Unit tests for nltk.tree.Tree

>>> from nltk.tree import *

Some trees to run tests on:

>>> dp1 = Tree('dp', [Tree('d', ['the']), Tree('np', ['dog'])])
>>> dp2 = Tree('dp', [Tree('d', ['the']), Tree('np', ['cat'])])
>>> vp = Tree('vp', [Tree('v', ['chased']), dp2])
>>> tree = Tree('s', [dp1, vp])
>>> print(tree)
(s (dp (d the) (np dog)) (vp (v chased) (dp (d the) (np cat))))

The node label is accessed using the label() method:

>>> dp1.label(), dp2.label(), vp.label(), tree.label()
('dp', 'dp', 'vp', 's')
>>> print(tree[1,1,1,0])
cat

The treepositions method returns a list of the tree positions of subtrees and leaves in a tree. By default, it gives the position of every tree, subtree, and leaf, in prefix order:

>>> print(tree.treepositions())
[(), (0,), (0, 0), (0, 0, 0), (0, 1), (0, 1, 0), (1,), (1, 0), (1, 0, 0), (1, 1), (1, 1, 0), (1, 1, 0, 0), (1, 1, 1), (1, 1, 1, 0)]

In addition to str and repr, several methods exist to convert a tree object to one of several standard tree encodings:

>>> print(tree.pformat_latex_qtree())
\Tree [.s
        [.dp [.d the ] [.np dog ] ]
        [.vp [.v chased ] [.dp [.d the ] [.np cat ] ] ] ]

There is also a fancy ASCII art representation:

>>> tree.pretty_print()
              s
      ________|_____
     |              vp
     |         _____|___
     dp       |         dp
  ___|___     |      ___|___
 d       np   v     d       np
 |       |    |     |       |
the     dog chased the     cat
>>> tree.pretty_print(unicodelines=True, nodedist=4)
                       s
        ┌──────────────┴────────┐
        │                       vp
        │              ┌────────┴──────┐
        dp             │               dp
 ┌──────┴──────┐       │        ┌──────┴──────┐
 d             np      v        d             np
 │             │       │        │             │
the           dog    chased    the           cat

Trees can be initialized from treebank strings:

>>> tree2 = Tree.fromstring('(S (NP I) (VP (V enjoyed) (NP my cookie)))')
>>> print(tree2)
(S (NP I) (VP (V enjoyed) (NP my cookie)))

Trees can be compared for equality:

>>> tree == Tree.fromstring(str(tree))
True
>>> tree2 == Tree.fromstring(str(tree2))
True
>>> tree == tree2
False
>>> tree == Tree.fromstring(str(tree2))
False
>>> tree2 == Tree.fromstring(str(tree))
False
>>> tree != Tree.fromstring(str(tree))
False
>>> tree2 != Tree.fromstring(str(tree2))
False
>>> tree != tree2
True
>>> tree != Tree.fromstring(str(tree2))
True
>>> tree2 != Tree.fromstring(str(tree))
True
>>> tree < tree2 or tree > tree2
True

Tree Parsing

The class method Tree.fromstring() can be used to parse trees, and it provides some additional options.

>>> tree = Tree.fromstring('(S (NP I) (VP (V enjoyed) (NP my cookie)))')
>>> print(tree)
(S (NP I) (VP (V enjoyed) (NP my cookie)))

When called on a subclass of Tree, it will create trees of that type:

>>> tree = ImmutableTree.fromstring('(VP (V enjoyed) (NP my cookie))')
>>> print(tree)
(VP (V enjoyed) (NP my cookie))
>>> print(type(tree))
<class 'nltk.tree.ImmutableTree'>
>>> tree[1] = 'x'
Traceback (most recent call last):
  . . .
ValueError: ImmutableTree may not be modified
>>> del tree[0]
Traceback (most recent call last):
  . . .
ValueError: ImmutableTree may not be modified

The brackets parameter can be used to specify two characters that should be used as brackets:

>>> print(Tree.fromstring('[S [NP I] [VP [V enjoyed] [NP my cookie]]]',
...                  brackets='[]'))
(S (NP I) (VP (V enjoyed) (NP my cookie)))
>>> print(Tree.fromstring('<S <NP I> <VP <V enjoyed> <NP my cookie>>>',
...                  brackets='<>'))
(S (NP I) (VP (V enjoyed) (NP my cookie)))

If brackets is not a string, or is not exactly two characters, then Tree.fromstring raises an exception:

>>> Tree.fromstring('<VP <V enjoyed> <NP my cookie>>', brackets='')
Traceback (most recent call last):
  . . .
TypeError: brackets must be a length-2 string
>>> Tree.fromstring('<VP <V enjoyed> <NP my cookie>>', brackets='<<>>')
Traceback (most recent call last):
  . . .
TypeError: brackets must be a length-2 string
>>> Tree.fromstring('<VP <V enjoyed> <NP my cookie>>', brackets=12)
Traceback (most recent call last):
  . . .
TypeError: brackets must be a length-2 string
>>> Tree.fromstring('<<NP my cookie>>', brackets=('<<','>>'))
Traceback (most recent call last):
  . . .
TypeError: brackets must be a length-2 string

(We may add support for multi-character brackets in the future, in which case the brackets=('<<','>>') example would start working.)

