lingpy.thirdparty.linkcomm package

Submodules

lingpy.thirdparty.linkcomm.link_clustering module

changes 2010-08-27:

• all three output files now contain the same community id numbers

• comm2nodes and comm2edges both present the cid as the first

entry of each line. Previously only comm2nodes did this. * implemented weighted version, added ‘-w’ switch * expanded help string to explain input and outputs

lingpy.thirdparty.linkcomm.link_clustering.Dc(m, n)

partition density

class lingpy.thirdparty.linkcomm.link_clustering.HLC(adj, edges)

Bases: object

initialize_edges()

merge_comms(edge1, edge2)

single_linkage(threshold=None, w=None)

lingpy.thirdparty.linkcomm.link_clustering.similarities_unweighted(adj)

Get all the edge similarities. Input dict maps nodes to sets of neighbors. Output is a list of decorated edge-pairs, (1-sim,eij,eik), ordered by similarity.

lingpy.thirdparty.linkcomm.link_clustering.similarities_weighted(adj, ij2wij)

Same as similarities_unweighted but using tanimoto coefficient. `adj’ is a dict mapping nodes to sets of neighbors, ij2wij is a dict mapping an edge (ni,nj) tuple to the weight wij of that edge.

lingpy.thirdparty.linkcomm.link_clustering.swap(a, b)

Module contents

Module provides a simple py3 port for link community analyses, following the algorithm by James Bagrow, Yong-Yeol Ahn.