feat(ggplot2): implement spectrogram-mel

[github-actions]

Implementation: spectrogram-mel - r/ggplot2

Implements the r/ggplot2 version of spectrogram-mel.

File: plots/spectrogram-mel/implementations/r/ggplot2.R

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 renders on a warm off-white #FAF8F1 background. The title "spectrogram-mel · r · ggplot2 · anyplot.ai" is bold and clearly visible in dark ink. The mel-spectrogram is displayed using a teal-green () to blue () gradient (imprint_seq) — teal-green = −80 dB (low energy), blue = 0 dB (high energy). The C-major arpeggio pattern is visually apparent as horizontal blue bands in the lower frequency region (100 Hz–2k Hz), where note changes are clearly distinguishable. The upper ~65% of the spectrogram (above ~2k Hz) is uniformly teal-green due to the synthesized audio's low high-frequency energy content. Y-axis shows Hz labels at 100 Hz, 250 Hz, 500 Hz, 1k Hz, 2k Hz, 4k Hz, 8k Hz. X-axis shows time 0–4 s. Colorbar labeled "dB" with range −80 to 0 is visible on the right inside an elevated-background box. All text is readable against the light background. No dark-on-light failures.

Dark render (plot-dark.png): The plot renders on a warm near-black #1A1A17 background. Title, axis labels, and tick labels are all rendered in light ink and clearly readable — no dark-on-dark failures. Data colors are identical to the light render (teal-green to blue gradient, same arpeggio pattern visible). The colorbar box uses the dark elevated background () with light text. Chrome (backgrounds, text, legend frame) has correctly flipped to dark-theme tokens while data colors remain unchanged. Both renders pass the theme-readability check.

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

Score: 83/100

Category	Score	Max
Visual Quality	27	30
Design Excellence	10	20
Spec Compliance	15	15
Data Quality	14	15
Code Quality	10	10
Library Mastery	7	10
Total	83	100

Visual Quality (27/30)

• VQ-01: Text Legibility (7/8) — All title, axis, tick, and legend text is readable in both themes at appropriate sizes; small deduction for colorbar tick labels being on the small side at scale
• VQ-02: No Overlap (6/6) — No element collisions in either render
• VQ-03: Element Visibility (4/6) — The arpeggio pattern is visible in lower bands, but the imprint_seq green-to-blue gradient has limited luminance contrast; large uniform teal area in the upper ~65% of the spectrogram (above 2k Hz) shows no structural detail
• VQ-04: Color Accessibility (2/2) — imprint_seq is CVD-safe by design
• VQ-05: Layout & Canvas (4/4) — Correct 3200×1800 canvas, clean proportions, no clipping, legend well-placed
• VQ-06: Axis Labels & Title (2/2) — "Time (s)", "Frequency (Hz)", colorbar "dB" all descriptive with units
• VQ-07: Palette Compliance (2/2) — Sequential colormap built from → (imprint_seq); backgrounds / ; both themes correct

Design Excellence (10/20)

• DE-01: Aesthetic Sophistication (4/8) — Correct palette use and clean layout; no added visual hierarchy, annotation, or emphasis to guide the viewer through the arpeggio structure; no design decisions beyond following the rules
• DE-02: Visual Refinement (3/6) — No grid (appropriate for spectrograms); panel border present; reasonable margins; could benefit from slightly more generous whitespace around the plot area
• DE-03: Data Storytelling (3/6) — The note changes in the arpeggio are visible, but the large monotone upper-frequency area reduces visual impact; no annotation or labeling to highlight what the viewer should notice

Spec Compliance (15/15)

• SC-01: Plot Type (5/5) — Correct mel-spectrogram using geom_tile()
• SC-02: Required Features (4/4) — dB scale conversion ✓, mel filterbank computed from scratch ✓, colorbar labeled in dB ✓, Hz labels at key mel band edges ✓
• SC-03: Data Mapping (3/3) — X = time in seconds, Y = mel band with Hz labels, fill = dB; all axes show full data range
• SC-04: Title & Legend (3/3) — Title is "spectrogram-mel · r · ggplot2 · anyplot.ai" ✓; colorbar labeled "dB" ✓

Data Quality (14/15)

