feat(highcharts): implement andrews-curves

[github-actions]

Implementation: andrews-curves - highcharts

Implements the highcharts version of andrews-curves.

File: plots/andrews-curves/implementations/highcharts.py

Parent Issue: #2859

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🤖 impl-generate workflow

[claude]

AI Review - Attempt 1/3

Image Description

The plot displays Andrews curves for the Iris dataset with three species (Setosa, Versicolor, Virginica) shown in different colors. The x-axis represents t (radians) ranging from -3 to 3, and the y-axis represents f(t) ranging from approximately -5 to 6. Blue curves represent Setosa, yellow/gold curves represent Versicolor, and purple curves represent Virginica. The curves show distinctive wave patterns that help distinguish species - Setosa curves (blue) tend to have lower amplitude and cluster together, while Versicolor (yellow) and Virginica (purple) show more overlap but with distinguishable patterns. A vertical legend is positioned in the upper right corner with a white background. The title reads "Iris Species · andrews-curves · highcharts · pyplots.ai". Grid lines are subtle and visible. Transparency is applied to the curves allowing overlapping patterns to be visible.

Quality Score: 92/100

Criteria Checklist

Visual Quality (37 pts)

• VQ-01: Text Legibility (10) - Title, axis labels, and legend text are all clearly readable at the large canvas size
• VQ-02: No Overlap (8) - No overlapping text elements; legend is well-positioned
• VQ-03: Element Visibility (7) - Curves are visible with good transparency (0.5 alpha); line width is appropriate for 60 curves
• VQ-04: Color Accessibility (5) - Uses colorblind-safe palette (blue #306998, yellow #FFD43B, purple #9467BD) - no red-green conflict
• VQ-05: Layout Balance (5) - Good use of canvas space, plot fills appropriate area with balanced margins
• VQ-06: Axis Labels (1) - Labels are descriptive ("t (radians)", "f(t)") but f(t) lacks context for general audience
• VQ-07: Grid & Legend (1) - Grid is subtle (alpha 0.15), legend well-placed with background; minor issue: legend could have more padding

Spec Compliance (25 pts)

• SC-01: Plot Type (8) - Correct Andrews curves visualization using Fourier series transformation
• SC-02: Data Mapping (5) - Multivariate data correctly transformed to wave patterns with t parameter
• SC-03: Required Features (5) - All spec features present: normalized data, color by category, transparency for overlapping
• SC-04: Data Range (3) - Full range of t from -π to π shown, y-axis accommodates all curve values
• SC-05: Legend Accuracy (2) - Legend correctly identifies all three species
• SC-06: Title Format (2) - Title follows spec format with variation ("Iris Species · andrews-curves · highcharts · pyplots.ai")

Data Quality (18 pts)

• DQ-01: Feature Coverage (7) - Shows cluster separation well; Setosa clearly distinct, Versicolor/Virginica show expected overlap
• DQ-02: Realistic Context (7) - Uses classic Iris dataset, a real botanical dataset commonly used for this visualization
• DQ-03: Appropriate Scale (4) - Standardized data produces reasonable curve amplitudes; 20 samples per species is good

Code Quality (9 pts)

• CQ-01: KISS Structure (2) - Has helper function andrews_curve() which deviates from pure KISS style, but necessary for clarity
• CQ-02: Reproducibility (3) - Uses np.random.seed(42) for sample selection
• CQ-03: Clean Imports (2) - All imports are used appropriately
• CQ-04: No Deprecated API (1) - Uses current APIs
• CQ-05: Output Correct (1) - Saves as plot.png and plot.html

Library Features (3 pts)

• LF-01: Uses distinctive library features (3) - Good use of Highcharts line series with opacity, interactive HTML output, proper legend styling

Strengths

• Excellent colorblind-safe palette choice (blue/yellow/purple)
• Clear cluster separation visible - Setosa distinctly separated from Versicolor/Virginica
• Proper use of transparency (0.5 opacity) to show overlapping curve density
• Well-implemented Andrews curve transformation following Fourier series formula
• Good canvas utilization with appropriate margins
• Interactive HTML version also generated
• Normalized data using StandardScaler as recommended in spec

Weaknesses

• Helper function andrews_curve() deviates from pure KISS structure (minor)
• Y-axis label "f(t)" could be more descriptive for general audience

Verdict: APPROVED