NEWS.md

migraph 1.3.4

2024-03-07

Measures

• Fixed DOI issue for Burchard/Cornwell paper

migraph 1.3.3

2024-03-06

Measures

• Added node_brokering_activity() and node_brokering_exclusivity() from Hamilton et al (2020)
• node_degree() now returns strength centrality (alpha = 1) for weighted networks by default
• node_redundancy() now works for weighted onemode and twomode networks (closed #292)
  • Matrix operations bring an approximately sixfold speed increase compared to vapply
• node_effsize() now works for weighted onemode and twomode networks
  • Matrix operations bring an approximately sixfold speed increase compared to vapply
• network_equivalency() now normalises weighted twomode networks (closed #291)

Members

• Added node_brokering() for identifying brokering roles from brokering activity and exclusivity
• node_roulette() now optimises group diversity based on historical interactions (Lai and Hao 2016)
  • Added more documentation about maximally diverse grouping problem
  • Matrix operations bring an approximately threefold speed increase compared to vapply
  • Perturbation helpers can be used also for blockmodelling (closed #38)

migraph 1.3.2

2024-01-25

Measures

• Updated network_scalefree() to work even when P scores are not available

Members

• Updated node_fluid() to work with different versions of {igraph}

migraph 1.3.1

2024-01-24

Package

• Completed significant documentation updates

Measures

• over_*() now reverts future plan on exit

Motifs

• node_brokerage_census() and network_brokerage_census() now treat two-mode networks correctly (closed #35)

Models

• test_random() now reverts future plan on exit
• test_permutation() now reverts future plan on exit
• network_reg() now reverts future plan on exit

migraph 1.3.0

2024-01-24

Package

• Migrated package repository to 'stocnet' organisation
• Significant documentation updates

Marks

• Migrated remaining marks functions to {manynet}

Measures

• Added network_change() to measure the Hamming distance between two or more networks
• Added network_stability() to measure the Jaccard index between two or more networks
• Added network_spatial() to measure spatial association (Moran's I, closes #209)
• Added node_deg() for a non-normalised version of node_degree()
• node_degree() now normalises strength centrality
• Added node_induced() to measure nodes' induced betweenness centralities
• Added node_flow() to measure nodes' flow betweenness centralities (closes #195)
• Added node_information() to measure nodes' information or current-flow closeness centralities (closes #194)
• Added node_multidegree() to measure the ratio of one type of tie in a multiplex network to another
• Added node_posneg() measures the PN centrality of signed networks

Members

• Fixed #287 by making node_tie_census() and node_triad_census() work with the new multiplex format in {manynet} (which relies on a "type" tie attribute rather than multiple tie attributes)
  • This restores functionality to node_structural_equivalence() and node_regular_equivalence()
  • Incidental speed improvements
• Added node_fluid() community detection algorithm
• Added node_roulette() for identifying groups of nodes that haven't interacted before

Models

• Migrated play_*() functions to {manynet}, including as_diffusion() and the diffusion tutorial
• Added specification advice to network_reg() so that specifications that include a 'sim' or 'same' effect for a variable are encouraged to also include more elementary 'ego' and 'alter' effects
• network_reg() now ignores the LHS of the formula for uniplex networks

migraph 1.2.1

2023-12-17

Measures

• Fixed documentation issues in node_adoption_time()

migraph 1.2.0

2023-12-17

Marks

• Added node_is_infected() to identify infected nodes at given time
• Added node_is_latent() to identify infected nodes at given time
• Added node_is_recovered() to identify infected nodes at given time
• Added node_is_fold() for identifying nodes that are occupying structural folds
• Dropped last is_*() functions from migraph to avoid unnecessary conflicts with manynet at startup
• Improved 'mark_nodes' documentation

Measures

• Added network_hazard() for calculating the hazard rate for each time point of a diff_model object
• node_adoption_time() now works with incomplete diffusions
  • Fixed bug with named vectors
• node_exposure() now uses node_is_infected() for more flexibility
• node_thresholds() now works with incomplete diffusions
  • Adds exposure data where not provided

Members

• node_adopter() now correctly identifies non-adopters

Models

• play_diffusion()
  • Now records only the first exposure event until susceptible again
  • Now uses node_is_exposed() and node_exposure() internally
  • Made play_diffusion() code easier to understand and debug
  • Added some tests for play_diffusion()

migraph 1.1.9

2023-12-13

Marks

• Added node_is_exposed() function to mark nodes (logical) that are currently exposed to diffusion content in a network.

Measures

• Fixed bugs for network_reproduction() function that calculates the R-nought value.
• Added network_immunity() function to calculate the Herd Immunity Threshold for the network.
• Added node_exposure() function to calculate the number of infected/adopting nodes to which each susceptible node is exposed.
• Added documentation for diffusion measures, separating documentation for node_*() and network_*() measures.

Models

• Added as_diffusion() function to convert a diffusion event table into a diff_model object.
• Added test_gof() function for testing goodness-of-fit in diffusion models.

Tutorials

• Updates to tutorial 7 (diffusion):
  • Added section on R-nought and Herd Immunity.
  • Fixed layouts for plots using autographs() and autographd() for diff_model objects.

migraph 1.1.8

2023-12-06

Measures

• Fixed bugs in diffusion measures.
  • Fixed node_thresholds() so that it infers nodes' thresholds from the amount of exposure they had when they became infected or exposed.
  • Updated node_adoption_time() and node_adopter() to return node_member and node_measure objects, which makes printing and summarising better.
  • Updated node_infection_length() and network_infection_length() which measures the average length nodes remain infected.

Members

• Added printing of membership class names if available in print method for node_member class.
• Added distributional statistics of the vector if no membership vector is assigned in summary method for node_member class.

Models

• Updated diff_model object to carry original network data for plotting.
• Updated play_diffusion() to forward exposure/contact information to the events table.

Tutorials

• Added plots for diffusion models in tutorial 7 using autographs() and autographd().

migraph 1.1.7

2023-11-15

Package

• Added diffusion measures to website.

Measures

• Fixed documentation issues for diffusion measures.

Marks

• Added node_is_mentor() for indicating nodes with high indegree.

Models

• Added 'minimising' distance option for segregation model choice.
• Changed 'satisficing' option in play_segregation() to sample randomly from those unoccupied options less than the desired threshold.

Tutorials

• Added multi-choice questions to tutorial 8.

migraph 1.1.6

2023-11-08

Measures

• Added first drafts of various diffusion measures: network_transmissability(), node_infection_length(), network_infection_length(), network_reproduction(), node_adoption_time(), node_adopter(), node_thresholds().

Models

• Fixed documentation for play_diffusion().
• Fixed bug in labelling in plot results for SIR models.

Tutorials

• Added plots using autographs() and elaboration for tutorial 7.

migraph 1.1.5

2023-11-02

Members

• Fixed documentation issue with summary.node_member()

Motifs

• Fixed documentation issue with node_census()

migraph 1.1.4

2023-11-01

Marks

• print.node_mark() and print.tie_mark() now allow infinite 'n' width

Measures

• print.node_measure() and print.tie_measure() now allow infinite 'n' width
  • Digit rounding is now fixed in print and summary methods

Members

• print.node_member() now prints the vector
  • Previous functionality is now available in summary.node_member()

migraph 1.1.3

2023-10-25

Tutorials

• Fixed bug in network setup in 'tutorial4' (Community)
• Fixed bug in blockmodelling interpretation in 'tutorial5' (Position)
• Added more to core-periphery section to 'tutorial6' (Topology)
• Added network resilience section to 'tutorial6' (Topology)

Measures

• Added network_richclub() to return a network's rich-club coefficient (closed #223)
• node_core() now offers eigenvector centrality-based rank selection in addition to degree-centrality
  • This can be selected with the argument method = "eigenvector"
• Added Krackhardt's graph theoretic dimensions of hierarchy measures, including
  • network_connectedness()
  • network_efficiency()
  • network_upperbound()
• Added node_eccentricity(), which wraps igraph::eccentricity()
• Added node_neighbours_degree(), which wraps igraph::knn()
• Added tie_cohesion() to measure how embedded ties are

