用ggplot在背景图上绘制数据 [英] Plot data over background image with ggplot
问题描述
我试图在背景图片上绘制一些数据。问题在于两个图层最终都使用相同的比例。这是不幸的问题。
一个例子。
我想绘制一些数据在这。
所以
ggplot(image,aes(row,-column,fill = fill) ))+ geom_tile()+
scale_fill_identity()+ geom_point(data = df2,aes(x = x,y = -y))
但它最终会像表示它不能完成,但我希望有一个解决方法或我忽略的东西。
试试这个(或者annotation_raster)
library(ggplot2)
library(jpeg)
library(grid)
$ b img< - readJPEG(image.jpg)
df < - data.frame(x = sample(1:64,1000,replace = T),
y = sample(1:64,1000,replace = T))
ggplot(df,aes(x,y))+
annotation_custom(rasterGrob(img,width = unit(1,npc),height = unit(1,npc)),
-Inf,Inf,-Inf,Inf)+
stat_bin2d()+
scale_x_continuous(expand = c(0,0))+
scale_y_continuous(expand = c(0, 0))
I'm trying to plot some data over a background image. The problem is that both layers end up using the same scale. This is unfortunately problematic.
An example.
I want to plot some data over this image.
Right. So I plot it in ggplot like so.
img <- readJPEG("image.jpg")
image <- apply(img, 1:2, function(v) rgb(v[1], v[2], v[3]))
image <- melt(image)
ggplot(image, aes(row, -column, fill=fill)) + geom_tile() + scale_fill_identity()
And it works well. So, let's add some data on top.
df <- data.frame(x=sample(1:64, 1000, replace=T),
y=sample(1:64, 1000, replace=T))
ggplot(df, aes(x,y)) + stat_bin2d()
Plotting the sample data, I get this.
So I just want this data plot layered over the gradient image.
ggplot(image, aes(row, -column, fill=fill)) + geom_tile() +
scale_fill_identity() + geom_point(data=df2, aes(x=x, y=-y))
But it ends up like this
Trying to specify a second fill scale throws an error. I see this says it can't be done, but I'm hoping that there is a workaround or something I'm overlooking.
Try this, (or alternatively annotation_raster)
library(ggplot2)
library(jpeg)
library(grid)
img <- readJPEG("image.jpg")
df <- data.frame(x=sample(1:64, 1000, replace=T),
y=sample(1:64, 1000, replace=T))
ggplot(df, aes(x,y)) +
annotation_custom(rasterGrob(img, width=unit(1,"npc"), height=unit(1,"npc")),
-Inf, Inf, -Inf, Inf) +
stat_bin2d() +
scale_x_continuous(expand=c(0,0)) +
scale_y_continuous(expand=c(0,0))
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