From 86a5af6bd191a08e576876c39a4ef75cd1155b44 Mon Sep 17 00:00:00 2001
From: "github-actions[bot]" <github-actions[bot]@users.noreply.github.com>
Date: Wed, 11 Mar 2026 19:42:38 +0000
Subject: [PATCH 1/7] feat(bokeh): implement spectrogram-mel

---
 .../spectrogram-mel/implementations/bokeh.py  | 449 ++++++++++++++++++
 1 file changed, 449 insertions(+)
 create mode 100644 plots/spectrogram-mel/implementations/bokeh.py

diff --git a/plots/spectrogram-mel/implementations/bokeh.py b/plots/spectrogram-mel/implementations/bokeh.py
new file mode 100644
index 0000000000..4dc9432fdf
--- /dev/null
+++ b/plots/spectrogram-mel/implementations/bokeh.py
@@ -0,0 +1,449 @@
+"""pyplots.ai
+spectrogram-mel: Mel-Spectrogram for Audio Analysis
+Library: bokeh | Python 3.13
+Quality: pending | Created: 2026-03-11
+"""
+
+import numpy as np
+from bokeh.io import export_png, output_file, save
+from bokeh.models import BasicTicker, ColorBar, FixedTicker, LinearColorMapper
+from bokeh.plotting import figure
+from scipy import signal
+
+
+# Data - Synthesize a melody-like audio signal with multiple frequency components
+np.random.seed(42)
+sample_rate = 22050
+duration = 4.0
+n_samples = int(sample_rate * duration)
+t = np.linspace(0, duration, n_samples, endpoint=False)
+
+# Create a rich audio signal: melody with harmonics and transients
+audio_signal = np.zeros(n_samples)
+
+# Melody notes (fundamental frequencies in Hz with harmonics)
+notes = [
+    (0.0, 1.0, 261.63),  # C4
+    (0.5, 1.5, 329.63),  # E4
+    (1.0, 2.0, 392.00),  # G4
+    (1.5, 2.5, 523.25),  # C5
+    (2.0, 3.0, 440.00),  # A4
+    (2.5, 3.5, 349.23),  # F4
+    (3.0, 4.0, 293.66),  # D4
+]
+
+for start, end, freq in notes:
+    mask = (t >= start) & (t < end)
+    envelope = np.zeros(n_samples)
+    note_len = np.sum(mask)
+    # ADSR-like envelope
+    attack = int(0.05 * sample_rate)
+    release = int(0.1 * sample_rate)
+    if note_len > attack + release:
+        env = np.ones(note_len)
+        env[:attack] = np.linspace(0, 1, attack)
+        env[-release:] = np.linspace(1, 0, release)
+        envelope[mask] = env
+    # Fundamental + harmonics
+    audio_signal += envelope * (
+        0.6 * np.sin(2 * np.pi * freq * t)
+        + 0.25 * np.sin(2 * np.pi * 2 * freq * t)
+        + 0.1 * np.sin(2 * np.pi * 3 * freq * t)
+        + 0.05 * np.sin(2 * np.pi * 4 * freq * t)
+    )
+
+# Add subtle background noise
+audio_signal += 0.02 * np.random.randn(n_samples)
+
+# Normalize
+audio_signal = audio_signal / np.max(np.abs(audio_signal))
+
+# Compute STFT
+n_fft = 2048
+hop_length = 512
+frequencies, times, Zxx = signal.stft(audio_signal, fs=sample_rate, nperseg=n_fft, noverlap=n_fft - hop_length)
+power_spectrum = np.abs(Zxx) ** 2
+
+
+# Mel filterbank construction
+n_mels = 128
+f_min = 0.0
+f_max = sample_rate / 2.0
+
+# Mel points evenly spaced on mel scale (Hz-to-mel: 2595 * log10(1 + f/700))
+mel_min = 2595.0 * np.log10(1.0 + f_min / 700.0)
+mel_max = 2595.0 * np.log10(1.0 + f_max / 700.0)
+mel_points = np.linspace(mel_min, mel_max, n_mels + 2)
+hz_points = 700.0 * (10.0 ** (mel_points / 2595.0) - 1.0)
+
+# Convert Hz points to FFT bin indices
+bin_points = np.floor((n_fft + 1) * hz_points / sample_rate).astype(int)
+
+# Build triangular filterbank
+n_freqs = len(frequencies)
+filterbank = np.zeros((n_mels, n_freqs))
+for m in range(n_mels):
+    f_left = bin_points[m]
+    f_center = bin_points[m + 1]
+    f_right = bin_points[m + 2]
+    for k in range(f_left, f_center):
+        if f_center != f_left:
+            filterbank[m, k] = (k - f_left) / (f_center - f_left)
+    for k in range(f_center, f_right):
+        if f_right != f_center:
+            filterbank[m, k] = (f_right - k) / (f_right - f_center)
+
+# Apply mel filterbank to power spectrum
+mel_spectrogram = filterbank @ power_spectrum
+
+# Convert to decibel scale
+mel_spectrogram_db = 10.0 * np.log10(mel_spectrogram + 1e-10)
+
+# Mel frequency axis - center frequencies for each mel band (mel-to-Hz conversion)
+mel_center_points = np.linspace(mel_min, mel_max, n_mels + 2)[1:-1]
+mel_center_freqs = 700.0 * (10.0 ** (mel_center_points / 2595.0) - 1.0)
+
+# Magma palette for mel spectrogram
+magma = [
+    "#000004",
+    "#010005",
+    "#010106",
+    "#010108",
+    "#020109",
+    "#02020b",
+    "#02020d",
+    "#03030f",
+    "#030312",
+    "#040414",
+    "#050416",
+    "#060518",
+    "#07051a",
+    "#08061c",
+    "#09071e",
+    "#0a0720",
+    "#0b0822",
+    "#0c0926",
+    "#0d0a28",
+    "#0e0b2a",
+    "#0f0b2c",
+    "#100c2f",
+    "#110d31",
+    "#120d33",
+    "#130e36",
+    "#140e38",
+    "#160f3b",
+    "#170f3d",
+    "#181040",
+    "#1a1042",
+    "#1b1044",
+    "#1c1147",
+    "#1e1149",
+    "#1f114b",
+    "#20114e",
+    "#221150",
+    "#231152",
+    "#251155",
+    "#261157",
+    "#281159",
+    "#29115b",
+    "#2b105d",
+    "#2d1060",
+    "#2e1062",
+    "#301064",
+    "#311066",
+    "#331068",
+    "#34106a",
+    "#36106b",
+    "#38106d",
+    "#39106f",
+    "#3b1070",
+    "#3d1072",
+    "#3e0f73",
+    "#400f75",
+    "#420f76",
+    "#430f77",
+    "#450e78",
+    "#470e79",
+    "#480e7a",
+    "#4a0e7b",
+    "#4c0e7c",
+    "#4d0d7c",
+    "#4f0d7d",
+    "#510d7d",
+    "#520d7e",
+    "#540d7e",
+    "#560c7e",
+    "#570c7f",
+    "#590c7f",
+    "#5b0c7f",
+    "#5c0b7f",
+    "#5e0b7f",
+    "#600b7f",
+    "#610a7f",
+    "#630a7f",
+    "#650a7f",
+    "#66097f",
+    "#68097e",
+    "#6a097e",
+    "#6b097e",
+    "#6d087d",
+    "#6f087d",
+    "#70087d",
+    "#72077c",
+    "#74077c",
+    "#75077b",
+    "#77067b",
+    "#79067a",
+    "#7a067a",
+    "#7c0679",
+    "#7e0578",
+    "#7f0578",
+    "#810577",
+    "#830476",
+    "#840476",
+    "#860475",
+    "#880474",
+    "#890374",
+    "#8b0373",
+    "#8d0372",
+    "#8e0271",
+    "#900270",
+    "#920270",
+    "#93026f",
+    "#95026e",
+    "#97016d",
+    "#98016c",
+    "#9a016b",
+    "#9c016b",
+    "#9d016a",
+    "#9f0169",
+    "#a10168",
+    "#a20167",
+    "#a40166",
+    "#a60165",
+    "#a70164",
+    "#a90163",
+    "#ab0162",
+    "#ac0161",
+    "#ae0160",
+    "#b00160",
+    "#b1015f",
+    "#b3015e",
+    "#b4015d",
+    "#b6015c",
+    "#b8015b",
+    "#b9015a",
+    "#bb0159",
+    "#bc0158",
+    "#be0157",
+    "#c00256",
+    "#c10255",
+    "#c30354",
+    "#c40453",
+    "#c60552",
+    "#c70651",
+    "#c90750",
+    "#ca084f",
+    "#cc094e",
+    "#cd0a4d",
+    "#cf0b4d",
+    "#d00d4c",
+    "#d10e4b",
+    "#d3104a",
+    "#d41149",
+    "#d51349",
+    "#d71448",
+    "#d81647",
+    "#d91847",
+    "#da1946",
+    "#dc1b46",
+    "#dd1d45",
+    "#de1f45",
+    "#df2044",
+    "#e02244",
+    "#e12444",
+    "#e22643",
+    "#e32843",
+    "#e42a43",
+    "#e52c43",
+    "#e62e43",
+    "#e73043",
+    "#e83243",
+    "#e93443",
+    "#ea3643",
+    "#eb3843",
+    "#eb3a43",
+    "#ec3c43",
+    "#ed3e44",
+    "#ee4044",
+    "#ef4344",
+    "#ef4545",
+    "#f04745",
+    "#f14946",
+    "#f14b46",
+    "#f24d47",
+    "#f34f48",
+    "#f35148",
+    "#f45349",
+    "#f5554a",
+    "#f5574b",
+    "#f6594c",
+    "#f65b4d",
+    "#f75d4e",
+    "#f75f4f",
+    "#f86250",
+    "#f86451",
+    "#f96653",
+    "#f96854",
+    "#f96a55",
+    "#fa6c57",
+    "#fa6e58",
+    "#fa705a",
+    "#fb725b",
+    "#fb745d",
+    "#fb765e",
+    "#fb7860",
+    "#fc7a62",
+    "#fc7c63",
+    "#fc7e65",
+    "#fc8067",
+    "#fc8269",
+    "#fc846b",
+    "#fd866d",
+    "#fd886f",
+    "#fd8a71",
+    "#fd8c73",
+    "#fd8e75",
+    "#fd9078",
+    "#fd927a",
+    "#fd947c",
+    "#fd967e",
+    "#fd9880",
+    "#fe9a83",
+    "#fe9c85",
+    "#fe9e87",
+    "#fea08a",
+    "#fea28c",
+    "#fea48e",
+    "#fea690",
+    "#fea893",
+    "#feaa95",
+    "#feac98",
+    "#feae9a",
+    "#feb09c",
+    "#feb29f",
+    "#feb4a1",
+    "#feb6a4",
+    "#feb8a6",
+    "#febaa8",
+    "#febcab",
+    "#fdbead",
+    "#fdc0b0",
+    "#fdc2b2",
+    "#fdc4b5",
+    "#fdc6b7",
+    "#fdc8ba",
+    "#fdcabc",
+    "#fdccbf",
+    "#fdcec1",
+    "#fdd0c4",
+    "#fdd2c6",
+    "#fdd4c9",
+    "#fdd5cb",
+    "#fdd7ce",
+    "#fdd9d1",
+    "#fddbd3",
+    "#fdddd6",
+    "#fddfd8",
+    "#fde1db",
+    "#fde3dd",
+    "#fde5e0",
+    "#fee7e3",
+    "#fee9e5",
+    "#feebe8",
+    "#fcedea",
+    "#fcefed",
+]
+
+# Plot
+p = figure(
+    width=4800,
+    height=2700,
+    title="spectrogram-mel · bokeh · pyplots.ai",
+    x_axis_label="Time (seconds)",
+    y_axis_label="Frequency (Hz)",
+    x_range=(times.min(), times.max()),
+    y_range=(mel_center_freqs[0], mel_center_freqs[-1]),
+    y_axis_type="log",
+    tools="",
+    toolbar_location=None,
+)
+
+# Color mapper
+vmin = np.percentile(mel_spectrogram_db, 5)
+vmax = mel_spectrogram_db.max()
+color_mapper = LinearColorMapper(palette=magma, low=vmin, high=vmax)
+
+# Render mel spectrogram as image
+p.image(
+    image=[mel_spectrogram_db],
+    x=times.min(),
+    y=mel_center_freqs[0],
+    dw=times.max() - times.min(),
+    dh=mel_center_freqs[-1] - mel_center_freqs[0],
+    color_mapper=color_mapper,
+    level="image",
+)
+
+# Colorbar labeled in dB
+color_bar = ColorBar(
+    color_mapper=color_mapper,
+    ticker=BasicTicker(desired_num_ticks=8),
+    label_standoff=20,
+    border_line_color=None,
+    location=(0, 0),
+    title="Power (dB)",
+    title_text_font_size="32pt",
+    major_label_text_font_size="24pt",
+    width=70,
+    padding=40,
+    title_standoff=20,
+)
+p.add_layout(color_bar, "right")
+
+# Y-axis tick labels at key mel band frequencies
+mel_tick_freqs = [50, 100, 200, 500, 1000, 2000, 4000, 8000]
+mel_tick_freqs = [f for f in mel_tick_freqs if mel_center_freqs[0] <= f <= mel_center_freqs[-1]]
+p.yaxis.ticker = FixedTicker(ticks=mel_tick_freqs)
+
+# Style for 4800x2700 canvas
+p.title.text_font_size = "40pt"
+p.xaxis.axis_label_text_font_size = "32pt"
+p.yaxis.axis_label_text_font_size = "32pt"
+p.xaxis.major_label_text_font_size = "24pt"
+p.yaxis.major_label_text_font_size = "24pt"
+
+# Axis styling
+p.xaxis.axis_line_width = 3
+p.yaxis.axis_line_width = 3
+p.xaxis.major_tick_line_width = 3
+p.yaxis.major_tick_line_width = 3
+
+# Grid - subtle dashed lines
+p.xgrid.grid_line_alpha = 0.2
+p.ygrid.grid_line_alpha = 0.2
+p.xgrid.grid_line_dash = "dashed"
+p.ygrid.grid_line_dash = "dashed"
+
+# Background
+p.background_fill_color = None
+p.border_fill_color = "white"
+p.outline_line_color = "#333333"
+p.outline_line_width = 2
+p.min_border_right = 100
+
+# Save
+export_png(p, filename="plot.png")
+
+output_file("plot.html", title="spectrogram-mel · bokeh · pyplots.ai")
+save(p)

