Package 'data.tree'

Title: General Purpose Hierarchical Data Structure
Description: Create tree structures from hierarchical data, and traverse the tree in various orders. Aggregate, cumulate, print, plot, convert to and from data.frame and more. Useful for decision trees, machine learning, finance, conversion from and to JSON, and many other applications.
Authors: Russ Hyde [ctb] (improve dependencies), Chris Hammill [ctb] (improve getting), Facundo Munoz [ctb] (improve list conversion), Markus Wamser [ctb] (fixed some typos), Pierre Formont [ctb] (additional features), Kent Russel [ctb] (documentation), Noam Ross [ctb] (fixes), Duncan Garmonsway [ctb] (fixes), Christoph Glur [aut, cre] (R interface)
Maintainer: Christoph Glur <[email protected]>
License: GPL (>= 2)
Version: 1.1.0
Built: 2024-07-09 05:49:21 UTC
Source: CRAN

Help Index

Sample Data: A Simple Company with Departments

Description

acme's tree representation is accessed through its root, acme.

Usage

data(acme)

Format

A data.tree root Node

Details

  • cost, only available for leaf nodes. Cost of the project.

  • p probability that a project will be undertaken.

Aggregate child values of a Node, recursively.

Description

The Aggregate method lets you fetch an attribute from a Node's children, and then aggregate them using aggFun. For example, you can aggregate cost by summing costs of child Nodes. This is especially useful in the context of tree traversal, when using post-order traversal mode.

Usage

Aggregate(node, attribute, aggFun, ...)

Arguments

node

the Node on which to aggregate
attribute

determines what is collected. The attribute can be

  • a.) the name of a field or a property/active of each Node in the tree, e.g. acme$Get("p") or acme$Get("position")

  • b.) the name of a method of each Node in the tree, e.g. acme$Get("levelZeroBased"), where e.g. acme$levelZeroBased <- function() acme$level - 1

  • c.) a function, whose first argument must be a Node e.g. acme$Get(function(node) node$cost * node$p)

aggFun

the aggregation function to be applied to the children's attributes
...

any arguments to be passed on to attribute (in case it's a function)

Details

As with Get, the attribute can be a field, a method or a function. If the attribute on a child is NULL, Aggregate is called recursively on its children.

See Also

Node

Examples

data(acme)

#Aggregate on a field
Aggregate(acme, "cost", sum)

#This is the same as:
HomeRolledAggregate <- function(node) {
  sum(sapply(node$children, function(child) {
    if (!is.null(child$cost)) child$cost
    else HomeRolledAggregate(child)
  }))
}
HomeRolledAggregate(acme)

#Aggregate using Get
print(acme, "cost", minCost = acme$Get(Aggregate, "cost", min))

#use Aggregate with a function:
Aggregate(acme, function(x) x$cost * x$p, sum)

#cache values along the way
acme$Do(function(x) x$cost <- Aggregate(x, "cost", sum), traversal = "post-order")
acme$IT$cost

Test whether all node names are unique.

Description

This can be useful for some conversions.

Usage

AreNamesUnique(node)

Arguments

node

The root Node of the data.tree structure to test

Value

TRUE if all Node$name == TRUE for all nodes in the tree

See Also

as.igraph.Node

Examples

data(acme)
AreNamesUnique(acme)
acme$name <- "IT"
AreNamesUnique(acme)

Convert a data.tree structure to a data.frame

Description

If a node field contains data of length > 1, then that is converted into a string in the data.frame.

Usage

## S3 method for class 'Node'
as.data.frame(
  x,
  row.names = NULL,
  optional = FALSE,
  ...,
  traversal = c("pre-order", "post-order", "in-order", "level", "ancestor"),
  pruneFun = NULL,
  filterFun = NULL,
  format = FALSE,
  inheritFromAncestors = FALSE
)

ToDataFrameTree(x, ..., pruneFun = NULL)

ToDataFrameTable(x, ..., pruneFun = NULL)

ToDataFrameNetwork(
  x,
  ...,
  direction = c("climb", "descend"),
  pruneFun = NULL,
  format = FALSE,
  inheritFromAncestors = FALSE
)

ToDataFrameTypeCol(x, ..., type = "level", prefix = type, pruneFun = NULL)

Arguments

x

The root Node of the tree or sub-tree to be convert to a data.frame
row.names

NULL or a character vector giving the row names for the data frame. Missing values are not allowed.
optional

logical. If TRUE, setting row names and converting column names (to syntactic names: see make.names) is optional.
...

the attributes to be added as columns of the data.frame. See Get for details. If a specific Node does not contain the attribute, NA is added to the data.frame.
traversal

any of 'pre-order' (the default), 'post-order', 'in-order', 'level', or 'ancestor'. See Traverse for details.
pruneFun

allows providing a prune criteria, i.e. a function taking a Node as an input, and returning TRUE or FALSE. If the pruneFun returns FALSE for a Node, then the Node and its entire sub-tree will not be considered.
filterFun

a function taking a Node as an argument. See Traverse for details.
format

if FALSE (the default), then no formatting will be applied. If TRUE, then the first formatter (if any) along the ancestor path is used for formatting.
inheritFromAncestors

if FALSE, and if the attribute is a field or a method, then only a Node itself is searched for the field/method. If TRUE, and if the Node does not contain the attribute, then ancestors are also searched.
direction

when converting to a network, should the edges point from root to children ("climb") or from child to parent ("descend")?
type

when converting type columns, the type is the discriminator, i.e. an attribute (e.g. field name) of each node
prefix

when converting type columns, the prefix used for the column names. Can be NULL to omit prefixes.

Value

ToDataFrameTree: a data.frame, where each row represents a Node in the tree or sub-tree spanned by x, possibly pruned according to pruneFun.

ToDataFrameTable: a data.frame, where each row represents a leaf Node in the tree or sub-tree spanned by x, possibly pruned according to pruneFun.

ToDataFrameNetwork: a data.frame, where each row represents a Node in the tree or sub-tree spanned by x, possibly pruned according to pruneFun. The first column is called 'from', while the second is called 'to', describing the parent to child edge (for direction "climb") or the child to parent edge (for direction "descend"). If AreNamesUnique is TRUE, then the Network is based on the Node$name, otherwise on the Node$pathString

ToDataFrameTypeCol: a data.frame in table format (i.e. where each row represents a leaf in the tree or sub-tree spanned by x), possibly pruned according to pruneFun. In addition to ..., each distinct type is output to a column.

Examples

data(acme)
acme$attributesAll
as.data.frame(acme, row.names = NULL, optional = FALSE, "cost", "p")

ToDataFrameTree(acme, "cost", "p")
ToDataFrameNetwork(acme, "cost", "p", direction = "climb")
ToDataFrameTable(acme, "cost", "p")
ToDataFrameTypeCol(acme)

#use the pruneFun:
acme$Do(function(x) x$totalCost <- Aggregate(x, "cost", sum), traversal = "post-order")
ToDataFrameTree(acme, "totalCost", pruneFun = function(x) x$totalCost > 300000)

#inherit
acme$Set(floor = c(1, 2, 3), filterFun = function(x) x$level == 2)
as.data.frame(acme, row.names = NULL, optional = FALSE, "floor", inheritFromAncestors = FALSE)
as.data.frame(acme, row.names = NULL, optional = FALSE, "floor", inheritFromAncestors = TRUE)

#using a function as an attribute:
acme$Accounting$Head <- "Mrs. Numright"
acme$Research$Head <- "Mr. Stein"
acme$IT$Head <- "Mr. Squarehead"
ToDataFrameTable(acme, department = function(x) x$parent$name, "name", "Head", "cost")

#complex TypeCol
acme$IT$Outsource$AddChild("India")
acme$IT$Outsource$AddChild("Poland")
acme$Set(type = c('company', 'department', 'project', 'project', 'department',
                  'project', 'project', 'department', 'program', 'project',
                  'project', 'project', 'project'
                  )
        )
print(acme, 'type')
ToDataFrameTypeCol(acme, type = 'type')

Convert a Node to a dendrogram

Description

Convert a data.tree structure to a dendrogram

Usage

## S3 method for class 'Node'
as.dendrogram(
  object,
  heightAttribute = DefaultPlotHeight,
  edgetext = FALSE,
  ...
)

Arguments

object

The Node to convert
heightAttribute

The attribute (field name or function) storing the height
edgetext

If TRUE, then the for non-leaf nodes the node name is stored as the dendrogram's edge text.
...

Additional parameters

Value

An object of class dendrogram

See Also

Other Conversions from Node: ToNewick()

Examples

data(acme)
acmed <- as.dendrogram(acme)
plot(acmed, center = TRUE)

#you can take an attribute for the height:
acme$Do( function(x) x$myPlotHeight <- (10 - x$level))
acmed <- as.dendrogram(acme, heightAttribute = "myPlotHeight")
plot(acmed, center = TRUE)

#or directly a function
acmed <- as.dendrogram(acme, heightAttribute = function(x) 10 - x$level)
plot(acmed)

Convert a data.tree structure to an igraph network

Description

This requires the igraph package to be installed. Also, this requires the names of the Nodes to be unique within the data.tree structure.

