feat(seaborn): implement eye-diagram-basic

[github-actions]

Implementation: eye-diagram-basic - seaborn

Implements the seaborn version of eye-diagram-basic.

File: plots/eye-diagram-basic/implementations/seaborn.py

Parent Issue: #4561

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🤖 impl-generate workflow

[claude]

AI Review - Attempt 1/3

Image Description

The plot displays an eye diagram on a black background using the inferno colormap. Two wide-open eye shapes span 0–2 UI on the x-axis ("Time (UI)"). The y-axis shows "Voltage (V)" ranging from approximately −0.2 to 1.2. Bright yellow/white bands at the 0V and 1V signal levels indicate high trace density, while transitions between levels form the characteristic eye openings in dark black. The title reads "eye-diagram-basic · seaborn · pyplots.ai" in white text. Top and right spines are removed; bottom and left spines are gray. Subtle dashed reference lines appear at 0V and 1V. The overall visual is striking and professional.

Score: 0/100

Category	Score	Max
Visual Quality	0	30
Design Excellence	0	20
Spec Compliance	0	15
Data Quality	0	15
Code Quality	0	10
Library Mastery	0	10
Total	0	100

⛔ Auto-Reject: AR-05 — Library Not Used

Seaborn is not imported or used anywhere in this implementation. The file imports only matplotlib.pyplot, matplotlib.colors, numpy, and scipy.ndimage. There is zero seaborn usage — no import seaborn as sns, no sns.* plot calls. This is a pure matplotlib implementation mislabeled as seaborn.

Per AR-05 rules: seaborn implementations must use seaborn plotting functions (sns.histplot, sns.heatmap, sns.kdeplot, etc.), not just styling utilities.

Quality Assessment (for repair guidance only — not scored due to AR-05)

The visual output is actually excellent. If this were a matplotlib implementation, it would score well (~84/100). Key quality notes for the repair:

What works well (keep these):

• Dark background with inferno colormap is visually striking
• PowerNorm with gamma=0.35 creates good density contrast
• Signal simulation is realistic (NRZ with noise, jitter, bandwidth limiting)
• Font sizes explicitly set (title 24, labels 20, ticks 16)
• Top/right spines removed, subtle reference lines
• Good canvas utilization and layout
• Title format correct

What must change:

• Must use seaborn plotting functions. Options:
  • sns.histplot(x=all_time, y=all_voltage, bins=(400, 250), cmap='inferno', cbar=True) for 2D histogram
  • sns.kdeplot(x=all_time, y=all_voltage, fill=True, cmap='inferno', levels=...) for density
  • The 2D histplot approach is most faithful to the current visual

Strengths

• Excellent signal simulation with realistic NRZ parameters (noise σ=5%, jitter σ=3%)
• Striking dark-theme density visualization with custom PowerNorm
• Professional layout with properly sized text and removed spines

Weaknesses

• CRITICAL: Seaborn is not used at all — pure matplotlib implementation (AR-05 violation)
• Missing optional eye height/width annotations (minor, spec says "optionally")

Issues Found

1. AR-05 CRITICAL: Seaborn library not imported or used. Zero sns.* calls in the entire file.
   • Fix: Use sns.histplot() with bivariate (x, y) data to create the 2D density heatmap, or sns.kdeplot() for a KDE-based approach. Apply seaborn theming with sns.set_theme().

AI Feedback for Next Attempt

The implementation must use seaborn plotting functions — this is the single blocking issue. Use sns.histplot(x=..., y=..., bins=..., cmap='inferno') for the 2D density visualization instead of manual np.histogram2d + ax.imshow. Keep the excellent signal simulation, dark theme, and PowerNorm approach but route them through seaborn's API. Also consider sns.set_theme(style='dark') for idiomatic seaborn styling.

Verdict: REJECTED

[github-actions]

❌ AI Review Failed

The AI review action completed but did not produce valid output files.

What happened:

• The Claude Code Action ran
• No quality_score.txt file was created
• No review data was extracted

Action required:
Re-run the impl-review workflow manually:

gh workflow run impl-review.yml -f pr_number=4978

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🤖 impl-review