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net_correlation() for calculating the
product-moment correlation between networksto_simplex.data.frame() and
to_simplex.network()is_aperiodic() where it would not work in
tutorial chunksover_membership() for obtaining summary
statistics by a membership vectorcreate_ego(),
create_empty(), create_filled(),
create_ring(), create_star(),
create_lattice())as_matrix() handles signed networksas_nodelist() for extracting nodelists from
networks into tibblesto_cosine()to_galois() until it can be refactoredto_signed() for adding signs to networksto_weighted() for adding weights to networksgraphr() where line types were inferred
incorrectlygraphr() so that layouts can now be
snapped to a grid, mileage may varynode_is_pendant() for identifying pendant
nodesnode_is_neighbor() for identifying adjacent
nodestie_is_imbalanced() for identifying ties in
imbalanced configurationssummary.network_measure() to return z-scores and
p-values for measuresnode_vitality() for measuring closeness vitality
centralitynode_eigenvector()node_in_community() which runs through most
salient community detection algorithms to find and return the one with
the highest modularitynode_in_regular() to inform user which census
is being usednode_by_quad() to node_by_tetrad()
to be more consistent with Greek origins
summary.network_motif() which returns the
z-scores for the motif scores based on random or configurational
networks, traces progressplot.network_motif() where motif names
were not identified correctly, internal make_network_motif now inherits
call informationcluster_cosine() for another equivalence
optionrun_tute() fuzzy matched so that
insertions are not as costlygloss(), clear_glossary(), and
print_glossary() for adding glossaries to tutorialsirps_wwi, a dynamic, signed networkison_blogs to irps_blogs, added
infoison_books to irps_books, added
infoison_usstates to irps_usgeo, added
infoison_friends to fict_friends,
added info and fixed directed issueison_greys to fict_greys, added
infoison_lotr to fict_lotr, added
infoison_thrones to fict_thrones,
added info and some additional nodal attributesison_potter to fict_potter, added
info and combined waves into single object{concaveman}{ggdendro}thisRequires() bug by testing for
interactivityto_ego() and to_egos() to specify
directiongraphr() where user not informed about
{concaveman} dependencygraphr() examplesto_dominating() for extracting the dominating
tree of a given networkgraphr() to make function more concise and
consistent (thanks @henriquesposito)
node_eccentricity() to allow normalisation,
appear in closeness documentationnode_stress() as a new betweenness-like
centrality measurenode_leverage() as a new degree-like centrality
measureread_*() now print the command used to the console
if the (default) file.choose() is usedread_gml()node_power()ison_dolphinsison_booksison_blogsoptions(manynet_verbosity ="quiet")create_ego() for collecting ego networks through
interviews, including arguments for:
create_motifs() for creating networks that
correspond to the isomorphic subgraphs of certain size and formatprint.mnet()
add_info() for adding grand info to tidygraph
objects
to_unweighted() so that it passes through
unweighted networks correctlyset_manynet_theme() to set theme (re #60), but
not yet fully implementedis_multiplex() to ignore “name” tie
attributesnode_authority() and node_hub()
centrality measuresnode_equivalency() for calculating four-cycle
closure by nodenet_equivalency() to one-mode networksnode_in_equivalence() to use census directlycreate_motifs()node_by_dyad() for node level dyad censusnet_by_quad() for network level quad censusnode_by_quad() to avoid {oaqc}
dependency (#89), more flexible but slowerprint.node_motif() to convert to tibble and add
modes and names where available only upon print
ison_southern_women with grand infoison_laterals with reordered nodes{cli}suppressPackageStartupMessages()stop() replaced by
cli::cli_abort(){minMSE} dependency{roxygen2} dependency to Config/Needs/build{grDevices} and {png}
dependencies{network} reexportsrun_tute() and extract_tute() to
look for installed packages and report progressread_cran() for creating networks of package
dependencies on CRAN
{manynet})generate_man() for generating dyad census
conditional uniform graphsgenerate_islands() only takes a single integer and not a
