如果您从 R 中使用 igraph,请使用此选项
layout_with_sugiyama {igraph} | R 文档 |
用于分层有向无环图的 Sugiyama 布局算法。该算法最小化边交叉。
layout_with_sugiyama(
graph,
layers = NULL,
hgap = 1,
vgap = 1,
maxiter = 100,
weights = NULL,
attributes = c("default", "all", "none")
)
with_sugiyama(...)
图 |
输入图。 |
layers |
一个数值向量或 |
hgap |
实数标量,同一图层中顶点之间的最小水平间隙。 |
vgap |
实数标量,图层之间的距离。 |
maxiter |
整数标量,交叉最小化阶段的最大迭代次数。 100 是一个合理的默认值;如果您觉得边交叉太多,请增加此值。 |
weights |
可选的边权重向量。如果为 |
attributes |
要在扩展图中保留哪些图/顶点/边属性。“default”保留“size”、“size2”、“shape”、“label”和“color”顶点属性以及“arrow.mode”和“arrow.size”边属性。“all”保留所有图、顶点和边属性,“none”不保留任何属性。 |
... |
传递给 |
此布局算法专为有向无环图设计,其中每个顶点都分配给一个图层。图层从零开始索引,同一图层的顶点将放置在同一水平线上。每个图层中顶点的 X 坐标由 Sugiyama 等人提出的启发式方法决定,以最小化边交叉。
您也可以尝试使用此算法来布局无向图、包含循环的图或没有先验分层分配的图。 igraph 将尝试消除循环并将顶点分配到图层,但无法保证在这种情况下布局的质量。
Sugiyama 布局可能会在边上引入“弯曲”,以获得视觉上更令人愉悦的布局。这是通过向跨越多个图层的边添加虚拟节点来实现的。生成的布局不仅为原始图的节点分配坐标,还为虚拟节点分配坐标。布局算法还将返回具有虚拟节点的扩展图。
有关更多详细信息,请参见下面的参考。
包含以下组件的列表
layout |
布局,一个两列矩阵,用于原始图顶点。 |
layout.dummy |
虚拟节点的布局,一个两列矩阵。 |
extd_graph |
原始图,用虚拟顶点扩展。“dummy”顶点属性在此图上设置,它是一个逻辑属性,它告诉您顶点是否是虚拟顶点。“layout”图属性也已设置,它是所有(原始和虚拟)顶点的布局矩阵。 |
Tamas Nepusz ntamas@gmail.com
K. Sugiyama, S. Tagawa and M. Toda, "Methods for Visual Understanding of Hierarchical Systems". IEEE Transactions on Systems, Man and Cybernetics 11(2):109-125, 1981.
其他图布局:add_layout_()
, component_wise()
, layout_as_bipartite()
, layout_as_star()
, layout_as_tree()
, layout_in_circle()
, layout_nicely()
, layout_on_grid()
, layout_on_sphere()
, layout_randomly()
, layout_with_dh()
, layout_with_fr()
, layout_with_gem()
, layout_with_graphopt()
, layout_with_kk()
, layout_with_lgl()
, layout_with_mds()
, layout_()
, merge_coords()
, norm_coords()
, normalize()
## Data taken from http://tehnick-8.narod.ru/dc_clients/
DC <- graph_from_literal("DC++" -+
"LinuxDC++":"BCDC++":"EiskaltDC++":"StrongDC++":"DiCe!++",
"LinuxDC++" -+ "FreeDC++", "BCDC++" -+ "StrongDC++",
"FreeDC++" -+ "BMDC++":"EiskaltDC++",
"StrongDC++" -+ "AirDC++":"zK++":"ApexDC++":"TkDC++",
"StrongDC++" -+ "StrongDC++ SQLite":"RSX++",
"ApexDC++" -+ "FlylinkDC++ ver <= 4xx",
"ApexDC++" -+ "ApexDC++ Speed-Mod":"DiCe!++",
"StrongDC++ SQLite" -+ "FlylinkDC++ ver >= 5xx",
"ApexDC++ Speed-Mod" -+ "FlylinkDC++ ver <= 4xx",
"ApexDC++ Speed-Mod" -+ "GreylinkDC++",
"FlylinkDC++ ver <= 4xx" -+ "FlylinkDC++ ver >= 5xx",
"FlylinkDC++ ver <= 4xx" -+ AvaLink,
"GreylinkDC++" -+ AvaLink:"RayLinkDC++":"SparkDC++":PeLink)
## Use edge types
E(DC)$lty <- 1
E(DC)["BCDC++" %->% "StrongDC++"]$lty <- 2
E(DC)["FreeDC++" %->% "EiskaltDC++"]$lty <- 2
E(DC)["ApexDC++" %->% "FlylinkDC++ ver <= 4xx"]$lty <- 2
E(DC)["ApexDC++" %->% "DiCe!++"]$lty <- 2
E(DC)["StrongDC++ SQLite" %->% "FlylinkDC++ ver >= 5xx"]$lty <- 2
E(DC)["GreylinkDC++" %->% "AvaLink"]$lty <- 2
## Layers, as on the plot
layers <- list(c("DC++"),
c("LinuxDC++", "BCDC++"),
c("FreeDC++", "StrongDC++"),
c("BMDC++", "EiskaltDC++", "AirDC++", "zK++", "ApexDC++",
"TkDC++", "RSX++"),
c("StrongDC++ SQLite", "ApexDC++ Speed-Mod", "DiCe!++"),
c("FlylinkDC++ ver <= 4xx", "GreylinkDC++"),
c("FlylinkDC++ ver >= 5xx", "AvaLink", "RayLinkDC++",
"SparkDC++", "PeLink"))
## Check that we have all nodes
all(sort(unlist(layers)) == sort(V(DC)$name))
## Add some graphical parameters
V(DC)$color <- "white"
V(DC)$shape <- "rectangle"
V(DC)$size <- 20
V(DC)$size2 <- 10
V(DC)$label <- lapply(V(DC)$name, function(x)
paste(strwrap(x, 12), collapse="\n"))
E(DC)$arrow.size <- 0.5
## Create a similar layout using the predefined layers
lay1 <- layout_with_sugiyama(DC, layers=apply(sapply(layers,
function(x) V(DC)$name %in% x), 1, which))
## Simple plot, not very nice
par(mar=rep(.1, 4))
plot(DC, layout=lay1$layout, vertex.label.cex=0.5)
## Sugiyama plot
plot(lay1$extd_graph, vertex.label.cex=0.5)
## The same with automatic layer calculation
## Keep vertex/edge attributes in the extended graph
lay2 <- layout_with_sugiyama(DC, attributes="all")
plot(lay2$extd_graph, vertex.label.cex=0.5)
## Another example, from the following paper:
## Markus Eiglsperger, Martin Siebenhaller, Michael Kaufmann:
## An Efficient Implementation of Sugiyama's Algorithm for
## Layered Graph Drawing, Journal of Graph Algorithms and
## Applications 9, 305--325 (2005).
ex <- graph_from_literal( 0 -+ 29: 6: 5:20: 4,
1 -+ 12,
2 -+ 23: 8,
3 -+ 4,
4,
5 -+ 2:10:14:26: 4: 3,
6 -+ 9:29:25:21:13,
7,
8 -+ 20:16,
9 -+ 28: 4,
10 -+ 27,
11 -+ 9:16,
12 -+ 9:19,
13 -+ 20,
14 -+ 10,
15 -+ 16:27,
16 -+ 27,
17 -+ 3,
18 -+ 13,
19 -+ 9,
20 -+ 4,
21 -+ 22,
22 -+ 8: 9,
23 -+ 9:24,
24 -+ 12:15:28,
25 -+ 11,
26 -+ 18,
27 -+ 13:19,
28 -+ 7,
29 -+ 25 )
layers <- list( 0, c(5, 17), c(2, 14, 26, 3), c(23, 10, 18), c(1, 24),
12, 6, c(29,21), c(25,22), c(11,8,15), 16, 27, c(13,19),
c(9, 20), c(4, 28), 7 )
layex <- layout_with_sugiyama(ex, layers=apply(sapply(layers,
function(x) V(ex)$name %in% as.character(x)),
1, which))
origvert <- c(rep(TRUE, vcount(ex)), rep(FALSE, nrow(layex$layout.dummy)))
realedge <- as_edgelist(layex$extd_graph)[,2] <= vcount(ex)
plot(layex$extd_graph, vertex.label.cex=0.5,
edge.arrow.size=.5,
vertex.size=ifelse(origvert, 5, 0),
vertex.shape=ifelse(origvert, "square", "none"),
vertex.label=ifelse(origvert, V(ex)$name, ""),
edge.arrow.mode=ifelse(realedge, 2, 0))