feat(highcharts): implement timeseries-forecast-uncertainty

[github-actions]

Implementation: timeseries-forecast-uncertainty - highcharts

Implements the highcharts version of timeseries-forecast-uncertainty.

File: plots/timeseries-forecast-uncertainty/implementations/highcharts.py

Parent Issue: #3188

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🤖 impl-generate workflow

[claude]

AI Review - Attempt 1/3

Image Description

The plot displays a time series forecast with uncertainty bands. The chart shows historical product demand data (Jan 2022 - Dec 2024) as a solid blue line with circular markers, followed by forecast data (Jan 2025 - Nov 2025) as a dashed orange line with diamond markers. Two nested confidence bands are shown: a lighter pale yellow/cream band for 95% CI and a darker golden yellow band for 80% CI, both widening over time to represent increasing uncertainty. A vertical dashed gray line labeled "Forecast Start" clearly delineates the historical from forecast periods. The title follows the required format "timeseries-forecast-uncertainty · highcharts · pyplots.ai" with a descriptive subtitle. Axes are properly labeled ("Date" for X, "Product Demand (Units)" for Y), and a clear legend at the bottom identifies all four series.

Quality Score: 93/100

Criteria Checklist

Visual Quality (37/40 pts)

• VQ-01: Text Legibility (10/10) - All text is clearly readable: title at 56px, axis labels at 36px, tick labels at 28px
• VQ-02: No Overlap (8/8) - No overlapping text elements; date labels are well spaced
• VQ-03: Element Visibility (7/8) - Line width and markers are appropriate; confidence bands are visible but could have slightly more contrast
• VQ-04: Color Accessibility (5/5) - Blue historical vs orange forecast with yellow bands - colorblind-safe palette, no red-green issues
• VQ-05: Layout Balance (5/5) - Chart fills canvas well with good margins, legend positioned appropriately at bottom
• VQ-06: Axis Labels (2/2) - Y-axis has units "Product Demand (Units)", X-axis has "Date"
• VQ-07: Grid & Legend (0/2) - Grid is subtle (alpha 0.1), but legend could be better positioned/sized

Spec Compliance (25/25 pts)

• SC-01: Plot Type (8/8) - Correct time series forecast with uncertainty bands
• SC-02: Data Mapping (5/5) - Date on X, demand on Y, correctly mapped
• SC-03: Required Features (5/5) - All features present: historical line, forecast line (dashed), 80% and 95% CI bands, vertical forecast start line
• SC-04: Data Range (3/3) - All data visible within axis ranges
• SC-05: Legend Accuracy (2/2) - Legend correctly identifies all four series
• SC-06: Title Format (2/2) - Title follows exact format: {spec-id} · {library} · pyplots.ai

Data Quality (18/20 pts)

• DQ-01: Feature Coverage (7/8) - Shows trend, seasonality, and widening uncertainty; could show more variation in forecast pattern
• DQ-02: Realistic Context (7/7) - Monthly product demand is a realistic business scenario
• DQ-03: Appropriate Scale (4/5) - Values 80-225 units are reasonable; time span appropriate

Code Quality (10/10 pts)

• CQ-01: KISS Structure (3/3) - Linear script structure: imports → data → plot → save
• CQ-02: Reproducibility (3/3) - np.random.seed(42) used
• CQ-03: Clean Imports (2/2) - All imports are used
• CQ-04: No Deprecated API (1/1) - Uses current highcharts-core 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) - Uses AreaRangeSeries for CI bands, LineSeries with dashed style, plotLines for forecast marker - good usage but not exceptional

Strengths

• Excellent implementation of nested confidence bands using AreaRangeSeries with proper z-ordering
• Clear visual distinction between historical (solid blue) and forecast (dashed orange) data
• Professional use of plotLines to mark forecast start with label
• High-resolution output (4800x2700) with appropriate font scaling
• Good use of shared tooltip for interactive viewing
• Both PNG and HTML outputs provided

Weaknesses

• Confidence bands use similar yellow tones (rgba(255, 212, 59, 0.25) and 0.45) - slightly more color differentiation would improve clarity
• Legend symbols at bottom are small relative to the large canvas

Verdict: APPROVED