如何在ggplot2中渐变填充注释形状答案

【问题标题】：How to gradient fill an annotation shape in ggplot2如何在ggplot2中渐变填充注释形状
【发布时间】：2019-09-26 18:05:29
【问题描述】：

我有一个极坐标图，可以绘制一年中每小时的数据。我已经设法放入四个注释矩形来表示季节。我希望这些矩形具有从清晰到当前颜色的渐变填充。这是我目前的图表：

我尝试专门为矩形添加渐变填充，但这与标记缩放填充渐变冲突。理想情况下，图表将如下所示：

到目前为止，这是我的代码：

#how to generate a dataset with hourly readings over a year and a half. 
library(lubridate)
NoOfHours <- as.numeric(ymd_hms("2019-6-1 00:00:00") - ymd_hms("2018-3-1 00:00:00"))*24 
data1 <- as.data.frame(ymd_hms("2018-3-01 8:00:00") + hours(0:NoOfHours))
colnames(data1) <- 'date' 
set.seed(10)
data1$level <- runif(nrow(data1), min = 0, max = 400)

library(readxl);library(lubridate); #loads the 'readxl' package.
#1.
Hours <- format(as.POSIXct(strptime(data1$date,"%Y-%m-%d %H:%M:%S",tz="")) ,format = "%H:%M:%S")
data1$hours <- Hours

Date <- format(as.POSIXct(strptime(data1$date,"%Y-%m-%d %H:%M:%S",tz="")) ,format = "%Y-%m-%d")
data1$date_date <- Date#output

month <- format(as.POSIXct(strptime(data1$date,"%Y-%m-%d %H:%M:%S",tz="")) ,format = "%m-%d")
data1$month<- month
#input the date here to select the start of the dataset, use the format: "yyyy-mm-dd". Then choose the end date by taking one full year of data. I.E. start = "2018-3-1", end = "2019-2-28"
start <- ceiling_date(ymd(data1$date_date[1]), "day", change_on_boundary = FALSE)
startdate <- as.Date(start) %m+% days(1)
enddate1 <- as.Date(startdate) %m+% years(1)
enddate<- as.Date(enddate1) %m-% days(1)

devicenumber <- "1"
Housename <- "level.tiff"
houseinfo <- c(devicenumber, Housename)

graphlimit <- 0 #need to define a limit for the graph
i<-200 #the initial lowest limit will always be 200
#this loop will now check for the highest levels of Radon and then graph a graphlimit that will encompass this maxima. This newly determined limit will allow different datasets to easily be automatically plotted with a range that is not too big or too small for the data.
if (max(data1$level) < (i+50)) {
  graphlimit <- i
} else {
while (max(data1$level)>(i+50)) {
  i<-i+200 }
  if(max(data1$level) < (i+50)) {graphlimit <- i
  }
}

library(openair)
yeardata <- selectByDate(data1, start = startdate, end = enddate, year = 2018:2019) #select for a defined set of years

library(ggplot2);library(extrafont)
graphlength <- graphlimit/(1350/1750)
innerlimit <- -(graphlength*(200/1750))
plotlimit <- graphlength+innerlimit #this sets the end limit of the outer plot ticks. This ratio was determined based on the largest dataset.

starttimedate <- ymd_hms(paste(startdate, "01:00:00"))
endtimedate <- ymd_hms(paste(enddate1, "01:00:00"))
#endtimedate2 <- ymd_hms(paste(floor_date(ymd(data1$date_date[1]), "year"), "01:00:00"))
NoOfhours <- as.numeric(ymd_hms(starttimedate) - ymd_hms("2018-01-01 00:00:00"))*24
NoOfHours <- (8760/12)*(month(startdate)-1)#as.numeric(ymd_hms(starttimedate) - ymd_hms(endtimedate2))*24  #need this to determine rotation. This will determine how many hours are between Jan 1-1 at 0:0:0 till the start of the dataset. 
NoOfHoursall <- as.numeric(ymd_hms(endtimedate) - ymd_hms(starttimedate))*24
date_vals <- seq(from = ceiling_date(ymd(startdate), "month", change_on_boundary = FALSE), length.out = 12, by = "months")
finalcell <- length(yeardata$date)