Usage

as.igraph.Node(
  x,
  vertexAttributes = character(),
  edgeAttributes = character(),
  directed = FALSE,
  direction = c("climb", "descend"),
  ...
)

Arguments

x

The root Node to convert
vertexAttributes

A vector of strings, representing the attributes in the data.tree structure to add as attributes to the vertices of the igraph
edgeAttributes

A vector of strings, representing the attributes in the data.tree structure to add as edge attributes of the igraph
directed

Logical scalar, whether or not to create a directed graph.
direction

when converting to a network, should the edges point from root to children ("climb") or from child to parent ("descend")?
...

Currently unused.

Value

an igraph object

See Also

AreNamesUnique

Examples

data(acme)
library(igraph)
ig <- as.igraph(acme, "p", c("level", "isLeaf"))
plot(ig)

Convert a data.tree structure to a list-of-list structure

Description

Convert a data.tree structure to a list-of-list structure

Usage

## S3 method for class 'Node'
as.list(
  x,
  mode = c("simple", "explicit"),
  unname = FALSE,
  nameName = ifelse(unname, "name", ""),
  childrenName = "children",
  rootName = "",
  keepOnly = NULL,
  pruneFun = NULL,
  ...
)

ToListSimple(x, nameName = "name", pruneFun = NULL, ...)

ToListExplicit(
  x,
  unname = FALSE,
  nameName = ifelse(unname, "name", ""),
  childrenName = "children",
  pruneFun = NULL,
  ...
)

Arguments

x

The Node to convert
mode

How the list is structured. "simple" (the default) will add children directly as nested lists. "explicit" puts children in a separate nested list called childrenName
unname

If TRUE, and if mode is "explicit", then the nested children list will not have named arguments. This can be useful e.g. in the context of conversion to JSON, if you prefer the children to be an array rather than named objects.
nameName

The name that should be given to the name element
childrenName

The name that should be given to the children nested list
rootName

The name of the node. If provided, this overrides Node$name
keepOnly

A character vector of attributes to include in the result. If NULL (the default), all attributes are kept.
pruneFun

allows providing a prune criteria, i.e. a function taking a Node as an input, and returning TRUE or FALSE. If the pruneFun returns FALSE for a Node, then the Node and its entire sub-tree will not be considered.
...

Additional parameters passed to as.list.Node

Examples

data(acme)

str(ToListSimple(acme))
str(ToListSimple(acme, keepOnly = "cost"))

str(ToListExplicit(acme))
str(ToListExplicit(acme, unname = TRUE))
str(ToListExplicit(acme, unname = TRUE, nameName = "id", childrenName = "descendants"))

Convert an object to a data.tree data structure

Description

Convert an object to a data.tree data structure

Usage

as.Node(x, ...)

Arguments

x

The object to be converted
...

Additional arguments

See Also

Other as.Node: as.Node.data.frame(), as.Node.dendrogram(), as.Node.list(), as.Node.phylo(), as.Node.rpart()

Convert a a SplitNode from the party package to a data.tree structure.

Description

Convert a a SplitNode from the party package to a data.tree structure.

Usage

## S3 method for class 'BinaryTree'
as.Node(x, ...)

Arguments

x

The BinaryTree
...

additional arguments (unused)

Examples

library(party)
airq <- subset(airquality, !is.na(Ozone))
airct <- ctree(Ozone ~ ., data = airq, 
               controls = ctree_control(maxsurrogate = 3))
               
tree <- as.Node(airct)
tree

print(tree, 
      "label", 
      criterion = function(x) round(x$criterion$maxcriterion, 3),
      statistic = function(x) round(max(x$criterion$statistic), 3)
      )

FindNode(tree, 6)$path

Convert a data.frame to a data.tree structure

Description

Convert a data.frame to a data.tree structure

Usage

## S3 method for class 'data.frame'
as.Node(
  x,
  ...,
  mode = c("table", "network"),
  pathName = "pathString",
  pathDelimiter = "/",
  colLevels = NULL,
  na.rm = TRUE
)

FromDataFrameTable(
  table,
  pathName = "pathString",
  pathDelimiter = "/",
  colLevels = NULL,
  na.rm = TRUE,
  check = c("check", "no-warn", "no-check")
)

FromDataFrameNetwork(network, check = c("check", "no-warn", "no-check"))

Arguments

x

The data.frame in the required format.
...

Any other argument implementations of this might need
mode

Either "table" (if x is a data.frame in tree or table format) or "network"
pathName

The name of the column in x containing the path of the row
pathDelimiter

The delimiter used to separate nodes in pathName
colLevels

Nested list of column names, determining on what node levels the attributes are written to.
na.rm

If TRUE, then NA's are treated as NULL and values will not be set on nodes
table

a data.frame in table or tree format, i.e. having a row for each leaf (and optionally for additional nodes). There should be a column called pathName, separated by pathDelimiter, describing the path of each row.
check

Either

  • "check": if the name conformance should be checked and warnings should be printed in case of non-conformance (the default)

  • "no-warn": if the name conformance should be checked, but no warnings should be printed in case of non-conformance (if you expect non-conformance)

  • "no-check" or FALSE: if the name conformance should not be checked; use this if performance is critical. However, in case of non-conformance, expect cryptic follow-up errors

network

A data.frame in network format, i.e. it must adhere to the following requirements:

  • It must contain as many rows as there are nodes (excluding the root, there is no row for the root)

  • Its first and second columns contain the network relationships. This can be either climbing (from parent to children) or descending (from child to parent)

  • Its subsequent columns contain the attributes to be set on the nodes

  • It must contain a single root

  • There are no cycles in the network

Value

The root Node of the data.tree structure

See Also

as.data.frame.Node

Other as.Node: as.Node.dendrogram(), as.Node.list(), as.Node.phylo(), as.Node.rpart(), as.Node()

Examples

data(acme)

#Tree
x <- ToDataFrameTree(acme, "pathString", "p", "cost")
x
xN <- as.Node(x)
print(xN, "p", "cost")

#Table
x <- ToDataFrameTable(acme, "pathString", "p", "cost")
x
xN <- FromDataFrameTable(x)
print(xN, "p", "cost")

#More complex Table structure, using colLevels
acme$Set(floor = c(1, 2, 3),  filterFun = function(x) x$level == 2)
x <- ToDataFrameTable(acme, "pathString", "floor", "p", "cost")
x
xN <- FromDataFrameTable(x, colLevels = list(NULL, "floor", c("p", "cost")), na.rm = TRUE)
print(xN, "floor", "p", "cost")

#Network
x <- ToDataFrameNetwork(acme, "p", "cost", direction = "climb")
x
xN <- FromDataFrameNetwork(x)
print(xN, "p", "cost")

Convert a dendrogram to a data.tree Node

Description

Convert a dendrogram to a data.tree Node

Usage

## S3 method for class 'dendrogram'
as.Node(
  x,
  name = "Root",
  heightName = "plotHeight",
  check = c("check", "no-warn", "no-check"),
  ...
)

Arguments

x

The dendrogram
name

The name of the root Node
heightName

The name under which the dendrogram's height is stored
check

Either

  • "check": if the name conformance should be checked and warnings should be printed in case of non-conformance (the default)

  • "no-warn": if the name conformance should be checked, but no warnings should be printed in case of non-conformance (if you expect non-conformance)

  • "no-check" or FALSE: if the name conformance should not be checked; use this if performance is critical. However, in case of non-conformance, expect cryptic follow-up errors

...

Additional parameters

Value

The root Node of a data.tree

See Also

Other as.Node: as.Node.data.frame(), as.Node.list(), as.Node.phylo(), as.Node.rpart(), as.Node()

Examples

hc <- hclust(dist(USArrests), "ave")
dend1 <- as.dendrogram(hc)
tree1 <- as.Node(dend1)
tree1$attributesAll
tree1$totalCount
tree1$leafCount
tree1$height

Convert a nested list structure to a data.tree structure

Description

Convert a nested list structure to a data.tree structure

Usage

## S3 method for class 'list'
as.Node(
  x,
  mode = c("simple", "explicit"),
  nameName = "name",
  childrenName = "children",
  nodeName = NULL,
  interpretNullAsList = FALSE,
  check = c("check", "no-warn", "no-check"),
  ...
)

FromListExplicit(
  explicitList,
  nameName = "name",
  childrenName = "children",
  nodeName = NULL,
  check = c("check", "no-warn", "no-check")
)

FromListSimple(
  simpleList,
  nameName = "name",
  nodeName = NULL,
  interpretNullAsList = FALSE,
  check = c("check", "no-warn", "no-check")
)

Arguments

x

The list to be converted.
mode

How the list is structured. "simple" (the default) will interpret any list to be a child. "explicit" assumes that children are in a nested list called childrenName
nameName

The name of the element in the list that should be used as the name, can be NULL if mode = explicit and the children lists are named, or if an automatic name (running number) should be assigned
childrenName

The name of the element that contains the child list (applies to mode 'explicit' only).
nodeName

A name suggestion for x, if the name cannot be deferred otherwise. This is for example the case for the root with mode explicit and named lists.
interpretNullAsList

If TRUE, then NULL-valued lists are interpreted as child nodes. Else, they are interpreted as attributes. This has only an effect if mode is "simple".
check

Either

  • "check": if the name conformance should be checked and warnings should be printed in case of non-conformance (the default)

  • "no-warn": if the name conformance should be checked, but no warnings should be printed in case of non-conformance (if you expect non-conformance)

  • "no-check" or FALSE: if the name conformance should not be checked; use this if performance is critical. However, in case of non-conformance, expect cryptic follow-up errors

...

