为什么我的 geom_lines 无法分成正确的颜色？
Why do my geom_lines fail to break into the correct colours?
我 运行 遇到了一个关于 geom_line() 函数使用的小问题。
我的数据由训练有素的观察者对某些行为进行的逐帧手动视频评估组成，这导致每个观察者有数千个数据点。这基本上是一个向量，由每个观察者的 0 和 1 组成，其中 1 代表想要的行为，0 代表不需要的行为。
四处游玩，我想到了以下几点：
# a dataset from a manual videoanalysis with frame by frame behaviour assessment in binary. 0 = no, 1 = yes.
data1<-read.csv("ObserversBehaviour.csv", ",", header=T)
# my solution of giving each observer his own line, without having to transform the entire set
Obsy0 <- rep(0,4528)
Obsy1 <- rep(1,4528)
Obsy2 <- rep(2,4528)
Obsy3 <- rep(3,4528)
Obsy4 <- rep(4,4528)
Obsy5 <- rep(5,4528)
Obsy6 <- rep(6,4528)
Obsy7 <- rep(7,4528)
Obsy8 <- rep(8,4528)
Obsy9 <- rep(9,4528)
Obsy10 <- rep(10,4528)
ObsData <- data.frame(data1,Obsy0,Obsy1,Obsy2,Obsy3,Obsy4,Obsy5,Obsy6,Obsy7,Obsy8,Obsy9,Obsy10)
#vector giving each observer a number
Obsall <- c(0:10)
#The list of individual frames of video M01 (4528 in total)
Framerange <- ObsData[["Frames.M01"]]
ylabels <- c("Observer0","Observer1","Observer2","Observer3","Observer4","Observer5","Observer6","Observer7","Observer8","Observer9","Observer10")
#Ob<n>value is the 1 or 0 assessment
#had to use as.factor() because for some reason my 0s and 1s are seen as continuous
GraphObserve <-ggplot(ObsData,ylim=range(Obsall),xlim=max(Framerange),aes(x=Framerange))
geom_point(aes(x=Frames.M01, y = Obsy0, colour = as.factor(Ob0value), size=as.factor(Ob0value)), shape=15) +
geom_point(aes(x=Frames.M01, y = Obsy1, colour = as.factor(Ob1value), size=as.factor(Ob1value)), shape=15) +
geom_point(aes(x=Frames.M01, y = Obsy2, colour = as.factor(Ob2value), size=as.factor(Ob2value)), shape=15) +
geom_point(aes(x=Frames.M01, y = Obsy3, colour = as.factor(Ob3value), size=as.factor(Ob3value)), shape=15) +
geom_point(aes(x=Frames.M01, y = Obsy4, colour = as.factor(Ob4freeze.0.no.1.yes), size=as.factor(Ob4freeze.0.no.1.yes)), shape=15) +
geom_point(aes(x=Frames.M01, y = Obsy5, colour = as.factor(Ob5value), size=as.factor(Ob5value)), shape=15) +
geom_point(aes(x=Frames.M01, y = Obsy6, colour = as.factor(Ob6value), size=as.factor(Ob6value)), shape=15) +
geom_point(aes(x=Frames.M01, y = Obsy7, colour = as.factor(Ob7value), size=as.factor(Ob7value)), shape=15) +
geom_point(aes(x=Frames.M01, y = Obsy8, colour = as.factor(Ob8value), size=as.factor(Ob8value)), shape=15) +
geom_point(aes(x=Frames.M01, y = Obsy9, colour = as.factor(Ob9value), size=as.factor(Ob9value)), shape=15) +
geom_point(aes(x=Frames.M01, y = Obsy10, colour = as.factor(Ob10value), size=as.factor(Ob10value)), shape=15) +
