Struct VietorisRips 

pub struct VietorisRips;

Vietoris-Rips complex for computing persistent homology

The Vietoris-Rips complex builds a filtration of simplicial complexes from point cloud data by including a simplex whenever all pairwise distances between its vertices are at most the filtration parameter ε.

Example

use scirs2_transform::tda::VietorisRips;
use scirs2_core::ndarray::Array2;

let points = Array2::from_shape_vec((4, 2), vec![
    0.0, 0.0,   1.0, 0.0,   1.0, 1.0,   0.0, 1.0,
]).expect("should succeed");

let diagram = VietorisRips::compute(&points, 1, 2.0).expect("should succeed");
assert!(!diagram.is_empty());

Implementations

impl VietorisRips

pub fn compute<S>( points: &ArrayBase<S, Ix2>, max_dim: usize, max_radius: f64, ) -> Result<PersistenceDiagram>

where S: Data, S::Elem: Float + NumCast,

Compute the persistent homology of a point cloud using the Vietoris-Rips filtration

Arguments

• points - Point cloud data (n_points × n_features)
• max_dim - Maximum homological dimension to compute (0 = components, 1 = loops, …)
• max_radius - Maximum filtration radius; simplices with diameter > 2*max_radius are ignored

Returns

• A persistence diagram with (birth, death) pairs for each dimension