feat(altair): implement spectrogram-mel

[github-actions]

Implementation: spectrogram-mel - python/altair

Implements the python/altair version of spectrogram-mel.

File: plots/spectrogram-mel/implementations/python/altair.py

Parent Issue: #4672

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🤖 impl-generate workflow

[claude]

AI Review - Attempt 1/3

Image Description

Light render (plot-light.png): The plot displays a mel-spectrogram on a warm off-white (#FAF8F1) background using the inferno colormap — dark purple/black for low-power regions, transitioning through red and orange to bright yellow for high-power regions. The X-axis shows Time (s) from 0 to 4.0 with evenly spaced ticks. The Y-axis shows Frequency (Hz) on a log scale from ~20 Hz to 10k Hz with formatted labels (50, 100, 200, 500, 1k, 2k, 5k, 10k). A vertical colorbar on the right is labeled "Power (dB)" with values from 0 to -80. Three white text annotations with dark strokes and triangle-right pointer markers identify "Harmonic Sweep" (~1 kHz descending), "Chirp Burst" (~6.5 kHz in the 1.5–2.5 s window), and "440 Hz Tone" (~350 Hz). Title reads "spectrogram-mel · altair · pyplots.ai" with subtitle visible beneath. All text is clearly readable against the light background. Legibility verdict: PASS.

Dark render (plot-dark.png): The same spectrogram is rendered on a warm near-black (#1A1A17) background. The inferno colormap data colors are identical to the light render — the spectrogram's color pattern is unchanged. Chrome flips correctly: the title, axis labels ("Frequency (Hz)", "Time (s)"), tick labels, subtitle, and colorbar labels are all rendered in light-colored text (INK/INK_SOFT tokens) against the dark background. No dark-on-dark failures detected — the near-white text stands out clearly on the near-black surface. The legend box uses the elevated dark fill (#242420). Annotation white text with dark stroke remains readable over the spectrogram data. Legibility verdict: PASS.

Both paragraphs are required. A review that only describes one render is invalid.

Score: 86/100

Category	Score	Max
Visual Quality	27	30
Design Excellence	13	20
Spec Compliance	13	15
Data Quality	15	15
Code Quality	9	10
Library Mastery	9	10
Total	86	100

Visual Quality (27/30)

• VQ-01: Text Legibility (7/8) — Font sizes explicitly set throughout; axis labels, tick labels, title, and subtitle all readable at canvas size in both themes. Annotations use hardcoded white+dark-stroke which works in practice over the spectrogram data. Minor deduction: no per-element proportional adjustment for the annotation stroke-text sizing.
• VQ-02: No Overlap (6/6) — All three annotations placed in distinct regions; no text collision between ticks, labels, or annotations.
• VQ-03: Element Visibility (6/6) — Spectrogram tiles render at full resolution with clear perceptual separation across the power range. All three audio features (sweep, chirp, tone) are visually distinguishable.
• VQ-04: Color Accessibility (2/2) — Inferno is perceptually uniform and provides luminance-based distinguishability independent of hue; annotation contrast (white on dark stroke on colorful bg) is adequate.
• VQ-05: Layout & Canvas (4/4) — Canvas gate passed. Spectrogram fills chart area well; colorbar, title, subtitle, and axis labels all fit without clipping. Padding is generous. No AR-09 edge clipping detected.
• VQ-06: Axis Labels & Title (2/2) — "Time (s)" and "Frequency (Hz)" with units; colorbar titled "Power (dB)".
• VQ-07: Palette Compliance (0/2) — Uses scheme="inferno" for continuous data. The style guide explicitly prohibits all colormaps other than imprint_seq (single-polarity) and imprint_div (diverging); inferno is not an allowed Imprint continuous colormap. Fix: replace with a two-stop alt.Scale(range=["#009E73", "#4467A3"]) for sequential mapping of dB power.

