Crate scirs2_spatial 

SciRS2 Spatial - Spatial Algorithms and Data Structures

scirs2-spatial provides comprehensive spatial algorithms modeled after SciPy’s spatial module, offering distance metrics, KD-trees, ball trees, Delaunay triangulation, convex hulls, Voronoi diagrams, and path planning with SIMD acceleration and parallel processing.

🎯 Key Features

• SciPy Compatibility: Drop-in replacement for scipy.spatial functions
• Distance Metrics: 20+ metrics (Euclidean, Manhattan, Minkowski, cosine, etc.)
• Spatial Trees: KD-tree and ball tree for efficient nearest neighbor queries
• Computational Geometry: Delaunay triangulation, Voronoi diagrams, convex hulls
• Set Distances: Hausdorff, Wasserstein (Earth Mover’s Distance)
• Path Planning: A*, RRT, visibility graphs for robotics/navigation
• Performance: SIMD-accelerated distance computations, parallel queries

📦 Module Overview

SciRS2 Module	SciPy Equivalent	Description
distance	scipy.spatial.distance	Distance metrics and matrices
KDTree	scipy.spatial.KDTree	K-dimensional tree for nearest neighbors
cKDTree	scipy.spatial.cKDTree	Optimized KD-tree (C-accelerated)
ConvexHull	scipy.spatial.ConvexHull	Convex hull computation
Delaunay	scipy.spatial.Delaunay	Delaunay triangulation
Voronoi	scipy.spatial.Voronoi	Voronoi diagram
transform	scipy.spatial.transform	Rotation and transformation utilities

🚀 Quick Start

[dependencies]
scirs2-spatial = "0.1.0-rc.2"

use scirs2_spatial::{KDTree, distance};
use scirs2_core::ndarray::array;

// KD-Tree for nearest neighbor search
let points = array![[0.0, 0.0], [1.0, 0.0], [0.0, 1.0], [1.0, 1.0]];
let tree = KDTree::new(&points).unwrap();
let (indices, dists) = tree.query(&[0.5, 0.5], 2).unwrap();

// Distance computation
let d = distance::euclidean(&[1.0, 2.0], &[4.0, 6.0]);

🔒 Version: 0.1.0-rc.2 (October 03, 2025)

Re-exports

pub use error::SpatialError;

pub use error::SpatialResult;

pub use distance::braycurtis;

pub use distance::canberra;

pub use distance::cdist;

pub use distance::chebyshev;

pub use distance::correlation;

pub use distance::cosine;

pub use distance::dice;

pub use distance::euclidean;

pub use distance::is_valid_condensed_distance_matrix;

pub use distance::jaccard;

pub use distance::kulsinski;

pub use distance::mahalanobis;

pub use distance::manhattan;

pub use distance::minkowski;

pub use distance::pdist;

pub use distance::rogerstanimoto;

pub use distance::russellrao;

pub use distance::seuclidean;

pub use distance::sokalmichener;

pub use distance::sokalsneath;

pub use distance::sqeuclidean;

pub use distance::squareform;

pub use distance::squareform_to_condensed;

pub use distance::yule;

pub use distance::ChebyshevDistance;

pub use distance::Distance;

pub use distance::EuclideanDistance;

pub use distance::ManhattanDistance;

pub use distance::MinkowskiDistance;

pub use kdtree::KDTree;

pub use kdtree::Rectangle;

pub use kdtree_optimized::KDTreeOptimized;

pub use kdtree_advanced::AdvancedKDTree;

pub use kdtree_advanced::BoundingBox as KDTreeBoundingBox;

pub use kdtree_advanced::KDTreeConfig;

pub use kdtree_advanced::TreeStatistics;

pub use balltree::BallTree;

pub use delaunay::Delaunay;

pub use voronoi::voronoi;

pub use voronoi::Voronoi;

pub use spherical_voronoi::SphericalVoronoi;

pub use procrustes::procrustes;

pub use procrustes::procrustes_extended;

pub use procrustes::ProcrustesParams;

pub use convex_hull::convex_hull;

pub use convex_hull::ConvexHull;

pub use alphashapes::AlphaShape;

pub use halfspace::Halfspace;

pub use halfspace::HalfspaceIntersection;

