feat(highcharts): implement scatter-lag

[github-actions]

Implementation: scatter-lag - highcharts

Implements the highcharts version of scatter-lag.

File: plots/scatter-lag/implementations/highcharts.py

Parent Issue: #5251

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🤖 impl-generate workflow

[claude]

AI Review - Attempt 1/3

Image Description

The plot shows a scatter lag plot on a light (#fafbfc) background. The title "scatter-lag · highcharts · pyplots.ai" appears at the top center in dark text, with the subtitle "AR(1) Temperature Series — Lag 1 Autocorrelation (r = 0.814)" below it. The x-axis is labeled "y(t)" and the y-axis is labeled "y(t+1)"; both axes span roughly 15–26. Approximately 299 scatter points are rendered in a blue gradient — lighter/more transparent blues for early time steps, darker blues for later ones — revealing a clear positive linear trend along the diagonal. A dashed gray reference line (y = x) runs diagonally from lower-left to upper-right. A small legend appears floating in the upper-right corner with entries "Lag 1 pairs" and "y = x reference". Dot grid lines at very low opacity provide subtle structure. The strong clustering of points near the diagonal visually confirms high positive autocorrelation at lag 1.

Score: 88/100

Category	Score	Max
Visual Quality	28	30
Design Excellence	13	20
Spec Compliance	15	15
Data Quality	15	15
Code Quality	10	10
Library Mastery	7	10
Total	88	100

Visual Quality (28/30)

• VQ-01: Text Legibility (8/8) — All font sizes explicitly set: 64px title, 38px subtitle, 44px axis labels, 34px tick labels, 30px legend
• VQ-02: No Overlap (6/6) — Text elements are clean; no label collisions
• VQ-03: Element Visibility (5/6) — Markers visible with appropriate alpha gradient; centre density causes slight crowding but manageable
• VQ-04: Color Accessibility (4/4) — Blue gradient palette is fully colorblind-safe
• VQ-05: Layout & Canvas (3/4) — Good proportions; slight excess whitespace visible at bottom of canvas
• VQ-06: Axis Labels & Title (2/2) — y(t) / y(t+1) are standard lag-plot notation, descriptive and correct

Design Excellence (13/20)

• DE-01: Aesthetic Sophistication (5/8) — Time-gradient coloring shows genuine design intent above defaults; custom background and typography; not yet publication-ready
• DE-02: Visual Refinement (4/6) — Subtle dotted grid at 6% opacity, refined axis lines; no equivalent of spine removal but clean overall
• DE-03: Data Storytelling (4/6) — Time-based color gradient creates temporal narrative; r-value in subtitle gives immediate quantitative insight; diagonal reference line provides clear comparison baseline

Spec Compliance (15/15)

• SC-01: Plot Type (5/5) — Correct lag scatter plot
• SC-02: Required Features (4/4) — Lag=1, diagonal reference line, time-index coloring, r-value annotation all present
• SC-03: Data Mapping (3/3) — y(t) on x-axis, y(t+1) on y-axis, correct
• SC-04: Title & Legend (3/3) — Title matches scatter-lag · highcharts · pyplots.ai; legend labels appropriate

Data Quality (15/15)

• DQ-01: Feature Coverage (6/6) — Demonstrates strong autocorrelation with clear diagonal clustering; time gradient shows temporal structure; diagonal line provides uncorrelated baseline contrast
• DQ-02: Realistic Context (5/5) — AR(1) temperature series is a real-world environmental monitoring scenario, neutral and plausible
• DQ-03: Appropriate Scale (4/4) — ~16–26°C range with mean 20°C is realistic for a daily temperature series; 300 observations appropriate

Code Quality (10/10)

• CQ-01: KISS Structure (3/3) — Linear: imports → data → chart options → series → export; no functions or classes
• CQ-02: Reproducibility (2/2) — np.random.seed(42) set
• CQ-03: Clean Imports (2/2) — All imported packages are used
• CQ-04: Code Elegance (2/2) — Per-point color loop is necessary and clean; well-organised overall
• CQ-05: Output & API (1/1) — Saves plot.png via container.screenshot(); also exports plot.html

Library Mastery (7/10)

• LM-01: Idiomatic Usage (4/5) — Correct use of typed series objects (ScatterSeries, SplineSeries), add_series(), per-point data dicts; CDN JS downloaded and inlined per guide
• LM-02: Distinctive Features (3/5) — Uses per-point color key in data objects and {point.color} in tooltip template (Highcharts-specific); enableMouseTracking: False on reference line; could go further with Highcharts colorAxis or chart zones

Score Caps Applied

• None

Strengths

• Perfect spec compliance: all four required features (lag=1, diagonal reference, time coloring, r-value) implemented correctly
• Time-based blue gradient adds genuine analytical value — viewer can see temporal drift within the autocorrelation structure
• Correlation coefficient in subtitle provides immediate quantitative framing without cluttering the plot area
• Subtle dotted grid at near-zero opacity is a refined choice that avoids visual noise

Weaknesses

• Design Excellence is the gap: at 13/20, the plot is above default but not publication-ready
• Bottom canvas whitespace reduces layout score slightly
• Library Mastery could be pushed further: a Highcharts colorAxis or gradient zone would make the time-coloring more idiomatic and visually impactful

Issues Found

1. DE-01 MEDIUM (5/8): Aesthetically intentional but not publication-ready — custom gradient is a good start but typography hierarchy and overall visual refinement could be stronger
   • Fix: Consider a more deliberate color ramp (e.g., viridis-inspired) for the gradient; add slight padding refinement; ensure the legend styling feels cohesive with the chart body
2. DE-02 MEDIUM (4/6): Grid styling is refined but spines/axis lines are still fully visible
   • Fix: Remove or fade the x/y axis line (lineWidth: 0 or very light color) and rely on the grid for structure; increase marginBottom slightly to remove bottom whitespace
3. LM-02 MEDIUM (3/5): Per-point coloring is correct but a Highcharts colorAxis would be more idiomatic for continuous gradients
   • Fix: Use a colorAxis with a blue gradient and attach colorKey to the time index — this also gives a native color scale legend

AI Feedback for Next Attempt

Focus on design polish: (1) replace manual per-point color loop with a Highcharts colorAxis driven by the time index — this is more idiomatic, gives a native legend, and allows a cleaner gradient; (2) increase bottom margin slightly to eliminate the whitespace gap below the x-axis; (3) lighten or remove the x/y axis spine lines (lineColor: "transparent") to rely purely on the subtle grid, creating a cleaner, more modern look; (4) consider making the diagonal reference line slightly thicker or a more distinct color to better contrast with the dense central cluster.

Verdict: REJECTED