scale_colour_manual(breaks = c(0, 1),
labels = c("No","Yes"),
values = c("green4","red"),
name="Assessment")+
#needed to let the wanted behaviour stand out, so I changed pointsize
scale_size_manual(breaks = c(0, 1), values=c(1,2), guide="none")+
scale_y_discrete(limit=Obsall, labels=ylabels, expand=c(0,0))+
scale_x_continuous(expand=c(0,0),breaks = round(seq(min(0), max(Framerange), by = 200),5000))+
expand_limits(y=c(1,-.5))
update_labels(GraphObserve,list(x="Frames (M01)",y ="Observers"))
这使我得到了一个公平的图表，其中包含每个数据点的漂亮彩色点，但由于这些点重叠并且仍然很小，所以这不是我要走的路。我没有使用 geom_point()，而是使用了 geom_line()。该图确实代表了我想要的每个颜色中断。
所以接下来我将每个 geom_point() 行更改为 geom_line()，同时保持其余部分不变。 （scale_size_manual() 变得相当多余）
geom_line(aes(x=Framerange, y=Obsy0, colour=as.factor(Ob0value)),size=14) +
geom_line(aes(x=Framerange, y=Obsy1, colour=as.factor(Ob1value)),size=14) +
geom_line(aes(x=Framerange, y=Obsy2, colour=as.factor(Ob2value)),size=14) +
geom_line(aes(x=Framerange, y=Obsy3, colour=as.factor(Ob3value)),size=14) +
geom_line(aes(x=Framerange, y=Obsy4, colour=as.factor(Ob4value)),size=14) +
geom_line(aes(x=Framerange, y=Obsy5, colour=as.factor(Ob5value)),size=14) +
geom_line(aes(x=Framerange, y=Obsy6, colour=as.factor(Ob6value)),size=14) +
geom_line(aes(x=Framerange, y=Obsy7, colour=as.factor(Ob7value)),size=14) +
geom_line(aes(x=Framerange, y=Obsy8, colour=as.factor(Ob8value)),size=14) +
geom_line(aes(x=Framerange, y=Obsy9, colour=as.factor(Ob9value)),size=14) +
geom_line(aes(x=Framerange, y=Obsy10, colour=as.factor(Ob10value)),size=14) +
我以为这会很好，但事实并非如此。
不是为文件中的每个 0 和 1 切换颜色，而是在数据集中出现的第一个和最后一个 1 处切换颜色。
上述脚本的图形：http://imgur.com/2baseCa,bJa2Ab7#0
我似乎无法在我的代码中找到错误，我似乎也无法在网上找到解决方案。这里有没有人可以帮我解决这个问题？
更新
为了更清楚地了解概览，我在它们下方放置了指向我以前的脚本生成的图表的链接。
在建议将我的数据置于 "long" 格式之后，我使用了以下脚本：
data1<-read.csv("ObserversBehaviour.csv", ",", header=T)
Frames<-data1[["Frames.M01"]]
Obs<-paste0("Observer",0:10)
Obsy <- sort(rep(0:10,4528),decreasing=F)
Obsvalue <- stack(data1[,c(Obs)])
ObsData2 <- expand.grid(Frames=data1[["Frames.M01"]],Obs=paste0("Observer",0:10))
ObsData2$Observer = Obsy
ObsData2$Assessment = Obsvalue$values
ggplot(ObsData2, aes(Frames, Observer, colour=Assessment)) +
geom_line(show_guide=T) +
scale_y_discrete(limit=0:10, labels=Obs, expand=c(0,0))+
scale_x_continuous(expand=c(0,0),breaks = round(seq(min(0), max(Frames), by = 200),5000))+
expand_limits(y=c(1,.5)) +
#The manual colorcoding actually failed, since it keeps returning this error "Continuous value supplied to discrete scale".
