cratepy.clustering.clusteringdata.set_clustering_data

set_clustering_data(strain_formulation, problem_type, rve_dims, n_voxels_dims, regular_grid, material_phases, material_phases_properties, dns_method, dns_method_data, standardization_method, base_clustering_scheme, adaptive_clustering_scheme)[source]

Compute the features data required to perform the RVE cluster analysis.

Parameters:

  • strain_formulation ({'infinitesimal', 'finite'}) – Problem strain formulation.

  • problem_type (int) – Problem type: 2D plane strain (1), 2D plane stress (2), 2D axisymmetric (3) and 3D (4).

  • rve_dims (list[float]) – RVE size in each dimension.

  • n_voxels_dims (list[int]) – Number of voxels in each dimension of the regular grid (spatial discretization of the RVE).

  • regular_grid (numpy.ndarray (2d or 3d)) – Regular grid of voxels (spatial discretization of the RVE), where each entry contains the material phase label (int) assigned to the corresponding voxel.

  • material_phases (list[str]) – RVE material phases labels (str).

  • material_phases_properties (dict) – Constitutive model material properties (item, dict) associated to each material phase (key, str).

  • dns_method (str) – DNS homogenization-based multi-scale method.

  • dns_method_data (dict) – Parameters of DNS homogenization-based multi-scale method.

  • standardization_method (int) – Identifier of global cluster analysis data standardization algorithm.

  • base_clustering_scheme (dict) – Prescribed base clustering scheme (item, numpy.ndarray of shape (n_clusterings, 3)) for each material phase (key, str). Each row is associated with a unique clustering characterized by a clustering algorithm (col 1, int), a list of features (col 2, list[int]) and a list of the features data matrix’ indexes (col 3, list[int]).

  • adaptive_clustering_scheme (dict) – Prescribed adaptive clustering scheme (item, numpy.ndarray of shape (n_clusterings, 3)) for each material phase (key, str). Each row is associated with a unique clustering characterized by a clustering algorithm (col 1, int), a list of features (col 2, list[int]) and a list of the features data matrix’ indexes (col 3, list[int]).

Returns:

  • clustering_data (ClusterAnalysisData) – Feature data required to perform the RVE cluster analysis.

  • rve_elastic_database (RVEElasticDatabase) – RVE’s local elastic response database.