Skip to content

Latest commit

 

History

History
81 lines (58 loc) · 2.94 KB

README.md

File metadata and controls

81 lines (58 loc) · 2.94 KB
Raw

easylayout: an R package for interactive force-directed layouts within RStudio

R-CMD-check

easylayout is an R package that leverages interactive force simulations within the IDE itself (e.g., RStudio, VSCode). It is not yet another visualization library, but instead aims to interconnect existing libraries and streamline their usage into the R ecosystem.

easylayout takes an igraph object and serializes it into a web application integrated with the IDE’s interface through a Shiny server. The web application lays out the network by simulating attraction and repulsion forces. Simulation parameters can be adjusted in real-time. An editing mode allows moving and rotating nodes. The implementation aims for performance, so that even lower-end devices are able to work with relatively large networks. Once the user finishes tinkering the layout, it is sent back to the R session to be plotted through popular libraries like ggplot2 or even the base package itself.

Installation

You can install the development version of easylayout from GitHub with:

# install.packages("devtools")
devtools::install_github("dalmolingroup/easylayout")

Example

This is a basic example which shows you how to solve a common problem:

library(easylayout)
library(igraph)

g <- igraph::erdos.renyi.game(n = 5000, p.or.m = 10000, type = "gnm")

number_of_vertices <- igraph::vcount(g)

igraph::V(g)$label <- NA
igraph::V(g)$size <- sample(1:5, number_of_vertices, replace = TRUE)
igraph::V(g)$color <- sample(rainbow(5), number_of_vertices, replace = TRUE)

plot(g, layout = easylayout, vertex.label = NA, margin = 0)

You can also run easylayout as a standalone function, attributing its output to a variable in your R environment. The output is just a 2-column matrix:

layout <- easylayout(g)

Once you store the final coordinates to a variable, use any plotting package to display the network. In the example below, we plot the network using ggraph.

ggraph::ggraph(g, layout = layout) +
  ggraph::geom_edge_link() +
  ggraph::geom_node_point(aes(color = color)) + 
  ggplot2::coord_fixed() +
  ggplot2::theme_void()

Future work

The current implementation focuses on the R ecosystem, but using web technologies makes it easily portable to similar environments, like Jupyter Notebooks. We expect this tool to reduce the time spent tweaking network layouts, allowing researches to generate more compelling figures.