Members

• Added node_louvain() community detection algorithm
• Added node_leiden() community detection algorithm
  • Note that this function optimises the Constant Potts Model rather than modularity

migraph 1.1.2

2023-10-18

Tutorials

• Added more code annotations in 'tutorial4' (Community)
• Elaborated 'tutorial5' (was named Equivalence, now Position)
• Chunks in tutorials that are incremental now hidden upon extraction using purl = FALSE argument

Members

• Improved printing of node_members and node_measures objects

migraph 1.1.1

2023-10-11

Package

• Added more questions to the Centrality tutorial (3)
• Added more instruction and more questions to the Community tutorial (4)

Measures

• Fixed scale, labelling, and other issues in plot.node_measure()

Members

• Added node_optimal(), node_infomap(), node_spinglass(), and node_leading_eigen() to extend the community detection options available in the package

migraph 1.1.0

Package

• Added Macports option to the README (closes #274, thank you @barracuda156)
• Updates to the Centrality tutorial

Measures

• Added node_outdegree(), node_indegree(), network_outdegee(), and network_indegree() wrappers
• Added network_reach()
• Added node_harmonic() and network_harmonic()
• Added node_pagerank()
• plot.node_measure() now returns a single plot for one-mode networks with a frequency histogram and a density overlay

Data

• Upgraded all old igraph data to work with most recent version

migraph 1.0.1

Measures

• Fixed backends in node_closeness() and node_betweenness() in preparation for an {igraph} deprecation (merci @maelle)

Models

• Fixed #272 by making test_random() and test_permutation() rely on graph dimensions rather than graph order (thank you finding this @rabenton)

Tutorials

• Fixed some defunct function names

migraph 1.0.0

Package

• Breaking changes by moving the making, manipulating, and mapping functions to {manynet}
  • All create_*() and generate_*() functions are now in {manynet}
  • All read_*() and write_*() functions are now in {manynet}
  • All as_*() and to_*() functions are now in {manynet}
  • Most is_*() functions are now in {manynet}
  • All add_*() and join_*() functions are now in {manynet}
  • Functions that grab metadata from network objects, e.g. network_nodes(), node_names(), and tie_weights(), are now in {manynet}
  • All autograph*() functions are now in {manynet}
  • {manynet} is now a Depends, but many dependencies removed or moved to {manynet}
• Most functions now expect .data as their first argument; previously it was object
• Moved data vignette (now a tutorial) and visualisation tutorial to {manynet}
• Updated README and pkgdown structure accordingly

Measures

• Added over_time() and over_waves() to measure (potentially parallelised) over split graphs
  • Added class construction and a plot method for resulting network_measures object
• Each of the four main types of centrality now get their own page of documentation
• Added node_alpha() for calculating alpha centrality, mostly just a wrapper for igraph::alpha_centrality()
• Added node_power() for calculating beta or Bonacich centrality, mostly just a wrapper for igraph::power_centrality(), though also correctly accounts for two-mode networks
• Renamed node_homophily() to node_heterophily(), which is more accurate and in line with the scale's direction
  • node_heterophily() now calculates EI indices in a faster, vectorised form, instead of the older, slower solution that calculated network_homophily() over all ego networks
• Renamed network_homophily() to network_heterophily()
  • network_heterophily() now ignores missing values
• network_congruency() is now more explicit about its data expectations

Models

• k_strict(), k_elbow() and k_silhouette() are now exported and documented
• Added play_segregation() for playing Schelling segregation models with various parameters
• Fixed some diff_model and diffs_model plotting irregularities
• Fixed bug in how merges were constructed as a distance matrix in cluster_concor()

Data

• Moved ison_ data to {manynet}

migraph 0.13.2

Package

• Updated README with better structuring and explanation
  • Also improved figure quality

Makes

• Added read_matrix() for importing CSVs of adjacency/incidence matrices
• Added read_dynetml() for importing DynetML .xml files (closed #261)

Manipulations

• Added list method for as_tidygraph() for merging nodelists and edgelists
  • Note that a named list is expected, with names "nodes" and "ties"
• Added igraph method for as_siena()
  • Note that this is a WIP proof of concept, and will currently only create the DV

migraph 0.13.1

Package

• Added hints, solutions, comments, and questions to equivalence and centrality tutorials
• Changed theme across all tutorials

Makes

• Fixed bug in read_pajek() where multiple networks/ties were causing an issue for partition assignment

Models

• Fixed bug in play_diffusion() relating to latency inversion

migraph 0.13.0

Package

• Added hints and questions to community tutorial
• Added diffusion tutorial

Marks

• Added is_aperiodic() for testing whether a network is aperiodic (the greatest common divisor for all cycles in the network is 1)
  • Note that for computational efficiency, this will check only up to a specified path length (by default 4)
• node_is_max() and node_is_min() now take a "rank" argument for selecting more than the first ranked maxima or minima

Manipulations

• Added several new functions for splitting networks into a list of networks
  • Added to_components() to return the components of a network as a list of networks
  • Added to_egos() to return the ego networks of a network as a list of networks
  • Added to_subgraphs() to return attribute-based subgraphs as a list of networks

Measures

• Added network_richness() and node_richness() for calculating the richness (a common diversity measure) of an attribute in a network

Models

• Extended play_diffusion() to include more compartment and transition options
  • The print method now tabulates the compartment sums per step
  • The summary method now presents the diffusion event list
  • The plot method now:
    • plots lines for S and I compartments, as blue and red lines respectively, if available or informs the user if no diffusion could be simulated
    • plots lines for E and R compartments, as orange and green lines respectively, if relevant
    • plots a bar graph behind showing the number of new infections per step
  • Added "transmissibility" parameter to allow for more probabilistic contagion, by default 1 (all contacts over the threshold result in contagion)
  • Added "latency" parameter to allow for an Exposed compartment to be included, by default 0 (no incubation period)
  • Added "recovery" rate parameter to allow for a Recovered compartment to be included, by default 0 (no recovery)
  • Added "waning" parameter to allow for returns to the Susceptible compartment, by default 0 (any recovered have lifelong immunity)
  • Added "immune" parameter to allow for issuing of targetted vaccinations or related
  • "thresholds" can now be proportions, in which case they are interpreted as complex
  • "seeds" is now 1 by default
• Added play_diffusions() for running a diffusion model multiple times
  • Note for accelerating documentation and tutorials, this is 5 by default, but for publication quality results this should be increased
  • A print method tabulates the compartment sums per step per simulation
  • A summary method tabulates the steps until complete infection (or recovery) for each simulation
  • A plot method visualises the loess for each compartment across all simulations
  • Note that this function uses {furrr} and so a multicore or multisession strategy can be used for parallelisation (but this only makes sense for many simulations)
• Added play_learning() for running a DeGroot learning model
  • A print method tabulates nodes beliefs at each step
  • A summary method informs how many steps it took until convergence or whether there was no convergence after t steps
  • A plot method visualises the belief trajectories for each node
• network_reg() now declares the reference category for nominal variables

Mapping

• Added autographs() for autoplotting lists of networks

migraph 0.12.6

Package

• Changed tutorial naming structure to numeric
• Made all existing tutorials solution oriented
• Converted visualisation vignette into tutorial
  • Added further instruction as to how to change e.g. node_color colors
• Converted centrality vignette into tutorial
• Converted regression vignette into tutorial
  • Added a lot more interactivity to regression tutorial
• Deleted vignette instructions off of the README
• Added some core/coreness aspects to topology tutorial

