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.