Updating CLAUDE settings to match initial rules
This commit is contained in:
Mikkeli Matlock
@@ -2,9 +2,9 @@
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A custom mastering toolkit that provides metrics to evaluate audio masterings through visual analysis.
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## Current Implementation
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## Current implementation
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### Core Features
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### Core features
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- **Audio Analysis**: Uses librosa to analyze audio files (MP3/WAV/FLAC support)
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- **Power Visualization**: Generates colorized power magnitude graphs over time
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- **Metadata Extraction**: Reads ID3 tags from MP3 files for better file identification
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@@ -12,14 +12,14 @@ A custom mastering toolkit that provides metrics to evaluate audio masterings th
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- **Font Management**: Comprehensive CJK-compatible font system with user-provided font support
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- **Threading & Logging**: Robust background processing with detailed logging system
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### Technical Stack
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### Technical stack
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- **Audio Processing**: librosa, numpy
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- **Visualization**: matplotlib with custom colormaps and embedded Qt widgets
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- **GUI Framework**: PyQt5 with modular widget architecture
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- **Metadata**: mutagen for audio tag reading
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- **Font Support**: Custom font loading system with CJK fallback
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### Key Components
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### Key components
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#### `main.py`
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- Complete GUI application with modular architecture
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@@ -47,79 +47,83 @@ A custom mastering toolkit that provides metrics to evaluate audio masterings th
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- `AudioFile` class with comprehensive metrics extraction
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- RMS power analysis and BPM detection
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### Current Analysis Features
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- **RMS Power Analysis**: 10-second rolling window with 2-second hops
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- **Adaptive Color Mapping**: Automatically adjusts scale based on detected headroom
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### Current analysis features
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- **RMS power analysis**: 10-second rolling window with 2-second hops
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- **Adaptive colour mapping**: Automatically adjusts scale based on detected headroom
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- High dynamic range: 0-0.6 scale for loud masters
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- Conservative mastering: 0-0.3 scale for quiet masters
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- **BPM Detection**: Automatic tempo analysis
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- **Metadata Display**: Artist and title from audio tags
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- **Real-time Visualization**: Embedded matplotlib plots with font-aware rendering
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- **BPM detection**: Automatic tempo analysis
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- **Metadata display**: Artist and title from audio tags
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- **Real-time visualization**: Embedded matplotlib plots with font-aware rendering
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### GUI Features
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- **File Management**: Drag-and-drop and file dialog for audio selection
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- **Font Control**: Unified font selector with size control and plot regeneration
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- **Analysis Display**: Real-time visualization with metadata panels
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- **Modular Architecture**: Self-contained widgets for easy layout management
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### GUI features
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- **File management**: Drag-and-drop and file dialog for audio selection
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- **Font control**: Unified font selector with size control and plot regeneration
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- **Analysis display**: Real-time visualization with metadata panels
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- **Modular architecture**: Self-contained widgets for easy layout management
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## Future Development Plans
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## Future development plans
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### Short-term (Urgent)
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1. **Plot Control Widget Cluster**
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### Short-term (urgent)
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1. **Plot control widget cluster**
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- Move 'Refresh Plot' into dedicated plot/graph widget cluster
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- Add metric selection widget (choose which analysis to display)
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- Implement plot style controller (colormap, line vs bar, etc.)
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- Prepare foundation for mastering comparison features
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### Short-term (Not Urgent)
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1. **Enhanced Metrics**
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### Short-term (not urgent)
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1. **Enhanced metrics**
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- LUFS loudness measurement implementation
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- Dynamic range measurement (DR meter)
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- Peak-to-average ratio analysis
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- Frequency spectrum analysis
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2. **Interactive Plot Features**
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2. **Interactive plot features**
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- GUI-controllable plotting styles (colormap, visualization type)
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- Select axis ranges on the fly with automatic graph updates
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- Zoom/pan controls for detailed analysis
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- Export analysis results to CSV/JSON
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3. **Advanced GUI Controls**
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3. **Advanced GUI controls**
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- Plot style customization interface
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- Real-time axis range selection
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- Real-time axis range selection (zooming in/out)
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- Interactive plot manipulation tools
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### Mid-Long term (Not Urgent)
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1. **Audio Comparison System**
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4. **Better looking UI**
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- Graphical loading bar
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- Graphical logging text box
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### Mid-to-long-term (very not urgent)
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1. **Audio comparison system**
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- Reference vs. comparee audio file analysis
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- Side-by-side track comparison interface
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- A/B testing for mastering versions
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- Overlay visualization for comparative analysis
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2. **Distribution & Deployment**
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2. **Distribution & deployment**
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- Self-contained executable releases
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- Cross-platform packaging
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- Installer creation and distribution
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### Future Vision
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1. **Advanced Analysis Tools**
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### Future vision
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1. **Advanced analysis tools**
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- Spectral centroid and bandwidth analysis
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- Stereo width measurements
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- Transient detection and analysis
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- Harmonic distortion detection
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2. **Professional Features**
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2. **Professional features**
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- EBU R128 compliance checking
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- Custom target curves
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- Professional reporting formats
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- Multi-format export capabilities
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3. **VST Plugin Development**
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3. **VST plugin development**
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- Real-time analysis during mixing/mastering
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- Integration with DAWs
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- Live feedback during production
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## Development Notes
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## Development notes
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### Dependencies
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- librosa: Audio analysis and feature extraction
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@@ -128,13 +132,13 @@ A custom mastering toolkit that provides metrics to evaluate audio masterings th
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- mutagen: Audio metadata extraction
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- PyQt5: GUI framework
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### Architecture Considerations
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### Architecture considerations
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- Current code mixes analysis and visualization - consider separation
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- File path handling needs improvement for cross-platform compatibility
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- Error handling should be enhanced for production use
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- Consider moving from PyQt5 to PyQt6 or PySide for better licensing
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### Testing Requirements
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### Testing requirements
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- Unit tests for audio analysis functions
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- GUI component testing
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- File format compatibility testing
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@@ -142,18 +146,18 @@ A custom mastering toolkit that provides metrics to evaluate audio masterings th
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## Usage
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### Current Usage
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### Current usage
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1. Run `python main.py` to launch the GUI application
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2. Use "Open Audio File..." button or drag-and-drop audio files for analysis
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3. Adjust font settings using the Font Settings panel
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4. View real-time analysis results with embedded matplotlib plots
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5. Select different analyzed files from the file list to compare results
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### Legacy Usage (Batch Mode)
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### Legacy usage (batch Mode)
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1. Add audio file paths to `files.txt`
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2. Run `python master_core.py` for batch analysis
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### Planned Usage Enhancements
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### Planned usage enhancements
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1. Interactive plot manipulation and style customization
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2. LUFS and advanced metric analysis
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3. Audio file comparison features
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