plot <- ggplot(yeardata, aes(x=date, y=level, color = level)) +
 annotate("rect", xmin =  ((yeardata$date[1])), xmax =  (yeardata$date[min(which(yeardata$date_date == ymd("2018-6-1")))]), ymin = graphlimit, ymax = Inf, fill = "springgreen4", alpha = 0.15)+
  annotate("rect", xmin =  (yeardata$date[min(which(yeardata$date_date == ymd("2018-6-1")))]), xmax =  (yeardata$date[min(which(yeardata$date_date == ymd("2018-9-1")))]), ymin = graphlimit, ymax = Inf, fill = "goldenrod2", alpha = 0.15)+
  annotate("rect", xmin =  (yeardata$date[min(which(yeardata$date_date == ymd("2018-9-1")))]), xmax =  (yeardata$date[min(which(yeardata$date_date == ymd("2018-12-1")))]), ymin = graphlimit, ymax = Inf, fill = "orangered3", alpha = 0.15)+
  annotate("rect", xmin =  (yeardata$date[min(which(yeardata$date_date == ymd("2018-12-1")))]), xmax =  (yeardata$date[min(which(yeardata$date_date == ymd("2019-3-1")))]), ymin = graphlimit, ymax = Inf, fill = "cornflowerblue", alpha = 0.15)+
  annotate("rect", xmin =  (yeardata$date[min(which(yeardata$date_date == ymd("2019-3-1")))]), xmax =  (yeardata$date[finalcell]), ymin = graphlimit, ymax = Inf, fill = "springgreen4", alpha = 0.15)+
  geom_hline(yintercept = seq(0, graphlimit, by = 200), colour = "black", size = 0.75, alpha = 0.3)+ 
  geom_hline(yintercept = seq(0, graphlimit, by = 50), colour = "black", size = 0.5, alpha = 0.1)+ 
  annotate("segment",x =  (yeardata$date[1]), xend =  (yeardata$date[1]), y = 0, yend = graphlimit, colour = "black", size = 1, alpha = 0.5) +
#annotate("text",x =  (max(yeardata$date)), y = innerlimit, colour = "black", size = 7, alpha = 1, label = devicenumber)+
  scale_colour_gradientn(limits = c(0,1000), colours = c("grey","yellow","orangered1","red","red4","black"), values = c(0,0.1,0.2,0.5,0.8,1), breaks = c(0, 100, 200, 500, 800, 1000), oob = scales::squish, name = expression(atop("",atop(textstyle("Level"^2*"")))))+ #need oob = scales::squish to get values over 200 to be red.
    geom_jitter(alpha = 0.2, size = 1) +
 theme(text = element_text(family="Calibri"),  axis.title=element_text(size=16,face="bold"), axis.text.x = element_blank(), axis.text.y = element_text(size = 12))+
   labs(x = NULL, y = bquote('Level'))+
  scale_y_continuous(breaks = seq(0, graphlimit, 200),
                     limits = c(innerlimit,plotlimit))+
 annotate("segment", x =  (yeardata$date[min(which(yeardata$date_date == ymd(date_vals[1])))]), xend =  (yeardata$date[min(which(yeardata$date_date == ymd(date_vals[1])))]), y = graphlimit, yend = plotlimit, colour = "black", size = 2)+
  annotate("segment", x =  (yeardata$date[min(which(yeardata$date_date == ymd(date_vals[2])))]), xend =  (yeardata$date[min(which(yeardata$date_date == ymd(date_vals[2])))]), y = graphlimit, yend = plotlimit, colour = "black", size = 2)+
  annotate("segment", x =  (yeardata$date[min(which(yeardata$date_date == ymd(date_vals[3])))]), xend =  (yeardata$date[min(which(yeardata$date_date == ymd(date_vals[3])))]), y = graphlimit, yend = plotlimit, colour = "black", size = 2)+
  annotate("segment", x =  (yeardata$date[min(which(yeardata$date_date == ymd(date_vals[4])))]), xend =  (yeardata$date[min(which(yeardata$date_date == ymd(date_vals[4])))]), y = graphlimit, yend = plotlimit, colour = "black", size = 2)+
  annotate("segment", x =  (yeardata$date[min(which(yeardata$date_date == ymd(date_vals[5])))]), xend =  (yeardata$date[min(which(yeardata$date_date == ymd(date_vals[5])))]), y = graphlimit, yend = plotlimit, colour = "black", size = 2)+
  annotate("segment", x =  (yeardata$date[min(which(yeardata$date_date == ymd(date_vals[6])))]), xend =  (yeardata$date[min(which(yeardata$date_date == ymd(date_vals[6])))]), y = graphlimit, yend = plotlimit, colour = "black", size = 2)+
  annotate("segment", x =  (yeardata$date[min(which(yeardata$date_date == ymd(date_vals[7])))]), xend =  (yeardata$date[min(which(yeardata$date_date == ymd(date_vals[7])))]), y = graphlimit, yend = plotlimit, colour = "black", size = 2)+
