scirs2_spatial/interpolate/
mod.rs

1//! Spatial interpolation methods
2//!
3//! This module provides various methods for interpolating scattered data in
4//! 2D and 3D space. These interpolation methods are useful for reconstructing
5//! continuous fields from discrete sample points, filling gaps in data, and
6//! generating smooth surfaces from irregularly sampled points.
7//!
8//! The available interpolation methods include:
9//!
10//! - Natural Neighbor interpolation: Local method that creates a weighted average
11//!   of neighboring points based on their Voronoi cells. Produces smooth surfaces
12//!   that respect the local structure of the data.
13//!
14//! - Radial Basis Function (RBF) interpolation: Uses radial basis functions to
15//!   create a global interpolation that can represent complex surfaces. Various
16//!   kernel functions can be selected to control the smoothness and locality of
17//!   the interpolation.
18//!
19//! - Inverse Distance Weighting (IDW): Simple interpolation method that weights
20//!   neighboring points by the inverse of their distance raised to a power. Fast
21//!   but can create "bull's-eye" patterns around sample points.
22//!
23//! - Kriging (planned): Geostatistical method that accounts for the spatial
24//!   correlation of data. Produces an interpolated surface along with an estimate
25//!   of the prediction error.
26
27// Re-export public modules
28pub mod idw;
29pub mod natural_neighbor;
30pub mod rbf;
31
32// Re-export key types and functions
33pub use idw::IDWInterpolator;
34pub use natural_neighbor::NaturalNeighborInterpolator;
35pub use rbf::{RBFInterpolator, RBFKernel};