阴影geom_line和x轴之间的区域 [英] Shading an area between geom_line and the x-axis
问题描述
我有两个图表显示供给和需求，还有一个图表是我从供给中减去需求以显示不对称结果。我想遮蔽x轴和不对称负面部分之间的区域，以显示赤字的程度。
我目前使用以下代码：
plot.asymmetry< ; - ggplot（data = df.overview.month，
aes（x = Date.Time，y = Asymmetry））+
geom_area（data = subset（df.overview.month，Asymmetry <0 ），
aes（x = Date.Time，y =不对称））
然而 - 正如可以预料的那样 - 这不会影响geom_line和x轴之间的区域，而只会影响非对称数据的负值，这是完全不同的情况，如结果图所示：
/编辑：一些示例数据：
time.initial< - as.POSIXct（2010-12-31 23:00:00，tz =GMT）
Date.Time< -vector（）
for（i in 1:24）{
Date.Time [i] < - time.initial + i * 3600
}
Demand< -vector（）
for（i in 0:23）{
Demand [i + 1] < - 155 + 20 * sin（（pi / 12）* i - （pi / 2））+ 10 * sin（（pi / 4380）* i +（pi / 2））
}
供应< -vector（）
for（i in 0:23）{
Supply [i + 1] <-165 + 5 * sin（（pi / 4380）* i-（pi / 2））+ rnorm（1，mean = 0，sd = 0.20 * data_frame（Date.Time，Demand，Supply，Asymmetry = Supply-Demand）
}
df.overview.month $ c>
解决方案这是怎么样的灵感。现在，只需要在非对称性等于零的情况下添加其他数据点（如@baptiste建议的那样）。当非对称性大于零时，我创建了一个新的列 NA ，这样就不会在那里绘制geom_ribbon。只是对数据进行子集化并不会导致所需的情节。
df.overview.month $ Assym_ribbon = ifelse（df.overview。月$不对称> 0，
NA，
df.overview.month $不对称）
ggplot（aes（x = Date.Time，y =不对称），
data = df.overview.month）+
geom_line（）+
geom_ribbon（aes（ymin = 0，ymax = Assym_ribbon），
data =，fill =red）
关于您构建示例的方式的一些附加说明。最重要的是R是矢量化的。例如：
set.seed（1）
供应< -vector（）
for（i在0:23）{
Supply [i + 1] < - 165 +
5 * sin（（pi / 4380）* i -
（pi / 2））+
rnorm（1，mean = 0，sd = 0.20 * 165）
}
相当于：
set.seed（1）
i = 0:23
Supply_vec < -
（n = 165 + 5 * sin（（pi / 4380）* i -
（pi / 2））+
rnorm（length（i），mean = 0，sd = 0.20 * 165）
> all.equal（Supply_vec，Supply）
[1] TRUE
在这种情况下，在代码中是适度的，但在其他（更现实的）设置使用向量化将节省你几十行代码。
I have two plots displaying supply and demand, and one plot in which I have subtracted the demand from the supply to show the resulting asymmetry. I would like to shade the area between the x-axis and the negative part of the asymmetry, to show the extent of the deficit.
I currently use the following code:
plot.asymmetry <- ggplot(data=df.overview.month,
aes(x=Date.Time, y=Asymmetry)) +
geom_area(data=subset(df.overview.month, Asymmetry < 0),
aes(x=Date.Time, y=Asymmetry))
However - as could be expected - this does not shade the area between geom_line and the x-axis, but only between negative values of the asymmetry data, which is something else entirely, as shown in the resulting graph:
Is there any way to overcome this problem?
/Edit: some example data:
time.initial <- as.POSIXct("2010-12-31 23:00:00", tz="GMT")
Date.Time<-vector()
for(i in 1:24) {
Date.Time[i] <- time.initial + i*3600
}
Demand<-vector()
for(i in 0:23) {
Demand[i+1] <- 155 + 20*sin((pi/12)*i - (pi/2)) + 10*sin((pi/4380)*i + (pi/2))
}
Supply<-vector()
for(i in 0:23) {
Supply[i+1] <- 165 + 5*sin((pi/4380)*i - (pi/2)) + rnorm(1, mean=0, sd=0.20*165)
}
df.overview.month <- data.frame(Date.Time, Demand, Supply, Asymmetry=Supply-Demand)
解决方案 What about this as inspiration. Now you only need to add additional data points where the asymmetry is equal to zero (like @baptiste suggested). I create a new column which is NA when the asymmetry is above zero, in this way no geom_ribbon will be drawn there. Just subsetting the data will not lead to the required plot.
df.overview.month$Assym_ribbon = ifelse(df.overview.month$Asymmetry > 0,
NA,
df.overview.month$Asymmetry)
ggplot(aes(x = Date.Time, y = Asymmetry),
data = df.overview.month) +
geom_line() +
geom_ribbon(aes(ymin = 0, ymax = Assym_ribbon),
data = , fill = "red")
Some additional notes about the way you constructed your example. The most important one is that R is vectorized. For example:
set.seed(1)
Supply<-vector()
for(i in 0:23) {
Supply[i+1] <- 165 +
5*sin((pi/4380)*i -
(pi/2)) +
rnorm(1, mean=0, sd=0.20*165)
}
is equivalent to:
set.seed(1)
i = 0:23
Supply_vec <- 165 + 5*sin((pi/4380)*i -
(pi/2)) +
rnorm(length(i), mean=0, sd=0.20*165)
> all.equal(Supply_vec, Supply)
[1] TRUE
In this case the reduction in code is modest, but in other (more realistic) settings using vectorization will save you dozens of lines of code.
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