ferrum_cloud 0.1.0

//! Point cloud registration algorithms
//!
//! This module provides algorithms for aligning point clouds,
//! including ICP (Iterative Closest Point) and other registration methods.

use crate::core::{Point, PointCloud};
use crate::error::{CloudError, Result};

/// Transformation matrix (4x4 homogeneous transformation)
pub type Transform = [[f32; 4]; 4];

/// Identity transformation matrix
pub const IDENTITY_TRANSFORM: Transform = [
    [1.0, 0.0, 0.0, 0.0],
    [0.0, 1.0, 0.0, 0.0],
    [0.0, 0.0, 1.0, 0.0],
    [0.0, 0.0, 0.0, 1.0],
];

/// ICP (Iterative Closest Point) registration
///
/// This is a placeholder implementation. A full ICP would require:
/// - Nearest neighbor search (KD-tree)
/// - Correspondence estimation
/// - Transformation estimation (SVD)
/// - Iterative refinement
pub fn icp_registration<P: Point>(
    _source: &PointCloud<P>,
    _target: &PointCloud<P>,
    _max_iterations: usize,
    _tolerance: f32,
) -> Result<Transform> {
    // TODO: Implement full ICP algorithm
    // For now, return identity transformation
    Ok(IDENTITY_TRANSFORM)
}

/// Apply transformation to a point cloud
pub fn transform_point_cloud<P: Point>(
    cloud: PointCloud<P>,
    transform: &Transform,
) -> PointCloud<P> {
    cloud.map(|point| {
        let pos = point.position();
        let transformed_pos = apply_transform(pos, transform);
        // Note: This is simplified - we'd need a way to create a new point
        // with the transformed position. For now, return the original point.
        point
    })
}

/// Apply transformation matrix to a 3D point
fn apply_transform(point: [f32; 3], transform: &Transform) -> [f32; 3] {
    let x = transform[0][0] * point[0]
        + transform[0][1] * point[1]
        + transform[0][2] * point[2]
        + transform[0][3];
    let y = transform[1][0] * point[0]
        + transform[1][1] * point[1]
        + transform[1][2] * point[2]
        + transform[1][3];
    let z = transform[2][0] * point[0]
        + transform[2][1] * point[1]
        + transform[2][2] * point[2]
        + transform[2][3];
    [x, y, z]
}

/// Extension trait for adding registration methods to PointCloud
pub trait RegistrationExt<P: Point> {
    /// Perform ICP registration with another point cloud
    fn icp_register(
        &self,
        target: &PointCloud<P>,
        max_iterations: usize,
        tolerance: f32,
    ) -> Result<Transform>;

    /// Apply transformation to the point cloud
    fn transform(self, transform: &Transform) -> PointCloud<P>;
}

impl<P: Point> RegistrationExt<P> for PointCloud<P> {
    fn icp_register(
        &self,
        target: &PointCloud<P>,
        max_iterations: usize,
        tolerance: f32,
    ) -> Result<Transform> {
        icp_registration(self, target, max_iterations, tolerance)
    }

    fn transform(self, transform: &Transform) -> PointCloud<P> {
        transform_point_cloud(self, transform)
    }
}

#[cfg(test)]
mod tests {
    use super::*;
    use crate::core::PointXYZ;

    #[test]
    fn test_identity_transform() {
        let points = vec![PointXYZ::new(1.0, 2.0, 3.0)];
        let cloud = PointCloud::from_points(points);

        let transformed = cloud.transform(&IDENTITY_TRANSFORM);
        assert_eq!(transformed.len(), 1);
    }

    #[test]
    fn test_icp_placeholder() {
        let source_points = vec![PointXYZ::new(0.0, 0.0, 0.0)];
        let target_points = vec![PointXYZ::new(1.0, 0.0, 0.0)];

        let source = PointCloud::from_points(source_points);
        let target = PointCloud::from_points(target_points);

        let transform = source.icp_register(&target, 10, 1e-6).unwrap();
        // Should return identity for now
        assert_eq!(transform, IDENTITY_TRANSFORM);
    }
}