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netrics 0.2.1

Package

• Added network analysis tutorials from {manynet}

Members

• Added more explanation for node_in_partition()

netrics 0.2.0

Package

• Added roxygen2 parameter templates (param_attr, param_data, param_dir, param_memb, param_motf, param_norm, param_select) and net/node/tie-level templates (net_measure, net_motif, node_mark, node_measure, node_member, node_motif, tie_mark, tie_measure) for consistent function documentation.
• Fixed startup messages.

Measuring

• Renamed node_adoption_time() to node_by_adopt_time()
• Renamed node_thresholds() to node_by_adopt_threshold()
• Renamed node_exposure() to node_by_adopt_exposure()
  
• Renamed node_recovery() to node_by_adopt_recovery()
  
• Separated centralisation scripts into different files per measure type (betweenness, closeness, degree, eigenvector) for easier maintenance, and into different documentation per level (node, tie) for better organization.
• Updated and separated brokerage, diversity/assortativity, cohesion, closure, cliques, components, features, and hierarchy documentation by level.

Members

• Separated node_in_community() documentation from the hierarchical and non-hierarchical community-detection algorithms.
• Core documentation split into separate mark, measure, and member pages.
• Improved various functions that rely on a membership argument to accept both a membership vector and a string identifier of a network attribute.

Motifs

• Renamed net_by_change() to net_x_change() and related functions to reflect their motif (subgraph-counting) nature.

Methods

• Added gap method for cluster k-selection in method_k().
• Renamed model_k() to method_k() and related cluster-selection utilities renamed for clarity.

netrics 0.1.0

Release notes

{netrics} 0.1.0 is the first formal release of the package as a standalone analytic engine for the stocnet ecosystem. The analytic functions — marks, measures, motifs, and memberships — have been extracted from {manynet} and {migraph} into this dedicated package, with consistent naming conventions and a range of bug fixes.

New naming conventions

All functions now follow a consistent verb–object–qualifier naming scheme:

• Marks (node_is_*(), tie_is_*()): logical vectors identifying which nodes or ties hold a particular structural property.
• Measures (*_by_*()): numeric vectors at the network (net_by_*()), node (node_by_*()), or tie (tie_by_*()) level.
• Motifs (*_x_*()): tabular counts of nodes’ or networks’ participation in structural sub-patterns.
• Memberships (*_in_*()): categorical vectors assigning nodes to groups (components, communities, equivalence classes, etc.).

Functions previously named with other prefixes (e.g. node_centrality_*, net_cohesion_*, node_equivalency_*) have been renamed to follow the *_by_*() / *_x_*() / *_in_*() convention. tie_by_cohesion() now correctly returns a tie_measure class object.

Functions moved from {manynet} / {migraph}

The following groups of functions have been moved into {netrics}:

Marks

• node_is_core(), node_is_cutpoint(), node_is_exposed(), node_is_fold(), node_is_independent(), node_is_infected(), node_is_isolate(), node_is_latent(), node_is_max(), node_is_mean(), node_is_mentor(), node_is_min(), node_is_neighbor(), node_is_pendant(), node_is_random(), node_is_recovered(), node_is_universal()
• tie_is_bridge(), tie_is_cyclical(), tie_is_feedback(), tie_is_imbalanced(), tie_is_loop(), tie_is_max(), tie_is_min(), tie_is_multiple(), tie_is_path(), tie_is_random(), tie_is_reciprocated(), tie_is_simmelian(), tie_is_transitive(), tie_is_triangular(), tie_is_triplet()