From 5b27b9cd64a431c4dba28f70cd11220a0e102529 Mon Sep 17 00:00:00 2001
From: "github-actions[bot]" <github-actions[bot]@users.noreply.github.com>
Date: Wed, 11 Mar 2026 19:42:56 +0000
Subject: [PATCH 2/7] chore(bokeh): add metadata for spectrogram-mel

---
 plots/spectrogram-mel/metadata/bokeh.yaml | 19 +++++++++++++++++++
 1 file changed, 19 insertions(+)
 create mode 100644 plots/spectrogram-mel/metadata/bokeh.yaml

diff --git a/plots/spectrogram-mel/metadata/bokeh.yaml b/plots/spectrogram-mel/metadata/bokeh.yaml
new file mode 100644
index 0000000000..95f92298de
--- /dev/null
+++ b/plots/spectrogram-mel/metadata/bokeh.yaml
@@ -0,0 +1,19 @@
+# Per-library metadata for bokeh implementation of spectrogram-mel
+# Auto-generated by impl-generate.yml
+
+library: bokeh
+specification_id: spectrogram-mel
+created: '2026-03-11T19:42:55Z'
+updated: '2026-03-11T19:42:55Z'
+generated_by: claude-opus-4-5-20251101
+workflow_run: 22970857215
+issue: 4672
+python_version: 3.14.3
+library_version: 3.9.0
+preview_url: https://storage.googleapis.com/pyplots-images/plots/spectrogram-mel/bokeh/plot.png
+preview_thumb: https://storage.googleapis.com/pyplots-images/plots/spectrogram-mel/bokeh/plot_thumb.png
+preview_html: https://storage.googleapis.com/pyplots-images/plots/spectrogram-mel/bokeh/plot.html
+quality_score: null
+review:
+  strengths: []
+  weaknesses: []

From 709d4a26c033372684c724fa04bbfefc52783b53 Mon Sep 17 00:00:00 2001
From: "github-actions[bot]" <github-actions[bot]@users.noreply.github.com>
Date: Wed, 11 Mar 2026 19:47:30 +0000
Subject: [PATCH 3/7] chore(bokeh): update quality score 80 and review feedback
 for spectrogram-mel

---
 .../spectrogram-mel/implementations/bokeh.py  |   6 +-
 plots/spectrogram-mel/metadata/bokeh.yaml     | 229 +++++++++++++++++-
 2 files changed, 225 insertions(+), 10 deletions(-)

diff --git a/plots/spectrogram-mel/implementations/bokeh.py b/plots/spectrogram-mel/implementations/bokeh.py
index 4dc9432fdf..5a7f522a80 100644
--- a/plots/spectrogram-mel/implementations/bokeh.py
+++ b/plots/spectrogram-mel/implementations/bokeh.py
@@ -1,7 +1,7 @@
-"""pyplots.ai
+""" pyplots.ai
 spectrogram-mel: Mel-Spectrogram for Audio Analysis
-Library: bokeh | Python 3.13
-Quality: pending | Created: 2026-03-11
+Library: bokeh 3.9.0 | Python 3.14.3
+Quality: 80/100 | Created: 2026-03-11
 """
 
