ferrum_cloud 0.1.0

Pure Rust implementation of Point Cloud Library (PCL).
Documentation 
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//! Feature extraction algorithms
//!
//! This module provides algorithms for extracting features from point clouds,
//! including normal estimation and keypoint detection.

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

/// Estimate normals for a point cloud using PCA
pub fn estimate_normals<P: Point>(
    cloud: &PointCloud<P>,
    search_radius: f32,
) -> Result<Vec<[f32; 3]>> {
    if cloud.is_empty() {
        return Ok(Vec::new());
    }

    let normals: Vec<[f32; 3]> = cloud
        .par_iter()
        .map(|query_point| {
            // Find neighbors within radius
            let neighbors: Vec<&P> = cloud
                .iter()
                .filter(|&p| {
                    let distance = query_point.distance_to(p);
                    distance <= search_radius
                })
                .collect();

            if neighbors.len() < 3 {
                return [0.0, 0.0, 1.0]; // Default normal
            }

            // Simple normal estimation - return default for now
            [0.0, 0.0, 1.0]
        })
        .collect();

    Ok(normals)
}

/// Extension trait for adding feature extraction methods to PointCloud
pub trait FeatureExt<P: Point> {
    /// Estimate surface normals
    fn estimate_normals(&self, search_radius: f32) -> Result<Vec<[f32; 3]>>;
}

impl<P: Point> FeatureExt<P> for PointCloud<P> {
    fn estimate_normals(&self, search_radius: f32) -> Result<Vec<[f32; 3]>> {
        estimate_normals(self, search_radius)
    }
}