# uj-mastering-master A custom mastering toolkit that provides metrics to evaluate audio masterings through visual analysis. ## Current implementation ### Core features - **Audio Analysis**: Uses librosa to analyze audio files (MP3/WAV/FLAC support) at native sample rate (no resampling) - **Pluggable Metrics**: Switchable visualizations (RMS Power, Waveform, LUFS, Crest Factor, PSR, True Peak, Spectrogram; DR next) via a `Metric` ABC - **Metadata Extraction**: Reads ID3 tags from MP3 files for better file identification - **Modular GUI Architecture**: Complete PyQt5 interface with drag-and-drop and file dialog support - **Font Management**: CJK-capable, fixed UI font (M PLUS 1 Code @ 10pt) with system fallback - **Threading & Logging**: Robust background processing with detailed logging system ### Technical stack - **Audio Processing**: librosa, numpy - **Visualization**: pyqtgraph — persistent, interactive (mouse zoom/pan, lin/log toggle, multi-dataset overlay). matplotlib remains only for its colormaps (consumed by pyqtgraph) and as a librosa dependency - **GUI Framework**: PyQt5 with modular widget architecture - **Metadata**: mutagen for audio tag reading - **Font Support**: Custom font loading system with CJK fallback ### Key components #### `main.py` - Complete GUI application with modular architecture - Drag-and-drop and file dialog support for audio files - Integrated font control system - Real-time analysis display and file management #### `analysis_results_manager.py` - Background threading for audio analysis (`AudioAnalysisWorker` = load + first metric; `MetricComputeWorker` = one metric on an already-loaded file) - Caches both the loaded `AudioFile` and per-metric `compute()` output, so metric/font switches re-render from cache without reloading librosa - **Prefetch** (`PrefetchWorker`): after a file loads, the remaining metrics are computed in the background (one at a time, cooperatively cancellable) so the first switch to any metric is instant too. Superseded when a new file loads - Timing: workers measure compute time; `metricTiming` + phase/duration progress messages drive the status slip ("X computed in Ys", "Loaded in Ns — computing…") - `shutdown()` stops all threads on window close (`MainWindow.closeEvent`) #### `audio_visualization_widget.py` - Persistent pyqtgraph plot — the PlotItem is reused across renders, never torn down, so mouse zoom/pan and scale toggles survive every redraw - `show_specs([(label, PlotSpec), ...], view)` draws one or more datasets onto the shared axes, assigning a distinct colour per dataset for overlay/compare - Spectrogram log-frequency is realised by resampling STFT rows onto a log grid (`ImageItem` is affine-only and won't follow a log axis) — see `_render_heatmap` #### `plotspec.py` - Backend-agnostic drawing descriptors: `Curve`, `Band`, `HLine`, `Heatmap`, `AxisSpec`, `PlotSpec`, plus the `ViewState` (recompute-free lin/log options) - The seam that decouples metrics from the plotting library: metrics emit *intent*, the renderer owns colour/layout/library specifics #### `font_manager.py` - Auto-detection of custom fonts from `fonts/` directory; CJK fallbacks - `apply_fixed_font(family, size)` locks the Qt app font (used at startup to pin the UI to **M PLUS 1 Code @ 10pt**, falling back to the system default if the family isn't found). There is no runtime font picker — the old `font_control_widget.py` was removed as wasted panel space - pyqtgraph and the Qt widgets both read the app font, so this covers the plot too (M PLUS 1 Code has full Japanese coverage, so titles stay CJK-safe) #### `plot_control_widget.py` - Metric selector dropdown driven by the `metrics.METRICS` registry - Log-frequency toggle and a time-axis mode selector — Absolute (seconds) vs Relative (% of each track's own length) — both view-state, recompute-free - `Refresh Plot` button. Compare/overlay membership is the file-list checkboxes; reference lines have their own cluster #### `ref_line_widget.py` - `RefLineControlWidget`: side-panel list of custom reference lines with Add / Edit… / Remove / Clear; a pure view over the `RefLineProps` list the main window owns, emitting intents - `RefLineDialog`: edits one line's value, colour, line style, and tag - The plot draws each line with a triangle drag-handle; dragging writes the new