Utils

Clusters

Functions to manipulate and sort clusters

cluster_sort(clusters, final_labels=None)

Return array of cluster labels sorted in order of appearance, with clusters unchanged

Example

>>> clusters = np.array([2, 2, 2, 3, 3, 1, 1, 1])
>>> cluster_sort(clusters)
[ 1 1 1 2 2 3 3 3 ]

rand_index_over_methods_and_sizes(valid_cluster_sets, reference_method='ward')

Compute Rand Index to compare any method to a reference method, for all combinations of methods and number of clusters

Parameters

• valid_cluster_sets (list) –

• reference_method (str) –

Returns

rand_scores – Array of dimension (n_sizes, n_methods) with rand index scores

Return type

ndarray

Graphs

Utility functions for static graphs

create_graph_from_interactions(filename, sheet, source, target)

Create a networkx.Graph from an excel sheet describing edges

Parameters

• filename (str) – Path to the excel file

• sheet (str) – Name of the sheet within the excel file

• source (str) – Name of the column containing the source nodes

• target (str) – Name of the column containing the target nodes

Returns

graph

Return type

networkx.Graph

graph_size_info(graph)

Return basic size info on about graph

Paths

Functions to deal with system paths

slugify(text, keep_characters=None)

Turn any text into a string that can be used in a filename

Parameters

• text (str) – text to slugify

• keep_characters (list of str) – characters in this iterable will be kept in the final string. Defaults to [‘_’]. Any other non-alphanumeric characters will be removed.

Returns

slug

Return type

str