❝本节来进行论文图表的复现；通过ggplot2绘制误差线点图
加载R包
代码语言：javascript复制library(tidyverse)
library(ggprism)
library(ggsci)
数据清洗
代码语言：javascript复制df <- read_tsv("F1-b.txt") %>% pivot_longer(-c(type,time)) %>%
select(-name) %>%
group_by(type,time) %>%
summarise(value_mean=mean(value),sd=sd(value),se=sd(value)/sqrt(n())) %>%
arrange(time) %>%
filter(type !="w/o")
定义因子
代码语言：javascript复制❝此处由于要根据时间与类型两个因素来调整顺序因此定义两个因子 ❞
df$time <- factor(df$time,levels = c("10min","1h","6h","10h","24h","48h"))
df$type <- factor(df$type,levels=read_tsv("F1-b.txt") %>% pivot_longer(-c(type,time)) %>%
select(type) %>% distinct() %>% pull())
数据可视化
代码语言：javascript复制❝此图虽然只是基础图形但是所包含的细节还是挺多的，需要注意的是根据需要调整各几何对象的顺序从而达到理想的结果，由于需要更改图例形状此处使用了两次「geom_point」 ❞
df %>% ggplot(aes(time,value_mean,fill=type,group=type,ymin=value_mean-se,ymax=value_mean se))
geom_errorbar(width=0.1)
geom_line(color="black")
geom_point(key_glyph="polygon",aes(color=type))
geom_point(pch=21,size=5,show.legend = F)
scale_fill_npg()
scale_color_npg()
scale_x_discrete(guide = "prism_bracket")
scale_y_continuous(limits = c(0,300),minor_breaks = seq(0,300,50), guide = "prism_offset_minor")
annotate("text",x = 3,y=16,label="***",size=7,color="#35627F")
labs(x=NULL,y=NULL)
theme_prism(base_line_size =0.5)
theme(plot.margin=unit(c(0.1,0.1,0.1,0.1),units=,"cm"),
axis.line = element_line(color = "black",size = 0.4),
panel.grid.minor = element_blank(),
panel.grid.major = element_line(size = 0.2,color = "#e5e5e5"),
axis.text.y = element_text(color="black",size=10),
axis.text.x = element_text(margin = margin(t = -5),color="black",size=10),
legend.key=element_blank(),
legend.title = element_blank(),
legend.text = element_text(color="black",size=8),
legend.spacing.x=unit(0.1,'cm'),
legend.spacing.y=unit(1,'cm'),
legend.key.width=unit(0.7,'cm'),
legend.key.height=unit(0.4,'cm'),
legend.background=element_blank(),
legend.box.margin = margin(0,0,0,0))