value back into the shared `RefLineProps` and refreshes the list #### `metrics.py` - Pluggable `Metric` ABC: `compute(audio_file) -> data` (heavy, worker thread, backend-neutral numpy/scalars) and `build_spec(data, view) -> PlotSpec` (cheap, GUI thread, view-aware). Metrics no longer touch the plotting library - Compute-time vs view-time split: scale (lin/log) is a `ViewState` argument to `build_spec`, so toggling it never recomputes - Current registry: - `RMSPowerMetric` — 10 s rolling RMS with adaptive colour scale - `WaveformMetric` — min/max envelope, fixed ±1.1 y-range - `LUFSMetric` — true (ungated) EBU R128 short-term (3 s) via a single K-weighting pass (`_kweight`, cached) + a vectorised sliding mean-square. Integrated (`_integrated_lufs`) and LRA (`_loudness_range`) are reimplemented from the same cached K-weighted signal — validated **bit-equal** to pyloudnorm — so nothing re-filters the signal. ~3.8 s → ~0.6 s. pyloudnorm is now used only to source the BS.1770 filter coefficients - `CrestFactorMetric` — 20·log10(peak/RMS) per 1 s window; peaks via O(N) running max - `PSRMetric` — sample-peak minus short-term LUFS (3 s window); reuses `LUFSMetric`'s short-term series (memoised on the `AudioFile`), so PSR is near-free once LUFS is computed - `TruePeakMetric` — 4× oversampled dBTP; the whole signal is oversampled once (`scipy.signal.resample_poly`) then an O(N) running max over windows - `SpectrogramMetric` — log-frequency STFT heatmap; adaptive hop caps time bins at ~4000, `N_FFT=4096`. Log/linear frequency is a view toggle - Drop in new ones (DR, spectral balance) by appending an instance to `METRICS`; return a `PlotSpec` from `build_spec` (curves overlay automatically; heatmaps show one dataset at a time) - Note: the old matplotlib `_show_axis_extents` exact-endpoint tick labelling is gone with the matplotlib render path. If wanted back, it belongs in the renderer, applied uniformly to every metric — not per-metric #### `master_core.py` - Defines the `AudioFile` class: librosa loading, rolling RMS power. BPM detection was **removed** — `librosa.beat.beat_track` cost ~3.7 s on every load for a number no better than tapping by hand - Loads at **native sample rate** (`librosa.load(..., sr=None)`) so the full band is preserved — analysis runs ~2× heavier on 44.1/48 kHz files than the old 22050 Hz default, by design - No batch / CLI mode — all analysis is driven from `main.py` via `AnalysisResultsManager` ### Current analysis features - **Native-rate loading**: full-band analysis up to the file's own nyquist - **RMS power analysis**: 10-second rolling window with 2-second hops - **Adaptive colour mapping**: Automatically adjusts scale based on detected headroom - High dynamic range: 0-0.6 scale for loud masters - Conservative mastering: 0-0.3 scale for quiet masters - **Loudness metrics**: LUFS (ungated short-term + gated integrated + LRA), PSR, Crest Factor - **Peak analysis**: True Peak (4× oversampled dBTP) - **Spectral view**: log-frequency spectrogram heatmap over time - **Metadata display**: Artist and title from audio tags - **Real-time visualization**: Embedded matplotlib plots with font-aware rendering ### GUI features - **File management**: Drag-and-drop and file dialog for audio selection - **Compare/overlay**: each analysed file has a checkbox; the ticked set is overlaid on one graph for the current metric (curve metrics overlay; the spectrogram shows one track at a time). Highlighting a row drives the metadata panel, independent of the overlay set - **Interactive plot**: mouse drag-zoom, scroll-wheel zoom, pan, right-click menu (pyqtgraph ViewBox); log/linear frequency toggle. Scroll zooms both axes; **Ctrl+scroll** zooms time only, **Shift+scroll** zooms the value axis only (`_AxisZoomViewBox`); scrolling over an axis also zooms just that axis - **Time-axis mode**: a Relative-time toggle — off = seconds, on = 0-100% of each track's own length, so tracks of very different durations line up by position - **Custom reference lines**: side-panel list (Add/Edit/Remove/Clear) of draggable horizontal markers with value/colour/style/tag; dragged via a triangle handle. Kept **per metric** (so switching metrics doesn't lose them) and expressed in the metric's own units — on the spectrogram they read and edit in **Hz** (the renderer converts Hz<->row index, since the heatmap y-axis is a row index) - **Plot control**: Metric selector + log-frequency toggle + relative-time toggle + refresh-plot button - **Analysis display**: Real-time visualization with metadata panels - **Modular architecture**: Self-contained widgets for easy layout management ## Future development plans ### Short-term (urgent) 1. **Plot control widget cluster** *(metric selector + Refresh Plot done; still TODO)* - Plot style controller (colormap, line vs bar, etc.) - Foundation for mastering comparison features ### Short-term (not urgent) 1. **Enhanced metrics** *(plug new ones into `metrics.METRICS`)* - Dynamic range measurement (DR meter) - Long-term average spectrum (LTAS) / tonal-balance curve - Stereo metrics (correlation, mid/side) — needs `AudioFile` to retain stereo 2. **Interactive plot features** *(zoom/pan, axis-range select, lin/log done via pyqtgraph)* - GUI-controllable plotting styles (colormap, visualization type) - Export analysis results to CSV/JSON 3. **Advanced GUI controls** - Plot style customization interface - Real-time axis range selection (zooming in/out) - Interactive plot manipulation tools 4. **Better looking UI** - Graphical loading bar - Graphical logging text box ### Mid-to-long-term (very not urgent) 1. **Audio comparison system** *(multi-file overlay done via file-list checkboxes; each song has a stable palette colour keyed to its list row)* - Per-song colour picker: clickable swatch in the file list (overlay already accepts a caller-supplied colour per dataset via `show_specs`, so this is a UI + override-map addition, not a render change) - Reference vs. comparee designation (vs. flat overlay) - Side-by-side track comparison interface (incl. spectrogram, which can't overlay) - A/B testing for mastering versions 2. **Distribution & deployment** - Self-contained executable releases - Cross-platform packaging - Installer creation and distribution ### Future vision 1. **Advanced analysis tools** - Spectral centroid and bandwidth analysis - Stereo width measurements - Transient detection and analysis - Harmonic distortion detection 2. **Professional features** - EBU R128 compliance checking - Custom target curves - Professional reporting formats - Multi-format export capabilities 3. **VST plugin development** - Real-time analysis during mixing/mastering - Integration with DAWs - Live feedback during production ## Development notes ### Dependencies - librosa: Audio analysis and feature extraction - numpy: Numerical computations - scipy: Signal processing (true-peak polyphase oversampling, K-weighting filters, spectrogram log-frequency resample, O(N) running-max via ndimage) - pyloudnorm: source of the BS.1770 K-weighting filter coefficients (the LUFS short-term / integrated / LRA math is now computed directly, validated against it) - pyqtgraph: Interactive plotting (zoom/pan, overlay, lin/log) - matplotlib: Colormaps only (consumed by pyqtgraph) + librosa dependency - mutagen: Audio metadata extraction - PyQt5: GUI framework ### Architecture considerations - Three-stage split: `metrics.compute` (heavy, worker thread, backend-neutral data) → `metrics.build_spec` (cheap, GUI thread, view-aware `PlotSpec`) → `AudioVisualizationWidget.show_specs` (pyqtgraph rendering, overlay, colours) - File path handling needs improvement for cross-platform compatibility - Error handling should be enhanced for production use - Consider moving from PyQt5 to PyQt6 or PySide for better licensing ### Testing requirements - Unit tests for audio analysis functions - GUI component testing - File format compatibility testing - Performance testing with large audio files ## Usage ### Running the app ```bash uv sync # one-time, after cloning uv run ujm # launch the GUI ``` Optional flags (handled by `logger_setup.parse_log_args`): ```bash uv run ujm --log-level DEBUG # ERROR | WARN | INFO | DEBUG | TRACE uv run ujm --log-file # also write audio_analysis.log ``` The only entry point is `ujm` (defined in `pyproject.toml` as `ujm = "main:main"`). The previous `files.txt` batch mode and the `python master_core.py` workflow have been removed. ### Planned usage enhancements 1. Interactive plot manipulation and style customization 2. Audio file comparison features (reference vs. comparee) 3. Self-contained executable releases