将ctree输出转换为JSON格式(用于D3树布局) [英] Converting ctree output into JSON Format (for D3 tree layout)
问题描述
我正在开发一个需要运行 ctree
的项目,然后以交互模式绘制 - 像'D3.js'树布局,我的主要障碍是将 ctree
输出转换为 json
格式,以供以后通过javascript使用。
I'm working on a project that requires to run a ctree
and then plot it in interactive mode - like the 'D3.js' tree layout, my main obstacle is to convert the ctree
output into a json
format, to later use by javascript.
以下是我需要的(例如来自iris数据):
Following is what i need (with example from the iris data):
> library(party)
> irisct <- ctree(Species ~ .,data = iris)
> irisct
Conditional inference tree with 4 terminal nodes
Response: Species
Inputs: Sepal.Length, Sepal.Width, Petal.Length, Petal.Width
Number of observations: 150
1) Petal.Length <= 1.9; criterion = 1, statistic = 140.264
2)* weights = 50
1) Petal.Length > 1.9
3) Petal.Width <= 1.7; criterion = 1, statistic = 67.894
4) Petal.Length <= 4.8; criterion = 0.999, statistic = 13.865
5)* weights = 46
4) Petal.Length > 4.8
6)* weights = 8
3) Petal.Width > 1.7
7)* weights = 46
现在我要转换 ctee
使用一些算法输出到下面的JSON格式(我手动),但这可能不是最好的方式来转换:
Now i want to convert the ctee
output into the following JSON format using some algorithm (i did it manually), though, this is probably not the best way to convert it:
{"name" : "Petal.Length <= 1.9 criterion = 1","value": 60, "children" : [
{"name" : "n=50" ,"value": 60},
{"name" : "Petal.Length > 1.9 criterion = 1","value": 60, "children": [
{"name" : "n=46","value": 60 },
{"name" : "Petal.Length > 4.8","value": 60, "children" :[
{"name" : "Petal.Width > 1.7" ,"value": 60},
{"name" : "46" ,"value": 60}
]}] }
]}
这里有两个R和 D3的图片。 js
图示:
我已经尝试在ctree对象上使用 RJSONIO
,这没有什么帮助。
i already tried using RJSONIO
on the ctree object, that didn't help much.
任何人都转换一个ctree对象/输出为JSON使用D3.js树布局?
Has anyone ever converted a ctree object/output into JSON for the use of D3.js tree layout? if not, does anyone have any idea of an algorithm that can convert one output to the other?
预先感谢任何帮助!
类似这样:
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,
variableName = psplit$variableName,
splitPoint = psplit$splitpoint,
pValue = 1 - round(criterion$maxcriterion, 3),
statistic = round(max(criterion$statistic), 3),
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
)
)
}
useful_bits_of_irisct <- get_ctree_parts(irisct)
toJSON(useful_bits_of_irisct)
的 unclass
函数。例如:
unclass(irisct)
unclass(attr(irisct, "tree"))
unclass(attr(irisct, "tree")$psplit)
code> party ::: print.SplittingNode 和 party ::: print.TerminalNode
也非常有用。 ( party ::: print。
和自动填充以查看可用的内容。)
The print methods in the package, party:::print.SplittingNode
and party:::print.TerminalNode
were also very useful. (Type party:::print.
and autocomplete to see what is available.)
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