vectoras_tidygraph() to add an additional class
‘mnet’ that is used for prettier printing
make_mnet() (internally) for future-proofingprint.tbl_graph() renamed to
print.mnet()print.mnet() uses ‘grand’ data if availablebind_ties() to be more flexible about the
input it accepts, converting all input into the required edgelistto_ego() for obtaining a single
neighbourhooddelete_nodes()
and delete_ties()add_ties() and
delete_ties() in documentationto_unnamed.igraph() when used with already
unlabelled networkstie_is_path() for tracing the ties on a
particular pathtie_is_triplet() for returning all the ties that
are members of transitive tripletstie_is_forbidden() for identifying ties in
forbidden triadstie_is_transitive() efficiency, now only
retrieves the edgelist onceis_aperiodic() to remove {minMSE}
dependency and offer a progress bar if it takes longer than 2
secondstie_is_triangular() to do with altpath
namingnode_distance() for measuring the distance from
or to particular nodesnode_degree() processed
isolates in calculating strength in weighted networksison_ data with new
as_tidygraph()ison_adolescents as a testison_thrones on kinship arcs between Game of
Thrones characters, with ‘grand’ dataison_monastery_ data into
ison_monks, a single multiplex, signed, weighted,
longitudinal networkcreate_degree() for creating networks of a given
degree sequence, including k-regular graphsgenerate_citations() for citation modelsgenerate_fire() for forest-fire modelsgenerate_islands() for island modelscreate_explicit() now has its own documentationtie_is_triangular() for identifying ties in
trianglestie_is_cyclical() for identifying ties in
cyclestie_is_transitive() for identifying ties involved
in transitive closuretie_is_simmelian() for identifying Simmelian
tiesgenerate_permutation() renamed to
to_permuted()graphr() plots edges in directed
networkstable_data() can now report on data from multiple
packages
{manynet} and {migraph} are included by
default, and if any are not installed they are just ignoredtable_data() can now filter by any reported formats,
such as ‘directed’ or ‘twomode’as_matrix.igraph() now only draws from the “weight”
attribute and not, e.g. “type”to_blocks() related to categorical
membership variablesmutate_ties()node_names() now returns names of the form “N01” etc
for unlabelled networksplot.matrix() works for unlabelled
networksgraphr()graphs() recognises ego networks so it is
compatible with other splitsgraphr()graphr()graphr()
functiongraphs() automatically uses “star” layout
to plot ego networksgraphr(),
graphs(), and grapht() also accept British
spellingsgraphs() and
grapht()to_subgraphs() no longer sampled{manynet} logo with stocnet GitHub address and
color blind safe colorway{minMse} dependencynetwork_*
prefix to net_* for conciseness{migraph}{migraph}create_core() where the membership
inferred when passing an existing network was incorrectgenerate_configuration() for generating
configuration models (including for two-mode networks)play_diffusion() now includes an explicit contact
argument to control the basis of exposurenode_is_*() functions now infer network data
contextnode_is_independent() for identifying nodes among
largest independent setsis_multiplex() now excludes reserved tie attribute
names other than type, such as “weight”, “sign”, or “wave”is_attributed() to check for non-name nodal
attributesnode_is_latent(),
node_is_recovered(), and node_is_infected()
(closes #71)is_twomode(),
is_labelled(), and is_complex()graphr(),
graphs(), and grapht()
(autographr(), autographs(), and
autographd() are now deprecated)scale_size(range = c(...,...)) to be usedscale_size() from
{ggplot2}graphr() now rescales node size depending on network
size (closes #51)to_named() now randomly generates and adds an
alphabetic sequence of names, where previously this was just a random
sample, which may assist pedagogical use
to_correlation() that implements pairwise
correlation on networkarrange_ties() for {dplyr}-like
reordering of ties based on some attributeto_correlation() for calculating the Pearson
correlation
as_diff_model() where events were out of
order and namedis_multiplex() now recognises “date”, “begin”, and
“end” as reserved{migraph}
node_degree(), node_deg(),
node_indegree(), node_outdegree(),
node_multidegree(), node_posneg(),
tie_degree(), net_degree(),
