1\name{xmlHashTree}
2\alias{xmlHashTree}
3\title{Constructors for trees stored as flat list of nodes with
4    information about parents and children.}
5\description{
6
7  These (and related internal) functions allow us to represent trees as
8  a simple, non-hierarchical collection of nodes along with
9  corresponding tables that identify the parent and child relationships.
10  This is different from representing a tree as a list of lists of lists
11  ...  in which each node has a list of its own children. In a
12  functional language like R, it is not possible then for the children
13  to be able to identify their parents.
14
15  We use an environment to represent these flat trees.  Since these are
16  mutable without requiring the change to be reassigned, we can modify a
17  part of the tree locally without having to reassign the top-level
18  object.
19
20  We can use either a list (with names) to store the nodes or a hash
21  table/associative array that uses names. There is a non-trivial
22  performance difference.
23}
24\usage{
25xmlHashTree(nodes = list(), parents = character(), children = list(),
26             env = new.env(TRUE, parent = emptyenv()))
27}
28\arguments{
29  \item{nodes}{ a collection of existing nodes that are to be added to
30    the tree. These are used to initialize the tree. If this is
31    specified, you must also specify \code{children} and \code{parents}.
32    }
33  \item{parents}{ the parent relationships for the nodes given by \code{nodes}.}
34  \item{children}{the children relationships for the nodes given by \code{nodes}.}
35  \item{env}{an environment in which the information for the tree  will
36    be stored. This is essentially the tree object as it allows us to
37    modify parts of the tree without having to reassign the top-level
38    object.    Unlike most R data types, environments are mutable.
39   }
40}
41
42\value{
43  An \code{xmlHashTree} object has an accessor method via
44  \code{$} for accessing individual  nodes within the tree.
45  One can use the node name/identifier in an expression such as
46  \code{tt$myNode} to obtain the element.
47  The name of a node is either its XML node name or if that is already
48  present in the tree, a machine generated name.
49
50  One can find the names of all the nodes using the
51  \code{objects} function since these trees are regular
52  environments in R.
53  Using the \code{all = TRUE} argument, one can also find the
54  \dQuote{hidden} elements that make define the tree's structure.
55  These are \code{.children} and \code{.parents}.
56  The former is an (hashed) environment. Each element is identified by the
57  node in the tree by the node's identifier (corresponding to the
58  name of the node in the tree's environment).
59  The value of that element is simply a character vector giving the
60  identifiers of all of the children of that node.
61
62  The \code{.parents} element is also an environemnt.
63  Each element in this gives the pair of node and parent identifiers
64  with the parent identifier being the value of the variable in the
65  environment. In other words, we look up the parent of a node
66  named 'kid' by retrieving the value of the variable 'kid' in the
67  \code{.parents} environment of this hash tree.
68
69  The function \code{.addNode} is used to insert a new node into the
70  tree.
71
72  The structure of this tree allows one to easily travers all nodes,
73  navigate up the tree from a node via its parent.  Certain tasks are
74  more complex as the hierarchy is not implicit within a node.
75}
76\references{\url{http://www.w3.org/XML}}
77\author{ Duncan Temple Lang }
78
79\seealso{
80  \code{\link{xmlTreeParse}}
81  \code{\link{xmlTree}}
82  \code{\link{xmlOutputBuffer}}
83  \code{\link{xmlOutputDOM}}
84}
85\examples{
86 f = system.file("exampleData", "dataframe.xml", package = "XML")
87 tr  = xmlHashTree()
88 xmlTreeParse(f, handlers = list(.startElement = tr[[".addNode"]]))
89
90 tr # print the tree on the screen
91
92  # Get the two child nodes of the dataframe node.
93 xmlChildren(tr$dataframe)
94
95  # Find the names of all the nodes.
96 objects(tr)
97  # Which nodes have children
98 objects(tr$.children)
99
100  # Which nodes are leaves, i.e. do not have children
101 setdiff(objects(tr), objects(tr$.children))
102
103  # find the class of each of these leaf nodes.
104 sapply(setdiff(objects(tr), objects(tr$.children)),
105         function(id) class(tr[[id]]))
106
107  # distribution of number of children
108 sapply(tr$.children, length)
109
110
111  # Get the first A node
112 tr$A
113
114  # Get is parent node.
115 xmlParent(tr$A)
116
117
118 f = system.file("exampleData", "allNodeTypes.xml", package = "XML")
119
120   # Convert the document
121 r = xmlInternalTreeParse(f, xinclude = TRUE)
122 ht = as(r, "XMLHashTree")
123 ht
124
125  # work on the root node, or any node actually
126 as(xmlRoot(r), "XMLHashTree")
127
128  # Example of making copies of an XMLHashTreeNode object to create a separate tree.
129 f = system.file("exampleData", "simple.xml", package = "XML")
130 tt = as(xmlParse(f), "XMLHashTree")
131
132 xmlRoot(tt)[[1]]
133 xmlRoot(tt)[[1, copy = TRUE]]
134
135 table(unlist(eapply(tt, xmlName)))
136 # if any of the nodes had any attributes
137 # table(unlist(eapply(tt, xmlAttrs)))
138}
139\keyword{IO}
140\concept{XML}
141