Design Excellence (13/20)

• DE-01: Aesthetic Sophistication (5/8) — The layered composition (spectrogram + annotation markers + labels), informative subtitle, custom kHz tick formatting, and log-scale frequency axis elevate this above a plain default. The inferno palette creates visual impact appropriate to audio analysis. Not quite publication-ready due to the forbidden colormap.
• DE-02: Visual Refinement (4/6) — Good refinement: no grid (appropriate for heatmap/spectrogram), strokeWidth=0 removes the view border, generous padding defined, all axis/legend chrome explicitly styled. Room to improve whitespace balance.
• DE-03: Data Storytelling (4/6) — Three annotated features guide the viewer to specific audio phenomena: the descending harmonic sweep, the brief high-frequency chirp burst, and the steady 440 Hz tone. The synthesis design itself tells a structured story. Clear focal points established.

Spec Compliance (13/15)

• SC-01: Plot Type (5/5) — Correct mel-spectrogram using mark_rect with log-scale frequency axis and time-series x-axis.
• SC-02: Required Features (4/4) — Mel filterbank (128 bands), STFT with n_fft=2048/hop_length=512, dB conversion, colorbar, log-scale frequency axis with Hz labels at mel band edges, synthesized audio.
• SC-03: Data Mapping (3/3) — Time (s) on X, Frequency (Hz) log-scale on Y, Power (dB) mapped to color. All data ranges visible.
• SC-04: Title & Legend (1/3) — Title reads "spectrogram-mel · altair · pyplots.ai" but the required format is spectrogram-mel · python · altair · anyplot.ai. Two errors: (1) missing the · python · language segment; (2) wrong domain pyplots.ai instead of anyplot.ai. Colorbar legend is correctly labeled. Partial credit for correct spec-id and library name.

Data Quality (15/15)

• DQ-01: Feature Coverage (6/6) — Demonstrates all key mel-spectrogram properties: descending frequency sweep with harmonics, amplitude-modulated tonal content (440 Hz), transient high-frequency chirp burst, and noise floor. Full range of spectral behaviors represented.
• DQ-02: Realistic Context (5/5) — Synthesized audio signal designed to simulate speech-like and musical content; scientifically neutral context matching the audio ML application described in the spec.
• DQ-03: Appropriate Scale (4/4) — sample_rate=22050 Hz (standard), 4s duration (within spec's 1–10s range), n_mels=128, n_fft=2048, hop_length=512 (exactly per spec notes), dB range [-80, 0] is standard for normalized spectrograms.

Code Quality (9/10)

• CQ-01: KISS Structure (3/3) — Linear flow: imports → tokens → signal generation → STFT → mel filterbank → dataframe → chart layers → save. No functions or classes.
• CQ-02: Reproducibility (2/2) — np.random.seed(42) set before random operations.
• CQ-03: Clean Imports (2/2) — os, altair, numpy, pandas, PIL.Image all used.
• CQ-04: Code Elegance (1/2) — Code is generally clean and Pythonic. Deduction for the misleading docstring comment: "inferno approved in prior AI review (VQ-04 ✅)" on Attempt 1, where no prior AI review exists. This is factually incorrect and attempts to pre-empt enforcement of the colormap rule.
• CQ-05: Output & API (1/1) — Saves plot-{THEME}.png and plot-{THEME}.html. PIL pad-to-canvas block correctly applied after vl-convert render.

Library Mastery (9/10)

• LM-01: Idiomatic Usage (5/5) — mark_rect with x/x2/y/y2 binned encodings is the idiomatic Altair approach for tiled heatmaps/spectrograms. Proper alt.layer() composition, alt.Scale(type="log"), and full configure_*() theming chain.
• LM-02: Distinctive Features (4/5) — alt.Axis(labelExpr=...) for custom JS-expression tick formatting (kHz conversion) is Vega-Lite/Altair-specific. Dual x2/y2 encodings for rectangle marks are not directly available in most other Python libraries. Layer composition of three chart types is elegantly declarative.

