在R中自定义类元素列表的排序列表?

I have a custom class object (list of tuples). I have defined <.myclass >.myclass and ==.myclass on it as well.

我有一个自定义类对象(元组列表)。我已经定义的<。myclass >。myclass和= =。我的课上也有。

Now I have a

现在我有一个

a <- obj1 # of myclass
b <- obj2 # of myclass
c <- obj3 # of myclass
L <- list(list(a,12,1),list(b,215,23),list(c,21,9))

I want to sort L, on index 1. i.e. I have b < c < a then, I want sorted L in this form list(list(b,215,23),list(c,21,9),list(a,12,1))

我想对L排序，在索引1上。例如，我有b < c < a那么，我想要在这个表单列表中排序L (list(b,215,23)，list(c,21,9)，list(a,12,1)

How do I achieve this?

我如何做到这一点?

In my searches, I found how to sort on particular index, and using that I wrote the following function

在我的搜索中，我找到了如何对特定索引进行排序，并使用它编写了以下函数

magic_sort <- function(lst, sortind, dec = T) {
    return(lst[order(sapply(lst,'[[',sortind), decreasing = dec)])
}

But when I give index 1 to it, to sort on obj1, it fails with

但是当我给它一个索引1，对obj1排序时，它会失败

> magic_sort(L,1)
Error in order(sapply(lst, "[[", sortind), decreasing = dec) : 
    unimplemented type 'list' in 'orderVector1'

Is there any fix for this? In general, can I have functions like sort, minimum and so on, based on custom definition of comparison operators?

有什么解决办法吗?一般来说，我能基于比较运算符的自定义定义定义拥有排序、最小等函数吗?

Edit: Following perhaps will help understand the structure better: http://pastebin.com/0M7JRLTu

编辑:以下内容可能有助于更好地理解结构:http://pastebin.com/0M7JRLTu

Edit 2:

编辑2:

library("sets")

a <- list()
class(a) <- "dfsc"
a[[1]] <- tuple(1L, 2L, "C", "a", "B")

b <- list()
class(b) <- "dfsc"
b[[1]] <- tuple(1L, 2L, "A", "b", "B")

c <- list()
class(c) <- "dfsc"
c[[1]] <- tuple(1L, 2L, "A", "a", "B")

L <- list()
L[[1]] <- list(a, 12, 132)
L[[2]] <- list(b, 21, 21)
L[[3]] <- list(c, 32, 123)

`<.dfsc` <- function(c1, c2) {
    return(lt_list(toList(c1),toList(c2)))
}

`==.dfsc` <- function(c1, c2) {
    return(toString(c1) == toString(c2))
}

`>.dfsc` <- function(c1, c2) {
    return(!((c1 < c2) || (c1 == c2)))
}

lt_list <- function(l1, l2) {
    n1 <- length(l1)
    n2 <- length(l2)
    j = 1
    while(j <= n1 && j <= n2) {
        if (l1[[j]] != l2[[j]]) {
            return (l1[[j]] < l2[[j]])
        }
        j = j + 1
    }
    return(n1 < n2)
}

toString.dfsc <- function(x) {
    code_string <- ""
    #for(ii in x[[1]]) {
    for(ii in x) {   
        code_string <- paste(code_string,"(",ii[[1]],",",ii[[2]],",",ii[[3]],",",ii[[4]],",",ii[[5]],")", sep = "")
    }
    return(code_string)
}

Now I want the L desired to be list(list(c,_,_),list(b,_,_),list(a,_,_))

现在我想要L所需的列表(列表(c、_、_),列表(b,_,_),列表(_,_))

2 个解决方案

#1

This answer from Aaron demonstrates, exactly, what is needed to apply a customized sort on a classed object. As Roland notes, you -actually- need to sort "L" and, thus, that is where the focus on custom sort should be. To provide flexibility specifying on which index of "L" 's elements to sort, a way would be to store an extra attr on "L":

