ggVis：在不同数据集上创建多个图层的情节 [英] ggVis : creating a plot with multiple layers on different dataset
问题描述
我试图用ggvis重现一个ggplot2图。
该图旨在表示点的坐标（来自对应分析）及其群集（hclust）标准色散椭圆。
TL; DR
我想根据多个数据集制作一个包含多个图层的ggvis图。
因此，功能/管道方法阻止我将其中一个图层分组，而不是其他分组。
整个（简短评论）的代码在那里： a href =https://gist.github.com/RCura/a135446cda079f4fbc10 =noreferrer> https://gist.github.com/RCura/a135446cda079f4fbc10
以下是创建数据的代码：
a （n = 100，平均= 50，sd = 5）
b < - rnorm（n = 100，平均值= 50，sd = 5）
c < - rnorm（n = 100，mean = 50，sd = 5）
mydf < - data.frame（A = a，B = b，C = c，row.names = c （1：100））
library（ade4）
myCA< - dudi.coa（df = mydf，scannf = FALSE，nf = 2）
myDist< - dist.dudi（myCA，amongrow = TRUE）
myClust< - hclust（d = myDist，method =ward.D2）
myClusters< - cutree（tree = myClust，k = 3）
myCAdata< - data.frame（Axis1 = myCA $ li $ Axis1，Axis2 = myCA $ li $ Axis2，Cluster = as.f actor（myClusters））
库（椭圆）＃计算标准偏差椭圆
df_ellipse< - data.frame（）
for（g （myCAdata $ Cluster））{
df_ellipse< - rbind（df_ellipse，
cbind（as.data.frame（
with（myCAdata [myCAdata $ Cluster == g，]，
ellipse（cor（Axis1，Axis2），
level = 0.7，
scale = c（sd（Axis1），sd（Axis2）），
center = c（mean Axis1），mean（Axis2））））），
Cluster = g））
}
我可以通过ggplot2绘图：
library（ggplot2）
myPlot< ; - ggplot（data = myCAdata，aes（x = Axis1，y = Axis2，color = Cluster））+
geom_point（size = 1.5，alpha = .6）+
geom_vline（xintercept = 0， color =black，alpha = 0.5，linetype =longdash）+
geom_hline（xintercept = 0，color =black，alpha = 0.5，linetype =longdash）+
geom_path数据= df_ellip se，aes（x = x，y = y，color = Cluster），size = 0.5，linetype = 1）
myPlot
但是我找不到如何使用ggvis来绘制这个图。
我可以绘制2个不同的图层：
$ b （x），：，格式（x），格式（x），格式（x） ，collapse =< br />）}
ggDF< - myCAdata
ggDF $ name< - row.names（ggDF）
##坐标图
myCoordPlot< - ggvis（x =〜Axis1，y =〜Axis2，key：=〜name，data = ggDF）％>％
（所有值，悬停）
myCoordPlot
省略图（不需要提示工具提示）
myEllPlot < - ggvis（data = df_ellipse，x =〜x，y =〜y）％>％
group_by（Cluster）％>％
layer_paths（x =〜x，y =〜y，stroke =〜Cluster，strokeWidth：= 1）
myEllPlot
但是，当我想在同一个图上绘制两层时：
myFullPlot< - ggvis（data = df_ellipse， x = y，y = y）％>％
layer_paths（x =〜x，y =〜y，stroke =〜Cluster，strokeWidth：= 1）％>％
layer_points（x =〜Axis1，y =〜Axis2，size：= 15，fill =〜Cluster，data = ggDF）％>％
add_tooltip（all_values，hover ）
myFullPlot
椭圆不分组，所以颜色不适合，而椭圆不分开。
如果我尝试对我的椭圆组进行分组，它不起作用：group_by只被layer_paths需要，并且会弄乱layer_points。
任何想法如何使这项工作？
抱歉，这篇很长的文章，但我一直在努力使这项工作数小时：/ $ / $>
问题在于，当您尝试将两者结合使用时，省略号数据集中的group_by Cluster 不是。你需要做以下的工作：
myFullPlot< - ggvis（data = df_ellipse，x =〜x， y =〜y）％>％group_by（Cluster）％>％
layer_paths（stroke =〜Cluster，strokeWidth：= 1）％>％
layer_points （x =〜Axis1，y =〜Axis2，size：= 15，fill =〜Cluster，data = ggDF）
myFullPlot
这样你就可以得到你想要的图表！
PS我假设您的数据创建中存在一些随机性，因为我得到的数据集与您的数据集不同。
I'm trying to reproduce a ggplot2 plot using ggvis. The plot aims at representing the coordinates of points (from a Correspondence Analysis) together with their clusters (hclust) Standard Dispersion Ellipses.