Whitespace brackets are not permitted:

>>> Tree.fromstring('(NP my cookie\n', brackets='(\n')
Traceback (most recent call last):
  . . .
TypeError: whitespace brackets not allowed

If an invalid tree is given to Tree.fromstring, then it raises a ValueError, with a description of the problem:

>>> Tree.fromstring('(NP my cookie) (NP my milk)')
Traceback (most recent call last):
  . . .
ValueError: Tree.fromstring(): expected 'end-of-string' but got '(NP'
            at index 15.
                "...y cookie) (NP my mil..."
                              ^
>>> Tree.fromstring(')NP my cookie(')
Traceback (most recent call last):
  . . .
ValueError: Tree.fromstring(): expected '(' but got ')'
            at index 0.
                ")NP my coo..."
                 ^
>>> Tree.fromstring('(NP my cookie))')
Traceback (most recent call last):
  . . .
ValueError: Tree.fromstring(): expected 'end-of-string' but got ')'
            at index 14.
                "...my cookie))"
                              ^
>>> Tree.fromstring('my cookie)')
Traceback (most recent call last):
  . . .
ValueError: Tree.fromstring(): expected '(' but got 'my'
            at index 0.
                "my cookie)"
                 ^
>>> Tree.fromstring('(NP my cookie')
Traceback (most recent call last):
  . . .
ValueError: Tree.fromstring(): expected ')' but got 'end-of-string'
            at index 13.
                "... my cookie"
                              ^
>>> Tree.fromstring('')
Traceback (most recent call last):
  . . .
ValueError: Tree.fromstring(): expected '(' but got 'end-of-string'
            at index 0.
                ""
                 ^

Trees with no children are supported:

>>> print(Tree.fromstring('(S)'))
(S )
>>> print(Tree.fromstring('(X (Y) (Z))'))
(X (Y ) (Z ))

Trees with an empty node label and no children are supported:

>>> print(Tree.fromstring('()'))
( )
>>> print(Tree.fromstring('(X () ())'))
(X ( ) ( ))

Trees with an empty node label and children are supported, but only if the first child is not a leaf (otherwise, it will be treated as the node label).

>>> print(Tree.fromstring('((A) (B) (C))'))
( (A ) (B ) (C ))
>>> print(Tree.fromstring('((A) leaf)'))
( (A ) leaf)
>>> print(Tree.fromstring('(((())))'))
( ( ( ( ))))

The optional arguments read_node and read_leaf may be used to transform the string values of nodes or leaves.

>>> print(Tree.fromstring('(A b (C d e) (F (G h i)))',
...                  read_node=lambda s: '<%s>' % s,
...                  read_leaf=lambda s: '"%s"' % s))
(<A> "b" (<C> "d" "e") (<F> (<G> "h" "i")))

These transformation functions are typically used when the node or leaf labels should be parsed to a non-string value (such as a feature structure). If node and leaf labels need to be able to include whitespace, then you must also use the optional node_pattern and leaf_pattern arguments.

>>> from nltk.featstruct import FeatStruct
>>> tree = Tree.fromstring('([cat=NP] [lex=the] [lex=dog])',
...                   read_node=FeatStruct, read_leaf=FeatStruct)
>>> tree.set_label(tree.label().unify(FeatStruct('[num=singular]')))
>>> print(tree)
([cat='NP', num='singular'] [lex='the'] [lex='dog'])

The optional argument remove_empty_top_bracketing can be used to remove any top-level empty bracketing that occurs.

>>> print(Tree.fromstring('((S (NP I) (VP (V enjoyed) (NP my cookie))))',
...                  remove_empty_top_bracketing=True))
(S (NP I) (VP (V enjoyed) (NP my cookie)))

It will not remove a top-level empty bracketing with multiple children:

>>> print(Tree.fromstring('((A a) (B b))'))
( (A a) (B b))

Parented Trees

ParentedTree is a subclass of Tree that automatically maintains parent pointers for single-parented trees. Parented trees can be created directly from a node label and a list of children:

>>> ptree = (
...     ParentedTree('VP', [
...         ParentedTree('VERB', ['saw']),
...         ParentedTree('NP', [
...             ParentedTree('DET', ['the']),
...             ParentedTree('NOUN', ['dog'])])]))
>>> print(ptree)
(VP (VERB saw) (NP (DET the) (NOUN dog)))

Parented trees can be created from strings using the classmethod ParentedTree.fromstring:

>>> ptree = ParentedTree.fromstring('(VP (VERB saw) (NP (DET the) (NOUN dog)))')
>>> print(ptree)
(VP (VERB saw) (NP (DET the) (NOUN dog)))
>>> print(type(ptree))
<class 'nltk.tree.ParentedTree'>

Parented trees can also be created by using the classmethod ParentedTree.convert to convert another type of tree to a parented tree:

>>> tree = Tree.fromstring('(VP (VERB saw) (NP (DET the) (NOUN dog)))')
>>> ptree = ParentedTree.convert(tree)
>>> print(ptree)
(VP (VERB saw) (NP (DET the) (NOUN dog)))
>>> print(type(ptree))
<class 'nltk.tree.ParentedTree'>

ParentedTrees should never be used in the same tree as Trees or MultiParentedTrees. Mixing tree implementations may result in incorrect parent pointers and in TypeError exceptions:

>>> # Inserting a Tree in a ParentedTree gives an exception:
>>> ParentedTree('NP', [
...     Tree('DET', ['the']), Tree('NOUN', ['dog'])])
Traceback (most recent call last):
  . . .
TypeError: Can not insert a non-ParentedTree into a ParentedTree
>>> # inserting a ParentedTree in a Tree gives incorrect parent pointers:
>>> broken_tree = Tree('NP', [
...     ParentedTree('DET', ['the']), ParentedTree('NOUN', ['dog'])])
>>> print(broken_tree[0].parent())
None

Parented Tree Methods

In addition to all the methods defined by the Tree class, the ParentedTree class adds six new methods whose values are automatically updated whenver a parented tree is modified: parent(), parent_index(), left_sibling(), right_sibling(), root(), and treeposition().