Manipulations

• mutate() now works with igraph objects

Marks

• Added node_is_random() for selecting n nodes at random

Models

• Added first draft of (SI) play_diffusion() model
  • Added diff_model class, together with print, summary, and plot methods

migraph 0.12.5

Package

• Added topology tutorial

Makes

• Fixed integer recognition bug in generate_random()

Manipulating

• Added more similarity options for projection (to_mode1() and to_mode2())
• Fixed bug in to_redirected.igraph() where routing through an edgelist caused problems

Measures

• Elaborated documentation on modularity
• Added network_scalefree() for returning power law alpha/exponent
  • A message is given if the KS p-value is less than 0.05

Data

• Added ison_lotr dataset for examples using interactions among Lord of the Rings characters in the books

migraph 0.12.4

Package

• Converted 'visualisation' vignette to a learnr tutorial
• Deleted troublesome URLs to correlatesofwar.org
• Brokerage census gets their own documentation page

migraph 0.12.3

Package

• Converted 'community' vignette to a learnr tutorial
• Converted 'equivalence' vignette to a learnr tutorial

Motifs

• Added node names to node_motif class where available
• Added node_brokerage_census() and network_brokerage_census() for counting Gould-Fernandez brokerage roles

migraph 0.12.2

Package

• Fixed several typos in the centrality vignette and reexported figures
• Added community detection vignette

Make

• create_lattice() now conforms to other create_*() functions in how it interprets "n"
  • from an inferred "n" for a one-mode network, it will create a transitive lattice of as even dimensions as possible
  • for a two-mode network, this depends on how balanced the two modes are, and is still a work in progress... (WIP)

Marks

• Added is_eulerian() for a logical expression of whether the network has an Eulerian path

Measures

• network_smallworld() now takes a method argument for different ways of calculating a small-world coefficient
  • "omega" (the new default) offers a better range, 0 to 1, than the previous (now "sigma") metric.
  • "SWI" is also included and offers a 0 to 1 range, but where 1 may not be realisable
• Added node_diversity() for calculating heterogeneity among each nodes' ego network
• Added node_homophily() for calculating homophilous ties among each nodes' ego network
• Added node_reciprocity() for calculating each node's reciprocity
• Added node_transitivity() for calculating each node's transitivity/clustering

Memberships

• Added wrappers for several community detection algorithms from igraph, unlike tidygraph these can operate on objects directly
  • Added node_walktrap()
  • Added node_edge_betweenness()
  • Added node_fast_greedy()

Mapping

• Reversed blue/red colour assignment for binary variables

migraph 0.12.1

Manipulations

• to_twomode() now returns an undirected network
• Added to_anti() for obtaining the complement of the given network
  • Note that unlike the implementation in {igraph}, this respects two-mode constructions

Marks

• Added is_perfect_matching() for a logical expression of whether the maximum matching of a network is also perfect
• Added node_is_core() for a logical vector of which nodes are members of the core

Measures

• node_degree() now has an additional parameter for trading off between degree and strength in the case of weighted networks
• Added node_power() for Bonacich power centrality for both one- and two-mode networks (closed #193)
• Tie centrality measures now have their own help page (WIP)

Mapping

• Fixed autographr() tests to work with new version of {ggraph} (closed #247, thanks @henriquesposito)

migraph 0.12.0

Package

• graph_*() functions now renamed to network_*() for terminological consistency
• Added p2visualization vignette
  • more motivation re Tufte and Brandes et al
  • an overview on key multimodal layouts
  • a few demonstrations of {patchwork} functionality

migraph 0.11.4

Package

• Added igraph/migraph layout comparison to README

migraph 0.11.3

Package

• Fixed CRAN LaTeX issue relating to underscores in manual figures

Mapping

• Fixed bug in plotting space coordinates for named two-mode networks
• Suppressed messages relating to 'graph' class being defined by multiple packages

migraph 0.11.2

Package

• Filled in some further documentation
• Dropped some older defunct functions

Measures

• Renamed graph_blau_index() to graph_diversity()
• Renamed graph_ei_index() to graph_homophily()

Mapping

• Fixed bug with autographr()'s "node_group" argument

migraph 0.11.1

Package

• Fixed documentation issues (URLs, equations)

migraph 0.11.0

Package

• Reference and articles tabs on package website now called "Function Overview" and "Practical Lessons" respectively
• Reinstated equivalence and blockmodelling vignettes
• All vignettes now precompiled to avoid CRAN issues

Manipulation

• Added as_graphAM() methods for all migraph-consistent object classes so {Rgraphviz} can be used effectively
• Added as_igraph(), as_tidygraph(), and as_network() methods for {RSiena} sienaData objects (thanks @JaelTan, closed #94)
• Added as_edgelist() and as_matrix() methods for network.goldfish class objects
• The "twomode" argument in as_matrix() is now NULL by default, allowing both one-mode and two-mode coercion
• to_mode1() and to_mode2() now take an extra argument to produce weighted projections by different "similarity" measures
  • "count" (the default) returns a raw count of the coincidence of nodes in the specified mode with nodes of the other mode
  • "jaccard" (Jaccard index) offers a measure of opportunity weighted by participation
  • "rand" (Simple Matching Coefficient) offers a measure of behavioral mirroring
  • "pearson" (Pearson's correlation) and "yule" (Yule's Q) offer correlation coefficients for valued and binary data, respectively
  • These options work for edgelists, matrices, igraph and tidygraph, and network objects
• Added to_matching() methods to transform a two-mode network or network with some other (binary) "mark" attribute into a network of matching ties
• Renamed to_main_component() to to_giant() to be more space efficient
  • Added methods for edgelists and matrices
• Added two-mode application for to_blocks() (closed #242)
  • Fixed bug in to_blocks() where NA blocks couldn't be subsequently coerced
• Filled in a number of S3 methods
  • to_blocks(), to_subgraph(), and to_ties() are now S3 methods, returning objects of the same class as given
  • Added to_onemode() method for matrices
  • Added to_twomode() methods for igraph, tidygraph, and network
  • Added network methods for to_named(), to_redirected(), to_uniplex(), and to_unsigned()
  • Added edgelist methods for to_undirected() and to_uniplex()
  • Added matrix method for to_uniplex()
• Fixed bug where to_unweighted() didn't respect the "threshold" specified

Marks

• Fixed eternal loop bug where node_mode() couldn't produce a "mark" class object
• Fixed bug where node names/labels were not being added to mark objects
• Fixed bug in is_twomode() where labelling information was being ignored

Measures

• graph_core() now runs node_core() (see below) if no "membership" vector is provided

Membership

• Added node_core() for partitioning nodes into core and periphery memberships
• Fixed floating point bug in k_strict()

Models

• Added "tertius" effect for network_reg()
• "ego" and "alter" effects now work better for two-mode networks in network_reg()

Mapping

• Added "hierarchy" and "alluvial" layout methods
• Added "railway" and "ladder" layout methods (closed #125)
• Added "concentric" layout method
• Restructured autographr() to improve future debugging and development
• autographr() now rotates labels for partitioning layouts, including "concentric", so that they are readable and overlap less
• Fixed gglineage() to use "alluvial" layout and better position nodes on the x-axis

Data

• mpn_cow_igo now includes "polity2" scores
• Added visualisations to some ison_ and mpn_ data documentation (closed #237)

migraph 0.10.6

Package

• Fixed URL error in a vignette

migraph 0.10.5

Package

• Dropped vignettes for now to ensure package makes it on to CRAN

migraph 0.10.4

Package

• Fixed some URL issues for CRAN

Manipulation

• Split to_*() functions into reformatting (changing properties) and transforming (changing dimensions) documentation

migraph 0.10.3

Package

• Updated the DESCRIPTION and CITATION
• Renamed edge_*() to tie_*() to offer more (SNA) consistent vocabulary
• Added DOIs to as much data and documentation as possible (closed #236, thanks @JaelTan)
• Some further rationalisation of the documentation
• Dropped visualization vignette for now

