffuse cluster). Yellow-gold scatter points (#FFD43B) with low alpha are overlaid showing the underlying data distribution. The x-axis shows "Temperature (°C)" ranging from ~8 to 46, and the y-axis shows "Relative Humidity (%)" ranging from ~35 to 100. The title "contour-density · letsplot · pyplots.ai" appears at the top.

Quality Score: 92/100

Criteria Checklist

Visual Quality (37/40 pts)

• VQ-01: Text Legibility (10/10) - Title, axis labels, and tick marks are all clearly readable at appropriate sizes
• VQ-02: No Overlap (8/8) - No overlapping text elements
• VQ-03: Element Visibility (7/8) - Contour lines are clearly visible; scatter points slightly compete with contours in dense areas
• VQ-04: Color Accessibility (5/5) - Blue/yellow combination is colorblind-safe with good contrast
• VQ-05: Layout Balance (5/5) - Plot fills canvas well with balanced margins
• VQ-06: Axis Labels (2/2) - "Temperature (°C)" and "Relative Humidity (%)" include units
• VQ-07: Grid & Legend (0/2) - Subtle grid present; no legend needed for this plot type

Spec Compliance (25/25 pts)

• SC-01: Plot Type (8/8) - Correct density contour plot with geom_density2d
• SC-02: Data Mapping (5/5) - X/Y correctly assigned to temperature/humidity
• SC-03: Required Features (5/5) - KDE contours, scatter overlay for context as spec suggests
• SC-04: Data Range (3/3) - All data visible within axes
• SC-05: Legend Accuracy (2/2) - No legend needed; plot is self-explanatory
• SC-06: Title Format (2/2) - Exact format "contour-density · letsplot · pyplots.ai"

Data Quality (18/20 pts)

• DQ-01: Feature Coverage (7/8) - Shows multiple clusters with different densities and spreads (dense vs diffuse)
• DQ-02: Realistic Context (7/7) - Temperature/humidity is a real-world scientific scenario
• DQ-03: Appropriate Scale (4/5) - Values are realistic though humidity reaching 100% is at the physical limit

Code Quality (10/10 pts)

• CQ-01: KISS Structure (3/3) - Clean imports → data → plot → save structure, no functions/classes
• CQ-02: Reproducibility (3/3) - np.random.seed(42) is set
• CQ-03: Clean Imports (2/2) - Only necessary imports (numpy, pandas, lets_plot)
• CQ-04: No Deprecated API (1/1) - Current lets-plot API
• CQ-05: Output Correct (1/1) - Saves as plot.png and plot.html

Library Features (4/5 pts)

• LF-01: Uses distinctive features (4/5) - Uses geom_density2d (ggplot2 grammar), proper ggsize scaling, and theme customization

Strengths

• Excellent visualization of three distinct density clusters with clear concentric contour lines
• Good use of scatter overlay with low alpha providing context without overwhelming the contours
• Proper ggplot2-style grammar with geom_density2d following lets-plot conventions
• Axis labels include appropriate units (°C, %) and are descriptive
• Title follows the exact required format: spec-id · library · pyplots.ai
• Realistic temperature/humidity scenario with sensible data ranges

Weaknesses

• Scatter point alpha could be slightly lower (0.2) for better contour visibility in dense areas

Verdict: APPROVED