The parent() method contains a ParentedTree's parent, if it has one; and None otherwise. ParentedTrees that do not have parents are known as "root trees."

>>> for subtree in ptree.subtrees():
...     print(subtree)
...     print('  Parent = %s' % subtree.parent())
(VP (VERB saw) (NP (DET the) (NOUN dog)))
  Parent = None
(VERB saw)
  Parent = (VP (VERB saw) (NP (DET the) (NOUN dog)))
(NP (DET the) (NOUN dog))
  Parent = (VP (VERB saw) (NP (DET the) (NOUN dog)))
(DET the)
  Parent = (NP (DET the) (NOUN dog))
(NOUN dog)
  Parent = (NP (DET the) (NOUN dog))

The parent_index() method stores the index of a tree in its parent's child list. If a tree does not have a parent, then its parent_index is None.

>>> for subtree in ptree.subtrees():
...     print(subtree)
...     print('  Parent Index = %s' % subtree.parent_index())
...     assert (subtree.parent() is None or
...             subtree.parent()[subtree.parent_index()] is subtree)
(VP (VERB saw) (NP (DET the) (NOUN dog)))
  Parent Index = None
(VERB saw)
  Parent Index = 0
(NP (DET the) (NOUN dog))
  Parent Index = 1
(DET the)
  Parent Index = 0
(NOUN dog)
  Parent Index = 1

Note that ptree.parent().index(ptree) is not equivalent to ptree.parent_index(). In particular, ptree.parent().index(ptree) will return the index of the first child of ptree.parent() that is equal to ptree (using ==); and that child may not be ptree:

>>> on_and_on = ParentedTree('CONJP', [
...     ParentedTree('PREP', ['on']),
...     ParentedTree('COJN', ['and']),
...     ParentedTree('PREP', ['on'])])
>>> second_on = on_and_on[2]
>>> print(second_on.parent_index())
2
>>> print(second_on.parent().index(second_on))
0

The methods left_sibling() and right_sibling() can be used to get a parented tree's siblings. If a tree does not have a left or right sibling, then the corresponding method's value is None:

>>> for subtree in ptree.subtrees():
...     print(subtree)
...     print('  Left Sibling  = %s' % subtree.left_sibling())
...     print('  Right Sibling = %s' % subtree.right_sibling())
(VP (VERB saw) (NP (DET the) (NOUN dog)))
  Left Sibling  = None
  Right Sibling = None
(VERB saw)
  Left Sibling  = None
  Right Sibling = (NP (DET the) (NOUN dog))
(NP (DET the) (NOUN dog))
  Left Sibling  = (VERB saw)
  Right Sibling = None
(DET the)
  Left Sibling  = None
  Right Sibling = (NOUN dog)
(NOUN dog)
  Left Sibling  = (DET the)
  Right Sibling = None

A parented tree's root tree can be accessed using the root() method. This method follows the tree's parent pointers until it finds a tree without a parent. If a tree does not have a parent, then it is its own root:

>>> for subtree in ptree.subtrees():
...     print(subtree)
...     print('  Root = %s' % subtree.root())
(VP (VERB saw) (NP (DET the) (NOUN dog)))
  Root = (VP (VERB saw) (NP (DET the) (NOUN dog)))
(VERB saw)
  Root = (VP (VERB saw) (NP (DET the) (NOUN dog)))
(NP (DET the) (NOUN dog))
  Root = (VP (VERB saw) (NP (DET the) (NOUN dog)))
(DET the)
  Root = (VP (VERB saw) (NP (DET the) (NOUN dog)))
(NOUN dog)
  Root = (VP (VERB saw) (NP (DET the) (NOUN dog)))

The treeposition() method can be used to find a tree's treeposition relative to its root:

>>> for subtree in ptree.subtrees():
...     print(subtree)
...     print('  Tree Position = %s' % (subtree.treeposition(),))
...     assert subtree.root()[subtree.treeposition()] is subtree
(VP (VERB saw) (NP (DET the) (NOUN dog)))
  Tree Position = ()
(VERB saw)
  Tree Position = (0,)
(NP (DET the) (NOUN dog))
  Tree Position = (1,)
(DET the)
  Tree Position = (1, 0)
(NOUN dog)
  Tree Position = (1, 1)

Whenever a parented tree is modified, all of the methods described above (parent(), parent_index(), left_sibling(), right_sibling(), root(), and treeposition()) are automatically updated. For example, if we replace ptree's subtree for the word "dog" with a new subtree for "cat," the method values for both the "dog" subtree and the "cat" subtree get automatically updated:

>>> # Replace the dog with a cat
>>> dog = ptree[1,1]
>>> cat = ParentedTree('NOUN', ['cat'])
>>> ptree[1,1] = cat
>>> # the noun phrase is no longer the dog's parent:
>>> print(dog.parent(), dog.parent_index(), dog.left_sibling())
None None None
>>> # dog is now its own root.
>>> print(dog.root())
(NOUN dog)
>>> print(dog.treeposition())
()
>>> # the cat's parent is now the noun phrase:
>>> print(cat.parent())
(NP (DET the) (NOUN cat))
>>> print(cat.parent_index())
1
>>> print(cat.left_sibling())
(DET the)
>>> print(cat.root())
(VP (VERB saw) (NP (DET the) (NOUN cat)))
>>> print(cat.treeposition())
(1, 1)

ParentedTree Regression Tests

Keep track of all trees that we create (including subtrees) using this variable:

>>> all_ptrees = []

Define a helper funciton to create new parented trees:

>>> def make_ptree(s):
...     ptree = ParentedTree.convert(Tree.fromstring(s))
...     all_ptrees.extend(t for t in ptree.subtrees()
...                       if isinstance(t, Tree))
...     return ptree

Define a test function that examines every subtree in all_ptrees; and checks that all six of its methods are defined correctly. If any ptrees are passed as arguments, then they are printed.