 import numpy as np
diff --git a/plots/spectrogram-mel/metadata/bokeh.yaml b/plots/spectrogram-mel/metadata/bokeh.yaml
index 95f92298de..b59b9b5ea0 100644
--- a/plots/spectrogram-mel/metadata/bokeh.yaml
+++ b/plots/spectrogram-mel/metadata/bokeh.yaml
@@ -1,10 +1,7 @@
-# Per-library metadata for bokeh implementation of spectrogram-mel
-# Auto-generated by impl-generate.yml
-
 library: bokeh
 specification_id: spectrogram-mel
 created: '2026-03-11T19:42:55Z'
-updated: '2026-03-11T19:42:55Z'
+updated: '2026-03-11T19:47:30Z'
 generated_by: claude-opus-4-5-20251101
 workflow_run: 22970857215
 issue: 4672
@@ -13,7 +10,225 @@ library_version: 3.9.0
 preview_url: https://storage.googleapis.com/pyplots-images/plots/spectrogram-mel/bokeh/plot.png
 preview_thumb: https://storage.googleapis.com/pyplots-images/plots/spectrogram-mel/bokeh/plot_thumb.png
 preview_html: https://storage.googleapis.com/pyplots-images/plots/spectrogram-mel/bokeh/plot.html
-quality_score: null
+quality_score: 80
 review:
-  strengths: []
-  weaknesses: []
+  strengths:
+  - Excellent audio synthesis with realistic musical notes, harmonics, and ADSR envelopes
+  - Correct mel filterbank construction from scratch without librosa dependency
+  - All font sizes explicitly set and appropriate for 4800x2700 canvas
+  - Good colormap choice (magma) for spectrogram visualization
+  - Proper dB conversion with floor value to avoid log(0)
+  weaknesses:
+  - Hardcoded 256-hex-value magma palette instead of using Bokeh built-in Magma256
+    from bokeh.palettes
+  - p.image() linear mapping combined with y_axis_type=log creates visual distortion
+    of mel bands
+  - No use of Bokeh interactive features like HoverTool for time/frequency/power readout
+  - Design could be more polished with better title positioning and colorbar integration
+  image_description: The plot displays a mel-spectrogram rendered with the magma colormap
+    (dark purple background transitioning through pink to near-white for high-intensity
+    regions). The x-axis shows "Time (seconds)" from 0 to 4, and the y-axis shows
+    "Frequency (Hz)" on a logarithmic scale with ticks at 50, 100, 200, 500, 1000,
+    2000, 4000, and 8000 Hz. A colorbar on the right is labeled "Power (dB)" ranging
+    from approximately -70 to -20 dB. Bright horizontal bands are clearly visible
+    at various frequency levels corresponding to the synthesized melody notes (C4,
+    E4, G4, C5, A4, F4, D4) and their harmonics, with fundamental frequencies showing
+    the brightest intensity. The note onsets and offsets are visible with ADSR envelope
+    shaping. Background noise appears as a low-level dark purple texture. The lower
+    mel bins appear heavily stretched due to the combination of linear image mapping
+    with a log y-axis, creating visually uneven band heights. The title reads "spectrogram-mel
+    · bokeh · pyplots.ai".
+  criteria_checklist:
+    visual_quality:
+      score: 27
+      max: 30
+      items:
+      - id: VQ-01
+        name: Text Legibility
+        score: 8
+        max: 8
+        passed: true
+        comment: 'All font sizes explicitly set: title=40pt, axis labels=32pt, tick
+          labels=24pt, colorbar title=32pt, colorbar labels=24pt'
+      - id: VQ-02
+        name: No Overlap
+        score: 6
+        max: 6
+        passed: true
+        comment: No overlapping text elements anywhere
+      - id: VQ-03
+        name: Element Visibility
+        score: 4
+        max: 6
+        passed: true
+        comment: Spectrogram visible but mel bands appear blocky due to log axis stretching
+          lower bins disproportionately
+      - id: VQ-04
+        name: Color Accessibility
+        score: 4
+        max: 4
+        passed: true
+        comment: Magma colormap is perceptually uniform and colorblind-safe
+      - id: VQ-05
+        name: Layout & Canvas
+        score: 3
+        max: 4
+        passed: true
+        comment: Good layout with colorbar on right, minor bottom gap and right margin
+          could be tighter
+      - id: VQ-06
+        name: Axis Labels & Title
+        score: 2
+        max: 2
+        passed: true
+        comment: Time (seconds) and Frequency (Hz) both descriptive with units
+    design_excellence:
+      score: 11
+      max: 20
+      items:
+      - id: DE-01
+        name: Aesthetic Sophistication
+        score: 5
+        max: 8
+        passed: true
+        comment: Magma colormap is strong choice, log y-axis with meaningful tick
+          positions, toolbar removed. Above default but not publication-quality
+      - id: DE-02
+        name: Visual Refinement
+        score: 3
+        max: 6
+        passed: true
+        comment: Subtle dashed grid with alpha=0.2, removed toolbar, styled outline,
+          background fill None
+      - id: DE-03
+        name: Data Storytelling
+        score: 3
+        max: 6
+        passed: true
+        comment: Synthesized melody creates visual narrative with note progressions
+          and harmonic structure visible
+    spec_compliance:
+      score: 14
+      max: 15
+      items:
+      - id: SC-01
+        name: Plot Type
+        score: 5
+        max: 5
+        passed: true
+        comment: Correct mel-spectrogram visualization
+      - id: SC-02
+        name: Required Features
+        score: 4
+        max: 4
+        passed: true
+        comment: 'All required features present: dB scale, sequential colormap, time/frequency
+          axes, colorbar, correct parameters, synthesized audio'
+      - id: SC-03
+        name: Data Mapping
+        score: 2
+        max: 3
+        passed: true
+        comment: X=time Y=frequency correct but p.image() linear mapping with log
+          y-axis causes visual distortion of mel bands
+      - id: SC-04
+        name: Title & Legend
+        score: 3
+        max: 3
+        passed: true
+        comment: Title format correct, no legend needed for this plot type
+    data_quality:
+      score: 14
+      max: 15
+      items:
+      - id: DQ-01
+        name: Feature Coverage
+        score: 5
+        max: 6
+        passed: true
+        comment: Rich audio with 7 notes, harmonics, ADSR envelopes, background noise.
+          Could show wider frequency variety
+      - id: DQ-02
+        name: Realistic Context
+        score: 5
+        max: 5
+        passed: true
+        comment: Real musical notes (C4-C5) with correct frequencies, realistic sample
+          rate and duration
+      - id: DQ-03
+        name: Appropriate Scale
+        score: 4
+        max: 4
+        passed: true
+        comment: 'All values sensible: 22050 Hz sample rate, musical frequencies in
+          hearing range, 128 mel bands'
+    code_quality:
+      score: 9
+      max: 10
+      items:
+      - id: CQ-01
+        name: KISS Structure
+        score: 3
+        max: 3
+        passed: true
+        comment: Clean imports-data-plot-save structure, no functions or classes
+      - id: CQ-02
+        name: Reproducibility
+        score: 2
+        max: 2
+        passed: true
+        comment: np.random.seed(42) set at beginning
+      - id: CQ-03
+        name: Clean Imports
+        score: 2
+        max: 2
+        passed: true
+        comment: 'All imports used: numpy, bokeh models, scipy.signal'
+      - id: CQ-04
+        name: Code Elegance
+        score: 1
+        max: 2
+        passed: false
+        comment: 256-line hardcoded magma palette is unnecessarily verbose when Bokeh
+          provides Magma256
+      - id: CQ-05
+        name: Output & API
+        score: 1
+        max: 1
+        passed: true
+        comment: Saves as plot.png and plot.html, current API usage
+    library_mastery:
+      score: 5
+      max: 10
+      items:
+      - id: LM-01
+        name: Idiomatic Usage
+        score: 3
+        max: 5
+        passed: true
+        comment: Correct figure/image/ColorBar usage but manually defines palette
+          instead of using bokeh.palettes
+      - id: LM-02
+        name: Distinctive Features
+        score: 2
+        max: 5
+        passed: false
+        comment: HTML export is Bokeh-specific but missing HoverTool and other interactive
+          features that make Bokeh distinctive
+  verdict: REJECTED
+impl_tags:
+  dependencies:
+  - scipy
+  techniques:
+  - colorbar
+  - manual-ticks
+  - html-export
+  patterns:
+  - data-generation
+  - matrix-construction
+  - iteration-over-groups
+  dataprep:
+  - binning
+  styling:
+  - custom-colormap
+  - grid-styling

From 6be6976d3bb73f1684841b232015fb3469f07396 Mon Sep 17 00:00:00 2001
From: "github-actions[bot]" <github-actions[bot]@users.noreply.github.com>
Date: Wed, 11 Mar 2026 19:52:52 +0000
Subject: [PATCH 4/7] fix(bokeh): address review feedback for spectrogram-mel

Attempt 1/3 - fixes based on AI review
---
 .../spectrogram-mel/implementations/bokeh.py  | 385 +++++-------------
 1 file changed, 93 insertions(+), 292 deletions(-)

diff --git a/plots/spectrogram-mel/implementations/bokeh.py b/plots/spectrogram-mel/implementations/bokeh.py
index 5a7f522a80..0f547d4a66 100644
--- a/plots/spectrogram-mel/implementations/bokeh.py
+++ b/plots/spectrogram-mel/implementations/bokeh.py
@@ -1,4 +1,4 @@
-""" pyplots.ai
+"""pyplots.ai
 spectrogram-mel: Mel-Spectrogram for Audio Analysis
 Library: bokeh 3.9.0 | Python 3.14.3
 Quality: 80/100 | Created: 2026-03-11
@@ -6,7 +6,8 @@
 
 import numpy as np
 from bokeh.io import export_png, output_file, save
-from bokeh.models import BasicTicker, ColorBar, FixedTicker, LinearColorMapper
+from bokeh.models import BasicTicker, ColorBar, ColumnDataSource, FixedTicker, HoverTool, LinearColorMapper
+from bokeh.palettes import Magma256
 from bokeh.plotting import figure
 from scipy import signal
 
@@ -99,302 +100,92 @@
 # Convert to decibel scale
 mel_spectrogram_db = 10.0 * np.log10(mel_spectrogram + 1e-10)
 
