feat(altair): implement roc-curve

[github-actions]

Implementation: roc-curve - altair

Implements the altair version of roc-curve.

File: plots/roc-curve/implementations/altair.py

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🤖 impl-generate workflow

[claude]

AI Review - Attempt 1/3

Image Description

The plot displays two ROC curves comparing classifier performance. A blue solid line represents the "Good Model" (AUC = 0.96) that rises steeply from the origin and hugs the top-left corner, indicating excellent classification performance. A yellow/gold solid line shows the "Moderate Model" (AUC = 0.71) with a more gradual curve. A gray dashed diagonal line represents the random classifier baseline (AUC = 0.50). The title "roc-curve · altair · pyplots.ai" appears at the top. The X-axis is labeled "False Positive Rate" (0 to 1), and the Y-axis is labeled "True Positive Rate" (0 to 1). A legend in the lower right clearly identifies all three lines with their AUC values. The plot uses a square 1:1 aspect ratio with subtle grid lines.

Quality Score: 91/100

Criteria Checklist

Visual Quality (36/40 pts)

• VQ-01: Text Legibility (10/10) - Title, axis labels, tick labels, and legend text are all clearly readable with appropriate font sizes
• VQ-02: No Overlap (8/8) - No overlapping text elements; all labels are well-separated
• VQ-03: Element Visibility (7/8) - Lines are well-sized with strokeWidth=4 for model curves and 3 for diagonal; however the dense tick labels on y-axis make it slightly busy
• VQ-04: Color Accessibility (5/5) - Blue (#306998) and yellow (#FFD43B) provide excellent contrast and are colorblind-safe; gray diagonal is appropriately muted
• VQ-05: Layout Balance (4/5) - Square format is appropriate for ROC curves; plot fills canvas well but legend positioning could be slightly better integrated
• VQ-06: Axis Labels (2/2) - Descriptive labels "False Positive Rate" and "True Positive Rate" (no units needed for rates 0-1)
• VQ-07: Grid & Legend (0/2) - Legend is placed in lower-right but overlaps slightly with the plot area. Grid is subtle with alpha 0.3.

Spec Compliance (25/25 pts)

• SC-01: Plot Type (8/8) - Correct ROC curve visualization with TPR vs FPR
• SC-02: Data Mapping (5/5) - X=FPR, Y=TPR correctly mapped
• SC-03: Required Features (5/5) - Diagonal reference line present, AUC displayed in legend, multiple models compared with distinct colors
• SC-04: Data Range (3/3) - Axes range from 0 to 1 as specified
• SC-05: Legend Accuracy (2/2) - Legend labels are accurate with AUC scores
• SC-06: Title Format (2/2) - Uses correct format "roc-curve · altair · pyplots.ai"

Data Quality (18/20 pts)

• DQ-01: Feature Coverage (7/8) - Shows two models with different performance levels plus random baseline; demonstrates full ROC curve behavior from (0,0) to (1,1)
• DQ-02: Realistic Context (6/7) - Generic model comparison scenario is plausible; could benefit from a more concrete domain context (e.g., medical diagnosis)
• DQ-03: Appropriate Scale (5/5) - All values correctly in 0-1 range; AUC values are realistic (0.96 good, 0.71 moderate)

Code Quality (9/10 pts)

• CQ-01: KISS Structure (3/3) - Linear structure: imports → data generation → ROC computation → plotting → save
• CQ-02: Reproducibility (3/3) - Uses np.random.seed(42)
• CQ-03: Clean Imports (2/2) - Only altair, numpy, pandas imported and all used
• CQ-04: No Deprecated API (0/1) - Uses np.trapezoid which is correct for newer numpy versions
• 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) - Uses Altair declarative encoding, layered charts, and configure methods correctly but does not leverage interactive features or tooltips that make Altair distinctive

Strengths

• Excellent color scheme with blue/yellow/gray that is accessible and visually appealing
• Clean declarative Altair code with proper encoding types (:Q, :N)
• AUC values prominently displayed in legend for easy comparison
• Diagonal reference line clearly distinguished with dashed style
• Square aspect ratio appropriate for ROC curves
• Both static PNG and interactive HTML outputs saved

Weaknesses

• Legend is positioned using absolute pixel coordinates (legendX=930, legendY=1150) which could be fragile; consider using orient="bottom-right" or similar relative positioning
• Y-axis has excessive tick density making it appear cluttered (every 0.02 increment)
• No interactivity or tooltips added despite Altair's strength in this area
• Grid lines could be styled more subtly with smaller dash pattern

Verdict: APPROVED