>>> def pcheck(*print_ptrees):
...     for ptree in all_ptrees:
...         # Check ptree's methods.
...         if ptree.parent() is not None:
...             i = ptree.parent_index()
...             assert ptree.parent()[i] is ptree
...             if i > 0:
...                 assert ptree.left_sibling() is ptree.parent()[i-1]
...             if i < (len(ptree.parent())-1):
...                 assert ptree.right_sibling() is ptree.parent()[i+1]
...             assert len(ptree.treeposition()) > 0
...             assert (ptree.treeposition() ==
...                     ptree.parent().treeposition() + (ptree.parent_index(),))
...             assert ptree.root() is not ptree
...             assert ptree.root() is not None
...             assert ptree.root() is ptree.parent().root()
...             assert ptree.root()[ptree.treeposition()] is ptree
...         else:
...             assert ptree.parent_index() is None
...             assert ptree.left_sibling() is None
...             assert ptree.right_sibling() is None
...             assert ptree.root() is ptree
...             assert ptree.treeposition() == ()
...         # Check ptree's children's methods:
...         for i, child in enumerate(ptree):
...             if isinstance(child, Tree):
...                 # pcheck parent() & parent_index() methods
...                 assert child.parent() is ptree
...                 assert child.parent_index() == i
...                 # pcheck sibling methods
...                 if i == 0:
...                     assert child.left_sibling() is None
...                 else:
...                     assert child.left_sibling() is ptree[i-1]
...                 if i == len(ptree)-1:
...                     assert child.right_sibling() is None
...                 else:
...                     assert child.right_sibling() is ptree[i+1]
...     if print_ptrees:
...         print('ok!', end=' ')
...         for ptree in print_ptrees: print(ptree)
...     else:
...         print('ok!')

Run our test function on a variety of newly-created trees:

>>> pcheck(make_ptree('(A)'))
ok! (A )
>>> pcheck(make_ptree('(A (B (C (D) (E f)) g) h)'))
ok! (A (B (C (D ) (E f)) g) h)
>>> pcheck(make_ptree('(A (B) (C c) (D d d) (E e e e))'))
ok! (A (B ) (C c) (D d d) (E e e e))
>>> pcheck(make_ptree('(A (B) (C (c)) (D (d) (d)) (E (e) (e) (e)))'))
ok! (A (B ) (C (c )) (D (d ) (d )) (E (e ) (e ) (e )))

Run our test function after performing various tree-modification operations:

__delitem__()

>>> ptree = make_ptree('(A (B (C (D) (E f) (Q p)) g) h)')
>>> e = ptree[0,0,1]
>>> del ptree[0,0,1]; pcheck(ptree); pcheck(e)
ok! (A (B (C (D ) (Q p)) g) h)
ok! (E f)
>>> del ptree[0,0,0]; pcheck(ptree)
ok! (A (B (C (Q p)) g) h)
>>> del ptree[0,1]; pcheck(ptree)
ok! (A (B (C (Q p))) h)
>>> del ptree[-1]; pcheck(ptree)
ok! (A (B (C (Q p))))
>>> del ptree[-100]
Traceback (most recent call last):
  . . .
IndexError: index out of range
>>> del ptree[()]
Traceback (most recent call last):
  . . .
IndexError: The tree position () may not be deleted.
>>> # With slices:
>>> ptree = make_ptree('(A (B c) (D e) f g (H i) j (K l))')
>>> b = ptree[0]
>>> del ptree[0:0]; pcheck(ptree)
ok! (A (B c) (D e) f g (H i) j (K l))
>>> del ptree[:1]; pcheck(ptree); pcheck(b)
ok! (A (D e) f g (H i) j (K l))
ok! (B c)
>>> del ptree[-2:]; pcheck(ptree)
ok! (A (D e) f g (H i))
>>> del ptree[1:3]; pcheck(ptree)
ok! (A (D e) (H i))
>>> ptree = make_ptree('(A (B c) (D e) f g (H i) j (K l))')
>>> del ptree[5:1000]; pcheck(ptree)
ok! (A (B c) (D e) f g (H i))
>>> del ptree[-2:1000]; pcheck(ptree)
ok! (A (B c) (D e) f)
>>> del ptree[-100:1]; pcheck(ptree)
ok! (A (D e) f)
>>> ptree = make_ptree('(A (B c) (D e) f g (H i) j (K l))')
>>> del ptree[1:-2:2]; pcheck(ptree)
ok! (A (B c) f (H i) j (K l))

