PL4246 Networks in Psychology: Tutorial 1

Video 2: Adjacency Matrices and Edge Lists

Set up

library(igraph)

load('data/examples_for_videos.RData') # loads the networks we will use 

Network with undirected, unweighted edges

g_ud_uw

## IGRAPH 767ab4c UN-- 5 6 -- 
## + attr: name (v/c)
## + edges from 767ab4c (vertex names):
## [1] Alex --Beth  Alex --Chris Alex --Doug  Alex --Eliza Beth --Doug 
## [6] Chris--Doug

Network to adjacency matrix

am_ud_uw <- as_adjacency_matrix(graph = g_ud_uw)

am_ud_uw

## 5 x 5 sparse Matrix of class "dgCMatrix"
##       Alex Beth Chris Doug Eliza
## Alex     .    1     1    1     1
## Beth     1    .     .    1     .
## Chris    1    .     .    1     .
## Doug     1    1     1    .     .
## Eliza    1    .     .    .     .

Adjacency matrix to network

g_ud_uw_am <- graph_from_adjacency_matrix(adjmatrix = am_ud_uw, mode = 'undirected', weighted = NULL)

g_ud_uw_am

## IGRAPH 8aac838 UN-- 5 6 -- 
## + attr: name (v/c)
## + edges from 8aac838 (vertex names):
## [1] Alex --Beth  Alex --Chris Alex --Doug  Alex --Eliza Beth --Doug 
## [6] Chris--Doug

Network to edgelist

el_ud_uw <- as_edgelist(graph = g_ud_uw)

el_ud_uw

##      [,1]    [,2]   
## [1,] "Alex"  "Beth" 
## [2,] "Alex"  "Chris"
## [3,] "Alex"  "Doug" 
## [4,] "Alex"  "Eliza"
## [5,] "Beth"  "Doug" 
## [6,] "Chris" "Doug"

Edgelist to network

g_ud_uw_el <- graph_from_edgelist(el = el_ud_uw, directed = FALSE)

g_ud_uw_el

## IGRAPH 6fcbb8f UN-- 5 6 -- 
## + attr: name (v/c)
## + edges from 6fcbb8f (vertex names):
## [1] Alex --Beth  Alex --Chris Alex --Doug  Alex --Eliza Beth --Doug 
## [6] Chris--Doug

Network with undirected, weighted edges

g_ud_w

## IGRAPH 767ab4c UNW- 5 6 -- 
## + attr: name (v/c), weight (e/n)
## + edges from 767ab4c (vertex names):
## [1] Alex --Beth  Alex --Chris Alex --Doug  Alex --Eliza Beth --Doug 
## [6] Chris--Doug

Network to adjacency matrix

am_ud_w <- as_adjacency_matrix(graph = g_ud_w, attr = 'weight')

am_ud_w

## 5 x 5 sparse Matrix of class "dgCMatrix"
##       Alex Beth Chris Doug Eliza
## Alex     .    1     4    1     2
## Beth     1    .     .    5     .
## Chris    4    .     .    3     .
## Doug     1    5     3    .     .
## Eliza    2    .     .    .     .

Adjacency matrix to network

g_ud_w_am <- graph_from_adjacency_matrix(adjmatrix = am_ud_w, mode = 'undirected', 
                                         weighted = 'weight')

g_ud_w_am

## IGRAPH e738398 UNW- 5 6 -- 
## + attr: name (v/c), weight (e/n)
## + edges from e738398 (vertex names):
## [1] Alex --Beth  Alex --Chris Alex --Doug  Alex --Eliza Beth --Doug 
## [6] Chris--Doug

Network to edgelist

el_ud_w <- as_edgelist(graph = g_ud_w)

el_ud_w # weights are missing! 

##      [,1]    [,2]   
## [1,] "Alex"  "Beth" 
## [2,] "Alex"  "Chris"
## [3,] "Alex"  "Doug" 
## [4,] "Alex"  "Eliza"
## [5,] "Beth"  "Doug" 
## [6,] "Chris" "Doug"

#first workaround 
cbind(as_edgelist(graph = g_ud_w), E(g_ud_w)$weight)

##      [,1]    [,2]    [,3]
## [1,] "Alex"  "Beth"  "1" 
## [2,] "Alex"  "Chris" "4" 
## [3,] "Alex"  "Doug"  "1" 
## [4,] "Alex"  "Eliza" "2" 
## [5,] "Beth"  "Doug"  "5" 
## [6,] "Chris" "Doug"  "3"

el_ud_w <- cbind(as_edgelist(graph = g_ud_w), E(g_ud_w)$weight) # for the next chunk 

# second workaround 
get.data.frame(x = g_ud_w, what = 'edges')

Edgelist to network

# we cannot use graph_from_edgelist to create a weighted network as there is no argument to specify weights 

# data frame
el_ud_w <- as.data.frame(el_ud_w)
colnames(el_ud_w)[3] <- 'weight' # relabel the 3rd column as 'weight' 

g_ud_uw_el <- graph_from_data_frame(d = el_ud_w, directed = FALSE, vertices = NULL)

g_ud_uw_el

## IGRAPH 5ce81d8 UNW- 5 6 -- 
## + attr: name (v/c), weight (e/c)
## + edges from 5ce81d8 (vertex names):
## [1] Alex --Beth  Alex --Chris Alex --Doug  Alex --Eliza Beth --Doug 
## [6] Chris--Doug

Network with directed, unweighted edges

g_d_uw

## IGRAPH 56acf83 DN-- 5 6 -- 
## + attr: name (v/c)
## + edges from 56acf83 (vertex names):
## [1] Alex ->Beth  Alex ->Chris Alex ->Doug  Alex ->Eliza Beth ->Doug 
## [6] Chris->Doug

Network to adjacency matrix

am_d_uw <- as_adjacency_matrix(graph = g_d_uw)

am_d_uw

## 5 x 5 sparse Matrix of class "dgCMatrix"
##       Alex Beth Chris Doug Eliza
## Alex     .    1     1    1     1
## Beth     .    .     .    1     .
## Chris    .    .     .    1     .
## Doug     .    .     .    .     .
## Eliza    .    .     .    .     .

