{"spec_id":"heatmap-chromagram","library":"bokeh","language":"python","code":"\"\"\" anyplot.ai\nheatmap-chromagram: Music Chromagram (Pitch Class Distribution over Time)\nLibrary: bokeh 3.9.1 | Python 3.13.14\nQuality: 89/100 | Updated: 2026-06-24\n\"\"\"\n\nimport os\nimport sys\nimport time\nfrom pathlib import Path\n\n\n# Remove this script's directory from sys.path so 'bokeh.py' doesn't shadow the installed package\n_here = os.path.dirname(os.path.abspath(__file__))\nsys.path = [p for p in sys.path if os.path.abspath(p) != _here]\n\nimport numpy as np\nimport pandas as pd\nfrom bokeh.io import output_file, save\nfrom bokeh.models import (\n    BasicTicker,\n    ColorBar,\n    ColumnDataSource,\n    FixedTicker,\n    HoverTool,\n    Label,\n    LinearColorMapper,\n    Range1d,\n    Span,\n)\nfrom bokeh.plotting import figure\nfrom selenium import webdriver\nfrom selenium.webdriver.chrome.options import Options\n\n\nTHEME = os.getenv(\"ANYPLOT_THEME\", \"light\")\n\nPAGE_BG = \"#FAF8F1\" if THEME == \"light\" else \"#1A1A17\"\nELEVATED_BG = \"#FFFDF6\" if THEME == \"light\" else \"#242420\"\nINK = \"#1A1A17\" if THEME == \"light\" else \"#F0EFE8\"\nINK_SOFT = \"#4A4A44\" if THEME == \"light\" else \"#B8B7B0\"\nINK_MUTED = \"#6B6A63\" if THEME == \"light\" else \"#A8A79F\"\n\n\n# Imprint sequential colormap: brand green (#009E73) → blue (#4467A3), single-polarity energy\nIMPRINT_SEQ = [\n    \"#{:02X}{:02X}{:02X}\".format(round(t * 68 / 255), round(158 - t * 55 / 255), round(115 + t * 48 / 255))\n    for t in range(256)\n]\n\n# Data — simulated chromagram: 12 pitch classes over 80 time frames\nnp.random.seed(42)\npitch_classes = [\"C\", \"C#\", \"D\", \"D#\", \"E\", \"F\", \"F#\", \"G\", \"G#\", \"A\", \"A#\", \"B\"]\nn_pitch = len(pitch_classes)\nn_frames = 80\ntime_seconds = np.linspace(0, 8, n_frames)\n\n# Build energy matrix simulating chord progressions:\n# C major (C-E-G) -> G major (G-B-D) -> Am (A-C-E) -> F major (F-A-C)\nenergy = np.random.uniform(0.02, 0.12, size=(12, n_frames))\n\nchord_patterns = {\n    \"C_major\": {\"notes\": [0, 4, 7], \"boost\": [0.9, 0.7, 0.8]},\n    \"G_major\": {\"notes\": [7, 11, 2], \"boost\": [0.9, 0.7, 0.75]},\n    \"A_minor\": {\"notes\": [9, 0, 4], \"boost\": [0.85, 0.7, 0.7]},\n    \"F_major\": {\"notes\": [5, 9, 0], \"boost\": [0.9, 0.7, 0.75]},\n}\n\nchord_sequence = [\"C_major\", \"G_major\", \"A_minor\", \"F_major\"]\nchord_display = [\"C major\", \"G major\", \"A minor\", \"F major\"]\nframes_per_chord = n_frames // len(chord_sequence)\n\nfor idx, chord_name in enumerate(chord_sequence):\n    start = idx * frames_per_chord\n    end = start + frames_per_chord\n    pattern = chord_patterns[chord_name]\n    for note_idx, boost in zip(pattern[\"notes\"], pattern[\"boost\"], strict=True):\n        energy[note_idx, start:end] += boost + np.random.uniform(-0.08, 0.08, end - start)\n    for note_idx in pattern[\"notes\"]:\n        neighbor = (note_idx + 7) % 12\n        energy[neighbor, start:end] += 0.15 + np.random.uniform(-0.03, 0.03, end - start)\n\n# Smooth transitions between chords\nfor i in range(1, len(chord_sequence)):\n    boundary = i * frames_per_chord\n    if boundary - 2 >= 0 and boundary + 2 < n_frames:\n        for row in range(12):\n            window = energy[row, boundary - 2 : boundary + 3]\n            energy[row, boundary - 2 : boundary + 3] = np.convolve(window, [0.15, 0.25, 0.3, 0.2, 0.1], mode=\"same\")\n\nenergy = np.clip(energy, 0, 1)\n\ndt = time_seconds[1] - time_seconds[0]\n\n# image glyph renders row 0 at bottom; reversing places C at top\nenergy_image = energy[::-1, :]\n\n# Flatten to DataFrame for HoverTool interactivity\nrecords = []\nfor i, pitch in enumerate(pitch_classes):\n    y_pos = n_pitch - 1 - i\n    for j in range(n_frames):\n        records.append(\n            {\"time\": float(time_seconds[j]), \"pitch\": pitch, \"y\": y_pos, \"energy\": round(float(energy[i, j]), 3)}\n        )\n\nsource = ColumnDataSource(pd.DataFrame(records))\n\nmapper = LinearColorMapper(palette=IMPRINT_SEQ, low=0, high=1)\n\n# Square canvas (2400×2400) — symmetric pitch×time grid suits 1:1 format\np = figure(\n    