scale_color_manual(breaks = c(0,1),
labels = c("No","Yes"),
values = c("green4","red"),
name="Assessment")
虽然颜色现在实际上根据行为评估值发生了变化，但出现了新问题。
Observer5-10的值全部替换为Observer10的值
通过更改几个参数，我发现通过更改行大小，值恢复正常。但是，Observer10 的值完全消失了。
新脚本的图表：
http://imgur.com/AiKeXLc,kPgIKKZ#1（第二张图是第一张图）
结合这些问题和我无法手动更改颜色的事实（即使我尝试在我的值上使用 as.factor() 和 as.discrete()）我不知道我现在可以尝试什么。
作为 R 的初学者，我可能在这里遗漏了一些明显的东西。
更新
dput(head(ObsData2))
的输出
## structure(list(Frames = 1:6, Obs = structure(c(1L, 1L, 1L, 1L, 1L, 1L), .Label = c("Observer0", "Observer1", "Observer2", "Observer3",
## "Observer4", "Observer5", "Observer6", "Observer7", "Observer8",
## "Observer9", "Observer10"), class = "factor"), Observer = c(0L,
## 0L, 0L, 0L, 0L, 0L), Assessment = c(0L, 0L, 0L, 0L, 0L, 0L)), .Names = c("Frames",
## "Obs", "Observer", "Assessment"), out.attrs = structure(list(
## dim = structure(c(4528, 11), .Names = c("Frames", "Obs")),
## dimnames = structure(list(Frames = c("Frames= 1", "Frames= 2",
## "Frames= 3", "Frames= 4", "Frames= 5", "Frames= 6",
## "Frames= 7", "Frames= 8", "Frames= 9", "Frames= 10",
## "Frames= 11", "Frames= 12", "Frames= 13", "Frames= 14",
## "Frames= 15", "Frames= 16", "Frames= 17", "Frames= 18",
## "Frames= 19", "Frames= 20", "Frames= 21", "Frames= 22",
## "Frames= 23", "Frames= 24", "Frames= 25", "Frames= 26",
## "Frames= 27", "Frames= 28", "Frames= 29", "Frames= 30",
## "Frames= 31", "Frames= 32", "Frames= 33", "Frames= 34",
## "Frames= 35", "Frames= 36", "Frames= 37", "Frames= 38",
## "Frames= 39", "Frames= 40", "Frames= 41", "Frames= 42",
## "Frames= 43", "Frames= 44", "Frames= 45", "Frames= 46",
## "Frames= 47", "Frames= 48", "Frames= 49", "Frames= 50",
## "Frames= 51", "Frames= 52", "Frames= 53", "Frames= 54",
## "Frames= 55", "Frames= 56", "Frames= 57", "Frames= 58",
## "Frames= 59", "Frames= 60", "Frames= 61", "Frames= 62",
## "Frames= 63", "Frames= 64", "Frames= 65", "Frames= 66",
## "Frames= 67", "Frames= 68", "Frames= 69", "Frames= 70",
## "Frames= 71", "Frames= 72", "Frames= 73", "Frames= 74",
# Long patch of "Frames= <75-4502>" omitted due to space saving
## "Frames=4503", "Frames=4504", "Frames=4505", "Frames=4506",
## "Frames=4507", "Frames=4508", "Frames=4509", "Frames=4510",
## "Frames=4511", "Frames=4512", "Frames=4513", "Frames=4514",
## "Frames=4515", "Frames=4516", "Frames=4517", "Frames=4518",
## "Frames=4519", "Frames=4520", "Frames=4521", "Frames=4522",
## "Frames=4523", "Frames=4524", "Frames=4525", "Frames=4526",
## "Frames=4527", "Frames=4528"), Obs = c("Obs=Observer0", "Obs=Observer1",
## "Obs=Observer2", "Obs=Observer3", "Obs=Observer4", "Obs=Observer5",
## "Obs=Observer6", "Obs=Observer7", "Obs=Observer8", "Obs=Observer9",
## "Obs=Observer10")), .Names = c("Frames", "Obs"))), .Names = c("dim",
## "dimnames")), row.names = c(NA, 6L), class = "data.frame")
如果您将数据设为 "long" 格式，这会容易得多。这是一个假数据的例子：
## Create fake data in long format
ObsData = expand.grid(Frames=1:4258, Obs=paste0("Observer",0:10))
# Add y values
set.seed(10)
ObsData$y = cumsum(rnorm(4258*11))
在长格式数据框中，所有观察者都 "stacked" 到一个具有 11 个类别的单一因子变量 (Obs) - 每个观察者一个。现在您可以将其用作 ggplot.
