feat(highcharts): implement histogram-cumulative

[github-actions]

Implementation: histogram-cumulative - highcharts

Implements the highcharts version of histogram-cumulative.

File: plots/histogram-cumulative/implementations/highcharts.py

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🤖 impl-generate workflow

[claude]

AI Review - Attempt 1/3

Image Description

The plot displays a cumulative histogram showing student test score distribution. The chart uses a step-area visualization with a blue color (#306998) and gradient fill transitioning from semi-transparent blue at the top to nearly transparent at the bottom. The title "histogram-cumulative · highcharts · pyplots.ai" appears at the top in bold, with a subtitle "Student Test Score Distribution (n=280)" below it. The x-axis shows "Test Score" ranging from 0 to 100, and the y-axis shows "Cumulative Percentage (%)" from 0% to 100%. Blue circular markers appear at each data point along the step function. The curve is monotonically increasing as expected for a cumulative distribution, with steeper slopes in the 40-80 range indicating where most scores fall. Grid lines are subtle light gray.

Quality Score: 91/100

Criteria Checklist

Visual Quality (36/40 pts)

• VQ-01: Text Legibility (9/10) - Title, subtitle, axis labels and tick labels are all clearly readable. Font sizes are appropriate for the 4800x2700 canvas.
• VQ-02: No Overlap (8/8) - No overlapping text elements anywhere in the chart.
• VQ-03: Element Visibility (7/8) - Markers are well-sized (radius 10), line width is good (4px). The step pattern is clearly visible. Minor deduction as markers could be slightly larger.
• VQ-04: Color Accessibility (5/5) - Uses single blue color (#306998), colorblind-safe, no red-green issues.
• VQ-05: Layout Balance (4/5) - Good margins and spacing. Plot area is well-utilized. Minor wasted space on the right side.
• VQ-06: Axis Labels (2/2) - "Test Score" and "Cumulative Percentage (%)" are descriptive with units.
• VQ-07: Grid & Legend (1/2) - Grid is subtle (light gray #e0e0e0). Legend is enabled but positioned by default rather than optimally placed.

Spec Compliance (25/25 pts)

• SC-01: Plot Type (8/8) - Correct cumulative histogram using step-area chart, showing monotonically increasing cumulative distribution.
• SC-02: Data Mapping (5/5) - X-axis correctly shows bin values (score), Y-axis shows cumulative percentage.
• SC-03: Required Features (5/5) - Shows cumulative count as percentage, step function appearance, proper bin boundaries.
• SC-04: Data Range (3/3) - X-axis shows 0-100 (full score range), Y-axis shows 0-100%.
• SC-05: Legend Accuracy (2/2) - "Cumulative Distribution" label is accurate.
• SC-06: Title Format (2/2) - Correctly uses "histogram-cumulative · highcharts · pyplots.ai" format.

Data Quality (18/20 pts)

• DQ-01: Feature Coverage (7/8) - Shows cumulative distribution with interesting shape (multimodal underlying data creates visible inflection points). The S-curve shape demonstrates percentile concepts well.
• DQ-02: Realistic Context (7/7) - Student test scores is a realistic, neutral educational scenario. The n=280 sample size is reasonable.
• DQ-03: Appropriate Scale (4/5) - Scores clipped to 0-100 are realistic. The tri-modal distribution (struggling/average/high performers) is plausible but somewhat stylized.

Code Quality (9/10 pts)

• CQ-01: KISS Structure (3/3) - Linear structure: imports → data → chart config → export. No functions or classes.
• CQ-02: Reproducibility (3/3) - Uses np.random.seed(42) for reproducible results.
• CQ-03: Clean Imports (2/2) - All imports are used (numpy, highcharts_core, selenium, etc.).
• CQ-04: No Deprecated API (1/1) - Uses current highcharts_core API.
• CQ-05: Output Correct (0/1) - Note: Image height is 2561px instead of specified 2700px (likely browser rendering difference).

Library Features (3/5 pts)

• LF-01: Uses distinctive library features (3/5) - Uses Highcharts step area chart with gradient fill, proper series configuration. Could leverage more Highcharts-specific features like tooltips configuration or animation settings.

Strengths

• Excellent step-area visualization that clearly shows cumulative distribution behavior
• Proper use of gradient fill creates visually appealing depth effect
• Clear title format following pyplots.ai convention with informative subtitle
• Well-chosen realistic educational context with appropriate sample size
• Good colorblind-safe color choice (#306998)
• Proper use of Selenium for PNG export with inline Highcharts JS

Weaknesses

• Legend could be positioned more optimally (e.g., inside the plot area in lower-right corner)
• Output image height slightly differs from specified 2700px

Verdict: APPROVED