【发布时间】:2018-09-05 16:16:04
【问题描述】:
我正在尝试对一些数据进行 AUDPC 分析。需要将数据拆分为处理和复制块以进行分析。下面我尝试编写一个函数,目的是拆分数据分析并最终将所有处理块的输出放在一个表/对象中
library("agricolae")
library("plyr")
library("dplyr")
data = read.csv("Bio2018.csv", header = TRUE, sep = ",")
data$Treatment = as.character(data$Treatment)
data$Block = as.character(data$Block)
data$Time = as.numeric(data$Time)
AUDPC.rel = function(Treatment, Block){
data.Treatment <- subset(data, data$Treatment == Treatment & data$Block == Block)
AUDPC = data.frame(audpc(data.Treatment$Foci, data.Treatment$Time, type = "absolute"))
}
variables = expand.grid(Treatment = c(unique(data$Treatment)), Block = c(unique(data$Block)))
Relative.AUDPC = mdply(variables,AUDPC.rel)
Relative.AUDPC
输出总是为所有治疗块提供相同的数字。如图:
治疗 - 阻止 - 评估
未经处理 - Rep.1 - 200;
翡翠 - Rep.1 - 200;
Nortica - Rep.1 - 200;
未处理 - Rep.2 - 200;
翡翠 - Rep.2 - 200;
Nortica - Rep.2 - 200;
未处理 - Rep.3 - 200;
翡翠 - Rep.3 - 200;
Nortica - Rep.3 - 200;
【问题讨论】: