这里是一个例子:
drugs<-c("Lapatinib-Ditosylate", "Caffeic-Acid-Phenethyl-Ester", "Pazopanib-HCl", "D-Pantethine")
ads<-"These are recently new released drugs Lapatinib Ditosylate, Pazopanib HCl, and Caffeic Acid Phenethyl Ester"
我想要的是用ads
中的名称更正drugs
中的药物名称,以使所需的输出为:
"These are recently new released drugs Lapatinib-Ditosylate, Pazopanib-HCl, and Caffeic-Acid-Phenethyl-Ester"
答案 0 :(得分:2)
如果创建一个要替换的单词向量,则可以在该向量和单词向量上进行循环以替换它们(drugs
),从而在循环的每个交互中替换一个元素的所有实例。
to_repl <- gsub('-', ' ', drugs)
for(i in seq_along(drugs))
ads <- gsub(to_repl[i], drugs[i], ads)
ads
# "These are recently new released drugs Lapatinib-Ditosylate, Pazopanib-HCl, and Caffeic-Acid-Phenethyl-Ester"
与普遍看法相反,R中的for
循环并不比lapply
慢
f_lapply <- function(ads){
to_repl <- gsub('-', ' ', drugs)
invisible(lapply(seq_along(to_repl), function(i) {
ads <<- gsub(to_repl[i], drugs[i], ads)
}))
ads
}
f_loop <- function(ads){
to_repl <- gsub('-', ' ', drugs)
for(i in seq_along(to_repl))
ads <- gsub(to_repl[i], drugs[i], ads)
ads
}
f_loop(ads) == f_lapply(ads)
# [1] TRUE
microbenchmark::microbenchmark(f_loop(ads), f_lapply(ads), times = 1e4)
# Unit: microseconds
# expr min lq mean median uq max neval
# f_loop(ads) 59.488 95.180 118.0793 107.487 120.205 7426.866 10000
# f_lapply(ads) 69.333 114.462 147.9732 130.872 152.205 27283.670 10000
或者,使用更一般的示例:
loop_over <- 1:1e5
microbenchmark::microbenchmark(
for_loop = {for(i in loop_over) 1},
lapply = {lapply(loop_over, function(x) 1)}
)
# Unit: milliseconds
# expr min lq mean median uq max neval
# for_loop 4.66174 5.865842 7.725975 6.354867 7.449429 35.26807 100
# lapply 94.09223 114.378778 125.149863 124.665128 134.217326 170.16889 100
loop_over <- 1:1e5
microbenchmark::microbenchmark(
for_loop = {y <- numeric(1e5); for(i in seq_along(loop_over)) y[i] <- loop_over[i]},
lapply = {lapply(loop_over, function(x) x)}
)
# Unit: milliseconds
# expr min lq mean median uq max neval
# for_loop 11.00184 11.49455 15.24015 12.10461 15.26050 134.139 100
# lapply 71.41820 81.14660 93.64569 87.05162 98.59295 357.219 100
答案 1 :(得分:0)
这也可以使用(::after)
来完成,它比lapply()
循环快。修改@IceCreamToucan的答案,可以在for
中进行如下操作
lapply
微基准测试
to_repl <- gsub('-', ' ', drugs)
invisible(lapply(seq_along(to_repl), function(i) {
ads <<- gsub(to_repl[i], drugs[i], ads)
}))
# [1] "These are recently new released drugs Lapatinib-Ditosylate, Pazopanib-HCl, and Caffeic-Acid-Phenethyl-Ester"