networking和弦图困扰着R

我有一些类似data.frame d数据如下。 

 d <- structure(list(ID = c("KP1009", "GP3040", "KP1757", "GP2243", "KP682", "KP1789", "KP1933", "KP1662", "KP1718", "GP3339", "GP4007", "GP3398", "GP6720", "KP808", "KP1154", "KP748", "GP4263", "GP1132", "GP5881", "GP6291", "KP1004", "KP1998", "GP4123", "GP5930", "KP1070", "KP905", "KP579", "KP1100", "KP587", "GP913", "GP4864", "KP1513", "GP5979", "KP730", "KP1412", "KP615", "KP1315", "KP993", "GP1521", "KP1034", "KP651", "GP2876", "GP4715", "GP5056", "GP555", "GP408", "GP4217", "GP641"), Type = c("B", "A", "B", "A", "B", "B", "B", "B", "B", "A", "A", "A", "A", "B", "B", "B", "A", "A", "A", "A", "B", "B", "A", "A", "B", "B", "B", "B", "B", "A", "A", "B", "A", "B", "B", "B", "B", "B", "A", "B", "B", "A", "A", "A", "A", "A", "A", "A"), Set = c(15L, 1L, 10L, 21L, 5L, 9L, 12L, 15L, 16L, 19L, 22L, 3L, 12L, 22L, 15L, 25L, 10L, 25L, 12L, 3L, 10L, 8L, 8L, 20L, 20L, 19L, 25L, 15L, 6L, 21L, 9L, 5L, 24L, 9L, 20L, 5L, 2L, 2L, 11L, 9L, 16L, 10L, 21L, 4L, 1L, 8L, 5L, 11L), Loc = c(3L, 2L, 3L, 1L, 3L, 3L, 3L, 1L, 2L, 1L, 3L, 1L, 1L, 2L, 2L, 1L, 3L, 2L, 2L, 2L, 3L, 2L, 3L, 2L, 1L, 3L, 3L, 3L, 2L, 3L, 1L, 3L, 3L, 1L, 3L, 2L, 3L, 1L, 1L, 1L, 2L, 3L, 3L, 3L, 2L, 2L, 3L, 3L)), .Names = c("ID", "Type", "Set", "Loc"), class = "data.frame", row.names = c(NA, -48L))

我想使用类似于下面的和弦来探索d$ID成员之间的关系。

在这里输入图像说明

它似乎有几个选项在R做。 （ R中的和弦图 ）。

在我的数据中，关系是根据d$Set （不是定向的），分组是根据d$Loc 。 以下是我将映射关系映射为和弦图的尝试。

尝试1：使用igraph

我已经按照程度按照节点大小尝试了igraph 。 

 # Get vertex relationships sets <- unique(d$Set[duplicated(d$Set)]) rel <- vector("list", length(sets)) for (i in 1:length(sets)) { rel[[i]] <- as.data.frame(t(combn(subset(d, d$Set ==sets[i])$ID, 2))) } library(data.table) rel <- rbindlist(rel) # Get the graph g <- graph.data.frame(rel, directed=F, vertices=d) clr <- as.factor(V(g)$Loc) levels(clr) <- c("salmon", "wheat", "lightskyblue") V(g)$color <- as.character(clr) # Plot plot(g, layout = layout.circle, vertex.size=degree(g)*5, vertex.label=NA)

在这里输入图像说明

如何修改情节看起来像第一个数字？ 看来，没有选项可以修改igraph layout.circle 。

尝试2：使用Circlize

看起来更平滑的贝塞尔曲线和分组是可能的R包circlize 。 但是在这里，我不能将节点分组，也不能根据程度来调整它们的大小，因为它们被绘制为扇区。 

 par(mar = c(1, 1, 1, 1), lwd = 0.1, cex = 0.7) circos.initialize(factors = as.factor(d$ID), xlim = c(0, 10)) circos.trackPlotRegion(factors = as.factor(d$ID), ylim = c(0, 0.5), bg.col = V(g)$color, bg.border = NA, track.height = 0.05) for(i in 1:nrow(rel)) { circos.link(rel[i,1], 0, rel[i,2],0, h = 0.4) }

