libspot 3.1.0

Rust FFI bindings for libspot, a fast time series anomaly detector
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# libspot

[![Crates.io](https://img.shields.io/crates/v/libspot.svg)](https://crates.io/crates/libspot)
[![Documentation](https://docs.rs/libspot/badge.svg)](https://docs.rs/libspot)
[![License: LGPL v3](https://img.shields.io/badge/License-LGPL%20v3-blue.svg)](https://www.gnu.org/licenses/lgpl-3.0)

A safe Rust wrapper (using FFI) for the [libspot](https://github.com/asiffer/libspot) time series anomaly detection library.

## 3.1.0

Bundles [libspot C 3.1.0](https://github.com/asiffer/libspot/releases/tag/v3.1.0),
including the P² extrema marker update fix and quantile input validation fixes.
The Rust API is unchanged. Refitting models can produce different thresholds
and classifications than 3.0.0, especially with monotonic training data.
Training data containing NaN is now consistently rejected with
`SpotError::ExcessThresholdIsNaN`.

```toml
[dependencies]
libspot = "3.1.0"
```

## Quick Start

```rust
use libspot::{SpotDetector, SpotConfig, SpotStatus};

fn main() -> Result<(), Box<dyn std::error::Error>> {
    // Create detector with default configuration
    let config = SpotConfig::default();
    let mut detector = SpotDetector::new(config)?;

    // Fit with training data
    let training_data: Vec<f64> = (0..1000)
        .map(|i| 5.0 + (i as f64 * 0.01).sin() * 2.0)
        .collect();
    detector.fit(&training_data)?;

    // Detect anomalies in real-time
    let test_value = 50.0; // This should be an anomaly
    match detector.step(test_value)? {
        SpotStatus::Normal => println!("Normal data point"),
        SpotStatus::Excess => println!("In the tail distribution"),
        SpotStatus::Anomaly => println!("Anomaly detected! 🚨"),
    }

    Ok(())
}
```


## Alternative

For a pure Rust implementation without FFI dependencies, see the [`libspot-rs`](https://crates.io/crates/libspot-rs) crate.

## License

This project is licensed under the **GNU Lesser General Public License v3.0 (LGPL-3.0)**.