Any other argument to be passed to generic sub implementations
explicitList

A list in which children are in a separate nested list called childrenName.
simpleList

A list in which children are stored as nested list alongside other attributes. Any list is interpreted as a child Node

See Also

Other as.Node: as.Node.data.frame(), as.Node.dendrogram(), as.Node.phylo(), as.Node.rpart(), as.Node()

Examples

kingJosephs <- list(name = "Joseph I",
                    spouse = "Mary",
                    born = "1818-02-23",
                    died = "1839-08-29",
                    children = list(
                                    list(name = "Joseph II",
                                         spouse = "Kathryn",
                                         born = "1839-03-28",
                                         died = "1865-12-19"),
                                    list(name = "Helen",
                                         born = "1840-17-08",
                                         died = "1845-01-01")
                                    )
                   )
FromListExplicit(kingJosephs)

kingJosephs <- list(head = "Joseph I",
                    spouse = "Mary",
                    born = "1818-02-23",
                    died = "1839-08-29",
                    list(head = "Joseph II",
                         spouse = "Kathryn",
                         born = "1839-03-28",
                         died = "1865-12-19"),
                    list(head = "Helen",
                         born = "1840-17-08",
                         died = "1845-01-01")       
                   )
FromListSimple(kingJosephs, nameName = "head")

kingJosephs <- list(spouse = "Mary",
                    born = "1818-02-23",
                    died = "1839-08-29",
                    `Joseph II` = list(spouse = "Kathryn",
                                       born = "1839-03-28",
                                       died = "1865-12-19"),
                    Helen = list(born = "1840-17-08",
                                 died = "1845-01-01")
                                 
                   )
FromListSimple(kingJosephs, nodeName = "Joseph I")

Convert a a party from the partykit package to a data.tree structure.

Description

Convert a a party from the partykit package to a data.tree structure.

Usage

## S3 method for class 'party'
as.Node(x, ...)

Arguments

x

The party object
...

other arguments (unused)

Examples

library(partykit)
data("WeatherPlay", package = "partykit")
### splits ###
# split in overcast, humidity, and windy
sp_o <- partysplit(1L, index = 1:3)
sp_h <- partysplit(3L, breaks = 75)
sp_w <- partysplit(4L, index = 1:2)

## query labels
character_split(sp_o)

### nodes ###
## set up partynode structure
pn <- partynode(1L, split = sp_o, kids = list(
  partynode(2L, split = sp_h, kids = list(
      partynode(3L, info = "yes"),
      partynode(4L, info = "no"))),
  partynode(5L, info = "yes"),
  partynode(6L, split = sp_w, kids = list(
      partynode(7L, info = "yes"),
      partynode(8L, info = "no")))))
pn
### tree ###
## party: associate recursive partynode structure with data
py <- party(pn, WeatherPlay)
tree <- as.Node(py)

print(tree, 
      "splitname",
      count = function(node) nrow(node$data), 
      "splitLevel")

SetNodeStyle(tree, 
             label = function(node) paste0(node$name, ": ", node$splitname), 
             tooltip = function(node) paste0(nrow(node$data), " observations"),
             fontname = "helvetica")
SetEdgeStyle(tree, 
             arrowhead = "none", 
             label = function(node) node$splitLevel,
             fontname = "helvetica",
             penwidth = function(node) 12 * nrow(node$data)/nrow(node$root$data),
             color = function(node) {
               paste0("grey", 
                      100 - as.integer( 100 * nrow(node$data)/nrow(node$root$data))
                      )
             }
             )
Do(tree$leaves, 
   function(node) {
     SetNodeStyle(node, 
                  shape = "box", 
                  color = ifelse(node$splitname == "yes", "darkolivegreen4", "lightsalmon4"),
                  fillcolor = ifelse(node$splitname == "yes", "darkolivegreen1", "lightsalmon"),
                  style = "filled,rounded",
                  penwidth = 2
                  )
   }
   )

plot(tree)

Convert a phylo object from the ape package to a Node

Description

Convert a phylo object from the ape package to a Node

Usage

## S3 method for class 'phylo'
as.Node(
  x,
  heightName = "plotHeight",
  replaceUnderscores = TRUE,
  namesNotUnique = FALSE,
  ...
)

Arguments

x

The phylo object to be converted
heightName

If the phylo contains edge lengths, then they will be converted to a height and stored in a field named according to this parameter (the default is "height")
replaceUnderscores

if TRUE (the default), then underscores in names are replaced with spaces
namesNotUnique

if TRUE, then the name of the Nodes will be prefixed with a unique id. This is useful if the children of a parent have non-unique names.
...

any other parameter to be passed to sub-implementations

See Also

Other ape phylo conversions: GetPhyloNr(), as.phylo.Node()

Other as.Node: as.Node.data.frame(), as.Node.dendrogram(), as.Node.list(), as.Node.rpart(), as.Node()

Examples

#which bird familes have the max height?
library(ape)
data(bird.families)
bf <- as.Node(bird.families)
height <- bf$height
t <- Traverse(bf, filterFun = function(x) x$level == 25)
Get(t, "name")

Convert an rpart object to a data.tree structure

Description

Convert an rpart object to a data.tree structure

Usage

## S3 method for class 'rpart'
as.Node(x, digits = getOption("digits") - 3, use.n = FALSE, ...)

Arguments

x

the rpart object to be converted
digits

the number of digits to be used for numeric values in labels
use.n

logical. Add cases to labels, see text.rpart for further information
...

any other argument to be passed to generic sub implementations

Value

a data.tree object. The tree contains a field rpart.id which references back to the original node id in the row names of the rpart object.

See Also

Other as.Node: as.Node.data.frame(), as.Node.dendrogram(), as.Node.list(), as.Node.phylo(), as.Node()

Examples

if (require(rpart)) {
   fit <- rpart(Kyphosis ~ Age + Number + Start, data = kyphosis)
   as.Node(fit)
}

Convert a Node to a phylo object from the ape package.

Description

This method requires the ape package to be installed and loaded.

Usage

as.phylo.Node(x, heightAttribute = DefaultPlotHeight, ...)

Arguments

x

The root Node of the tree or sub-tree to be converted
heightAttribute

The attribute (field name or function) storing the height
...

any other argument

See Also

Other ape phylo conversions: GetPhyloNr(), as.Node.phylo()

Examples

library(ape)
data(acme)
acmephylo <- as.phylo(acme)
#plot(acmephylo)

Calculate the average number of branches each non-leaf has

Description

Calculate the average number of branches each non-leaf has

Usage

averageBranchingFactor(node)

Arguments

node

The node to calculate the average branching factor for

Checks whether name is a reserved word, as defined in NODE_RESERVED_NAMES_CONST.

Description

Checks whether name is a reserved word, as defined in NODE_RESERVED_NAMES_CONST.

Usage

CheckNameReservedWord(name, check = c("check", "no-warn", "no-check"))

Arguments

name

the name to check
check

Either

  • "check": if the name conformance should be checked and warnings should be printed in case of non-conformance (the default)

  • "no-warn": if the name conformance should be checked, but no warnings should be printed in case of non-conformance (if you expect non-conformance)

  • "no-check" or FALSE: if the name conformance should not be checked; use this if performance is critical. However, in case of non-conformance, expect cryptic follow-up errors

Climb a tree from parent to children, by provided criteria.

Description

This method lets you climb the tree, from crutch to crutch. On each Node, the Climb finds the first child having attribute value equal to the the provided argument.

Usage

#node$Climb(...)
Climb(node, ...)

Arguments

node

The root Node of the tree or subtree to climb
...

an attribute-value pairlist to be searched. For brevity, you can also provide a character vector to search for names.

Value

the Node having path ..., or NULL if such a path does not exist

See Also

Node

Navigate

Examples

data(acme)

#the following are all equivalent
Climb(acme, 'IT', 'Outsource')
Climb(acme, name = 'IT', name = 'Outsource')
Climb(acme, 'IT')$Climb('Outsource')
Navigate(acme, path = "IT/Outsource")

Climb(acme, name = 'IT')

Climb(acme, position = c(2, 1))
#or, equivalent:
Climb(acme, position = 2, position = 1)
Climb(acme, name = "IT", cost = 250000)

tree <- CreateRegularTree(5, 2)
tree$Climb(c("1", "1"), position = c(2, 2))$path

Clone a tree (creates a deep copy)

Description

The method also clones object attributes (such as the formatters), if desired. If the method is called on a non-root, then the parent relationship is not cloned, and the resulting Node will be a root.

Usage

Clone(node, pruneFun = NULL, attributes = FALSE)

Arguments

node

the root node of the tree or sub-tree to clone
pruneFun

allows providing a prune criteria, i.e. a function taking a Node as an input, and returning TRUE or FALSE. If the pruneFun returns FALSE for a Node, then the Node and its entire sub-tree will not be considered.
attributes

if FALSE, then R class attributes (e.g. formatters and grViz styles) are not cloned. This makes the method faster.

