feat(bokeh): implement subplot-grid

[github-actions]

Implementation: subplot-grid - bokeh

Implements the bokeh version of subplot-grid.

File: plots/subplot-grid/implementations/bokeh.py

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🤖 impl-generate workflow

[claude]

AI Review - Attempt 1/3

Image Description

The plot displays a 2x2 grid financial dashboard with four distinct visualizations: (1) Top-left shows a blue line chart with data points tracking stock price from ~$105 down to ~$85 over 60 trading days; (2) Top-right displays yellow/gold vertical bars representing daily trading volume in millions; (3) Bottom-left presents a color-coded scatter plot (green for high performers >8%, red for low <5%, blue for mid-range) showing risk vs return analysis; (4) Bottom-right shows a blue histogram of daily returns with a roughly normal distribution centered near 0%. The main title "subplot-grid · bokeh · pyplots.ai" appears above the top-left subplot.

Quality Score: 91/100

Criteria Checklist

Visual Quality (35/40 pts)

• VQ-01: Text Legibility (8/10) - Text is readable but titles at 24pt are slightly smaller than the recommended 28pt for bokeh at this resolution
• VQ-02: No Overlap (8/8) - No overlapping text elements
• VQ-03: Element Visibility (7/8) - Elements are well-sized; scatter markers are appropriately sized for 40 points, histogram bins are clear
• VQ-04: Color Accessibility (5/5) - Good color choices: Python blue, yellow, green/red/blue for categorical distinction
• VQ-05: Layout Balance (4/5) - Grid layout is well-balanced, but individual subplots could use more of their canvas area
• VQ-06: Axis Labels (2/2) - All axes have descriptive labels with units (Price ($), Volume (Millions), Risk (Volatility %), etc.)
• VQ-07: Grid & Legend (1/2) - Grid lines are subtle with dashed style and 0.3 alpha; no legend needed for this layout

Spec Compliance (25/25 pts)

• SC-01: Plot Type (8/8) - Correctly implements a 2x2 subplot grid with different plot types (line, bar, scatter, histogram)
• SC-02: Data Mapping (5/5) - X/Y correctly assigned for all four subplots
• SC-03: Required Features (5/5) - All spec features present: configurable grid, different plot types per cell, clear titles
• SC-04: Data Range (3/3) - All axes show complete data ranges
• SC-05: Legend Accuracy (2/2) - N/A (no legend needed; color coding is self-explanatory in context)
• SC-06: Title Format (2/2) - Uses correct format "subplot-grid · bokeh · pyplots.ai"

Data Quality (18/20 pts)

• DQ-01: Feature Coverage (7/8) - Shows multiple subplot types (line, bar, scatter, histogram) demonstrating grid versatility; could include one more diverse type
• DQ-02: Realistic Context (7/7) - Financial dashboard scenario is realistic and cohesive (price, volume, risk/return, returns distribution)
• DQ-03: Appropriate Scale (4/5) - Values are realistic; stock price ~$85-110, volume in millions, returns in percentages

Code Quality (10/10 pts)

• CQ-01: KISS Structure (3/3) - Clean imports → data → plot → save structure
• 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) - Uses current Bokeh API
• CQ-05: Output Correct (1/1) - Saves as plot.png and plot.html

Library Features (3/5 pts)

• LF-01: Distinctive Features (3/5) - Uses gridplot, ColumnDataSource, and both PNG/HTML export; could leverage more interactive features like tooltips

Strengths

• Excellent implementation of a cohesive financial dashboard demonstrating diverse plot types in a grid
• Clean code structure with good use of ColumnDataSource for all subplots
• Effective color scheme using Python blue/yellow with meaningful semantic colors for risk categories
• Proper dual output (PNG and HTML) for both static and interactive viewing
• Well-organized data generation with realistic financial relationships (volume correlated with price movement)

Weaknesses

• Main title placement is unconventional (added to first subplot rather than as true grid title) causing slight visual asymmetry
• Individual subplot dimensions (2400x1350 each) result in a total grid size that may not match the target 4800x2700 exactly

Verdict: APPROVED