feat(seaborn): implement line-stepwise

[github-actions]

Implementation: line-stepwise - seaborn

Implements the seaborn version of line-stepwise.

File: plots/line-stepwise/implementations/seaborn.py

---

🤖 impl-generate workflow

[claude]

AI Review - Attempt 1/3

Image Description

The plot displays a step line chart showing server load percentage (0-100%) over 24 hours (Hour of Day 0-23). A blue step line with steps-post style creates clear horizontal segments that persist until the next data point, then jump vertically to the new value. Yellow circular markers (with blue edges) appear at each data point, making the actual measurements visible. The title "line-stepwise · seaborn · pyplots.ai" is displayed at the top. The background uses seaborn's whitegrid style with subtle dashed grid lines (alpha ~0.3). X-axis ticks appear every 2 hours. The data shows a realistic server load pattern: low overnight (~15-25%), ramping up in morning (~40-70%), peak during business hours (~75-92%), and declining in evening back to ~25%.

Quality Score: 92/100

Criteria Checklist

Visual Quality (37/40 pts)

• VQ-01: Text Legibility (10/10) - Title 24pt, labels 20pt, ticks 16pt - all perfectly readable
• VQ-02: No Overlap (8/8) - No overlapping text elements
• VQ-03: Element Visibility (7/8) - Step line (linewidth=3) and markers (s=150) are clearly visible, but markers could be slightly smaller for better step visibility
• VQ-04: Color Accessibility (5/5) - Blue/yellow combination is colorblind-safe with good contrast
• VQ-05: Layout Balance (5/5) - Plot fills canvas well with balanced margins
• VQ-06: Axis Labels (2/2) - "Hour of Day" and "Server Load (%)" with units
• VQ-07: Grid & Legend (0/2) - Grid alpha is 0.3 which is acceptable, but no legend is needed here (-0 for no legend issue, however sns.set_style("whitegrid") is called after subplot creation which may not apply correctly)

Spec Compliance (25/25 pts)

• SC-01: Plot Type (8/8) - Correct step function plot with horizontal-then-vertical transitions
• SC-02: Data Mapping (5/5) - X=time (hours), Y=values that change at specific points
• SC-03: Required Features (5/5) - Step alignment (post), clear distinction from smooth interpolation, horizontal segments show persistence, vertical segments show changes
• SC-04: Data Range (3/3) - Axes show all data (x: -0.5 to 23.5, y: 0 to 105)
• SC-05: Legend Accuracy (2/2) - N/A (single series, no legend needed)
• SC-06: Title Format (2/2) - Correct format: "line-stepwise · seaborn · pyplots.ai"

Data Quality (18/20 pts)

• DQ-01: Feature Coverage (7/8) - Shows step transitions, value persistence, discrete jumps; could show multiple step styles (pre/mid/post) but single style is acceptable
• DQ-02: Realistic Context (7/7) - Server load over 24 hours is a realistic, neutral scenario - low at night, high during business hours
• DQ-03: Appropriate Scale (4/5) - Server load 10-100% is realistic; the noise addition with clipping is good, though the base pattern is somewhat predictable

Code Quality (10/10 pts)

• CQ-01: KISS Structure (3/3) - Imports → Data → Plot → Save structure, no functions/classes
• CQ-02: Reproducibility (3/3) - np.random.seed(42) is set
• CQ-03: Clean Imports (2/2) - All imports are used (matplotlib.pyplot, numpy, seaborn)
• CQ-04: No Deprecated API (1/1) - Uses current seaborn API
• CQ-05: Output Correct (1/1) - Saves as plot.png

Library Features (2/5 pts)

• LF-01: Uses distinctive library features (2/5) - Uses sns.lineplot with drawstyle and sns.scatterplot, but drawstyle is a matplotlib passthrough parameter, not a seaborn-native feature. Could have used more seaborn-specific features like statistical aggregation or themed palettes.

Strengths

• Excellent visualization of step function with clear horizontal and vertical transitions
• Realistic server load scenario that demonstrates the plot type well
• Perfect text sizing and legibility at target resolution
• Good use of markers to highlight actual data points on the step line
• Clean color scheme (Python blue/yellow) with good colorblind accessibility
• Proper title format following spec-id · library · pyplots.ai convention

Weaknesses

• sns.set_style("whitegrid") is called after figure creation, which may not apply the style correctly (should be called before plt.subplots)
• Limited use of seaborn-specific features - the implementation relies heavily on matplotlib's drawstyle parameter passed through seaborn

Verdict: APPROVED