Value

the clone of the tree or sub-tree

See Also

SetFormat

Examples

data(acme)
acmeClone <- Clone(acme)
acmeClone$name <- "New Acme"
# acmeClone does not point to the same reference object anymore:
acme$name

#cloning a subtree
data(acme)
itClone <- Clone(acme$IT)
itClone$isRoot

Create a tree for demo and testing

Description

Create a tree for demo and testing

Usage

CreateRandomTree(nodes = 100, root = Node$new("1"), id = 1)

Arguments

nodes

The number of nodes to create
root

the previous node (for recursion, typically use default value)
id

The id (for recursion)

Create a tree for demo and testing

Description

Create a tree for demo and testing

Usage

CreateRegularTree(height = 5, branchingFactor = 3, parent = Node$new("1"))

Arguments

height

the number of levels
branchingFactor

the number of children per node
parent

the parent node (for recursion)

Cumulate values among siblings

Description

For example, you can sum up values of siblings before this Node.

Usage

Cumulate(node, attribute, aggFun, ...)

Arguments

node

The node on which we want to cumulate
attribute

determines what is collected. The attribute can be

  • a.) the name of a field or a property/active of each Node in the tree, e.g. acme$Get("p") or acme$Get("position")

  • b.) the name of a method of each Node in the tree, e.g. acme$Get("levelZeroBased"), where e.g. acme$levelZeroBased <- function() acme$level - 1

  • c.) a function, whose first argument must be a Node e.g. acme$Get(function(node) node$cost * node$p)

aggFun

the aggregation function to be applied to the children's attributes
...

any arguments to be passed on to attribute (in case it's a function)

Examples

data(acme)
acme$Do(function(x) x$cost <- Aggregate(x, "cost", sum), traversal = "post-order")
acme$Do(function(x) x$cumCost <- Cumulate(x, "cost", sum))
print(acme, "cost", "cumCost")

Calculates the height of a Node given the height of the root.

Description

This function puts leafs at the bottom (not hanging), and makes edges equally long. Useful for easy plotting with third-party packages, e.g. if you have no specific height attribute, e.g. with as.dendrogram.Node, ToNewick, and as.phylo.Node

Usage

DefaultPlotHeight(node, rootHeight = 100)

Arguments

node

The node
rootHeight

The height of the root

Examples

data(acme)
dacme <- as.dendrogram(acme, heightAttribute = function(x) DefaultPlotHeight(x, 200))
plot(dacme, center = TRUE)

Find the distance between two nodes of the same tree

Description

The distance is measured as the number of edges that need to be traversed to reach node2 when starting from node1.

Usage

Distance(node1, node2)

Arguments

node1

the first node in the tree
node2

the second node in the same tree

Examples

data(acme)
Distance(FindNode(acme, "Outsource"), FindNode(acme, "Research"))

Executes a function on a set of nodes

Description

Executes a function on a set of nodes

Usage

# OO-style:
# node$Do(fun, 
#         ..., 
#         traversal = c("pre-order", "post-order", "in-order", "level", "ancestor"), 
#         pruneFun = NULL, 
#         filterFun = NULL)
         
# traditional:
Do(nodes, fun, ...)

Arguments

nodes

The nodes on which to perform the Get (typically obtained via Traverse)
fun

the function to execute. The function is expected to be either a Method, or to take a Node as its first argument
...

any additional parameters to be passed on to fun

See Also

Node

Get

Set

Traverse

Examples

data(acme)
traversal <- Traverse(acme)
Do(traversal, function(node) node$expectedCost <- node$p * node$cost)
print(acme, "expectedCost")

Find a node by name in the (sub-)tree

Description

Scans the entire sub-tree spanned by node and returns the first Node having the name specified. This is mainly useful for trees whose name is unique. If AreNamesUnique is FALSE, i.e. if there is more than one Node called name in the tree, then it is undefined which one will be returned. Also note that this method is not particularly fast. See examples for a faster way to index large trees, if you need to do multiple searches. See Traverse if you need to find multiple Nodes.

Usage

FindNode(node, name)

Arguments

node

The root Node of the tree or sub-tree to search
name

The name of the Node to be returned

Value

The first Node whose name matches, or NULL if no such Node is found.

See Also

AreNamesUnique, Traverse

Examples

data(acme)
FindNode(acme, "Outsource")

#re-usable hashed index for multiple searches:
if(!AreNamesUnique(acme)) stop("Hashed index works for unique names only!")
trav <- Traverse(acme, "level")
names(trav) <- Get(trav, "name")
nameIndex <- as.environment(trav)
#you could also use hash from package hash instead!
#nameIndex <- hash(trav)
nameIndex$Outsource
nameIndex$IT

Format a Number as a Decimal

Description

Simple function that can be used as a format function when converting trees to a data.frame

Usage

FormatFixedDecimal(x, digits = 3)

Arguments

x

a numeric scalar or vector
digits

the number of digits to print after the decimal point

Value

A string corresponding to x, suitable for printing

Examples

data(acme)
print(acme, prob = acme$Get("p", format = function(x) FormatFixedDecimal(x, 4)))

Format a Number as a Percentage

Description

This utility method can be used as a format function when converting trees to a data.frame

Usage

FormatPercent(x, digits = 2, format = "f", ...)

Arguments

x

A number
digits

The number of digits to print
format

The format to use
...

Any other argument passed to formatC

Value

A string corresponding to x, suitable for printing

See Also

formatC

Examples

data(acme)
print(acme, prob = acme$Get("p", format = FormatPercent))

Traverse a Tree and Collect Values

Description

The Get method is one of the most important ones of the data.tree package. It lets you traverse a tree and collect values along the way. Alternatively, you can call a method or a function on each Node.

Usage

# OO-style:
#node$Get(attribute, 
#        ..., 
#        traversal = c("pre-order", "post-order", "in-order", "level", "ancestor"), 
#        pruneFun = NULL, 
#        filterFun = NULL, 
#        format = FALSE, 
#        inheritFromAncestors = FALSE)
         
# traditional:
Get(nodes, 
    attribute, 
    ..., 
    format = FALSE, 
    inheritFromAncestors = FALSE, 
    simplify = c(TRUE, FALSE, "array", "regular"))

Arguments

nodes

The nodes on which to perform the Get (typically obtained via Traverse)
attribute

determines what is collected. The attribute can be

  • a.) the name of a field or a property/active of each Node in the tree, e.g. acme$Get("p") or acme$Get("position")

  • b.) the name of a method of each Node in the tree, e.g. acme$Get("levelZeroBased"), where e.g. acme$levelZeroBased <- function() acme$level - 1

  • c.) a function, whose first argument must be a Node e.g. acme$Get(function(node) node$cost * node$p)

...

in case the attribute is a function or a method, the ellipsis is passed to it as additional arguments.
format

if FALSE (the default), no formatting is being used. If TRUE, then the first formatter (if any) found along the ancestor path is being used for formatting (see SetFormat). If format is a function, then the collected value is passed to that function, and the result is returned.
inheritFromAncestors

if TRUE, then the path above a Node is searched to get the attribute in case it is NULL.
simplify

same as sapply, i.e. TRUE, FALSE or "array". Additionally, you can specify "regular" if each returned value is of length > 1, and equally named. See below for an example.

Value

a vector containing the atrributes collected during traversal, in traversal order. NULL is converted to NA, such that length(Node$Get) == Node$totalCount

See Also

Node

Set

Do

Traverse

Examples

data(acme)
acme$Get("level")
acme$Get("totalCount")
 

acme$Get(function(node) node$cost * node$p,
         filterFun = isLeaf)

#This is equivalent:
nodes <- Traverse(acme, filterFun = isLeaf)
Get(nodes, function(node) node$cost * node$p)

   
#simplify = "regular" will preserve names
acme$Get(function(x) c(position = x$position, level = x$level), simplify = "regular")

Get an attribute from a Node.

Description

Get an attribute from a Node.

Usage

GetAttribute(
  node,
  attribute,
  ...,
  format = FALSE,
  inheritFromAncestors = FALSE,
  nullAsNa = TRUE
)

Arguments

node

The Node from which the attribute should be fetched.
attribute

determines what is collected. The attribute can be

  • a.) the name of a field or a property/active of each Node in the tree, e.g. acme$Get("p") or acme$Get("position")

  • b.) the name of a method of each Node in the tree, e.g. acme$Get("levelZeroBased"), where e.g. acme$levelZeroBased <- function() acme$level - 1

  • c.) a function, whose first argument must be a Node e.g. acme$Get(function(node) node$cost * node$p)

...

in case the attribute is a function or a method, the ellipsis is passed to it as additional arguments.
format

if FALSE (the default), no formatting is being used. If TRUE, then the first formatter (if any) found along the ancestor path is being used for formatting (see SetFormat). If format is a function, then the collected value is passed to that function, and the result is returned.
inheritFromAncestors

if TRUE, then the path above a Node is searched to get the attribute in case it is NULL.
nullAsNa

If TRUE (the default), then NULL is returned as NA. Otherwise it is returned as NULL.

Examples

data(acme)
GetAttribute(acme$IT$Outsource, "cost")

Determine the number a Node has after conversion to a phylo object

Description

Use this function when plotting a Node as a phylo, e.g. to set custom labels to plot.

