如何在具有多个z轴的3D中绘制“ggridges”类型的图

Question

我正在寻找一个在ggplot中的包来制作下面的图。

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我知道ggridges，但它没有3个维度。

Answer 1

您还可以使用ggridges欺骗x轴和网格线以获得相同的效果：

library(ggridges)
library(ggplot2)

slant_factor = 5   # How many units x shift per category? Won't work with zero

intercepts = (20 * (0:4)) / slant_factor + 0.8
ggplot(lincoln_weather, 
       aes(x = `Mean Temperature [F]` - as.numeric(Month)*slant_factor, 
           y = Month, fill = stat(x))) +
  
  geom_abline(slope = -1 / slant_factor , 
              intercept = intercepts,
              color = "gray90") +
  
  geom_density_ridges_gradient(scale = 3, rel_min_height = 0.01, gradient_lwd = 1.) +
  
  scale_x_continuous(expand = c(0, 0),
                     breaks = 20 * (0:4)) +
  scale_y_discrete(expand = expand_scale(mult = c(0.01, 0.25))) +
  scale_fill_viridis_c(name = "Temp. [F]", option = "C") +
  labs(
    title = 'Temperatures in Lincoln NE',
    subtitle = 'Mean temperatures (Fahrenheit) by month for 2016'
  ) +
  theme_ridges(font_size = 13, grid = TRUE) + 
  theme(axis.title.y = element_blank(), panel.grid.major.x = element_blank())

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Answer 2

解决您的问题的两个可能的选项(如果我理解正确的话)如下：

# dummy data
df <- data.frame(grps = factor(sort(rep(c("a","b","c"), 10))),
                 seq = rep(1:10, 3),
                 vlr = c(c(1:6, 4:1), c(1:6, 4:1) + 1, c(1:6, 4:1) + 2))

使用plotly：

library(plotly)

fig <- plot_ly(df, x = ~vlr, y = ~seq, z = ~grps, type = 'scatter3d', mode = 'lines',
  transforms = list(
    list(
      type = 'groupby',
      groups = df$grps)))

fig # you have to rotate it

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使用rayshader将线状图转换为3D，但它将转换为条形图(它的工作诀窍是:定义高度的值进入颜色美感)

library(ggplot2)
library(rayshader)

gl <- ggplot2::ggplot(df, aes(x = grps, y = seq, group = grps, color = vlr)) + 
    ggplot2::geom_line()

rayshader::plot_gg(gl)

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在使用geom_ridgeline()并通知height参数时，ggridges可以处理第三维，但它似乎有点有限(尽管我没有阅读文档以及如何润色和改进这种类型的图表：

library(ggplot2)
library(ggridges)

ggplot2::ggplot(df, aes(x = seq, height = vlr, y = grps, color = grps)) + 
  ggridges::geom_ridgeline()

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