Rap*_*ter 9 recursion dependencies r function function-declaration
可能重复:
在R中生成调用图
我想系统地分析给定的函数,以找出在该函数中调用的其他函数.如果可能的话,递归地.
我在milktrader的博客文章中遇到了这个函数,我可以用它来做类似的包(或命名空间)
listFunctions <- function(
name,
...
){
name.0 <- name
name <- paste("package", ":", name, sep="")
if (!name %in% search()) {
stop(paste("Invalid namespace: '", name.0, "'"))
}
# KEEP AS REFERENCE
# out <- ls(name)
funlist <- lsf.str(name)
out <- head(funlist, n=length(funlist))
return(out)
}
> listFunctions("stats")
[1] "acf" "acf2AR" "add.scope"
[4] "add1" "addmargins" "aggregate"
[7] "aggregate.data.frame" "aggregate.default" "aggregate.ts"
[10] "AIC" "alias" "anova"
....
[499] "xtabs"
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然而,我想要一个函数,name它将是函数的名称,返回值是在其中调用的函数的字符向量(或者列表,如果以递归方式完成)name.
我实际上需要某种基于字符的输出(矢量或列表).这样做的原因是,我工作的一个通用的包装功能并行的abitrary"内部函数",你不必经过耗时的试错的过程,以找出其他功能内在的功能取决于.所以我之后的函数的输出将直接用于snowfall::sfExport()和/或snowfall::sfSouce.
编辑2012-08-08
由于两面派有一些近距离投票,我将在明天检查答案如何与其他问题合并.
试试这个例子:
library(codetools)
ff <- function(f) {
leaf <- function (e, w) {
r <- try(eval(e), silent = TRUE)
if(!is.null(r) && is.function(r)) ret <<- c(ret, as.character(e))
}
call <- function (e, w) {
walkCode(e[[1]], w)
for (a in as.list(e[-1])) if (!missing(a)) walkCode(a, w)
}
ret <- c()
walkCode(body(f), makeCodeWalker(call = call, leaf = leaf, write = cat))
unique(ret)
}
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然后,
> ff(data.frame)
[1] "{" "<-" "if" "&&" "is.null" "row.names" "function" "is.character"
[9] "new" "as.character" "anyDuplicated" "return" "||" "all" "==" "stop"
[17] "gettextf" "warning" "paste" "which" "duplicated" "[" "as.list" "substitute"
[25] "list" "-" "missing" "length" "<" "!" "is.object" "is.integer"
[33] "any" "is.na" "unique" "integer" "structure" "character" "names" "!="
[41] "nzchar" "for" "seq_len" "[[" "is.list" "as.data.frame" ".row_names_info" ">"
[49] "deparse" "substr" "nchar" "attr" "abs" "max" "(" "%%"
[57] "unclass" "seq_along" "is.vector" "is.factor" "rep" "class" "inherits" "break"
[65] "next" "unlist" "make.names" "match" ".set_row_names"
> ff(read.table)
[1] "{" "if" "&&" "missing" "file" "!" "text" "<-" "textConnection"
[10] "on.exit" "close" "is.character" "nzchar" "inherits" "stop" "isOpen" "open" ">"
[19] "readLines" "<" "min" "(" "+" "lines" ".Internal" "quote" "length"
[28] "all" "==" "pushBack" "c" "stdin" "scan" "col" "numeric" "-"
[37] "for" "seq_along" "[" "max" "!=" "warning" "paste0" ":" "make.names"
[46] "names" "is.null" "rep" "match" "any" "<=" "rep.int" "list" "%in%"
[55] "sapply" "do.call" "data" "flush" "[[" "which" "is.logical" "is.numeric" "|"
[64] "gettextf" "&" "is.na" "type.convert" "character" "as.factor" "as.Date" "as.POSIXct" "::"
[73] "methods" "as" "row.names" ".set_row_names" "as.integer" "||" "is.object" "is.integer" "as.character"
[82] "anyDuplicated" "class" "attr"
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必须有更好的方法,但这是我的尝试:
listFunctions <- function(function.name, recursive = FALSE,
checked.functions = NULL){
# Get the function's code:
function.code <- deparse(get(function.name))
# break code up into sections preceding left brackets:
left.brackets <- c(unlist(strsplit(function.code,
split="[[:space:]]*\\(")))
called.functions <- unique(c(unlist(sapply(left.brackets,
function (x) {
# Split up according to anything that can't be in a function name.
# split = not alphanumeric, not '_', and not '.'
words <- c(unlist(strsplit(x, split="[^[:alnum:]_.]")))
last.word <- tail(words, 1)
last.word.is.function <- tryCatch(is.function(get(last.word)),
error=function(e) return(FALSE))
return(last.word[last.word.is.function])
}))))
if (recursive){
# checked.functions: We need to keep track of which functions
# we've checked to avoid infinite loops.
functs.to.check <- called.functions[!(called.functions %in%
checked.functions)]
called.functions <- unique(c(called.functions,
do.call(c, lapply(functs.to.check, function(x) {
listFunctions(x, recursive = T,
checked.functions = c(checked.functions,
called.functions))
}))))
}
return(called.functions)
}
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结果如下:
> listFunctions("listFunctions", recursive = FALSE)
[1] "function" "deparse" "get" "c"
[5] "unlist" "strsplit" "unique" "sapply"
[9] "tail" "tryCatch" "is.function" "return"
[13] "if" "do.call" "lapply" "listFunctions"
> system.time(all.functions <- listFunctions("listFunctions", recursive = TRUE))
user system elapsed
92.31 0.08 93.49
> length(all.functions)
[1] 518
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如您所见,递归版本返回了许多函数.这个问题是它返回进程中调用的每个函数,这显然会随着你的进行而增加.无论如何,我希望你可以使用它(或修改它)来满足你的需求.
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