feat(plotnine): implement forest-basic

[github-actions]

Implementation: forest-basic - plotnine

Implements the plotnine version of forest-basic.

File: plots/forest-basic/implementations/plotnine.py

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🤖 impl-generate workflow

[claude]

AI Review - Attempt 1/3

Image Description

The plot displays a forest plot with 10 individual studies listed vertically on the left side (Smith 2018 through Anderson 2023), each with a blue horizontal error bar representing the confidence interval and a blue dot at the point estimate. A vertical dashed gray line at x=0 marks the null effect reference. At the bottom, a yellow diamond shape represents the pooled estimate. On the right side, effect sizes with confidence intervals are displayed in text format (e.g., "-0.45 [-0.72, -0.18]"). The pooled estimate is shown in bold ("-0.31 [-0.46, -0.15]"). The title follows the required format: "forest-basic · plotnine · pyplots.ai". The x-axis is labeled "Mean Difference (Treatment - Control)". The background is white with subtle light gray vertical grid lines.

Quality Score: 92/100

Criteria Checklist

Visual Quality (36/40 pts)

• VQ-01: Text Legibility (10/10) - Title at 24pt, axis labels at 20pt, study names and effect values clearly readable at appropriate sizes
• VQ-02: No Overlap (8/8) - All text elements are well-separated with no overlap
• VQ-03: Element Visibility (7/8) - Points and error bars well-sized; marker sizes vary by weight as specified; slightly conservative sizing
• VQ-04: Color Accessibility (5/5) - Blue (#306998) and yellow (#FFD43B) are colorblind-safe; high contrast against white background
• VQ-05: Layout Balance (4/5) - Good use of canvas space; slight imbalance with more whitespace on the right
• VQ-06: Axis Labels (2/2) - X-axis has descriptive label "Mean Difference (Treatment - Control)" with context
• VQ-07: Grid & Legend (0/2) - No legend needed; grid is subtle but only vertical lines present which is appropriate for forest plots

Spec Compliance (25/25 pts)

• SC-01: Plot Type (8/8) - Correct forest plot with study estimates, CIs, and pooled diamond
• SC-02: Data Mapping (5/5) - Effect sizes on x-axis, studies on y-axis as expected
• SC-03: Required Features (5/5) - All spec features present: point estimates, CI whiskers, diamond for pooled estimate, reference line at null, marker size by weight
• SC-04: Data Range (3/3) - All data visible within axis limits
• SC-05: Legend Accuracy (2/2) - No legend needed for this plot type; labels are inline
• SC-06: Title Format (2/2) - Correctly uses "forest-basic · plotnine · pyplots.ai"

Data Quality (18/20 pts)

• DQ-01: Feature Coverage (7/8) - Shows both significant (CI not crossing 0) and non-significant results; varying CI widths; pooled estimate clearly shown. Could have more variation in effect directions.
• DQ-02: Realistic Context (7/7) - Meta-analysis of RCTs comparing treatment vs control is a perfect real-world scenario for forest plots
• DQ-03: Appropriate Scale (4/5) - Effect sizes and CIs are realistic for clinical trials; all effects are negative which is slightly monotonic

Code Quality (10/10 pts)

• CQ-01: KISS Structure (3/3) - Linear script: imports → data → calculations → plot → save
• CQ-02: Reproducibility (3/3) - Deterministic data (no random generation)
• CQ-03: Clean Imports (2/2) - All imports are used
• CQ-04: No Deprecated API (1/1) - Uses current plotnine API
• CQ-05: Output Correct (1/1) - Saves as "plot.png"

Library Features (3/5 pts)

• LF-01: Uses plotnine's grammar of graphics (3/5) - Good use of geom_errorbarh, geom_point with size identity, geom_polygon for diamond, geom_text for labels. Uses ggplot properly but doesn't showcase any particularly distinctive plotnine features beyond standard ggplot grammar.

Strengths

• Excellent implementation of forest plot structure with clear visual hierarchy
• Proper diamond shape for pooled estimate using geom_polygon
• Study labels and effect size values clearly displayed on left and right sides
• Good color choices with Python blue (#306998) and yellow accent (#FFD43B)
• Appropriate sizing for all text elements following quality guidelines
• Clean, readable code structure following KISS principles
• Realistic meta-analysis data context with meaningful study names

Weaknesses

• All individual study effects are negative; including some positive effects would better demonstrate the plot's ability to show heterogeneous results
• Grid lines only on x-axis (though appropriate for forest plots, full grid could be considered)

Verdict: APPROVED