“Intergraph” is an R package with coercion routines for netowrk data objects.
This is a short tutorial showing how to use functions in package “intergraph” using some example network data contained in the package.
Typographical conventions:
##
(two hash symbols).For example:
# This is some input code with output below
x <- 2+2
x
## [1] 4
RMarkdown source of this document can be found here. The most up-to-date version is always available as a package vignette.
Package intergraph contains four example networks:
exNetwork
and exIgraph
contain the same directed network as objects of class “network” and “igraph” respectively.exNetwork2
and exIgraph2
contain the same undirected network as objects of class “network” and “igraph” respectively.All four datasets contain:
label
with vertex labels. These are letters from a
to o
.label
with edge labels. These are pasted letters of the adjecent nodes.layout
storing a function that computes the vertex placement for plotting. It is a copy of layout.fruchterman.reingold
function from package igraph.We will use them in the examples below.
To show the data, first load the packages.
library(intergraph)
library(network)
## network: Classes for Relational Data
## Version 1.13.0 created on 2015-08-31.
## copyright (c) 2005, Carter T. Butts, University of California-Irvine
## Mark S. Handcock, University of California -- Los Angeles
## David R. Hunter, Penn State University
## Martina Morris, University of Washington
## Skye Bender-deMoll, University of Washington
## For citation information, type citation("network").
## Type help("network-package") to get started.
library(igraph)
##
## Attaching package: 'igraph'
##
## The following objects are masked from 'package:network':
##
## add.edges, add.vertices, %c%, delete.edges, delete.vertices,
## get.edge.attribute, get.edges, get.vertex.attribute,
## is.bipartite, is.directed, list.edge.attributes,
## list.vertex.attributes, %s%, set.edge.attribute,
## set.vertex.attribute
##
## The following objects are masked from 'package:stats':
##
## decompose, spectrum
##
## The following object is masked from 'package:base':
##
## union
Now, these are the summaries of the “igraph” objects:
summary(exIgraph)
## IGRAPH 3625f1a D--- 15 11 --
## + attr: label (v/c), label (e/c)
summary(exIgraph2)
## IGRAPH d2bf475 U--- 15 11 --
## + attr: label (v/c), label (e/c)
These are the summaries of the “network” objects:
exNetwork
## Network attributes:
## vertices = 15
## directed = TRUE
## hyper = FALSE
## loops = FALSE
## multiple = FALSE
## bipartite = FALSE
## total edges= 11
## missing edges= 0
## non-missing edges= 11
##
## Vertex attribute names:
## label vertex.names
##
## Edge attribute names:
## label
exNetwork2
## Network attributes:
## vertices = 15
## directed = FALSE
## hyper = FALSE
## loops = FALSE
## multiple = FALSE
## bipartite = FALSE
## total edges= 11
## missing edges= 0
## non-missing edges= 11
##
## Vertex attribute names:
## label vertex.names
##
## Edge attribute names:
## label
Networks are shown below using the following code:
layout(matrix(1:4, 2, 2, byrow=TRUE))
op <- par(mar=c(1,1,2,1))
# compute layout
coords <- layout.fruchterman.reingold(exIgraph)
plot(exIgraph, main="exIgraph", layout=coords)
plot(exIgraph2, main="exIgraph2", layout=coords)
plot(exNetwork, main="exNetwork", displaylabels=TRUE, coord=coords)
plot(exNetwork2, main="exNetwork2", displaylabels=TRUE, coord=coords)
par(op)
asNetwork
and asIgraph
Conversion of network objects between classes “network” and “igraph” can be performed using functions asNetwork
and asIgraph
.
Converting “network” objects to “igraph” is done by calling function asIgraph
on a “network” object:
# check class of 'exNetwork'
class(exNetwork)
## [1] "network"
# convert to 'igraph'
g <- asIgraph(exNetwork)
# check class of the result
class(g)
## [1] "igraph"
Check if edgelists of the objects are identical
el.g <- get.edgelist(g)
el.n <- as.matrix(exNetwork, "edgelist")
identical( as.numeric(el.g), as.numeric(el.n))
## [1] TRUE
Converting “igraph” objects to “network” is done by calling function asNetwork
on an “igraph” object:
net <- asNetwork(exIgraph)
Note the warning because of a “non-standard” network attribute layout
, which is a function. Printing “network” objects does not handle non-standard attributes very well. However, all the data and attributes are copied correctly.
Check if edgelists of the objects are identical
el.g2 <- get.edgelist(exIgraph)
el.n2 <- as.matrix(net, "edgelist")
identical( as.numeric(el.g2), as.numeric(el.n2))
## [1] TRUE
Objects of class “igraph” and “network”, apart from storing actual network data (vertexes and edges), allow for adding attributes of vertexes, edges, and attributes of the network as a whole (called “network attributes” or “graph attributes” in the nomenclatures of packages “network” and “igraph” respectively).
Vertex and edge attributes are used by “igraph” and “network” in a largely similar fashion. However, network-level attributes are used differently. Objects of class “network” use network-level attributes to store various metadata, e.g., network size, whether the network is directed, is bipartite, etc. In “igraph” this information is stored separately.
The above difference affects the way the attributes are copied when we convert “network” and “igraph” objects into one another.
