magnet.aggmodels.metis.METIS#

class magnet.aggmodels.metis.METIS#

Bases: AgglomerationModel

Metis algorithm for graph partitioning.

Constructor

__init__()#

Methods

direct_k_way(mesh, k[, volume_weights])

Bisect the mesh recursively a set number of times.
direct_k_way(mesh: Mesh, k: int, volume_weights: bool = True) → List[ndarray[int]]#

Bisect the mesh recursively a set number of times.

The agglomearated mesh will have (at most) 2^`Nref` agglomerated elements.

Parameters:

  • Mesh (mesh) – Mesh to be bisected.

  • Nref (int) – Number of times to recursively bisect the mesh.

  • volume_weights (bool, optional) – If true, use volume as node weights, otherwise use unitary weights.

Returns:

A list of arrays, each containing the indices of the elements corresponding to one of the agglomerated elements.

Return type:

Classlist

Inherited Methods

__init__()

agglomerate(mesh[, mode, nref, mult_factor])

Agglomerate a mesh.

agglomerate_dataset(dataset, **kwargs)

Agglomerate all meshes in a dataset.

bisect(mesh)

Bisect the mesh once.

bisection_Nref(mesh, Nref[, warm_start])

Bisect the mesh recursively a set number of times.

bisection_mult_factor(mesh, mult_factor[, ...])

Bisect a mesh until the agglomerated elements are small enough.

bisection_segregated(mesh, mult_factor[, subset])

Bisect heterogeneous mesh until elements are small enough.

coarsen(mesh, subset[, mode, nref, mult_factor])

Coarsen a subregion of the mesh.

multilevel_bisection(mesh[, refiner, ...])