Usage

GetPhyloNr(x, type = c("node", "edge"))

Arguments

x

The Node
type

Either "node" (the default) or "edge" (to get the number of the edge from x to its parent)

Value

an integer representing the node

See Also

Other ape phylo conversions: as.Node.phylo(), as.phylo.Node()

Examples

library(ape)
library(data.tree)
data(acme)
ap <- as.phylo(acme)
#plot(ap)
#nodelabels("IT Dep.", GetPhyloNr(Climb(acme, "IT")))
#edgelabels("Good!", GetPhyloNr(Climb(acme, "IT", "Switch to R"), "edge"))

Check if a Node is a leaf

Description

Check if a Node is a leaf

Usage

isLeaf(node)

Arguments

node

The Node to test.

Value

TRUE if the Node is a leaf, FALSE otherwise

Check if a Node is not a leaf

Description

Check if a Node is not a leaf

Usage

isNotLeaf(node)

Arguments

node

The Node to test.

Value

FALSE if the Node is a leaf, TRUE otherwise

Check if a Node is not a root

Description

Check if a Node is not a root

Usage

isNotRoot(node)

Arguments

node

The Node to test.

Value

FALSE if the Node is the root, TRUE otherwise

Check if a Node is the root

Description

Check if a Node is the root

Usage

isRoot(node)

Arguments

node

The Node to test.

Value

TRUE if the Node is the root, FALSE otherwise

Sample Data: Data Used by the ID3 Vignette

Description

mushroom contains attributes of mushrooms. We can use this data to predict a mushroom's toxicity based on its attributes. The attributes available in the data set are:

Usage

data(mushroom)

Format

data.frame

Details

  • color the color of a mushroom

  • size whether a mushroom is small or large

  • points whether a mushroom has points

  • edibility whether a mushroom is edible or toxic

Navigate to another node by relative path.

Description

Navigate to another node by relative path.

Usage

Navigate(node, path)

Arguments

node

The starting Node to navigate
path

A string or a character vector describing the path to navigate

Details

The path is always relative to the node. Navigation to the parent is defined by .., whereas navigation to a child is defined via the child's name. If path is provided as a string, then the navigation steps are separated by '/'.

See Also

Climb

Examples

data(acme)
Navigate(acme$Research, "../IT/Outsource")
Navigate(acme$Research, c("..", "IT", "Outsource"))

Create a data.tree Structure With Nodes

Description

Node is at the very heart of the data.tree package. All trees are constructed by tying together Node objects.

Usage

# n1 <- Node$new("Node 1")

Format

An R6Class generator object

Details

Assemble Node objects into a data.tree structure and use the traversal methods to set, get, and perform operations on it. Typically, you construct larger tree structures by converting from data.frame, list, or other formats.

Most methods (e.g. node$Sort()) also have a functional form (e.g. Sort(node))

Active bindings

name

Gets or sets the name of a Node. For example Node$name <- "Acme".

printFormatters

gets or sets the formatters used to print a Node. Set this as a list to a root node. The different formatters are h (horizontal), v (vertical), l (L), j (junction), and s (separator). For example, you can set the formatters to list(h = "\u2500" , v = "\u2502", l = "\u2514", j = "\u251C", s = " ") to get a similar behavior as in fs::dir_tree(). The defaults are: list(h = "--" , v = "\u00A6", l = "\u00B0", j = "\u00A6", s = " ")

parent

Gets or sets the parent Node of a Node. Only set this if you know what you are doing, as you might mess up the tree structure!

children

Gets or sets the children list of a Node. Only set this if you know what you are doing, as you might mess up the tree structure!

isLeaf

Returns TRUE if the Node is a leaf, FALSE otherwise

isRoot

Returns TRUE if the Node is the root, FALSE otherwise

count

Returns the number of children of a Node

totalCount

Returns the total number of Nodes in the tree

path

Returns a vector of mode character containing the names of the Nodes in the path from the root to this Node

pathString

Returns a string representing the path to this Node, separated by backslash

position

The position of a Node within its siblings

fields

Will be deprecated, use attributes instead

fieldsAll

Will be deprecated, use attributesAll instead

attributes

The attributes defined on this specific node

attributesAll

The distinct union of attributes defined on all the nodes in the tree spanned by this Node

levelName

Returns the name of the Node, preceded by level times '*'. Useful for printing and not typically called by package users.

leaves

Returns a list containing all the leaf Nodes

leafCount

Returns the number of leaves are below a Node

level

Returns an integer representing the level of a Node. For example, the root has level 1.

height

Returns max(level) of any of the Nodes of the tree

isBinary

Returns TRUE if all Nodes in the tree (except the leaves) have count = 2

root

Returns the root of a Node in a tree.

siblings

Returns a list containing all the siblings of this Node

averageBranchingFactor

Returns the average number of crotches below this Node

Methods

Public methods

Method new()

Create a new Node object. This is often used to create the root of a tree when creating a tree programmatically.

Usage
Node$new(name, check = c("check", "no-warn", "no-check"), ...)
Arguments
name

the name of the node to be created

check

Either

  • "check": if the name conformance should be checked and warnings should be printed in case of non-conformance (the default)

  • "no-warn": if the name conformance should be checked, but no warnings should be printed in case of non-conformance (if you expect non-conformance)

  • "no-check" or FALSE: if the name conformance should not be checked; use this if performance is critical. However, in case of non-conformance, expect cryptic follow-up errors

...

A name-value mapping of node attributes

Returns

A new 'Node' object

Examples
node <- Node$new("mynode", x = 2, y = "value of y")
node$y

Method AddChild()

Creates a Node and adds it as the last sibling as a child to the Node on which this is called.

Usage
Node$AddChild(name, check = c("check", "no-warn", "no-check"), ...)
Arguments
name

the name of the node to be created

check

Either

  • "check": if the name conformance should be checked and warnings should be printed in case of non-conformance (the default)

  • "no-warn": if the name conformance should be checked, but no warnings should be printed in case of non-conformance (if you expect non-conformance)

  • "no-check" or FALSE: if the name conformance should not be checked; use this if performance is critical. However, in case of non-conformance, expect cryptic follow-up errors

...

A name-value mapping of node attributes

Returns

The new Node (invisibly)

Examples
root <- Node$new("myroot", myname = "I'm the root")
root$AddChild("child1", myname = "I'm the favorite child")
child2 <- root$AddChild("child2", myname = "I'm just another child")
child3 <- child2$AddChild("child3", myname = "Grandson of a root!")
print(root, "myname")

Method AddChildNode()

Adds a Node as a child to this node.

Usage
Node$AddChildNode(child)
Arguments
child

The child "Node" to add.

Returns

the child node added (this lets you chain calls)

Examples
root <- Node$new("myroot")
child <- Node$new("mychild")
root$AddChildNode(child)

Method AddSibling()

Creates a new Node called name and adds it after this Node as a sibling.

Usage
Node$AddSibling(name, check = c("check", "no-warn", "no-check"), ...)
Arguments
name

the name of the node to be created

check

Either

  • "check": if the name conformance should be checked and warnings should be printed in case of non-conformance (the default)

  • "no-warn": if the name conformance should be checked, but no warnings should be printed in case of non-conformance (if you expect non-conformance)

  • "no-check" or FALSE: if the name conformance should not be checked; use this if performance is critical. However, in case of non-conformance, expect cryptic follow-up errors

...

A name-value mapping of node attributes

Returns

the sibling node (this lets you chain calls)

Examples
#' root <- Node$new("myroot")
child <- root$AddChild("child1")
sibling <- child$AddSibling("sibling1")

Method AddSiblingNode()

Adds a Node after this Node, as a sibling.

Usage
Node$AddSiblingNode(sibling)
Arguments
sibling

The "Node" to add as a sibling.

Returns

the added sibling node (this lets you chain calls, as in the examples)

Examples
root <- Node$new("myroot")
child <- Node$new("mychild")
sibling <- Node$new("sibling")
root$AddChildNode(child)$AddSiblingNode(sibling)

Method RemoveChild()

Remove the child Node called name from a Node and returns it.

Usage
Node$RemoveChild(name)
Arguments
name

the name of the node to be created

Returns

the subtree spanned by the removed child.

Examples
node <- Node$new("myroot")$AddChild("mychild")$root
node$RemoveChild("mychild")

Method RemoveAttribute()

Removes attribute called name from this Node.

Usage
Node$RemoveAttribute(name, stopIfNotAvailable = TRUE)
Arguments
name

the name of the node to be created

stopIfNotAvailable

Gives an error if stopIfNotAvailable and the attribute does not exist.

Examples
node <- Node$new("mynode")
node$RemoveAttribute("age", stopIfNotAvailable = FALSE)
node$age <- 27
node$RemoveAttribute("age")
node

Method Sort()

Sort children of a Node or an entire data.tree structure

Usage
Node$Sort(attribute, ..., decreasing = FALSE, recursive = TRUE)
Arguments
attribute

determines what is collected. The attribute can be

  • a.) the name of a field or a property/active of each Node in the tree, e.g. acme$Get("p") or acme$Get("position")

  • b.) the name of a method of each Node in the tree, e.g. acme$Get("levelZeroBased"), where e.g. acme$levelZeroBased <- function() acme$level - 1

  • c.) a function, whose first argument must be a Node e.g. acme$Get(function(node) node$cost * node$p)

...

any parameters to be passed on the the attribute (in case it's a method or a function)

decreasing

sort order

recursive

if TRUE, the method will be called recursively on the Node's children. This allows sorting an entire tree.