TL; DR
I'd like to make a ggvis plot with multiple layers based on multiple datasets. Thus, the functional/pipe approach stops me from grouping one of the layers and not the other.
The whole (briefly commented) code is there : https://gist.github.com/RCura/a135446cda079f4fbc10
Here's the code for creating the data:
a <- rnorm(n = 100, mean = 50, sd = 5)
b <- rnorm(n = 100, mean = 50, sd = 5)
c <- rnorm(n = 100, mean = 50, sd = 5)
mydf <- data.frame(A = a, B = b, C = c, row.names = c(1:100))
library(ade4)
myCA <- dudi.coa(df = mydf,scannf = FALSE, nf = 2)
myDist <- dist.dudi(myCA, amongrow = TRUE)
myClust <- hclust(d = myDist, method = "ward.D2")
myClusters <- cutree(tree = myClust, k = 3)
myCAdata <- data.frame(Axis1 = myCA$li$Axis1, Axis2 = myCA$li$Axis2, Cluster = as.factor(myClusters))
library(ellipse) # Compute Standard Deviation Ellipse
df_ellipse <- data.frame()
for(g in levels(myCAdata$Cluster)){
df_ellipse <- rbind(df_ellipse,
cbind(as.data.frame(
with(myCAdata[myCAdata$Cluster==g,],
ellipse(cor(Axis1, Axis2),
level=0.7,
scale=c(sd(Axis1),sd(Axis2)),
centre=c(mean(Axis1),mean(Axis2))))),
Cluster=g))
}
I can plot this through ggplot2:
library(ggplot2)
myPlot <- ggplot(data=myCAdata, aes(x=Axis1, y=Axis2,colour=Cluster)) +
geom_point(size=1.5, alpha=.6) +
geom_vline(xintercept = 0, colour="black",alpha = 0.5, linetype = "longdash" ) +
geom_hline(xintercept = 0, colour="black", alpha = 0.5, linetype = "longdash" ) +
geom_path(data=df_ellipse, aes(x=x, y=y,colour=Cluster), size=0.5, linetype=1)
myPlot
But I can't find how to plot this using ggvis.
I can plot the 2 different layers:
library(ggvis)
all_values <- function(x) { paste0(names(x), ": ", format(x), collapse = "<br />")}
ggDF <- myCAdata
ggDF$name <- row.names(ggDF)
## Coordinates plot
myCoordPlot <- ggvis(x = ~Axis1, y = ~Axis2, key := ~name, data = ggDF) %>%
layer_points(size := 15, fill= ~Cluster, data = ggDF) %>%
add_tooltip(all_values, "hover")
myCoordPlot
Ellipses plot (no tooltip requested)
myEllPlot <- ggvis(data = df_ellipse, x = ~x, y = ~ y) %>%
group_by(Cluster) %>%
layer_paths(x= ~x, y= ~y, stroke = ~Cluster, strokeWidth := 1)
myEllPlot
But when I want to plot the 2 layers on the same plot :
myFullPlot <- ggvis(data = df_ellipse, x = ~x, y = ~ y) %>%
layer_paths(x= ~x, y= ~y, stroke = ~Cluster, strokeWidth := 1) %>%
layer_points(x = ~Axis1, y= ~Axis2, size := 15, fill= ~Cluster, data = ggDF) %>%
add_tooltip(all_values, "hover")
myFullPlot
The ellipses are not grouped, so, the color don't fit, and the ellipses are not separated. If I try to group my Ellipses, it doesn't work: the group_by is only required by the layer_paths, and it mess up the layer_points.
Any idea how to make this work? And sorry for this very long post, but I've been trying to make this work for hours :/
The problem is that when you try to combine the two, you do not group_by Cluster on the ellipsis dataset. You need to do the following for it to work:
myFullPlot <- ggvis(data = df_ellipse, x = ~x, y = ~ y) %>% group_by(Cluster) %>%
layer_paths(stroke = ~Cluster, strokeWidth := 1) %>%
layer_points(x = ~Axis1, y= ~Axis2, size := 15, fill= ~Cluster, data = ggDF)
myFullPlot
And this way you get the graph you want!
P.S. I assume there is some randomness in your data creation because I got a different data set than yours.
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