我对ggplot2中的线条颜色有疑问。我需要绘制太阳辐射数据,但我只有6小时的数据,所以geom_line
不能给出“好”的输出。我试过geom_smooth
,结果接近我的需要。但我有一个新问题,是否可以根据y值改变线条颜色?
用于绘图的代码是
library(ggplot2)
library(lubridate)
# Lectura de datos
datos.uvi=read.csv("serie-temporal-1.dat",sep=",",header=T,na.strings="-99.9")
datos.uvi=within(datos.uvi, fecha <- ymd_h(datos.uvi$fecha.hora))
# geom_smooth
ggplot(data=datos.uvi, aes(x=fecha, y=Rad_Global_.mW.m2., colour="GLOBAL")) +
geom_smooth(se=FALSE, span=0.3)
在所需的输出中,对于250以下的辐射值,250-500区间内为绿色,对于高于500的值,蓝线应为红色。
是否可以使用geom_smooth
?我试图重用代码here,但找不到重点。
用于情节的数据:
dput(datos.uvi)
structure(list(fecha.hora = c(2016012706L, 2016012712L, 2016012718L,
2016012800L, 2016012806L, 2016012812L, 2016012818L, 2016012900L,
2016012906L, 2016012912L, 2016012908L, 2016013000L), latitud = c(37.75,
37.75, 37.75, 37.75, 37.75, 37.75, 37.75, 37.75, 37.75, 37.75,
37.75, 37.75), longitud = c(-1.25, -1.25, -1.25, -1.25, -1.25,
-1.25, -1.25, -1.25, -1.25, -1.25, -1.25, -1.25), altitud = c(300L,
300L, 300L, 300L, 300L, 300L, 300L, 300L, 300L, 300L, 300L, 300L
), cobertura_nubosa = c(0.91, 0.02, 0.62, 1, 0.53, 0.49, 0.01,
0, 0, 0.13, 0.62, 0.84), longitud_de_onda_inicial.nm. = c(284.55,
284.55, 284.55, 284.55, 284.55, 284.55, 284.55, 284.55, 284.55,
284.55, 284.55, 284.55), Rad_Global_.mW.m2. = c(5e-04, 259.2588,
5, 100.5, 1, 886.5742, 110, 40, 20, 331.3857, 0, 0), Rad_Directa_.mW.m2. = c(0,
16.58034, 0, 0, 0, 202.5683, 0, 0, 0, 89.81712, 0, 0), Rad_Difusa_.mW.m2. = c(0,
242.6785, 0, 0, 0, 684.0059, 0, 0, 0, 241.5686, 0, 0), Angulo_zenital_.º. = c(180,
56.681, 180, 180, 180, 56.431, 180, 180, 180, 56.176, 180, 180
), blank = c(NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA),
fecha = structure(c(1453874400, 1453896000, 1453917600, 1453939200,
1453960800, 1453982400, 1454004000, 1454025600, 1454047200,
1454068800, 1454054400, 1454112000), tzone = "UTC", class = c("POSIXct",
"POSIXt"))), row.names = c(NA, -12L), .Names = c("fecha.hora",
"latitud", "longitud", "altitud", "cobertura_nubosa", "longitud_de_onda_inicial.nm.",
"Rad_Global_.mW.m2.", "Rad_Directa_.mW.m2.", "Rad_Difusa_.mW.m2.",
"Angulo_zenital_.º.", "blank", "fecha"), class = "data.frame")
提前致谢。
答案 0 :(得分:7)
计算ggplot2外的平滑,然后使用geom_segment
:
fit <- loess(Rad_Global_.mW.m2. ~ as.numeric(fecha), data = datos.uvi, span = 0.3)
#note the warnings
new.x <- seq(from = min(datos.uvi$fecha),
to = max(datos.uvi$fecha),
by = "5 min")
new.y <- predict(fit, newdata = data.frame(fecha = as.numeric(new.x)))
DF <- data.frame(x1 = head(new.x, -1), x2 = tail(new.x, -1) ,
y1 = head(new.y, -1), y2 = tail(new.y, -1))
DF$col <- cut(DF$y1, c(-Inf, 250, 500, Inf))
ggplot(data=DF, aes(x=x1, y=y1, xend = x2, yend = y2, colour=col)) +
geom_segment(size = 2)
注意切割点会发生什么。如果可能更具视觉吸引力,可以使预测的x网格非常精细,然后使用geom_point
代替。但是,绘图将会很慢。
答案 1 :(得分:4)
这不是你要求的,但可能有同样的目的:不是给线条着色,而是为背景着色。首先,我们创建一个矩形/极限坐标的数据框。
rect_data <- data.frame(xmin=min(datos.uvi$fecha),
xmax=max(datos.uvi$fecha),
ymin=c(0,250,500),
ymax=c(250,500,max(datos.uvi$Rad_Global_.mW.m2.)),
col=c("red","green","blue"))
然后我们使用scale_fill_identity()
将它们添加到绘图中ggplot(data=datos.uvi) +
geom_smooth(aes(x=fecha, y=Rad_Global_.mW.m2.),colour="black",se=FALSE, span=0.3) +
geom_rect(data=rect_data, aes(xmin=xmin,xmax=xmax,ymin=ymin,ymax=ymax,fill=col),alpha=0.1)+
scale_fill_identity()