responses

.gitignore

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.Rhistory
.RData

responses.R

#library(devtools)
#devtools::install_github("gluc/data.tree@v0.2.1")
library(data.tree)

#load data

csv <- "location,type,customer,response
suburban,ranch,yes,no
rural,ranch,yes,yes
urban,ranch,yes,no
suburban,multi-story,yes,yes
rural,multi-story,yes,yes
urban,multi-story,yes,no
suburban,ranch,no,no
rural,ranch,no,yes
urban,ranch,no,yes
suburban,multi-story,no,yes
rural,multi-story,no,yes
urban,multi-story,no,yes"


#Convert to tree
df <- read.csv(textConnection(csv), stringsAsFactors = FALSE)
df$pathString <- paste("response", df$location, df$type, df$customer, rownames(df), sep = "/")
responses <- as.Node(df[,c(4,5)])

responses$Set(type = "location", filterFun = function(x) x$level == 2)
responses$Set(type = "type", filterFun = function(x) x$level == 3)
responses$Set(type = "customer", filterFun = function(x) x$level == 4)
                     
#Aggregate responses
Aggregate(responses, "response", function(responses) {
  if (all(responses == "yes")) return ("yes")
  if (all(responses == "no")) return ("no")
  return ("mixed")
}, "response")

#Make a clone, in case we want to compare later
responsesOrig <- Clone(responses)

#Now, we simplify the tree by mergin nodes that are not discriminating

#if two nodes are equal in terms of their child decisions, they are not discriminating
AreNodesEqual <- function(node1, node2) {
  n1t <- node1$Get("response", filterFun = isNotLeaf)
  n2t <- node2$Get("response", filterFun = isNotLeaf)
  names(n1t) <- node1$Get("type", filterFun = isNotLeaf)
  names(n2t) <- node2$Get("type", filterFun = isNotLeaf)
  isTRUE(all.equal(n1t, n2t))
}


#group siblings into a single else node if they are non-discriminating 
GroupNodes <- function(node1, node2) {
  CreateElse <- function(node) {
    nc <- Clone(node)
    nc$parent <- NULL
    nc$name <- "else"
    nc$type <- "else"
    nc$response <- node$response
    return (nc)
  }
  n1c <- CreateElse(node1)
  n2c <- CreateElse(node2)
  elseNode <- as.Node( rbind(ToDataFrameTree(n1c, "pathString", "type", "response"), 
                             ToDataFrameTree(n2c, "pathString", "type", "response"))
  )
  parent <- node1$parent
  parent$RemoveChild(node1$name)
  parent$RemoveChild(node2$name)
  parent$AddChildNode(elseNode)
}

GroupChildren <- function(parent) {
  
  if (parent$count <= 1) return()
  combos <- combn(lapply(parent$children, function(x) x$name), 2)
  for (i in 1: ncol(combos)) {
    n1 <- parent$children[[combos[[1, i]]]]
    n2 <- parent$children[[combos[[2, i]]]]
    if (AreNodesEqual(n1, n2)) {
      GroupNodes(n1, n2)
      GroupChildren(parent)
      break
    }
  }
}


DoGroupChildren <- function(node) {
  if (node$height <= 2) return()
  GroupChildren(node)
  sapply(node$children, function(x) DoGroupChildren(x))
}

DoGroupChildren(responses)





responses$Do(function(x) x$obsCount <- x$totalCount)
responses$Prune(pruneFun = isNotLeaf)

print(responses, "response", "type", "obsCount")
#print(responsesOrig, "response", "type")


#Finally, print the statement
GetIfStatement <- function(node) {
  paste0("IF(", node$type, " = ", node$name, ") ")
}


GetStatement <- function(node) {
  paste(c(rev(node$Get(GetIfStatement, 
                       traversal = "ancestor", 
                       filterFun = function(x) !x$isRoot && ( x$type != "else" || x$parent$count > 1) )
              ), 
        ", THEN (response = ", node$response, ") with ", node$obsCount, " obs"),
        collapse = ""
        )

}

stmt <- paste(responses$Get(GetStatement, filterFun = isLeaf), collapse = "\n")
cat(stmt)

responses.Rproj

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