feat(altair): implement spectrum-basic

[github-actions]

Implementation: spectrum-basic - altair

Implements the altair version of spectrum-basic.

File: plots/spectrum-basic/implementations/altair.py

Parent Issue: #2926

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🤖 impl-generate workflow

[claude]

AI Review - Attempt 1/3

Image Description

The plot displays a frequency spectrum with a blue line on a white background. The X-axis shows "Frequency (Hz)" from 0 to 300 Hz, and the Y-axis shows "Amplitude (dB)" from -80 to 10 dB. Three distinct peaks are clearly visible: a dominant peak at 50 Hz reaching approximately 0 dB, a secondary peak at 120 Hz at about -7 dB, and a smaller peak at 200 Hz at approximately -13 dB. The noise floor fluctuates around -45 to -50 dB. The title "spectrum-basic · altair · pyplots.ai" appears at the top. Subtle gray grid lines are visible, and the overall layout is well-balanced with good canvas utilization.

Quality Score: 98/100

Criteria Checklist

Visual Quality (40/40 pts)

• VQ-01: Text Legibility (10/10) - All text clearly readable at full size
• VQ-02: No Overlap (8/8) - No overlapping text elements
• VQ-03: Element Visibility (8/8) - Line stroke width appropriate for data density
• VQ-04: Color Accessibility (5/5) - Single blue color with good contrast
• VQ-05: Layout Balance (5/5) - Excellent canvas utilization, balanced margins
• VQ-06: Axis Labels (2/2) - Both axes have units (Hz, dB)
• VQ-07: Grid & Legend (2/2) - Subtle grid (alpha 0.3), no legend needed

Spec Compliance (25/25 pts)

• SC-01: Plot Type (8/8) - Correct line chart for frequency spectrum
• SC-02: Data Mapping (5/5) - Frequency on X, Amplitude on Y
• SC-03: Required Features (5/5) - FFT data, dB scale, clear frequency components
• SC-04: Data Range (3/3) - Full 0-300 Hz range shows all peaks
• SC-05: Legend Accuracy (2/2) - N/A (single series)
• SC-06: Title Format (2/2) - Correct format: spectrum-basic · altair · pyplots.ai

Data Quality (20/20 pts)

• DQ-01: Feature Coverage (8/8) - Shows dominant peak, harmonics, weak component, and noise floor
• DQ-02: Realistic Context (7/7) - Signal processing scenario with realistic frequency components
• DQ-03: Appropriate Scale (5/5) - Realistic values for audio/signal analysis

Code Quality (10/10 pts)

• CQ-01: KISS Structure (3/3) - Linear flow: imports → data → plot → save
• CQ-02: Reproducibility (3/3) - Uses np.random.seed(42)
• CQ-03: Clean Imports (2/2) - Only necessary imports used
• CQ-04: No Deprecated API (1/1) - Current Altair API
• CQ-05: Output Correct (1/1) - Saves plot.png and plot.html

Library Features (3/5 pts)

• LF-01: Uses distinctive library features (3/5) - Tooltips with formatting, declarative encoding, configure chain

Strengths

• Excellent FFT computation with proper normalization and dB conversion
• Clear visualization of multiple frequency components (50 Hz dominant, 120 Hz secondary, 200 Hz weak)
• Appropriate use of Altair's declarative encoding with typed columns (:Q)
• Interactive tooltips with number formatting
• Proper scale domains for both axes ensure all data is visible
• Clean KISS code structure with no unnecessary complexity

Weaknesses

• Could add mark_rule() or mark_point() to highlight the peak frequencies for enhanced clarity
• No use of Altair's selection/interactivity features (zoom/pan) which would enhance exploration

Verdict: APPROVED