-# Mel frequency axis - center frequencies for each mel band (mel-to-Hz conversion)
-mel_center_points = np.linspace(mel_min, mel_max, n_mels + 2)[1:-1]
-mel_center_freqs = 700.0 * (10.0 ** (mel_center_points / 2595.0) - 1.0)
-
-# Magma palette for mel spectrogram
-magma = [
-    "#000004",
-    "#010005",
-    "#010106",
-    "#010108",
-    "#020109",
-    "#02020b",
-    "#02020d",
-    "#03030f",
-    "#030312",
-    "#040414",
-    "#050416",
-    "#060518",
-    "#07051a",
-    "#08061c",
-    "#09071e",
-    "#0a0720",
-    "#0b0822",
-    "#0c0926",
-    "#0d0a28",
-    "#0e0b2a",
-    "#0f0b2c",
-    "#100c2f",
-    "#110d31",
-    "#120d33",
-    "#130e36",
-    "#140e38",
-    "#160f3b",
-    "#170f3d",
-    "#181040",
-    "#1a1042",
-    "#1b1044",
-    "#1c1147",
-    "#1e1149",
-    "#1f114b",
-    "#20114e",
-    "#221150",
-    "#231152",
-    "#251155",
-    "#261157",
-    "#281159",
-    "#29115b",
-    "#2b105d",
-    "#2d1060",
-    "#2e1062",
-    "#301064",
-    "#311066",
-    "#331068",
-    "#34106a",
-    "#36106b",
-    "#38106d",
-    "#39106f",
-    "#3b1070",
-    "#3d1072",
-    "#3e0f73",
-    "#400f75",
-    "#420f76",
-    "#430f77",
-    "#450e78",
-    "#470e79",
-    "#480e7a",
-    "#4a0e7b",
-    "#4c0e7c",
-    "#4d0d7c",
-    "#4f0d7d",
-    "#510d7d",
-    "#520d7e",
-    "#540d7e",
-    "#560c7e",
-    "#570c7f",
-    "#590c7f",
-    "#5b0c7f",
-    "#5c0b7f",
-    "#5e0b7f",
-    "#600b7f",
-    "#610a7f",
-    "#630a7f",
-    "#650a7f",
-    "#66097f",
-    "#68097e",
-    "#6a097e",
-    "#6b097e",
-    "#6d087d",
-    "#6f087d",
-    "#70087d",
-    "#72077c",
-    "#74077c",
-    "#75077b",
-    "#77067b",
-    "#79067a",
-    "#7a067a",
-    "#7c0679",
-    "#7e0578",
-    "#7f0578",
-    "#810577",
-    "#830476",
-    "#840476",
-    "#860475",
-    "#880474",
-    "#890374",
-    "#8b0373",
-    "#8d0372",
-    "#8e0271",
-    "#900270",
-    "#920270",
-    "#93026f",
-    "#95026e",
-    "#97016d",
-    "#98016c",
-    "#9a016b",
-    "#9c016b",
-    "#9d016a",
-    "#9f0169",
-    "#a10168",
-    "#a20167",
-    "#a40166",
-    "#a60165",
-    "#a70164",
-    "#a90163",
-    "#ab0162",
-    "#ac0161",
-    "#ae0160",
-    "#b00160",
-    "#b1015f",
-    "#b3015e",
-    "#b4015d",
-    "#b6015c",
-    "#b8015b",
-    "#b9015a",
-    "#bb0159",
-    "#bc0158",
-    "#be0157",
-    "#c00256",
-    "#c10255",
-    "#c30354",
-    "#c40453",
-    "#c60552",
-    "#c70651",
-    "#c90750",
-    "#ca084f",
-    "#cc094e",
-    "#cd0a4d",
-    "#cf0b4d",
-    "#d00d4c",
-    "#d10e4b",
-    "#d3104a",
-    "#d41149",
-    "#d51349",
-    "#d71448",
-    "#d81647",
-    "#d91847",
-    "#da1946",
-    "#dc1b46",
-    "#dd1d45",
-    "#de1f45",
-    "#df2044",
-    "#e02244",
-    "#e12444",
-    "#e22643",
-    "#e32843",
-    "#e42a43",
-    "#e52c43",
-    "#e62e43",
-    "#e73043",
-    "#e83243",
-    "#e93443",
-    "#ea3643",
-    "#eb3843",
-    "#eb3a43",
-    "#ec3c43",
-    "#ed3e44",
-    "#ee4044",
-    "#ef4344",
-    "#ef4545",
-    "#f04745",
-    "#f14946",
-    "#f14b46",
-    "#f24d47",
-    "#f34f48",
-    "#f35148",
-    "#f45349",
-    "#f5554a",
-    "#f5574b",
-    "#f6594c",
-    "#f65b4d",
-    "#f75d4e",
-    "#f75f4f",
-    "#f86250",
-    "#f86451",
-    "#f96653",
-    "#f96854",
-    "#f96a55",
-    "#fa6c57",
-    "#fa6e58",
-    "#fa705a",
-    "#fb725b",
-    "#fb745d",
-    "#fb765e",
-    "#fb7860",
-    "#fc7a62",
-    "#fc7c63",
-    "#fc7e65",
-    "#fc8067",
-    "#fc8269",
-    "#fc846b",
-    "#fd866d",
-    "#fd886f",
-    "#fd8a71",
-    "#fd8c73",
-    "#fd8e75",
-    "#fd9078",
-    "#fd927a",
-    "#fd947c",
-    "#fd967e",
-    "#fd9880",
-    "#fe9a83",
-    "#fe9c85",
-    "#fe9e87",
-    "#fea08a",
-    "#fea28c",
-    "#fea48e",
-    "#fea690",
-    "#fea893",
-    "#feaa95",
-    "#feac98",
-    "#feae9a",
-    "#feb09c",
-    "#feb29f",
-    "#feb4a1",
-    "#feb6a4",
-    "#feb8a6",
-    "#febaa8",
-    "#febcab",
-    "#fdbead",
-    "#fdc0b0",
-    "#fdc2b2",
-    "#fdc4b5",
-    "#fdc6b7",
-    "#fdc8ba",
-    "#fdcabc",
-    "#fdccbf",
-    "#fdcec1",
-    "#fdd0c4",
-    "#fdd2c6",
-    "#fdd4c9",
-    "#fdd5cb",
-    "#fdd7ce",
-    "#fdd9d1",
-    "#fddbd3",
-    "#fdddd6",
-    "#fddfd8",
-    "#fde1db",
-    "#fde3dd",
-    "#fde5e0",
-    "#fee7e3",
-    "#fee9e5",
-    "#feebe8",
-    "#fcedea",
-    "#fcefed",
-]
+# Mel band edge frequencies (for positioning rectangles correctly on log scale)
+mel_edge_freqs = hz_points  # n_mels + 2 edges
+# Clamp to positive values for log scale
+mel_edge_freqs = np.maximum(mel_edge_freqs, 1.0)
+
+# Build quad data for each mel band x time frame
+n_times = len(times)
+time_step = times[1] - times[0] if n_times > 1 else hop_length / sample_rate
+
+quad_left = []
+quad_right = []
+quad_bottom = []
+quad_top = []
+quad_power = []
+quad_time_label = []
+quad_freq_label = []
+
+for ti in range(n_times):
+    for mi in range(n_mels):
+        quad_left.append(times[ti] - time_step / 2)
+        quad_right.append(times[ti] + time_step / 2)
+        quad_bottom.append(mel_edge_freqs[mi + 1])
+        quad_top.append(mel_edge_freqs[mi + 2])
+        quad_power.append(mel_spectrogram_db[mi, ti])
+        quad_time_label.append(round(times[ti], 3))
+        quad_freq_label.append(round((mel_edge_freqs[mi + 1] + mel_edge_freqs[mi + 2]) / 2, 1))
+
+quad_power_arr = np.array(quad_power)
+vmin = float(np.percentile(mel_spectrogram_db, 5))
+vmax = float(mel_spectrogram_db.max())
+
+# Map power to palette indices for fill_color
+normalized = (quad_power_arr - vmin) / (vmax - vmin)
+normalized = np.clip(normalized, 0, 1)
+color_indices = (normalized * 255).astype(int)
+colors = [Magma256[i] for i in color_indices]
+
+source = ColumnDataSource(
+    data={
+        "left": quad_left,
+        "right": quad_right,
+        "bottom": quad_bottom,
+        "top": quad_top,
+        "power": quad_power,
+        "color": colors,
+        "time_s": quad_time_label,
+        "freq_hz": quad_freq_label,
+    }
+)
 
 # Plot
 p = figure(
     width=4800,
     height=2700,
-    title="spectrogram-mel · bokeh · pyplots.ai",
+    title="spectrogram-mel \u00b7 bokeh \u00b7 pyplots.ai",
     x_axis_label="Time (seconds)",
     y_axis_label="Frequency (Hz)",
-    x_range=(times.min(), times.max()),
-    y_range=(mel_center_freqs[0], mel_center_freqs[-1]),
+    x_range=(times.min() - time_step / 2, times.max() + time_step / 2),
+    y_range=(mel_edge_freqs[1], mel_edge_freqs[-1]),
     y_axis_type="log",
     tools="",
     toolbar_location=None,
 )
 
-# Color mapper
-vmin = np.percentile(mel_spectrogram_db, 5)
-vmax = mel_spectrogram_db.max()
-color_mapper = LinearColorMapper(palette=magma, low=vmin, high=vmax)
-
-# Render mel spectrogram as image
-p.image(
-    image=[mel_spectrogram_db],
-    x=times.min(),
-    y=mel_center_freqs[0],
-    dw=times.max() - times.min(),
-    dh=mel_center_freqs[-1] - mel_center_freqs[0],
-    color_mapper=color_mapper,
+# Render mel bands as quads for correct log-scale positioning
+p.quad(
+    left="left",
+    right="right",
+    bottom="bottom",
+    top="top",
+    fill_color="color",
+    line_color=None,
+    source=source,
     level="image",
 )
 
+# HoverTool for interactive readout
+hover = HoverTool(
+    tooltips=[("Time", "@time_s{0.000} s"), ("Frequency", "@freq_hz{0.0} Hz"), ("Power", "@power{0.0} dB")],
+    point_policy="follow_mouse",
+)
+p.add_tools(hover)
+
+# Color mapper for the colorbar
+color_mapper = LinearColorMapper(palette=Magma256, low=vmin, high=vmax)
+
 # Colorbar labeled in dB
 color_bar = ColorBar(
     color_mapper=color_mapper,
@@ -413,37 +204,47 @@
 
 # Y-axis tick labels at key mel band frequencies
 mel_tick_freqs = [50, 100, 200, 500, 1000, 2000, 4000, 8000]
-mel_tick_freqs = [f for f in mel_tick_freqs if mel_center_freqs[0] <= f <= mel_center_freqs[-1]]
+mel_tick_freqs = [f for f in mel_tick_freqs if mel_edge_freqs[1] <= f <= mel_edge_freqs[-1]]
 p.yaxis.ticker = FixedTicker(ticks=mel_tick_freqs)
 
 # Style for 4800x2700 canvas
 p.title.text_font_size = "40pt"
+p.title.text_font_style = "bold"
+p.title.text_color = "#222222"
 p.xaxis.axis_label_text_font_size = "32pt"
 p.yaxis.axis_label_text_font_size = "32pt"
 p.xaxis.major_label_text_font_size = "24pt"
 p.yaxis.major_label_text_font_size = "24pt"
+p.xaxis.axis_label_text_font_style = "normal"
+p.yaxis.axis_label_text_font_style = "normal"
 
 # Axis styling
 p.xaxis.axis_line_width = 3
 p.yaxis.axis_line_width = 3
 p.xaxis.major_tick_line_width = 3
 p.yaxis.major_tick_line_width = 3
+p.xaxis.minor_tick_line_color = None
+p.yaxis.minor_tick_line_color = None
 
-# Grid - subtle dashed lines
-p.xgrid.grid_line_alpha = 0.2
-p.ygrid.grid_line_alpha = 0.2
-p.xgrid.grid_line_dash = "dashed"
-p.ygrid.grid_line_dash = "dashed"
+# Grid - subtle styling
+p.xgrid.grid_line_alpha = 0.15
+p.ygrid.grid_line_alpha = 0.15
+p.xgrid.grid_line_dash = [6, 4]
+p.ygrid.grid_line_dash = [6, 4]
+p.xgrid.grid_line_color = "#aaaaaa"
+p.ygrid.grid_line_color = "#aaaaaa"
 
 # Background
-p.background_fill_color = None
+p.background_fill_color = "#000004"
 p.border_fill_color = "white"
 p.outline_line_color = "#333333"
 p.outline_line_width = 2
-p.min_border_right = 100
+p.min_border_right = 140
+p.min_border_left = 120
+p.min_border_bottom = 100
 
 # Save
 export_png(p, filename="plot.png")
 
-output_file("plot.html", title="spectrogram-mel · bokeh · pyplots.ai")
+output_file("plot.html", title="spectrogram-mel \u00b7 bokeh \u00b7 pyplots.ai")
 save(p)

From 99fec2cdc5e4d9869dba901fd4323bb7d7b2c9e1 Mon Sep 17 00:00:00 2001
From: "github-actions[bot]" <github-actions[bot]@users.noreply.github.com>
Date: Wed, 11 Mar 2026 19:58:05 +0000
Subject: [PATCH 5/7] chore(bokeh): update quality score 85 and review feedback
 for spectrogram-mel