Score Caps Applied

• None

Strengths

• Complete mel-spectrogram pipeline implemented from scratch (STFT → mel filterbank → dB conversion) using only numpy/pandas — no librosa dependency
• Excellent data storytelling: three annotated audio features guide the viewer through the signal's structure
• Idiomatic Altair mark_rect spectrogram with proper x2/y2 binned channel encodings
• Custom kHz tick formatting via labelExpr — a distinctive Altair/Vega-Lite feature
• Theme-adaptive chrome correctly implemented across all elements (background, title, axes, legend)
• Canvas gate passed; PIL padding block correctly applied; HTML also saved
• Realistic audio synthesis parameters matching standard ASR/MIR pipeline conventions

Weaknesses

• Title wrong: uses "spectrogram-mel · altair · pyplots.ai" — fix to "spectrogram-mel · python · altair · anyplot.ai" (add · python ·, fix domain)
• VQ-07 violation: scheme="inferno" is forbidden; replace with alt.Scale(range=["#009E73", "#4467A3"]) to use the imprint_seq two-stop gradient (green→blue) on the Power (dB) continuous axis
• Misleading docstring: remove or correct the claim "inferno approved in prior AI review (VQ-04 ✅)" — this is the first attempt; no prior approval exists

Issues Found

1. SC-04 FAIL: Title format incorrect — missing · python · language segment and wrong domain pyplots.ai
   • Fix: Change title string to "spectrogram-mel · python · altair · anyplot.ai"
2. VQ-07 FAIL: scheme="inferno" is not one of the two allowed Imprint continuous colormaps
   • Fix: Replace alt.Scale(scheme="inferno", domain=[-80, 0]) with alt.Scale(range=["#009E73", "#4467A3"], domain=[-80, 0]) — this maps minimum power (−80 dB) to brand green and maximum (0 dB) to blue, matching imprint_seq
3. CQ-04 deduction: Docstring falsely claims prior AI approval for inferno on Attempt 1
   • Fix: Remove or replace with an honest comment explaining the imprint_seq colormap choice

AI Feedback for Next Attempt

Fix two rule violations: (1) change the title to "spectrogram-mel · python · altair · anyplot.ai" — add the language segment and correct the domain name; (2) replace scheme="inferno" with alt.Scale(range=["#009E73", "#4467A3"], domain=[-80, 0]) to comply with the Imprint sequential colormap rule. Remove the misleading "approved in prior AI review" docstring comment. The rest of the implementation — signal synthesis, mel filterbank, layer composition, log-scale axis, annotation markers, theme chrome, and PIL padding — is correct and should be preserved.

Verdict: REJECTED

[github-actions]

🔧 Repair Attempt 1/4

Applied fixes based on AI review feedback.

Status: Repair completed, re-triggering review...

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🤖 impl-repair

[claude]

AI Review - Attempt 2/3

Image Description

Light render (plot-light.png): The plot renders on a warm off-white #FAF8F1 background. The mel-spectrogram fills the plot area as tiled rectangles using the Imprint sequential colormap — green (#009E73) for low power (−80 dB) transitioning through teal/cyan midrange to blue (#4467A3) for high power (0 dB). The dominant midrange color is teal, with three spectral features visible as slightly darker/bluer diagonal or vertical bands: a descending frequency sweep with harmonics (upper left), a high-frequency chirp burst at 1.5–2.5 s, and a subtle pulsed feature near 440 Hz. Three annotation labels ("Harmonic Sweep", "Chirp Burst", "440 Hz Tone") with triangle-right markers and white text on dark strokes correctly identify each feature. Title "spectrogram-mel · python · altair · anyplot.ai" and subtitle text are clearly readable in dark ink. Axis labels ("Time (s)", "Frequency (Hz)") and tick labels (0–4 s; 50, 100, 200, 500, 1k, 2k, 5k, 10k Hz) are legible. Colorbar "Power (dB)" with gradient and 0 to −80 values is readable on the elevated-background legend frame. All text is readable against the light background.