Manipulation

• Added methods for converting network.goldfish objects (and linked events and nodelists) to migraph-compatible objects (closed #96)
• Renamed add_node_attributes() to add_node_attribute() and add_edge_attributes() to add_tie_attribute()

Marks

• All is_*() are now considered graph-level 'marks'
• Added 'node_mark' and 'tie_mark' classes with printing methods (closed #233)
• Added node_is_isolate() for marking isolates
• Added node_is_max(), node_is_min(), tie_is_max(), tie_is_min() for converting 'measures' into 'marks'

Measures

• Printing 'node_measure' class objects now is prettier, extending the width of the console, indicating how many additional observations, and separates out each mode (closed #232)

Motifs

• Added print method for graph_motif (fixed #234)

Memberships

• Equivalence examples now \dontrun

Models

• cluster_concor() and cluster_hierarchical() are now exported

Mapping

• autographr() no longer requires "highlight_measure" and "identify_function" arguments as users can now convert 'measures' to 'marks' and use these for "node_color" or "edge_color"

Data

• Added prints of each data object to @format for more consistent documentation
• Added ison_brandes2 dataset, a two-mode version of the original one-mode dataset
• Added mpn_cow_trade and mpn_cow_igo datasets (thanks @JaelTan)
• Fixed non-unique names in mpn_elite_mex

migraph 0.10.2

Memberships

• Further shortened equivalence examples

migraph 0.10.1

Measures

• Added node_reach() for calculating reach centrality (closed #196)
• Separated (again) centrality and centralisation documentation

Memberships

• Shortened equivalence examples

migraph 0.10.0

Package

• Reduced package dependencies by 5
  • {concaveman}, {ggdendro}, {oaqc} are now Suggests; the user is prompted to install them when required in autographr(), plot.member(), and node_quad_census() respectively
  • {stringr} and {tibble} replaced with base or other code and therefore no longer necessary
• Relabelled scripts to follow website function structure
  • Added @family tags for improved cross-referencing
  • Added a lot more references/sources
• README elaborated, including listing functions and data in the package
• Switched to S3 classes as outputs for most functions
  • Several methods, e.g. print(), plot(), summary(), have been added for them (see appropriate sections below)

Making

• All create_ and generate_ functions now:
  • work when n passed an existing network
  • work with two-mode networks, including create_tree(), generate_smallworld(), generate_scalefree()
  • return undirected network by default
• Some create_ functions can now take a membership vector or split into equal partitions by default
  • create_components() no longer accepts a number of components, instead relying on the membership vector
  • Added create_core() for creating core-periphery graphs
• generate_random() now inherits attributes from any network

Manipulation

• Added a couple of to_ functions useful for working with networks of different types
  • Added to_redirected() for adding or swapping direction to networks (closed #219)
  • Added to_blocks() for reducing a network down by a membership vector; blockmodel() and reduce_graph() are now deprecated
  • to_multilevel.igraph() now only works on two-mode networks; returns the original network if passed a one-mode network
• Fixed some bugs in a number of is_ functions
  • is_signed.data.frame() and is_signed.matrix() now rely on new helper is.wholenumber() rather than misleading is.integer()
  • is_directed.igraph() and is_directed.matrix() now return FALSE for two-mode networks
  • is_connected() now returns result for strong components if directed and weak components if undirected
• as_igraph.data.frame() now infers third column as weight

Marks

• Added new set of functions that return logical vectors for nodes and edges:
  • edge_multiple(), edge_loop(), edge_reciprocal() moved from measures
  • Added edge_bridges()

Measures

• A new "edge_measure" S3 class has been added, along with print() and plot() methods
• Added summary.node_measure() method for printing a summary by a membership vector; summarise_statistics() is now deprecated
• All cohesion, connection, and diversity measures now return "graph_measure" class results
  • graph_components() now calculates strong components for directed networks else weak components
  • print.graph_measure() now correctly labels two-mode results where a vector is given
• Added new script for measuring features, including graph_smallworld()
  • Added graph_core() for calculating correlation of an observed network to a core-periphery network of the same dimensions (closed #39)
  • Added graph_factions() for calculating correlation of an observed network to a component network of the same dimensions (closed #40)
  • Added graph_modularity() for calculating modularity of an observed network, including modularity for two-mode networks (closed #144)
• Added new script for measuring structural holes, including node_constraint()
  • Added several additional measures of structural holes: node_bridges(), node_redundancy(), node_effsize(), node_efficiency(), node_hierarchy()
• node_betweenness() no longer needs nobigint argument; just uses default from {igraph}

Motifs

• Added "node_motif" S3 class for the output of node_*_census() functions
  • Added print.node_motif() for tibble-printing of census results
  • Added summary.node_motif() to summarise censuses by a membership vector, replacing group_tie_census() and group_triad_census(), which are now deprecated
• Added "graph_motif" S3 class for the output of graph_*_census() functions
• Added node_path_census() for returning the shortest distances from each node to every other node (closed #222)
• node_tie_census() now creates unique column names

Memberships

• Added new "node_member" S3 class for vectors of nodes' cluster memberships
  • The class hides a hierarchical clustering object as an attribute, so plot.node_member() replaces ggtree()
• Moved to an equivalence identification scheme that hides many of the technical aspects from users when unnecessary
  • Added node_equivalence() for identifying nodes' membership in classes equivalent with respect to some arbitrary motif census
    • "hierarchical" and "concor" now options for cluster within node_equivalence(); blockmodel_concor() is now deprecated (closed #123)
    • "elbow" now an option for k selection within node_equivalence(); ggidentify_clusters() is now deprecated
    • Added "silhouette" and "strict" options for k selection (closed #197)
    • Added option for k to be defined
    • There is now an argument distance passed to stats::dist that defines the distance metric (closed #36)
    • The argument range constrains the number of k evaluated by "elbow" and "silhouette" to improve parsimony and avoid long elapsed times
  • Added node_automorphic_equivalence() for identifying nodes' membership in automorphically-equivalent classes (closed #187)
  • node_structural_equivalence() replaces cluster_structural_equivalence()
  • node_regular_equivalence() replaces cluster_regular_equivalence()
• Added community identification scheme that mirrors equivalence identification in many respects
  • Added node_kernaghinlin() for identifying nodes' membership in communities based on the Kernaghin-Lin algorithm (thank you, @jaeltan, closed #198)
• Added connected identification scheme that mirrors equivalence identification in many respects
  • Added node_coreness() for nodes' k-core score (closed #200)
  • Added node_strong_components() and node_weak_components() for more direct calls; node_components() now calculates strong components for directed networks else weak components

Models

• A single "graph_test" S3 class replaces "cug_test" and "qap_test"
  • plot.graph_test() replaces plot.cug_test() and plot.qap_test()
  • Added print.graph_test() method
• plot.matrix() now plots adjacency/incidence matrices with sorting and horizontal/vertical lines if a membership vector is provided, effectively replacing plot.block_model()

Mapping

• autographr() can highlight nodes that max (by default) some measure (thank you, @BBieri, closed #224)
• Added layout_tbl_graph_stressgrid() as an extra option
• ggatyear() is deprecated

Data

• ison_algebra's edge attributes now named "friends", "social", and "tasks"

migraph 0.9.3

Package

• Trialling {roxytest}
• Updated favicons
• Updated several vignettes
  • Closed #154 by building out data vignette
  • Updated centrality vignette with more modern plotting
• Added some more informative documentation families

Making

• Folded m argument into p for generate_random(), p can now be passed an integer to indicate the number of ties the network should have

Manipulation

• Refactored to_edges() to be ~26 times faster on average
• Corrected edge labelling in to_edges()
• Using to_subgraph() now instead of dplyr::filter() or strain()