• DQ-01: Feature Coverage (5/6) — Complete mel filterbank, STFT with Hann window, 128 mel bands, peak normalization; slight deduction as the synthesized signal concentrates most energy below 2k Hz, leaving ~65% of the plot with no spectral detail
• DQ-02: Realistic Context (5/5) — C-major arpeggio with harmonics and pluck-style envelope is a realistic, neutral audio ML example
• DQ-03: Appropriate Scale (4/4) — 4 s at 22050 Hz, n_fft=2048, hop_length=512, n_mels=128, −80 to 0 dB range — all within typical parameters

Code Quality (10/10)

• CQ-01: KISS Structure (3/3) — Flat script; small inline helper functions hz_to_mel/mel_to_hz are minimal and necessary
• CQ-02: Reproducibility (2/2) — set.seed(42) ✓
• CQ-03: Clean Imports (2/2) — ggplot2, dplyr, scales, ragg all present; dplyr imported but unused (minor, harmless)
• CQ-04: Code Elegance (2/2) — Clean section structure, no fake UI, no unnecessary complexity
• CQ-05: Output & API (1/1) — Saves as plot-{THEME}.png via sprintf ✓

Library Mastery (7/10)

• LM-01: Idiomatic Usage (4/5) — geom_tile() for heatmap/spectrogram, scale_fill_gradient() for continuous fill, scale_y_continuous() with explicit breaks for mel-band labels — all idiomatic ggplot2
• LM-02: Distinctive Features (3/5) — Uses ggplot2's grammar-of-graphics long-format data pipeline effectively; custom Y-axis break mapping from mel bands to Hz labels is a nice ggplot2 pattern; does not leverage faceting, coord_trans, or other distinctive ggplot2 capabilities that could enhance the visualization

Score Caps Applied

• None

Strengths

• Complete from-scratch mel filterbank and STFT implementation without external audio libraries (librosa) — impressive for R/ggplot2
• Full spec compliance: all required features (mel scale, dB colorbar, Hz tick labels, synthesized audio, correct parameters) implemented correctly
• Theme-adaptive chrome is correctly wired through all elements; both renders pass the readability check with no dark-on-dark failures
• Palette compliance: imprint_seq (#009E73 → #4467A3) is the correct Imprint continuous colormap for single-polarity data
• Clean, flat script structure with clear sections and minimal helper functions

Weaknesses

• VQ-03: The imprint_seq colormap (teal-green to blue) has limited luminance contrast compared to the conventional dark-to-bright spectral colormaps; subtle energy differences in the spectrogram are harder to distinguish. The upper ~65% of the plot area is uniformly teal/green (−80 dB region) with no visible spectral structure, making the visualization look visually flat. Consider synthesizing audio with more high-frequency content (e.g. add noise bursts, higher harmonics, or a wider-bandwidth signal) to better utilize the full frequency axis
• DE-01/DE-03: No visual storytelling or emphasis — the arpeggio note structure is visible but the viewer has no guidance; a simple annotation marking note onsets or a horizontal reference line at the fundamental frequency range would significantly improve the design
• DQ-01: The synthesized signal has most energy below 2 kHz, leaving ~65% of the mel bands (above ~2k Hz) uniformly at −80 dB; for a 128-band mel-spectrogram demo this wastes the frequency axis. Adding higher harmonics, broadband noise, or a frequency sweep would better demonstrate the mel scale's perceptual compression

Issues Found

1. VQ-03 REDUCED: Flat upper frequency region — synthesized audio energy is concentrated below ~2k Hz; the upper 65% of the spectrogram shows no spectral structure
   • Fix: Synthesize broader-bandwidth audio (e.g. add white noise at low amplitude, or extend the arpeggio to include higher octaves) so the mel-scale frequency compression is visually demonstrated across the full axis
2. DE-01/DE-03 LOW: No visual hierarchy or focal point to guide the viewer
   • Fix: Add a subtle annotation (geom_text or geom_hline) marking the fundamental frequency range of the notes, or annotate the time axis with note names to give context to the arpeggio pattern

AI Feedback for Next Attempt

The implementation is technically excellent and spec-compliant. To improve the score: (1) synthesize audio with energy across a wider frequency range so the mel-spectrogram uses more of its vertical axis — add upper octave harmonics, a brief broadband noise layer, or a frequency sweep to demonstrate the mel scale's perceptual compression; (2) add minimal visual storytelling — annotate the note onset positions on the x-axis or add a horizontal band marking the fundamental frequency range to give viewers a focal point; (3) the imprint_seq colormap is correct per palette rules, but the limited contrast it provides for spectrograms means the data representation benefits from more varied audio content.

