ggplot中自定义渐变颜色渐变的标签
我想绘制一些数据，在这里我使用一种自定义转换来分散色彩比例。 如此处所示，标签有时甚至根本没有。 我希望标签能够圆整，并显示颜色代表的价值而不是转型。
我已经能够成功地将其应用于非负面的规模，我相信它对trans_new的负数或inverse调用trans_new ，我从文档中不太明白：
以下是我探索的一些链接：
R：自定义ggplot2颜色转换给标签中的错误
GGplot自定义刻度转换与自定义刻度
https://github.com/tidyverse/ggplot2/issues/980看起来对我的头很有帮助
library(scales)
library(tidyverse)
log_both <- function(x){ifelse(x == 0, 0, log(abs(x)) * sign(x))}
log_both_trans <-
function(){
trans_new(name = 'log_both',
transform = log_both,
inverse = log_both) #not clear what `inverse` does
}
df <-
tibble(y = (-10:10),
x = (y^4)*sign(y))
ggplot(df) +
#no transformation
geom_point(aes(factor(x), y = 1, fill = x), shape = 21, size = 10) +
scale_fill_gradient2(low = "blue", mid = "white", high = "red") +
#transformed
geom_point(aes(factor(x), y = - 1, color = x), size = 10) +
scale_color_gradient2(low = "blue", mid = "white", high = "red", trans = "log_both") +
ylim(-2, 2) +
labs(colour = "transformed", fill = "default", x = "", y = "")
参数inverse取一个函数，它是原始变换的数学倒数。 如果你记录变换，则逆是幂。 计算与所选断点相对应的标签需要反算。 （您可以对数据进行日志转换以获取缩放数据，然后进行反转换以获取标签。另请参阅此SO帖子。）
library(scales)
library(tidyverse)
log_both <- function(x){ifelse(x == 0, 0, log(abs(x)) * sign(x))}
exp_both <- function(x){exp(abs(x)) * sign(x)} # this is the inverse of log_both
log_both_trans <-
function(){
trans_new(name = 'log_both',
transform = log_both,
inverse = exp_both)
}
df <-
tibble(y = (-10:10),
x = (y^4)*sign(y))
ggplot(df) +
#no transformation
geom_point(aes(factor(x), y = 1, fill = x), shape = 21, size = 10) +
scale_fill_gradient2(low = "blue", mid = "white", high = "red",
guide = guide_colorbar(order = 1)) +
#transformed
geom_point(aes(factor(x), y = - 1, color = x), size = 10) +
scale_color_gradient2(low = "blue", mid = "white", high = "red",
trans = "log_both",
breaks = c(-10000, -100, 0, 100, 10000), # desired breaks on transformed scale
guide = guide_colorbar(order = 2)) +
ylim(-2, 2) +
labs(colour = "transformed", fill = "default", x = "", y = "")
线条guide = guide_colorbar(order = 1)和guide = guide_colorbar(order = 2)仅用于确保图例以正确的顺序显示。 否则它们以随机顺序出现。