Mapping

• Layouts now use times argument instead of maxiter

Measures

• Renamed "measure" class "node_measure" and added "graph_measure" class with print method
• Overhaul of centrality measures
  • Centrality and centralization measures now return normalized scores by default, normalized is now the second argument
  • directed and weights arguments have been removed and are now imputed, if this is undesired please use to_*() first
  • node_degree() now calculates strength centrality if network is weighted
  • node_eigenvector() and graph_eigenvector() both work with two-mode networks
  • Added edge_degree() and edge_eigenvector(), which both just apply the corresponding nodal measure to the edge graph
• edge_mutual() renamed to edge_reciprocal()
• Closed #225 by adding graph_assortativity()

Modelling

• Closed #151 with blockmodel coloring for signed graphs

Data

• Dropped weight from mpn_elite_mex
• Dropped direction from ison_brandes

migraph 0.9.2

Package

• Streamlined some examples to reduce testing time
• Fixed a DOI URL for Ortmann and Brandes reference

migraph 0.9.1

Package

• Streamlined some tests to reduce testing time

Manipulation

• is_multiplex.igraph() and is_multiplex.tbl_graph() now checks for multiple edge attributes
• Added strain() as wrapper for {dplyr}'s filter(), renamed to avoid conflicts with {stats}

Data

• ison_algebra now unlabelled

migraph 0.9.0

Package

• Recognised contributors Henrique Sposito and Jael Tan
• Updated dependencies
  • {readxl} is now suggested, but required if importing from an Excel sheet
  • {patchwork} replaces {gridExtra} to make for more concise multiplot visualisations
  • {dplyr} also serves to export {magrittr}'s pipe
  • {RColorBrewer} has been dropped and the Dark2 discrete set of colors is now internal
• README has been updated and now compiles from a .Rmd file
• Changed website theme to 'superhero'
• All prior deprecated functions have been removed
• Increased testing to ~80% (closed #126, #212)
• CITATION has been updated too

Making

• Moved to @describeIn documentation (closed #215)
• Distinguished directed and direction arguments in some functions; whereas directed is always logical (TRUE/FALSE), direction expects a character string, e.g. "in", "out", or "undirected"
• generate_permutation() now has an additional logical argument, with_attr, that indicates whether any attributes from the original data should be passed to the permuted object
• All create_*() functions now accept existing objects as their first argument and will create networks with the same dimensions
• read_pajek() now imports nodal attributes alongside the main edges
• read_ucinet() now enjoys clearer documentation

Manipulation

• All as_*() functions now retain weights where present; if you want an unweighted result, use is_unweighted() afterwards
  • as_edgelist.network() now better handles edge weights
  • as_matrix.igraph() now better handles edge signs
• Pivoted to S3 methods for most manipulation functions for better dispatching and performance
  • Added matrix, data.frame, network, igraph, and tbl_graph methods for is_twomode(), is_directed(), is_weighted(), is_labelled(), is_signed(), is_multiplex(), is_complex(), and is_graph()
  • Added data.frame methods for as_edgelist(), and to_unweighted(), and improved the data.frame method for as_matrix()
  • Added data.frame and matrix methods for to_named() and to_unsigned()
• Added to_edges() for creating adjacency matrices using a network's edges as nodes
• Renamed project_rows() and project_cols() functions to to_mode1() and to_mode2(), which is both more consistent with other functions naming conventions and more generic by avoiding the matrix-based row/column distinction
• Added node_mode(), which returns a vector of the mode assignments of the nodes in a network
• Added edge_signs(), which returns a vector of the sign assignments of the edges in a network

Mapping

• Added 'visualization' vignette that starts to introduce how autographr() works and how {ggraph} extends this
• autographr() now incorporates ggidentify() functionality (closed #150)
• {patchwork} is now used to assemble multiple plots together
• Fixed #204 layout issues with ggatyear()

Measures

• Added new measure class and directed most node_*() functions to create objects of this class
  • A print method for this class prints an abbreviated vector (the full vector is always still contained within the object) and prints elements from both modes in the event that the original object was two-mode (closed #202)
  • A plot method replaces ggdistrib() and offers "hist" and "dens" methods for histograms and density plots respectively
• Added some edge-based centrality measures (closed #165)
  • edge_betweenness() wraps {igraph}'s function of the same name
  • edge_closeness() measures the closeness centrality of nodes in an edge adjacency
• Added several more measures of connectedness
  • node_cuts() identifies articulation points (nodes) in a network
  • edge_bridges() identifies edges that serve as bridges in a network
  • graph_cohesion() measures how many nodes would need to be removed to increase the number of components (closed #192)
  • graph_adhesion() measures how many edges would need to be removed to increase the number of components
  • graph_length() measures the average path length
  • graph_diameter() measures the longest path length
• Removed node_smallworld() and added graph_smallworld(), which works with both one- and two-mode networks (fixed #214)

Motifs

• Added some guidance to the naming convention used in node_quad_census()

Models

• Extended network_reg()'s formula-based system
  • network_reg() can now handle binary and multiple categorical variables (factors and characters, closed #211);
  • network_reg() can now manage interactions specified in the common syntax; var1 * var2 expands to var1 + var2 + var1:var2 (closed #163)
  • dist() and sim() effects have been added (closed #207)
• network_reg() now employs logistic regression to estimate a binary outcome and linear regression to estimate a continuous outcome (closed #184)
• network_reg() now uses Dekker et al's semi-partialling procedure by default for multivariate specifications (closed #206), defaulting to y-permutations in the case of a single predictor (closed #208)
• Added parallelisation to Monte Carlo based tests
  • Refactored network_reg(), relying on {furrr} for potential parallelisation and {progressr} for progress reports (closed #185, #186)
  • Refactored test_random() and test_permutation(), relying on {furrr} for potential parallelisation and {progressr} for progress reports; note that nSim argument now times (closed #199)
• Added {broom} S3 methods for netlm and netlogit class objects (closed #183)
  • tidy() extracts coefficients and related values
  • glance()extracts model-level values such as R^2
• Added plot method for netlm and netlogit class objects (closed #216), which plots the empirical distribution for each test statistic, indicates percentiles relating to common critical values, and superimposes the observed coefficients
• Added plot method for cug_test and qap_test class objects, which plots the empirical distribution, highlighting tails beyond some critical value (closed #213), and superimposing the observed coefficient and, possibly, 0
• Relabelled some classes to avoid loading conflicts with {sna}
  • print.block_model() replaces print.blockmodel()
  • plot.block_model() replaces plot.blockmodel()
• Reduced the number of simulations used in tests, examples, and vignettes to avoid CRAN warnings

Data

• Updated several names of datasets for consistency and conciseness
  • ison_southern_women instead of southern_women
  • ison_brandes instead of brandes
  • ison_networkers instead of ison_eies
  • ison_algebra instead of ison_m182
  • ison_adolescents instead of ison_coleman
• Extended several datasets
  • mpn_elite_mex is extended with data from Pajek and with help from Frank Heber
  • ison_networkers becomes named with information from {tnet}
• Elaborated documentation of most mpn_* and ison_* datasets, including references/sources

migraph 0.8.13

Modelling

• Closed #149 by adding extra column to node_tie_census in cluster_structural_equivalence() for isolates
  • Note that this renders all isolates structurally equivalent

migraph 0.8.12

Package

• Closed #168 by adding {patchwork} to suggested packages in DESCRIPTION
• Updated function reference page on website

Manipulation

• Updated add_ functions
  • Closed #178 by adding name to existing edges when further edges added in mutate_edges()
  • Closed #179 by inferring an attribute vector is for one of the two modes where possible in add_node_attributes()
• Added is_ methods: is_multiplex(), is_uniplex(), is_acyclic()
• Added edge_ functions to identify edges by properties: edge_mutual(), edge_multiple(), edge_loop()

migraph 0.8.11

Import and export

• Fixed #172 by removing redundant header argument in read_nodelist() and read_edgelist()