  annotate("segment", x =  (yeardata$date[min(which(yeardata$date_date == ymd(date_vals[8])))]), xend =  (yeardata$date[min(which(yeardata$date_date == ymd(date_vals[8])))]), y = graphlimit, yend = plotlimit, colour = "black", size = 2)+
  annotate("segment", x =  (yeardata$date[min(which(yeardata$date_date == ymd(date_vals[9])))]), xend =  (yeardata$date[min(which(yeardata$date_date == ymd(date_vals[9])))]), y = graphlimit, yend = plotlimit, colour = "black", size = 2)+
  annotate("segment", x =  (yeardata$date[min(which(yeardata$date_date == ymd(date_vals[10])))]), xend =  (yeardata$date[min(which(yeardata$date_date == ymd(date_vals[10])))]), y = graphlimit, yend = plotlimit, colour = "black", size = 2)+
  annotate("segment", x =  (yeardata$date[min(which(yeardata$date_date == ymd(date_vals[11])))]), xend =  (yeardata$date[min(which(yeardata$date_date == ymd(date_vals[11])))]), y = graphlimit, yend = plotlimit, colour = "black", size = 2)+
  annotate("segment", x =  (yeardata$date[min(which(yeardata$date_date == ymd(date_vals[12])))]), xend =  (yeardata$date[min(which(yeardata$date_date == ymd(date_vals[12])))]), y = graphlimit, yend = plotlimit, colour = "black", size = 2)+
                  annotate("text", x =  (yeardata$date[min(which(yeardata$month == "01-16"))]), y = ((graphlimit+plotlimit)/2), colour = "black", size = 9, family="Calibri", label = "JAN", angle = -15)+
  annotate("text", x =  (yeardata$date[min(which(yeardata$month == "02-16"))]), y = ((graphlimit+plotlimit)/2), colour = "black", size = 9, family="Calibri", label = "FEB", angle = -45)+
  annotate("text", x =  (yeardata$date[min(which(yeardata$month == "03-16"))]), y = ((graphlimit+plotlimit)/2), colour = "black", size = 9, family="Calibri", label = "MAR", angle = -74)+
  annotate("text", x =  (yeardata$date[min(which(yeardata$month == "04-16"))]), y = ((graphlimit+plotlimit)/2), colour = "black", size = 9, family="Calibri", label = "APR", angle = -104)+
  annotate("text", x =  (yeardata$date[min(which(yeardata$month == "05-16"))]), y = ((graphlimit+plotlimit)/2), colour = "black", size = 9, family="Calibri", label = "MAY", angle = -133)+
  annotate("text", x =  (yeardata$date[min(which(yeardata$month == "06-16"))]), y = ((graphlimit+plotlimit)/2), colour = "black", size = 9, family="Calibri", label = "JUN", angle = -163)+
  annotate("text", x =  (yeardata$date[min(which(yeardata$month == "07-16"))]), y = ((graphlimit+plotlimit)/2), colour = "black", size = 9, family="Calibri", label = "JUL", angle = 165)+
  annotate("text", x =  (yeardata$date[min(which(yeardata$month == "08-16"))]), y = ((graphlimit+plotlimit)/2), colour = "black", size = 9, family="Calibri", label = "AUG", angle = 135)+
  annotate("text", x =  (yeardata$date[min(which(yeardata$month == "09-16"))]), y = ((graphlimit+plotlimit)/2), colour = "black", size = 9, family="Calibri", label = "SEP", angle = 105)+
  annotate("text", x =  (yeardata$date[min(which(yeardata$month == "10-16"))]), y = ((graphlimit+plotlimit)/2), colour = "black", size = 9, family="Calibri", label = "OCT", angle = 75)+
  annotate("text", x =  (yeardata$date[min(which(yeardata$month == "11-16"))]), y = ((graphlimit+plotlimit)/2), colour = "black", size = 9, family="Calibri", label = "NOV", angle = 45)+
  annotate("text", x =  (yeardata$date[min(which(yeardata$month == "12-16"))]), y = ((graphlimit+plotlimit)/2), colour = "black", size = 9, family="Calibri", label = "DEC", angle = 15)
plot
plot <- plot + coord_polar(start = ((2*NoOfhours/NoOfHoursall)*pi))+ #scale_x_continuous(breaks = as.POSIXct.Date(ymd_hms(yeardata$date[min(which(yeardata$date_date == ymd(date_vals[2])))]), origin))+ #need to have the number of radians to get my start position. If march 1st is the start date, then 60 days have past since Jan 1.
  theme(legend.title = element_text(color = "black", size = 14, face = "bold"), panel.background = element_rect(fill = "white"), panel.grid  = element_blank())
plot