Details

You can sort with respect to any argument of the tree. But note that sorting has side-effects, meaning that you modify the underlying, original data.tree object structure.

See also Sort for the equivalent function.

Returns

Returns the node on which Sort is called, invisibly. This can be useful to chain Node methods.

Examples
data(acme)
acme$Do(function(x) x$totalCost <- Aggregate(x, "cost", sum), traversal = "post-order")
Sort(acme, "totalCost", decreasing = FALSE)
print(acme, "totalCost")

Method Revert()

Reverts the sort order of a Node's children.

See also Revert for the equivalent function.

Usage
Node$Revert(recursive = TRUE)
Arguments
recursive

if TRUE, the method will be called recursively on the Node's children. This allows sorting an entire tree.

Returns

returns the Node invisibly (for chaining)

Method Prune()

Prunes a tree.

Pruning refers to removing entire subtrees. This function has side-effects, it modifies your data.tree structure!

See also Prune for the equivalent function.

Usage
Node$Prune(pruneFun)
Arguments
pruneFun

allows providing a a prune criteria, i.e. a function taking a Node as an input, and returning TRUE or FALSE. If the pruneFun returns FALSE for a Node, then the Node and its entire sub-tree will not be considered.

Returns

the number of nodes removed

Examples
data(acme)
acme$Do(function(x) x$cost <- Aggregate(x, "cost", sum))
Prune(acme, function(x) x$cost > 700000)
print(acme, "cost")

Method Climb()

Climb a tree from parent to children, by provided criteria.

Usage
Node$Climb(...)
Arguments
...

an attribute-value pairlist to be searched. For brevity, you can also provide a character vector to search for names.

node

The root Node of the tree or subtree to climb

Details

This method lets you climb the tree, from crutch to crutch. On each Node, the Climb finds the first child having attribute value equal to the the provided argument.

See also Climb and Navigate

Climb(node, ...)

Returns

the Node having path ..., or NULL if such a path does not exist

Examples
data(acme)

#the following are all equivalent
Climb(acme, 'IT', 'Outsource')
Climb(acme, name = 'IT', name = 'Outsource')
Climb(acme, 'IT')$Climb('Outsource')
Navigate(acme, path = "IT/Outsource")

Climb(acme, name = 'IT')

Climb(acme, position = c(2, 1))
#or, equivalent:
Climb(acme, position = 2, position = 1)
Climb(acme, name = "IT", cost = 250000)

tree <- CreateRegularTree(5, 2)
tree$Climb(c("1", "1"), position = c(2, 2))$path

Method Navigate()

Navigate to another node by relative path.

Usage
Node$Navigate(path)
Arguments
path

A string or a character vector describing the path to navigate

node

The starting Node to navigate

Details

The path is always relative to the Node. Navigation to the parent is defined by .., whereas navigation to a child is defined via the child's name. If path is provided as a string, then the navigation steps are separated by '/'.

See also Navigate and Climb

Examples
data(acme)
Navigate(acme$Research, "../IT/Outsource")
Navigate(acme$Research, c("..", "IT", "Outsource"))

Method Get()

Traverse a Tree and Collect Values

Usage
Node$Get(
  attribute,
  ...,
  traversal = c("pre-order", "post-order", "in-order", "level", "ancestor"),
  pruneFun = NULL,
  filterFun = NULL,
  format = FALSE,
  inheritFromAncestors = FALSE,
  simplify = c(TRUE, FALSE, "array", "regular")
)
Arguments
attribute

determines what is collected. The attribute can be

  • a.) the name of a field or a property/active of each Node in the tree, e.g. acme$Get("p") or acme$Get("position")

  • b.) the name of a method of each Node in the tree, e.g. acme$Get("levelZeroBased"), where e.g. acme$levelZeroBased <- function() acme$level - 1

  • c.) a function, whose first argument must be a Node e.g. acme$Get(function(node) node$cost * node$p)

...

in case the attribute is a function or a method, the ellipsis is passed to it as additional arguments.

traversal

defines the traversal order to be used. This can be

pre-order

Go to first child, then to its first child, etc.

post-order

Go to the first branch's leaf, then to its siblings, and work your way back to the root

in-order

Go to the first branch's leaf, then to its parent, and only then to the leaf's sibling

level

Collect root, then level 2, then level 3, etc.

ancestor

Take a node, then the node's parent, then that node's parent in turn, etc. This ignores the pruneFun

function

You can also provide a function, whose sole parameter is a Node object. The function is expected to return the node's next node, a list of the node's next nodes, or NULL.

Read the data.tree vignette for a detailed explanation of these traversal orders.

pruneFun

allows providing a prune criteria, i.e. a function taking a Node as an input, and returning TRUE or FALSE. If the pruneFun returns FALSE for a Node, then the Node and its entire sub-tree will not be considered.

filterFun

allows providing a a filter, i.e. a function taking a Node as an input, and returning TRUE or FALSE. Note that if filter returns FALSE, then the node will be excluded from the result (but not the entire subtree).

format

if FALSE (the default), no formatting is being used. If TRUE, then the first formatter (if any) found along the ancestor path is being used for formatting (see SetFormat). If format is a function, then the collected value is passed to that function, and the result is returned.

inheritFromAncestors

if TRUE, then the path above a Node is searched to get the attribute in case it is NULL.

simplify

same as sapply, i.e. TRUE, FALSE or "array". Additionally, you can specify "regular" if each returned value is of length > 1, and equally named. See below for an example.

Details

The Get method is one of the most important ones of the data.tree package. It lets you traverse a tree and collect values along the way. Alternatively, you can call a method or a function on each Node.

See also Get, Node, Set, Do, Traverse

Returns

a vector containing the atrributes collected during traversal, in traversal order. NULL is converted to NA, such that length(Node$Get) == Node$totalCount

Examples
data(acme)
acme$Get("level")
acme$Get("totalCount")
 

acme$Get(function(node) node$cost * node$p,
         filterFun = isLeaf)

#This is equivalent:
nodes <- Traverse(acme, filterFun = isLeaf)
Get(nodes, function(node) node$cost * node$p)

   
#simplify = "regular" will preserve names
acme$Get(function(x) c(position = x$position, level = x$level), simplify = "regular")

Method Do()

Executes a function on a set of nodes

Usage
Node$Do(
  fun,
  ...,
  traversal = c("pre-order", "post-order", "in-order", "level", "ancestor"),
  pruneFun = NULL,
  filterFun = NULL
)
Arguments
fun

the function to execute. The function is expected to be either a Method, or to take a Node as its first argument

...

A name-value mapping of node attributes

traversal

defines the traversal order to be used. This can be

pre-order

Go to first child, then to its first child, etc.

post-order

Go to the first branch's leaf, then to its siblings, and work your way back to the root

in-order

Go to the first branch's leaf, then to its parent, and only then to the leaf's sibling

level

Collect root, then level 2, then level 3, etc.

ancestor

Take a node, then the node's parent, then that node's parent in turn, etc. This ignores the pruneFun

function

You can also provide a function, whose sole parameter is a Node object. The function is expected to return the node's next node, a list of the node's next nodes, or NULL.

Read the data.tree vignette for a detailed explanation of these traversal orders.

pruneFun

allows providing a prune criteria, i.e. a function taking a Node as an input, and returning TRUE or FALSE. If the pruneFun returns FALSE for a Node, then the Node and its entire sub-tree will not be considered.

filterFun

allows providing a a filter, i.e. a function taking a Node as an input, and returning TRUE or FALSE. Note that if filter returns FALSE, then the node will be excluded from the result (but not the entire subtree).

Details

See also Node, Get, Set, Traverse

Examples
data(acme)
acme$Do(function(node) node$expectedCost <- node$p * node$cost)
print(acme, "expectedCost")

Method Set()

Traverse a Tree and Assign Values

Usage
Node$Set(
  ...,
  traversal = c("pre-order", "post-order", "in-order", "level", "ancestor"),
  pruneFun = NULL,
  filterFun = NULL
)
Arguments
...

each argument can be a vector of values to be assigned. Recycled.

traversal

defines the traversal order to be used. This can be

pre-order

Go to first child, then to its first child, etc.

post-order

Go to the first branch's leaf, then to its siblings, and work your way back to the root

in-order

Go to the first branch's leaf, then to its parent, and only then to the leaf's sibling

level

Collect root, then level 2, then level 3, etc.

ancestor

Take a node, then the node's parent, then that node's parent in turn, etc. This ignores the pruneFun

function

You can also provide a function, whose sole parameter is a Node object. The function is expected to return the node's next node, a list of the node's next nodes, or NULL.

Read the data.tree vignette for a detailed explanation of these traversal orders.

pruneFun

allows providing a prune criteria, i.e. a function taking a Node as an input, and returning TRUE or FALSE. If the pruneFun returns FALSE for a Node, then the Node and its entire sub-tree will not be considered.

filterFun

allows providing a a filter, i.e. a function taking a Node as an input, and returning TRUE or FALSE. Note that if filter returns FALSE, then the node will be excluded from the result (but not the entire subtree).

Details

The method takes one or more vectors as an argument. It traverses the tree, whereby the values are picked from the vector. Also available as OO-style method on Node.