Measures

• Network-level: net_by_adhesion(), net_by_assortativity(), net_by_balance(), net_by_betweenness(), net_by_change(), net_by_closeness(), net_by_cohesion(), net_by_components(), net_by_congruency(), net_by_connectedness(), net_by_core(), net_by_correlation(), net_by_degree(), net_by_density(), net_by_diameter(), net_by_diversity(), net_by_efficiency(), net_by_eigenvector(), net_by_equivalency(), net_by_factions(), net_by_harmonic(), net_by_heterophily(), net_by_hierarchy(), net_by_homophily(), net_by_immunity(), net_by_indegree(), net_by_independence(), net_by_infection_complete(), net_by_infection_peak(), net_by_infection_total(), net_by_length(), net_by_modularity(), net_by_outdegree(), net_by_reach(), net_by_reciprocity(), net_by_recovery(), net_by_reproduction(), net_by_richclub(), net_by_richness(), net_by_scalefree(), net_by_smallworld(), net_by_spatial(), net_by_stability(), net_by_strength(), net_by_toughness(), net_by_transitivity(), net_by_transmissibility(), net_by_upperbound(), net_by_waves()
• Node-level: node_by_adoption_time(), node_by_alpha(), node_by_authority(), node_by_betweenness(), node_by_bridges(), node_by_brokering_activity(), node_by_brokering_exclusivity(), node_by_closeness(), node_by_constraint(), node_by_coreness(), node_by_deg(), node_by_degree(), node_by_distance(), node_by_diversity(), node_by_eccentricity(), node_by_efficiency(), node_by_effsize(), node_by_eigenvector(), node_by_equivalency(), node_by_exposure(), node_by_flow(), node_by_harmonic(), node_by_heterophily(), node_by_hierarchy(), node_by_homophily(), node_by_hub(), node_by_indegree(), node_by_induced(), node_by_information(), node_by_kcoreness(), node_by_leverage(), node_by_multidegree(), node_by_neighbours_degree(), node_by_outdegree(), node_by_pagerank(), node_by_posneg(), node_by_power(), node_by_randomwalk(), node_by_reach(), node_by_reciprocity(), node_by_recovery(), node_by_redundancy(), node_by_richness(), node_by_stress(), node_by_subgraph(), node_by_thresholds(), node_by_transitivity(), node_by_vitality()
• Tie-level: tie_by_betweenness(), tie_by_closeness(), tie_by_cohesion(), tie_by_degree(), tie_by_eigenvector()

Motifs

• net_x_brokerage(), net_x_dyad(), net_x_hazard(), net_x_mixed(), net_x_tetrad(), net_x_triad()
• node_x_brokerage(), node_x_dyad(), node_x_exposure(), node_x_path(), node_x_tetrad(), node_x_tie(), node_x_triad()

Memberships

• node_in_adopter(), node_in_automorphic(), node_in_betweenness(), node_in_brokering(), node_in_community(), node_in_component(), node_in_core(), node_in_eigen(), node_in_equivalence(), node_in_fluid(), node_in_greedy(), node_in_infomap(), node_in_leiden(), node_in_louvain(), node_in_optimal(), node_in_partition(), node_in_regular(), node_in_roulette(), node_in_spinglass(), node_in_strong(), node_in_structural(), node_in_walktrap(), node_in_weak()

Bug fixes

• node_is_isolate() and node_is_pendant() now work correctly with signed networks.
• tie_is_random() now correctly returns a tie_mark class object (previously returned a node mark).
• node_by_authority() and node_by_hub() updated to use current {igraph} API.
• node_by_brokering_activity() and node_by_brokering_exclusivity() now handle unlabelled networks correctly.
• node_by_homophily() no longer resolves the attribute to a vector prematurely.
• node_by_pagerank() updated to correctly extract the vector output from {igraph}.
• node_by_power() reverts to a lower exponent (closer to degree centrality) when there is no degree variation.
• node_by_randomwalk() now works with two-mode networks.
• net_by_degree(), net_by_harmonic(), and net_by_reach() now consistently include the function call in the returned object.
• net_by_richclub() returns 0 (rather than erroring) when all nodes have equivalent degree.
• net_by_smallworld() and node_by_bridges() now use internal {netrics} functions rather than {manynet} equivalents.
• net_by_waves() returns 1 for cross-sectional networks and correctly returns a network measure class.
• net_x_hierarchy() correctly classified as a motif function.
• node_in_community() now delegates to {netrics} membership functions internally.
• Dyad census fixed to handle two-mode networks.
• Equivalence k-assignment fixed for the degenerate case where every node is placed in the same cluster.
• tie_by_cohesion() now correctly returns a tie_measure class object.

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.