任何帮助将不胜感激。

谢谢

【问题讨论】：

标签： r ggplot2 gradient polar-coordinates annotate

【解决方案1】：

好吧，经过一番寻找，我已经找到了一个解决方案。我找到了这个帖子：How can I apply a gradient fill to a geom_rect object in ggplot2?

据此，我修改了给出的答案，以包括我在下面的代码中看到的内容。引用@baptiste 的一句话：“你有两个选择：i) 沿 y 离散矩形并将填充或 alpha 映射到该变量；ii) 后处理绘图，例如通过 gridSVG，它支持本机渐变填充。”

所以本质上，我创建了一个将透明度值映射到 n 个矩形的函数。为了让它与我想要的不同颜色一起工作，我必须为每个季节创建一个单独的数据框，然后在函数中将每个季节映射到它自己的一组具有特定颜色的离散矩形。这里是具体的dataframe和function code。

    spring <- data.frame(matrix(ncol = 0, nrow = 1))
      spring$seasonstartdate <- ymd_hms((yeardata$date[1]))
      spring$seasonenddates <- ymd_hms(yeardata$date[min(which(yeardata$date_date == ymd("2018-6-1")))])
      spring$colour <- "springgreen4"
       summer <- data.frame(matrix(ncol = 0, nrow = 1))
       summer$seasonstartdate <- ymd_hms(yeardata$date[min(which(yeardata$date_date == ymd("2018-6-1")))])
        summer$seasonenddates <- ymd_hms(yeardata$date[min(which(yeardata$date_date == ymd("2018-9-1")))])
        summer$colour <- "goldenrod2"
        fall <- data.frame(matrix(ncol = 0, nrow = 1))
       fall$seasonstartdate <- ymd_hms(yeardata$date[min(which(yeardata$date_date == ymd("2018-9-1")))])
        fall$seasonenddates <- ymd_hms(yeardata$date[min(which(yeardata$date_date == ymd("2018-12-1")))])
        fall$colour <- "orangered3"
         winter <- data.frame(matrix(ncol = 0, nrow = 1))
         winter$seasonstartdate <- ymd_hms(yeardata$date[min(which(yeardata$date_date == ymd("2018-12-1")))])
        winter$seasonenddates <- ymd_hms(yeardata$date[min(which(yeardata$date_date == ymd("2019-3-1")))])
        winter$colour <- "orangered3"
          spring1 <- data.frame(matrix(ncol = 0, nrow = 1))
      spring1$seasonstartdate <- ymd_hms(yeardata$date[min(which(yeardata$date_date == ymd("2019-3-1")))])
      spring1$seasonenddates <- ymd_hms(yeardata$date[finalcell])
      spring1$colour <- "springgreen4"

      ggplot_grad_rects <- function(n, ymin, ymax) {
      y_steps <- seq(from = ymin, to = ymax, length.out = n + 1)
      alpha_steps <- seq(from = 0, to = 0.2, length.out = n)
      rect_grad <- data.frame(ymin = y_steps[-(n + 1)], 
                              ymax = y_steps[-1], 
                              alpha = alpha_steps)
      rect_total <- merge(spring, rect_grad)
      rect_total2 <- merge(summer, rect_grad)
      rect_total3 <- merge(fall, rect_grad)
      rect_total4 <- merge(winter, rect_grad)
      rect_total5 <- merge(spring1, rect_grad)
        ggplot(yeardata)+
                 geom_rect(data=rect_total, 
                  aes(xmin=ymd_hms(seasonstartdate), xmax=ymd_hms(seasonenddates),
                      ymin=ymin, ymax=ymax, 
                      alpha=alpha), fill="springgreen4") +
                 geom_rect(data=rect_total2, 
                  aes(xmin=ymd_hms(seasonstartdate), xmax=ymd_hms(seasonenddates),
                      ymin=ymin, ymax=ymax, 
                      alpha=alpha), fill="goldenrod2") +
                 geom_rect(data=rect_total3, 
                  aes(xmin=ymd_hms(seasonstartdate), xmax=ymd_hms(seasonenddates),
                      ymin=ymin, ymax=ymax, 
                      alpha=alpha), fill="orangered3") +
                 geom_rect(data=rect_total4, 
                  aes(xmin=ymd_hms(seasonstartdate), xmax=ymd_hms(seasonenddates),
                      ymin=ymin, ymax=ymax, 
                      alpha=alpha), fill="cornflowerblue") +
                 geom_rect(data=rect_total5, 
                  aes(xmin=ymd_hms(seasonstartdate), xmax=ymd_hms(seasonenddates),
                      ymin=ymin, ymax=ymax, 
                      alpha=alpha), fill="springgreen4") +
        guides(alpha = FALSE)
    }

