feat(plotly): implement point-basic

[github-actions]

Implementation: point-basic - plotly

Implements the plotly version of point-basic.

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

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🤖 impl-generate workflow

[claude]

AI Review - Attempt 1/3

Image Description

The plot displays a horizontal point estimate plot with 6 treatment groups (Control, Treatment A through Treatment E) arranged vertically on the y-axis. The x-axis shows "Effect Size (units)" ranging from approximately -1 to 5.5. Each group has a blue circular marker (#306998) representing the point estimate, with horizontal error bars extending to show the 95% confidence intervals. The error bars have visible caps at the endpoints. A dashed yellow/gold vertical reference line at x=0 is labeled "Null" at the top, representing the null hypothesis. The Control group is centered at 0, while all treatment groups show positive effects of varying magnitudes (Treatment D highest at ~4.2, Treatment C lowest at ~1.5). The legend "Estimate ± 95% CI" is positioned in the bottom right corner with a semi-transparent white background. The plot uses the plotly_white template with subtle gray gridlines.

Quality Score: 92/100

Criteria Checklist

Visual Quality (37/40 pts)

• VQ-01: Text Legibility (10/10) - Title at 32pt, axis labels at 24pt, tick labels at 18-20pt, all perfectly readable
• VQ-02: No Overlap (8/8) - No overlapping text elements, all labels fully visible
• VQ-03: Element Visibility (8/8) - Markers sized at 18 with good visibility, error bars thickness=3 with width=10 caps
• VQ-04: Color Accessibility (5/5) - Single blue color (#306998) with yellow reference line, colorblind-safe
• VQ-05: Layout Balance (4/5) - Good use of canvas space, margins well configured, slight excess space on left
• VQ-06: Axis Labels (2/2) - "Effect Size (units)" and "Treatment Group" are descriptive with units
• VQ-07: Grid & Legend (0/2) - Grid is subtle (alpha 0.1), but legend placement in bottom-right corner is suboptimal for this horizontal layout - would be better positioned outside the plot area or top-right

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 on X-axis (horizontal orientation per spec)
• SC-03: Required Features (5/5) - Has point estimates, confidence intervals, reference line at zero, error bar caps
• SC-04: Data Range (3/3) - Axes show all data points and confidence intervals
• SC-05: Legend Accuracy (2/2) - Legend label "Estimate ± 95% CI" accurately describes the data
• SC-06: Title Format (2/2) - Uses exact format "point-basic · plotly · pyplots.ai"

Data Quality (18/20 pts)

• DQ-01: Feature Coverage (7/8) - Shows varying CI widths, positive and zero effects, but all treatments positive (no negative treatment effect shown)
• DQ-02: Realistic Context (7/7) - Clinical trial treatment effects scenario is realistic and neutral
• DQ-03: Appropriate Scale (4/5) - Effect sizes 0-4.2 with CIs 0.8-1.5 are plausible, though units are generic

Code Quality (10/10 pts)

• CQ-01: KISS Structure (3/3) - Simple linear structure: imports → data → plot → save
• CQ-02: Reproducibility (3/3) - Uses np.random.seed(42)
• CQ-03: Clean Imports (2/2) - Only numpy and plotly.graph_objects, both used
• CQ-04: No Deprecated API (1/1) - Uses current Plotly 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 go.Scatter with error_x and add_vline which are standard Plotly features, but doesn't leverage Plotly's interactive capabilities in the static output (hover templates, annotations with arrows, etc.)

Strengths

• Excellent horizontal orientation matching spec recommendation for readability
• Clear reference line at null hypothesis with annotation
• Well-sized markers (18) and error bars with visible caps (width=10)
• Proper use of asymmetric error bars calculated from CI bounds
• Clean clinical trial context that's realistic and neutral
• Good font sizing hierarchy (title 32, labels 24, ticks 18-20)

Weaknesses

• Legend positioned in bottom-right could overlap with data in some scenarios; top-right or outside placement preferred
• All treatment effects are positive; including one negative effect would better demonstrate the plot type's full capability
• Grid opacity at 0.1 is very subtle, 0.2-0.3 would improve readability

Verdict: APPROVED