{manynet}node_in_partition()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.node_adoption_time() to node_by_adopt_time()node_thresholds() to node_by_adopt_threshold()node_exposure() to node_by_adopt_exposure()node_recovery() to node_by_adopt_recovery()node_in_community() documentation from the hierarchical
and non-hierarchical community-detection algorithms.net_by_change() to net_x_change() and related functions to
reflect their motif (subgraph-counting) nature.method_k().model_k() to method_k() and related cluster-selection utilities
renamed for clarity.{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.
All functions now follow a consistent verb–object–qualifier naming scheme:
node_is_*(), tie_is_*()): logical vectors identifying which nodes
or ties hold a particular structural property.*_by_*()): numeric vectors at the network (net_by_*()),
node (node_by_*()), or tie (tie_by_*()) level.*_x_*()): tabular counts of nodes' or networks' participation
in structural sub-patterns.*_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.
The following groups of functions have been moved into {netrics}:
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()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_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_by_betweenness(), tie_by_closeness(),
tie_by_cohesion(), tie_by_degree(), tie_by_eigenvector()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()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()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.tie_by_cohesion() now correctly returns a tie_measure class object.