# Week42 - adjacency matrix

*October 22, 2015*

## This Week’s Widget - adjacency matrix

This beautiful little adjacency matrix by Mike Bostock inspired this Github issue/request. At the beginning of the week, I started banging away on a `htmlwidget`

extension to `networkD3`

using Elijah Meeks’ d3.layout.adjacencyMatrix. The deeper I got the more I realized that an adjacency matrix really is just a subset of a heatmap, so then I started replicating Matthew Lincoln’s fine `Shiny`

/`ggplot2`

adjacency matrix with RStudio/Joe Cheng’s `d3heatmap`

. This bl.ock visualizing 2015 NCAA football is one result.

As the end of this week nears, I don’t have a whole lot in terms of a finished `htmlwidget`

, but I do have some prototype code and some examples.

## Installation

This is not on CRAN and not even in the `master`

branch, so to install we will need some help from `devtools::install_github`

.

`devtools::install_github("timelyportfolio/networkD3@feature/adjacency")`

For `d3heatmap`

, you can just `install.packages("d3heatmap")`

.

## Examples

Let’s start small with the bridges of Koenigsberg.

```
#devtools::install_github("timelyportfolio/networkD3@feature/adjacency")
library(networkD3)
library(igraph)
data(Koenigsberg, package="igraphdata")
koen_df <- get.data.frame(upgrade_graph(Koenigsberg), what="both")
koen_df$edges$from <- match(koen_df$edges$from,koen_df$vertices$name) - 1
koen_df$edges$to <- match(koen_df$edges$to,koen_df$vertices$name) - 1
adjacencyNetwork(
Links = koen_df$edges,
Nodes = koen_df$vertices,
Source = "from",
Target = "to",
NodeID = "name",
Group = "name",
margin = list(left=150, top=150),
colourScale = htmlwidgets::JS("d3.scale.category10()"),
width = 500,
height = 500
)
```

Now we can compare with `d3heatmap`

.

```
library(d3heatmap)
d3heatmap(
get.adjacency(
upgrade_graph(Koenigsberg),
sparse = FALSE
),
colors = "Blues",
dendrogram = "none",
cexRow = 0.7, cexCol = 0.7
)
```

One more example with the `karate`

data from `igraphdata`

.

```
library(networkD3)
library(igraph)
data(karate, package="igraphdata")
karate_df <- get.data.frame(upgrade_graph(karate), what="both")
karate_df$edges$from <- match(karate_df$edges$from,karate_df$vertices$name) - 1
karate_df$edges$to <- match(karate_df$edges$to,karate_df$vertices$name) - 1
adjacencyNetwork(
Links = karate_df$edges,
Nodes = karate_df$vertices,
Source = "from",
Target = "to",
NodeID = "name",
Group = "Faction",
margin = list(left=150, top=150),
width = 500,
height = 500
)
```

Again, let’s do the same network but in `d3heatmap`

, but we will include the dendrogram this time.

```
library(d3heatmap)
d3heatmap(
get.adjacency(
upgrade_graph(karate),
sparse = FALSE
),
colors = "Blues",
cexRow = 0.7, cexCol = 0.7
)
```

With a little sorting, our `karate`

adjacency matrix can be more helpful.

```
# community then by degree sorting
library(dplyr)
fc <- fastgreedy.community(karate)
karate_df <- get.data.frame(karate, what = "both")
karate_df$vertices <- data.frame(membership = unclass(membership(fc)), degree = degree(karate)) %>%
mutate( name = rownames(.) ) %>%
arrange( membership, desc( degree ) ) %>%
select( name ) %>%
as.vector %>%
inner_join( karate_df$vertices )
karate_df$edges$from <- match(karate_df$edges$from,karate_df$vertices$name) - 1
karate_df$edges$to <- match(karate_df$edges$to,karate_df$vertices$name) - 1
adjacencyNetwork(
Links = karate_df$edges,
Nodes = karate_df$vertices[,c(2,1)],
Source = "from",
Target = "to",
NodeID = "name",
Group = "Faction",
margin = list(left=100, top=100)
)
```

As you can see, I have a long way to go with this. The dynamic sorting in the Mike Bostock example is probably first to implement. I’d love help, comments, feedback, anything…

## Thanks

Thanks Mike Bostock for `d3`

and another great example using it. Thanks Elijah Meeks for all his `d3`

posts, book, examples, and layouts. Thanks Joe Cheng for `d3heatmap`

.

As always, thanks to

- Ramnath Vaidyanathan and RStudio for
`htmlwidgets`

- all the contributors to
`R`

and`JavaScript`