---
 .../spectrogram-mel/implementations/bokeh.py  |   4 +-
 plots/spectrogram-mel/metadata/bokeh.yaml     | 151 ++++++++++--------
 2 files changed, 85 insertions(+), 70 deletions(-)

diff --git a/plots/spectrogram-mel/implementations/bokeh.py b/plots/spectrogram-mel/implementations/bokeh.py
index 0f547d4a66..a66c5ed7e4 100644
--- a/plots/spectrogram-mel/implementations/bokeh.py
+++ b/plots/spectrogram-mel/implementations/bokeh.py
@@ -1,7 +1,7 @@
-"""pyplots.ai
+""" pyplots.ai
 spectrogram-mel: Mel-Spectrogram for Audio Analysis
 Library: bokeh 3.9.0 | Python 3.14.3
-Quality: 80/100 | Created: 2026-03-11
+Quality: 85/100 | Created: 2026-03-11
 """
 
 import numpy as np
diff --git a/plots/spectrogram-mel/metadata/bokeh.yaml b/plots/spectrogram-mel/metadata/bokeh.yaml
index b59b9b5ea0..49a0199836 100644
--- a/plots/spectrogram-mel/metadata/bokeh.yaml
+++ b/plots/spectrogram-mel/metadata/bokeh.yaml
@@ -1,7 +1,7 @@
 library: bokeh
 specification_id: spectrogram-mel
 created: '2026-03-11T19:42:55Z'
-updated: '2026-03-11T19:47:30Z'
+updated: '2026-03-11T19:58:05Z'
 generated_by: claude-opus-4-5-20251101
 workflow_run: 22970857215
 issue: 4672
@@ -10,37 +10,41 @@ library_version: 3.9.0
 preview_url: https://storage.googleapis.com/pyplots-images/plots/spectrogram-mel/bokeh/plot.png
 preview_thumb: https://storage.googleapis.com/pyplots-images/plots/spectrogram-mel/bokeh/plot_thumb.png
 preview_html: https://storage.googleapis.com/pyplots-images/plots/spectrogram-mel/bokeh/plot.html
-quality_score: 80
+quality_score: 85
 review:
   strengths:
-  - Excellent audio synthesis with realistic musical notes, harmonics, and ADSR envelopes
-  - Correct mel filterbank construction from scratch without librosa dependency
-  - All font sizes explicitly set and appropriate for 4800x2700 canvas
-  - Good colormap choice (magma) for spectrogram visualization
-  - Proper dB conversion with floor value to avoid log(0)
+  - Excellent mel filterbank construction from scratch using scipy.signal STFT, avoiding
+    librosa dependency
+  - Quad rendering correctly positions mel bands on log y-axis, fixing the visual
+    distortion from attempt 1
+  - HoverTool provides genuinely interactive readout of time, frequency, and power
+    values
+  - Dark background matching Magma colormap floor creates cohesive visual design
+  - Rich audio synthesis with harmonics and ADSR envelopes produces a visually engaging
+    spectrogram
   weaknesses:
-  - Hardcoded 256-hex-value magma palette instead of using Bokeh built-in Magma256
-    from bokeh.palettes
-  - p.image() linear mapping combined with y_axis_type=log creates visual distortion
-    of mel bands
-  - No use of Bokeh interactive features like HoverTool for time/frequency/power readout
-  - Design could be more polished with better title positioning and colorbar integration
-  image_description: The plot displays a mel-spectrogram rendered with the magma colormap
-    (dark purple background transitioning through pink to near-white for high-intensity
-    regions). The x-axis shows "Time (seconds)" from 0 to 4, and the y-axis shows
-    "Frequency (Hz)" on a logarithmic scale with ticks at 50, 100, 200, 500, 1000,
-    2000, 4000, and 8000 Hz. A colorbar on the right is labeled "Power (dB)" ranging
-    from approximately -70 to -20 dB. Bright horizontal bands are clearly visible
-    at various frequency levels corresponding to the synthesized melody notes (C4,
-    E4, G4, C5, A4, F4, D4) and their harmonics, with fundamental frequencies showing
-    the brightest intensity. The note onsets and offsets are visible with ADSR envelope
-    shaping. Background noise appears as a low-level dark purple texture. The lower
-    mel bins appear heavily stretched due to the combination of linear image mapping
-    with a log y-axis, creating visually uneven band heights. The title reads "spectrogram-mel
-    · bokeh · pyplots.ai".
+  - 'Design Excellence needs improvement: typography could be more refined, no visual
+    emphasis or annotation guiding viewer to key insight'
+  - Nested loop for building quad data arrays is verbose and could be vectorized with
+    np.repeat/np.tile
+  - Colorbar right margin slightly tight, could use more breathing room
+  image_description: The plot displays a mel-spectrogram rendered with the Magma colormap
+    on a dark background (#000004, matching the colormap's lowest value). The x-axis
+    shows "Time (seconds)" from 0 to 4, and the y-axis shows "Frequency (Hz)" on a
+    logarithmic scale with fixed ticks at 50, 100, 200, 500, 1000, 2000, 4000, and
+    8000 Hz. A colorbar on the right is labeled "Power (dB)" ranging from approximately
+    -70 to -20 dB. Bright horizontal bands (yellow-white through pink) are clearly
+    visible at various frequency levels corresponding to the synthesized melody notes
+    (C4, E4, G4, C5, A4, F4, D4) and their harmonics, with fundamentals showing the
+    brightest intensity and harmonics progressively dimmer. Note onsets and offsets
+    show clean ADSR envelope shaping. The mel bands are rendered as individual quads
+    correctly positioned on the log y-axis, eliminating the distortion seen in attempt
+    1. Background noise appears as low-level dark texture primarily in the lower frequencies.
+    The title reads "spectrogram-mel · bokeh · pyplots.ai" in bold at the top left.
+    Subtle dashed grid lines are visible at low opacity.
   criteria_checklist:
     visual_quality:
-      score: 27
+      score: 28
       max: 30
       items:
       - id: VQ-01
@@ -49,41 +53,45 @@ review:
         max: 8
         passed: true
         comment: 'All font sizes explicitly set: title=40pt, axis labels=32pt, tick
-          labels=24pt, colorbar title=32pt, colorbar labels=24pt'
+          labels=24pt, colorbar title=32pt, colorbar labels=24pt. All text clearly
+          readable.'
       - id: VQ-02
         name: No Overlap
         score: 6
         max: 6
         passed: true
-        comment: No overlapping text elements anywhere
+        comment: No overlapping text elements anywhere in the plot.
       - id: VQ-03
         name: Element Visibility
-        score: 4
+        score: 5
         max: 6
         passed: true
-        comment: Spectrogram visible but mel bands appear blocky due to log axis stretching
-          lower bins disproportionately
+        comment: Mel bands clearly visible with good contrast. Quad rendering correctly
+          positions bands on log scale. Lower frequency bins slightly coarse due to
+          narrow mel bandwidth.
       - id: VQ-04
         name: Color Accessibility
         score: 4
         max: 4
         passed: true
-        comment: Magma colormap is perceptually uniform and colorblind-safe
+        comment: Magma is perceptually uniform and colorblind-safe with excellent
+          contrast.
       - id: VQ-05
         name: Layout & Canvas
         score: 3
         max: 4
         passed: true
-        comment: Good layout with colorbar on right, minor bottom gap and right margin
-          could be tighter
+        comment: Good canvas utilization with colorbar on right. Colorbar title text
+          slightly tight against right edge.
       - id: VQ-06
         name: Axis Labels & Title
         score: 2
         max: 2
         passed: true
-        comment: Time (seconds) and Frequency (Hz) both descriptive with units
+        comment: Time (seconds) and Frequency (Hz) descriptive with units. Colorbar
+          labeled Power (dB).
     design_excellence:
-      score: 11
+      score: 12
       max: 20
       items:
       - id: DE-01
@@ -91,24 +99,26 @@ review:
         score: 5
         max: 8
         passed: true
-        comment: Magma colormap is strong choice, log y-axis with meaningful tick
-          positions, toolbar removed. Above default but not publication-quality
+        comment: Magma colormap is strong choice. Dark background matching colormap
+          floor is professional. Toolbar removed, bold title. Above default but not
+          publication-grade.
       - id: DE-02
         name: Visual Refinement
-        score: 3
+        score: 4
         max: 6
         passed: true
-        comment: Subtle dashed grid with alpha=0.2, removed toolbar, styled outline,
-          background fill None
+        comment: Subtle dashed grid (alpha=0.15), minor ticks hidden, custom outline,
+          dark background fill, generous padding. Clear refinement effort.
       - id: DE-03
         name: Data Storytelling
         score: 3
         max: 6
         passed: true
         comment: Synthesized melody creates visual narrative with note progressions
-          and harmonic structure visible
+          and harmonic structure. No explicit visual emphasis guiding viewer to key
+          insight.
     spec_compliance:
-      score: 14
+      score: 15
       max: 15
       items:
       - id: SC-01
@@ -116,27 +126,27 @@ review:
         score: 5
         max: 5
         passed: true
-        comment: Correct mel-spectrogram visualization
+        comment: Correct mel-spectrogram visualization with mel-scaled frequency axis.
       - id: SC-02
         name: Required Features
         score: 4
         max: 4
         passed: true
         comment: 'All required features present: dB scale, sequential colormap, time/frequency
-          axes, colorbar, correct parameters, synthesized audio'
+          axes, colorbar in dB, correct parameters, synthesized audio.'
       - id: SC-03
         name: Data Mapping
-        score: 2
+        score: 3
         max: 3
         passed: true
-        comment: X=time Y=frequency correct but p.image() linear mapping with log
-          y-axis causes visual distortion of mel bands
+        comment: X=time Y=frequency correctly mapped. Quads properly positioned on
+          mel scale with log y-axis.
       - id: SC-04
         name: Title & Legend
         score: 3
         max: 3
         passed: true
-        comment: Title format correct, no legend needed for this plot type
+        comment: Title format correct. No legend needed for this plot type.
     data_quality:
       score: 14
       max: 15
@@ -147,21 +157,21 @@ review:
         max: 6
         passed: true
         comment: Rich audio with 7 notes, harmonics, ADSR envelopes, background noise.
-          Could show wider frequency variety
+          Could show wider frequency variety.
       - id: DQ-02
         name: Realistic Context
         score: 5
         max: 5
         passed: true
-        comment: Real musical notes (C4-C5) with correct frequencies, realistic sample
-          rate and duration
+        comment: Real musical notes with correct frequencies, standard sample rate
+          and duration.
       - id: DQ-03
         name: Appropriate Scale
         score: 4
         max: 4
         passed: true
         comment: 'All values sensible: 22050 Hz sample rate, musical frequencies in
-          hearing range, 128 mel bands'
+          hearing range, 128 mel bands.'
     code_quality:
       score: 9
       max: 10
@@ -171,50 +181,52 @@ review:
         score: 3
         max: 3
         passed: true
-        comment: Clean imports-data-plot-save structure, no functions or classes
+        comment: Clean imports-data-STFT-mel-plot-save structure, no functions or
+          classes.
       - id: CQ-02
         name: Reproducibility
         score: 2
         max: 2
         passed: true
-        comment: np.random.seed(42) set at beginning
+        comment: np.random.seed(42) set at beginning.
       - id: CQ-03
         name: Clean Imports
         score: 2
         max: 2
         passed: true
-        comment: 'All imports used: numpy, bokeh models, scipy.signal'
+        comment: 'All imports used: numpy, bokeh models/palettes/plotting/io, scipy.signal.'
       - id: CQ-04
         name: Code Elegance
         score: 1
         max: 2
         passed: false
-        comment: 256-line hardcoded magma palette is unnecessarily verbose when Bokeh
-          provides Magma256
+        comment: Nested loop for quad data construction is verbose; could be vectorized
+          with np.repeat/np.tile.
       - id: CQ-05
         name: Output & API
         score: 1
         max: 1
         passed: true
-        comment: Saves as plot.png and plot.html, current API usage
+        comment: Saves as plot.png and plot.html, current API usage.
     library_mastery:
-      score: 5
+      score: 7
       max: 10
       items:
       - id: LM-01
         name: Idiomatic Usage
-        score: 3
+        score: 4
         max: 5
         passed: true
-        comment: Correct figure/image/ColorBar usage but manually defines palette
-          instead of using bokeh.palettes
+        comment: Good use of ColumnDataSource, quad renderer, ColorBar, LinearColorMapper,
+          FixedTicker, Magma256 from bokeh.palettes, export_png/output_file/save.
       - id: LM-02
         name: Distinctive Features
-        score: 2
+        score: 3
         max: 5
-        passed: false
-        comment: HTML export is Bokeh-specific but missing HoverTool and other interactive
-          features that make Bokeh distinctive
+        passed: true
+        comment: HoverTool with time/frequency/power readout is genuinely distinctive
+          Bokeh feature. HTML export alongside PNG. ColumnDataSource enables hover
+          interactivity.
   verdict: REJECTED
 impl_tags:
   dependencies:
@@ -222,13 +234,16 @@ impl_tags:
   techniques:
   - colorbar
   - manual-ticks
+  - hover-tooltips
   - html-export
   patterns:
   - data-generation
   - matrix-construction
   - iteration-over-groups
+  - columndatasource
   dataprep:
   - binning
   styling:
   - custom-colormap
   - grid-styling
+  - dark-theme

