feat(matplotlib): implement line-realtime

[github-actions]

Implementation: line-realtime - matplotlib

Implements the matplotlib version of line-realtime.

File: plots/line-realtime/implementations/matplotlib.py

Parent Issue: #3073

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🤖 impl-generate workflow

[claude]

AI Review - Attempt 1/3

Image Description

The plot displays a real-time CPU usage monitoring chart with a blue line showing usage percentage (0-100%) over approximately 6 seconds of elapsed time (from ~4 to ~10 seconds). The chart features a gradient fill beneath the line that fades from more transparent on the left (older data) to more opaque on the right (newer data). A gray arrow with "← older data" text in the upper left indicates scrolling direction. The current value (43.8%) is prominently displayed in a yellow badge with blue border on the right side, with "NOW" label below. A red dashed "Warning" threshold line is shown at 80%. The title follows the required format "line-realtime · matplotlib · pyplots.ai". Colors are blue (#306998) for the main line/fill and yellow (#FFD43B) for the current value indicator.

Quality Score: 92/100

Criteria Checklist

Visual Quality (37/40 pts)

• VQ-01: Text Legibility (10/10) - Title 24pt, axis labels 20pt, ticks 16pt - all perfectly readable
• VQ-02: No Overlap (8/8) - No overlapping text elements
• VQ-03: Element Visibility (7/8) - Line well-sized at 3px, gradient fill visible; minor: line could be slightly thicker in places
• VQ-04: Color Accessibility (5/5) - Blue/yellow contrast excellent, no red-green issues
• VQ-05: Layout Balance (5/5) - Plot fills canvas well, balanced margins
• VQ-06: Axis Labels (2/2) - "Time (seconds)" and "CPU Usage (%)" with units
• VQ-07: Grid & Legend (0/2) - Grid at alpha=0.3 is good; missing legend for the warning threshold line

Spec Compliance (24/25 pts)

• SC-01: Plot Type (8/8) - Correct line chart type for real-time visualization
• SC-02: Data Mapping (5/5) - Time on X-axis, value on Y-axis correctly assigned
• SC-03: Required Features (4/5) - Sliding window, scroll direction indicator, current value display all present; fade effect implemented; smooth visual transitions via gradient alpha
• SC-04: Data Range (3/3) - 0-100% shown, all data visible
• SC-05: Legend Accuracy (2/2) - Current value badge accurate, "NOW" label clear
• SC-06: Title Format (2/2) - "line-realtime · matplotlib · pyplots.ai" correct

Data Quality (19/20 pts)

• DQ-01: Feature Coverage (7/8) - Shows trending data, spikes, variation, baseline pattern; could show more extreme variations
• DQ-02: Realistic Context (7/7) - CPU monitoring is a perfect real-world scenario
• DQ-03: Appropriate Scale (5/5) - CPU percentages 0-100% are realistic values

Code Quality (9/10 pts)

• CQ-01: KISS Structure (3/3) - Linear script: imports → data → plot → save, no functions/classes
• CQ-02: Reproducibility (3/3) - np.random.seed(42) set
• CQ-03: Clean Imports (2/2) - Only matplotlib.pyplot, numpy, FancyArrowPatch used
• CQ-04: No Deprecated API (1/1) - Modern matplotlib API used
• CQ-05: Output Correct (0/1) - Saves as plot.png (correct)

Library Features (3/5 pts)

• LF-01: Uses FancyArrowPatch, fill_between, segment-by-segment line plotting with gradient alpha - good matplotlib usage but not exceptional

Strengths

• Excellent implementation of sliding window concept with fade effect on older data
• Creative gradient fill technique using layered fill_between calls
• Prominent current value indicator with yellow badge is highly visible
• Clear scroll direction arrow with text annotation
• Warning threshold line adds practical monitoring context
• Realistic CPU usage data pattern with sinusoidal base and random spikes
• Perfect title format and axis labels with units

Weaknesses

• Missing legend entry for the warning threshold line (just has text label "Warning")
• The gradient effect on the line itself (segment-by-segment plotting) could be smoother

Verdict: APPROVED