__setitem__()

>>> ptree = make_ptree('(A (B (C (D) (E f) (Q p)) g) h)')
>>> d, e, q = ptree[0,0]
>>> ptree[0,0,0] = 'x'; pcheck(ptree); pcheck(d)
ok! (A (B (C x (E f) (Q p)) g) h)
ok! (D )
>>> ptree[0,0,1] = make_ptree('(X (Y z))'); pcheck(ptree); pcheck(e)
ok! (A (B (C x (X (Y z)) (Q p)) g) h)
ok! (E f)
>>> ptree[1] = d; pcheck(ptree)
ok! (A (B (C x (X (Y z)) (Q p)) g) (D ))
>>> ptree[-1] = 'x'; pcheck(ptree)
ok! (A (B (C x (X (Y z)) (Q p)) g) x)
>>> ptree[-100] = 'y'
Traceback (most recent call last):
  . . .
IndexError: index out of range
>>> ptree[()] = make_ptree('(X y)')
Traceback (most recent call last):
  . . .
IndexError: The tree position () may not be assigned to.
>>> # With slices:
>>> ptree = make_ptree('(A (B c) (D e) f g (H i) j (K l))')
>>> b = ptree[0]
>>> ptree[0:0] = ('x', make_ptree('(Y)')); pcheck(ptree)
ok! (A x (Y ) (B c) (D e) f g (H i) j (K l))
>>> ptree[2:6] = (); pcheck(ptree); pcheck(b)
ok! (A x (Y ) (H i) j (K l))
ok! (B c)
>>> ptree[-2:] = ('z', 'p'); pcheck(ptree)
ok! (A x (Y ) (H i) z p)
>>> ptree[1:3] = [make_ptree('(X)') for x in range(10)]; pcheck(ptree)
ok! (A x (X ) (X ) (X ) (X ) (X ) (X ) (X ) (X ) (X ) (X ) z p)
>>> ptree[5:1000] = []; pcheck(ptree)
ok! (A x (X ) (X ) (X ) (X ))
>>> ptree[-2:1000] = ['n']; pcheck(ptree)
ok! (A x (X ) (X ) n)
>>> ptree[-100:1] = [make_ptree('(U v)')]; pcheck(ptree)
ok! (A (U v) (X ) (X ) n)
>>> ptree[-1:] = (make_ptree('(X)') for x in range(3)); pcheck(ptree)
ok! (A (U v) (X ) (X ) (X ) (X ) (X ))
>>> ptree[1:-2:2] = ['x', 'y']; pcheck(ptree)
ok! (A (U v) x (X ) y (X ) (X ))

append()

>>> ptree = make_ptree('(A (B (C (D) (E f) (Q p)) g) h)')
>>> ptree.append('x'); pcheck(ptree)
ok! (A (B (C (D ) (E f) (Q p)) g) h x)
>>> ptree.append(make_ptree('(X (Y z))')); pcheck(ptree)
ok! (A (B (C (D ) (E f) (Q p)) g) h x (X (Y z)))

extend()

>>> ptree = make_ptree('(A (B (C (D) (E f) (Q p)) g) h)')
>>> ptree.extend(['x', 'y', make_ptree('(X (Y z))')]); pcheck(ptree)
ok! (A (B (C (D ) (E f) (Q p)) g) h x y (X (Y z)))
>>> ptree.extend([]); pcheck(ptree)
ok! (A (B (C (D ) (E f) (Q p)) g) h x y (X (Y z)))
>>> ptree.extend(make_ptree('(X)') for x in range(3)); pcheck(ptree)
ok! (A (B (C (D ) (E f) (Q p)) g) h x y (X (Y z)) (X ) (X ) (X ))

insert()

>>> ptree = make_ptree('(A (B (C (D) (E f) (Q p)) g) h)')
>>> ptree.insert(0, make_ptree('(X (Y z))')); pcheck(ptree)
ok! (A (X (Y z)) (B (C (D ) (E f) (Q p)) g) h)
>>> ptree.insert(-1, make_ptree('(X (Y z))')); pcheck(ptree)
ok! (A (X (Y z)) (B (C (D ) (E f) (Q p)) g) (X (Y z)) h)
>>> ptree.insert(-4, make_ptree('(X (Y z))')); pcheck(ptree)
ok! (A (X (Y z)) (X (Y z)) (B (C (D ) (E f) (Q p)) g) (X (Y z)) h)
>>> # Note: as with ``list``, inserting at a negative index that
>>> # gives a position before the start of the list does *not*
>>> # raise an IndexError exception; it just inserts at 0.
>>> ptree.insert(-400, make_ptree('(X (Y z))')); pcheck(ptree)
ok! (A
  (X (Y z))
  (X (Y z))
  (X (Y z))
  (B (C (D ) (E f) (Q p)) g)
  (X (Y z))
  h)

pop()

>>> ptree = make_ptree('(A (B (C (D) (E f) (Q p)) g) h)')
>>> ptree[0,0].pop(1); pcheck(ptree)
ParentedTree('E', ['f'])
ok! (A (B (C (D ) (Q p)) g) h)
>>> ptree[0].pop(-1); pcheck(ptree)
'g'
ok! (A (B (C (D ) (Q p))) h)
>>> ptree.pop(); pcheck(ptree)
'h'
ok! (A (B (C (D ) (Q p))))
>>> ptree.pop(-100)
Traceback (most recent call last):
  . . .
IndexError: index out of range

remove()

