blue_sampler.from_geometry

blue_sampler.from_geometry(geometry, gtype, p=3, **kwargs)

Convert tessels or clusters into low-discrepancy point set.

Each tessel or cluster is replaced by n points by solving a moment-matching problem (Levenberg-Marquardt) via momentum_fit.

Parameters:

• geometry (NDArray) –

  Batch of tessels or clusters to convert. - gtype=”polygons” : quadrilaterals of shape (N, 4, 2),

  e.g. the quad output of sample_tessels.

  • gtype=”clusters” : point sets of shape (N, K, D), e.g. the output of sample_clusters, or the atoms output of sample_tessels(…, return_atoms=True).

• gtype (str) – Geometry type. “polygons” only supports D = 2.

• p (int) – Maximum total moment order to match (centroid plus central moments up to order p).

• **kwargs – Additional arguments passed to momentum_fit (e.g., n_restarts, random_state, tol).

Returns:

n points per tessel or cluster, matching its moments up to order p.

Return type:

NDArray