中颜色美学的分组变量
## Plot with a different color for each observer
ggplot(ObsData, aes(Frames, y, colour=Obs)) +
geom_line()
这是图表使用默认颜色时的样子，但您可以通过将 scale_colour_manual() 添加到绘图并设置您喜欢的任何颜色来更改它。
问题规避
在我同事的帮助下，使用 geom_tile() 而不是 geom_line()，图表现在完全符合我的要求。
require("ggplot2")
data1<-read.csv("ObserversBehaviour.csv", ",", header=T)
Frames<-data1[["Frames.M01"]]
Obs.lab<-paste0("Observer",0:10)
Obsy <- sort(rep(1:11,4528),decreasing=F)
Obsvalue <- stack(data1[,c(Obs.lab)])
ObsData2 <- expand.grid(Frames=data1[["Frames.M01"]],Obs.lab=paste0("Observer",0:10))
ObsData2$Observer = Obsy
ObsData2$Assessment = Obsvalue$values
GraphObserve <- ggplot(ObsData2, aes(Frames, Observer, height=.9)) +
geom_tile(aes(fill = factor(Assessment)))+
scale_fill_manual(values=c("0"="green4", "1"="red"), labels= c("No", "Yes"))+
scale_y_discrete(expand=c(0,0), limit=1:11, labels=Obs.lab)+
scale_x_continuous(expand=c(0,0), breaks = round(seq(min(0), max(Frames), by = 200),5000))
update_labels(GraphObserve,list(x="Frames (M01)",y ="Observers"))
颜色中断恰好出现在他们需要的地方，没有重叠，所有观察者都列在图中。
虽然这并没有真正解决我之前脚本中出现的问题，但它确实提供了更好的结果。
最终图表：
http://i.imgur.com/pW8Qh0I.png
谢谢 eipi10，告诉我如何压缩我的脚本。
我 运行 遇到了一个关于 geom_line() 函数使用的小问题。
我的数据由训练有素的观察者对某些行为进行的逐帧手动视频评估组成，这导致每个观察者有数千个数据点。这基本上是一个向量，由每个观察者的 0 和 1 组成，其中 1 代表想要的行为，0 代表不需要的行为。
四处游玩，我想到了以下几点：
# a dataset from a manual videoanalysis with frame by frame behaviour assessment in binary. 0 = no, 1 = yes.
data1<-read.csv("ObserversBehaviour.csv", ",", header=T)
# my solution of giving each observer his own line, without having to transform the entire set
Obsy0 <- rep(0,4528)
Obsy1 <- rep(1,4528)
Obsy2 <- rep(2,4528)
Obsy3 <- rep(3,4528)
Obsy4 <- rep(4,4528)
Obsy5 <- rep(5,4528)
Obsy6 <- rep(6,4528)
Obsy7 <- rep(7,4528)
Obsy8 <- rep(8,4528)
Obsy9 <- rep(9,4528)
Obsy10 <- rep(10,4528)
ObsData <- data.frame(data1,Obsy0,Obsy1,Obsy2,Obsy3,Obsy4,Obsy5,Obsy6,Obsy7,Obsy8,Obsy9,Obsy10)
#vector giving each observer a number
Obsall <- c(0:10)
#The list of individual frames of video M01 (4528 in total)
Framerange <- ObsData[["Frames.M01"]]
ylabels <- c("Observer0","Observer1","Observer2","Observer3","Observer4","Observer5","Observer6","Observer7","Observer8","Observer9","Observer10")
#Ob<n>value is the 1 or 0 assessment
#had to use as.factor() because for some reason my 0s and 1s are seen as continuous
GraphObserve <-ggplot(ObsData,ylim=range(Obsall),xlim=max(Framerange),aes(x=Framerange))
geom_point(aes(x=Frames.M01, y = Obsy0, colour = as.factor(Ob0value), size=as.factor(Ob0value)), shape=15) +
geom_point(aes(x=Frames.M01, y = Obsy1, colour = as.factor(Ob1value), size=as.factor(Ob1value)), shape=15) +