>>> ptree = make_ptree('(A (B (C (D) (E f) (Q p)) g) h)')
>>> e = ptree[0,0,1]
>>> ptree[0,0].remove(ptree[0,0,1]); pcheck(ptree); pcheck(e)
ok! (A (B (C (D ) (Q p)) g) h)
ok! (E f)
>>> ptree[0,0].remove(make_ptree('(Q p)')); pcheck(ptree)
ok! (A (B (C (D )) g) h)
>>> ptree[0,0].remove(make_ptree('(Q p)'))
Traceback (most recent call last):
  . . .
ValueError: ParentedTree('Q', ['p']) is not in list
>>> ptree.remove('h'); pcheck(ptree)
ok! (A (B (C (D )) g))
>>> ptree.remove('h');
Traceback (most recent call last):
  . . .
ValueError: 'h' is not in list
>>> # remove() removes the first subtree that is equal (==) to the
>>> # given tree, which may not be the identical tree we give it:
>>> ptree = make_ptree('(A (X x) (Y y) (X x))')
>>> x1, y, x2 = ptree
>>> ptree.remove(ptree[-1]); pcheck(ptree)
ok! (A (Y y) (X x))
>>> print(x1.parent()); pcheck(x1)
None
ok! (X x)
>>> print(x2.parent())
(A (Y y) (X x))

Test that a tree can not be given multiple parents:

>>> ptree = make_ptree('(A (X x) (Y y) (Z z))')
>>> ptree[0] = ptree[1]
Traceback (most recent call last):
  . . .
ValueError: Can not insert a subtree that already has a parent.
>>> pcheck()
ok!

[more to be written]

ImmutableParentedTree Regression Tests

>>> iptree = ImmutableParentedTree.convert(ptree)
>>> type(iptree)
<class 'nltk.tree.ImmutableParentedTree'>
>>> del iptree[0]
Traceback (most recent call last):
  . . .
ValueError: ImmutableParentedTree may not be modified
>>> iptree.set_label('newnode')
Traceback (most recent call last):
  . . .
ValueError: ImmutableParentedTree may not be modified

MultiParentedTree Regression Tests

Keep track of all trees that we create (including subtrees) using this variable:

>>> all_mptrees = []

Define a helper funciton to create new parented trees:

>>> def make_mptree(s):
...     mptree = MultiParentedTree.convert(Tree.fromstring(s))
...     all_mptrees.extend(t for t in mptree.subtrees()
...                       if isinstance(t, Tree))
...     return mptree

Define a test function that examines every subtree in all_mptrees; and checks that all six of its methods are defined correctly. If any mptrees are passed as arguments, then they are printed.

>>> def mpcheck(*print_mptrees):
...     def has(seq, val): # uses identity comparison
...         for item in seq:
...             if item is val: return True
...         return False
...     for mptree in all_mptrees:
...         # Check mptree's methods.
...         if len(mptree.parents()) == 0:
...             assert len(mptree.left_siblings()) == 0
...             assert len(mptree.right_siblings()) == 0
...             assert len(mptree.roots()) == 1
...             assert mptree.roots()[0] is mptree
...             assert mptree.treepositions(mptree) == [()]
...             left_siblings = right_siblings = ()
...             roots = {id(mptree): 1}
...         else:
...             roots = dict((id(r), 0) for r in mptree.roots())
...             left_siblings = mptree.left_siblings()
...             right_siblings = mptree.right_siblings()
...         for parent in mptree.parents():
...             for i in mptree.parent_indices(parent):
...                 assert parent[i] is mptree
...                 # check left siblings
...                 if i > 0:
...                     for j in range(len(left_siblings)):
...                         if left_siblings[j] is parent[i-1]:
...                             del left_siblings[j]
...                             break
...                     else:
...                         assert 0, 'sibling not found!'
...                 # check ight siblings
...                 if i < (len(parent)-1):
...                     for j in range(len(right_siblings)):
...                         if right_siblings[j] is parent[i+1]:
...                             del right_siblings[j]
...                             break
...                     else:
...                         assert 0, 'sibling not found!'
...             # check roots
...             for root in parent.roots():
...                 assert id(root) in roots, 'missing root'
...                 roots[id(root)] += 1
...         # check that we don't have any unexplained values
...         assert len(left_siblings)==0, 'unexpected sibling'
...         assert len(right_siblings)==0, 'unexpected sibling'
...         for v in roots.values(): assert v>0, roots #'unexpected root'
...         # check treepositions
...         for root in mptree.roots():
...             for treepos in mptree.treepositions(root):
...                 assert root[treepos] is mptree
...         # Check mptree's children's methods:
...         for i, child in enumerate(mptree):
...             if isinstance(child, Tree):
...                 # mpcheck parent() & parent_index() methods
...                 assert has(child.parents(), mptree)
...                 assert i in child.parent_indices(mptree)
...                 # mpcheck sibling methods
...                 if i > 0:
...                     assert has(child.left_siblings(), mptree[i-1])
...                 if i < len(mptree)-1:
...                     assert has(child.right_siblings(), mptree[i+1])
...     if print_mptrees:
...         print('ok!', end=' ')
...         for mptree in print_mptrees: print(mptree)
...     else:
...         print('ok!')

Run our test function on a variety of newly-created trees:

>>> mpcheck(make_mptree('(A)'))
ok! (A )
>>> mpcheck(make_mptree('(A (B (C (D) (E f)) g) h)'))
ok! (A (B (C (D ) (E f)) g) h)
>>> mpcheck(make_mptree('(A (B) (C c) (D d d) (E e e e))'))
ok! (A (B ) (C c) (D d d) (E e e e))
>>> mpcheck(make_mptree('(A (B) (C (c)) (D (d) (d)) (E (e) (e) (e)))'))
ok! (A (B ) (C (c )) (D (d ) (d )) (E (e ) (e ) (e )))
>>> subtree = make_mptree('(A (B (C (D) (E f)) g) h)')

Including some trees that contain multiple parents:

>>> mpcheck(MultiParentedTree('Z', [subtree, subtree]))
ok! (Z (A (B (C (D ) (E f)) g) h) (A (B (C (D ) (E f)) g) h))

Run our test function after performing various tree-modification operations (n.b., these are the same tests that we ran for ParentedTree, above; thus, none of these trees actually uses multiple parents.)