Both functions asNetwork
and asIgraph
have an additional argument attrmap
that is used to specify how vertex, edge, and network attributes are copied. The attrmap
argument requires a data frame. Rows of that data frame specify rules of copying/renaming different attributes. The data frame should have the following columns (all of class “character”):
type
: one of “network”, “vertex” or “edge”, whether the rule applies to network, vertex or edge attribute.fromslc
: name of the which we are converting fromfromattr
: name of the attribute in the object we are converting fromtocls
: name of the class of the object we are converting totoattr
: name of the attribute in the object we are converting toThe default rules are returned by a function attrmap()
, these are:
attrmap()
## type fromcls fromattr tocls toattr
## 1 network network directed igraph <NA>
## 2 network network bipartite igraph <NA>
## 3 network network loops igraph <NA>
## 4 network network mnext igraph <NA>
## 5 network network multiple igraph <NA>
## 6 network network n igraph <NA>
## 7 network network hyper igraph <NA>
## 8 vertex igraph name network vertex.names
For example, the last row specifies a rule that when an object of class “igraph” is converted to class “network”, then a vertex attribute name
in the “igraph” object will be copied to a vertex attribute called vertex.names
in the resulting object of class “network.
If the column toattr
contains an NA
, that means that the corresponding attribute is not copied. For example, the first row specifies a rule that when an object of class “network” is converted to class “igraph”, then a network attribute directed
in the “network” object is not copied to the resulting object of class “igraph”.
Users can customize the rules, or add new ones, by constructing similar data frames and supplying them through argument attrmap
to functions asIgraph
and asNetwork
.
Function asDF
can be used to convert network object (of class “igraph” or “network”) to a list of two data frames:
l <- asDF(exIgraph)
str(l)
## List of 2
## $ edges :'data.frame': 11 obs. of 3 variables:
## ..$ V1 : num [1:11] 2 3 4 5 6 8 10 11 12 13 ...
## ..$ V2 : num [1:11] 1 1 1 1 7 9 11 12 13 14 ...
## ..$ label: chr [1:11] "ba" "ca" "da" "ea" ...
## $ vertexes:'data.frame': 15 obs. of 2 variables:
## ..$ intergraph_id: int [1:15] 1 2 3 4 5 6 7 8 9 10 ...
## ..$ label : chr [1:15] "a" "b" "c" "d" ...
The resulting list has two components edges
and vertexes
. The edges
component is essentially an edge list containing ego and alter ids in the first two columns. The remaining columns store edge attributes (if any). For our example data it is
l$edges
## V1 V2 label
## 1 2 1 ba
## 2 3 1 ca
## 3 4 1 da
## 4 5 1 ea
## 5 6 7 fg
## 6 8 9 hi
## 7 10 11 jk
## 8 11 12 kl
## 9 12 13 lm
## 10 13 14 mn
## 11 14 12 nl
The vertexes
component contains data on vertexes with vertex id (the same that is used in the first two column of edges
) is stored in the first two columns. The remaining columns store vertex attributes (if any). For our example data it is:
l$vertexes
## intergraph_id label
## 1 1 a
## 2 2 b
## 3 3 c
## 4 4 d
## 5 5 e
## 6 6 f
## 7 7 g
## 8 8 h
## 9 9 i
## 10 10 j
## 11 11 k
## 12 12 l
## 13 13 m
## 14 14 n
## 15 15 o
Functions asNetwork
and asIgraph
can also be used to create network objects from data frames such as those above. The first argument should be an edge list data frame. Optional argument vertices
expectes data frames with vertex data (just like l$vertexes
). Additionally we need to specify whether the edges should be interpreted as directed or not through the argument directed
.
For example, to create an object of class “network” from the dataframes created above from object exIgraph
we can:
z <- asNetwork(l$edges, directed=TRUE, l$vertexes)
z
## Network attributes:
## vertices = 15
## directed = TRUE
## hyper = FALSE
## loops = FALSE
## multiple = FALSE
## bipartite = FALSE
## total edges= 11
## missing edges= 0
## non-missing edges= 11
##
## Vertex attribute names:
## label vertex.names
##
## Edge attribute names:
## label
This is actually what basically happens when we call asNetwork(exIgraph)
sessionInfo()
## R version 3.2.2 (2015-08-14)
## Platform: x86_64-pc-linux-gnu (64-bit)
## Running under: Ubuntu 14.04.3 LTS
##
## locale:
## [1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C
## [3] LC_TIME=en_US.UTF-8 LC_COLLATE=en_US.UTF-8
## [5] LC_MONETARY=en_US.UTF-8 LC_MESSAGES=en_US.UTF-8
## [7] LC_PAPER=en_US.UTF-8 LC_NAME=C
## [9] LC_ADDRESS=C LC_TELEPHONE=C
## [11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C
##
## attached base packages:
## [1] stats graphics grDevices utils datasets methods base
##
## other attached packages:
## [1] igraph_1.1.0 network_1.13.0 knitr_1.11 intergraph_2.0-2
##
## loaded via a namespace (and not attached):
## [1] magrittr_1.5 formatR_1.2.1 tools_3.2.2 htmltools_0.2.6
## [5] yaml_2.1.13 stringi_0.5-5 rmarkdown_0.8 stringr_1.0.0
## [9] digest_0.6.8 pkgconfig_2.0.0 evaluate_0.8