cluster_neighbourhoods

cluster_neighbourhoods(domains_to_analyse, label_name, populations_to_analyse=None, neighbourhood_source=None, include_boundaries=None, exclude_boundaries=None, boundary_exclude_distance=0, network_type='Delaunay', force_labels_to_include=[], labels_to_ignore=[], k_hops=3, max_edge_distance=inf, min_edge_distance=0, number_of_nearest_neighbours=10, neighbourhood_label_name='Neighbourhood ID', cluster_method='kmeans', cluster_parameters={'n_clusters': 8})

A function to cluster neighbourhoods based on the enrichment of labels within the neighbourhoods of objects using a network connectivity.

Parameters:

domains_to_analyselist or object

A list of muspan domains or a single muspan domain to be analyzed.

label_namestr

The name of the label to be used for clustering.

populations_to_analysearray-like, query-like, or None, optional

Populations to be analyzed within the domains. If None, defaults to the neighbourhood_source.

neighbourhood_sourcearray-like, query-like, or None, optional

Source of neighbourhoods within the domains. If None, defaults to populations_to_analyse.

include_boundariesarray-like, query-like, or None, optional

Boundaries to include in the analysis. If None, no boundaries are included.

exclude_boundariesarray-like, query-like, or None, optional

Boundaries to exclude from the analysis. If None, no boundaries are excluded.

boundary_exclude_distancefloat, optional

Distance to exclude from the boundaries. Default is 0.

network_typestr, optional

Type of network to generate. Default is ‘Delaunay’.

force_labels_to_includelist, optional

Labels to forcefully include in the analysis. Default is an empty list.

labels_to_ignorelist, optional

Labels to ignore in the analysis. Default is an empty list.

k_hopsint, optional

Number of hops for neighbourhood calculation. Default is 3.

max_edge_distancefloat, optional

Maximum edge distance for network generation. Default is np.inf.

min_edge_distancefloat, optional

Minimum edge distance for network generation. Default is 0.

number_of_nearest_neighboursint, optional

Number of nearest neighbours for network generation. Default is 10.

neighbourhood_label_namestr, optional

Name for the neighbourhood label. Default is ‘Neighbourhood ID’.

cluster_methodstr, optional

Clustering method to use. Default is ‘kmeans’.

cluster_parametersdict, optional

Parameters for the clustering method. Default is {‘n_clusters’: 8}.

Returns:

neighbourhood_enrichment_matrixnumpy.ndarray

Matrix representing the enrichment of neighbourhoods.

consistent_global_labelslist

List of consistent global labels across all domains.

unique_cluster_labelsnumpy.ndarray

Array of unique cluster labels.