avila-clustering 0.1.0

//! Clustering in curved spacetime manifolds

use crate::metrics::distance::Manifold;
use crate::{ClusteringError, Result};
use ndarray::{Array1, ArrayView2};

/// DBSCAN adapted for curved spacetime
pub struct ManifoldDBSCAN {
    epsilon: f64,
    min_samples: usize,
    manifold: Manifold,
}

impl ManifoldDBSCAN {
    pub fn new(epsilon: f64, min_samples: usize) -> Self {
        Self {
            epsilon,
            min_samples,
            manifold: Manifold::Euclidean,
        }
    }

    pub fn manifold(mut self, manifold: Manifold) -> Self {
        self.manifold = manifold;
        self
    }

    pub fn fit(&self, data: &ArrayView2<f64>) -> Result<Array1<i32>> {
        // TODO: Implement DBSCAN using geodesic distances
        // 1. Compute geodesic distances on manifold
        // 2. Apply DBSCAN algorithm with geodesic metric
        // 3. Account for spacetime curvature effects
        unimplemented!("ManifoldDBSCAN::fit")
    }
}

/// KMeans adapted for curved manifolds
pub struct ManifoldKMeans {
    n_clusters: usize,
    manifold: Manifold,
}

impl ManifoldKMeans {
    pub fn new(n_clusters: usize, manifold: Manifold) -> Self {
        Self {
            n_clusters,
            manifold,
        }
    }

    pub fn fit(&self, data: &ArrayView2<f64>) -> Result<ManifoldClusteringResult> {
        // TODO: Implement KMeans on manifold
        // 1. Initialize centroids on manifold
        // 2. Assign points using geodesic distance
        // 3. Update centroids using Riemannian center of mass
        unimplemented!("ManifoldKMeans::fit")
    }
}

pub struct ManifoldClusteringResult {
    pub labels: Array1<usize>,
    pub centroids: Vec<Vec<f64>>,
}

/// Compute Riemannian center of mass (Fréchet mean) on a manifold
pub fn frechet_mean(
    points: &[Vec<f64>],
    manifold: &Manifold,
    max_iter: usize,
    tolerance: f64,
) -> Result<Vec<f64>> {
    // TODO: Implement Fréchet mean computation
    // Iteratively find point that minimizes sum of squared geodesic distances
    unimplemented!("frechet_mean")
}