Package

• Fixed #173 by extending as_network() method to convert correctly form an {igraph} to a {network} object.
• Removed ggraphgrid() documentation

migraph 0.8.10

Import and export

• Replaced xlsx dependency in read_edgelist() and read_nodelist() to readxl to avoid Java dependency
• Replaced xlsx dependency in write_edgelist() and write_nodelist() to avoid Java dependency
  • Note that these functions will now export to .csv rather than .xlsx

Manipulation

• Fixed direction recognition bug in as_network(), as_igraph(), and is_directed()

migraph 0.8.9

Package

• Closed #139 by adding vignette on importing and connecting data

Import and export

• Added read_ and write_ functions and updated documentation
  • Closed #137 by adding read_edgelist() for importing edgelists from Excel and csv files
  • Closed #170 by adding read_pajek() for importing .net and .paj files
  • Added write_edgelist(), write_nodelist, write_pajek(), and write_ucinet() for exporting into various file formats (Excel, csv, Pajek, and UCINET)
  • Closed #140 by adding links to further data resources

Manipulation

• Added is_graph() to check if an object is a graph or not
• Extended as_network() to retain attributes
• Fixed bugs in as_ and to_ functions
  • Fixed bug in as_ functions to convert from dataframes instead of tibbles
  • Fixed bug in conversion from network to igraph object in as_igraph() function
  • Fixed bug in to_undirected() function to work with network objects
  • Fixed bug in to_main_component() function so that it retains vertex attributes in network objects
• Added edge_attribute() to grab a named edge attribute from a graph/network
• Updated to_unweighted() to prevent conversion of network object into igraph object when deleting weights

Measures

• Closed #143 by adding nodal summary by cluster function summarise_statistics()

Modelling

• Fixed network_reg() example

Visualisation

• Closed #117 by updating the node/edge/arrow size limits in autographr()

migraph 0.8.8

Package

• Added start to network linear model part of practical 7 vignette
• Thanks to @BBieri for adding many tests and working on igraph<->network interchange

Data

• Added ison_eies dataset for use in practical 7 vignette

Manipulation

• The as_matrix() method for networks now works with two-mode and weighted networks
• The as_igraph() method for matrices now checks for weights independently of coercion
• The as_igraph() method for networks now works with two-mode and weighted networks
• The as_network() method for matrices now works with two-mode and weighted networks
• The as_network() method for edgelists, igraph, and tidygraphs now works with weighted networks
• Added to_unnamed() method for edge lists
• Added to_simplex() method for matrices
• Added to_main_component() method for networks
• Added to_multilevel() method for matrices
• mutate_edges() now coalesces rows of edges

Measures

• Fixed bug where clusters were not being reported in the correct order in graph_blau_index()

Modelling

• Fixed one-mode bug with generate_permutation() and thus test_permutation()
• Renamed netlm() to network_reg() to avoid frustrating conflicts
  • network_reg() now accepts migraph-consistent objects
  • network_reg() now accepts formula terms such as ego(), alter(), and same()

migraph 0.8.7

Package

• Added new issue templates and refined the wording in existing templates
• Improved documentation across many help pages
• Closed #146 by adding vignette on homophily

Data

• Added generate_permutation() which takes an object and returns an object with the edges permuted, but retaining all nodal attributes
• Made generate_random() also work with an existing object as input, in which it will return a random graph with the same dimensions and density
• Consolidated data scripts

Manipulation

• Added mutate_edges() for adding new edges as attributes to existing edges in an object

Measures

• Closed #159 by fixing bug in graph_blau_index()
• Closed #157 by fixing bug in graph_ei_index()
• Closed #156 and #158 by fixing bugs with test_random() (defunct test_cug())

Visualisation

• Closed #148 and #153 by making all autographr() arguments take variable names in quotation marks

migraph 0.8.6

Package

• Closed #75 by updating the README

Manipulation

• Added some functions for grabbing key information from objects
  • node_names() for quickly accessing node labels
  • node_attribute() for quickly accessing a certain nodal attribute
  • edge_weights() for quickly accessing edge weights
  • graph_nodes() for quickly accessing a count of nodes in the graph, note that for two-mode networks this will be a vector of length 2
  • graph_edges() for quickly accessing a count of edges in the graph
  • graph_dimensions() is currently a copy of graph_nodes()
• Added some functions for adding key information to objects
  • add_node_attributes() for adding particular nodal attributes
  • add_edge_attributes() for adding edges from another graph
  • copy_edge_attributes() for copying all nodal attributes from another graph
• Improved twomode and weighted handling of several functions

Measures

• Added diversity functions
  • graph_blau_index() for summarising diversity of an attribute in a network or group
  • graph_ei_index() for summarising diversity of an attribute over a network's ties

Modelling

• Closed #119 by adding node_quad_census(), especially useful for two-mode blockmodelling
• Closed #95 and #120 by adding graph_mixed_census()
• Closed #97 by adding test functions
  • test_random() carries out a conditional uniform graph (CUG) test
  • test_permutation() carries out a quadratic assignment procedure (QAP) test

Visualization

• Closed #135 by reexporting aes() from {ggplot2}
• Added node_shape option to autographr()

migraph 0.8.5

Package

• Updated various URLs in the vignettes to pass CRAN tests
• Reduce number of layout examples to avoid examples taking too long to run

migraph 0.8.4

Classes

• Closed #128 by adding as_edgelist() methods for converting other objects into edgelists
  • Note that this currently returns a tibble
• Using to_unnamed() on 'network' objects now operates on them directly
• Elaborated to_ documentation significantly
• Fixed bug in to_onemode() that was tripping blockmodel() on networks that are already one-mode
• Added is_connected() to test whether network is connected, method = argument can be specified as weak or strong

Data

• Added create_tree() and create_lattice(), and made create_star() a bit faster for one-mode networks
• Added generate_smallworld() and generate_scalefree(), though only for one-mode networks currently

Measures

• Added rounding to centralization measures, by default =2
• Closed #109 by adding centrality vignette

Modelling

• Added graph_dyad_census() for more graph profile options
• Fixed bug with blockmodel_concor() when an object was of class 'igraph' but not 'tbl_graph'
• Fixed bug in how blockmodel() was treating two-mode networks
• Closed #116 by offering both "elbow" and "strict" methods for k-identification
  • Fixed bug in elbow method that biased heavily bipartitioned data
• Closed #131 by refactoring ggidentify_clusters() for speed
  • Takes now roughly half the time (see issue for details)

Visualization

• Added ggdistrib() for easy plotting of degree and other node score distributions
• Reexported ggsave(), xlab() and ylab() from {ggplot2} for easier plot annotation

migraph 0.8.3

Package

• Closed #108 by adding cohesion and community vignette

Classes

• Fixed #122 by retaining edge weights from igraph in as_matrix() where available

Measures

• Split graph_equivalency() into the same for two-mode networks and graph_congruency()for three-mode (two two-mode) networks
• Added option for graph_reciprocity() method
• Added graph_components() and node_components()

Modelling

• Fixed #113 by retaining node labels through census functions
• Closed #114 by transposing node_tie_census() output so that it's consistent with node_triad_census() and future node_census functions
• Closed #121 by renaming cluster_triad_census() to group_triad_census()
• Added group_tie_census()

Visualization

• Added option to autographr() for plotting convex/concave hulls
• Closed #124 by making ggraphgrid() a set of layout functions:
  • layout_tbl_graph_frgrid() or autographr(object, "frgrid") for snapping Fruchterman-Reingold to a grid
  • layout_tbl_graph_kkgrid() or autographr(object, "kkgrid") for snapping Kamada-Kawai to a grid
  • layout_tbl_graph_gogrid() or autographr(object, "gogrid") for snapping graph optimisation to a grid
  • ggraphgrid() has been deprecated

Data

• Fixed some ison_m182 documentation

migraph 0.8.2

Package

• Fixed CRAN package check dependencies bug where 'knitr' and 'rmarkdown' were listed as Imports without being used in the package

