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scalednap 1.0.0

• First public release.
• cluster_milano(): community detection by maximising a persistence-based objective with the Milano local-search algorithm and multi-restart search. The objective is selected by H0: persistence probability (H0 = NULL), null-adjusted persistence / NAP (H0 = 0), or scaled null-adjusted persistence / Scaled-NAP (H0 in (0, 1]).
• global_persistence() and local_persistence(): score a whole partition or a single community under the three measures.
• Methods for base graphs (vertex/edge lists) and for ‘igraph’ objects.
• Reproducible results from a master seed (SplitMix64-derived restart seeds), identical to the Python package and the command-line tool.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.