小值变量使用scale_colour_gradient2不可见 [英] Small value variation invisible using scale_colour_gradient2
问题描述
我想在这个图中做出小回报。最合适的函数似乎是 scale_colour_gradient2
,但这会清除小回报,这是最常发生的。使用 limits
帮助,但我不能解决如何设置oob(超出界限),所以它只是一个饱和值,而不是灰色。而且日志变换只是使小值出现。有人知道如何优雅地做这件事吗?
I'd like to make small returns in this plot more visible. The most appropriate function seems to be scale_colour_gradient2
, but this washes out the small returns, which happen most often. Using limits
helped but I couldn't work out how to set oob (out of bounds) so it would just have a "saturated" value rather than be grey. And the log transform just made small values stand out. Has someone else figured out how to do this elegantly?
library(zoo)
library(ggplot2)
library(tseries)
spx <- get.hist.quote(instrument="^gspc", start="2000-01-01",
end="2013-12-14", quote="AdjClose",
provider="yahoo", origin="1970-01-01",
compression="d", retclass="zoo")
spx.rtn <- diff(log(spx$AdjClose)) * 100
rtn.data <- data.frame(x=time(spx.rtn),yend=spx.rtn)
p <- ggplot(rtn.data) +
geom_segment(aes(x=x,xend=x,y=0,yend=yend,colour=yend)) +
xlab("") + ylab("S&P 500 Daily Return %") +
theme(legend.position="null",axis.title.x=element_blank())
# low returns invisible
p + scale_colour_gradient2(low="blue",high="red")
# extreme values are grey
p + scale_colour_gradient2(low="blue",high="red",limits=c(-3,3))
# log transform returns has opposite problem
max_val <- max(log(abs(spx.rtn)))
values <- seq(-max_val, max_val, length = 11)
library(RColorBrewer)
p + scale_colour_gradientn(colours = brewer_pal(type="div",pal="RdBu")(11),
values = values
, rescaler = function(x, ...) sign(x)*log(abs(x)), oob = identity)
推荐答案
这是另一种可能性,使用 scale_colour_gradientn
。使用 values = rescale(...)
设置颜色的映射
,以便接近零的分辨率更高。我在这里查看了一些颜色标度: http://colorbrewer2.org 。我选择了一个5级发散的配色方案,RdBu,从红色到蓝色通过近白色。可能还有其他尺度适合你的需要更好,这只是为了显示基本原则。
Here is another possibility, using scale_colour_gradientn
. Mapping of colours
is set using values = rescale(...)
so that resolution is higher for values close to zero. I had a look at some colour scales here: http://colorbrewer2.org. I chose a 5-class diverging colour scheme, RdBu, from red to blue via near-white. There might be other scales that suit your needs better, this is just to show the basic principles.
# check the colours
library(RColorBrewer)
# cols <- brewer_pal(pal = "RdBu")(5) # not valid in 1.1-2
cols <- brewer.pal(n = 5, name = "RdBu")
cols
# [1] "#CA0020" "#F4A582" "#F7F7F7" "#92C5DE" "#0571B0"
# show_col(cols) # not valid in 1.1-2
display.brewer.pal(n = 5, name = "RdBu")
使用 rescale
10对应于蓝色#0571B0; -1 =浅蓝色#92C5DE; 0 =浅灰色#F7F7F7; 1 =浅红色#F4A582; 10 =红#CA0020。在-1和1之间的值在浅蓝色和浅红色之间插值,等等。因此,映射不是线性的,对于小的值,分辨率较高。
Using rescale
, -10 corresponds to blue #0571B0; -1 = light blue #92C5DE; 0 = light grey #F7F7F7; 1 = light red #F4A582; 10 = red #CA0020. Values between -1 and 1 are interpolated between light blue and light red, et c. Thus, mapping is not linear and resolution is higher for small values.
library(ggplot2)
library(scales) # needed for rescale
ggplot(rtn.data) +
geom_segment(aes(x = x, xend = x, y = 0, yend = yend, colour = yend)) +
xlab("") + ylab("S&P 500 Daily Return %") +
scale_colour_gradientn(colours = cols,
values = rescale(c(-10, -1, 0, 1, 10)),
guide = "colorbar", limits=c(-10, 10)) +
theme(legend.position = "null", axis.title.x = element_blank())
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