Classes

• Fixed bug where bipartite edge lists were not being recognised as a twomode network by as_igraph()
• Fixed bug where to_uniplex() was not returning a weighted graph

Models

• Fixed bug where blockmodel() was not retaining node names in all parts of the object structure

Visualization

• Closed #107 by choosing better brewer pallette (though note this is not a very deep pallette with only 9 colors)

Vignettes

• Expanded on the blockmodelling vignette with more intro, discussion, interpretation clues

migraph 0.8.1

Package

• Fixed codecov url bug
• Removed several package dependencies by moving plot_releases() to another package
• Made many dependencies more explicit
• Entire package 'linted'

Classes

• Added is_signed() to logically test whether the network is a signed network
• Added to_unsigned() for extracting networks of either "positive" or "negative" ties from a signed network
• Added tbl_graph methods for all other to_ functions
• Reexported activate() from {tidygraph}

Visualisation

• Added sensible plotting defaults for signed networks in autographr()
• Removed plot_releases() from this package

Measures

• Refactored graph_balance() to be much faster, following David Schoch's {signnet} package (see that package for further extensions)

Data

• Updated the edge 'sign' attribute of ison_marvel_relationships to be a double (-1/1) to be compatible with the new graph_balance() and {signnet}

migraph 0.8.0

Classes

• Fixed coercion to {igraph} from data frames and updated read script
• Added to_main_component() to extract the main component of a network
• Added to_onemode() for moving to multimodal igraph objects
• Added to_uniplex() method to delete edge types and their edges from multiplex networks
• Added to_simplex() method to delete loops from a network
• Added to_named() method for randomly naming unlabeled networks

Data

• Added ison_mm, ison_mb, ison_bm, and ison_bb projection illustration data
• Added ison_karateka community detection illustration data
• Added ison_marvel_teams and ison_marvel_relationships datasets
• Added ison_m182 dataset of friends, social and task ties between 16 anonymous students
• Renamed adolescent_society dataset to ison_colemanfor consistency
• Data now listed at the bottom of the website References page

Measures

• Added graph_eigenvector() for one mode networks
• Added graph_balance() for measuring structural balance
• Added node_tie_census(), node_triad_census(), cluster_triad_census(), and graph_triad_census()
• Separated out graph_clustering() into the cohesion measures graph_density(), graph_reciprocity(), graph_transitivity(), and graph_equivalence()
• Fixed node_smallworld() to use separated cohesion measures

Models

• Added blockmodel() which masks its {sna} namesake but has the advantages of working with two-mode networks and retaining node names where available
  • Added cluster_structural_equivalence() and cluster_regular_equivalence() as bases for blockmodelling
  • Added reduce_graph() for creating a network from a blockmodel
• Added first vignette on structural holes, structural equivalence and regular equivalence blockmodelling

Visualization

• Added autographr() for plotting graphs with sensible defaults
  • Uses a more contrastive discrete palette when some nodal attribute is given
  • Uses an alpha for edges, and edges will now be sized by edge weight, where available
  • Uses node labels, sans borders, where available
  • Uses different shaped nodes, and different fonts, for different node sets
  • Removed ggraphlabel() since core functionality now provided by autographr
• Added ability for ggidentify() to identify the node with the highest value of a specified node-level measure
• Added a couple of more specific visualization functions
  • Added ggatyear() for subsetting and plotting edgelists at year
  • Updated gglineage() to return a graph colored according to lineage
    • Added tick marks
• Added several more specific functions for diagnosing and visualising blockmodels
  • Added ggtree() for neatly visualising hierarchical clusters
  • Added ggidentify_clusters() for identifying which number of clusters is most appropriate following the elbow method
• Fixed bug related to ggraph::theme_graph() present in a few different visualisation functions

migraph 0.7.2

Data

• Added brandes dataset for teaching centrality measures
• Added adolescent_society dataset for teaching friendship paradox
• Added read_edgelist() for importing Excel-created edgelists directly

Visualization

• Added ggraphlabel() for one-function (1F) plotting label-based network graphs
• Added ggevolution() for 1F-plotting begin/end graph comparisons
• Added ggraphgrid() for 1F snap-to-grid graph layouts based on Fruchterman-Reingold or Kamada-Kawai
• Added ggidentify() for 1F identifying nodes with maximum scores based on some arbitrary function

Manipulation

• Added to_undirected() for symmetrising networks of all types
• Made existing to_ functions S3 methods

migraph 0.7.1

Classes

• Fixed Unicode char bug in coercion documentation

migraph 0.7.0

Classes

• Closed #100 by converting as_ coercion functions to S3 methods

  • Added a little more readable documentation
  • Fixed bug with as_matrix() weighting
  • Fixed bug with as_tidygraph()

Visualisation

• Closed #92 by adding gglineage() for graphing a citation network through time
• Closed #99 by adding ggevolution() for graphing two timepoints of the same network side by side
• Closed #102 by adding ggraphgrid() for locking a graph to a grid
• Slight improvements to plot.igraph() defaults

Analysis

• Added tidygraph lookups to node_ functions

migraph 0.6.6

Classes

• Fixed bug in as_matrix() with frame matrix by dropping (rarely necessary) functionality

  • Improved handling of weights column in three-column edgelists
  • Improved documentation of as_ functions

Visualisation

• Fixed bugs in plot_releases() with more graceful handling of http errors

  • Added online condition to example in documentation
  • Specified encoding for more silent operation

migraph 0.6.5

Package

• Removed unused package dependencies ({R6}, {ggraph})
• Avoided M1mac check issue by dropping sensitive netlm() test
• Added some tests

Classes

• Renamed binarise() to to_unweighted()
• Added to_unnamed() for unlabelling networks

migraph 0.6.4

Package

• Extended R version dependence back to 3.6.*

Classes

• Added binarise() for unweighting networks
• Fixed bug in as_tidygraph() when passed a tbl_graph directly

Visualization

• Added plot_releases() for more general use
• Fixed bug in plot.igraph() with layouts and one-mode graphs

migraph 0.6.3

Package

• Updated README

  • Updated installation instructions for CRAN
  • Added package functions overview

• Added CITATION details

Classes

• Separated coercion (previously conversion) and manipulation

• Added some more inter-class coercion tests

• Fixed bug in how as_network() sometimes coerced two-mode networks into much larger dimension matrices

• Added more is_ tests for class-independent property tests

  • Added is_weighted()
  • Added is_directed()
  • Added is_labelled()

Data

• Added @csteglich 's read_ucinet() and write_ucinet() functions

  • read_ucinet() offers a file-picker when file path unknown
  • read_ucinet() now imports to an igraph-class object by default, with an argument to allow other alternatives
  • write_ucinet() works with all migraph-compatible objects

• Updated mpn_bristol documentation

• Added create_star() function

  • Added in-star/out-star option via directed = argument
  • Updated create_ documentation

• Renamed sample_affiliation() to generate_random()

  • Rewrote generate_random() to be able to generate random one- or two-mode networks
  • Updated documentation

Models

• Added test for print.blockmodel()

migraph 0.6.2

2021-04-13

Package

• Reran usethis::use_mit_license("James Hollway"). MIT License file now contains only the standard two lines.
• Removed \dontrun from examples. netlm() now runs in <5 seconds.
• Fixed missing website item

migraph 0.6.1

2021-04-11

Package

• Closed #21 by elaborating DESCRIPTION file in preparation for CRAN submission
• Updated several old URLs in documentation

Classes

• Closed #85 by adding as_network() to coerce objects into network class
• Modified other coercion functions to also work with network class objects

migraph 0.6.0

2021-03-03

Package

• Moved package's Github repository from jhollway/ to snlab-ch/ organisation
• Trimmed some package dependencies and added others

Data

• Elaborated documentation for the remainder of the datasets

  • Now all datasets in this package are titled with whether they are one-mode, two-mode, or three-mode