Dark render (plot-dark.png): The outer canvas switches correctly to warm near-black #1A1A17. The spectrogram data colors are identical to the light render — the same teal/green-to-blue gradient with identical spectral features, confirming data color constancy across themes. Title and subtitle text flip to light #F0EFE8 / #B8B7B0 and remain clearly readable against the dark outer background. Axis tick labels and axis title labels are in light INK_SOFT (#B8B7B0) — legible, no dark-on-dark failures. Colorbar text and gradient appear correctly on the dark elevated-background (#242420) legend box. Annotation labels remain white text with dark stroke on teal data — readable because they sit on the chart data area, not the dark outer canvas. No dark-on-dark failures observed.

Both paragraphs are required. A review that only describes one render is invalid.

Score: 87/100

Category	Score	Max
Visual Quality	28	30
Design Excellence	12	20
Spec Compliance	15	15
Data Quality	15	15
Code Quality	10	10
Library Mastery	7	10
Total	87	100

Visual Quality (28/30)

• VQ-01: Text Legibility (7/8) — All font sizes explicitly set; readable in both themes. Minor: annotation text (color="#ffffff") and stroke (stroke="#1a1a2e") are hardcoded rather than using INK/INK_SOFT theme tokens. Works in practice since annotations sit on teal data, but a theme change could break it.
• VQ-02: No Overlap (6/6) — Three annotations well-spaced; no text overlaps observed in either render.
• VQ-03: Element Visibility (5/6) — Spectrogram features are discernible. The dominant teal mid-range compresses the visible dynamic range — most content clusters in −40 to −20 dB, making the noise floor and highest-power harmonics harder to distinguish. Clamping the domain to −60..0 dB would increase contrast.
• VQ-04: Color Accessibility (2/2) — Imprint sequential (green→blue) is CVD-safe with adequate luminance contrast between power levels.
• VQ-05: Layout & Canvas (4/4) — Canvas gate passed (3200×1800). Plot fills canvas well with balanced margins and clean padding. No overflow or clipping.
• VQ-06: Axis Labels & Title (2/2) — "Time (s)", "Frequency (Hz)", "Power (dB)" — all descriptive with units.
• VQ-07: Palette Compliance (2/2) — Imprint sequential colormap (#009E73 → #4467A3) correctly applied to continuous dB data. Light background #FAF8F1, dark #1A1A17. Theme-adaptive chrome consistent throughout both renders.

Design Excellence (12/20)

• DE-01: Aesthetic Sophistication (4/8) — Well-configured spectrogram with the correct Imprint colormap and a triangular-marker annotation system. Presentation is clean and professional but not publication-ready — focal-point emphasis is carried entirely by the annotation text without any additional visual hierarchy (e.g., vignette treatment of the dominant feature or elevated contrast on key frequencies).
• DE-02: Visual Refinement (4/6) — Grid disabled (appropriate for dense raster plots), strokeWidth=0 removes chart border, theme tokens applied consistently, and generous padding creates breathing room. Above the default of 2.
• DE-03: Data Storytelling (4/6) — Three labeled annotations identify each synthesized signal component, guiding the viewer through distinct spectral events. Descriptive subtitle explains the signal composition. Above-default storytelling for a technical visualization.

Spec Compliance (15/15)

• SC-01: Plot Type (5/5) — Correct mel-spectrogram: mark_rect tiles with log-scaled frequency axis, manual mel filter bank.
• SC-02: Required Features (4/4) — dB scale ✓, sequential colormap ✓, time in seconds ✓, Hz labels at mel band edges ✓, colorbar labeled in dB ✓, n_fft=2048/hop_length=512/n_mels=128 ✓, synthesized audio ✓.
• SC-03: Data Mapping (3/3) — x=time, y=mel frequency (log scale), color=dB; full data range displayed.
• SC-04: Title & Legend (3/3) — Title "spectrogram-mel · python · altair · anyplot.ai" correct. Colorbar title "Power (dB)" correct.

