添加自定义图像到 geom_polygon 填写 ggplot
Adding custom image to geom_polygon fill in ggplot
一位学生问我是否可以使用 R 重新创建类似于下面的图：
这是来自 this paper....
这类东西不是我的专长，但使用以下代码我能够创建 95% CI 椭圆并用 geom_polygon() 绘制它们。我用 rphylopic 包从系统库中抓取的图像填充图像。
#example data/ellipses
set.seed(101)
n <- 1000
x1 <- rnorm(n, mean=2)
y1 <- 1.75 + 0.4*x1 + rnorm(n)
df <- data.frame(x=x1, y=y1, group="A")
x2 <- rnorm(n, mean=8)
y2 <- 0.7*x2 + 2 + rnorm(n)
df <- rbind(df, data.frame(x=x2, y=y2, group="B"))
x3 <- rnorm(n, mean=6)
y3 <- x3 - 5 - rnorm(n)
df <- rbind(df, data.frame(x=x3, y=y3, group="C"))
#calculating ellipses
library(ellipse)
df_ell <- data.frame()
for(g in levels(df$group)){
df_ell <- rbind(df_ell, cbind(as.data.frame(with(df[df$group==g,], ellipse(cor(x, y),
scale=c(sd(x),sd(y)),
centre=c(mean(x),mean(y))))),group=g))
}
#drawing
library(ggplot2)
p <- ggplot(data=df, aes(x=x, y=y,colour=group)) +
#geom_point(size=1.5, alpha=.6) +
geom_polygon(data=df_ell, aes(x=x, y=y,colour=group, fill=group), alpha=0.1, size=1, linetype=1)
### get center points of ellipses
library(dplyr)
ell_center <- df_ell %>% group_by(group) %>% summarise(x=mean(x), y=mean(y))
### animal images
library(rphylopic)
lion <- get_image("e2015ba3-4f7e-4950-9bde-005e8678d77b", size = "512")[[1]]
mouse <- get_image("6b2b98f6-f879-445f-9ac2-2c2563157025", size="512")[[1]]
bug <- get_image("136edfe2-2731-4acd-9a05-907262dd1311", size="512")[[1]]
### overlay images on center points
p + add_phylopic(lion, alpha=0.9, x=ell_center[[1,2]], y=ell_center[[1,3]], ysize=2, color="firebrick1") +
add_phylopic(mouse, alpha=1, x=ell_center[[2,2]], y=ell_center[[2,3]], ysize=2, color="darkgreen") +
add_phylopic(bug, alpha=0.9, x=ell_center[[3,2]], y=ell_center[[3,3]], ysize=2, color="mediumblue") +
theme_bw()
给出以下内容：
这没问题，但我真正想做的是将图像直接添加到 geom_polygon 的 'fill' 命令中。这可能吗 ？
#example data/ellipses set.seed(101) n <- 1000 x1 <- rnorm(n, mean=2) y1 <- 1.75 + 0.4*x1 + rnorm(n) df <- data.frame(x=x1, y=y1,
group="A") x2 <- rnorm(n, mean=8) y2 <- 0.7*x2 + 2 + rnorm(n) df <-
rbind(df, data.frame(x=x2, y=y2, group="B")) x3 <- rnorm(n, mean=6)
y3 <- x3 - 5 - rnorm(n) df <- rbind(df, data.frame(x=x3, y=y3,
group="C"))
#calculating ellipses library(ellipse) df_ell <- data.frame() for(g in levels(df$group)){
df_ell <- rbind(df_ell,
cbind(as.data.frame(with(df[df$group==g,], ellipse(cor(x, y),
scale=c(sd(x),sd(y)),
centre=c(mean(x),mean(y))))),group=g)) }
#drawing library(ggplot2) p <- ggplot(data=df, aes(x=x, y=y,colour=group)) +
#geom_point(size=1.5, alpha=.6) +
geom_polygon(data=df_ell, aes(x=x, y=y,colour=group, fill=group),
alpha=0.1, size=1, linetype=1)
一个不使用 ggplot 的快速而丑陋的解决方案可能是使用 rasterImager 和 package(jpg)（或 png，具体取决于您的图像格式）：
set.seed(101)
n <- 1000
x1 <- rnorm(n, mean=2)
y1 <- 1.75 + 0.4*x1 + rnorm(n)
df <- data.frame(x=x1, y=y1, group="1")
x2 <- rnorm(n, mean=8)
y2 <- 0.7*x2 + 2 + rnorm(n)
df <- rbind(df, data.frame(x=x2, y=y2, group="2"))
x3 <- rnorm(n, mean=6)
y3 <- x3 - 5 - rnorm(n)
df <- rbind(df, data.frame(x=x3, y=y3, group="3"))
plot(df$x,df$y,type="n")
for(g in unique(df$group)){
ifile=readJPEG(paste(g,".jpg",sep=""),FALSE)
x=df$x[df$group == g]
y=df$y[df$group == g]