事实证明最终会。这是一个创建的情节。

现在这里是完整的代码，所以你们都可以看到这个过程。

library(lubridate)
NoOfHours <- as.numeric(ymd_hms("2019-6-1 00:00:00") - ymd_hms("2018-3-1 00:00:00"))*24 
data1 <- as.data.frame(ymd_hms("2018-3-01 8:00:00") + hours(0:NoOfHours))
colnames(data1) <- 'date' 
set.seed(10)
data1$level <- runif(nrow(data1), min = 0, max = 400)

library(readxl);library(lubridate); #loads the 'readxl' package.
#1.
Hours <- format(as.POSIXct(strptime(data1$date,"%Y-%m-%d %H:%M:%S",tz="")) ,format = "%H:%M:%S")
data1$hours <- Hours

Date <- format(as.POSIXct(strptime(data1$date,"%Y-%m-%d %H:%M:%S",tz="")) ,format = "%Y-%m-%d")
data1$date_date <- Date#output

month <- format(as.POSIXct(strptime(data1$date,"%Y-%m-%d %H:%M:%S",tz="")) ,format = "%m-%d")
data1$month<- month
#input the date here to select the start of the dataset, use the format: "yyyy-mm-dd". Then choose the end date by taking one full year of data. I.E. start = "2018-3-1", end = "2019-2-28"
start <- ceiling_date(ymd(data1$date_date[1]), "day", change_on_boundary = FALSE)
startdate <- as.Date(start) %m+% days(1)
enddate1 <- as.Date(startdate) %m+% years(1)
enddate<- as.Date(enddate1) %m-% days(1)

devicenumber <- "1"
Housename <- "level.tiff"
houseinfo <- c(devicenumber, Housename)

graphlimit <- 0 #need to define a limit for the graph
i<-200 #the initial lowest limit will always be 200
#this loop will now check for the highest levels of Radon and then graph a graphlimit that will encompass this maxima. This newly determined limit will allow different datasets to easily be automatically plotted with a range that is not too big or too small for the data.
if (max(data1$level) < (i+50)) {
  graphlimit <- i
} else {
while (max(data1$level)>(i+50)) {
  i<-i+200 }
  if(max(data1$level) < (i+50)) {graphlimit <- i
  }
}

library(openair)
yeardata <- selectByDate(data1, start = startdate, end = enddate, year = 2018:2019) #select for a defined set of years

library(ggplot2);library(extrafont)
graphlength <- graphlimit/(1350/1750)
innerlimit <- -(graphlength*(200/1750))
plotlimit <- graphlength+innerlimit #this sets the end limit of the outer plot ticks. This ratio was determined based on the largest dataset.