net_indegree(), and net_outdegree()node_betweenness(), node_induced(),
node_flow(), tie_betweenness(), and
net_betweenness()node_closeness(), node_reach(),
node_harmonic(), node_information(),
tie_closeness(), net_closeness(),
net_reach(), and net_harmonic()node_eigenvector(), node_power(),
node_alpha(), node_pagerank(),
tie_eigenvector(), and net_eigenvector()net_reciprocity(),
node_reciprocity(), net_transitivity(),
node_transitivity(), net_equivalency(), and
net_congruency()net_density(),
net_components(), net_cohesion(),net_adhesion(), net_diameter(),
net_length(), and net_independence()net_transmissibility(),
net_recovery(), net_reproduction(),
net_immunity(), net_hazard(),
net_infection_complete(),
net_infection_total(), net_infection_peak(),
node_adoption_time(), node_thresholds(),
node_recovery(), and node_exposure()net_richness(),
node_richness(), net_diversity(),
node_diversity(), net_heterophily(),
node_heterophily(), net_assortativity(), and
net_spatial()net_reciprocity(),
net_connectedness(), net_efficiency(), and
net_upperbound()node_bridges(),
node_redundancy(), node_effsize(),node_efficiency(), node_constraint(),
node_hierarchy(), node_eccentricity(),
node_neighbours_degree(), and
tie_cohesion()net_core(),
net_richclub(), net_factions(),
node_partition(), net_modularity(),
net_smallworld(), net_scalefree(),
net_balance(), net_change(), and
net_stability()node_mode() (deprecated) to
node_is_mode() since it returns a logical vectornode_attribute() and
tie_attribute() to return measures when the output is
numericnode_exposure() to work with two-mode and
signed networksnode_constraint() to work with weighted two-mode
networks, thanks to Toshitaka Izumi for spotting thismutate()
without specifying .datanet_independence() for calculating the number of
nodes in the largest independent setnode_coreness() now returns ‘node_measure’ outputnode_exposure() now sums tie weights where passed a
weighted network{migraph}
node_in_roulette() (previously
node_roulette())node_in_optimal(), node_in_partition()
(previously node_kernaghinlin()),
node_in_infomap(), node_in_spinglass(),
node_in_fluid(), node_in_louvain(),
node_in_leiden(), node_in_betweenness(),
node_in_greedy(), node_in_eigen(), and
node_in_walktrap()node_in_component(),
node_in_weak(), and node_in_strong() (NB:
node_in_component() is no longer phrased in the
plural)node_is_core() and
node_coreness()node_in_adopter()node_in_equivalence(),
node_in_structural(), node_in_regular(), and
node_in_automorphic()node_*(), but including the preposition _in_
is more consistent.node_member class is now categorical
make_node_member() now converts numeric results to
LETTER character resultsprint.node_member() now works with categorical
membership vectorsprint.node_member() now declares how many groups before
reporting the vectorsmutate() without specifying .data{migraph}, these include
node_by_tie(), node_by_triad(),
node_by_quad(), node_by_path(),
net_by_dyad(), net_by_triad(),
net_by_mixed(), node_by_brokerage(),
net_by_brokerage()
*_*_census(), but the preposition _by_ is more
consistent.node_tie_census() now works on longitudinal network
dataprint.node_motif() wasn’t printing the
requested number of lines{migraph}
cluster_hierarchical() and
cluster_concor()k_strict(),
k_elbow(), and k_silhouette()cluster_concor()
cluster_concor() now uses to_correlation()
for initial correlationstats::cor() for subsequent
iterationscluster_concor() handles unlabelled
networkscluster_concor() handles two-mode
networkscluster_concor() cutoff resulted in
unsplit groupscluster_hierarchical() now also uses
to_correlation()ison_greys dataset, including some corrections to
that published in {networkdata}ison_friends dataset to be explicitly
longitudinalison_usstates dataset with population data
(Alaska and Hawaii missing)ison_southern_women dataset with surnames,
titles, event dates, and corrected ties2024-03-15
to_scope() for CRAN
resubmission2024-03-13
autographr() examples that were
taking too long to runautographr(),
autographs(), and autographd() functionsautographr(),
autographs(), and autographd() functionsnode_is_infected(),
node_is_recovery(), node_is_latent() work for
network lists2024-03-12
play_diffusions() to revert
future plan on exitgenerate_random() works for two-mode
networks with specified number of tiesautographr() more flexible and
