feat(bokeh): implement line-filled

[github-actions]

Implementation: line-filled - bokeh

Implements the bokeh version of line-filled.

File: plots/line-filled/implementations/bokeh.py

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🤖 impl-generate workflow

[claude]

AI Review - Attempt 1/3

Image Description

The plot shows a filled line chart displaying website traffic (visitors) over 12 months. The area beneath the line is filled with a semi-transparent blue color (#306998 with alpha 0.4). A solid blue line traces the top of the filled area, with small circular markers at each data point. The chart shows a seasonal pattern peaking around month 7 (July) at approximately 81,000 visitors, with lower values at the start (~40,000) and end (~57,000) of the year. The background is a light gray (#fafafa), and there is a subtle dashed grid. The title "line-filled · bokeh · pyplots.ai" appears in the top-left. The x-axis shows months 1-12 labeled as "Month", and the y-axis shows "Website Visitors" ranging from 0 to ~80,000. Bokeh toolbar icons are visible in the top-right corner.

Quality Score: 91/100

Criteria Checklist

Visual Quality (36/40 pts)

• VQ-01: Text Legibility (9/10) - Title, axis labels, and tick marks are readable but could be slightly larger for the canvas size
• VQ-02: No Overlap (8/8) - No overlapping text elements
• VQ-03: Element Visibility (8/8) - Line, fill, and markers are well-sized and clearly visible
• VQ-04: Color Accessibility (5/5) - Single blue color is colorblind-safe
• VQ-05: Layout Balance (4/5) - Good use of canvas, slight imbalance with toolbar in corner
• VQ-06: Axis Labels (1/2) - Descriptive labels but no units (e.g., "Website Visitors (count)")
• VQ-07: Grid & Legend (1/2) - Grid is subtle with dashed lines and alpha 0.3, no legend needed for single series

Spec Compliance (25/25 pts)

• SC-01: Plot Type (8/8) - Correct filled line/area chart
• SC-02: Data Mapping (5/5) - X (months) and Y (visitors) correctly mapped
• SC-03: Required Features (5/5) - Semi-transparent fill, visible line on top, fill matches line color
• SC-04: Data Range (3/3) - All data visible, y-axis starts at 0 (baseline)
• SC-05: Legend Accuracy (2/2) - N/A for single series, no legend needed
• SC-06: Title Format (2/2) - Uses correct format "line-filled · bokeh · pyplots.ai"

Data Quality (18/20 pts)

• DQ-01: Feature Coverage (7/8) - Shows seasonal variation and trend well, demonstrates magnitude emphasis
• DQ-02: Realistic Context (7/7) - Website traffic is a realistic, neutral business scenario
• DQ-03: Appropriate Scale (4/5) - Values are plausible for website traffic, though seasonal amplitude is slightly exaggerated

Code Quality (10/10 pts)

• CQ-01: KISS Structure (3/3) - Clean sequential structure: imports → data → plot → save
• 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 (2/5 pts)

• LF-01: Uses distinctive library features (2/5) - Uses ColumnDataSource and HoverTool for interactivity, varea for fill; could leverage more Bokeh-specific features like CustomJS callbacks or more advanced tooltips

Strengths

• Excellent use of Bokeh's varea glyph for the filled area effect
• Clean implementation with ColumnDataSource for data management
• Interactive HTML output with HoverTool showing formatted visitor counts
• Proper font sizing for the 4800x2700 canvas
• Subtle grid styling with dashed lines and low alpha
• Realistic website traffic scenario with seasonal variation

Weaknesses

• Axis labels lack units (e.g., "Website Visitors (count)" or "Month of Year")
• Could use more distinctive Bokeh features like CustomJS, band annotations, or span annotations to highlight peaks

Verdict: APPROVED