feat(plotnine): implement volcano-basic

[github-actions]

Implementation: volcano-basic - plotnine

Implements the plotnine version of volcano-basic.

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

Parent Issue: #2924

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🤖 impl-generate workflow

[claude]

AI Review - Attempt 1/3

Image Description

The volcano plot displays a scatter plot with Log2 Fold Change on the x-axis (ranging from approximately -3 to 4) and -Log10(p-value) on the y-axis (ranging from 0 to 4). Three distinct groups of points are visible: blue points on the left representing down-regulated genes clustered around x = -2.5 with high significance (y > 2), gray points in the center showing non-significant genes spread across x = -2 to 2 with low significance (y < 1.3), and red points on the right representing up-regulated genes clustered around x = 2.5 with high significance (y > 2). Dashed threshold lines are present: horizontal line at y ≈ 1.3 (significance cutoff) and vertical lines at x = -1 and x = 1 (fold change thresholds). Six gene labels are annotated (Gene_416, Gene_415, Gene_443 on the left; Gene_469, Gene_478, Gene_475 on the right). The legend shows "Significance" with three categories. Title follows the required format.

Quality Score: 91/100

Criteria Checklist

Visual Quality (36/40 pts)

• VQ-01: Text Legibility (10/10) - Title at 24pt, axis labels at 20pt, tick labels at 16pt, all perfectly readable
• VQ-02: No Overlap (7/8) - Minor overlap between Gene_469 and Gene_478 labels on the right side
• VQ-03: Element Visibility (8/8) - Point size=3 with alpha=0.7 is well-suited for 500 data points
• VQ-04: Color Accessibility (4/5) - Blue and red are distinguishable but red-blue is not fully colorblind-safe; gray provides good contrast for non-significant
• VQ-05: Layout Balance (5/5) - Plot fills canvas well with balanced margins
• VQ-06: Axis Labels (1/2) - Labels are descriptive but could include units or more detail
• VQ-07: Grid & Legend (1/2) - No visible grid (minimal theme), legend well-placed on right

Spec Compliance (25/25 pts)

• SC-01: Plot Type (8/8) - Correct volcano plot with fold change vs significance
• SC-02: Data Mapping (5/5) - X=log2FC, Y=-log10(p-value) correctly assigned
• SC-03: Required Features (5/5) - Horizontal threshold at -log10(0.05), vertical thresholds at ±1, color by significance, gene labels present
• SC-04: Data Range (3/3) - All data visible within axes
• SC-05: Legend Accuracy (2/2) - Legend correctly shows Down-regulated, Not significant, Up-regulated
• SC-06: Title Format (2/2) - Uses correct format: volcano-basic · plotnine · pyplots.ai

Data Quality (18/20 pts)

• DQ-01: Feature Coverage (7/8) - Shows up-regulated, down-regulated, and non-significant genes; good distribution
• DQ-02: Realistic Context (7/7) - Gene expression data is a perfect real-world scenario for volcano plots
• DQ-03: Appropriate Scale (4/5) - Reasonable fold changes and p-values for gene expression

Code Quality (9/10 pts)

• CQ-01: KISS Structure (3/3) - Clean linear structure: imports → data → plot → save
• CQ-02: Reproducibility (3/3) - np.random.seed(42) used
• CQ-03: Clean Imports (2/2) - All imports are used
• CQ-04: No Deprecated API (0/1) - Uses 'size' parameter in geom_hline/geom_vline which should be 'linewidth' in newer versions
• CQ-05: Output Correct (1/1) - Saves as plot.png

Library Features (3/5 pts)

• LF-01: Uses distinctive library features (3/5) - Good use of plotnine's grammar of graphics (ggplot, aes, geom layers, scale_color_manual, theme_minimal), but could leverage more advanced features like faceting or stat layers

Strengths

• Excellent implementation of the volcano plot specification with all required features (threshold lines, color coding, gene labels)
• Clean grammar of graphics approach using plotnine's ggplot2-style syntax
• Good data simulation that realistically represents differential gene expression results
• Text sizes properly configured for 4800x2700 output
• Proper use of categorical coloring with meaningful significance categories

Weaknesses

• Minor label overlap between Gene_469 and Gene_478 on the right side of the plot
• Could use colorblind-safe palette instead of red-blue (consider using orange or different saturation)
• Grid lines not visible (theme_minimal removes them) which could aid reading values

Verdict: APPROVED