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README.Rmd
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README.Rmd
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---
output: github_document
---
<!-- README.md is generated from README.Rmd. Please edit that file -->
# geomnet <img src="man/figures/logo.png" align="right" width="120" />
[](https://cran.r-project.org/package=geomnet)
[](https://www.r-pkg.org/pkg/geomnet)
[](https://travis-ci.org/sctyner/geomnet)
`geomnet` is a package built on top of the most recent major `ggplot2` release. It provides a `ggplot2` `geom` called `geom_net` to visualize graphs and networks. It also include the function `stat_net` to calculate network layouts with the `sna` package. Finally, the function `geom_circle` is included to draw circles using `ggplot2`.
You can install `geomnet` directly from CRAN
`install.packages('geomnet')`
or from Github
`devtools::install_github("sctyner/geomnet")`
```{r, echo = FALSE}
knitr::opts_chunk$set(
collapse = TRUE,
comment = "#>",
fig.path = "man/figures/README-"
)
```
# Examples
## `ggplot2` Theme Elements
This example shows the theme inheritance properties of the theme elements of `ggplot2`. Note: this example has not been updated since the release of `ggplot2 2.2.0` and as such the content may have changed.
```{r theme, fig.align='center', message=FALSE, warning=FALSE}
library(dplyr)
library(geomnet)
data(theme_elements)
# data step
TEnet <- fortify(as.edgedf(theme_elements$edges[,c("parent", "child")]), theme_elements$vertices)
# create a degree variable for use later
TEnet <- TEnet %>%
group_by(from_id) %>%
mutate(degree = sqrt(10 * n() + 1))
# plot
ggplot(data = TEnet,
aes(from_id = from_id, to_id = to_id)) +
geom_net(layout.alg = "fruchtermanreingold",
aes(fontsize = degree), directed = TRUE,
labelon = TRUE, size = 1, labelcolour = 'black',
ecolour = "grey70", arrowsize = 0.5,
linewidth = 0.5, repel = TRUE) +
theme_net() +
xlim(c(-0.05, 1.05))
```
## Blood Donation Diagram
In this example, we reimagine the [traditional blood donation diagram](http://www.redcrossblood.org/learn-about-blood/blood-types) as a directed network. Arrows point to the blood type that receives. This example provides two data frames to `geom_net()`.
```{r blood, fig.align='center'}
library(geomnet)
data(blood)
ggplot(data = blood$edges, aes(from_id = from, to_id = to)) +
geom_net(colour = "darkred", layout.alg = "circle", labelon = TRUE,
size = 15, directed = TRUE, vjust = 0.5, labelcolour = "grey80",
arrowsize = 1.5, linewidth = 0.5, arrowgap = 0.05,
selfloops = TRUE, ecolour = "grey40") +
theme_net()
```
## Harry Potter Peer Support Network
In this fun example from [this website](http://www.stats.ox.ac.uk/~snijders/siena/siena.html), there is a tie between two students if one provides emotional support to the other at some point in the book. It is a directed network, so in the visualization, the arrow points to the student receiving support.
```{r HP, echo = FALSE, message=FALSE, warning=FALSE}
library(dplyr)
temp <- tempfile()
download.file("http://www.stats.ox.ac.uk/~snijders/siena/bossaert_meidert_harrypotter.zip",temp)
hp1 <- read.table(unz(temp, "hpbook1.txt"))
hp1 <- as.matrix(hp1)
diag(hp1) <- 0
hp1 <- data.frame(hp1)
hp1$id <- 1:64
hp1 <- hp1 %>% tidyr::gather(var, value, -id) %>%
dplyr::filter(value == 1) %>%
dplyr::select(-value) %>%
dplyr::mutate(var = readr::parse_number(var), book = 1) %>%
dplyr::rename(from = id, to = var)
hp2 <- read.table(unz(temp, "hpbook2.txt"))
hp2 <- as.matrix(hp2)
diag(hp2) <- 0
hp2 <- data.frame(hp2)
hp2$id <- 1:64
hp2 <- hp2 %>% tidyr::gather(var, value, -id) %>%
dplyr::filter(value == 1) %>%
dplyr::select(-value) %>%
dplyr::mutate(var = readr::parse_number(var), book = 2) %>%
dplyr::rename(from = id, to = var)
hp3 <- read.table(unz(temp, "hpbook3.txt"))
hp3 <- as.matrix(hp3)
diag(hp3) <- 0