See also Node, Get, Do, Traverse

Returns

invisibly returns the nodes (useful for chaining)

Examples
data(acme)
acme$Set(departmentId = 1:acme$totalCount, openingHours = NULL, traversal = "post-order")
acme$Set(head = c("Jack Brown", 
                  "Mona Moneyhead", 
                  "Dr. Frank N. Stein", 
                  "Eric Nerdahl"
                  ),
         filterFun = function(x) !x$isLeaf
        )
print(acme, "departmentId", "head")

Method clone()

The objects of this class are cloneable with this method.

Usage
Node$clone(deep = FALSE)
Arguments
deep

Whether to make a deep clone.

See Also

For more details see the data.tree documentations, or the data.tree vignette: vignette("data.tree")

Node

Sort

Examples

library(data.tree)
acme <- Node$new("Acme Inc.")
accounting <- acme$AddChild("Accounting")$
              AddSibling("Research")$
              AddChild("New Labs")$
              parent$
              AddSibling("IT")$
              AddChild("Outsource")
print(acme)



## ------------------------------------------------
## Method `Node$new`
## ------------------------------------------------

node <- Node$new("mynode", x = 2, y = "value of y")
node$y


## ------------------------------------------------
## Method `Node$AddChild`
## ------------------------------------------------

root <- Node$new("myroot", myname = "I'm the root")
root$AddChild("child1", myname = "I'm the favorite child")
child2 <- root$AddChild("child2", myname = "I'm just another child")
child3 <- child2$AddChild("child3", myname = "Grandson of a root!")
print(root, "myname")


## ------------------------------------------------
## Method `Node$AddChildNode`
## ------------------------------------------------

root <- Node$new("myroot")
child <- Node$new("mychild")
root$AddChildNode(child)


## ------------------------------------------------
## Method `Node$AddSibling`
## ------------------------------------------------

#' root <- Node$new("myroot")
child <- root$AddChild("child1")
sibling <- child$AddSibling("sibling1")


## ------------------------------------------------
## Method `Node$AddSiblingNode`
## ------------------------------------------------

root <- Node$new("myroot")
child <- Node$new("mychild")
sibling <- Node$new("sibling")
root$AddChildNode(child)$AddSiblingNode(sibling)


## ------------------------------------------------
## Method `Node$RemoveChild`
## ------------------------------------------------

node <- Node$new("myroot")$AddChild("mychild")$root
node$RemoveChild("mychild")


## ------------------------------------------------
## Method `Node$RemoveAttribute`
## ------------------------------------------------

node <- Node$new("mynode")
node$RemoveAttribute("age", stopIfNotAvailable = FALSE)
node$age <- 27
node$RemoveAttribute("age")
node


## ------------------------------------------------
## Method `Node$Sort`
## ------------------------------------------------

data(acme)
acme$Do(function(x) x$totalCost <- Aggregate(x, "cost", sum), traversal = "post-order")
Sort(acme, "totalCost", decreasing = FALSE)
print(acme, "totalCost")


## ------------------------------------------------
## Method `Node$Prune`
## ------------------------------------------------

data(acme)
acme$Do(function(x) x$cost <- Aggregate(x, "cost", sum))
Prune(acme, function(x) x$cost > 700000)
print(acme, "cost")


## ------------------------------------------------
## Method `Node$Climb`
## ------------------------------------------------

data(acme)

#the following are all equivalent
Climb(acme, 'IT', 'Outsource')
Climb(acme, name = 'IT', name = 'Outsource')
Climb(acme, 'IT')$Climb('Outsource')
Navigate(acme, path = "IT/Outsource")

Climb(acme, name = 'IT')

Climb(acme, position = c(2, 1))
#or, equivalent:
Climb(acme, position = 2, position = 1)
Climb(acme, name = "IT", cost = 250000)

tree <- CreateRegularTree(5, 2)
tree$Climb(c("1", "1"), position = c(2, 2))$path



## ------------------------------------------------
## Method `Node$Navigate`
## ------------------------------------------------

data(acme)
Navigate(acme$Research, "../IT/Outsource")
Navigate(acme$Research, c("..", "IT", "Outsource"))


## ------------------------------------------------
## Method `Node$Get`
## ------------------------------------------------

data(acme)
acme$Get("level")
acme$Get("totalCount")
 

acme$Get(function(node) node$cost * node$p,
         filterFun = isLeaf)

#This is equivalent:
nodes <- Traverse(acme, filterFun = isLeaf)
Get(nodes, function(node) node$cost * node$p)

   
#simplify = "regular" will preserve names
acme$Get(function(x) c(position = x$position, level = x$level), simplify = "regular")
 

## ------------------------------------------------
## Method `Node$Do`
## ------------------------------------------------

data(acme)
acme$Do(function(node) node$expectedCost <- node$p * node$cost)
print(acme, "expectedCost")


## ------------------------------------------------
## Method `Node$Set`
## ------------------------------------------------

data(acme)
acme$Set(departmentId = 1:acme$totalCount, openingHours = NULL, traversal = "post-order")
acme$Set(head = c("Jack Brown", 
                  "Mona Moneyhead", 
                  "Dr. Frank N. Stein", 
                  "Eric Nerdahl"
                  ),
         filterFun = function(x) !x$isLeaf
        )
print(acme, "departmentId", "head")

Names that are reserved by the Node class.

Description

These are reserved by the Node class, you cannot use these as attribute names. Note also that all attributes starting with a . are reserved.

Usage

NODE_RESERVED_NAMES_CONST

Format

An object of class character of length 43.

Plot a graph, or get a graphviz dot representation of the tree

Description

Use these methods to style your graph, and to plot it. The functionality is built around the DiagrammeR package, so for anything that goes beyond simple plotting, it is recommended to read its documentation at https://rich-iannone.github.io/DiagrammeR/docs.html. Note that DiagrammeR is only suggested by data.tree, so 'plot' only works if you have installed it on your system.

Usage

## S3 method for class 'Node'
plot(
  x,
  ...,
  direction = c("climb", "descend"),
  pruneFun = NULL,
  output = "graph"
)

ToDiagrammeRGraph(root, direction = c("climb", "descend"), pruneFun = NULL)

SetNodeStyle(node, inherit = TRUE, keepExisting = FALSE, ...)

SetEdgeStyle(node, inherit = TRUE, keepExisting = FALSE, ...)

SetGraphStyle(root, keepExisting = FALSE, ...)

GetDefaultTooltip(node)

Arguments

x

The root node of the data.tree structure to plot
...

For the SetStyle methods, this can be any stlyeName / value pair. See https://graphviz.org/Documentation.php for details. For the plot.Node generic method, this is not used.
direction

when converting to a network, should the edges point from root to children ("climb") or from child to parent ("descend")?
pruneFun

allows providing a prune criteria, i.e. a function taking a Node as an input, and returning TRUE or FALSE. If the pruneFun returns FALSE for a Node, then the Node and its entire sub-tree will not be considered.
output

A string specifying the output type; graph (the default) renders the graph using the grViz() function and visNetwork renders the graph using the visnetwork() function.
root

The root Node of the data.tree structure to visualize.
node

The Node of the data.tree structure on which you would like to set style attributes.
inherit

If TRUE, then children will inherit this node's style. Otherwise they inherit from this node's parent. Note that the inherit always applies to the node, i.e. all style attributes of a node and not to a single style attribute.
keepExisting

If TRUE, then style attributes are added to possibly existing style attributes on the node.

Details

Use SetNodeStyle and SetEdgeStyle to define the style of your plot. Use plot to display a graphical representation of your tree.

The most common styles that can be set on the nodes are:

  • color

  • fillcolor

  • fixedsize true or false

  • fontcolor

  • fontname

  • fontsize

  • height

  • penwidth

  • shape box, ellipse, polygon, circle, box, etc.

  • style

  • tooltip

  • width

The most common styles that can be set on the edges are:

  • arrowhead e.g. normal, dot, vee

  • arrowsize

  • arrowtail

  • color

  • dir forward, back, both, none

  • fontcolor

  • fontname

  • fontsize

  • headport

  • label

  • minlen

  • penwidth

  • tailport

  • tooltip

A good source to understand the attributes is https://graphviz.org/Documentation.php. Another good source is the DiagrammeR package documentation, or more specifically: https://rich-iannone.github.io/DiagrammeR/docs.html

In addition to the standard GraphViz functionality, the data.tree plotting infrastructure takes advantage of the fact that data.tree structure are always hierarchic. Thus, style attributes are inherited from parents to children on an individual basis. For example, you can set the fontcolor to red on a parent, and then all children will also have red font, except if you specifically disallow inheritance. Labels and tooltips are never inherited.

Another feature concerns functions: Instead of setting a fixed value (e.g. SetNodeStyle(acme, label = "Acme. Inc"), you can set a function (e.g. SetNodeStyle(acme, label = function(x) x$name)). The function must take a Node as its single argument. Together with inheritance, this becomes a very powerful tool.

The GetDefaultTooltip method is a utility method that can be used to print all attributes of a Node.