pub use boolean_ops::compute_polygon_area;

pub use boolean_ops::is_convex_polygon;

pub use boolean_ops::is_self_intersecting;

pub use boolean_ops::polygon_difference;

pub use boolean_ops::polygon_intersection;

pub use boolean_ops::polygon_symmetric_difference;

pub use boolean_ops::polygon_union;

pub use kriging::KrigingPrediction;

pub use kriging::OrdinaryKriging;

pub use kriging::SimpleKriging;

pub use kriging::VariogramModel;

pub use geospatial::cross_track_distance;

pub use geospatial::destination_point;

pub use geospatial::final_bearing;

pub use geospatial::geographic_to_utm;

pub use geospatial::geographic_to_web_mercator;

pub use geospatial::haversine_distance;

pub use geospatial::initial_bearing;

pub use geospatial::midpoint;

pub use geospatial::normalize_bearing;

pub use geospatial::point_in_spherical_polygon;

pub use geospatial::spherical_polygon_area;

pub use geospatial::vincenty_distance;

pub use geospatial::web_mercator_to_geographic;

pub use geospatial::EARTH_RADIUS_KM;

pub use geospatial::EARTH_RADIUS_M;

pub use set_distance::directed_hausdorff;

pub use set_distance::gromov_hausdorff_distance;

pub use set_distance::hausdorff_distance;

pub use set_distance::wasserstein_distance;

pub use polygon::convex_hull_graham;

pub use polygon::douglas_peucker_simplify;

pub use polygon::is_simple_polygon;

pub use polygon::point_in_polygon;

pub use polygon::point_on_boundary;

pub use polygon::polygon_area;

pub use polygon::polygon_centroid;

pub use polygon::polygon_contains_polygon;

pub use polygon::visvalingam_whyatt_simplify;

pub use rtree::RTree;

pub use rtree::Rectangle as RTreeRectangle;

pub use octree::BoundingBox as OctreeBoundingBox;

pub use octree::Octree;

pub use quadtree::BoundingBox2D;

pub use quadtree::Quadtree;

pub use interpolate::IDWInterpolator;

pub use interpolate::NaturalNeighborInterpolator;

pub use interpolate::RBFInterpolator;

pub use interpolate::RBFKernel;

pub use pathplanning::astar::AStarPlanner;

pub use pathplanning::astar::ContinuousAStarPlanner;

pub use pathplanning::astar::GridAStarPlanner;

pub use pathplanning::astar::Node;

pub use pathplanning::astar::Path;

pub use pathplanning::rrt::RRT2DPlanner;

pub use pathplanning::rrt::RRTConfig;

pub use pathplanning::rrt::RRTPlanner;

pub use collision::shapes::Box2D;

pub use collision::shapes::Box3D;

pub use collision::shapes::Circle;

pub use collision::shapes::LineSegment2D;

pub use collision::shapes::LineSegment3D;

pub use collision::shapes::Sphere;

pub use collision::shapes::Triangle2D;

pub use collision::shapes::Triangle3D;

pub use collision::narrowphase::box2d_box2d_collision;

pub use collision::narrowphase::box3d_box3d_collision;

pub use collision::narrowphase::circle_box2d_collision;

pub use collision::narrowphase::circle_circle_collision;

pub use collision::narrowphase::gjk_box_box_collision;

pub use collision::narrowphase::gjk_collision_detection;

pub use collision::narrowphase::gjk_sphere_box_collision;

pub use collision::narrowphase::gjk_sphere_sphere_collision;

pub use collision::narrowphase::point_box2d_collision;

pub use collision::narrowphase::point_box3d_collision;

pub use collision::narrowphase::point_circle_collision;

pub use collision::narrowphase::point_sphere_collision;

pub use collision::narrowphase::point_triangle2d_collision;

pub use collision::narrowphase::ray_box3d_collision;

pub use collision::narrowphase::ray_sphere_collision;

pub use collision::narrowphase::ray_triangle3d_collision;

pub use collision::narrowphase::sphere_box3d_collision;

pub use collision::narrowphase::sphere_sphere_collision;

pub use collision::narrowphase::GJKShape;

pub use collision::continuous::continuous_sphere_sphere_collision;

pub use spatial_stats::clark_evans_index;

