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Mikkeli Matlock a322f08d0c Add spectrogram, native-rate loading, and always-labelled axis extremes

- SpectrogramMetric: log-frequency STFT power heatmap over time, magma
  colormap, -80 dB floor. Adaptive hop caps time bins at ~4000 so long
  tracks stay responsive on redraw; N_FFT=4096 keeps low-freq resolution.
- master_core: load audio at native sample rate (librosa.load sr=None)
  instead of librosa's 22050 Hz default, so the full band up to the
  file's own nyquist (~22 kHz at 44.1 kHz) is analysed. ~2x heavier on
  44.1/48 kHz files, by design.
- metrics: shared _show_axis_extents helper forces each axis's exact
  min/max onto the tick list with compact labels (_fmt_tick), so the
  true range is always readable -- notably the spectrogram's 22 kHz top,
  which otherwise sits unlabelled between log-scale decade ticks. Applied
  to all metric renders.
- Docs: README + CLAUDE updated for the new metric, native-rate loading,
  and axis-readability behaviour.

Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>

2026-06-07 00:06:50 +09:00

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uj-mastering-master

Custom mastering toolkit providing visual metrics for evaluating audio masterings. Developed with Claude Code assistance.

Features

Current

PyQt5 GUI: drag-and-drop or file-dialog ingest of .mp3, .wav, .flac
Switchable metrics via a dropdown, all sharing one analysis cache:
- RMS Power — 10 s rolling window with adaptive colour scale
- Waveform — min/max envelope, fixed ±1.1 scale
- LUFS — BS.1770 short-term (3 s) + integrated + loudness range (LRA)
- Crest Factor — peak-to-RMS spread over time
- PSR — peak-to-short-term-loudness ratio ("is it still breathing?")
- True Peak — 4× oversampled dBTP, catches inter-sample peaks
- Spectrogram — log-frequency STFT power heatmap over time
Always-labelled axis extremes: every plot forces its exact min/max onto the ticks, so you can read the true range even on a log axis (e.g. the spectrogram's 22 kHz top, which otherwise falls between decade ticks)
Native sample rate: audio is loaded without resampling, so the full band (up to the file's own nyquist, e.g. ~22 kHz for 44.1 kHz files) is analysed
BPM detection via librosa
CJK-safe font system with custom fonts loaded from fonts/ (gitignored), system fallbacks, and a live font selector
Background analysis thread so the UI stays responsive; metric switches compute off the GUI thread and cache, so re-selecting a metric is instant
Embedded matplotlib canvas with auto-regenerated plots on font change

Roadmap

See CLAUDE.md for the full development roadmap. Near-term: dynamic range (DR meter), plot-style controls, interactive axis controls.

Quick start

This project uses uv. With uv installed:

uv sync
uv run ujm

uv run ujm is the only supported entry point — it boots the GUI.

Logging flags

uv run ujm --log-level DEBUG       # ERROR | WARN | INFO | DEBUG | TRACE
uv run ujm --log-file               # also write audio_analysis.log

Fonts

Drop .ttf / .otf / .ttc files into fonts/ to get them in the font selector. The directory is gitignored to avoid bundling licensed font data. See CJK_FONTS.md for details.

Dependencies

librosa, numpy, matplotlib, mutagen, pyloudnorm, PyQt5 — all pinned through uv.lock. Python 3.10+.

Architecture

Module	Responsibility
`main.py`	`MainWindow` + the `ujm` entry point
`analysis_results_manager.py`	Background `QThread` worker, result + metric-data cache
`master_core.py`	`AudioFile`: native-rate librosa loading, RMS rolling window, BPM
`metrics.py`	Pluggable `Metric` ABC + registry (RMS, Waveform, LUFS, Crest, PSR, True Peak, Spectrogram)
`audio_visualization_widget.py`	Embedded `FigureCanvasQTAgg` host
`font_manager.py`	Custom + system CJK font discovery, matplotlib/Qt config
`font_control_widget.py`	Font picker + size slider
`plot_control_widget.py`	Metric selector + refresh-plot button
`logger_setup.py`	CLI log-level parsing + custom TRACE level
`setup_fonts.py`	Diagnostic utility (run standalone)

Adding a metric

Subclass Metric in metrics.py, implement compute(audio_file) -> data (the heavy part, runs on the worker thread) and render(data, file_path) -> Figure (cheap, runs on the GUI thread). Register the instance in the METRICS dict at the bottom of the file — it shows up in the dropdown automatically.

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