From 73b2c8c03cb98101d40bd4fd9cd0646acdbfebb4 Mon Sep 17 00:00:00 2001
From: "github-actions[bot]" <github-actions[bot]@users.noreply.github.com>
Date: Wed, 11 Mar 2026 20:04:01 +0000
Subject: [PATCH 6/7] fix(bokeh): address review feedback for spectrogram-mel

Attempt 2/3 - fixes based on AI review
---
 .../spectrogram-mel/implementations/bokeh.py  | 194 +++++++++++-------
 1 file changed, 115 insertions(+), 79 deletions(-)

diff --git a/plots/spectrogram-mel/implementations/bokeh.py b/plots/spectrogram-mel/implementations/bokeh.py
index a66c5ed7e4..919ac6076f 100644
--- a/plots/spectrogram-mel/implementations/bokeh.py
+++ b/plots/spectrogram-mel/implementations/bokeh.py
@@ -1,12 +1,21 @@
-""" pyplots.ai
+"""pyplots.ai
 spectrogram-mel: Mel-Spectrogram for Audio Analysis
 Library: bokeh 3.9.0 | Python 3.14.3
-Quality: 85/100 | Created: 2026-03-11
 """
 
 import numpy as np
 from bokeh.io import export_png, output_file, save
-from bokeh.models import BasicTicker, ColorBar, ColumnDataSource, FixedTicker, HoverTool, LinearColorMapper
+from bokeh.models import (
+    BasicTicker,
+    BoxAnnotation,
+    ColorBar,
+    ColumnDataSource,
+    FixedTicker,
+    HoverTool,
+    Label,
+    LinearColorMapper,
+    Span,
+)
 from bokeh.palettes import Magma256
 from bokeh.plotting import figure
 from scipy import signal
@@ -37,7 +46,6 @@
     mask = (t >= start) & (t < end)
     envelope = np.zeros(n_samples)
     note_len = np.sum(mask)
-    # ADSR-like envelope
     attack = int(0.05 * sample_rate)
     release = int(0.1 * sample_rate)
     if note_len > attack + release:
@@ -45,7 +53,6 @@
         env[:attack] = np.linspace(0, 1, attack)
         env[-release:] = np.linspace(1, 0, release)
         envelope[mask] = env
-    # Fundamental + harmonics
     audio_signal += envelope * (
         0.6 * np.sin(2 * np.pi * freq * t)
         + 0.25 * np.sin(2 * np.pi * 2 * freq * t)
@@ -53,10 +60,7 @@
         + 0.05 * np.sin(2 * np.pi * 4 * freq * t)
     )
 
-# Add subtle background noise
 audio_signal += 0.02 * np.random.randn(n_samples)
-
-# Normalize
 audio_signal = audio_signal / np.max(np.abs(audio_signal))
 
 # Compute STFT
@@ -65,88 +69,63 @@
 frequencies, times, Zxx = signal.stft(audio_signal, fs=sample_rate, nperseg=n_fft, noverlap=n_fft - hop_length)
 power_spectrum = np.abs(Zxx) ** 2
 
-
 # Mel filterbank construction
 n_mels = 128
 f_min = 0.0
 f_max = sample_rate / 2.0
 
-# Mel points evenly spaced on mel scale (Hz-to-mel: 2595 * log10(1 + f/700))
 mel_min = 2595.0 * np.log10(1.0 + f_min / 700.0)
 mel_max = 2595.0 * np.log10(1.0 + f_max / 700.0)
 mel_points = np.linspace(mel_min, mel_max, n_mels + 2)
 hz_points = 700.0 * (10.0 ** (mel_points / 2595.0) - 1.0)
 
-# Convert Hz points to FFT bin indices
 bin_points = np.floor((n_fft + 1) * hz_points / sample_rate).astype(int)
 
-# Build triangular filterbank
+# Build triangular filterbank (vectorized inner loop)
 n_freqs = len(frequencies)
 filterbank = np.zeros((n_mels, n_freqs))
 for m in range(n_mels):
-    f_left = bin_points[m]
-    f_center = bin_points[m + 1]
-    f_right = bin_points[m + 2]
-    for k in range(f_left, f_center):
-        if f_center != f_left:
-            filterbank[m, k] = (k - f_left) / (f_center - f_left)
-    for k in range(f_center, f_right):
-        if f_right != f_center:
-            filterbank[m, k] = (f_right - k) / (f_right - f_center)
-
-# Apply mel filterbank to power spectrum
-mel_spectrogram = filterbank @ power_spectrum
+    f_left, f_center, f_right = bin_points[m], bin_points[m + 1], bin_points[m + 2]
+    if f_center > f_left:
+        rising = np.arange(f_left, f_center)
+        filterbank[m, rising] = (rising - f_left) / (f_center - f_left)
+    if f_right > f_center:
+        falling = np.arange(f_center, f_right)
+        filterbank[m, falling] = (f_right - falling) / (f_right - f_center)
 
-# Convert to decibel scale
+mel_spectrogram = filterbank @ power_spectrum
 mel_spectrogram_db = 10.0 * np.log10(mel_spectrogram + 1e-10)
 
-# Mel band edge frequencies (for positioning rectangles correctly on log scale)
-mel_edge_freqs = hz_points  # n_mels + 2 edges
-# Clamp to positive values for log scale
-mel_edge_freqs = np.maximum(mel_edge_freqs, 1.0)
+# Mel band edge frequencies for quad positioning on log scale
+mel_edge_freqs = np.maximum(hz_points, 1.0)
 
-# Build quad data for each mel band x time frame
+# Build quad data vectorized with np.repeat/np.tile
 n_times = len(times)
 time_step = times[1] - times[0] if n_times > 1 else hop_length / sample_rate
 
-quad_left = []
-quad_right = []
-quad_bottom = []
-quad_top = []
-quad_power = []
-quad_time_label = []
-quad_freq_label = []
-
-for ti in range(n_times):
-    for mi in range(n_mels):
-        quad_left.append(times[ti] - time_step / 2)
-        quad_right.append(times[ti] + time_step / 2)
-        quad_bottom.append(mel_edge_freqs[mi + 1])
-        quad_top.append(mel_edge_freqs[mi + 2])
-        quad_power.append(mel_spectrogram_db[mi, ti])
-        quad_time_label.append(round(times[ti], 3))
-        quad_freq_label.append(round((mel_edge_freqs[mi + 1] + mel_edge_freqs[mi + 2]) / 2, 1))
-
-quad_power_arr = np.array(quad_power)
+time_grid = np.repeat(times, n_mels)
+bottom_grid = np.tile(mel_edge_freqs[1 : n_mels + 1], n_times)
+top_grid = np.tile(mel_edge_freqs[2 : n_mels + 2], n_times)
+power_grid = mel_spectrogram_db.T.ravel()
+
 vmin = float(np.percentile(mel_spectrogram_db, 5))
 vmax = float(mel_spectrogram_db.max())
 
-# Map power to palette indices for fill_color
-normalized = (quad_power_arr - vmin) / (vmax - vmin)
-normalized = np.clip(normalized, 0, 1)
+# Map power to palette colors
+normalized = np.clip((power_grid - vmin) / (vmax - vmin), 0, 1)
 color_indices = (normalized * 255).astype(int)
 colors = [Magma256[i] for i in color_indices]
 
 source = ColumnDataSource(
     data={
-        "left": quad_left,
-        "right": quad_right,
-        "bottom": quad_bottom,
-        "top": quad_top,
-        "power": quad_power,
+        "left": time_grid - time_step / 2,
+        "right": time_grid + time_step / 2,
+        "bottom": bottom_grid,
+        "top": top_grid,
+        "power": power_grid,
         "color": colors,
-        "time_s": quad_time_label,
-        "freq_hz": quad_freq_label,
+        "time_s": np.round(time_grid, 3),
+        "freq_hz": np.round((bottom_grid + top_grid) / 2, 1),
     }
 )
 
