ggplot的条件stat_summary R

Question

如果数据大于某个值，我想在图中写一些条件统计量。

与杰克瑞安的热心帮助（Cut data and access groups to draw percentile lines），我可以创建以下脚本组数据到小时，并绘制结果：

# Read example data 
A <- read.csv(url('http://people.ee.ethz.ch/~hoferr/download/data-20130812.csv')) 

# Libraries 
library(doBy) 
library(ggplot2) 
library(plyr) 
library(reshape2) 
library(MASS) 
library(scales) 

# Sample size function 
give.n <- function(x){ 
     return(c(y = min(x) - 0.2, label = length(x))) 
} 

# Calculate gaps 
gaps <- rep(NA, length(A$Timestamp)) 
times <- A$Timestamp 
loss <- A$pingLoss 
gap.start <- 1 
gap.end <- 1 
for(i in 2:length(A$Timestamp)) 
{ #For all rows 
    if(is.na(A$pingRTT.ms.[i])) 
    { #Currently no connection 
     if(!is.na(A$pingRTT.ms.[i-1])) 
     { #Connection lost now 
      gap.start <- i 
     } 
     if(!is.na(A$pingRTT.ms.[i+1])) 
     { # Connection restores next time 
      gap.end <- i+1 
      gaps[gap.start] <- as.numeric(A$Timestamp[gap.end]-A$Timestamp[gap.start], units="secs") 
      loss[gap.start] <- gap.end - gap.start 
     } 
    }  
}    
H <- data.frame(times, gaps, loss) 
H <- H[complete.cases(H),] 
C <- H  
C$dates <- strptime(C$times, "%Y-%m-%d %H:%M:%S") 
C$h1 <- C$dates$hour 

# Calculate percentiles 
cuts <- c(1, .75, .5, .25, 0) 
c <- ddply(C, .(h1), function (x) { summarise(x, y = quantile(x$gaps, cuts)) }) 
c$cuts <- cuts 
c <- dcast(c, h1 ~ cuts, value.var = "y") 
c.melt <- melt(c, id.vars = "h1") 

p <- ggplot(c.h1.melt, aes(x = h1, y = value, color = variable)) + 
geom_point(size = 4) + 
stat_summary(fun.data = max.n, geom = "text", fun.y = max, colour = "red", angle = 90, size=4) + 
scale_colour_brewer(palette="RdYlBu", name="Percentile", guide = guide_legend(reverse=TRUE)) + 
scale_x_continuous(breaks=0:23, limits = c(0,23)) + 
annotation_logticks(sides = "lr") + 
theme_bw() + 
scale_y_log10(breaks=c(1e0,1e1,1e2,1e3,1e4), labels = trans_format("log10", math_format(10^.x)), limits=c(1e0,1e4)) + 
xlab("Hour of day") + ylab("Ping gaps [s]") 
p 

p <- ggplot(c.m1.melt, aes(x = m1/60, y = value, color = variable)) + 
geom_point(size = 1) + 
stat_summary(fun.data = give.n, geom = "text", fun.y = median, angle = 90, size=4) + 
stat_summary(fun.data = max.n, geom = "text", fun.y = max, colour = "red", angle = 90, size=4) + 
scale_colour_brewer(palette="RdYlBu", name="Percentile", guide = guide_legend(reverse=TRUE)) + 
scale_x_continuous(breaks=0:23, limits = c(0,24)) + 
annotation_logticks(sides = "lr") + 
theme_bw() + 
scale_y_log10(breaks=c(1e0,1e1,1e2,1e3,1e4), labels = trans_format("log10", math_format(10^.x)), limits=c(1e0,1e4)) + 
xlab("Time of day") + ylab("Ping gaps [s]") 
p 

这就造成差距与长度每小时分组情节最长的差距书面旁边的数据点：

下面是微小的分组情节。这个数字是不可读的，为什么我想添加条件统计数据，如果差距超过5分钟，或者只有10个最长的差距或类似的东西。

我试着只是改变统计功能

max.n.filt <- function(x){ 
    filter = 300 
    if (x > filter) { 
     return(c(y = max(x) + 0.4, label = round(max(10^x),2))) 
    } else { 
     return(c(y=x, label = "")) 
    } 
} 

，并使用这个细微的情节分组。但我得到这个错误：

Error in list_to_dataframe(res, attr(.data, "split_labels")) : 
    Results do not have equal lengths 
In addition: There were 50 or more warnings (use warnings() to see the first 50) 
Error in if (nrow(layer_data) == 0) return() : argument is of length zero 
Calls: print ... print.ggplot -> ggplot_gtable -> Map -> mapply -> <Anonymous> 
In addition: Warning message: 
Removed 6 rows containing missing values (geom_point). 

此外，在每小时情节，我想写旁边的缝隙的长度每小时的样本数量。我想我可以在c数据框中添加一个新列，但不幸的是我找不到这样做的方法。

任何帮助，非常感谢。

Answer 1

请参阅？stat_summary。

fun.data : Complete summary function. Should take data frame as input and return data frame as output

你的功能max.n.filt使用试图评估条件x > filter的if()声明。但是当length(x) > 1时，if()语句仅评估第一个值x的条件。当在数据框上使用时，这将返回从原始输入x拼凑在一起的列表以及if()语句返回的任何标签。

​​

尝试使用ifelse()的函数：

max.n.filt2 <- function(x){ 
    filter = 300     # whatever threshold 
    y = ifelse(x > filter, max(x) + 1, x[,1]) 
    label = ifelse(x > filter, round(max(x),2), NA) 
    return(data.frame(y=y[,1], label=label[,1])) 
} 

> max.n.filt2(data.frame(x=c(10,15,400))) 
    y label 
1 10 NA 
2 15 NA 
3 401 400 

或者，你可能发现它更容易使用geom_text()。我无法重现你的榜样，但这里有一个模拟数据集：

set.seed(101) 
sim_data <- expand.grid(m1=1:1440, variable=factor(c(0,0.25,0.5,0.75,1))) 
sim_data$sample_size <- sapply(1:1440, function(.) sample(1:25, 1, replace=T)) 
sim_data$value = t(sapply(1:1440, function(.) quantile(rgamma(sim_data$sample_size, 0.9, 0.5),c(0,0.25,0.5,0.75,1))))[1:(1440*5)] 

只需使用subset论点geom_text()选择那些你想标记点：

ggplot(sim_data, aes(x = m1/60, y = value, color = variable)) + 
geom_point(size = 4) + geom_text(aes(label=round(value)), subset = .(variable == 1 & value > 25), angle = 90, size = 4, colour = "red", hjust = -0.5) 

如果你有一列样品的尺寸，那些可并入label与paste()：

ggplot(sim_data, aes(x = m1/60, y = value, color = variable)) + 
geom_point(size = 4) + geom_text(aes(label=paste(round(value),", N=",sample_size)), subset = .(variable == 1 & value > 25), angle = 90, size = 4, colour = "red", hjust = -0.25) 

（或创建一个单独的列的数据与你想要的任何标签。）如果你问如何取回样本大小，您可以修改您的来电ddply()这样的：

... 
c2 <- ddply(C, .(h1), function (x) { cbind(summarise(x, y = quantile(x$gaps, cuts)), n=nrow(x)) }) 
c2$cuts <- cuts 
c2 <- dcast(c2, h1 + n ~ cuts, value.var = "y") 
c2.h1.melt <- melt(c2, id.vars = c("h1","n")) 
...