ggplot R:使用固定/等距 X、Y 坐标将 X、Y、Z 点图转换为六边形热图

问题描述 投票:0回答:1

是否可以使用“值”列进行填充,将以下点图转换为感人的六边形热图?

library(ggplot2)

rows = 1:10; cols = 1:10
grid_data = expand.grid(rows, cols)
colnames(grid_data) <- c("x", "y")
set.seed(123)
grid_data$value = sample(1:100, size = nrow(grid_data), replace = TRUE)

ggplot(grid_data, aes(x = x, y = y, color = value)) + geom_point() + theme_void()

非常感谢!

我期待一个感人的六边形热图或用“值”着色的点图。

r ggplot2 heatmap
1个回答
2
投票

不可能直接将方形值网格转换为六边形值网格而不显着扭曲点的相对位置。

另一种方法是将值手动二维插值到六角形网格上:

library(tidyverse)

m1 <- interp::interp(grid_data$x, grid_data$y, grid_data$value, 
                     xo = 0:11, yo = seq(0, 11, sqrt(3)/2))

m2 <- interp::interp(grid_data$x, grid_data$y, grid_data$value, 
                     xo = 0:11 + 0.5, yo = seq(0, 11, sqrt(3)/2))

m1$y <- m1$y[  seq_along(m1$y) %% 2 == 1]
m1$z <- m1$z[, seq_along(m1$x) %% 2 == 1]
m2$y <- m2$y[  seq_along(m2$y) %% 2 == 0]
m2$z <- m2$z[, seq_along(m2$x) %% 2 == 0]

interp::interp2xyz(m1) |>
  as.data.frame() |>
  rbind(interp::interp2xyz(m2) |> as.data.frame()) %>%
  filter(!is.na(z)) %>%
  mutate(group = row_number()) %>%
  rowwise() %>%
  reframe(x = x + hexbin::hexcoords(0.5, sqrt(3)/6)$x,
          y = y + hexbin::hexcoords(0.5, sqrt(3)/6)$y,
          z = first(z),
          group = first(group)) %>%
  ggplot(aes(x, y)) + 
  geom_polygon(aes( fill = z, group = group), color = 'white') + 
  scale_fill_viridis_c() +
  theme_minimal() +
  coord_equal(xlim = c(0, 11), ylim = c(0, 11))


编辑

如果您想要对值进行空间填充插值,并保留实际数据点,则不需要六边形箱:

library(akima)

with(grid_data, interp(x, y, value, nx = 500, ny = 500, linear = FALSE)) |> 
  interp::interp2xyz() |>
  as.data.frame() |>
  ggplot(aes(x = x, y = y, fill = z)) + 
  scale_fill_viridis_c("value") +
  geom_raster() + 
  theme_void(base_size = 20) +
  coord_equal()

如果我们叠加原始点,我们可以看到每个位置都保留了原始值:

with(grid_data, interp(x, y, value, linear = FALSE, nx = 500, ny = 500)) |> 
  interp::interp2xyz() |>
  as.data.frame() |>
  ggplot(aes(x = x, y = y, fill = z)) + 
  scale_fill_viridis_c("value", limits = c(-10, 110), na.value = NA) +
  geom_raster() + 
  geom_point(data = grid_data, shape = 21, size = 5, aes(fill = value)) +
  theme_void(base_size = 20) +
  coord_equal()

如果您愿意,您可以使用填充轮廓:

with(grid_data, interp(x, y, value, nx = 500, ny = 500, linear = FALSE)) |> 
  interp::interp2xyz() |>
  as.data.frame() |>
  ggplot(aes(x = x, y = y, z = z)) + 
  geom_contour_filled() + 
  theme_void(base_size = 20) +
  coord_equal()

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