Metadata-Version: 2.4
Name: flareverb
Version: 0.0.4
Summary: An Open-Source Library for RIR Synthesis and Analysis in PyTorch based on FLAMO
Project-URL: Homepage, https://github.com/gdalsanto/flare
Project-URL: Issues, https://github.com/gdalsanto/flare/issues
Author-email: Gloria Dal Santo <gloria.dalsanto@aalto.fi>
Maintainer-email: Gloria Dal Santo <gloria.dalsanto@aalto.fi>
License: MIT License
        
        Copyright (c) 2025 Gloria Dal Santo
        
        Permission is hereby granted, free of charge, to any person obtaining a copy
        of this software and associated documentation files (the "Software"), to deal
        in the Software without restriction, including without limitation the rights
        to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
        copies of the Software, and to permit persons to whom the Software is
        furnished to do so, subject to the following conditions:
        
        The above copyright notice and this permission notice shall be included in all
        copies or substantial portions of the Software.
        
        THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
        IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
        FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
        AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
        LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
        OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
        SOFTWARE.
License-File: LICENSE
Keywords: audio signal processing,data augmentation,data generation,reverb
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3
Requires-Python: >=3.10
Requires-Dist: flamo==0.2.6
Requires-Dist: pandas
Requires-Dist: pydantic
Requires-Dist: pyyaml
Description-Content-Type: text/markdown

# FLARE
[LBDP](https://github.com/gdalsanto/flare/blob/main/AES_AIMLA_abstract.pdf) | [poster](https://github.com/gdalsanto/flare/blob/main/AES_AIMLA_poster.pdf)  

An Open-Source Library for Room Impulse Response Synthesis and Analysis in PyTorch based on [FLAMO](https://github.com/gdalsanto/flamo).  

This library will be presented at the AES Conference on Artificial Intelligence and Machine Learning for Audio (AIMLA), Queen Mary University, London (UK), 8-10 September 2025

More information soon! 
## Installation

```bash
pip install flareverb
```

## Project Structure

```
src/flareverb/
├── reverb.py            # Core FDN implementations
├── generate.py          # RIR generation utilities
├── sampling.py          # Delays, gains, and filters sampling
├── analysis.py          # Acoustic analysis functions
├── utils.py             # Utility functions
├── config/              # Configuration modules
└── data/                # Data folder (contains absorption coefficients)

```

## Configuration

FLARE uses Pydantic models for configuration management. The main configuration classes are:

### FDNConfig
Core FDN configuration parameters:
- `N`: Number of delay lines (default: 6)
- `fs`: Sampling frequency in Hz (default: 48000)
- `in_ch` / `out_ch`: Input/output channels (default: 1)
- `delay_range_ms`: Delay lengths range in milliseconds (default: [20.0, 50.0])
- `delay_log_spacing`: Use logarithmic spacing for delays (default: False)
- `early_reflections_type`: Type of early reflections - 'gain', 'FIR', or None (default: None)
- `drr`: Direct-to-reverberant ratio (default: 0.25, auto-set to 0 if early_reflections_type is None)
- `gain_init`: Gain initialization - 'randn' or 'uniform' (default: 'randn')

### FDNAttenuation
Attenuation filter configuration:
- `attenuation_type`: Filter type - 'homogeneous', 'geq', or 'first_order_lp' (default: 'homogeneous')
- `attenuation_range`: RT range in seconds when attenuation_param not given (default: [0.5, 3.5])
- `t60_center_freq`: Center frequencies for T60 (default: [63, 125, 250, 500, 1000, 2000, 4000, 8000])
- `rt_nyquist`: RT at Nyquist frequency for first-order filters (default: 0.2)

### FDNMixing
Mixing matrix configuration:
- `mixing_type`: Matrix type - 'orthogonal', 'householder', 'hadamard', or 'rotation' (default: 'orthogonal')
- `is_scattering`: Use scattering matrix (default: False)
- `is_velvet_noise`: Use velvet noise (default: False)
- `n_stages`: Number of scattering stages (default: 3)

### GFDNConfig
Grouped FDN configuration (inherits from FDNConfig):
- `n_groups`: Number of groups (default: 2)
- `coupling_angles`: Inter-group coupling angles (default: [0.0])
- `mixing_angles`: Intra-group mixing angles (default: [0.0, 0.0])

## Requirements

- Python >= 3.10
- PyTorch
- FLAMO >= 0.1.13
- pydantic
- pyyaml
- pandas

## License

This project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details.

## Contributing

Contributions are welcome! Please feel free to submit issues and pull requests.

## Links

- [Issues](https://github.com/gdalsanto/flare/issues)
