feat(bokeh): implement violin-swarm

[github-actions]

Implementation: violin-swarm - bokeh

Implements the bokeh version of violin-swarm.

File: plots/violin-swarm/implementations/bokeh.py

Parent Issue: #3526

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🤖 impl-generate workflow

[claude]

AI Review - Attempt 1/3

Image Description

The plot displays four violin shapes arranged horizontally representing different experimental conditions (Control, Low Dose, Medium Dose, High Dose) for reaction time data. Each violin is rendered in Python Blue (#306998) with ~40% transparency (semi-transparent light blue appearance). Yellow/gold circular markers (Python Yellow #FFD43B) with dark gray outlines are overlaid as swarm points within each violin, showing individual data observations. The title "violin-swarm · bokeh · pyplots.ai" appears at the top-left. The Y-axis shows "Reaction Time (ms)" ranging from approximately 150-450ms, and the X-axis shows "Experimental Condition" with the four category labels. The violins display different distribution shapes - Control and Low Dose are more symmetric, Medium Dose has a wider spread, and High Dose is more compact and lower on the scale. Grid lines are subtle with dashed styling. There is a small Bokeh toolbar visible in the top-right corner.

Quality Score: 91/100

Criteria Checklist

Visual Quality (36/40 pts)

• VQ-01: Text Legibility (10/10) - Title at 36pt, axis labels at 28pt/22pt, tick labels at 24pt/22pt - all perfectly readable at 4800x2700
• VQ-02: No Overlap (8/8) - No overlapping text or elements, category labels well-spaced
• VQ-03: Element Visibility (7/8) - Markers size=18 with alpha=0.9 are clearly visible, violin alpha=0.4 provides good contrast; slightly dense in some areas
• VQ-04: Color Accessibility (5/5) - Blue/yellow contrast is excellent and colorblind-safe
• VQ-05: Layout Balance (4/5) - Good canvas utilization, violins well-distributed, slight extra whitespace on right side
• VQ-06: Axis Labels (2/2) - Descriptive with units: "Reaction Time (ms)", "Experimental Condition"
• VQ-07: Grid & Legend (0/2) - Grid is subtle (alpha=0.3, dashed), but no legend is present (not needed for this plot type)

Spec Compliance (25/25 pts)

• SC-01: Plot Type (8/8) - Correct violin plot with overlaid swarm points
• SC-02: Data Mapping (5/5) - Categories on X-axis, continuous values on Y-axis
• SC-03: Required Features (5/5) - Violin shows KDE distribution, swarm points overlaid and centered within violin shape, transparency applied, contrasting colors used
• SC-04: Data Range (3/3) - All data visible within axis range
• SC-05: Legend Accuracy (2/2) - No legend needed for this single-series plot
• SC-06: Title Format (2/2) - Uses correct format "violin-swarm · bokeh · pyplots.ai"

Data Quality (18/20 pts)

• DQ-01: Feature Coverage (7/8) - Shows 4 different distributions with varying means, spreads, and shapes; good demonstration of violin+swarm combination; could show more extreme outliers
• DQ-02: Realistic Context (7/7) - Reaction time drug dose study is a realistic scientific scenario
• DQ-03: Appropriate Scale (4/5) - Reaction times 150-450ms are plausible; the pattern of decreasing reaction time with increasing dose makes scientific sense

Code Quality (10/10 pts)

• CQ-01: KISS Structure (3/3) - Linear flow: imports → data → plot → save, no functions/classes
• CQ-02: Reproducibility (3/3) - Uses np.random.seed(42)
• CQ-03: Clean Imports (2/2) - All imports used (numpy, bokeh modules, scipy.stats)
• CQ-04: No Deprecated API (1/1) - Using current Bokeh API
• CQ-05: Output Correct (1/1) - Saves both plot.png and plot.html

Library Features (2/5 pts)

• LF-01: Distinctive Features (2/5) - Uses ColumnDataSource and patch() for violins, but does not leverage Bokeh's distinctive interactivity (HoverTool could show point values on hover)

Strengths

• Excellent implementation of KDE-based violin shapes using scipy.stats.gaussian_kde with proper normalization
• Smart swarm point jittering algorithm that respects violin boundaries by scaling jitter to local density
• Good color contrast between semi-transparent blue violins and opaque yellow points
• Proper text sizing for 4800x2700 canvas with all elements clearly readable
• Clean, KISS code structure with good reproducibility (seed=42)
• Both PNG and HTML outputs provided

Weaknesses

• Missing HoverTool for interactive tooltips on swarm points (would showcase Bokeh's interactivity strength)
• Small Bokeh toolbar visible in corner is not very useful for PNG output
• Could benefit from slight median/quartile indicators within the violins

Verdict: APPROVED