hp3 <- data.frame(hp3)
hp3$id <- 1:64
hp3 <- hp3 %>% tidyr::gather(var, value, -id) %>%
dplyr::filter(value == 1) %>%
dplyr::select(-value) %>%
dplyr::mutate(var = readr::parse_number(var), book = 3) %>%
dplyr::rename(from = id, to = var)
hp4 <- read.table(unz(temp, "hpbook4.txt"))
hp4 <- as.matrix(hp4)
diag(hp4) <- 0
hp4 <- data.frame(hp4)
hp4$id <- 1:64
hp4 <- hp4 %>% tidyr::gather(var, value, -id) %>%
dplyr::filter(value == 1) %>%
dplyr::select(-value) %>%
dplyr::mutate(var = readr::parse_number(var), book = 4) %>%
dplyr::rename(from = id, to = var)
hp5 <- read.table(unz(temp, "hpbook5.txt"))
hp5 <- as.matrix(hp5)
diag(hp5) <- 0
hp5 <- data.frame(hp5)
hp5$id <- 1:64
hp5 <- hp5 %>% tidyr::gather(var, value, -id) %>%
dplyr::filter(value == 1) %>%
dplyr::select(-value) %>%
dplyr::mutate(var = readr::parse_number(var), book = 5) %>%
dplyr::rename(from = id, to = var)
hp6 <- read.table(unz(temp, "hpbook6.txt"))
hp6 <- as.matrix(hp6)
diag(hp6) <- 0
hp6 <- data.frame(hp6)
hp6$id <- 1:64
hp6 <- hp6 %>% tidyr::gather(var, value, -id) %>%
dplyr::filter(value == 1) %>%
dplyr::select(-value) %>%
dplyr::mutate(var = readr::parse_number(var), book = 6) %>%
dplyr::rename(from = id, to = var)
hp <- rbind(hp1, hp2, hp3, hp4, hp5, hp6)
hp.attributes <- read.table(unz(temp, "hpattributes.txt"), header=TRUE, stringsAsFactors = F)
hp.names <- read.table(unz(temp, "hpnames.txt"), header=TRUE, stringsAsFactors = F)
hp.names[,1] <- as.integer(hp.names[,1])
hp.1 <- merge(hp, hp.names, by.x = "from", by.y = "id")
names(hp.1)[4] <- "name1"
hp.2 <- merge(hp.1, hp.names, by.x = "to", by.y = "id")
names(hp.2)[5] <- "name2"
hp.edges <- hp.2[, c("name1", "name2", "book")] %>% dplyr::arrange(book, name1, name2)
hp.chars <- merge(hp.names, hp.attributes)
hp.chars$house <- factor(hp.chars$house, labels = c("Gryffindor", "Hufflepuff", "Ravenclaw", "Slytherin"))
hp.chars$gender <- factor(hp.chars$gender, labels = c("M", "F"))
unlink(temp)
hp.chars <- hp.chars[,-1]
```
```{r HPplot, fig.width=10, fig.height=8, fig.align='center', warning = FALSE}
library(geomnet)
head(hp.edges)
head(hp.chars)
hp.all <- fortify(as.edgedf(hp.edges), hp.chars, group = "book")
# only plot the characters with any connections in a given book.
ggplot(data=hp.all, aes(from_id = from, to_id = to_id)) +
geom_net(fiteach=T, directed = T, size = 3, linewidth = .5,
ealpha = .5, labelon = T, fontsize = 3, repel = T,
labelcolour = "black", arrowsize = .5, singletons = FALSE,
aes(colour = house, group = house, shape = gender)) +
scale_colour_manual(values = c("#941B08","#F1F31C",
"#071A80", "#154C07")) +
facet_wrap(~book, labeller = "label_both") +
theme_net() + theme(panel.background = element_rect(colour = 'black'))
```
## Interactivity with `plotly`!
Now including interactivity with `ggplotly()`!
```{r football, eval = FALSE}
# blood donation example
library(geomnet)
# devtools::install_github("ropensci/plotly")
library(plotly)
data(blood)
bloodnet <- fortify(as.edgedf(blood$edges), blood$vertices)
p <- ggplot(data = bloodnet, aes(from_id = from_id, to_id = to_id))
# create data plot
p2 <- p + geom_net(aes(size=Predominance, colour=type, shape=rho, linetype=group_to),
linewidth=0.75, labelon =TRUE, directed = TRUE, labelcolour="black") +
facet_wrap(~Ethnicity) +
scale_colour_brewer(palette="Set2")
ggplotly(p2) %>% hide_legend()
# Classic College Football Example
data("football")
# data step: merge vertices and edges
ftnet <- fortify(as.edgedf(football$edges), football$vertices)
# create data plot
gg <- ggplot(data = ftnet,
aes(from_id = from_id, to_id = to_id)) +
geom_net(layout.alg = 'fruchtermanreingold',
aes(colour = value, group = value,
linetype = factor(same.conf != 1)),
linewidth = 0.5,
size = 5, vjust = -0.75, alpha = 0.3) +
theme_net() +
theme(legend.position = "bottom") +
scale_colour_brewer("Conference", palette = "Paired") +
guides(linetype = FALSE)
ggplotly(gg)
```