xmin=mean(x)-sd(x)*2
ymin=mean(y)-sd(y)*2
xmax=mean(x)+sd(x)*2
ymax=mean(y)+sd(y)*2
rasterImage(ifile,xmin,ymin,xmax,ymax)
}
（图片是 "random"在维基媒体上找到的图片，因此重命名）
在这里，我只是将图像以每组的平均值为中心（如文章中所示），并使它们的大小与标准差成正比。使其符合文章中使用的 95% 置信区间并不难。
这不完全是所需的结果，但它很容易做到（尽管如果你真的想让你的图像适合椭圆，我更愿意使用 gimp 解决方案，正如@Mike 所建议的）
我们无法为 ggplot 设置图案填充，但我们可以在 geom_tile 的帮助下做出一个非常简单的解决方法。重现您的初始数据：
#example data/ellipses
set.seed(101)
n <- 1000
x1 <- rnorm(n, mean=2)
y1 <- 1.75 + 0.4*x1 + rnorm(n)
df <- data.frame(x=x1, y=y1, group="A")
x2 <- rnorm(n, mean=8)
y2 <- 0.7*x2 + 2 + rnorm(n)
df <- rbind(df, data.frame(x=x2, y=y2, group="B"))
x3 <- rnorm(n, mean=6)
y3 <- x3 - 5 - rnorm(n)
df <- rbind(df, data.frame(x=x3, y=y3, group="C"))
#calculating ellipses
library(ellipse)
df_ell <- data.frame()
for(g in levels(df$group)){
df_ell <-
rbind(df_ell, cbind(as.data.frame(
with(df[df$group==g,], ellipse(cor(x, y), scale=c(sd(x),sd(y)),
centre=c(mean(x),mean(y))))),group=g))
}
我想展示的主要功能是将光栅图像转换为 data.frame，列为 X、Y、color，这样我们稍后可以用 geom_tile
require("dplyr")
require("tidyr")
require("ggplot2")
require("png")
# getting sample pictures
download.file("http://content.mycutegraphics.com/graphics/alligator/alligator-reading-a-book.png", "alligator.png", mode = "wb")
download.file("http://content.mycutegraphics.com/graphics/animal/elephant-and-bird.png", "elephant.png", mode = "wb")
download.file("http://content.mycutegraphics.com/graphics/turtle/girl-turtle.png", "turtle.png", mode = "wb")
pic_allig <- readPNG("alligator.png")
pic_eleph <- readPNG("elephant.png")
pic_turtl <- readPNG("turtle.png")
# converting raster image to plottable data.frame
ggplot_rasterdf <- function(color_matrix, bottom = 0, top = 1, left = 0, right = 1) {
require("dplyr")
require("tidyr")
if (dim(color_matrix)[3] > 3) hasalpha <- T else hasalpha <- F
outMatrix <- matrix("#00000000", nrow = dim(color_matrix)[1], ncol = dim(color_matrix)[2])
for (i in 1:dim(color_matrix)[1])
for (j in 1:dim(color_matrix)[2])
outMatrix[i, j] <- rgb(color_matrix[i,j,1], color_matrix[i,j,2], color_matrix[i,j,3], ifelse(hasalpha, color_matrix[i,j,4], 1))
colnames(outMatrix) <- seq(1, ncol(outMatrix))
rownames(outMatrix) <- seq(1, nrow(outMatrix))
as.data.frame(outMatrix) %>% mutate(Y = nrow(outMatrix):1) %>% gather(X, color, -Y) %>%
mutate(X = left + as.integer(as.character(X))*(right-left)/ncol(outMatrix), Y = bottom + Y*(top-bottom)/nrow(outMatrix))
}
正在转换图像：
# preparing image data
pic_allig_dat <-
ggplot_rasterdf(pic_allig,
left = min(df_ell[df_ell$group == "A",]$x),
right = max(df_ell[df_ell$group == "A",]$x),
bottom = min(df_ell[df_ell$group == "A",]$y),
top = max(df_ell[df_ell$group == "A",]$y) )
pic_eleph_dat <-
ggplot_rasterdf(pic_eleph, left = min(df_ell[df_ell$group == "B",]$x),
right = max(df_ell[df_ell$group == "B",]$x),
bottom = min(df_ell[df_ell$group == "B",]$y),
top = max(df_ell[df_ell$group == "B",]$y) )
pic_turtl_dat <-
ggplot_rasterdf(pic_turtl, left = min(df_ell[df_ell$group == "C",]$x),
right = max(df_ell[df_ell$group == "C",]$x),
bottom = min(df_ell[df_ell$group == "C",]$y),
top = max(df_ell[df_ell$group == "C",]$y) )
据我所知，作者只想在椭圆内绘制图像，而不是原始矩形。我们可以借助包 sp.
