我通常发现使用tidygraph和ggraph生态系统定制网络图更容易。您的图形具有比给定示例更多的边，因此可能需要进行一些调整以使边看起来像您想要的那样。

library(tidygraph)
library(ggraph)

# Match colours in given example:
colormap <- c(red = '#fa3233', blue = '#3d85e9',
  green = '#4cb30f', purple = '#7b29ef',
  cyan = '#e02aef', brown = '#ffa500')

fillmap <- c(red = '#fb7e81', blue = '#97c2fc',
             green = '#7be142', purple = '#ad85e4',
             cyan = '#ea7cf3', brown = '#ffff00')

tbl_graph(nodes, 
          cbind(edges, colour = nodes$group[match(edges$from, nodes$id)])) %>%
  ggraph(layout = 'igraph', algorithm = 'fr') +
  geom_edge_diagonal(aes(color = colour, width = weight)) +
  geom_node_circle(aes(r = 1, color = group, fill = group)) +
  coord_equal() +
  scale_edge_color_manual(values = colormap) +
  scale_color_manual(values = colormap) +
  scale_fill_manual(values = fillmap) +
  scale_edge_width_continuous(range = c(0.1, 5)) +
  theme_void() +
  theme(legend.position = 'none')

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的数据

编辑

要调整布局，使组之间不会太近，并以清晰的方式标记节点，您可以执行以下操作：

tbl_graph(nodes, 
          cbind(edges, colour = nodes$group[match(edges$from, nodes$id)])) %>%
  ggraph(layout = 'igraph', algorithm = 'fr', weights = (edges$weight)^0.2) +
  geom_edge_diagonal(aes(color = colour, width = weight)) +
  geom_node_label(aes(label = label, fill = group, color = group), size = 3,
                  label.r = unit(0.5, "lines")) +
  geom_node_text(aes(label = label), size = 3) +
  coord_equal(clip = 'off') +
  scale_edge_color_manual(values = colormap) +
  scale_color_manual(values = colormap) +
  scale_fill_manual(values = fillmap) +
  scale_edge_width_continuous(range = c(0.1, 5)) +
  theme_void() +
  theme(legend.position = 'none')

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的

这就是我对igraph的尝试

g <- edges %>%
    mutate(
        color1 = with(nodes, as.character(group)[match(from, id)]),
        color2 = with(nodes, as.character(group)[match(to, id)])
    ) %>%
    mutate(color = ifelse(color1 == color2, color1, "gray")) %>%
    mutate(width = ifelse(color == "gray", weight, weight * 100)) %>%
    graph_from_data_frame(directed = FALSE) %>%
    set_vertex_attr(name = "color", value = with(nodes, as.character(group)[match(names(V(.)), id)])) %>%
    set_vertex_attr(name = "label", value = with(nodes, label[match(names(V(.)), label)])) %>%
    set_vertex_attr(name = "size", value = 10) %>%
    set_edge_attr(name = "curved", value = TRUE)

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然后把它画出来

plot(g, layout = layout_with_fr)

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的数据