Verdict: APPROVED

[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 displays on a warm off-white #FAF8F1 background. The mel spectrogram fills the entire plot area as a teal-to-blue heatmap (imprint_seq: #009E73 low → #4467A3 high). The title "spectrogram-mel · r · ggplot2 · anyplot.ai" is bold and dark, occupying ~70% of the plot width. The subtitle "C-major arpeggio · 8 harmonics · mel scale compresses perceptual distances" is readable below. X-axis is labeled "Time (s)" and Y-axis "Frequency (Hz)" with Hz tick labels at 100 Hz, 250 Hz, 500 Hz, 1k Hz, 2k Hz, 4k Hz, 8k Hz. A dashed horizontal line at 1 kHz and dotted vertical onset lines are visible. A colorbar labeled "dB" (0 to -80) is displayed on the right with a subtle border. "Fundamentals" and "Overtones" region annotations are present but subtle in muted gray (#6B6A63) against the teal tiles. All main text is readable against the light background.
Legibility verdict: PASS (with note: annotation text is small and slightly low-contrast on teal tiles)

Dark render (plot-dark.png): The same mel spectrogram appears on a warm near-black #1A1A17 background. Data colors are identical to the light render — the imprint_seq green-to-blue gradient is unchanged. Title, axis labels, and tick labels flip to light ink (#F0EFE8 / #B8B7B0), all clearly readable against the dark background. The "Fundamentals" and "Overtones" annotations use #A8A79F (INK_MUTED dark) which actually reads more clearly against the dark teal tiles than in light mode. The "1 kHz" annotation and dashed boundary line are both visible. The colorbar legend uses the elevated background #242420 with a soft border — clearly readable. No dark-on-dark failures detected.
Legibility verdict: PASS

Score: 88/100

Category	Score	Max
Visual Quality	29	30
Design Excellence	12	20
Spec Compliance	15	15
Data Quality	15	15
Code Quality	10	10
Library Mastery	7	10
Total	88	100

Visual Quality (29/30)

• VQ-01: Text Legibility (7/8) — Title, axis labels, tick labels all explicitly sized and readable at full resolution in both themes. Annotation text at size=2.3 mm (~6.5 pt) is slightly small; "Fundamentals" has marginal contrast against teal tiles in the light render and may not be mobile-readable when scaled to 400 px.
• VQ-02: No Overlap (6/6) — No text-text or text-data overlaps in either render.
• VQ-03: Element Visibility (6/6) — Heatmap tiles clearly visible with full dynamic range; dotted onset lines thin but appropriate as secondary reference elements.
• VQ-04: Color Accessibility (2/2) — imprint_seq (green→blue) is CVD-safe and perceptually uniform.
• VQ-05: Layout & Canvas (4/4) — Canvas 3200×1800 passes gate; proportions appropriate for a spectrogram; colorbar well-positioned.
• VQ-06: Axis Labels & Title (2/2) — "Time (s)", "Frequency (Hz)", colorbar "dB" all labeled with units.
• VQ-07: Palette Compliance (2/2) — Continuous data uses imprint_seq (#009E73 low, #4467A3 high). Backgrounds #FAF8F1 / #1A1A17 correct. All chrome tokens theme-adaptive.

Design Excellence (12/20)

• DE-01: Aesthetic Sophistication (5/8) — Intentional design: custom imprint_seq colormap, annotated frequency boundary at 1 kHz, region labels, percussive burst synthesis for richness. Clear visual hierarchy.
• DE-02: Visual Refinement (4/6) — Grid fully removed (appropriate for heatmap), panel border absent, axis lines styled, legend with subtle elevated-background border. Generous margins at 16 px all sides.
• DE-03: Data Storytelling (3/6) — The 1 kHz dashed boundary with "Fundamentals" / "Overtones" labels and onset markers provide meaningful interpretive scaffolding. Subtitle gives immediate context. However, the color dynamic range of the spectrogram itself (most energy concentrated in a narrow band) somewhat limits visual impact.

