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有谁知道如何更改椭圆中颜色的透明度（或 alpha）？
我只想保留情节中的边界线。
我试图模仿这个站点中的代码：http: //www.sthda.com/english/wiki/fviz-pca-quick-principal-component-analysis-data-visualization-r-software-and-data-mining

但我找不到关于椭圆颜色的 alpha 值的选项。

#Dataset
require(ggplot2)
require(ggfortify)
require(factoextra)

set.seed(1)
df <- structure(list(Sample = c("cat", "dog", "rabbit", "chicken", "duck", "butterfly", "ladybug", "rose", "lily", "iris", "maple tree", "pinetree", "ginkgo"), 
                     Class = c("mammalia", "mammalia", "mammalia", "bird", "bird", "insect", "insect", "flower", "flower", "flower", "tree", "tree", "tree"), 
                     Kingdom = c("animalia", "animalia", "animalia", "animalia", "animalia", "animalia", "animalia", "plantae", "plantae", "plantae", "plantae", "plantae", "plantae")), 
                class = "data.frame", row.names = c(NA, -13L))
rownames(df)<-df[,1]
df[,1]<-NULL

for(i in 3:20){
  df[,i]<-sample(100, size=nrow(df), replace=TRUE)
}
df[,c(3:20)]<-log(df[,c(3:20)]+1, base=2)

df #I ommitted the value from v13 to v20 for simplicity
              Class  Kingdom       V3       V4       V5       V6       V7       V8       V9      V10      V11      V12
cat        mammalia animalia 6.108524 5.781360 5.087463 5.357552 4.247928 5.614710 5.000000 5.129283 5.321928 6.303781
dog        mammalia animalia 5.321928 6.228819 6.409391 5.491853 4.523562 6.491853 4.169925 3.459432 4.643856 4.523562
rabbit     mammalia animalia 1.000000 3.000000 5.169925 4.700440 6.303781 4.584963 6.209453 1.000000 5.754888 6.149747
chicken        bird animalia 5.129283 6.209453 6.149747 6.149747 6.044394 6.409391 6.459432 5.459432 6.539159 4.857981
duck           bird animalia 6.459432 6.321928 6.228819 5.321928 6.149747 4.906891 6.392317 5.906891 6.442943 5.247928
butterfly    insect animalia 5.459432 6.426265 5.426265 5.700440 6.459432 3.807355 6.507795 4.754888 5.357552 5.954196
ladybug      insect animalia 3.906891 5.247928 5.285402 5.426265 6.149747 4.523562 5.614710 4.000000 6.614710 5.554589
rose         flower  plantae 6.375039 6.491853 4.392317 2.807355 6.247928 6.554589 6.022368 5.882643 6.392317 6.087463
lily         flower  plantae 5.906891 5.247928 4.857981 4.643856 6.357552 4.857981 6.569856 4.906891 6.507795 6.442943
iris         flower  plantae 5.700440 5.129283 4.392317 5.044394 6.658211 5.614710 6.599913 4.643856 5.169925 6.643856
maple tree     tree  plantae 6.614710 6.491853 5.491853 3.906891 3.807355 5.087463 5.930737 5.426265 5.459432 6.169925
pinetree       tree  plantae 6.426265 5.491853 6.459432 1.584963 5.357552 5.523562 5.700440 5.614710 1.000000 6.643856
ginkgo         tree  plantae 4.459432 6.321928 6.149747 5.523562 6.491853 4.459432 6.554589 6.266787 4.906891 5.700440

pca_df<-prcomp(df[,-c(1,2)], scale.=TRUE)
fviz_pca_ind(pca_df,
             col.ind=df$Kingdom,
             addEllipses = TRUE,
             col.ind.sup=df$Kingdom,
             repel=TRUE)

在此处输入图像描述

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1 回答 1

1

您可以使用ellipse.alpha可以在此处找到的参数。

fviz_pca_ind(pca_df,
             col.ind=df$Kingdom,
             addEllipses = TRUE,
             col.ind.sup=df$Kingdom,
             repel=TRUE, ellipse.alpha = 0)

在此处输入图像描述

（我忘了设置种子。对不起......）

于 2021-12-14T02:35:22.060 回答