geom_point(aes(x=Frames.M01, y = Obsy2, colour = as.factor(Ob2value), size=as.factor(Ob2value)), shape=15) +
geom_point(aes(x=Frames.M01, y = Obsy3, colour = as.factor(Ob3value), size=as.factor(Ob3value)), shape=15) +
geom_point(aes(x=Frames.M01, y = Obsy4, colour = as.factor(Ob4freeze.0.no.1.yes), size=as.factor(Ob4freeze.0.no.1.yes)), shape=15) +
geom_point(aes(x=Frames.M01, y = Obsy5, colour = as.factor(Ob5value), size=as.factor(Ob5value)), shape=15) +
geom_point(aes(x=Frames.M01, y = Obsy6, colour = as.factor(Ob6value), size=as.factor(Ob6value)), shape=15) +
geom_point(aes(x=Frames.M01, y = Obsy7, colour = as.factor(Ob7value), size=as.factor(Ob7value)), shape=15) +
geom_point(aes(x=Frames.M01, y = Obsy8, colour = as.factor(Ob8value), size=as.factor(Ob8value)), shape=15) +
geom_point(aes(x=Frames.M01, y = Obsy9, colour = as.factor(Ob9value), size=as.factor(Ob9value)), shape=15) +
geom_point(aes(x=Frames.M01, y = Obsy10, colour = as.factor(Ob10value), size=as.factor(Ob10value)), shape=15) +
scale_colour_manual(breaks = c(0, 1),
labels = c("No","Yes"),
values = c("green4","red"),
name="Assessment")+
#needed to let the wanted behaviour stand out, so I changed pointsize
scale_size_manual(breaks = c(0, 1), values=c(1,2), guide="none")+
scale_y_discrete(limit=Obsall, labels=ylabels, expand=c(0,0))+
scale_x_continuous(expand=c(0,0),breaks = round(seq(min(0), max(Framerange), by = 200),5000))+
expand_limits(y=c(1,-.5))
update_labels(GraphObserve,list(x="Frames (M01)",y ="Observers"))
这使我得到了一个公平的图表，其中包含每个数据点的漂亮彩色点，但由于这些点重叠并且仍然很小，所以这不是我要走的路。我没有使用 geom_point()，而是使用了 geom_line()。该图确实代表了我想要的每个颜色中断。
所以接下来我将每个 geom_point() 行更改为 geom_line()，同时保持其余部分不变。 （scale_size_manual() 变得相当多余）
geom_line(aes(x=Framerange, y=Obsy0, colour=as.factor(Ob0value)),size=14) +
geom_line(aes(x=Framerange, y=Obsy1, colour=as.factor(Ob1value)),size=14) +
geom_line(aes(x=Framerange, y=Obsy2, colour=as.factor(Ob2value)),size=14) +
geom_line(aes(x=Framerange, y=Obsy3, colour=as.factor(Ob3value)),size=14) +
geom_line(aes(x=Framerange, y=Obsy4, colour=as.factor(Ob4value)),size=14) +
geom_line(aes(x=Framerange, y=Obsy5, colour=as.factor(Ob5value)),size=14) +
geom_line(aes(x=Framerange, y=Obsy6, colour=as.factor(Ob6value)),size=14) +
geom_line(aes(x=Framerange, y=Obsy7, colour=as.factor(Ob7value)),size=14) +
geom_line(aes(x=Framerange, y=Obsy8, colour=as.factor(Ob8value)),size=14) +
geom_line(aes(x=Framerange, y=Obsy9, colour=as.factor(Ob9value)),size=14) +
geom_line(aes(x=Framerange, y=Obsy10, colour=as.factor(Ob10value)),size=14) +
我以为这会很好，但事实并非如此。