starttimedate <- ymd_hms(paste(startdate, "01:00:00"))
endtimedate <- ymd_hms(paste(enddate1, "01:00:00"))
#endtimedate2 <- ymd_hms(paste(floor_date(ymd(data1$date_date[1]), "year"), "01:00:00"))
NoOfhours <- as.numeric(ymd_hms(starttimedate) - ymd_hms("2018-01-01 00:00:00"))*24
NoOfHours <- (8760/12)*(month(startdate)-1)#as.numeric(ymd_hms(starttimedate) - ymd_hms(endtimedate2))*24  #need this to determine rotation. This will determine how many hours are between Jan 1-1 at 0:0:0 till the start of the dataset. 
NoOfHoursall <- as.numeric(ymd_hms(endtimedate) - ymd_hms(starttimedate))*24
date_vals <- seq(from = ceiling_date(ymd(startdate), "month", change_on_boundary = FALSE), length.out = 12, by = "months")
finalcell <- length(yeardata$date)
#HERE IS THE SOLUTION
#I created a few dataframes to represent the seasons with their start and end times. From there I modified a previous solution to create a gradient geom_rect function. 
spring <- data.frame(matrix(ncol = 0, nrow = 1))
  spring$seasonstartdate <- ymd_hms((yeardata$date[1]))
  spring$seasonenddates <- ymd_hms(yeardata$date[min(which(yeardata$date_date == ymd("2018-6-1")))])
  spring$colour <- "springgreen4"
   summer <- data.frame(matrix(ncol = 0, nrow = 1))
   summer$seasonstartdate <- ymd_hms(yeardata$date[min(which(yeardata$date_date == ymd("2018-6-1")))])
    summer$seasonenddates <- ymd_hms(yeardata$date[min(which(yeardata$date_date == ymd("2018-9-1")))])
    summer$colour <- "goldenrod2"
    fall <- data.frame(matrix(ncol = 0, nrow = 1))
   fall$seasonstartdate <- ymd_hms(yeardata$date[min(which(yeardata$date_date == ymd("2018-9-1")))])
    fall$seasonenddates <- ymd_hms(yeardata$date[min(which(yeardata$date_date == ymd("2018-12-1")))])
    fall$colour <- "orangered3"
     winter <- data.frame(matrix(ncol = 0, nrow = 1))
     winter$seasonstartdate <- ymd_hms(yeardata$date[min(which(yeardata$date_date == ymd("2018-12-1")))])
    winter$seasonenddates <- ymd_hms(yeardata$date[min(which(yeardata$date_date == ymd("2019-3-1")))])
    winter$colour <- "orangered3"
      spring1 <- data.frame(matrix(ncol = 0, nrow = 1))
  spring1$seasonstartdate <- ymd_hms(yeardata$date[min(which(yeardata$date_date == ymd("2019-3-1")))])
  spring1$seasonenddates <- ymd_hms(yeardata$date[finalcell])
  spring1$colour <- "springgreen4"

  ggplot_grad_rects <- function(n, ymin, ymax) {
  y_steps <- seq(from = ymin, to = ymax, length.out = n + 1)
  alpha_steps <- seq(from = 0, to = 0.2, length.out = n)
  rect_grad <- data.frame(ymin = y_steps[-(n + 1)], 
                          ymax = y_steps[-1], 
                          alpha = alpha_steps)
  rect_total <- merge(spring, rect_grad)
  rect_total2 <- merge(summer, rect_grad)
  rect_total3 <- merge(fall, rect_grad)
  rect_total4 <- merge(winter, rect_grad)
  rect_total5 <- merge(spring1, rect_grad)
    ggplot(yeardata)+
             geom_rect(data=rect_total, 
              aes(xmin=ymd_hms(seasonstartdate), xmax=ymd_hms(seasonenddates),
                  ymin=ymin, ymax=ymax, 
                  alpha=alpha), fill="springgreen4") +
             geom_rect(data=rect_total2, 
              aes(xmin=ymd_hms(seasonstartdate), xmax=ymd_hms(seasonenddates),
                  ymin=ymin, ymax=ymax, 
                  alpha=alpha), fill="goldenrod2") +
             geom_rect(data=rect_total3, 
              aes(xmin=ymd_hms(seasonstartdate), xmax=ymd_hms(seasonenddates),
                  ymin=ymin, ymax=ymax, 
                  alpha=alpha), fill="orangered3") +
             geom_rect(data=rect_total4, 
              aes(xmin=ymd_hms(seasonstartdate), xmax=ymd_hms(seasonenddates),
                  ymin=ymin, ymax=ymax, 
                  alpha=alpha), fill="cornflowerblue") +
             geom_rect(data=rect_total5, 
              aes(xmin=ymd_hms(seasonstartdate), xmax=ymd_hms(seasonenddates),
                  ymin=ymin, ymax=ymax, 
                  alpha=alpha), fill="springgreen4") +
    guides(alpha = FALSE)
}



