feat(bokeh): implement point-basic

[github-actions]

Implementation: point-basic - bokeh

Implements the bokeh version of point-basic.

File: plots/point-basic/implementations/bokeh.py

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🤖 impl-generate workflow

[claude]

AI Review - Attempt 1/3

Image Description

The plot shows a horizontal point estimate plot with 6 treatment groups (Treatment A through E, plus Control) on the y-axis and Effect Size on the x-axis. Each group has a yellow circular point marker with a blue outline representing the estimate, connected to horizontal blue error bars (confidence intervals) with T-shaped caps at each end. A vertical dashed gray reference line is drawn at x=0 (null hypothesis). The title "point-basic · bokeh · pyplots.ai" appears at the top left. Treatment groups show varying effect sizes: Treatment A (~2.5), Treatment B (~1.8), Treatment C (3.2), Treatment D (-0.5, only one crossing zero), Treatment E (~1.2), and Control (at 0). The confidence interval widths vary appropriately across groups.

Quality Score: 91/100

Criteria Checklist

Visual Quality (36/40 pts)

• VQ-01: Text Legibility (9/10) - Title, axis labels, and tick labels are all clearly readable at full size. Font sizes are appropriate for the 4800x2700 canvas.
• VQ-02: No Overlap (8/8) - No overlapping text elements; category labels are well-spaced vertically.
• VQ-03: Element Visibility (8/8) - Point markers are large and clearly visible; error bars have good line width and distinct T-caps.
• VQ-04: Color Accessibility (5/5) - Blue/yellow color scheme is colorblind-safe; good contrast against white background.
• VQ-05: Layout Balance (4/5) - Good use of canvas space; plot is well-centered with balanced margins. Minor deduction as there's slightly more whitespace than ideal.
• VQ-06: Axis Labels (1/2) - "Effect Size" and "Treatment Group" are descriptive but lack units.
• VQ-07: Grid & Legend (1/2) - Grid is subtle with dashed lines and alpha=0.3; no legend needed for this plot type.

Spec Compliance (25/25 pts)

• SC-01: Plot Type (8/8) - Correct point estimate plot with confidence intervals.
• SC-02: Data Mapping (5/5) - Categories on Y-axis, estimates/intervals on X-axis (horizontal orientation as spec recommends).
• SC-03: Required Features (5/5) - Has point estimates, error bars with caps, reference line at zero.
• SC-04: Data Range (3/3) - All data points and intervals are fully visible.
• SC-05: Legend Accuracy (2/2) - N/A for this plot type (single series).
• SC-06: Title Format (2/2) - Correctly uses "point-basic · bokeh · pyplots.ai" format.

Data Quality (18/20 pts)

• DQ-01: Feature Coverage (7/8) - Shows positive and negative estimates, varying CI widths, reference line crossing. Minor deduction: only one negative estimate.
• DQ-02: Realistic Context (7/7) - Treatment effect comparison is a classic, neutral use case for point estimates.
• DQ-03: Appropriate Scale (4/5) - Effect sizes in reasonable range (-0.5 to 3.2); CI widths are plausible.

Code Quality (10/10 pts)

• CQ-01: KISS Structure (3/3) - Clean linear 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 Bokeh-specific features like Whisker with TeeHead and Span for reference line, but doesn't leverage Bokeh's interactive capabilities (HoverTool, etc.) which are its main strength.

Strengths

• Excellent implementation of horizontal point estimate plot with proper orientation for readability
• Proper use of Bokeh's Whisker annotation with TeeHead caps for error bars
• Clean reference line at zero using Span model
• Appropriate font sizing for the large canvas (36pt title, 28pt labels, 22pt ticks)
• Good visual hierarchy with yellow-filled points outlined in blue
• Realistic treatment effect data with varying confidence interval widths

Weaknesses

• Could benefit from HoverTool to show exact values on mouse-over (Bokeh's key interactive feature)
• Axis labels lack units (e.g., "Effect Size (Cohen's d)" would be more informative)

Verdict: APPROVED