pub use spatial_stats::distance_weights_matrix;

pub use spatial_stats::gearys_c;

pub use spatial_stats::getis_ord_gi;

pub use spatial_stats::local_morans_i;

pub use spatial_stats::morans_i;

pub use simd_distance::parallel_cdist;

pub use simd_distance::parallel_pdist;

pub use simd_distance::simd_euclidean_distance;

pub use simd_distance::simd_euclidean_distance_batch;

pub use simd_distance::simd_knn_search;

pub use simd_distance::simd_manhattan_distance;

pub use simd_distance::SimdMetric;

pub use simd_distance::advanced_simd_clustering::AdvancedSimdKMeans;

pub use simd_distance::advanced_simd_clustering::AdvancedSimdNearestNeighbors;

pub use simd_distance::bench::benchmark_distance_computation;

pub use simd_distance::bench::report_simd_features;

pub use simd_distance::bench::BenchmarkResults;

pub use simd_distance::mixed_precision_simd::simd_euclidean_distance_batch_f32;

pub use simd_distance::mixed_precision_simd::simd_euclidean_distance_f32;

pub use memory_pool::global_clustering_arena;

pub use memory_pool::global_distance_pool;

pub use memory_pool::ArenaStatistics;

pub use memory_pool::ClusteringArena;

pub use memory_pool::DistanceBuffer;

pub use memory_pool::DistancePool;

pub use memory_pool::IndexBuffer;

pub use memory_pool::MatrixBuffer;

pub use memory_pool::MemoryPoolConfig;

pub use memory_pool::PoolStatistics;

pub use gpu_accel::get_gpu_capabilities;

pub use gpu_accel::global_gpu_device;

pub use gpu_accel::is_gpu_acceleration_available;

pub use gpu_accel::report_gpu_status;

pub use gpu_accel::GpuCapabilities;

pub use gpu_accel::GpuDevice;

pub use gpu_accel::GpuDistanceMatrix;

pub use gpu_accel::GpuKMeans;

pub use gpu_accel::GpuNearestNeighbors;

pub use gpu_accel::HybridProcessor;

pub use gpu_accel::ProcessingStrategy;

pub use advanced_parallel::get_numa_topology;

pub use advanced_parallel::initialize_global_pool;

pub use advanced_parallel::report_advanced_parallel_capabilities;

pub use advanced_parallel::AdvancedParallelDistanceMatrix;

pub use advanced_parallel::AdvancedParallelKMeans;

pub use advanced_parallel::MemoryStrategy;

pub use advanced_parallel::NumaTopology;

pub use advanced_parallel::PoolStatistics as AdvancedPoolStatistics;

pub use advanced_parallel::ThreadAffinityStrategy;

pub use advanced_parallel::WorkStealingConfig;

pub use advanced_parallel::WorkStealingPool;

pub use quantum_inspired::algorithms::QuantumSpatialOptimizer;

pub use quantum_inspired::ErrorCorrectionConfig;

pub use quantum_inspired::ErrorCorrectionType;

pub use quantum_inspired::OptimizationConfig;

pub use quantum_inspired::OptimizerType;

pub use quantum_inspired::PerformanceMetrics;

pub use quantum_inspired::QuantumAmplitude;

pub use quantum_inspired::QuantumClusterer;

pub use quantum_inspired::QuantumConfig;

pub use quantum_inspired::QuantumNearestNeighbor;

pub use quantum_inspired::QuantumSpatialFramework;

pub use quantum_inspired::QuantumState;

pub use neuromorphic::AdaptiveSpikingNeuron;

pub use neuromorphic::CompetitiveNeuralClusterer;

pub use neuromorphic::HomeostaticNeuralClusterer;

pub use neuromorphic::HomeostaticSynapse;

pub use neuromorphic::MetaplasticSynapse;

pub use neuromorphic::NetworkStats;

pub use neuromorphic::NeuromorphicCapability;

pub use neuromorphic::NeuromorphicConfig;

pub use neuromorphic::NeuromorphicFactory;

pub use neuromorphic::NeuromorphicProcessor;

pub use neuromorphic::SpikeEvent;

pub use neuromorphic::SpikeSequence;

pub use neuromorphic::SpikingNeuralClusterer;

pub use neuromorphic::SpikingNeuron;