不是为文件中的每个 0 和 1 切换颜色，而是在数据集中出现的第一个和最后一个 1 处切换颜色。
上述脚本的图形：http://imgur.com/2baseCa,bJa2Ab7#0
我似乎无法在我的代码中找到错误，我似乎也无法在网上找到解决方案。这里有没有人可以帮我解决这个问题？
更新
为了更清楚地了解概览，我在它们下方放置了指向我以前的脚本生成的图表的链接。
在建议将我的数据置于 "long" 格式之后，我使用了以下脚本：
data1<-read.csv("ObserversBehaviour.csv", ",", header=T)
Frames<-data1[["Frames.M01"]]
Obs<-paste0("Observer",0:10)
Obsy <- sort(rep(0:10,4528),decreasing=F)
Obsvalue <- stack(data1[,c(Obs)])
ObsData2 <- expand.grid(Frames=data1[["Frames.M01"]],Obs=paste0("Observer",0:10))
ObsData2$Observer = Obsy
ObsData2$Assessment = Obsvalue$values
ggplot(ObsData2, aes(Frames, Observer, colour=Assessment)) +
geom_line(show_guide=T) +
scale_y_discrete(limit=0:10, labels=Obs, expand=c(0,0))+
scale_x_continuous(expand=c(0,0),breaks = round(seq(min(0), max(Frames), by = 200),5000))+
expand_limits(y=c(1,.5)) +
#The manual colorcoding actually failed, since it keeps returning this error "Continuous value supplied to discrete scale".
scale_color_manual(breaks = c(0,1),
labels = c("No","Yes"),
values = c("green4","red"),
name="Assessment")
虽然颜色现在实际上根据行为评估值发生了变化，但出现了新问题。
Observer5-10的值全部替换为Observer10的值
通过更改几个参数，我发现通过更改行大小，值恢复正常。但是，Observer10 的值完全消失了。
新脚本的图表： http://imgur.com/AiKeXLc,kPgIKKZ#1（第二张图是第一张图）
结合这些问题和我无法手动更改颜色的事实（即使我尝试在我的值上使用 as.factor() 和 as.discrete()）我不知道我现在可以尝试什么。
作为 R 的初学者，我可能在这里遗漏了一些明显的东西。
更新
dput(head(ObsData2))
## structure(list(Frames = 1:6, Obs = structure(c(1L, 1L, 1L, 1L, 1L, 1L), .Label = c("Observer0", "Observer1", "Observer2", "Observer3",
## "Observer4", "Observer5", "Observer6", "Observer7", "Observer8",
## "Observer9", "Observer10"), class = "factor"), Observer = c(0L,
## 0L, 0L, 0L, 0L, 0L), Assessment = c(0L, 0L, 0L, 0L, 0L, 0L)), .Names = c("Frames",
## "Obs", "Observer", "Assessment"), out.attrs = structure(list(
## dim = structure(c(4528, 11), .Names = c("Frames", "Obs")),
## dimnames = structure(list(Frames = c("Frames= 1", "Frames= 2",
## "Frames= 3", "Frames= 4", "Frames= 5", "Frames= 6",
## "Frames= 7", "Frames= 8", "Frames= 9", "Frames= 10",
## "Frames= 11", "Frames= 12", "Frames= 13", "Frames= 14",
## "Frames= 15", "Frames= 16", "Frames= 17", "Frames= 18",
## "Frames= 19", "Frames= 20", "Frames= 21", "Frames= 22",
## "Frames= 23", "Frames= 24", "Frames= 25", "Frames= 26",
## "Frames= 27", "Frames= 28", "Frames= 29", "Frames= 30",
## "Frames= 31", "Frames= 32", "Frames= 33", "Frames= 34",
## "Frames= 35", "Frames= 36", "Frames= 37", "Frames= 38",
## "Frames= 39", "Frames= 40", "Frames= 41", "Frames= 42",
## "Frames= 43", "Frames= 44", "Frames= 45", "Frames= 46",
## "Frames= 47", "Frames= 48", "Frames= 