Spec Compliance (15/15)

• SC-01: Plot Type (5/5) — Correct mel spectrogram via geom_tile heatmap on mel-scaled frequency axis.
• SC-02: Required Features (4/4) — dB conversion ✓, mel filterbank applied ✓, sequential colormap ✓, colorbar labeled in dB ✓.
• SC-03: Data Mapping (3/3) — X = time in seconds, Y = mel band with Hz labels at key edges, fill = dB values.
• SC-04: Title & Legend (3/3) — Title is spectrogram-mel · r · ggplot2 · anyplot.ai. Colorbar labeled "dB".

Data Quality (15/15)

• DQ-01: Feature Coverage (6/6) — Full 128-band mel spectrogram, 8 harmonics per note, percussive onset bursts, additive noise floor — covers all aspects of the plot type.
• DQ-02: Realistic Context (5/5) — C-major arpeggio is a neutral, universally recognizable audio example with realistic synthesis parameters.
• DQ-03: Appropriate Scale (4/4) — Standard parameters: 22050 Hz SR, n_fft=2048, hop_length=512, n_mels=128, -80 to 0 dB range.

Code Quality (10/10)

• CQ-01: KISS Structure (3/3) — No wrapper functions or classes; hz_to_mel/mel_to_hz helpers are necessary for the filterbank computation.
• CQ-02: Reproducibility (2/2) — set.seed(42) at top.
• CQ-03: Clean Imports (2/2) — ggplot2, scales, ragg — all used.
• CQ-04: Code Elegance (2/2) — DSP complexity is inherent to the plot type; no fake UI elements; clean R idioms throughout.
• CQ-05: Output & API (1/1) — Saves as plot-%s.png with THEME env var; modern linewidth = API used.

Library Mastery (7/10)

• LM-01: Idiomatic Usage (4/5) — geom_tile, scale_fill_gradient with limits/breaks/oob, guide_colorbar with barheight/barwidth, scale_y_continuous with custom breaks/labels, expand = c(0,0) for tight edges. Fully idiomatic ggplot2.
• LM-02: Distinctive Features (3/5) — Full mel filterbank computed in pure R without librosa; custom frequency labels derived from mel scale inversion; guide_colorbar customization; annotate() with fontface = \"italic\" for region labels. Distinctive use of ggplot2's grammar for a DSP-heavy plot type.

Score Caps Applied

• None

Strengths

• Full STFT and mel filterbank implemented in pure R — no librosa dependency, impressive DSP fidelity
• imprint_seq colormap (#009E73 → #4467A3) correctly applied to continuous intensity data
• Complete theme-adaptive chrome with all tokens (INK, INK_SOFT, INK_MUTED, PAGE_BG, ELEVATED_BG)
• Meaningful annotations (1 kHz boundary, region labels, note onset markers) that guide interpretation
• Perfect spec compliance: dB scale, mel filter, colorbar, Hz-labeled y-axis, time x-axis
• Clean, reproducible code with set.seed(42) and no external audio dependencies

Weaknesses

• Annotation text at size=2.3 mm is slightly small; "Fundamentals" in light render has marginal contrast against teal tiles (#6B6A63 on #009E73) — consider raising to size=2.8 and using INK or a slightly brighter token for annotations that sit on colored backgrounds
• Data storytelling could be stronger: the spectrogram dynamic range is dominated by a narrow band of energy; a reference line at a second frequency (e.g., 2 kHz overtone boundary) or slight contrast enhancement of the lower-energy regions would improve visual impact

Issues Found

1. VQ-01 MINOR: Annotation text (size=2.3 mm) slightly small and low-contrast on colored tiles in light render
   • Fix: Raise annotation size to 2.8–3.0; consider using INK_SOFT instead of INK_MUTED for better contrast on the teal background
2. DE-03 MODERATE: Spectrogram energy concentration is visually monotone in the upper frequency region
   • Fix: Consider clamping the dB floor at -60 instead of -80 to improve contrast in the visible energy bands, or add a second annotated boundary

AI Feedback for Next Attempt

This is a strong implementation that passes all spec requirements with excellent code and data quality. To improve the score: (1) raise annotation text sizes from 2.3 to ~2.8–3.0 mm and use INK_SOFT for annotations that overlay colored tiles; (2) consider tightening the colorbar floor from -80 dB to -60 dB to enhance visual contrast in the meaningful energy region; (3) design excellence can be lifted by adding one more interpretive element (e.g., a 2nd annotated frequency boundary or a text callout on a specific note cluster).

Verdict: APPROVED