plot <- ggplot_grad_rects(100, graphlimit, graphlength) +
 annotate("rect", xmin =  ((yeardata$date[1])), xmax =  (yeardata$date[min(which(yeardata$date_date == ymd("2018-6-1")))]), ymin = graphlimit, ymax = Inf, fill = "springgreen4", alpha = 0.15)+
  annotate("rect", xmin =  (yeardata$date[min(which(yeardata$date_date == ymd("2018-6-1")))]), xmax =  (yeardata$date[min(which(yeardata$date_date == ymd("2018-9-1")))]), ymin = graphlimit, ymax = Inf, fill = "goldenrod2", alpha = 0.15)+
  annotate("rect", xmin =  (yeardata$date[min(which(yeardata$date_date == ymd("2018-9-1")))]), xmax =  (yeardata$date[min(which(yeardata$date_date == ymd("2018-12-1")))]), ymin = graphlimit, ymax = Inf, fill = "orangered3", alpha = 0.15)+
  annotate("rect", xmin =  (yeardata$date[min(which(yeardata$date_date == ymd("2018-12-1")))]), xmax =  (yeardata$date[min(which(yeardata$date_date == ymd("2019-3-1")))]), ymin = graphlimit, ymax = Inf, fill = "cornflowerblue", alpha = 0.15)+
  annotate("rect", xmin =  (yeardata$date[min(which(yeardata$date_date == ymd("2019-3-1")))]), xmax =  (yeardata$date[finalcell]), ymin = graphlimit, ymax = Inf, fill = "springgreen4", alpha = 0.15)+
  geom_hline(yintercept = seq(0, graphlimit, by = 200), colour = "black", size = 0.75, alpha = 0.3)+ 
  geom_hline(yintercept = seq(0, graphlimit, by = 50), colour = "black", size = 0.5, alpha = 0.1)+ 
  annotate("segment",x =  (yeardata$date[1]), xend =  (yeardata$date[1]), y = 0, yend = graphlimit, colour = "black", size = 1, alpha = 0.5) +
#annotate("text",x =  (max(yeardata$date)), y = innerlimit, colour = "black", size = 7, alpha = 1, label = devicenumber)+
  scale_colour_gradientn(limits = c(0,1000), colours = c("grey","yellow","orangered1","red","red4","black"), values = c(0,0.1,0.2,0.5,0.8,1), breaks = c(0, 100, 200, 500, 800, 1000), oob = scales::squish, name = expression(atop("",atop(textstyle("Level"^2*"")))))+ #need oob = scales::squish to get values over 200 to be red.
    geom_jitter(alpha = 0.2, size = 1) +
 theme(text = element_text(family="Calibri"),  axis.title=element_text(size=16,face="bold"), axis.text.x = element_blank(), axis.text.y = element_text(size = 12))+
   labs(x = NULL, y = bquote('Level'))+
  scale_y_continuous(breaks = seq(0, graphlimit, 200),
                     limits = c(innerlimit,plotlimit))+
 annotate("segment", x =  (yeardata$date[min(which(yeardata$date_date == ymd(date_vals[1])))]), xend =  (yeardata$date[min(which(yeardata$date_date == ymd(date_vals[1])))]), y = graphlimit, yend = plotlimit, colour = "black", size = 2)+
  annotate("segment", x =  (yeardata$date[min(which(yeardata$date_date == ymd(date_vals[2])))]), xend =  (yeardata$date[min(which(yeardata$date_date == ymd(date_vals[2])))]), y = graphlimit, yend = plotlimit, colour = "black", size = 2)+
  annotate("segment", x =  (yeardata$date[min(which(yeardata$date_date == ymd(date_vals[3])))]), xend =  (yeardata$date[min(which(yeardata$date_date == ymd(date_vals[3])))]), y = graphlimit, yend = plotlimit, colour = "black", size = 2)+
  annotate("segment", x =  (yeardata$date[min(which(yeardata$date_date == ymd(date_vals[4])))]), xend =  (yeardata$date[min(which(yeardata$date_date == ymd(date_vals[4])))]), y = graphlimit, yend = plotlimit, colour = "black", size = 2)+
  annotate("segment", x =  (yeardata$date[min(which(yeardata$date_date == ymd(date_vals[5])))]), xend =  (yeardata$date[min(which(yeardata$date_date == ymd(date_vals[5])))]), y = graphlimit, yend = plotlimit, colour = "black", size = 2)+
  annotate("segment", x =  (yeardata$date[min(which(yeardata$date_date == ymd(date_vals[6])))]), xend =  (yeardata$date[min(which(yeardata$date_date == ymd(date_vals[6])))]), y = graphlimit, yend = plotlimit, colour = "black", size = 2)+
  annotate("segment", x =  (yeardata$date[min(which(yeardata$date_date == ymd(date_vals[7])))]), xend =  (yeardata$date[min(which(yeardata$date_date == ymd(date_vals[7])))]), y = graphlimit, yend = plotlimit, colour = "black", size = 2)+