中的 point.in.polygon 函数来实现它
# filter image-data.frames keeping only rows inside ellipses
require("sp")
gr_A_df <-
pic_allig_dat[point.in.polygon(pic_allig_dat$X, pic_allig_dat$Y,
df_ell[df_ell$group == "A",]$x,
df_ell[df_ell$group == "A",]$y ) %>% as.logical,]
gr_B_df <-
pic_eleph_dat[point.in.polygon(pic_eleph_dat$X, pic_eleph_dat$Y,
df_ell[df_ell$group == "B",]$x,
df_ell[df_ell$group == "B",]$y ) %>% as.logical,]
gr_C_df <-
pic_turtl_dat[point.in.polygon(pic_turtl_dat$X, pic_turtl_dat$Y,
df_ell[df_ell$group == "C",]$x,
df_ell[df_ell$group == "C",]$y ) %>% as.logical,]
最后...
#drawing
p <- ggplot(data=df) +
geom_polygon(data=df_ell, aes(x=x, y=y,colour=group, fill=group), alpha=0.1, size=1, linetype=1)
p + geom_tile(data = gr_A_df, aes(x = X, y = Y), fill = gr_A_df$color) +
geom_tile(data = gr_B_df, aes(x = X, y = Y), fill = gr_B_df$color) +
geom_tile(data = gr_C_df, aes(x = X, y = Y), fill = gr_C_df$color) + theme_bw()
我们可以轻松地调整图的大小而无需更改代码。
当然，您应该牢记机器的性能，并且可能不会选择 20MP 图片在 ggplot =)
中打印
一位学生问我是否可以使用 R 重新创建类似于下面的图：
这类东西不是我的专长，但使用以下代码我能够创建 95% CI 椭圆并用 geom_polygon() 绘制它们。我用 rphylopic 包从系统库中抓取的图像填充图像。
#example data/ellipses
set.seed(101)
n <- 1000
x1 <- rnorm(n, mean=2)
y1 <- 1.75 + 0.4*x1 + rnorm(n)
df <- data.frame(x=x1, y=y1, group="A")
x2 <- rnorm(n, mean=8)
y2 <- 0.7*x2 + 2 + rnorm(n)
df <- rbind(df, data.frame(x=x2, y=y2, group="B"))
x3 <- rnorm(n, mean=6)
y3 <- x3 - 5 - rnorm(n)
df <- rbind(df, data.frame(x=x3, y=y3, group="C"))
#calculating ellipses
library(ellipse)
df_ell <- data.frame()
for(g in levels(df$group)){
df_ell <- rbind(df_ell, cbind(as.data.frame(with(df[df$group==g,], ellipse(cor(x, y),
scale=c(sd(x),sd(y)),
centre=c(mean(x),mean(y))))),group=g))
}
#drawing
library(ggplot2)
p <- ggplot(data=df, aes(x=x, y=y,colour=group)) +
#geom_point(size=1.5, alpha=.6) +
geom_polygon(data=df_ell, aes(x=x, y=y,colour=group, fill=group), alpha=0.1, size=1, linetype=1)
### get center points of ellipses
library(dplyr)
ell_center <- df_ell %>% group_by(group) %>% summarise(x=mean(x), y=mean(y))
### animal images
library(rphylopic)
lion <- get_image("e2015ba3-4f7e-4950-9bde-005e8678d77b", size = "512")[[1]]
mouse <- get_image("6b2b98f6-f879-445f-9ac2-2c2563157025", size="512")[[1]]
bug <- get_image("136edfe2-2731-4acd-9a05-907262dd1311", size="512")[[1]]
### overlay images on center points
p + add_phylopic(lion, alpha=0.9, x=ell_center[[1,2]], y=ell_center[[1,3]], ysize=2, color="firebrick1") +
add_phylopic(mouse, alpha=1, x=ell_center[[2,2]], y=ell_center[[2,3]], ysize=2, color="darkgreen") +
add_phylopic(bug, alpha=0.9, x=ell_center[[3,2]], y=ell_center[[3,3]], ysize=2, color="mediumblue") +
theme_bw()
给出以下内容：
这没问题，但我真正想做的是将图像直接添加到 geom_polygon 的 'fill' 命令中。这可能吗 ？