@@ -164,7 +143,7 @@
     toolbar_location=None,
 )
 
-# Render mel bands as quads for correct log-scale positioning
+# Render mel bands as quads
 p.quad(
     left="left",
     right="right",
@@ -176,6 +155,53 @@
     level="image",
 )
 
+# Visual storytelling: annotate the C-major arpeggio rising pattern
+arpeggio_box = BoxAnnotation(
+    left=0.0, right=2.5, fill_alpha=0, line_color="#ffffff", line_alpha=0.45, line_width=3, line_dash="dashed"
+)
+p.add_layout(arpeggio_box)
+
+arpeggio_label = Label(
+    x=0.05,
+    y=mel_edge_freqs[-1] * 0.85,
+    text="C Major Arpeggio (C4 \u2192 E4 \u2192 G4 \u2192 C5)",
+    text_font_size="22pt",
+    text_color="#ffffff",
+    text_alpha=0.85,
+    text_font_style="italic",
+)
+p.add_layout(arpeggio_label)
+
+# Mark octave fundamentals (C4, C5) with horizontal frequency guides
+for freq, name in [(261.63, "C4"), (523.25, "C5")]:
+    if mel_edge_freqs[1] <= freq <= mel_edge_freqs[-1]:
+        span = Span(
+            location=freq, dimension="width", line_color="#ffffff", line_alpha=0.25, line_width=2, line_dash="dotted"
+        )
+        p.add_layout(span)
+        label = Label(
+            x=times.max() + time_step * 0.3,
+            y=freq,
+            text=name,
+            text_font_size="20pt",
+            text_color="#ffffff",
+            text_alpha=0.7,
+            text_font_style="bold",
+        )
+        p.add_layout(label)
+
+# Descending passage label
+desc_label = Label(
+    x=2.55,
+    y=mel_edge_freqs[-1] * 0.85,
+    text="Descending (A4 \u2192 F4 \u2192 D4)",
+    text_font_size="22pt",
+    text_color="#ffffff",
+    text_alpha=0.65,
+    text_font_style="italic",
+)
+p.add_layout(desc_label)
+
 # HoverTool for interactive readout
 hover = HoverTool(
     tooltips=[("Time", "@time_s{0.000} s"), ("Frequency", "@freq_hz{0.0} Hz"), ("Power", "@power{0.0} dB")],
@@ -183,65 +209,75 @@
 )
 p.add_tools(hover)
 
-# Color mapper for the colorbar
+# Colorbar
 color_mapper = LinearColorMapper(palette=Magma256, low=vmin, high=vmax)
-
-# Colorbar labeled in dB
 color_bar = ColorBar(
     color_mapper=color_mapper,
     ticker=BasicTicker(desired_num_ticks=8),
-    label_standoff=20,
+    label_standoff=24,
     border_line_color=None,
     location=(0, 0),
     title="Power (dB)",
     title_text_font_size="32pt",
+    title_text_font_style="italic",
     major_label_text_font_size="24pt",
+    major_label_text_color="#444444",
     width=70,
-    padding=40,
-    title_standoff=20,
+    padding=50,
+    title_standoff=24,
 )
 p.add_layout(color_bar, "right")
 
 # Y-axis tick labels at key mel band frequencies
-mel_tick_freqs = [50, 100, 200, 500, 1000, 2000, 4000, 8000]
-mel_tick_freqs = [f for f in mel_tick_freqs if mel_edge_freqs[1] <= f <= mel_edge_freqs[-1]]
+mel_tick_freqs = [
+    f for f in [50, 100, 200, 500, 1000, 2000, 4000, 8000] if mel_edge_freqs[1] <= f <= mel_edge_freqs[-1]
+]
 p.yaxis.ticker = FixedTicker(ticks=mel_tick_freqs)
 
-# Style for 4800x2700 canvas
-p.title.text_font_size = "40pt"
+# Typography for 4800x2700 canvas
+p.title.text_font_size = "42pt"
 p.title.text_font_style = "bold"
-p.title.text_color = "#222222"
+p.title.text_color = "#333333"
 p.xaxis.axis_label_text_font_size = "32pt"
 p.yaxis.axis_label_text_font_size = "32pt"
 p.xaxis.major_label_text_font_size = "24pt"
 p.yaxis.major_label_text_font_size = "24pt"
 p.xaxis.axis_label_text_font_style = "normal"
 p.yaxis.axis_label_text_font_style = "normal"
+p.xaxis.axis_label_text_color = "#444444"
+p.yaxis.axis_label_text_color = "#444444"
+p.xaxis.major_label_text_color = "#555555"
+p.yaxis.major_label_text_color = "#555555"
 
 # Axis styling
 p.xaxis.axis_line_width = 3
 p.yaxis.axis_line_width = 3
+p.xaxis.axis_line_color = "#555555"
+p.yaxis.axis_line_color = "#555555"
 p.xaxis.major_tick_line_width = 3
 p.yaxis.major_tick_line_width = 3
+p.xaxis.major_tick_line_color = "#555555"
+p.yaxis.major_tick_line_color = "#555555"
 p.xaxis.minor_tick_line_color = None
 p.yaxis.minor_tick_line_color = None
 
 # Grid - subtle styling
-p.xgrid.grid_line_alpha = 0.15
-p.ygrid.grid_line_alpha = 0.15
+p.xgrid.grid_line_alpha = 0.12
+p.ygrid.grid_line_alpha = 0.12
 p.xgrid.grid_line_dash = [6, 4]
 p.ygrid.grid_line_dash = [6, 4]
-p.xgrid.grid_line_color = "#aaaaaa"
-p.ygrid.grid_line_color = "#aaaaaa"
+p.xgrid.grid_line_color = "#888888"
+p.ygrid.grid_line_color = "#888888"
 
 # Background
 p.background_fill_color = "#000004"
-p.border_fill_color = "white"
+p.border_fill_color = "#fafafa"
 p.outline_line_color = "#333333"
 p.outline_line_width = 2
-p.min_border_right = 140
-p.min_border_left = 120
-p.min_border_bottom = 100
+p.min_border_right = 180
+p.min_border_left = 130
+p.min_border_bottom = 110
+p.min_border_top = 80
 
 # Save
 export_png(p, filename="plot.png")

From 76cb57a61e00e957962fef560b5454cfc2cfef19 Mon Sep 17 00:00:00 2001
From: "github-actions[bot]" <github-actions[bot]@users.noreply.github.com>
Date: Wed, 11 Mar 2026 20:09:08 +0000
Subject: [PATCH 7/7] chore(bokeh): update quality score 92 and review feedback
 for spectrogram-mel

---
 .../spectrogram-mel/implementations/bokeh.py  |   3 +-
 plots/spectrogram-mel/metadata/bokeh.yaml     | 168 ++++++++----------
 2 files changed, 81 insertions(+), 90 deletions(-)

diff --git a/plots/spectrogram-mel/implementations/bokeh.py b/plots/spectrogram-mel/implementations/bokeh.py
index 919ac6076f..5579aa5bc2 100644
--- a/plots/spectrogram-mel/implementations/bokeh.py
+++ b/plots/spectrogram-mel/implementations/bokeh.py
@@ -1,6 +1,7 @@
-"""pyplots.ai
+""" pyplots.ai
 spectrogram-mel: Mel-Spectrogram for Audio Analysis
 Library: bokeh 3.9.0 | Python 3.14.3
+Quality: 92/100 | Created: 2026-03-11
 """
 
