在geom_tile()/ geom_raster()中标记特定的tile

时间:2012-11-06 20:00:14

标签: r ggplot2

假设我有一个像这样的data.frame:

df <- matrix( rnorm(100), nrow = 10)
rownames(df) <- LETTERS[1:10]
molten <- melt(df)
molten$na <- FALSE
molten[ round(runif(10,  0, 100 )), "na" ] <- T
head(molten)

  Var1 Var2      value    na
1    A    1 -0.2413015 FALSE
2    B    1  1.5077282 FALSE
3    C    1 -1.0798806 TRUE
4    D    1  2.0723791 FALSE

现在,我想使用ggplot和标记那些具有na=TRUE的图块来绘制图块(或栅格)图。目前我将标记绘制为点:

g <- ggplot( molten ) +
  geom_raster( aes( x = Var1, y = Var2, fill = value )  ) + 
  scale_fill_gradient2( low = "blue", high = "red", na.value="black", name = "" ) +
  geom_point( aes( x = Var1, y = Var2, size= as.numeric(na) ) )

tiles with points

然而,由于两个原因,我不太喜欢这个情节:

  1. 即使molten$na = FALSE,仍有一点意义。当然,我可以指定data=molten[ molten$na, ],但实际上这应该是可能的,而无需指定其他数据集。
  2. 我不喜欢这些点,但更喜欢在瓷砖周围有框架或条纹。但我不知道如何实现这一目标。如果我使用geom_segment()条纹,我该如何指定yendxend
  3. 感谢任何帮助。

    修改1 以下是dput的再现性:

    structure(list(Var1 = structure(c(1L, 2L, 3L, 4L, 1L, 2L, 3L, 
    4L, 1L, 2L, 3L, 4L, 1L, 2L, 3L, 4L, 1L, 2L, 3L, 4L), .Label = c("A", 
    "B", "C", "D", "E", "F", "G", "H", "I", "J"), class = "factor"), 
        Var2 = c(6L, 6L, 6L, 6L, 7L, 7L, 7L, 7L, 8L, 8L, 8L, 8L, 
        9L, 9L, 9L, 9L, 10L, 10L, 10L, 10L), value = c(-0.468920099229389, 
        0.996105987531978, -0.527496444770932, -0.767851702991822, 
        -0.36077954422072, -0.145335912847538, 0.114951323188032, 
        0.644232124274217, 0.971443502096584, 0.774515290180507, 
        -0.436252398260595, -0.111174676975868, 1.16095688943808, 
        0.44677656465583, -0.708779168274131, 0.460296447139761, 
        -0.475304748445917, -0.481548436194392, -1.66560630161765, 
        -2.06055347675196), na = c(FALSE, FALSE, FALSE, FALSE, FALSE, 
        FALSE, FALSE, FALSE, TRUE, FALSE, FALSE, FALSE, FALSE, FALSE, 
        FALSE, FALSE, TRUE, FALSE, FALSE, FALSE)), .Names = c("Var1", 
    "Var2", "value", "na"), row.names = c(51L, 52L, 53L, 54L, 61L, 
    62L, 63L, 64L, 71L, 72L, 73L, 74L, 81L, 82L, 83L, 84L, 91L, 92L, 
    93L, 94L), class = "data.frame")
    

2 个答案:

答案 0 :(得分:14)

以下是两种可能的方法:

在示例1中,我使用ifelsescale_size_manual来控制是否在每个单元格中绘制一个点。

在示例2中,我创建了一个小的辅助data.frame并使用geom_rect绘制矩形而不是点。为方便起见,我将Var2转换为因子。在ggplot2中,沿离散/因子轴的每个步长都是1.0。这样可以轻松计算geom_rect的值。

# Using ggplot2 version 0.9.2.1
library(ggplot2)

# Test dataset from original post has been assigned to 'molten'.

molten$Var2 = factor(molten$Var2)

# Example 1.
p1 = ggplot(data=molten, aes(x=Var1, y=Var2, fill=value)) +
     geom_raster() +
     scale_fill_gradient2(low="blue", high="red", na.value="black", name="") +
     geom_point(aes(size=ifelse(na, "dot", "no_dot"))) +
     scale_size_manual(values=c(dot=6, no_dot=NA), guide="none") +
     labs(title="Example 1")

ggsave(plot=p1, filename="plot_1.png", height=3, width=3.5) 

enter image description here

# Example 2.
# Create auxiliary data.frame.
frames = molten[molten$na, c("Var1", "Var2")]
frames$Var1 = as.integer(frames$Var1)
frames$Var2 = as.integer(frames$Var2)

p2 = ggplot(data=molten) +
     geom_raster(aes(x=Var1, y=Var2, fill=value)) +
     scale_fill_gradient2(low="blue", high="red", na.value="black", name="") +
     geom_rect(data=frames, size=1, fill=NA, colour="black",
       aes(xmin=Var1 - 0.5, xmax=Var1 + 0.5, ymin=Var2 - 0.5, ymax=Var2 + 0.5)) +
     labs(title="Example 2")

ggsave(plot=p2, filename="plot_2.png", height=3, width=3.5) 

enter image description here

答案 1 :(得分:5)

正如@joran在评论中建议的那样,您可以将数据的子集传递给特定的图层。

使用您的示例数据

g <- ggplot( molten ) +
  geom_raster( aes( x = Var1, y = Var2, fill = value )  ) + 
  scale_fill_gradient2( low = "blue", high = "red", na.value="black", name = "" ) +
  geom_point(data = molten[molten$na,], aes( x = Var1, y = Var2, size= as.numeric(na) ) )


g

enter image description here

如果您希望图例说明点的含义

 g <- ggplot( molten ) +
  geom_raster( aes( x = Var1, y = Var2, fill = value )  ) + 
  scale_fill_gradient2( low = "blue", high = "red", na.value="black", name = "" ) +
  geom_point(data = molten[molten$na,], aes( x = Var1, y = Var2, colour = 'black' )) +
  scale_colour_manual(name = 'Ooh look', values = 'black', labels = 'Something cool')

enter image description here