将toJson R对象转换为适合d3.js树形布局的格式 [英] Converting toJson R object into a format that fits d3.js tree layout

问题描述

这是来自以下问题的后续问题:转换ctree输出为JSON格式(用于D3树布局)

This is a followup question from : Converting ctree output into JSON Format (for D3 tree layout)

我有以下代码，是使用ctree生成的(来自Party，请参见下面的代码)，我的意图是创建一个递归函数，以转换以下Json输出:

I have the following code, produced using ctree (from Party, see bellow the code that produced it), my intention is to create a recursive function that transforms the following Json output:

    {"nodeID":[1],"left":
          {"nodeID":[2],"weights":[50],"prediction":[1,0,0]},
          "right":
          {"nodeID":[3],"left":{
          "nodeID":[4],"left":
          {"nodeID":[5],"weights":[46],"prediction":[0,0.9783,0.0217]},"right":
          {"nodeID":[6],"weights":[8],"prediction":[0,0.5,0.5]}},"right":
          {"nodeID":[7],"weights":[46],"prediction":[0,0.0217,0.9783]}}} 

分为以下内容:

      { "name": "1", "children": [
            {
            "name": "3","children": [
                {
                "name": "4","children":[
                    {"name":"5 weights:[46] prediction:[0,0.9783,0.0217]"},
                    {"name":"6 weights:[8]  prediction[0,0.5,0.5]}"
                    ]                          
                }
                {{"nodeID":"7 weights:[46]prediction[0,0.0217,0.9783]"}
                }
            ]
            },
           {
            "name": "2 weights:[50] prediction[1,0,0]",
           }
        ]
      }

这让我创建了以下出色的d3.js输出:

which lets me create the following wonderful d3.js output:

背景:

我有以下代码可以创建Json输出，但不能退出我需要的代码:

I have the following code which creates a Json output, but not quit the code i need:

library(party)
irisct <- ctree(Species ~ .,data = iris)
plot(irisct)

get_ctree_parts <- function(x, ...)
{
  UseMethod("get_ctree_parts")
}

get_ctree_parts.BinaryTree <- function(x, ...)
{
  get_ctree_parts(attr(x, "tree"))
}

get_ctree_parts.SplittingNode <- function(x, ...)
{
  with(
    x,
    list(
      nodeID       = nodeID,
      left         = get_ctree_parts(x$left),
      right        = get_ctree_parts(x$right)
    )
  )
}

get_ctree_parts.TerminalNode <- function(x, ...)
{
  with(
    x,
    list(
      nodeID     = nodeID,
      weights    = sum(weights),
      prediction = prediction
    )
  )
}

toJSON(get_ctree_parts(irisct))

我试图对其进行改造，但似乎我面临一些挑战，但我无法解决: 为了获得一个通用的解决方案，我需要一些递归函数，只要有一个分割(孩子)，它就会创建一个嵌套的Json对象，而且，ctree具有与d3.js导航约定不同的导航约定，在ctree中的导航使用向右"和向左"产生，其中d3.js需要子级"导航"

I tried to transform it, but it seems like i have a few challenges, i just cant solve: in order to get a general solution, i need some recursive function, that creates a nested Json object, whenever there is a split (children), also, ctree have different navigation conventions from the d3.js navigation convention, where in ctree the navigation accrues using "right" and "left", where d3.js requires "children" navigation"

任何对此的帮助都将是很棒的，我在此停留了一段时间:)

Any help on this would be wonderful, i'm stuck on this for quit a while :)

推荐答案

我刚刚看完文章后才开始R编码.

hi i just started R coding after seeing post this is i achieved so far ..

library(party)
irisct <- ctree(Species ~ .,data = iris)
plot(irisct)

get_ctree_parts <- function(x, ...)
{
  UseMethod("get_ctree_parts")
}

get_ctree_parts.BinaryTree <- function(x, ...)
{
  get_ctree_parts(attr(x, "tree"))
}

get_ctree_parts.SplittingNode <- function(x, ...)
{
  with(
    x,
    list(
      name       = toString(nodeID),
      children   = list(get_ctree_parts(x$left),get_ctree_parts(x$right))

    )
  )
}

get_ctree_parts.TerminalNode <- function(x, ...)
{
  with(
    x,
    list(
      name     = paste(nodeID,"weights",sum(weights),"prediaction",toString(paste("[",toString(prediction),"]",sep=" ")),sep = " ")

    )
  )
}

toJSON(get_ctree_parts(irisct))

Json输出:

{"name":["1"],"children":[
    {"name":["2 weights 50 prediaction [ 1, 0, 0 ]"]},
        {"name":["3"],"children":[
            {"name":["4"],"children":[
                {"name":["5 weights 46 prediaction [ 0, 0.978260869565217, 0.0217391304347826 ]"]},
                {"name":["6 weights 8 prediaction [ 0, 0.5, 0.5 ]"]}]
            },
            {"name":["7 weights 46 prediaction [ 0, 0.0217391304347826, 0.978260869565217 ]"]
            }]
        }]
} 

如果您有任何问题评论，我会尽力而为.

If you have any problem comment i will try my best.

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