我试图绘制一个网络，显示17种植物性状之间的依赖关系。该网络将用于帮助解释其他一些分析的结果，而不是为依赖关系本身提供方向。
我在R中使用igraph，输入一个17 x17的相关矩阵。矩阵中的相关性被改变，第一位数字代表一个类别。虽然我对R相当陌生，但从某种意义上说，我几乎可以生成我所设想的图形。
但是，我找不到一种方法使边样式依赖于相关性的值。我可以对颜色和权重这样做，但是以依赖于权重的方式添加lty或edge.lty并不能得到所需的图形，尽管代码运行没有错误。我们的想法是使用3种线型，这样介于-4和-3之间的值与介于-3和-2等之间的值具有不同的样式。“组”表示仅在处理x中或仅在y中等存在的相关性。
在这里四处寻找帮助很多次，我没有遇到这个问题，所以我想我应该问一下。
我一直在使用的代码（下面）可能不漂亮，但对于像我这样没有经验的用户来说，它最不起作用：）
我尝试（在其他人中）添加E（graphY 1 W）[weight <= -4.0 & weight < -3.75]$lty <- 3 #dotted。然而，正如前面所说的，代码运行时没有错误，但行仍然是实心的。能做到吗？

graphY1W<-graph.adjacency(Y1W,weighted=TRUE,mode="undirected",diag=FALSE)
E(graphY1W)[weight <= -4.0 & weight < -3.75]$color <- "black"      #strong - relationship group1
E(graphY1W)[weight <= -4.0 & weight < -3.75]$width <- 7
E(graphY1W)[weight >= -3.75 & weight <= -3.5 ]$color <- "black"    #weak - relationship group1
E(graphY1W)[weight >= -3.75 & weight <= -3.5 ]$width <- 3
E(graphY1W)[weight <=  4.0 & weight > 3.75 ]$color <- "grey"       #strong + relationship group1
E(graphY1W)[weight <=  4.0 & weight > 3.75 ]$width <- 7
E(graphY1W)[weight <= 3.75 & weight >= 3.5 ]$color <- "grey"      #weak + relationship group1
E(graphY1W)[weight <= 3.75 & weight >= 3.5 ]$width <- 3
E(graphY1W)[weight >= -3.0 & weight < -2.75]$color <- "black"     #strong - relationship group2
E(graphY1W)[weight >= -3.0 & weight < -2.75]$width <- 7
E(graphY1W)[weight >= -2.75 & weight <= -2.5 ]$color <- "black"   #etc
E(graphY1W)[weight >= -2.75 & weight <= -2.5 ]$width <- 3
E(graphY1W)[weight <=  3.0 & weight > 2.75 ]$color <- "grey"
E(graphY1W)[weight <=  3.0 & weight > 2.75 ]$width <- 7
E(graphY1W)[weight <= 2.75 & weight >= 2.5 ]$color <- "grey"
E(graphY1W)[weight <= 2.75 & weight >= 2.5 ]$width <- 3
E(graphY1W)[weight >= -2.0 & weight < -1.75 ]$color <- "black" 
E(graphY1W)[weight >= -2.0 & weight < -1.75 ]$width <- 7
E(graphY1W)[weight >= -1.75 & weight <= -1.5 ]$color <- "black"
E(graphY1W)[weight >= -1.75 & weight <= -1.5 ]$width <- 3
E(graphY1W)[weight <= 2.0 & weight >  1.75 ]$color <- "grey"
E(graphY1W)[weight <= 2.0 & weight >  1.75 ]$width <- 7
E(graphY1W)[weight <= 1.75 & weight >= 1.5 ]$color <- "grey"
E(graphY1W)[weight <= 1.75 & weight >= 1.5 ]$width <- 3
V(graphY1W)$color <-  ifelse(V(graphY1W)$name=="Pn", "grey",
                      ifelse(V(graphY1W)$name=="gs", "grey",
                      ifelse(V(graphY1W)$name=="Pn_amb.Pn_sat", "grey",
                      ifelse(V(graphY1W)$name=="WUE", "grey",
                      ifelse(V(graphY1W)$name=="WP", "grey",
                      ifelse(V(graphY1W)$name=="TL", "grey95",
                      ifelse(V(graphY1W)$name=="FMDM", "grey95",
                      ifelse(V(graphY1W)$name=="Chl", "grey45",
                      ifelse(V(graphY1W)$name=="Chlab", "grey45",
                      ifelse(V(graphY1W)$name=="Car", "grey45",
                      ifelse(V(graphY1W)$name=="MP", "white",
                      ifelse(V(graphY1W)$name=="LMF", "white",
                      ifelse(V(graphY1W)$name=="SRR", "white",
                      ifelse(V(graphY1W)$name=="SLAP", "grey95",
                      ifelse(V(graphY1W)$name=="AP", "grey95",
                      ifelse(V(graphY1W)$name=="NAR", "white",
                      ifelse(V(graphY1W)$name=="RGR", "white","white")))))))))))))))))
plot(graphY1W,layout=layout.fruchterman.reingold, vertex.color=V(graphY1W)$color,
     vertex.label.color="black", vertex.shape="circle",vertex.size=10, vertex.label.cex=0.9,
     asp=0.5, frame=FALSE)