Understanding Arc Position in Geospatial Network Analysis

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In this article, we will delve into understanding arc position in geospatial network analysis using R and the ggraph library.

Introduction

Arc length is a measure used to quantify the distance between two points along a curve, such as the shortest path between two nodes in a graph. The strength of an edge is often represented by its color or size, with longer edges having greater weight. However, when working with networks that have varying arc lengths, separating the direction of the edge from its length and weight can be challenging.

Workaround Solution

One workaround to handle this issue is to separate the vector of desired arc positions based on the sign of edge_width and then feed it into the geom_edge_arc function outside of aes.

library(tidyverse)
library(tidygraph)
library(igraph)
library(ggraph)

set.seed(1)

# Define nodes
nodes <- data.frame(node_name = paste0("node", 1:5))

# Define edges
edges <- t(combn(nodes$node_name, 2)) %>%
  as_tibble(.name_repair = "universal") %>%
  rename(from = 1, to = 2) %>%
  mutate(edge_width = sample(x = -10:10, size = nrow(.), replace = T))

# Extract vector of desired arc positions based on sign of edge width
arc_direction <- sign(edges$edge_width)

# Build network from nodes and edges
network <- tbl_graph(edges = edges, nodes = nodes, directed = FALSE)

# Visualize network as arcplot
network %>%
  ggraph(layout = "linear") +
  geom_edge_arc(aes(color = edge_width >= 0, width = abs(edge_width)),
                strength = arc_direction,
                alpha = 0.65) +
  geom_node_label(aes(label = node_name), size = 3)

Step-by-Step Explanation

To create a geospatial network with varying arc lengths and separate the direction of the edge from its length and weight, follow these steps:

Define your nodes using data.frame.
Create your edges by generating random pairs of node names.
Extract the vector of desired arc positions based on the sign of edge_width in edges.
Use tbl_graph from the tidygraph package to create a graph object with the defined nodes and edges.
Visualize the network using ggraph with the geom_edge_arc function, separating arc direction, length, and weight into different aesthetic components.

Conclusion

In this article, we’ve discussed how to handle varying arc lengths in geospatial network analysis by separating the arc position from its length and weight. We’ve also provided a workaround solution using R and the ggraph library, which can be adapted for use in other graph visualization tools and languages.

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Last modified on 2023-09-15