Measures

• Fixed bug in graph_degree() where data was hard-coded in

Models

• Closed #18 by adding blockmodel_concor() for employing the CONCOR algorithm to blockmodel both one-mode and two-mode networks

  • Added a new print method for "blockmodel"-class objects based on the print.blockmodel() method in the {sna} package that also prints blockmodel results for two-mode networks consistently
  • Added a new plot method for "blockmodel"-class objects that leverages {ggplot2} for pretty plotting and that better inherits names from the underlying object

migraph 0.5.0

2021-02-06

Package

• Closed #81 by making {migraph} depend on R versions 4.0 or above
• Updated PR template

Classes

• Added functions for class conversion between migraph-consistent graph formats
• as_matrix() function to coerce objects into an adjacency or incidence matrix class
• as_igraph() function to coerce objects into an {igraph} graph class
• as_tidygraph() function to coerce objects into an {tidygraph} tbl_graph class
• Closed #79 by adding is_twomode() function to check whether network is two-mode on all object types

Data

• Renamed several datasets and elaborated their documentation

  • mpn_mexicanpower was renamed to mpn_elite_mex
  • mpn_powerelite was renamed to mpn_elite_usa_advice
  • mpn_opensecrets was renamed to mpn_elite_usa_money

• Reconstructed several creation functions to take universal (one-mode/two-mode) input: specifying n = 5 creates a one-mode network, while specifying n = c(5, 5) creates a two-mode network

  • Added create_empty()
  • Added create_complete()
  • Closed #65 by extending create_ring() to create rings of varying breadth
  • Closed #66 by extending create_components() (renamed from create_silos()) to create networks with varying numbers of components
  • Added sample_affiliation() for random two-mode networks
  • Removed create_match() and create_nest()

Measures

• Renamed centrality_ functions with node_ prefix and ensured they all also wrapped one-mode measures

  • centrality_degree() renamed to node_degree()
  • centrality_closeness() renamed to node_closeness()
  • centrality_betweenness() renamed to node_betweenness()
  • Closed #31 by adding node_eigenvector()

• Re-added node_constraint() for calculating Burt's constraint measure for one- and two-mode networks

• Re-added node_smallworld() for calculating Watts-Strogatz measure of small-worldness for two-mode networks

• Closed #32 by re-adding centralization functions for one- and two-mode networks

  • graph_degree() for degree centralization
  • graph_closeness() for closeness centralization
  • graph_betweenness() for betweenness centralization

• Re-added graph_clustering() for calculating (see Knoke et al 2021):

  • transitivity on one-mode networks
  • shared four-cycles on two-mode networks
  • congruent four-cycles on three-mode networks

Models

• Re-added netlm() for performing linear regression for multimodal network data

  • Closed #76 by changing netlm() to accept a formula-based input
  • Closed #77 by adding print.summary.netlm() for netlm() regressions

Visualization

• Closed #82 by re-adding a version plot.igraph() with sensible defaults for two-mode networks

migraph 0.4.1

2021-01-11

Package

• pkgdown now deploys after release
• Reexported a number of {igraph} and {tidygraph} functions for internal use
• Completed some convert_ and project_ documentation

Data

• Updated mpn_ data source references

Analysis

• Added centrality measures that take (and if necessary return) matrix, igraph, or tidygraph objects, and offer a correct normalization for two-mode networks

  • Added centrality_degree()
  • Added centrality_closeness()
  • Added centrality_betweenness()

migraph 0.4.0

2021-01-08

Package

• Package name change from roctopus to {migraph}

  • Closed #50 with new logo

• Now builds Linux binary too

Manipulation

• Added project_rows() and project_cols() to make it easier to project two-mode networks in different formats (matrix, igraph, tidygraph) into projected versions in the same format
• Closed #30 with conversion from different data frame formats, e.g. weighted and unweighted edgelists, into an incidence matrix with as_incidence_matrix()

Data

• Renamed data related to the book "Multimodal Political Networks" with "mpn_" prefix

roctopus 0.3.0

2020-11-06

Data

• Data creation updated for {tidygraph} defaults

  • Renamed create_lattice() to create_chain() to avoid conflicts with tidygraph::create_lattice()
  • Renamed create_poles() to create_silos()
  • Renamed create_random() to play_twomode() to avoid conflicts with tidygraph::play_bipartite()
  • Added export options for all create_ and play_ functions as tbl_graph (default), igraph, and base matrix
  • Updated tests for new create_ and play_ function names

• Packaged data updated for {tidygraph} defaults

  • Renamed packaged data from book to mpn_

roctopus 0.2.6

2020-08-18

Analysis

• Renamed twomode_netlm() to netlm2()
• Fixed various printing issues with netlm2()

Package

• Added tests for netlm2()
• Added tests for create_random()

Data

• Added opensecrets data
• Added powerelite data

roctopus 0.2.5

2020-07-21

Package

• Renamed data documentation scripts
• Added tests for most create_() functions
• Renamed test scripts and removed context() declaration
• create_nest() now exports matrix object

roctopus 0.2.4

2020-07-20

Package

• Added row_project() and col_project() functions to make it easier to remember project directions

roctopus 0.2.3

2020-07-19

Data

• Added mexicanpower dataset
• Added senate112 datasets
• Updated evs datasets to matrices

Package

• Added df_to_mat() function for converting regular adjacency and incidence data frames into matrices

roctopus 0.2.1

2020-07-17

Data

• Added ryanair dataset from Christopoulos 2006

Package

• Split workflow into pull-request and merge/push prompted actions
• Added codecov calculation to workflows

roctopus 0.2.0

2020-07-03

Data

• Added evs datasets from Knoke et al 2020

roctopus 0.1.0

2020-06-30

Data

• Added bristol dataset from Knoke et al 2020

roctopus 0.0.4

2018-12-20

Package

• Added hex sticker
• Updated README with more detailed installation information
• Pkgdown exports to https://jhollway.bitbucket.io/roctopus/

Analysis

• Added twomode_modularity() to calculate modularity in two-mode networks

Visualization

• Added plot_multilevel() that rotates a force-directed igraph plot in three dimensions to reveal multilevel structure
• Added plot_globalnet() to map a multilevel network on to a javascript, rotatable global

roctopus 0.0.3

2018-08-25

Analysis

• Added twomode_smallworld() to calculate observed/expected clustering, observed/expected path-length, and the observed/expected clustering ratio
• Added twomode_2x2() to identify dominance and coherence values for networks over time
• Updated twomode_coherence() to allow for introduction of second-mode attributes
• Renamed twomode_fragmentation() to twomode_components()

Visualisation

• Added plot_2x2() to plot values through a two-by-two matrix

roctopus 0.0.2

2018-08-14

Package

• Renamed package to roctopus
• Added two-mode @family tag to documentation

Analysis

• Added twomode_fragmentation() to calculate number of components in two-mode networks and identify their membership
• Added twomode_dominance() to allow an nodal attribute to be passed to the function to weight the centralization measure
• Added twomode_coherence() to calculate Jaccard similarity

Visualisation

• Added plot_twomode(), which wraps plot(igraph::graph_from_incidence_matrix()) with some useful defaults

  • coloured grayscale by default, with green/blue option
  • shaped circles and squares by default

roctopus 0.0.1

2018-07-30

Package

• Initialised package
• Added README.md file with instructions on how to install package
• Added LICENSE file and pointed to bug/issue tracker
• Added a NEWS.md file to track changes to the package

Analysis

• Added twomode_clustering() to calculate percentage of three-paths closed by four-paths
• Added twomode_lattice() to create two-mode lattices
• Added twomode_centralization_degree() to calculate degree centralization in two-mode networks, for rows, columns, or both
• Added twomode_centralization_between() to calculate betweenness centralization in two-mode networks
• Added twomode_constraint() to calculate network constraint in two-mode networks
• Added arrange.vars() to rearrange variables by position