Aaron给出的这个答案演示了在一个类对象上应用自定义排序所需的东西。正如Roland所指出的，实际上，您需要对“L”进行排序，因此，这就是关注自定义排序的地方。为了提供对“L”元素的索引进行排序的灵活性，一种方法是在“L”上存储一个额外的attr:

Turn "L" to an appropriate object:

将“L”转到合适的对象:

class(L) = "myclass"
attr(L, "sort_ind") = 1L

Ops methods need to be defined (extract the relevant element of your data):

需要定义Ops方法(提取数据的相关元素):

"<.myclass" = function(x, y) 
{
    i = attr(x, "sort_ind") ## also check if 'x' and 'y' have the same 'attr(, "sort_ind")'
    x[[1]][[i]] < y[[1]][[i]] 
}
"==.myclass" = function(x, y) 
{
     i = attr(x, "sort_ind")
     x[[1]][[i]] == y[[1]][[i]] 
}
">.myclass" = function(x, y) 
{
    i = attr(x, "sort_ind")
    x[[1]][[i]] > y[[1]][[i]] 
}

And a subset method:

和一个子集法:

"[.myclass" = function(x, i) 
{
    y = .subset(x, i)
    attributes(y) = attributes(x)
    return(y)
}

The above methods are necessary (perhaps, except "<") to be defined since a call to sort/order will end up calling rank which needs .gt in order to subset accordingly each element and compare. Finally, a get/set function for sauce:

上述方法是必须定义的(可能除了“<”)，因为对排序/排序的调用最终会调用需要.gt的rank，以便相应地对每个元素进行子集划分并进行比较。最后，酱料的get/set函数:

sort_ind = function(x) attr(x, "sort_ind")
"sort_ind<-" = function(x, value) 
{
    attr(x, "sort_ind") = value
    return(x)
}

And:

和:

order(L)
#[1] 3 2 1
sort_ind(L) = 3
order(L)
#[1] 2 3 1

A method for sort can be, also, created to wrap all the above:

一种排序方法也可以被创建来包装上述所有内容:

sort.myclass = function(x, sort_ind = attr(x, "sort_ind"), ...)
{
    sort_ind(x) = sort_ind
    NextMethod()
}

sort(L)
sort(L, sort_ind = 1)

(I assumed that your toList function would look like something toList = function(x) x[[1L]])

(我假设toList函数应该是toList = function(x) x[[1L]]))

#2

I wanted to make use of internal and supposedly more efficient sort, but doesn't seem like this sort has facility to take custom comparison operator. So I ended up using implementation of quicksort to sort lists of lists at arbitrary index, assuming comparison exists between the elements at that index.

我想要使用内部的并且被认为是更有效的排序，但是看起来这种排序并没有使用自定义比较运算符的功能。因此，我最终使用了快速排序的实现来对任意索引中的列表进行排序，假设该索引中的元素之间存在比较。

part_qsort <- function(l, idx, low, high) {
    lst <- l
    pivot <- lst[[high]][[idx]]
    i <- low - 1

    for(j in low:(high-1)) {
        if ((lst[[j]][[idx]] < pivot) || (lst[[j]][[idx]] == pivot)) {
            i <- i + 1
            swap(lst[[i]],lst[[j]])
        }
    }
    swap(lst[[(i+1)]],lst[[high]])
    eval.parent(substitute(l <- lst))
    return(i+1)
}

# recursive calls to quicksort
qsort <- function(l,idx,low,high) {
    if (low < high) {
        lst <- l
        pi <- part_qsort(lst,idx,low,high)
        qsort(lst, idx, low, pi-1)
        qsort(lst, idx, pi+1, high)
        eval.parent(substitute(l <- lst))
    }
}

Another thing to look into can be library("rlist") which seems to have a bunch of functions implemented on lists.

另一件要研究的事情是库(“rlist”)，它似乎有一堆在列表上实现的函数。

#1