#example data/ellipses set.seed(101) n <- 1000 x1 <- rnorm(n, mean=2) y1 <- 1.75 + 0.4*x1 + rnorm(n) df <- data.frame(x=x1, y=y1,
group="A") x2 <- rnorm(n, mean=8) y2 <- 0.7*x2 + 2 + rnorm(n) df <-
rbind(df, data.frame(x=x2, y=y2, group="B")) x3 <- rnorm(n, mean=6)
y3 <- x3 - 5 - rnorm(n) df <- rbind(df, data.frame(x=x3, y=y3,
group="C"))
#calculating ellipses library(ellipse) df_ell <- data.frame() for(g in levels(df$group)){
df_ell <- rbind(df_ell,
cbind(as.data.frame(with(df[df$group==g,], ellipse(cor(x, y),
scale=c(sd(x),sd(y)),
centre=c(mean(x),mean(y))))),group=g)) }
#drawing library(ggplot2) p <- ggplot(data=df, aes(x=x, y=y,colour=group)) +
#geom_point(size=1.5, alpha=.6) +
geom_polygon(data=df_ell, aes(x=x, y=y,colour=group, fill=group),
alpha=0.1, size=1, linetype=1)
一个不使用 ggplot 的快速而丑陋的解决方案可能是使用 rasterImager 和 package(jpg)（或 png，具体取决于您的图像格式）：
set.seed(101)
n <- 1000
x1 <- rnorm(n, mean=2)
y1 <- 1.75 + 0.4*x1 + rnorm(n)
df <- data.frame(x=x1, y=y1, group="1")
x2 <- rnorm(n, mean=8)
y2 <- 0.7*x2 + 2 + rnorm(n)
df <- rbind(df, data.frame(x=x2, y=y2, group="2"))
x3 <- rnorm(n, mean=6)
y3 <- x3 - 5 - rnorm(n)
df <- rbind(df, data.frame(x=x3, y=y3, group="3"))
plot(df$x,df$y,type="n")
for(g in unique(df$group)){
ifile=readJPEG(paste(g,".jpg",sep=""),FALSE)
x=df$x[df$group == g]
y=df$y[df$group == g]
xmin=mean(x)-sd(x)*2
ymin=mean(y)-sd(y)*2
xmax=mean(x)+sd(x)*2
ymax=mean(y)+sd(y)*2
rasterImage(ifile,xmin,ymin,xmax,ymax)
}
（图片是 "random"在维基媒体上找到的图片，因此重命名）
在这里，我只是将图像以每组的平均值为中心（如文章中所示），并使它们的大小与标准差成正比。使其符合文章中使用的 95% 置信区间并不难。
这不完全是所需的结果，但它很容易做到（尽管如果你真的想让你的图像适合椭圆，我更愿意使用 gimp 解决方案，正如@Mike 所建议的）
我们无法为 ggplot 设置图案填充，但我们可以在 geom_tile 的帮助下做出一个非常简单的解决方法。重现您的初始数据：
#example data/ellipses
set.seed(101)
n <- 1000
x1 <- rnorm(n, mean=2)
y1 <- 1.75 + 0.4*x1 + rnorm(n)
df <- data.frame(x=x1, y=y1, group="A")
x2 <- rnorm(n, mean=8)
y2 <- 0.7*x2 + 2 + rnorm(n)
df <- rbind(df, data.frame(x=x2, y=y2, group="B"))
x3 <- rnorm(n, mean=6)
y3 <- x3 - 5 - rnorm(n)
df <- rbind(df, data.frame(x=x3, y=y3, group="C"))
#calculating ellipses
library(ellipse)
df_ell <- data.frame()
for(g in levels(df$group)){
df_ell <-
rbind(df_ell, cbind(as.data.frame(
with(df[df$group==g,], ellipse(cor(x, y), scale=c(sd(x),sd(y)),
centre=c(mean(x),mean(y))))),group=g))
}
我想展示的主要功能是将光栅图像转换为 data.frame，列为 X、Y、color，这样我们稍后可以用 geom_tile
require("dplyr")
require("tidyr")
require("ggplot2")
require("png")
# getting sample pictures
download.file("http://content.mycutegraphics.com/graphics/alligator/alligator-reading-a-book.png", "alligator.png", mode = "wb")
download.file("http://content.mycutegraphics.com/graphics/animal/elephant-and-bird.png", "elephant.png", mode = "wb")
download.file("http://content.mycutegraphics.com/graphics/turtle/girl-turtle.png", "turtle.png", mode = "wb")