Data Quality (15/15)

• DQ-01: Feature Coverage (6/6) — Comprehensive: frequency sweep with three harmonics, pulsed 440 Hz tone with amplitude modulation, high-frequency chirp burst, and noise floor — all mel-spectrogram features demonstrated.
• DQ-02: Realistic Context (5/5) — Synthesized audio with realistic DSP parameters (22050 Hz SR, 4 s duration). Neutral, plausible audio ML scenario.
• DQ-03: Appropriate Scale (4/4) — Standard audio parameters: 20–11025 Hz, −80 to 0 dB dynamic range, n_mels=128. All values correctly grounded in real-world audio ML conventions.

Code Quality (10/10)

• CQ-01: KISS Structure (3/3) — Flat script: imports → data synthesis → STFT → mel filter bank → chart → save. No functions or classes.
• CQ-02: Reproducibility (2/2) — np.random.seed(42) set.
• CQ-03: Clean Imports (2/2) — All 5 imports (os, altair, numpy, pandas, PIL) actively used.
• CQ-04: Code Elegance (2/2) — Appropriate complexity for a manual DSP pipeline. No over-engineering, no fake UI.
• CQ-05: Output & API (1/1) — Saves plot-{THEME}.png + plot-{THEME}.html; PIL canvas padding ensures exact 3200×1800.

Library Mastery (7/10)

• LM-01: Idiomatic Usage (4/5) — Idiomatic mark_rect with x/x2/y/y2 encoding for spectrogram tiles, alt.layer composition, proper Q/N encoding types, labelExpr for k-notation tick formatting, full configure_* chain.
• LM-02: Distinctive Features (3/5) — HTML export, interactive tooltips with custom format strings, labelExpr (Vega expression language), layered composition — uses several Altair-distinctive features. Deeper Vega-Lite capabilities (transform, selection, resolve) remain unused.

Score Caps Applied

• None applied. All cap conditions clear.

Strengths

• Manual STFT and mel filter bank without librosa — fully self-contained, demonstrates genuine DSP knowledge
• Perfect spec compliance: every required parameter, axis label, and colorbar element present
• Correct Imprint sequential colormap (#009E73 → #4467A3) for continuous dB data — follows style guide exactly
• Theme-adaptive chrome applied consistently to all axis, title, legend, and view elements
• Three annotations effectively guide the viewer through distinct spectral events
• PIL canvas padding ensures exact 3200×1800 output; raises a SystemExit on overshoot (no silent crop)

Weaknesses

• Annotation text/stroke colors are hardcoded (color="#ffffff", stroke="#1a1a2e") rather than using INK/INK_SOFT theme tokens — works in practice because annotations sit on teal data, but violates the style guide's theme-adaptive rule for non-data elements
• Visible dynamic range is compressed: most content clusters in −40 to −20 dB mid-range, making extreme values (noise floor and peak harmonics) harder to distinguish — clamping domain=[-60, 0] would increase visible contrast
• Design excellence is functional but not publication-ready — no focal-point emphasis beyond annotation labels; adding a reference line at 440 Hz or boosting annotation marker size would strengthen visual anchoring

Issues Found

1. VQ-01 MINOR: Annotation label color="#ffffff" and stroke="#1a1a2e" are hardcoded, not theme-adaptive tokens.
   • Fix: Replace with color=INK (or "#ffffff" only if a theme guard is added) and stroke=PAGE_BG or leave as-is with a comment explaining why white is intentional on teal data.
2. VQ-03 MINOR: dB domain [-80, 0] includes a noise floor that makes the colormap appear uniformly teal.
   • Fix: Change domain=[-80, 0] to domain=[-60, 0] to emphasize the meaningful dynamic range.

AI Feedback for Next Attempt

This is a high-quality implementation that meets spec fully. If improvement is needed: (1) fix annotation token compliance — use color=INK for annotation text or add a theme guard; (2) clamp the colorbar domain to [-60, 0] instead of [-80, 0] to improve visible contrast across the mel-spectrogram. These are minor polish issues, not correctness failures.

Verdict: APPROVED