| Node | R Documentation |
data.tree Structure With NodesNode is at the very heart of the data.tree package. All trees are constructed
by tying together Node objects.
# n1 <- Node$new("Node 1")
An R6Class generator object
Assemble Node objects into a data.tree
structure and use the traversal methods to set, get, and perform operations on it. Typically, you construct larger tree
structures by converting from data.frame, list, or other formats.
Most methods (e.g. node$Sort()) also have a functional form (e.g. Sort(node))
nameGets or sets the name of a Node. For example Node$name <- "Acme".
printFormattersgets 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 = " ")
parentGets 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!
childrenGets 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!
isLeafReturns TRUE if the Node is a leaf, FALSE otherwise
isRootReturns TRUE if the Node is the root, FALSE otherwise
countReturns the number of children of a Node
totalCountReturns the total number of Nodes in the tree
pathReturns a vector of mode character containing the names of the Nodes in the path from the root to this Node
pathStringReturns a string representing the path to this Node, separated by backslash
positionThe position of a Node within its siblings
attributesThe attributes defined on this specific node
attributesAllThe distinct union of attributes defined on all the nodes in the tree spanned by this Node
levelNameReturns the name of the Node, preceded by level times '*'. Useful for printing and not typically called by package users.
leavesReturns a list containing all the leaf Nodes
leafCountReturns the number of leaves are below a Node
levelReturns an integer representing the level of a Node. For example, the root has level 1.
heightReturns max(level) of any of the Nodes of the tree
isBinaryReturns TRUE if all Nodes in the tree (except the leaves) have count = 2
rootReturns the root of a Node in a tree.
siblingsReturns a list containing all the siblings of this Node
averageBranchingFactorReturns the average number of crotches below this Node
new()Create a new Node object. This is often used to create the root of a tree when creating a tree programmatically.
Node$new(name, check = c("check", "no-warn", "no-check"), ...)namethe name of the node to be created
checkEither
"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
A new 'Node' object
node <- Node$new("mynode", x = 2, y = "value of y")
node$y
AddChild()Creates a Node and adds it as the last sibling as a child to the Node on which this is called.
Node$AddChild(name, check = c("check", "no-warn", "no-check"), ...)namethe name of the node to be created
checkEither
"check": if the name conformance should be checked and warnings should be printed in case of non-conformance (the default)
"no-warn": if the name conformance should be checked, but no warnings should be printed in case of non-conformance (if you expect non-conformance)
"no-check" or FALSE: if the name conformance should not be checked; use this if performance is critical. However, in case of non-conformance, expect cryptic follow-up errors
...A name-value mapping of node attributes
The new Node (invisibly)
root <- Node$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$AddChild("child3", myname = "Grandson of a root!")
print(root, "myname")
AddChildNode()Adds a Node as a child to this node.
Node$AddChildNode(child)
childThe child "Node" to add.
the child node added (this lets you chain calls)
root <- Node$new("myroot")
child <- Node$new("mychild")
root$AddChildNode(child)
AddSibling()Creates a new Node called name and adds it after this Node as a sibling.
Node$AddSibling(name, check = c("check", "no-warn", "no-check"), ...)namethe name of the node to be created
checkEither
"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
the sibling node (this lets you chain calls)
#' root <- Node$new("myroot")
child <- root$AddChild("child1")
sibling <- child$AddSibling("sibling1")
AddSiblingNode()Adds a Node after this Node, as a sibling.
Node$AddSiblingNode(sibling)
siblingThe "Node" to add as a sibling.
the added sibling node (this lets you chain calls, as in the examples)
root <- Node$new("myroot")
child <- Node$new("mychild")
sibling <- Node$new("sibling")
root$AddChildNode(child)$AddSiblingNode(sibling)
RemoveChild()Remove the child Node called name from a Node and returns it.
Node$RemoveChild(name)
namethe name of the node to be created
the subtree spanned by the removed child.
node <- Node$new("myroot")$AddChild("mychild")$root
node$RemoveChild("mychild")
RemoveAttribute()Removes attribute called name from this Node.
Node$RemoveAttribute(name, stopIfNotAvailable = TRUE)
namethe name of the node to be created
stopIfNotAvailableGives an error if stopIfNotAvailable and the attribute does not exist.
node <- Node$new("mynode")
node$RemoveAttribute("age", stopIfNotAvailable = FALSE)
node$age <- 27
node$RemoveAttribute("age")
node
Sort()Sort children of a Node or an entire data.tree structure
Node$Sort(attribute, ..., decreasing = FALSE, recursive = TRUE)
attributedetermines 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)
decreasingsort order
recursiveif TRUE, the method will be called recursively on the Node's children. This allows sorting an entire tree.
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 the node on which Sort is called, invisibly. This can be useful to chain Node methods.
data(acme) acme$Do(function(x) x$totalCost <- Aggregate(x, "cost", sum), traversal = "post-order") Sort(acme, "totalCost", decreasing = FALSE) print(acme, "totalCost")
Revert()Reverts the sort order of a Node's children.
