我想将散布图转换为网球场图像上的热图图块图

Question

我在网球场上有一些分散的位置，例如：

x  y 
20 22
30 41 
20 89

网球场图像转换为100x100

我想在网球场的图像上叠加的热图，以指出出现次数最多和发生次数最少的区域

示例：

Answer 1

您可以创建平滑的梯度热图，而不是平铺的热图。这是一个用您的网球场图像和一些废话数据制作的示例。

示例代码：

#load the libraries
library(ggplot2)
library(png)

#load the image of the tennis court
backgroundImage <- readPNG("tennis_court.png")

#load your data
#the data used in this example would be a .csv file with "x" and "y" columns
data <- read.csv("tennis_data.csv", header = TRUE, sep = ",", stringsAsFactors = FALSE)

#make the plot
ggplot(data, aes(x,y)) + #the 'x' and 'y' here reference the column names in your .csv file 
  annotation_raster(backgroundImage, xmin=-Inf, xmax=Inf, ymin=-Inf, ymax=Inf) +
  stat_density2d(geom = "polygon", aes(fill=..level.., alpha=..level..)) +
  scale_alpha_continuous(range=c(0.05,0.4)) + #range values adjust opacity of the overlay
  scale_fill_gradient(low="blue",high="red") +
  scale_x_continuous(limits=c(0,dim(backgroundImage )[2]),expand=c(0,0)) +
  scale_y_continuous(limits=c(0,dim(backgroundImage )[1]),expand=c(0,0)) +
  ggtitle("Tennis court heatmap") + #you can put a title here
  #geom_point(colour="red",alpha=0.01)+ #uncomment this line to show the individual data points
  coord_fixed()