pub use neuromorphic::Synapse;

pub use tensor_cores::detect_tensor_core_capabilities;

pub use tensor_cores::GpuArchitecture;

pub use tensor_cores::PrecisionMode;

pub use tensor_cores::TensorCoreCapabilities;

pub use tensor_cores::TensorCoreClustering;

pub use tensor_cores::TensorCoreDistanceMatrix;

pub use tensor_cores::TensorCoreType;

pub use tensor_cores::TensorLayout;

pub use ml_optimization::ActivationFunction;

pub use ml_optimization::ClusteringParameters;

pub use ml_optimization::ClusteringResult;

pub use ml_optimization::DataState;

pub use ml_optimization::DistanceMetric;

pub use ml_optimization::Experience;

pub use ml_optimization::NeuralSpatialOptimizer;

pub use ml_optimization::ReinforcementLearningSelector;

pub use ml_optimization::SpatialAlgorithm;

pub use distributed::ClusterStatistics;

pub use distributed::DataPartition;

pub use distributed::DistributedMessage;

pub use distributed::DistributedSpatialCluster;

pub use distributed::LoadBalancer;

pub use distributed::LoadMetrics;

pub use distributed::NodeConfig;

pub use distributed::NodeStatus;

pub use distributed::QueryResults;

pub use distributed::QueryType;

pub use distributed::SpatialBounds;

pub use adaptive_selection::ActualPerformance;

pub use adaptive_selection::AdaptiveAlgorithmSelector;

pub use adaptive_selection::AlgorithmParameters;

pub use adaptive_selection::AlgorithmSelection;

pub use adaptive_selection::DataCharacteristics;

pub use adaptive_selection::ExecutionResult;

pub use adaptive_selection::PerformancePrediction;

pub use adaptive_selection::SelectedAlgorithm;

pub use adaptive_selection::SelectionContext;

pub use quantum_classical_hybrid::HybridClusterer;

pub use quantum_classical_hybrid::HybridClusteringMetrics;

pub use quantum_classical_hybrid::HybridOptimizationResult;

pub use quantum_classical_hybrid::HybridPerformanceMetrics;

pub use quantum_classical_hybrid::HybridSpatialOptimizer;

pub use quantum_classical_hybrid::OptimizationStepResult;

pub use neuromorphic_quantum_fusion::FusionMetrics;

pub use neuromorphic_quantum_fusion::NeuralQuantumOptimizationResult;

pub use neuromorphic_quantum_fusion::NeuralQuantumOptimizer;

pub use neuromorphic_quantum_fusion::QuantumSpikeEvent;

pub use neuromorphic_quantum_fusion::QuantumSpikePattern;

pub use neuromorphic_quantum_fusion::QuantumSpikingClusterer;

pub use neuromorphic_quantum_fusion::QuantumSpikingNeuron;

pub use next_gen_gpu_architecture::NextGenGpuArchitecture;

pub use next_gen_gpu_architecture::NextGenPerformanceMetrics;

pub use next_gen_gpu_architecture::PhotonicAccelerator;

pub use next_gen_gpu_architecture::PhotonicProcessingUnit;

pub use next_gen_gpu_architecture::QuantumGpuProcessor;

pub use next_gen_gpu_architecture::QuantumProcessingUnit;

pub use generic_traits::ChebyshevMetric;

pub use generic_traits::EuclideanMetric;

pub use generic_traits::ManhattanMetric;

pub use generic_traits::Point;

pub use generic_traits::SpatialArray;

pub use generic_traits::SpatialPoint;

pub use generic_traits::SpatialScalar;

pub use generic_algorithms::DBSCANResult;

pub use generic_algorithms::GMMResult;

pub use generic_algorithms::GenericConvexHull;

pub use generic_algorithms::GenericDBSCAN;

pub use generic_algorithms::GenericDistanceMatrix;

pub use generic_algorithms::GenericGMM;

pub use generic_algorithms::GenericKDTree;

pub use generic_algorithms::GenericKMeans;

pub use generic_algorithms::KMeansResult;

pub use ai_driven_optimization::AIAlgorithmSelector;

pub use ai_driven_optimization::AdaptationRecord;

pub use ai_driven_optimization::AlgorithmCandidate;