49", "Frames= 50",
## "Frames= 51", "Frames= 52", "Frames= 53", "Frames= 54",
## "Frames= 55", "Frames= 56", "Frames= 57", "Frames= 58",
## "Frames= 59", "Frames= 60", "Frames= 61", "Frames= 62",
## "Frames= 63", "Frames= 64", "Frames= 65", "Frames= 66",
## "Frames= 67", "Frames= 68", "Frames= 69", "Frames= 70",
## "Frames= 71", "Frames= 72", "Frames= 73", "Frames= 74",
# Long patch of "Frames= <75-4502>" omitted due to space saving
## "Frames=4503", "Frames=4504", "Frames=4505", "Frames=4506",
## "Frames=4507", "Frames=4508", "Frames=4509", "Frames=4510",
## "Frames=4511", "Frames=4512", "Frames=4513", "Frames=4514",
## "Frames=4515", "Frames=4516", "Frames=4517", "Frames=4518",
## "Frames=4519", "Frames=4520", "Frames=4521", "Frames=4522",
## "Frames=4523", "Frames=4524", "Frames=4525", "Frames=4526",
## "Frames=4527", "Frames=4528"), Obs = c("Obs=Observer0", "Obs=Observer1",
## "Obs=Observer2", "Obs=Observer3", "Obs=Observer4", "Obs=Observer5",
## "Obs=Observer6", "Obs=Observer7", "Obs=Observer8", "Obs=Observer9",
## "Obs=Observer10")), .Names = c("Frames", "Obs"))), .Names = c("dim",
## "dimnames")), row.names = c(NA, 6L), class = "data.frame")
如果您将数据设为 "long" 格式，这会容易得多。这是一个假数据的例子：
## Create fake data in long format
ObsData = expand.grid(Frames=1:4258, Obs=paste0("Observer",0:10))
# Add y values
set.seed(10)
ObsData$y = cumsum(rnorm(4258*11))
在长格式数据框中，所有观察者都 "stacked" 到一个具有 11 个类别的单一因子变量 (Obs) - 每个观察者一个。现在您可以将其用作 ggplot.
## Plot with a different color for each observer
ggplot(ObsData, aes(Frames, y, colour=Obs)) +
geom_line()
这是图表使用默认颜色时的样子，但您可以通过将 scale_colour_manual() 添加到绘图并设置您喜欢的任何颜色来更改它。
问题规避
在我同事的帮助下，使用 geom_tile() 而不是 geom_line()，图表现在完全符合我的要求。
require("ggplot2")
data1<-read.csv("ObserversBehaviour.csv", ",", header=T)
Frames<-data1[["Frames.M01"]]
Obs.lab<-paste0("Observer",0:10)
Obsy <- sort(rep(1:11,4528),decreasing=F)
Obsvalue <- stack(data1[,c(Obs.lab)])
ObsData2 <- expand.grid(Frames=data1[["Frames.M01"]],Obs.lab=paste0("Observer",0:10))
ObsData2$Observer = Obsy
ObsData2$Assessment = Obsvalue$values
GraphObserve <- ggplot(ObsData2, aes(Frames, Observer, height=.9)) +
geom_tile(aes(fill = factor(Assessment)))+
scale_fill_manual(values=c("0"="green4", "1"="red"), labels= c("No", "Yes"))+
scale_y_discrete(expand=c(0,0), limit=1:11, labels=Obs.lab)+
scale_x_continuous(expand=c(0,0), breaks = round(seq(min(0), max(Frames), by = 200),5000))
update_labels(GraphObserve,list(x="Frames (M01)",y ="Observers"))
颜色中断恰好出现在他们需要的地方，没有重叠，所有观察者都列在图中。
虽然这并没有真正解决我之前脚本中出现的问题，但它确实提供了更好的结果。
最终图表： http://i.imgur.com/pW8Qh0I.png
谢谢 eipi10，告诉我如何压缩我的脚本。