  annotate("segment", x =  (yeardata$date[min(which(yeardata$date_date == ymd(date_vals[8])))]), xend =  (yeardata$date[min(which(yeardata$date_date == ymd(date_vals[8])))]), y = graphlimit, yend = plotlimit, colour = "black", size = 2)+
  annotate("segment", x =  (yeardata$date[min(which(yeardata$date_date == ymd(date_vals[9])))]), xend =  (yeardata$date[min(which(yeardata$date_date == ymd(date_vals[9])))]), y = graphlimit, yend = plotlimit, colour = "black", size = 2)+
  annotate("segment", x =  (yeardata$date[min(which(yeardata$date_date == ymd(date_vals[10])))]), xend =  (yeardata$date[min(which(yeardata$date_date == ymd(date_vals[10])))]), y = graphlimit, yend = plotlimit, colour = "black", size = 2)+
  annotate("segment", x =  (yeardata$date[min(which(yeardata$date_date == ymd(date_vals[11])))]), xend =  (yeardata$date[min(which(yeardata$date_date == ymd(date_vals[11])))]), y = graphlimit, yend = plotlimit, colour = "black", size = 2)+
  annotate("segment", x =  (yeardata$date[min(which(yeardata$date_date == ymd(date_vals[12])))]), xend =  (yeardata$date[min(which(yeardata$date_date == ymd(date_vals[12])))]), y = graphlimit, yend = plotlimit, colour = "black", size = 2)+
                  annotate("text", x =  (yeardata$date[min(which(yeardata$month == "01-16"))]), y = ((graphlimit+plotlimit)/2), colour = "black", size = 9, family="Calibri", label = "JAN", angle = -15)+
  annotate("text", x =  (yeardata$date[min(which(yeardata$month == "02-16"))]), y = ((graphlimit+plotlimit)/2), colour = "black", size = 9, family="Calibri", label = "FEB", angle = -45)+
  annotate("text", x =  (yeardata$date[min(which(yeardata$month == "03-16"))]), y = ((graphlimit+plotlimit)/2), colour = "black", size = 9, family="Calibri", label = "MAR", angle = -74)+
  annotate("text", x =  (yeardata$date[min(which(yeardata$month == "04-16"))]), y = ((graphlimit+plotlimit)/2), colour = "black", size = 9, family="Calibri", label = "APR", angle = -104)+
  annotate("text", x =  (yeardata$date[min(which(yeardata$month == "05-16"))]), y = ((graphlimit+plotlimit)/2), colour = "black", size = 9, family="Calibri", label = "MAY", angle = -133)+
  annotate("text", x =  (yeardata$date[min(which(yeardata$month == "06-16"))]), y = ((graphlimit+plotlimit)/2), colour = "black", size = 9, family="Calibri", label = "JUN", angle = -163)+
  annotate("text", x =  (yeardata$date[min(which(yeardata$month == "07-16"))]), y = ((graphlimit+plotlimit)/2), colour = "black", size = 9, family="Calibri", label = "JUL", angle = 165)+
  annotate("text", x =  (yeardata$date[min(which(yeardata$month == "08-16"))]), y = ((graphlimit+plotlimit)/2), colour = "black", size = 9, family="Calibri", label = "AUG", angle = 135)+
  annotate("text", x =  (yeardata$date[min(which(yeardata$month == "09-16"))]), y = ((graphlimit+plotlimit)/2), colour = "black", size = 9, family="Calibri", label = "SEP", angle = 105)+
  annotate("text", x =  (yeardata$date[min(which(yeardata$month == "10-16"))]), y = ((graphlimit+plotlimit)/2), colour = "black", size = 9, family="Calibri", label = "OCT", angle = 75)+
  annotate("text", x =  (yeardata$date[min(which(yeardata$month == "11-16"))]), y = ((graphlimit+plotlimit)/2), colour = "black", size = 9, family="Calibri", label = "NOV", angle = 45)+
  annotate("text", x =  (yeardata$date[min(which(yeardata$month == "12-16"))]), y = ((graphlimit+plotlimit)/2), colour = "black", size = 9, family="Calibri", label = "DEC", angle = 15)
plot
plot <- plot + coord_polar(start = ((2*NoOfhours/NoOfHoursall)*pi))+ #scale_x_continuous(breaks = as.POSIXct.Date(ymd_hms(yeardata$date[min(which(yeardata$date_date == ymd(date_vals[2])))]), origin))+ 
  theme(legend.title = element_text(color = "black", size = 14, face = "bold"), panel.background = element_rect(fill = "white"), panel.grid  = element_blank())
plot

感谢并享受

【讨论】：