我有以下数据集,其中包含每个单个班级的多次运行的数据(即,在以下情况下,每个班级仅两次运行):
Class Total_individuals 1 2 3 4 5
A 1000 10 6 8 5 2
A 1000 3 9 1 2 5
B 1000 7 2 6 4 8
B 1000 1 9 8 2 5
C 1000 6 4 2 8 7
C 1000 9 1 5 4 8
我想生成一个多图,其中每个类包含一个图,如下所示:
此图显示了三个类别的首次运行的数据:
A 10 6 8 5 2
B 7 2 6 4 8
C 6 4 2 8 7
然后,我想为第二次运行的数据生成另一个多重绘图:
A 3 9 1 2 5
B 1 9 8 2 5
C 9 1 5 4 8
为此,我编写了以下R
脚本:
####################################
multiplot <- function(..., plotlist=NULL, file, cols=1, layout=NULL) {
library(grid)
# Make a list from the ... arguments and plotlist
plots <- c(list(...), plotlist)
numPlots = length(plots)
# If layout is NULL, then use 'cols' to determine layout
if (is.null(layout)) {
# Make the panel
# ncol: Number of columns of plots
# nrow: Number of rows needed, calculated from # of cols
layout <- matrix(seq(1, cols * ceiling(numPlots/cols)),
ncol = cols, nrow = ceiling(numPlots/cols))
}
if (numPlots==1) {
print(plots[[1]])
} else {
# Set up the page
grid.newpage()
pushViewport(viewport(layout = grid.layout(nrow(layout), ncol(layout))))
# Make each plot, in the correct location
for (i in 1:numPlots) {
# Get the i,j matrix positions of the regions that contain this subplot
matchidx <- as.data.frame(which(layout == i, arr.ind = TRUE))
print(plots[[i]], vp = viewport(layout.pos.row = matchidx$row,
layout.pos.col = matchidx$col))
}
}
}
###################################
library(readr)
library(reshape2)
library(dplyr)
library(ggplot2)
library(scales)
dataset <- read_csv("/home/adam/Desktop/a.csv")
YaxisTitle <- "Fitness"
dataset <- dataset %>% melt(id.vars = c("Class"))
dataset <- subset(dataset, variable != "Total_individuals")
dataset <- transform(dataset, value = as.numeric(value))
myplots <- list() # new empty list
for (x in unique(dataset$Class)){
p2_data <- dataset %>% filter(Class == x)
pp2 <- p2_data %>% ggplot(aes(x=variable, y=value, group=Class, colour=Class)) +
geom_line() +
scale_x_discrete(breaks = seq(0, 5, 1)) +
labs(x = as.character(p2_data$Class), y = YaxisTitle) +
theme(text = element_text(size=10),legend.position="none")
myplots[[i]] <- pp2
i <- i+1
}
xx <- multiplot(myplots[[1]], myplots[[2]], myplots[[3]], cols=2)
png(filename="/home/adam/Desktop/name.png")
plot(xx)
dev.off()
但是这个脚本给了我以下图:
将一个运行中所有运行的所有数据组合在一起。
所以我要为三个类的每次运行生成一个多图。
答案 0 :(得分:2)
使用刻面:从宽到长整形,添加 x 值和 runN ,然后使用刻面进行绘制:
# example data
df1 <- read.table(text = "Class Total_individuals 1 2 3 4 5
A 1000 10 6 8 5 2
A 1000 3 9 1 2 5
B 1000 7 2 6 4 8
B 1000 1 9 8 2 5
C 1000 6 4 2 8 7
C 1000 9 1 5 4 8", header = TRUE)
library(ggplot2)
library(tidyr)
plotDat <- df1 %>%
group_by(Class) %>%
mutate(runN = paste0("run_", row_number())) %>%
gather(key = "k", value = "v", -c(Class, Total_individuals, runN)) %>%
group_by(Class, runN) %>%
mutate(x = row_number())
对运行ID进行紧急检查:
ggplot(plotDat, aes(x, v, col = Class)) +
geom_line() +
facet_grid(.~runN)
或者在运行ID和类方面:
ggplot(plotDat, aes(x, v, col = Class)) +
geom_line() +
facet_wrap(.~runN + Class, ncol = length(unique(plotDat$Class)))
甚至更好的版本,如@Axemen的评论中所述:
ggplot(plotDat, aes(x, v, col = Class)) +
geom_line() +
facet_grid(runN ~ Class)