efficient in setting variables to aesthetics{ggplot2}to_reciprocated.matrix() to consistently work
with matrices2023-12-24
run_tute()2023-12-24
pkg_data() to report an overview of data
contained within the package(s){ggplot2}
releaseplay_diffusion() and
play_diffusions() from {migraph}
print(),
summary(), and plot() methodsplay_learning() and
play_segregation() from {migraph}
print(),
summary(), and plot() methodscreate_tree() where it was not returning a
two-mode network correctlyas_diffusion() to coerce a table of diffusion
events into diff_model class
as_*() functions are now considered modificationsmutate_nodes()filter_nodes()rename_nodes()bind_ties()delete_ties()to_tree() to find one or more spanning trees
amongst a network’s tiesfrom_ties() to collect multiple networks into a
multiplex networkis.igraph() to is_igraph() for
igraph v2.0.0is_list() for identifying a list of networksnode_is_core(),
node_is_cutpoint(), node_is_fold(),
node_is_isolate(), node_is_mentor() from
{migraph}node_is_exposed(),
node_is_infected(), node_is_latent(),
node_is_recovered() from {migraph}node_is_max(), node_is_min(),
node_is_random() from {migraph}tie_is_bridge(), tie_is_loop(),
tie_is_multiple(), tie_is_reciprocated() from
{migraph}tie_is_feedback()tie_is_max(), tie_is_min() from
{migraph}tie_is_random()scale_edge_color_centres(),
scale_edge_color_ethz(),
scale_edge_color_iheid(),
scale_edge_color_rug(),
scale_edge_color_sdgs()
autographr() now provides legends by default where
multiple colours are used (closes #52)autographs() now labels legends correctly for binary
variables (closes #38)autographs() now graphs just the first and last
networks in a list (closes #45)autographs() now includes an option whether the layout
should be based on the first, last, or both of two networks (closes
#48)ison_konigsberg to
ison_koenigsberg and named the bridgesison_algebra now in long multiplex formatison_karateka now weighted, anonymous members are named
by number, and “obc” variable renamed “allegiance”ison_lawfirm enlarged from 36 to 71 nodes and now
consists of three multiplex, directed networksison_southern_women names are now title caseison_hightech, a multiplex, directed network from
Krackhardt 1987ison_monastery datasets, three of which are
signed and weighted, and the other is longitudinal, from Sampson 1969
(closes #49)ison_potter datasets in a list of networks,
from Bossaert and Meidert 2013 (closes #47)ison_usstates data on the contiguity of US
states, from Meghanathan 20172023-12-17
as_tidygraph.diff_model() no longer creates names for
unlabelled networksto_waves.diff_model() now adds three logical vectors as
variables, “Infected”, “Exposed”, and “Recovered”
node_is_latent(),
node_is_infected(), and
node_is_recovered()autographr() now shapes seed, adopter, and non-adopter
nodes using a parallel to migraph’s node_adoption_time()
for
autographs() now colors susceptible, exposed, infected,
and recovered nodes correctlyautographd() now colors susceptible, exposed, infected,
and recovered nodes correctly2023-12-15
as_tidygraph() method for diff_model objectsas_siena() method for tidygraph objectsto_waves() now works on diff_model objects, add
attributes and namesis_multiplex() now recognises a tie/edge ‘type’
attribute as evidence of multiplexityigraph::is_bipartite() is superseded by
is_twomode()tidygraph::activate() is superseded by
mutate_ties() and similar functionsigraph::as_incidence_matrix() and
igraph::graph_from_incidence_matrix() with
igraph::as_biadjacency_matrix() and
igraph::graph_from_biadjacency_matrix()autographr() now plots diff_model objects, showing the
diffusion as a heatmap on the verticesautographs() and autographd() now utilise
network information in diff_model objects to provide better layouts
(closed #17)node_size in
autographd()many_palettes replaces iheid_palettetheme_ethz(),
scale_color_ethz()/scale_colour_ethz(), and
scale_fill_ethz() for ETH Zürichtheme_uzh(),
scale_color_uzh()/scale_colour_uzh(), and
scale_fill_uzh() for Uni Zürichtheme_rug(),
scale_color_rug()/scale_colour_rug(), and
scale_fill_rug() for Uni Gröningenison_physicians data that includes four,
multiplex networks with adoption data2023-12-06
run_tute()read_graphml() and write_graphml()
for importing and exporting graphml objects, mostly wrappers for igraph
functions.autographd() and autographs() can now be
used for plotting diffusion models.