pub use ai_driven_optimization::AlgorithmKnowledgeBase;

pub use ai_driven_optimization::AlgorithmMetadata;

pub use ai_driven_optimization::ComplexityModel;

pub use ai_driven_optimization::MetaLearningModel;

pub use ai_driven_optimization::MetaLearningOptimizer;

pub use ai_driven_optimization::MetaOptimizationResult;

pub use ai_driven_optimization::PerformanceModel;

pub use ai_driven_optimization::PerformanceRecord;

pub use ai_driven_optimization::PredictionNetworks;

pub use ai_driven_optimization::ReinforcementLearningAgent;

pub use ai_driven_optimization::TaskMetadata;

pub use extreme_performance_optimization::benchmark_extreme_optimizations;

pub use extreme_performance_optimization::create_ultimate_optimizer;

pub use extreme_performance_optimization::AdvancedfastDistanceMatrix;

pub use extreme_performance_optimization::CacheHierarchyInfo;

pub use extreme_performance_optimization::CacheObliviousSpatialAlgorithms;

pub use extreme_performance_optimization::ExtremeMemoryAllocator;

pub use extreme_performance_optimization::ExtremeOptimizer;

pub use extreme_performance_optimization::ExtremePerformanceMetrics;

pub use extreme_performance_optimization::HardwarePerformanceCounters;

pub use extreme_performance_optimization::JitCompiler;

pub use extreme_performance_optimization::LockFreeSpatialStructures;

pub use extreme_performance_optimization::NumaTopologyInfo;

pub use extreme_performance_optimization::OptimizationRecord;

pub use extreme_performance_optimization::SelfOptimizingAlgorithm;

Modules

adaptive_selection

Real-time adaptive algorithm selection system

advanced_parallel

Advanced-parallel algorithms with work-stealing and NUMA-aware optimizations

ai_driven_optimization

AI-Driven Algorithm Selection and Optimization (Advanced Mode)

alphashapes

Alpha shapes implementation for spatial analysis

balltree

Ball tree for efficient nearest neighbor searches

boolean_ops

Boolean operations for polygons and polyhedra

collision

Collision detection algorithms for various geometric primitives

convex_hull

Convex hull algorithms and utilities

delaunay

Delaunay triangulation algorithms

distance

Distance metrics for spatial data

distributed

Distributed spatial computing framework

error

Error types for the SciRS2 spatial module

extreme_performance_optimization

Extreme Performance Optimization (Advanced Mode)

generic_algorithms

Generic implementations of spatial algorithms

generic_traits

Generic traits and type parameters for spatial algorithms

geospatial

Geospatial functionality for working with geographic coordinates

gpu_accel

GPU acceleration for spatial algorithms

halfspace

Halfspace intersection and convex polytope construction

interpolate

Spatial interpolation methods

kdtree

KD-Tree for efficient nearest neighbor searches

kdtree_advanced

Advanced-optimized KD-Tree implementations with advanced performance features

kdtree_optimized

KD-Tree optimizations for common spatial operations

kriging

Kriging interpolation methods

memory_pool

Advanced-optimized memory pool system for spatial algorithms

ml_optimization

Machine learning-based spatial optimization

neuromorphic

Neuromorphic Computing for Spatial Data Processing

neuromorphic_quantum_fusion

Neuromorphic-Quantum Fusion Algorithms (Advanced Mode)

next_gen_gpu_architecture

Next-Generation GPU Architecture Support (Advanced Mode)

octree

Octree data structure for 3D space

pathplanning

Path planning algorithms

polygon

Polygon operations module

procrustes

Procrustes analysis

quadtree

Quadtree data structure for 2D space

quantum_classical_hybrid

Quantum-Classical Hybrid Spatial Algorithms (Advanced Mode)

quantum_inspired

Quantum-Inspired Spatial Algorithms

rtree

R-tree implementation for efficient spatial indexing

set_distance

Set-based distance metrics

simd_distance

SIMD-accelerated distance calculations for spatial operations

spatial_stats

Spatial statistics module for analyzing spatial patterns and relationships

spherical_voronoi

SphericalVoronoi Implementation

tensor_cores

Advanced GPU Tensor Core utilization for spatial algorithms

transform

voronoi

Voronoi diagrams