See also Revert for the equivalent function.
Node$Revert(recursive = TRUE)
recursiveif TRUE, the method will be called recursively on the Node's children. This allows sorting an entire tree.
returns the Node invisibly (for chaining)
Prune()Prunes a tree.
Pruning refers to removing entire subtrees. This function has side-effects, it modifies your data.tree structure!
See also Prune for the equivalent function.
Node$Prune(pruneFun)
pruneFunallows 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.
the number of nodes removed
data(acme) acme$Do(function(x) x$cost <- Aggregate(x, "cost", sum)) Prune(acme, function(x) x$cost > 700000) print(acme, "cost")
Climb()Climb a tree from parent to children, by provided criteria.
Node$Climb(...)
...an attribute-value pairlist to be searched. For brevity, you can also provide a character vector to search for names.
nodeThe root Node of the tree or subtree to climb
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, ...)
the Node having path ..., or NULL if such a path does not exist
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))$path
Navigate()Navigate to another node by relative path.
Node$Navigate(path)
pathA string or a character vector describing the path to navigate
nodeThe starting Node to navigate
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
data(acme)
Navigate(acme$Research, "../IT/Outsource")
Navigate(acme$Research, c("..", "IT", "Outsource"))
Get()Traverse a Tree and Collect Values
Node$Get(
attribute,
...,
traversal = c("pre-order", "post-order", "in-order", "level", "ancestor"),
pruneFun = NULL,
filterFun = NULL,
format = FALSE,
inheritFromAncestors = FALSE,
simplify = c(TRUE, FALSE, "array", "regular")
)attributedetermines what is collected. The attribute can be
a.) the name of a field or a property/active of each Node in the tree, e.g. acme$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.
traversaldefines the traversal order to be used. This can be
Go to first child, then to its first child, etc.
Go to the first branch's leaf, then to its siblings, and work your way back to the root
Go to the first branch's leaf, then to its parent, and only then to the leaf's sibling
Collect root, then level 2, then level 3, etc.
Take a node, then the node's parent, then that node's parent in turn, etc. This ignores the pruneFun
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.
pruneFunallows 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.
filterFunallows 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).
formatif 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.
inheritFromAncestorsif TRUE, then the path above a Node is searched to get the attribute in case it is NULL.
simplifysame 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.
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
a vector containing the atrributes collected during traversal, in traversal order. NULL is converted
to NA, such that length(Node$Get) == Node$totalCount
data(acme)
acme$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$level), simplify = "regular")
Do()Executes a function on a set of nodes
Node$Do(
fun,
...,
traversal = c("pre-order", "post-order", "in-order", "level", "ancestor"),
pruneFun = NULL,
filterFun = NULL
)funthe 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
traversaldefines the traversal order to be used. This can be
Go to first child, then to its first child, etc.
Go to the first branch's leaf, then to its siblings, and work your way back to the root
Go to the first branch's leaf, then to its parent, and only then to the leaf's sibling
Collect root, then level 2, then level 3, etc.
Take a node, then the node's parent, then that node's parent in turn, etc. This ignores the pruneFun
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.
pruneFunallows 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.
filterFunallows 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).
See also Node, Get, Set, Traverse
data(acme) acme$Do(function(node) node$expectedCost <- node$p * node$cost) print(acme, "expectedCost")
Set()Traverse a Tree and Assign Values
Node$Set(
...,
traversal = c("pre-order", "post-order", "in-order", "level", "ancestor"),
pruneFun = NULL,
filterFun = NULL
)...each argument can be a vector of values to be assigned. Recycled.
traversaldefines the traversal order to be used. This can be
Go to first child, then to its first child, etc.
Go to the first branch's leaf, then to its siblings, and work your way back to the root
Go to the first branch's leaf, then to its parent, and only then to the leaf's sibling
Collect root, then level 2, then level 3, etc.
Take a node, then the node's parent, then that node's parent in turn, etc. This ignores the pruneFun
You can also provide a function, whose sole parameter is a Node object. The function is expected to return the node's next node, a list of the node's next nodes, or NULL.
Read the data.tree vignette for a detailed explanation of these traversal orders.
pruneFunallows providing a prune criteria, i.e. a function taking a Node as an input, and returning TRUE or FALSE.
If the pruneFun returns FALSE for a Node, then the Node and its entire sub-tree will not be considered.
filterFunallows providing a a filter, i.e. a function taking a Node as an input, and returning TRUE or FALSE.
Note that if filter returns FALSE, then the node will be excluded from the result (but not the entire subtree).
The method takes one or more vectors as an argument. It traverses the tree, whereby the values are picked
from the vector. Also available as OO-style method on Node.
See also Node, Get, Do, Traverse
invisibly returns the nodes (useful for chaining)
data(acme)
acme$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$isLeaf
)
print(acme, "departmentId", "head")
clone()The objects of this class are cloneable with this method.
Node$clone(deep = FALSE)
deepWhether to make a deep clone.
For more details see the data.tree documentations, or the data.tree vignette: vignette("data.tree")
Node
Sort
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")
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