ggraph tricks

---

[참고] https://www.r-bloggers.com/ggraph-tricks-for-common-problems/

---

1 ggraph tricks for common problems

1.1 packages

---

1.2 Arrow heads and node size

“How can I achieve that my directed edges stop at the node border, independent from the node size?”

# create a random network
set.seed(1071)
g <- sample_pa(30, 1)
V(g)$degree <- degree(g, mode = "in")

ggraph(g, "stress") +
  geom_edge_link(
    aes(end_cap = circle(node2.degree + 2, "pt")),
    edge_colour = "black",
    arrow = arrow(
      angle = 10,
      length = unit(0.15, "inches"),
      ends = "last",
      type = "closed"
    )
  ) +
  geom_node_point(aes(size = degree), col = "grey66", show.legend = FALSE) +
  scale_size(range = c(3, 11)) +
  theme_graph()

# this function is borrowed from the ambient package
normalise <- function (x, from = range(x), to = c(0, 1)) {
  x <- (x - from[1])/(from[2] - from[1])
  if (!identical(to, c(0, 1))) {
    x <- x * (to[2] - to[1]) + to[1]
  }
  x
}

# map to the range you want
V(g)$degree <- normalise(V(g)$degree, to = c(3, 11))

ggraph(g, "stress") +
  geom_edge_link(
    aes(end_cap = circle(node2.degree + 2, "pt")),
    edge_colour = "grey25",
    arrow = arrow(
      angle = 10,
      length = unit(0.15, "inches"),
      ends = "last",
      type = "closed"
    )
  ) +
  geom_node_point(aes(size = I(degree)), col = "grey66") +
  theme_graph()

---

1.3 low opacity nodes

“How can I lower the opacity of nodes without making edges visible underneath?”

g <- sample_gnp(20, 0.5)
V(g)$degree <- degree(g)

ggraph(g, "stress") +
  geom_edge_link(edge_colour = "grey66") +
  geom_node_point(
    size = 8,
    aes(alpha = degree),
    col = "red",
    show.legend = FALSE
  ) +
  theme_graph()

ggraph(g, "stress") +
  geom_edge_link(edge_colour = "grey66") +
  geom_node_point(size = 8, col = "white") +
  geom_node_point(
    aes(alpha = degree),
    size = 8,
    col = "red",
    show.legend = FALSE
  ) +
  theme_graph()

---

1.4 use the ggforce

The {{ggforce}} package works pretty nicely with {{ggraph}}. You can, for instance, use the geom_mark_*() functions to highlight clusters.

set.seed(665)

#create network with a group structure
g <- sample_islands(9, 40, 0.4, 15)
g <- igraph::simplify(g)
V(g)$grp <- as.character(rep(1:9, each = 40))

bb <- layout_as_backbone(g, keep = 0.4)
E(g)$col <- F
E(g)$col[bb$backbone] <- T
ggraph(g,
       layout = "manual",
       x = bb$xy[, 1],
       y = bb$xy[, 2]) +
  geom_edge_link0(aes(col = col), width = 0.2) +
  geom_node_point(aes(fill = grp), shape = 21, size = 3) +
  geom_mark_hull(
    aes(x, y, group = grp, fill = grp),
    concavity = 4,
    expand = unit(2, "mm"),
    alpha = 0.25
  ) +
  scale_color_brewer(palette = "Set1") +
  scale_fill_brewer(palette = "Set1") +
  scale_edge_color_manual(values = c(rgb(0, 0, 0, 0.3), rgb(0, 0, 0, 1))) +
  theme_graph()+
  theme(legend.position = "none")

ggraph(g,
       layout = "manual",
       x = bb$xy[, 1],
       y = bb$xy[, 2]) +
  geom_edge_link0(aes(col = col), width = 0.2) +
  geom_node_point(aes(fill = grp), shape = 21, size = 3) +
  geom_mark_hull(
    aes(x, y, group = grp, fill = grp, label=grp),
    concavity = 4,
    expand = unit(2, "mm"),
    alpha = 0.25
  ) +
  scale_color_brewer(palette = "Set1") +
  scale_fill_brewer(palette = "Set1") +
  scale_edge_color_manual(values = c(rgb(0, 0, 0, 0.3), rgb(0, 0, 0, 1))) +
  theme_graph()+
  theme(legend.position = "none")

ggraph(g,
       layout = "manual",
       x = bb$xy[, 1],
       y = bb$xy[, 2]) +
  geom_edge_link0(aes(filter = !col, col = col), width = 0.2) +
  geom_node_voronoi(
    aes(x, y, fill = grp),
    max.radius = 0.4,
    expand = unit(-0.5, 'mm'),
    colour = 'black'
  ) +
  scale_color_brewer(palette = "Set1") +
  scale_fill_brewer(palette = "Set1") +
  scale_edge_color_manual(values = c(rgb(0, 0, 0, 0.3), rgb(0, 0, 0, 1))) +
  theme(
    legend.position = "none",
    panel.grid = element_blank(),
    axis.ticks = element_blank(),
    axis.text = element_blank()
  ) +
  theme_graph() +
  theme(legend.position = "none")

