In petedodd/HEdtree: A Package For Decision Tree Modelling

knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>"
)

knitr::include_graphics("figures/tree_diagram.png")

We can load in a tree structure as a text file.

library(HEdtree)

Dx <- txt2tree('inst/Dx.txt')

Dx

Treatment tree version.

library(data.tree)


# create new tree objects
Tx <- Node$new('treated')

Tx$AddChild('Dies')
Tx$AddChild('Survives')
Tx$Dies$p <- 'cfr.tx'
Tx$Survives$p <- '1-cfr.tx'

print(Tx, "p")

No treatment tree version.

noTx <- Node$new('untreated')
noTx$AddChild('Dies')
noTx$AddChild('Survives')
noTx$Dies$p <- 'cfr.notx'
noTx$Survives$p <- '1-cfr.notx'

print(noTx, "p")

Combine the base tree and the subtrees.

## merge on outcomes
MergeByName(rootnode = Dx, nodetoadd = Tx, nodename = 'Confirmatory test positive')
MergeByName(rootnode = Dx, nodetoadd = noTx, nodename = 'Negative')

print(Dx,'p')

## example of setting by grep:
## check
Dx$Set(check=1)
Dx$Set(check=0, filterFun=function(x) length(x$children)>0)

## deaths
Dx$Set(deaths=0)
Dx$Set(deaths=1, filterFun=function(x) (x$name=='Dies'))

print(Dx,'deaths','check')

Example of using CSV I/O to set labels.

# tree2file(Dx,
#           filename = here::here('inst/Dx0.csv'),
#           'p','check','deaths','treatments')

## read in and set labels
CD <- read.csv(here::here('inst/Dx1.csv')) #the edited version

## want to do automatically
## LabelFromData <- function(tree,data){
##   ## TODO
## }

Dx$Set(p=CD$p)
Dx$Set(treatments=CD$treatments)

print(Dx,'p','treatments','deaths')

## make tree functions
qnts <- c('p','check','deaths','treatments')
tree_fns <- makeTfuns(Dx, qnt=qnts)
str(tree_fns)

$$ c_0 + p_{screen} (c_{screen} + p_{test} (c_{test} + CFR_{Tx} c_{CFR} + (1 - CFR_{Tx})c_{nCFR})) \cdots $$

## quantity example
getAQ(Dx, 'deaths')

## get the variables
(pmz <- showAllParmz(Dx))

##TODO: wheres this function?
## make test data
# test <- makeTestData(100,pmz)
# head(test)
# 
# tree_fns$checkfun(test)

dat <-
 data.frame(
   p.screen = 1,
   p.test = 1,
   cfr.tx = 1,
   cfr.notx = 1)

tree_fns[[1]](dat)

## run all
test <- appendResults(dat, tree_fns)
head(test)