在这里输入图像说明

但是在这里没有修改节点的选项。 事实上，他们只能被划分为部门？ 在这种情况下，有没有办法根据程度将扇区修改为大小的循环节点？

尝试3：使用edgebundleR （ https://github.com/garthtarr/edgebundleR ） 

 require(edgebundleR) edgebundle(g,tension = 0.1,cutoff = 0.5, fontsize = 18,padding=40)

在这里输入图像说明 在这里，似乎修改美学的select有限。

我做了一堆edgebundleR的变化。 这些现在在主要回购。 下面的代码应该让你接近所需的结果。 活的例子 

 # devtools::install_github("garthtarr/edgebundleR") library(edgebundleR) library(igraph) library(data.table) d <- structure(list(ID = c("KP1009", "GP3040", "KP1757", "GP2243", "KP682", "KP1789", "KP1933", "KP1662", "KP1718", "GP3339", "GP4007", "GP3398", "GP6720", "KP808", "KP1154", "KP748", "GP4263", "GP1132", "GP5881", "GP6291", "KP1004", "KP1998", "GP4123", "GP5930", "KP1070", "KP905", "KP579", "KP1100", "KP587", "GP913", "GP4864", "KP1513", "GP5979", "KP730", "KP1412", "KP615", "KP1315", "KP993", "GP1521", "KP1034", "KP651", "GP2876", "GP4715", "GP5056", "GP555", "GP408", "GP4217", "GP641"), Type = c("B", "A", "B", "A", "B", "B", "B", "B", "B", "A", "A", "A", "A", "B", "B", "B", "A", "A", "A", "A", "B", "B", "A", "A", "B", "B", "B", "B", "B", "A", "A", "B", "A", "B", "B", "B", "B", "B", "A", "B", "B", "A", "A", "A", "A", "A", "A", "A"), Set = c(15L, 1L, 10L, 21L, 5L, 9L, 12L, 15L, 16L, 19L, 22L, 3L, 12L, 22L, 15L, 25L, 10L, 25L, 12L, 3L, 10L, 8L, 8L, 20L, 20L, 19L, 25L, 15L, 6L, 21L, 9L, 5L, 24L, 9L, 20L, 5L, 2L, 2L, 11L, 9L, 16L, 10L, 21L, 4L, 1L, 8L, 5L, 11L), Loc = c(3L, 2L, 3L, 1L, 3L, 3L, 3L, 1L, 2L, 1L, 3L, 1L, 1L, 2L, 2L, 1L, 3L, 2L, 2L, 2L, 3L, 2L, 3L, 2L, 1L, 3L, 3L, 3L, 2L, 3L, 1L, 3L, 3L, 1L, 3L, 2L, 3L, 1L, 1L, 1L, 2L, 3L, 3L, 3L, 2L, 2L, 3L, 3L)), .Names = c("ID", "Type", "Set", "Loc"), class = "data.frame", row.names = c(NA, -48L)) # let's add Loc to our ID d$key <- d$ID d$ID <- paste0(d$Loc,".",d$ID) # Get vertex relationships sets <- unique(d$Set[duplicated(d$Set)]) rel <- vector("list", length(sets)) for (i in 1:length(sets)) { rel[[i]] <- as.data.frame(t(combn(subset(d, d$Set ==sets[i])$ID, 2))) } rel <- rbindlist(rel) # Get the graph g <- graph.data.frame(rel, directed=F, vertices=d) clr <- as.factor(V(g)$Loc) levels(clr) <- c("salmon", "wheat", "lightskyblue") V(g)$color <- as.character(clr) V(g)$size = degree(g)*5 # Plot plot(g, layout = layout.circle, vertex.label=NA) edgebundle( g )->eb eb

