{"id":30957154,"url":"https://github.com/cbueth/infomeasure-rs","last_synced_at":"2025-09-11T13:16:47.862Z","repository":{"id":304690036,"uuid":"1018947713","full_name":"cbueth/infomeasure-rs","owner":"cbueth","description":"Rust library for calculating various information-theoretic measures, including entropy, mutual information, transfer entropy, and more, with support for both discrete and continuous variables. 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This project is a Rust implementation of the [infomeasure](https://github.com/cbueth/infomeasure), designed to provide superior performance while maintaining API compatibility.\n\n\u003e [!IMPORTANT]  \n\u003e This crate is under development, features will be added step by step.\n\n## Features\n\n- **Multiple Estimation Techniques**: Supports discrete and kernel-based approaches\n- **Future**: all features from the parent pacakge, see [infomeasure introduction](https://infomeasure.readthedocs.io/en/latest/guide/introduction/)\n- **High Performance**: Leverages Rust's zero-cost abstractions for efficient computation\n- **Python Compatibility**: Designed to potentially serve as a backend for the Python package\n- **Modular Design**: Easily extensible architecture for adding new estimators and methods\n\n\n## Installation\n\n\u003e [!NOTE]\n\u003e As of now infomeasure is not on crates.io, yet.\n\nAdd this to your `Cargo.toml`:\n\n```toml\n[dependencies]\ninfomeasure = \"0.1.0\"\n```\n\n## Usage Examples\n\n### Calculating Entropy with Gaussian Kernel\n\n```rust\nuse infomeasure::estimators::entropy::Entropy;\nuse ndarray::Array2;\n\nfn main() {\n    // Create or load your data\n    let data = Array2::from_shape_vec((1000, 2), vec![/* your data */]).unwrap();\n\n    // Calculate entropy with Gaussian kernel\n    let bandwidth = 0.5;\n    let entropy = Entropy::nd_kernel_with_type::\u003c2\u003e(\n        data.clone(),\n        \"gaussian\".to_string(),\n        bandwidth\n    ).global_value();\n\n    println!(\"Entropy: {}\", entropy);\n}\n```\n\n## Repository Structure\n\n- `src/` - Main source code\n  - `estimators/` - Estimation techniques implementations\n    - `approaches/` - Specific implementations (discrete, kernel, ...)\n    - `traits/` - Shared interfaces for estimators\n- `benches/` - Performance benchmarks using Criterion\n- `tests/` - Unit and integration tests\n- `examples/` - Example usage and demonstrations\n\n## Testing and Validation\n\nThe project includes a validation crate that compares results with the Python implementation to ensure compatibility and correctness. Run tests with:\n\n```bash\ncargo test\n```\n\n## Benchmarks\n\nPerformance benchmarks are available for different estimation methods:\n\n```bash\ncargo bench\n```\n\n## Contributing\n\nContributions are welcome! Please feel free to submit a Pull Request.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fcbueth%2Finfomeasure-rs","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fcbueth%2Finfomeasure-rs","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fcbueth%2Finfomeasure-rs/lists"}