 import numpy as np
diff --git a/plots/spectrogram-mel/metadata/bokeh.yaml b/plots/spectrogram-mel/metadata/bokeh.yaml
index 49a0199836..30d1b72877 100644
--- a/plots/spectrogram-mel/metadata/bokeh.yaml
+++ b/plots/spectrogram-mel/metadata/bokeh.yaml
@@ -1,7 +1,7 @@
 library: bokeh
 specification_id: spectrogram-mel
 created: '2026-03-11T19:42:55Z'
-updated: '2026-03-11T19:58:05Z'
+updated: '2026-03-11T20:09:08Z'
 generated_by: claude-opus-4-5-20251101
 workflow_run: 22970857215
 issue: 4672
@@ -10,41 +10,40 @@ library_version: 3.9.0
 preview_url: https://storage.googleapis.com/pyplots-images/plots/spectrogram-mel/bokeh/plot.png
 preview_thumb: https://storage.googleapis.com/pyplots-images/plots/spectrogram-mel/bokeh/plot_thumb.png
 preview_html: https://storage.googleapis.com/pyplots-images/plots/spectrogram-mel/bokeh/plot.html
-quality_score: 85
+quality_score: 92
 review:
   strengths:
-  - Excellent mel filterbank construction from scratch using scipy.signal STFT, avoiding
-    librosa dependency
-  - Quad rendering correctly positions mel bands on log y-axis, fixing the visual
-    distortion from attempt 1
-  - HoverTool provides genuinely interactive readout of time, frequency, and power
-    values
-  - Dark background matching Magma colormap floor creates cohesive visual design
-  - Rich audio synthesis with harmonics and ADSR envelopes produces a visually engaging
-    spectrogram
+  - Mel filterbank computed from scratch with proper triangular filters demonstrating
+    deep audio signal processing understanding
+  - Magma colormap on dark background is industry-standard for spectrograms and looks
+    professional
+  - Musical narrative (C Major Arpeggio to descending passage) with annotations creates
+    excellent data storytelling
+  - All font sizes explicitly scaled for 4800x2700 canvas with careful typography
+    hierarchy
+  - Vectorized quad construction is efficient and clean
+  - HoverTool adds genuine interactive value for the HTML export
   weaknesses:
-  - 'Design Excellence needs improvement: typography could be more refined, no visual
-    emphasis or annotation guiding viewer to key insight'
-  - Nested loop for building quad data arrays is verbose and could be vectorized with
-    np.repeat/np.tile
-  - Colorbar right margin slightly tight, could use more breathing room
-  image_description: The plot displays a mel-spectrogram rendered with the Magma colormap
-    on a dark background (#000004, matching the colormap's lowest value). The x-axis
-    shows "Time (seconds)" from 0 to 4, and the y-axis shows "Frequency (Hz)" on a
-    logarithmic scale with fixed ticks at 50, 100, 200, 500, 1000, 2000, 4000, and
-    8000 Hz. A colorbar on the right is labeled "Power (dB)" ranging from approximately
-    -70 to -20 dB. Bright horizontal bands (yellow-white through pink) are clearly
-    visible at various frequency levels corresponding to the synthesized melody notes
-    (C4, E4, G4, C5, A4, F4, D4) and their harmonics, with fundamentals showing the
-    brightest intensity and harmonics progressively dimmer. Note onsets and offsets
-    show clean ADSR envelope shaping. The mel bands are rendered as individual quads
-    correctly positioned on the log y-axis, eliminating the distortion seen in attempt
-    1. Background noise appears as low-level dark texture primarily in the lower frequencies.
-    The title reads "spectrogram-mel · bokeh · pyplots.ai" in bold at the top left.
-    Subtle dashed grid lines are visible at low opacity.
+  - LM-01 could reach 5/5 with use of Bokeh built-in image glyph (p.image) instead
+    of manually constructing quads
+  - DE-02 could benefit from removing the outline line entirely for a cleaner aesthetic
+  image_description: The plot displays a mel-spectrogram on a dark (#000004) background
+    using the Magma256 sequential colormap. The title "spectrogram-mel · bokeh · pyplots.ai"
+    appears at the top left in bold dark text. The x-axis is labeled "Time (seconds)"
+    spanning 0 to ~4 seconds, and the y-axis shows "Frequency (Hz)" on a logarithmic
+    scale with mel-spaced tick marks at 50, 100, 200, 500, 1000, 2000, 4000, and 8000
+    Hz. Bright yellow-white horizontal bands clearly depict individual musical notes
+    with visible harmonic overtones above each fundamental. A white dashed bounding
+    box in the left portion annotates "C Major Arpeggio (C4 → E4 → G4 → C5)" in italic
+    white text, while the right portion shows "Descending (A4 → F4 → D4)". Dotted
+    white horizontal reference lines mark the C4 (261 Hz) and C5 (523 Hz) frequencies
+    with bold labels at the right edge. A colorbar on the right displays "Power (dB)"
+    ranging from approximately −100 to −20 dB. The spectrogram clearly shows the ascending
+    arpeggio followed by a descending passage, with visible attack/release envelopes,
+    harmonic structure, and a subtle noise floor.
   criteria_checklist:
     visual_quality:
-      score: 28
+      score: 30
       max: 30
       items:
       - id: VQ-01
@@ -52,71 +51,66 @@ review:
         score: 8
         max: 8
         passed: true
-        comment: 'All font sizes explicitly set: title=40pt, axis labels=32pt, tick
-          labels=24pt, colorbar title=32pt, colorbar labels=24pt. All text clearly
-          readable.'
+        comment: 'All font sizes explicitly set: 42pt title, 32pt axis labels, 24pt
+          tick labels, 22pt annotations'
       - id: VQ-02
         name: No Overlap
         score: 6
         max: 6
         passed: true
-        comment: No overlapping text elements anywhere in the plot.
+        comment: All text elements well-positioned, annotations in upper region away
+          from dense data
       - id: VQ-03
         name: Element Visibility
-        score: 5
+        score: 6
         max: 6
         passed: true
-        comment: Mel bands clearly visible with good contrast. Quad rendering correctly
-          positions bands on log scale. Lower frequency bins slightly coarse due to
-          narrow mel bandwidth.
+        comment: Mel band quads clearly visible with excellent contrast, harmonic
+          structure distinguishable
       - id: VQ-04
         name: Color Accessibility
         score: 4
         max: 4
         passed: true
-        comment: Magma is perceptually uniform and colorblind-safe with excellent
-          contrast.
+        comment: Magma256 is perceptually uniform and colorblind-safe
       - id: VQ-05
         name: Layout & Canvas
-        score: 3
+        score: 4
         max: 4
         passed: true
-        comment: Good canvas utilization with colorbar on right. Colorbar title text
-          slightly tight against right edge.
+        comment: Plot fills canvas well with explicitly set margins, colorbar properly
+          positioned
       - id: VQ-06
         name: Axis Labels & Title
         score: 2
         max: 2
         passed: true
-        comment: Time (seconds) and Frequency (Hz) descriptive with units. Colorbar
-          labeled Power (dB).
+        comment: Time (seconds) and Frequency (Hz) - descriptive with units
     design_excellence:
-      score: 12
+      score: 15
       max: 20
       items:
       - id: DE-01
         name: Aesthetic Sophistication
-        score: 5
+        score: 6
         max: 8
         passed: true
-        comment: Magma colormap is strong choice. Dark background matching colormap
-          floor is professional. Toolbar removed, bold title. Above default but not
-          publication-grade.
+        comment: 'Strong design: Magma on dark background, intentional typography
+          hierarchy, white annotation overlays'
       - id: DE-02
         name: Visual Refinement
         score: 4
         max: 6
         passed: true
-        comment: Subtle dashed grid (alpha=0.15), minor ticks hidden, custom outline,
-          dark background fill, generous padding. Clear refinement effort.
+        comment: Subtle grid (alpha=0.12, dashed), minor ticks removed, custom background/border
+          colors
       - id: DE-03
         name: Data Storytelling
-        score: 3
+        score: 5
         max: 6
         passed: true
-        comment: Synthesized melody creates visual narrative with note progressions
-          and harmonic structure. No explicit visual emphasis guiding viewer to key
-          insight.
+        comment: Dashed box highlights ascending arpeggio, separate label for descending
+          passage, C4/C5 frequency guides
     spec_compliance:
       score: 15
       max: 15
@@ -126,54 +120,53 @@ review:
         score: 5
         max: 5
         passed: true
-        comment: Correct mel-spectrogram visualization with mel-scaled frequency axis.
+        comment: Correct mel-spectrogram with proper mel filterbank computed from
+          scratch
       - id: SC-02
         name: Required Features
         score: 4
         max: 4
         passed: true
-        comment: 'All required features present: dB scale, sequential colormap, time/frequency
-          axes, colorbar in dB, correct parameters, synthesized audio.'
+        comment: 'All spec requirements met: dB scale, Magma colormap, time x-axis,
+          mel-scaled y-axis, colorbar in dB, correct parameters'
       - id: SC-03
         name: Data Mapping
         score: 3
         max: 3
         passed: true
-        comment: X=time Y=frequency correctly mapped. Quads properly positioned on
-          mel scale with log y-axis.
+        comment: X=time in seconds, Y=mel-frequency in Hz on log scale
       - id: SC-04
         name: Title & Legend
         score: 3
         max: 3
         passed: true
-        comment: Title format correct. No legend needed for this plot type.
+        comment: Title matches required format, colorbar serves as scale reference
     data_quality:
-      score: 14
+      score: 15
       max: 15
       items:
       - id: DQ-01
         name: Feature Coverage
-        score: 5
+        score: 6
         max: 6
         passed: true
-        comment: Rich audio with 7 notes, harmonics, ADSR envelopes, background noise.
-          Could show wider frequency variety.
+        comment: 'Rich audio: 7 notes with 4 harmonics each, attack/release envelopes,
+          background noise'
       - id: DQ-02
         name: Realistic Context
         score: 5
         max: 5
         passed: true
-        comment: Real musical notes with correct frequencies, standard sample rate
-          and duration.
+        comment: Musical melody context (C Major Arpeggio) is realistic and neutral
       - id: DQ-03
         name: Appropriate Scale
         score: 4
         max: 4
         passed: true
-        comment: 'All values sensible: 22050 Hz sample rate, musical frequencies in
-          hearing range, 128 mel bands.'
+        comment: Sample rate 22050 Hz, 4-second duration, musical frequencies - all
+          realistic
     code_quality:
-      score: 9
+      score: 10
       max: 10
       items:
       - id: CQ-01
@@ -181,33 +174,31 @@ review:
         score: 3
         max: 3
         passed: true
-        comment: Clean imports-data-STFT-mel-plot-save structure, no functions or
-          classes.
+        comment: Clean imports-data-plot-save structure, no functions or classes
       - id: CQ-02
         name: Reproducibility
         score: 2
         max: 2
         passed: true
-        comment: np.random.seed(42) set at beginning.
+        comment: np.random.seed(42) set at start
       - id: CQ-03
         name: Clean Imports
         score: 2
         max: 2
         passed: true
-        comment: 'All imports used: numpy, bokeh models/palettes/plotting/io, scipy.signal.'
+        comment: 'All imports used: numpy, bokeh models, Magma256, scipy.signal'
       - id: CQ-04
         name: Code Elegance
-        score: 1
+        score: 2
         max: 2
-        passed: false
-        comment: Nested loop for quad data construction is verbose; could be vectorized
-          with np.repeat/np.tile.
+        passed: true
+        comment: Appropriate complexity, vectorized quad construction, no fake functionality
       - id: CQ-05
         name: Output & API
         score: 1
         max: 1
         passed: true
-        comment: Saves as plot.png and plot.html, current API usage.
+        comment: Saves as plot.png via export_png and plot.html via save
     library_mastery:
       score: 7
       max: 10
@@ -217,29 +208,28 @@ review:
         score: 4
         max: 5
         passed: true
-        comment: Good use of ColumnDataSource, quad renderer, ColorBar, LinearColorMapper,
-          FixedTicker, Magma256 from bokeh.palettes, export_png/output_file/save.
+        comment: Excellent use of ColumnDataSource, quad glyphs, layout system, ColorBar,
+          FixedTicker
       - id: LM-02
         name: Distinctive Features
         score: 3
         max: 5
         passed: true
-        comment: HoverTool with time/frequency/power readout is genuinely distinctive
-          Bokeh feature. HTML export alongside PNG. ColumnDataSource enables hover
-          interactivity.
-  verdict: REJECTED
+        comment: HoverTool with formatted tooltips, HTML export, BoxAnnotation - distinctively
+          Bokeh features
+  verdict: APPROVED
 impl_tags:
   dependencies:
   - scipy
   techniques:
   - colorbar
-  - manual-ticks
+  - annotations
   - hover-tooltips
+  - manual-ticks
   - html-export
   patterns:
   - data-generation
   - matrix-construction
-  - iteration-over-groups
   - columndatasource
   dataprep:
   - binning