在这里输入图像说明

我讨厌为另一个问题添加另一个答案，但我不知道有什么办法来处理评论中提出的额外问题。 评论问我们如何着色边缘。 一般来说，响应很容易，但在这种情况下，答案需要重写edgebundleR的大部分代码，或者需要进行破解。 我会在下面进行破解。 

 library(edgebundleR) library(igraph) library(data.table) d <- structure(list(ID = c("KP1009", "GP3040", "KP1757", "GP2243", "KP682", "KP1789", "KP1933", "KP1662", "KP1718", "GP3339", "GP4007", "GP3398", "GP6720", "KP808", "KP1154", "KP748", "GP4263", "GP1132", "GP5881", "GP6291", "KP1004", "KP1998", "GP4123", "GP5930", "KP1070", "KP905", "KP579", "KP1100", "KP587", "GP913", "GP4864", "KP1513", "GP5979", "KP730", "KP1412", "KP615", "KP1315", "KP993", "GP1521", "KP1034", "KP651", "GP2876", "GP4715", "GP5056", "GP555", "GP408", "GP4217", "GP641"), Type = c("B", "A", "B", "A", "B", "B", "B", "B", "B", "A", "A", "A", "A", "B", "B", "B", "A", "A", "A", "A", "B", "B", "A", "A", "B", "B", "B", "B", "B", "A", "A", "B", "A", "B", "B", "B", "B", "B", "A", "B", "B", "A", "A", "A", "A", "A", "A", "A"), Set = c(15L, 1L, 10L, 21L, 5L, 9L, 12L, 15L, 16L, 19L, 22L, 3L, 12L, 22L, 15L, 25L, 10L, 25L, 12L, 3L, 10L, 8L, 8L, 20L, 20L, 19L, 25L, 15L, 6L, 21L, 9L, 5L, 24L, 9L, 20L, 5L, 2L, 2L, 11L, 9L, 16L, 10L, 21L, 4L, 1L, 8L, 5L, 11L), Loc = c(3L, 2L, 3L, 1L, 3L, 3L, 3L, 1L, 2L, 1L, 3L, 1L, 1L, 2L, 2L, 1L, 3L, 2L, 2L, 2L, 3L, 2L, 3L, 2L, 1L, 3L, 3L, 3L, 2L, 3L, 1L, 3L, 3L, 1L, 3L, 2L, 3L, 1L, 1L, 1L, 2L, 3L, 3L, 3L, 2L, 2L, 3L, 3L)), .Names = c("ID", "Type", "Set", "Loc"), class = "data.frame", row.names = c(NA, -48L)) # let's add Loc to our ID d$key <- d$ID d$ID <- paste0(d$Loc,".",d$ID) # Get vertex relationships sets <- unique(d$Set[duplicated(d$Set)]) rel <- vector("list", length(sets)) for (i in 1:length(sets)) { rel[[i]] <- as.data.frame(t(combn(subset(d, d$Set ==sets[i])$ID, 2))) } rel <- rbindlist(rel) # Get the graph g <- graph.data.frame(rel, directed=F, vertices=d) clr <- as.factor(V(g)$Loc) levels(clr) <- c("salmon", "wheat", "lightskyblue") V(g)$color <- as.character(clr) # Plot plot(g, layout = layout.circle, vertex.size=degree(g)*5, vertex.label=NA) edgebundle( g )->eb eb # temporary hack to accomplish edge coloring # requires newest Github version of htmlwidgets # devtools::install_github("ramnathv/htmlwidgets") # add some imaginary colors E(g)$color <- c("purple","green","black")[floor(runif(length(E(g)),1,4))] # now append these edge attributes to our htmlwidget x eb$x$edges <- jsonlite::toJSON(get.data.frame(g,what="edges")) eb <- htmlwidgets::onRender( eb, ' function(el,x){ // loop through each of our edges supplied // and change the color x.edges.map(function(edge){ var source = edge.from.split(".")[1]; var target = edge.to.split(".")[1]; d3.select(el).select(".link.source-" + source + ".target-" + target) .style("stroke",edge.color); }) } ' ) eb
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