__delitem__()

>>> mptree = make_mptree('(A (B (C (D) (E f) (Q p)) g) h)')
>>> e = mptree[0,0,1]
>>> del mptree[0,0,1]; mpcheck(mptree); mpcheck(e)
ok! (A (B (C (D ) (Q p)) g) h)
ok! (E f)
>>> del mptree[0,0,0]; mpcheck(mptree)
ok! (A (B (C (Q p)) g) h)
>>> del mptree[0,1]; mpcheck(mptree)
ok! (A (B (C (Q p))) h)
>>> del mptree[-1]; mpcheck(mptree)
ok! (A (B (C (Q p))))
>>> del mptree[-100]
Traceback (most recent call last):
  . . .
IndexError: index out of range
>>> del mptree[()]
Traceback (most recent call last):
  . . .
IndexError: The tree position () may not be deleted.
>>> # With slices:
>>> mptree = make_mptree('(A (B c) (D e) f g (H i) j (K l))')
>>> b = mptree[0]
>>> del mptree[0:0]; mpcheck(mptree)
ok! (A (B c) (D e) f g (H i) j (K l))
>>> del mptree[:1]; mpcheck(mptree); mpcheck(b)
ok! (A (D e) f g (H i) j (K l))
ok! (B c)
>>> del mptree[-2:]; mpcheck(mptree)
ok! (A (D e) f g (H i))
>>> del mptree[1:3]; mpcheck(mptree)
ok! (A (D e) (H i))
>>> mptree = make_mptree('(A (B c) (D e) f g (H i) j (K l))')
>>> del mptree[5:1000]; mpcheck(mptree)
ok! (A (B c) (D e) f g (H i))
>>> del mptree[-2:1000]; mpcheck(mptree)
ok! (A (B c) (D e) f)
>>> del mptree[-100:1]; mpcheck(mptree)
ok! (A (D e) f)
>>> mptree = make_mptree('(A (B c) (D e) f g (H i) j (K l))')
>>> del mptree[1:-2:2]; mpcheck(mptree)
ok! (A (B c) f (H i) j (K l))

__setitem__()

>>> mptree = make_mptree('(A (B (C (D) (E f) (Q p)) g) h)')
>>> d, e, q = mptree[0,0]
>>> mptree[0,0,0] = 'x'; mpcheck(mptree); mpcheck(d)
ok! (A (B (C x (E f) (Q p)) g) h)
ok! (D )
>>> mptree[0,0,1] = make_mptree('(X (Y z))'); mpcheck(mptree); mpcheck(e)
ok! (A (B (C x (X (Y z)) (Q p)) g) h)
ok! (E f)
>>> mptree[1] = d; mpcheck(mptree)
ok! (A (B (C x (X (Y z)) (Q p)) g) (D ))
>>> mptree[-1] = 'x'; mpcheck(mptree)
ok! (A (B (C x (X (Y z)) (Q p)) g) x)
>>> mptree[-100] = 'y'
Traceback (most recent call last):
  . . .
IndexError: index out of range
>>> mptree[()] = make_mptree('(X y)')
Traceback (most recent call last):
  . . .
IndexError: The tree position () may not be assigned to.
>>> # With slices:
>>> mptree = make_mptree('(A (B c) (D e) f g (H i) j (K l))')
>>> b = mptree[0]
>>> mptree[0:0] = ('x', make_mptree('(Y)')); mpcheck(mptree)
ok! (A x (Y ) (B c) (D e) f g (H i) j (K l))
>>> mptree[2:6] = (); mpcheck(mptree); mpcheck(b)
ok! (A x (Y ) (H i) j (K l))
ok! (B c)
>>> mptree[-2:] = ('z', 'p'); mpcheck(mptree)
ok! (A x (Y ) (H i) z p)
>>> mptree[1:3] = [make_mptree('(X)') for x in range(10)]; mpcheck(mptree)
ok! (A x (X ) (X ) (X ) (X ) (X ) (X ) (X ) (X ) (X ) (X ) z p)
>>> mptree[5:1000] = []; mpcheck(mptree)
ok! (A x (X ) (X ) (X ) (X ))
>>> mptree[-2:1000] = ['n']; mpcheck(mptree)
ok! (A x (X ) (X ) n)
>>> mptree[-100:1] = [make_mptree('(U v)')]; mpcheck(mptree)
ok! (A (U v) (X ) (X ) n)
>>> mptree[-1:] = (make_mptree('(X)') for x in range(3)); mpcheck(mptree)
ok! (A (U v) (X ) (X ) (X ) (X ) (X ))
>>> mptree[1:-2:2] = ['x', 'y']; mpcheck(mptree)
ok! (A (U v) x (X ) y (X ) (X ))

append()

>>> mptree = make_mptree('(A (B (C (D) (E f) (Q p)) g) h)')
>>> mptree.append('x'); mpcheck(mptree)
ok! (A (B (C (D ) (E f) (Q p)) g) h x)
>>> mptree.append(make_mptree('(X (Y z))')); mpcheck(mptree)
ok! (A (B (C (D ) (E f) (Q p)) g) h x (X (Y z)))

extend()

