如何计算自定义尺寸网格中每平方点的点数？

Question

我有一个区域内个人的大型数据集。但我想通过用预定义的网格分隔我的场或空间来改变采样设计。这是数据集：

set.seed(1456)
n = 100
x=rnorm(n)
x
y = 1:n
df =data.frame(x = x, y = y, sp = sample(letters[1:5], size = 100,replace = T),stringsAsFactors = TRUE)

plot(y = df$x, x =  y, pch =21, 
     bg = df$sp,
     col = df$sp, 
     cex = .4)

这将创建我正在学习的区域的网格

xytransect <- expand.grid(seq(0, n, 5), seq(min(x), max(x), .6))

这是为了显示＆＃34;节点＆＃34;网格

points(xytransect, cex= 0.3, pch = 21, 
       bg  = "pink", 
       col = "pink")

这只是显示该区域的实际网格。

abline(v = seq(0, n, 5), h = seq(min(x), max(x), .6))

这个想法是将物种分组，看看有多少物种存在于网格的正方形内。

我能够在整个区域根据他们的名字对物种（这里是字母）进行分组。但是如何将它们分组到我创建的网格上？

library(dplyr)
df %>%  
  group_by(sp) %>% 
  summarise(n()) 

是否有可能获得每个方块的中心并根据其内部的物种（字母）数量为方块着色？

杰森的答案。

Answer 1

我编辑了响应以使用与Q中相同的bin定义。

ibins <- seq(0, nrow(df)+5, 5)
jbins <- seq(min(df$x)-0.6, max(df$x)+0.6, .6)
xytransect <- expand.grid(seq(0, n, 5), seq(min(x), max(x), .6))

out <- df %>% 
  mutate(i = min(ibins) + 5*(cut(row_number(), breaks= ibins,labels=FALSE)-1),
         j = min(jbins) + 0.6*(cut(x,breaks=jbins,labels=FALSE)-1)) %>%
  group_by(i,j) %>% 
  summarise(count=n()) %>%
  ungroup() %>%
  mutate(i_center = i+2.5,
         j_center = j+0.3)


plot(out$i_center, out$j_center, cex = out$count/max(out$count), pch = 21, col ="orange", bg = "orange")
abline(v = seq(0, n, 5), h = seq(min(x), max(x), .6))

Answer 2

这是一个答案，使用ggplot2的geom_tile()绘制每个图块中找到的唯一种类数量填充的图块，这是OP请求的，并且与每个图块的个体数量不同。

library(dplyr)
library(ggplot2)

# Add some excess to the limits to ensure that all points are captured,
# even those on the edges.
xcoords <- seq(min(x)-1, max(x)+1, .6)
ycoords <- seq(-5, n+5, 5)

# Determine cell index and its coordinates for each individual.
df <- df %>%
  mutate(x_cell_index = sapply(x, function(z) which(z < xcoords)[1]),
         x_cell_min = xcoords[x_cell_index - 1],
         x_cell_max = xcoords[x_cell_index],
         y_cell_index = sapply(y, function(z) which(z < ycoords)[1]),
         y_cell_min = ycoords[y_cell_index - 1],
         y_cell_max = ycoords[y_cell_index])

# Summarize the number of unique species found in each cell.
df_cellcounts <- df %>%
  group_by(x_cell_min, x_cell_max, y_cell_min, y_cell_max) %>%
  summarize(n_spp = length(unique(sp)))

# Plot it.
ggplot(df_cellcounts, aes(x = (x_cell_min+x_cell_max)/2, y = (y_cell_min+y_cell_max)/2, fill = factor(n_spp))) +
  geom_tile()

这会生成以下图表。