There are some more examples in the 'applications' vignette, see vignette('applications', package = "data.tree")

Examples

data(acme)
SetGraphStyle(acme, rankdir = "TB")
SetEdgeStyle(acme, arrowhead = "vee", color = "blue", penwidth = 2)
#per default, Node style attributes will be inherited:
SetNodeStyle(acme, style = "filled,rounded", shape = "box", fillcolor = "GreenYellow", 
             fontname = "helvetica", tooltip = GetDefaultTooltip)
SetNodeStyle(acme$IT, fillcolor = "LightBlue", penwidth = "5px")
#inheritance can be avoided:
SetNodeStyle(acme$Accounting, inherit = FALSE, fillcolor = "Thistle", 
             fontcolor = "Firebrick", tooltip = "This is the accounting department")
SetEdgeStyle(acme$Research$`New Labs`, 
             color = "red", 
             label = "Focus!", 
             penwidth = 3, 
             fontcolor = "red")
#use Do to set style on specific nodes:
Do(acme$leaves, function(node) SetNodeStyle(node, shape = "egg"))
plot(acme)

#print p as label, where available:
SetNodeStyle(acme, label = function(node) node$p)
plot(acme)

Print a Node in a human-readable fashion.

Description

Print a Node in a human-readable fashion.

Usage

## S3 method for class 'Node'
print(
  x,
  ...,
  pruneMethod = c("simple", "dist", NULL),
  limit = 100,
  pruneFun = NULL,
  row.names = T
)

Arguments

x

The Node
...

Node attributes to be printed. Can be either a character (i.e. the name of a Node field), a Node method, or a function taking a Node as a single argument. See Get for details on the meaning of attribute.
pruneMethod

The method can be used to prune for printing in a simple way. If NULL, the entire tree is displayed. If "simple", then only the first limit nodes are displayed. If "dist", then Nodes are removed everywhere in the tree, according to their level. If pruneFun is provided, then pruneMethod is ignored.
limit

The maximum number of nodes to print. Can be NULL if the entire tree should be printed.
pruneFun

allows providing a prune criteria, i.e. a function taking a Node as an input, and returning TRUE or FALSE. If the pruneFun returns FALSE for a Node, then the Node and its entire sub-tree will not be considered.
row.names

If TRUE (default), then the row names are printed out. Else, they are not.

Examples

data(acme)
print(acme, "cost", "p")
print(acme, "cost", probability = "p")
print(acme, expectedCost = function(x) x$cost * x$p)
do.call(print, c(acme, acme$attributesAll))

tree <- CreateRegularTree(4, 5)
# print entire tree:
print(tree, pruneMethod = NULL)
# print first 20 nodes:
print(tree, pruneMethod = "simple", limit = 20)
# print 20 nodes, removing leafs first:
print(tree, pruneMethod = "dist", limit = 20)
# provide your own pruning function:
print(tree, pruneFun = function(node) node$position != 2)

Prunes a tree.

Description

Pruning refers to removing entire subtrees. This function has side-effects, it modifies your data.tree structure!

Usage

Prune(node, pruneFun)

Arguments

node

The root of the sub-tree to be pruned
pruneFun

allows providing a prune criteria, i.e. a function taking a Node as an input, and returning TRUE or FALSE. If the pruneFun returns FALSE for a Node, then the Node and its entire sub-tree will not be considered.

Value

the number of nodes removed

See Also

Node

Examples

data(acme)
acme$Do(function(x) x$cost <- Aggregate(x, "cost", sum))
Prune(acme, function(x) x$cost > 700000)
print(acme, "cost")

Reverts the sort order of a Node's children.

Description

Reverts the sort order of a Node's children.

Usage

Revert(node, recursive = TRUE)

Arguments

node

the Node whose childrens' sort order is to be reverted
recursive

If TRUE, then revert is called recursively on all children.

Value

returns the Node invisibly (for chaining)

See Also

Node

Sort

Traverse a Tree and Assign Values

Description

The method takes one or more vectors as an argument. It traverses the tree, whereby the values are picked from the vector. Also available as OO-style method on Node.

Usage

#OO-style:
# node$Set(..., 
#          traversal = c("pre-order", "post-order", "in-order", "level", "ancestor"),  
#          pruneFun = NULL, 
#          filterFun = NULL)
#traditional:
Set(nodes, ...)

Arguments

nodes

The nodes on which to perform the Get (typically obtained via Traverse)
...

each argument can be a vector of values to be assigned. Recycled.

Value

invisibly returns the nodes (useful for chaining)

See Also

Node

Get

Do

Traverse

Examples

data(acme)
acme$Set(departmentId = 1:acme$totalCount, openingHours = NULL, traversal = "post-order")
acme$Set(head = c("Jack Brown", 
                  "Mona Moneyhead", 
                  "Dr. Frank N. Stein", 
                  "Eric Nerdahl"
                  ),
         filterFun = function(x) !x$isLeaf
        )
print(acme, "departmentId", "head")

Set a formatter function on a specific node

Description

Formatter functions set on a Node act as a default formatter when printing and using the Get method. The formatter is inherited, meaning that whenever Get fetches an attribute from a Node, it checks on the Node or on any of its ancestors whether a formatter is set.

Usage

SetFormat(node, name, formatFun)

Arguments

node

The node on which to set the formatter
name

The attribute name for which to set the formatter
formatFun

The formatter, i.e. a function taking a value as an input, and formatting returning the formatted value

See Also

Get

print.Node

Examples

data(acme)
acme$Set(id = 1:(acme$totalCount))
SetFormat(acme, "id", function(x) FormatPercent(x, digits = 0))
SetFormat(Climb(acme, "IT"), "id", FormatFixedDecimal)
print(acme, "id")
# Calling Get with an explicit formatter will overwrite the default set on the Node:
print(acme, id = acme$Get("id", format = function(x) paste0("id:", x)))

# Or, to avoid formatters, even though you set them on a Node:
print(acme, id = acme$Get("id", format = identity))

Sort children of a Node or an entire data.tree structure

Description

You can sort with respect to any argument of the tree. But note that sorting has side-effects, meaning that you modify the underlying, original data.tree object structure.

Usage

Sort(node, attribute, ..., decreasing = FALSE, recursive = TRUE)

Arguments

node

The node whose children are to be sorted
attribute

determines what is collected. The attribute can be

  • a.) the name of a field or a property/active of each Node in the tree, e.g. acme$Get("p") or acme$Get("position")

  • b.) the name of a method of each Node in the tree, e.g. acme$Get("levelZeroBased"), where e.g. acme$levelZeroBased <- function() acme$level - 1

  • c.) a function, whose first argument must be a Node e.g. acme$Get(function(node) node$cost * node$p)

...

any parameters to be passed on the the attribute (in case it's a method or a function)
decreasing

sort order
recursive

if TRUE, Sort will be called recursively on the Node's children. This allows sorting an entire tree.

Value

Returns the node on which Sort is called, invisibly. This can be useful to chain Node methods.

See Also

Node

Revert

Examples

data(acme)
acme$Do(function(x) x$totalCost <- Aggregate(x, "cost", sum), traversal = "post-order")
Sort(acme, "totalCost", decreasing = FALSE)
print(acme, "totalCost")

Write a data.tree structure to Newick notation

Description

To read from Newick, you can use the ape package, and convert the resulting phylo object to a data.tree structure.

Usage

ToNewick(node, heightAttribute = DefaultPlotHeight, ...)

Arguments

node

The root Node of a tree or sub-tree to be converted
heightAttribute

The attribute (field name, method, or function) storing or calculating the height for each Node
...

parameters that will be passed on the the heightAttributeName, in case it is a function

See Also

Other Conversions from Node: as.dendrogram.Node()

Examples

data(acme)
ToNewick(acme)
ToNewick(acme, heightAttribute = NULL)
ToNewick(acme, heightAttribute = function(x) DefaultPlotHeight(x, 200))
ToNewick(acme, rootHeight = 200)

Traverse a tree or a sub-tree

Description

Traverse takes the root of a tree or a sub-tree, and "walks" the tree in a specific order. It returns a list of Node objects, filtered and pruned by filterFun and pruneFun.

Usage

Traverse(
  node,
  traversal = c("pre-order", "post-order", "in-order", "level", "ancestor"),
  pruneFun = NULL,
  filterFun = NULL
)

Arguments

node

the root of a tree or a sub-tree that should be traversed
traversal

any of 'pre-order' (the default), 'post-order', 'in-order', 'level', 'ancestor', or a custom function (see details)
pruneFun

allows providing a prune criteria, i.e. a function taking a Node as an input, and returning TRUE or FALSE. If the pruneFun returns FALSE for a Node, then the Node and its entire sub-tree will not be considered.
filterFun

allows providing a a filter, i.e. a function taking a Node as an input, and returning TRUE or FALSE. Note that if filter returns FALSE, then the node will be excluded from the result (but not the entire subtree).

Details

The traversal order is as follows. (Note that these descriptions are not precise and complete. They are meant for quick reference only. See the data.tree vignette for a more detailed description).

pre-order

Go to first child, then to its first child, etc.

post-order

Go to the first branch's leaf, then to its siblings, and work your way back to the root

in-order

Go to the first branch's leaf, then to its parent, and only then to the leaf's sibling

level

Collect root, then level 2, then level 3, etc.

ancestor

Take a node, then the node's parent, then that node's parent in turn, etc. This ignores the pruneFun

function

You can also provide a function, whose sole parameter is a Node object. The function is expected to return the node's next node, a list of the node's next nodes, or NULL.

Value

a list of Nodes

See Also

Node

Get

Set

Do