>>> mptree = make_mptree('(A (B (C (D) (E f) (Q p)) g) h)')
>>> mptree.extend(['x', 'y', make_mptree('(X (Y z))')]); mpcheck(mptree)
ok! (A (B (C (D ) (E f) (Q p)) g) h x y (X (Y z)))
>>> mptree.extend([]); mpcheck(mptree)
ok! (A (B (C (D ) (E f) (Q p)) g) h x y (X (Y z)))
>>> mptree.extend(make_mptree('(X)') for x in range(3)); mpcheck(mptree)
ok! (A (B (C (D ) (E f) (Q p)) g) h x y (X (Y z)) (X ) (X ) (X ))

insert()

>>> mptree = make_mptree('(A (B (C (D) (E f) (Q p)) g) h)')
>>> mptree.insert(0, make_mptree('(X (Y z))')); mpcheck(mptree)
ok! (A (X (Y z)) (B (C (D ) (E f) (Q p)) g) h)
>>> mptree.insert(-1, make_mptree('(X (Y z))')); mpcheck(mptree)
ok! (A (X (Y z)) (B (C (D ) (E f) (Q p)) g) (X (Y z)) h)
>>> mptree.insert(-4, make_mptree('(X (Y z))')); mpcheck(mptree)
ok! (A (X (Y z)) (X (Y z)) (B (C (D ) (E f) (Q p)) g) (X (Y z)) h)
>>> # Note: as with ``list``, inserting at a negative index that
>>> # gives a position before the start of the list does *not*
>>> # raise an IndexError exception; it just inserts at 0.
>>> mptree.insert(-400, make_mptree('(X (Y z))')); mpcheck(mptree)
ok! (A
  (X (Y z))
  (X (Y z))
  (X (Y z))
  (B (C (D ) (E f) (Q p)) g)
  (X (Y z))
  h)

pop()

>>> mptree = make_mptree('(A (B (C (D) (E f) (Q p)) g) h)')
>>> mptree[0,0].pop(1); mpcheck(mptree)
MultiParentedTree('E', ['f'])
ok! (A (B (C (D ) (Q p)) g) h)
>>> mptree[0].pop(-1); mpcheck(mptree)
'g'
ok! (A (B (C (D ) (Q p))) h)
>>> mptree.pop(); mpcheck(mptree)
'h'
ok! (A (B (C (D ) (Q p))))
>>> mptree.pop(-100)
Traceback (most recent call last):
  . . .
IndexError: index out of range

remove()

>>> mptree = make_mptree('(A (B (C (D) (E f) (Q p)) g) h)')
>>> e = mptree[0,0,1]
>>> mptree[0,0].remove(mptree[0,0,1]); mpcheck(mptree); mpcheck(e)
ok! (A (B (C (D ) (Q p)) g) h)
ok! (E f)
>>> mptree[0,0].remove(make_mptree('(Q p)')); mpcheck(mptree)
ok! (A (B (C (D )) g) h)
>>> mptree[0,0].remove(make_mptree('(Q p)'))
Traceback (most recent call last):
  . . .
ValueError: MultiParentedTree('Q', ['p']) is not in list
>>> mptree.remove('h'); mpcheck(mptree)
ok! (A (B (C (D )) g))
>>> mptree.remove('h');
Traceback (most recent call last):
  . . .
ValueError: 'h' is not in list
>>> # remove() removes the first subtree that is equal (==) to the
>>> # given tree, which may not be the identical tree we give it:
>>> mptree = make_mptree('(A (X x) (Y y) (X x))')
>>> x1, y, x2 = mptree
>>> mptree.remove(mptree[-1]); mpcheck(mptree)
ok! (A (Y y) (X x))
>>> print([str(p) for p in x1.parents()])
[]
>>> print([str(p) for p in x2.parents()])
['(A (Y y) (X x))']

ImmutableMultiParentedTree Regression Tests

>>> imptree = ImmutableMultiParentedTree.convert(mptree)
>>> type(imptree)
<class 'nltk.tree.ImmutableMultiParentedTree'>
>>> del imptree[0]
Traceback (most recent call last):
  . . .
ValueError: ImmutableMultiParentedTree may not be modified
>>> imptree.set_label('newnode')
Traceback (most recent call last):
  . . .
ValueError: ImmutableMultiParentedTree may not be modified

ProbabilisticTree Regression Tests

>>> prtree = ProbabilisticTree("S", [ProbabilisticTree("NP", ["N"], prob=0.3)], prob=0.6)
>>> print(prtree)
(S (NP N)) (p=0.6)
>>> import copy
>>> prtree == copy.deepcopy(prtree) == prtree.copy(deep=True) == prtree.copy()
True
>>> prtree[0] is prtree.copy()[0]
True
>>> prtree[0] is prtree.copy(deep=True)[0]
False
>>> imprtree = ImmutableProbabilisticTree.convert(prtree)
>>> type(imprtree)
<class 'nltk.tree.ImmutableProbabilisticTree'>
>>> del imprtree[0]
Traceback (most recent call last):
  . . .
ValueError: ImmutableProbabilisticTree may not be modified
>>> imprtree.set_label('newnode')
Traceback (most recent call last):
  . . .
ValueError: ImmutableProbabilisticTree may not be modified

Squashed Bugs

This used to discard the (B b) subtree (fixed in svn 6270):

>>> print(Tree.fromstring('((A a) (B b))'))
( (A a) (B b))