pic_allig <- readPNG("alligator.png")
pic_eleph <- readPNG("elephant.png")
pic_turtl <- readPNG("turtle.png")
# converting raster image to plottable data.frame
ggplot_rasterdf <- function(color_matrix, bottom = 0, top = 1, left = 0, right = 1) {
require("dplyr")
require("tidyr")
if (dim(color_matrix)[3] > 3) hasalpha <- T else hasalpha <- F
outMatrix <- matrix("#00000000", nrow = dim(color_matrix)[1], ncol = dim(color_matrix)[2])
for (i in 1:dim(color_matrix)[1])
for (j in 1:dim(color_matrix)[2])
outMatrix[i, j] <- rgb(color_matrix[i,j,1], color_matrix[i,j,2], color_matrix[i,j,3], ifelse(hasalpha, color_matrix[i,j,4], 1))
colnames(outMatrix) <- seq(1, ncol(outMatrix))
rownames(outMatrix) <- seq(1, nrow(outMatrix))
as.data.frame(outMatrix) %>% mutate(Y = nrow(outMatrix):1) %>% gather(X, color, -Y) %>%
mutate(X = left + as.integer(as.character(X))*(right-left)/ncol(outMatrix), Y = bottom + Y*(top-bottom)/nrow(outMatrix))
}
正在转换图像：
# preparing image data
pic_allig_dat <-
ggplot_rasterdf(pic_allig,
left = min(df_ell[df_ell$group == "A",]$x),
right = max(df_ell[df_ell$group == "A",]$x),
bottom = min(df_ell[df_ell$group == "A",]$y),
top = max(df_ell[df_ell$group == "A",]$y) )
pic_eleph_dat <-
ggplot_rasterdf(pic_eleph, left = min(df_ell[df_ell$group == "B",]$x),
right = max(df_ell[df_ell$group == "B",]$x),
bottom = min(df_ell[df_ell$group == "B",]$y),
top = max(df_ell[df_ell$group == "B",]$y) )
pic_turtl_dat <-
ggplot_rasterdf(pic_turtl, left = min(df_ell[df_ell$group == "C",]$x),
right = max(df_ell[df_ell$group == "C",]$x),
bottom = min(df_ell[df_ell$group == "C",]$y),
top = max(df_ell[df_ell$group == "C",]$y) )
据我所知，作者只想在椭圆内绘制图像，而不是原始矩形。我们可以借助包 sp.
point.in.polygon 函数来实现它
# filter image-data.frames keeping only rows inside ellipses
require("sp")
gr_A_df <-
pic_allig_dat[point.in.polygon(pic_allig_dat$X, pic_allig_dat$Y,
df_ell[df_ell$group == "A",]$x,
df_ell[df_ell$group == "A",]$y ) %>% as.logical,]
gr_B_df <-
pic_eleph_dat[point.in.polygon(pic_eleph_dat$X, pic_eleph_dat$Y,
df_ell[df_ell$group == "B",]$x,
df_ell[df_ell$group == "B",]$y ) %>% as.logical,]
gr_C_df <-
pic_turtl_dat[point.in.polygon(pic_turtl_dat$X, pic_turtl_dat$Y,
df_ell[df_ell$group == "C",]$x,
df_ell[df_ell$group == "C",]$y ) %>% as.logical,]
最后...
#drawing
p <- ggplot(data=df) +
geom_polygon(data=df_ell, aes(x=x, y=y,colour=group, fill=group), alpha=0.1, size=1, linetype=1)
p + geom_tile(data = gr_A_df, aes(x = X, y = Y), fill = gr_A_df$color) +
geom_tile(data = gr_B_df, aes(x = X, y = Y), fill = gr_B_df$color) +
geom_tile(data = gr_C_df, aes(x = X, y = Y), fill = gr_C_df$color) + theme_bw()
我们可以轻松地调整图的大小而无需更改代码。
当然，您应该牢记机器的性能，并且可能不会选择 20MP 图片在 ggplot =)