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我正在尝试制作一个类似于此问题底部所示的图：Adding ellipses to a principal component analysis (PCA) plot。但是，我既不熟悉ggplot也不熟悉修改函数ordiellipse()本身，如下所示：Color-coding 95% confidence ellipses for centroids。

因此，我尝试使用参数show.groups，ordiellipse()但我不知道如何告诉这个参数我想要什么。

我正在分析一个包含 83 个站点的表，其中包含大约 418 个物种的丰度数据。我运行了一个具有函数的 DCA，decorana()并在数据上降低了稀有物种的权重。之后，我将平均 Ellenberg 指标值拟合到排序上。

vali <-read.table(file = "VegOrdi2012.txt", header=T)
attach(vali)

calcul.env<-read.table(file = "indicator-values-2012.txt",header=T)
attach(calcul.env)
names(calcul.env)

#Downweighting of rare species
calcul.dca1<-decorana(vali,iweigh=1)
calcul.dca1

#Fitting of environmental values
habi<-envfit(calcul.dca1~Habitat+Light+Temp+Continent+Moisture+pH+Nutrients+Salt,calcul.env,permu=999)
habi

这是Habitat我需要通过以ordiellipse()点显示的所有 83 个图及其作为文本的图号在图表中可视化的因素。栖息地由九个类别组成，其中包括：

with(calcul.env, levels(Habitat))
[1] "Brown"  "Emb"    "Eph"    "FBS"    "GreeS"  "RiBa"   "Tracks" "TraffA"
[9] "UrbanL"

我能够为它们着色和标记，而无需在它们周围绘制椭圆：

#Assigning colors to the nine categories
colvec <- c("black", "darkviolet", "green3", "darkorange", "magenta", "deepskyblue", "red", "blue", "forestgreen")

plot(calcul.dca1, type = "n", xlim=c(-1.5,1.6),ylim=c(-3,3))
ordipointlabel(calcul.dca1, display="site", cex=0.7, col = colvec[Habitat],bg = colvec[Habitat],pch = 21)

# Creating a legend
with(calcul.env, legend("topright", legend = levels(Habitat), cex=0.65,bty = "n",col = colvec, pch = 21, pt.bg = colvec))

但是我如何告诉show.groups参数如何为不同的Habitat类型着色以及为九个椭圆分配标准线型以外的不同线型？

到目前为止，我想出了这个情节使用：

plot(calcul.dca, type="n", xlim=c(-1.5,1.6),ylim=c(-1,1))

ordiellipse(calcul.dca, Habitat, display="site", kind = "sd",
conf = 0.95, label = T, col="black", cex=0.7)

但它相当难以捉摸，因为即使我添加了它也只显示没有绘图的椭圆display="site"。此外，由于它们严重重叠，很难看出哪个是哪个。因此，最好对每种栖息地类型进行不同的着色。

如果您需要我的 DCA 排序数据的摘录，它来了：

dput(calcul.dca1)

structure(list(rproj = structure(c(0.622196100508291, 0.0425187062298239, 
0.809118643435233, 1.42649346881288, 0.942469303820393, 2.14549756552088, 
2.41922446503012, 1.28982244065239, 2.38544988614361, 1.40637644094225, 
1.91277135864581, 0.605410167146248, 0.806888393988314, 0.683853698855826, 
0.487565297706596, 1.33517822183407, 1.0239859712969, 1.11996240234112, 
0.878649568698446, 1.53912253203697, 1.10967929396299, 1.23838793138041, 
0.423890604035373, 0.624635178433215, 0.625774941613906, 0.873372685928585, 
1.02496140772642, 1.44785313041614, 1.08257665268759, 0.349688854561329, 
0.391547839427374, 0.730346245879122, 0.286646737460428, 0.731484625760109, 
1.08559070145785, 1.53243971551768, 0.85664914035342, 1.81525177285522, 
1.5519555131377, 1.39064843441504, 0.760013397658093, 1.22801365648165, 
2.21178067417998, 1.79390604164473, 1.65361126768449, 1.73966835197937, 
1.9237320812287, 1.80114956024378, 2.23293893445506, 2.02322760613128, 
...
0.857428410615221, 1.48594779863814, 0.935954361867925, 1.0524685508641, 
0.898391402052793), .Dim = c(84L, 4L), .Dimnames = list(c("p1", 
"p2", "p3", "p4", "p5", "p6", "p7", "p8", "p9", "p10", "p11", 
"p12", "p13", "p14", "p15", "p16", "p17", "p18", "p19", "p20", 
"p21", "p22", "p23", "p24", "p25", "p26", "p27", "p28", "p29", 
"p30", "p31", "p32", "p33", "p34", "p35", "p36", "p37", "p38", 
"p39", "p40", "p41", "p42", "p43", "p44", "p45", "p46", "p47", 
"p48", "p49", "p50", "p51", "p52", "p53", "p54", "p55", "p56", 
"p57", "p58", "p59", "p61", "p62", "p63", "p64", "p65", "p66", 
"p67", "p68", "p69", "p70", "p71", "p73", "p74", "p75", "p76", 
"p77", "p78", "p79", "p80", "p81", "p82", "p83", "p85", "p86", 
"p87"), c("DCA1", "DCA2", "DCA3", "DCA4"))), cproj = structure(c(1.25651540418674, 
4.10086480672813, 0.985170303000948, 0.356752380731314, 0.0871005927968299, 
-0.65389620717045, 0.416500256857967, -0.0687562150601063, -0.448057138258203, 
-0.851379298478351, -4.22395990436862, 3.38456796429771, 3.50656010401288, 
3.0970679364606, 3.76068022295243, 4.15832492473722, 1.73508588573266, 
-0.0979648246992866, -1.54594775838685, 0.0871005366833882, 2.10389514743405, 
0.705016209734685, -1.54594765746973, -0.264737082168187, 1.28992362813467, 
...
2.37831113227017, 2.6918186855265, 3.96654774047496), .Dim = c(414L, 
4L), .Dimnames = list(c("Ace_cam", "Ace_pla", "Ace_pse", "Ach_mil", 
"Aeg_pod", "Aes_hip", "Agr_cap", "Agr_sto", "All_pet", "Alo_pra", 
"Alo_myo", "Ama_alb", "Ama_bli", "Ama_pow", "Ama_ret", "Amb_art", 
"Ame_lam", "Ang_arc", "Anc_arv", "Ant_cau", "Ant_syl", "Ant_tin", 
"Ant_vul", "Ape_spi", "Aqu_vul", "Ara_tha", "Arc_lap", "Arc_min", 
"Are_ser", "Arr_ela", "Art_bie", "Art_cam", "Art_vul", "Asp_rut", 
...
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1 回答 1

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尝试分别添加每个椭圆，并使用 .将 colvec 中的颜色分别分配给每个 Habitat 组show.groups。例如： 

with(calcul.env, ordiellipse(calcul.dca, Habitat, kind="se", conf=0.95,
                       lwd=2, col="black", show.groups = "Brown"))
with(calcul.env, ordiellipse(calcul.dca, Habitat, kind="se", conf=0.95,
                       lwd=2, col="darkviolet", show.groups = "Emb"))
with(calcul.env, ordiellipse(calcul.dca, Habitat, kind="se", conf=0.95,
                       lwd=2, col="green3", show.groups = "Eph"))

等等。如果需要，您可以通过创建循环来简化此操作。请参阅http://www.mail-archive.com/r-help@r-project.org/msg149786.html

于 2013-03-17T16:35:26.187 回答