---

1.5 new node shapes with scatterpie

How can I make my nodes into a pie chart?

set.seed(1439)
# create a random graph with three random attributes
g <- sample_pa(20, 1)
V(g)$A <- abs(rnorm(20, sd = 1))
V(g)$B <- abs(rnorm(20, sd = 2))
V(g)$C <- abs(rnorm(20, sd = 3))

#precompute the layout
xy <- layout_with_stress(g)
V(g)$x <- xy[, 1]
V(g)$y <- xy[, 2]

ggraph(g, "manual", x = V(g)$x, y = V(g)$y) +
  geom_edge_link0() +
  geom_scatterpie(
    cols = c("A", "B", "C"),
    data = as_data_frame(g, "vertices"),
    colour = NA,
    pie_scale = 2
  ) +
  coord_fixed() +
  theme_graph() +
  theme(legend.position = "bottom")

#create network with a group structure
g <- sample_islands(9, 40, 0.4, 15)
g <- igraph::simplify(g)
V(g)$grp <- as.character(rep(1:9, each = 40))

# create a random categorical variable
V(g)$cat <- sample(c("A", "B", "C"), vcount(g), replace = T)

# contract the network based on the groups
g_clu <- contract(g, V(g)$grp, vertex.attr.comb = "concat")
E(g_clu)$weight <- 1
g_clu <- simplify(g_clu, edge.attr.comb = "sum")

# calculate the number of occurrences of each attribute in each cluster
V(g_clu)$A <- sapply(V(g_clu)$cat, function(x)
  sum(x == "A"))
V(g_clu)$B <- sapply(V(g_clu)$cat, function(x)
  sum(x == "B"))
V(g_clu)$C <- sapply(V(g_clu)$cat, function(x)
  sum(x == "C"))

# precompute layout
xy <- layout_with_stress(g_clu)
V(g_clu)$x <- xy[, 1]
V(g_clu)$y <- xy[, 2]

ggraph(g_clu, "manual", x = V(g_clu)$x, y = V(g_clu)$y) +
  geom_edge_link0() +
  geom_scatterpie(
    cols = c("A", "B", "C"),
    data = as_data_frame(g_clu, "vertices"),
    colour = "white",
    pie_scale = 3
  ) +
  scale_fill_manual(values = c("goldenrod", "black", "darkorchid2")) +
  coord_fixed() +
  theme_graph() +
  theme(legend.position = "bottom")

---

Can I do something else besides pie charts?

#create data frames for nodes (wide and long)
nodes_wide <- igraph::as_data_frame(g_clu, "vertices")

nodes_long <- nodes_wide %>% select(A:C) %>%
  mutate(id = 1:nrow(nodes_wide)) %>%
  gather("attr", "value", A:C)

# create the bar charts
bar_list <- lapply(1:vcount(g_clu), function(i) {
  gt_plot <- ggplotGrob(
    ggplot(nodes_long[nodes_long$id == i, ]) +
      geom_col(
        aes(factor(id), value, group = id, fill = attr),
        position = 'dodge2',
        color = NA
      ) +
      scale_fill_manual(values = c("goldenrod", "black", "darkorchid2")) +
      labs(x = NULL, y = NULL) +
      coord_cartesian(expand = FALSE) +
      theme(
        legend.position = "none",
        panel.background = element_rect(fill = "white", colour = NA),
        line = element_blank(),
        text = element_blank()
      )
  )
  panel_coords <- gt_plot$layout[gt_plot$layout$name == "panel", ]
  gt_plot[panel_coords$t:panel_coords$b, panel_coords$l:panel_coords$r]
})

# convert to custom annotation
annot_list <- lapply(1:vcount(g_clu), function(i) {
  xmin <- nodes_wide$x[i] - 0.07
  xmax <- nodes_wide$x[i] + 0.07
  ymin <- nodes_wide$y[i] - 0.07
  ymax <- nodes_wide$y[i] + 0.07
  annotation_custom(
    bar_list[[i]],
    xmin = xmin,
    xmax = xmax,
    ymin = ymin,
    ymax = ymax
  )
})

# create basic network
p <- ggraph(g_clu, "manual", x = V(g_clu)$x, y = V(g_clu)$y) +
  geom_edge_link0() +
  theme_graph()+
  coord_fixed()

# put everything together
Reduce("+", annot_list, p)

---