to_waves() and autographd() to
account for ‘exposed’ nodes in diffusion models.hierarchical layout so that node name can be
specified for centering the layouttheme_heid() layoutison_starwars data, thanks
to coding by Yichen Shen and Tiphaine Aeby2023-11-15
run_tute()function to “fuzzy” match tutorial
names+.ggplot() method for visualising multiple plots
in the same panetheme_iheid for plotsscale_ family of functions for changing
colour scales in plotsautographr():
autographd() function2023-11-02
2023-11-01
as_igraph()
in accordance with upcoming updates to {igraph} package
(closing #27)to_mentoring functionautographr() related to
edge_size and edge_colorautographr()autographr()autographr()ison_friends, a one-mode network on character
connections of a popular TV series2023-10-25
generate examples leverage autographr()
againto_redirected.tbl_graph()print.tbl_graph() no longer mentions the object
classlayout_tbl_graph_concentric() now works with two-mode
networks, multiple levels for one-mode networks, and accepts new
vectorslayout_tbl_graph_multilevel() for laying out
multilevel networkslayout_tbl_graph_triad() and
layout_tbl_graph_quad() configurational layoutsison_starwars, a collection of seven weighted
interaction networks on a popular film franchiseison_networkers names are now in title case, not all
caps2023-10-19
run_tute() helper for quicker access to
{manynet} and {migraph} tutorialsextract_tute() for extracting the main code
examples from {manynet} and {migraph}
tutorialspurl = FALSE to tutorial chunks that are not
needed for extraction (thanks @JaelTan)run_tute() and
extract_tute()node_group and updated
documentation2023-10-11
{graphlayouts}, {ggforce}, and
{multiplex} to Suggestedto_galois() for transforming networks into
partially ordered Galois latticesautographr()autographr(),
closes #11autographr()autographr() now automatically bends arcs for
reciprocated ties when directed network is not too large/denseautographr() now accepts unquoted variables as
argumentsautographr() now uses
graphlayouts::layout_igraph_multilevel where
appropriateison_algebra now an anonymised network (again)2023-09-17
2023-09-17
{migraph} earlierison_lawfirm data from Lazega, see documentation
for more details2023-08-11
2023-08-11
thisRequiresBio() helper function
to download Bioconductor packagesison_konigsberg for illustrating Seven Bridges of
Konigsbergison_brandes2 and added potential modal type as
extra variable to ison_brandesison_bb, ison_bm,
ison_mb, and ison_mm into a list of networks
called ison_lateralscreate_explicit() for creating networks based on
explicit nodes and tiesdelete_nodes() for deleting specific nodesto_eulerian() function that returns a Eulerian
path network, if available, from a given networkis_ functions from
{migraph}
is_connected() to test if network is strongly
connectedis_perfect_matching() to test if there is a
matching for every node in the networkis_eulerian() to test whether there is a Eulerian
path for a networkis_acyclic to test whether network is a directed
acyclic graphis_aperiodic to test whether network is
aperiodiclayout_tbl_graph_alluvial() that places
successive layers horizontallylayout_tbl_graph_concentric()that places a
“hierarchy” layout around a circlelayout_tbl_graph_hierarchy() that layers the
nodes along the top and bottom sequenced to minimise overlaplayout_tbl_graph_ladder()that aligns nodes across
successive layers horizontallylayout_tbl_graph_railway that aligns nodes across
successive layers verticallytheme_iheid() function that themes graphs with
colors based on the Geneva Graduate Institute2023-06-20
{migraph}{migraph}2023-06-09
na_to_mean.data.frame()network_dims.network()2023-06-07
{migraph} package, adding the Make,
Manipulate, and Map functions to this package.dataprint.tbl_graph method that offers easy to
interpret informationread_*() functions,
e.g. read_edgelist()write_*() functions,
e.g. write_edgelist()
write_matrix() for exporting to matricescreate_*() functions,
e.g. create_lattice()
create_*() functions return tbl_graph
class objectsgenerate_*() functions,
e.g. generate_smallworld()ison_* network data,
e.g. ison_southern_womenas_*() functions, e.g. as_igraph()
as_edgelist.network()as_network.data.frame()as_network.tbl_graph()join_*() functions,
e.g. join_ties()add_*() functions,
e.g. add_node_attribute()
create_*() functions return tbl_graph
class objectsmutate_*() functions,
e.g. mutate_ties()
mutate_ties(), it is no longer necessary to
activate(edges)rename_*() functions,
e.g. rename_ties()is_*() functions, e.g. is_dynamic()
is_labelled() to work correctly with multiple
network formatsto_*() functions, e.g. to_mode1()
to_giant.network()to_directed() now a methodto_subgraphs() now returns a list of
tbl_graphsto_reciprocated() now works on edgelists, matrices,
tbl_graphs, and networksto_acylic() now works on matrices, tbl_graphs, and
networksfrom_*() functions, e.g. from_egos()
from_subgraphs()network_nodes()
network_dims() is now a methodautographr(), autographs(), and
autographd()layout_tbl_graph_concentric()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.