Adjacency matrix to network

g_d_uw_am <- graph_from_adjacency_matrix(adjmatrix = am_d_uw, mode = 'directed', weighted = NULL)

g_d_uw_am

## IGRAPH 14a3b55 DN-- 5 6 -- 
## + attr: name (v/c)
## + edges from 14a3b55 (vertex names):
## [1] Alex ->Beth  Alex ->Chris Alex ->Doug  Beth ->Doug  Chris->Doug 
## [6] Alex ->Eliza

Network to edgelist

el_d_uw <- as_edgelist(graph = g_ud_uw)

el_d_uw # this is not different from el_ud_uw! but your interpretation of the data is different.

##      [,1]    [,2]   
## [1,] "Alex"  "Beth" 
## [2,] "Alex"  "Chris"
## [3,] "Alex"  "Doug" 
## [4,] "Alex"  "Eliza"
## [5,] "Beth"  "Doug" 
## [6,] "Chris" "Doug"

Edgelist to network

g_d_uw_el <- graph_from_edgelist(el = el_d_uw, directed = TRUE)

g_d_uw_el

## IGRAPH b73b15d DN-- 5 6 -- 
## + attr: name (v/c)
## + edges from b73b15d (vertex names):
## [1] Alex ->Beth  Alex ->Chris Alex ->Doug  Alex ->Eliza Beth ->Doug 
## [6] Chris->Doug

Network with directed, weighted edges

g_d_w

## IGRAPH 56acf83 DNW- 5 6 -- 
## + attr: name (v/c), weight (e/n)
## + edges from 56acf83 (vertex names):
## [1] Alex ->Beth  Alex ->Chris Alex ->Doug  Alex ->Eliza Beth ->Doug 
## [6] Chris->Doug

Network to adjacency matrix

am_d_w <- as_adjacency_matrix(graph = g_d_w, attr = 'weight')

am_d_w

## 5 x 5 sparse Matrix of class "dgCMatrix"
##       Alex Beth Chris Doug Eliza
## Alex     .    5     1    5     1
## Beth     .    .     .    4     .
## Chris    .    .     .    5     .
## Doug     .    .     .    .     .
## Eliza    .    .     .    .     .

Adjacency matrix to network

g_d_w_am <- graph_from_adjacency_matrix(adjmatrix = am_d_w, mode = 'directed', weighted = 'weight')

g_d_w_am

## IGRAPH c462bc7 DNW- 5 6 -- 
## + attr: name (v/c), weight (e/n)
## + edges from c462bc7 (vertex names):
## [1] Alex ->Beth  Alex ->Chris Alex ->Doug  Beth ->Doug  Chris->Doug 
## [6] Alex ->Eliza

Network to edgelist

el_d_w <- as_edgelist(graph = g_d_w)

el_d_w # we run into the same problem as before - the weights are missing

##      [,1]    [,2]   
## [1,] "Alex"  "Beth" 
## [2,] "Alex"  "Chris"
## [3,] "Alex"  "Doug" 
## [4,] "Alex"  "Eliza"
## [5,] "Beth"  "Doug" 
## [6,] "Chris" "Doug"

#first workaround 
cbind(as_edgelist(graph = g_d_w), E(g_d_w)$weight)

##      [,1]    [,2]    [,3]
## [1,] "Alex"  "Beth"  "5" 
## [2,] "Alex"  "Chris" "1" 
## [3,] "Alex"  "Doug"  "5" 
## [4,] "Alex"  "Eliza" "1" 
## [5,] "Beth"  "Doug"  "4" 
## [6,] "Chris" "Doug"  "5"

el_d_w <- cbind(as_edgelist(graph = g_d_w), E(g_d_w)$weight) # for the next chunk 

# second workaround 
get.data.frame(x = g_d_w, what = 'edges')

Edgelist to network

# we cannot use graph_from_edgelist to create a weighted network as there is no argument to specify weights 

# data frame
el_d_w <- as.data.frame(el_d_w)
colnames(el_d_w)[3] <- 'weight' # relabel the 3rd column as 'weight' 

g_d_w_el <- graph_from_data_frame(d = el_d_w, directed = TRUE, vertices = NULL)

g_d_w_el

## IGRAPH 988a5c0 DNW- 5 6 -- 
## + attr: name (v/c), weight (e/c)
## + edges from 988a5c0 (vertex names):
## [1] Alex ->Beth  Alex ->Chris Alex ->Doug  Alex ->Eliza Beth ->Doug 
## [6] Chris->Doug

Appendix

Code chunk to generate the example networks.

g_ud_uw <- graph_from_literal(Alex-Beth, 
                        Chris-Doug, Eliza-Alex, 
                        Beth-Doug, Alex-Chris,
                        Doug-Alex)

g_ud_w <- g_ud_uw
set.seed(1)
E(g_ud_w)$weight <- sample(1:5, 6, replace = T)

g_d_uw <- as.directed(g_ud_uw, mode = 'arbitrary') 

g_d_w <- g_d_uw
set.seed(2)
E(g_d_w)$weight <- sample(1:5, 6, replace = T)

save(g_ud_uw, g_ud_w, g_d_uw, g_d_w, file = 'examples_for_video1.RData')