feat(pygal): implement facet-grid

[github-actions]

Implementation: facet-grid - pygal

Implements the pygal version of facet-grid.

File: plots/facet-grid/implementations/pygal.py

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🤖 impl-generate workflow

[claude]

AI Review - Attempt 1/3

Image Description

The plot displays a 2×3 faceted grid showing plant growth data (height vs days). The grid has two rows labeled "Sandy Soil" and "Clay Soil" (rotated labels on left side), and three columns labeled "Low Light", "Medium Light", and "High Light" at the top. Each cell contains a line chart with blue lines and circular markers showing plant height (cm) on the y-axis (0-32 range) over days (0-30) on the x-axis. The main title "facet-grid · pygal · pyplots.ai" is centered at the top in dark gray. All subplots share consistent y-axis scales. The layout is clean with light gray plot backgrounds and subtle horizontal grid lines.

Quality Score: 91/100

Criteria Checklist

Visual Quality (36/40 pts)

• VQ-01: Text Legibility (9/10) - Title and labels are clearly readable; font sizes are good but could be slightly larger for optimal readability
• VQ-02: No Overlap (8/8) - No overlapping text anywhere in the plot
• VQ-03: Element Visibility (8/8) - Line strokes and markers are appropriately sized and clearly visible
• VQ-04: Color Accessibility (5/5) - Single blue color (#306998) used consistently, no colorblind issues
• VQ-05: Layout Balance (4/5) - Good use of canvas space, slight padding imbalance with row label area
• VQ-06: Axis Labels (2/2) - Labels include units: "Height (cm)" and "Days"
• VQ-07: Grid & Legend (0/2) - No legend shown (though not strictly needed here), grid is subtle

Spec Compliance (25/25 pts)

• SC-01: Plot Type (8/8) - Correct faceted grid with line charts in each cell
• SC-02: Data Mapping (5/5) - X=Days, Y=Height correctly mapped
• SC-03: Required Features (5/5) - Has row/column faceting, shared axes, facet labels
• SC-04: Data Range (3/3) - All data visible within 0-35 y-axis range
• SC-05: Legend Accuracy (2/2) - Row labels correctly identify soil types
• SC-06: Title Format (2/2) - Uses exact format "{spec-id} · {library} · pyplots.ai"

Data Quality (18/20 pts)

• DQ-01: Feature Coverage (7/8) - Shows variation across conditions; different growth rates visible across facets; could show more dramatic differences
• DQ-02: Realistic Context (7/7) - Plant growth experiment is an excellent, realistic scientific scenario
• DQ-03: Appropriate Scale (4/5) - Height values (0-32 cm over 30 days) are plausible for plant growth

Code Quality (9/10 pts)

• CQ-01: KISS Structure (2/3) - Mostly linear flow but uses functions/imports for image composition
• CQ-02: Reproducibility (3/3) - Uses np.random.seed(42)
• CQ-03: Clean Imports (2/2) - All imports are used
• CQ-04: No Deprecated API (1/1) - No deprecated functions
• CQ-05: Output Correct (1/1) - Saves as plot.png

Library Features (3/5 pts)

• LF-01: Uses distinctive library features (3/5) - Uses pygal.Line with custom Style, but the multi-panel composition is done via PIL rather than native pygal features

Strengths

• Excellent implementation of faceted grid layout using creative PIL-based composition approach
• Clear, readable labels with proper units (Height in cm, Days)
• Consistent shared y-axis range across all facets for easy comparison
• Realistic plant growth scenario with meaningful variation between conditions
• Clean color scheme using pyplots primary blue (#306998)
• Both PNG and interactive HTML outputs generated
• Proper title format following spec requirements

Weaknesses

• Grid lines could be more subtle (currently visible but acceptable)
• The faceted composition relies heavily on PIL rather than pygal native features - this is a reasonable workaround given pygal limitations
• Row labels could be slightly larger for better visibility

Verdict: APPROVED