width=2400,\n    height=2400,\n    y_range=Range1d(-0.5, n_pitch - 0.5),\n    x_range=(-dt / 2, 8 + dt / 2),\n    title=\"heatmap-chromagram · python · bokeh · anyplot.ai\",\n    x_axis_label=\"Time (seconds)\",\n    y_axis_label=\"Pitch Class\",\n    toolbar_location=None,\n    min_border_bottom=160,\n    min_border_left=180,\n    min_border_top=110,\n    min_border_right=230,\n)\n\n# Y-axis: pitch class labels\np.yaxis.ticker = FixedTicker(ticks=list(range(n_pitch)))\np.yaxis.major_label_overrides = {i: pitch_classes[n_pitch - 1 - i] for i in range(n_pitch)}\n\n# Seamless heatmap via image glyph — no cell gaps\np.image(image=[energy_image], x=-dt / 2, y=-0.5, dw=8 + dt, dh=n_pitch, color_mapper=mapper)\n\n# Invisible rect overlay for HoverTool interactivity\nr = p.rect(x=\"time\", y=\"y\", width=dt, height=1, source=source, fill_alpha=0, line_alpha=0)\n\n# Chord boundary Span annotations\nfor t_boundary in [2.0, 4.0, 6.0]:\n    p.add_layout(\n        Span(\n            location=t_boundary,\n            dimension=\"height\",\n            line_color=INK_SOFT,\n            line_width=3,\n            line_alpha=0.55,\n            line_dash=\"dashed\",\n        )\n    )\n\n# Chord label annotations at the top of each region\nfor idx, label_text in enumerate(chord_display):\n    t_center = idx * 2.0 + 1.0\n    p.add_layout(\n        Label(\n            x=t_center,\n            y=n_pitch - 0.6,\n            text=label_text,\n            text_font_size=\"28pt\",\n            text_color=INK_SOFT,\n            text_align=\"center\",\n            text_baseline=\"top\",\n            background_fill_color=PAGE_BG,\n            background_fill_alpha=0.65,\n        )\n    )\n\n# Color bar\ncolor_bar = ColorBar(\n    color_mapper=mapper,\n    width=60,\n    ticker=BasicTicker(desired_num_ticks=6),\n    label_standoff=15,\n    major_label_text_font_size=\"34pt\",\n    major_label_text_color=INK_SOFT,\n    border_line_color=None,\n    padding=20,\n    title=\"Energy\",\n    title_text_font_size=\"36pt\",\n    title_text_color=INK,\n    title_standoff=20,\n    background_fill_color=PAGE_BG,\n    bar_line_color=None,\n    major_tick_line_color=INK_SOFT,\n    minor_tick_line_color=None,\n)\np.add_layout(color_bar, \"right\")\n\nhover = HoverTool(\n    tooltips=[(\"Pitch\", \"@pitch\"), (\"Time\", \"@time{0.00} s\"), (\"Energy\", \"@energy{0.000}\")], renderers=[r]\n)\np.add_tools(hover)\n\n# Font sizes — canonical bokeh values for 2400×2400 canvas\np.title.text_font_size = \"50pt\"\np.title.text_color = INK\np.xaxis.axis_label_text_font_size = \"42pt\"\np.yaxis.axis_label_text_font_size = \"42pt\"\np.xaxis.major_label_text_font_size = \"34pt\"\np.yaxis.major_label_text_font_size = \"34pt\"\np.xaxis.axis_label_text_color = INK\np.yaxis.axis_label_text_color = INK\np.xaxis.major_label_text_color = INK_SOFT\np.yaxis.major_label_text_color = INK_SOFT\np.xaxis.axis_line_color = INK_SOFT\np.yaxis.axis_line_color = INK_SOFT\np.xaxis.major_tick_line_color = INK_SOFT\np.yaxis.major_tick_line_color = INK_SOFT\n\n# No grid — heatmap fills the entire plot area\np.xgrid.grid_line_color = None\np.ygrid.grid_line_color = None\np.outline_line_color = INK_SOFT\n\n# Theme-adaptive background\np.background_fill_color = PAGE_BG\np.border_fill_color = PAGE_BG\n\n# Save interactive HTML (required Bokeh catalog artifact)\noutput_file(f\"plot-{THEME}.html\")\nsave(p)\n\n# Screenshot with headless Chrome — avoid export_png (snap chromium incompatibility)\nW, H = 2400, 2400\nopts = Options()\nfor arg in (\n    \"--headless=new\",\n    \"--no-sandbox\",\n    \"--disable-dev-shm-usage\",\n    \"--disable-gpu\",\n    f\"--window-size={W},{H}\",\n    \"--hide-scrollbars\",\n):\n    opts.add_argument(arg)\ndriver = webdriver.Chrome(options=opts)\n# CDP override ensures exact viewport — window-size alone can drift due to browser chrome\ndriver.execute_cdp_cmd(\n    \"Emulation.setDeviceMetricsOverride\", {\"width\": W, \"height\": H, \"deviceScaleFactor\": 1, \"mobile\": False}\n)\ndriver.get(f\"file://{Path(f'plot-{THEME}.html').resolve()}\")\ntime.sleep(3)\ndriver.save_screenshot(f\"plot-{THEME}.png\")\ndriver.quit()\n"}