Module generic_traits 

Generic traits and type parameters for spatial algorithms

This module provides generic traits that enable spatial algorithms to work with different numeric types and array structures. This improves API flexibility and allows for better integration with the broader Rust ecosystem.

Features

• Generic numeric types: Support for f32, f64, and other numeric types
• Array ecosystem integration: Work with ndarray, nalgebra, and other array types
• Iterator support: Process data from various sources efficiently
• Dimension awareness: Compile-time and runtime dimension checking
• Memory efficiency: Zero-copy operations where possible

Examples

use scirs2_spatial::generic_traits::{SpatialScalar};
use scirs2_core::ndarray::array;

// Generic distance calculation (simplified example)
fn calculate_distance<T>(p1: &[T], p2: &[T]) -> T
where
    T: SpatialScalar,
{
    // Generic implementation (simplified)
    T::zero()
}

// Works with different array types
let point1 = array![1.0f32, 2.0f32, 3.0f32];
let point2 = array![4.0f32, 5.0f32, 6.0f32];
let _result = calculate_distance(point1.as_slice().unwrap(), point2.as_slice().unwrap());

Modules

ndarray_integration

Integration with ndarray

utils

Utility functions for generic spatial operations

Structs

ChebyshevMetric

Chebyshev distance metric

EuclideanMetric

Euclidean distance metric

ManhattanMetric

Manhattan distance metric

Point

Generic point structure for spatial algorithms

Traits

DistanceMetric

Trait for distance metrics

SpatialArray

Trait for collections of spatial points

SpatialPoint

Trait for types that can represent a point in space

SpatialScalar

Trait for scalar types that can be used in spatial computations