feat(altair): implement shap-summary

[github-actions]

Implementation: shap-summary - altair

Implements the altair version of shap-summary.

File: plots/shap-summary/implementations/altair.py

Parent Issue: #2923

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🤖 impl-generate workflow

[claude]

AI Review - Attempt 1/3

Image Description

The plot displays a SHAP summary visualization with 10 features arranged vertically, ordered by feature importance from top (Account Age, Transaction Count) to bottom (Support Tickets). Each feature row contains scattered points representing individual samples, positioned horizontally by their SHAP value (ranging from approximately -0.8 to 0.8). Points are colored using a blue-to-orange diverging color scheme: blue indicates low feature values (0) and orange indicates high feature values (1), with a gradient legend on the right. A vertical dashed line at x=0 separates positive and negative SHAP impacts. The title "shap-summary · altair · pyplots.ai" appears at the top center. Points are jittered vertically within each feature row to reduce overlap.

Quality Score: 92/100

Criteria Checklist

Visual Quality (36/40 pts)

• VQ-01: Text Legibility (10/10) - All text clearly readable at full size, appropriate font sizes
• VQ-02: No Overlap (8/8) - Jittering effectively prevents point overlap within rows
• VQ-03: Element Visibility (7/8) - Points well-sized for 300 samples, good alpha, though some clustering at zero for less important features
• VQ-04: Color Accessibility (5/5) - Blue-orange diverging scheme is colorblind-safe
• VQ-05: Layout Balance (4/5) - Good proportions, though slight empty space on right side
• VQ-06: Axis Labels (2/2) - X-axis has descriptive label with context "SHAP Value (Impact on Model Output)"
• VQ-07: Grid & Legend (0/2) - Grid is subtle but legend could be better positioned; the legend is somewhat isolated on the right

Spec Compliance (25/25 pts)

• SC-01: Plot Type (8/8) - Correct SHAP summary plot with beeswarm-style visualization
• SC-02: Data Mapping (5/5) - SHAP values on X, features on Y, color mapped to feature values
• SC-03: Required Features (5/5) - All spec features present: sorted by importance, diverging colors, zero line, jittering
• SC-04: Data Range (3/3) - All data visible within axes
• SC-05: Legend Accuracy (2/2) - Legend correctly shows feature value mapping
• SC-06: Title Format (2/2) - Correct format: "shap-summary · altair · pyplots.ai"

Data Quality (18/20 pts)

• DQ-01: Feature Coverage (7/8) - Shows varying importances and feature effects well, though the pattern is somewhat uniform across features
• DQ-02: Realistic Context (7/7) - Credit/financial model context with plausible features (Account Age, Credit Score, Debt Ratio)
• DQ-03: Appropriate Scale (4/5) - SHAP values in reasonable range, though all features normalized to 0-1 is slightly artificial

Code Quality (10/10 pts)

• CQ-01: KISS Structure (3/3) - Simple imports → data → plot → save structure
• CQ-02: Reproducibility (3/3) - Uses np.random.seed(42)
• CQ-03: Clean Imports (2/2) - Only necessary imports used
• CQ-04: No Deprecated API (1/1) - Uses current Altair API
• CQ-05: Output Correct (1/1) - Saves as plot.png and plot.html

Library Features (3/5 pts)

• LF-01: Uses distinctive library features (3/5) - Good use of transform_calculate for jittering, layered chart composition, but could leverage more Altair-specific features like interactive selection

Strengths

• Excellent implementation of SHAP summary plot matching specification requirements
• Effective use of Altair's declarative syntax with proper encoding types (Q for quantitative, N for nominal)
• Good jittering implementation using transform_calculate for random vertical offsets
• Clean code structure following KISS principles
• Appropriate color scheme (blueorange) matching SHAP convention of low=blue, high=red/orange
• Features properly sorted by mean absolute SHAP value (importance)

Weaknesses

• Legend positioning could be closer to the plot area to reduce isolation
• Grid styling via VQ-07 is minimal - could add subtle horizontal grid lines to help trace feature rows
• Interactive features not utilized (no tooltips or zoom/pan) which is an Altair strength

Verdict: APPROVED