nltk.tree.ProbabilisticTree

class documentation

class ProbabilisticTree(Tree, ProbabilisticMixIn): (source)

Constructor: ProbabilisticTree(node, children, **prob_kwargs)

Undocumented

Class Method	`convert`	Convert a tree between different subtypes of Tree. `cls` determines which class will be used to encode the new tree.
Method	`__eq__`	Undocumented
Method	`__init__`	Initialize this object's probability. This initializer should be called by subclass constructors. `prob` should generally be the first argument for those constructors.
Method	`__lt__`	Undocumented
Method	`__repr__`	Undocumented
Method	`__str__`	Undocumented
Method	`copy`	Undocumented
Method	`_frozen_class`	Undocumented

Inherited from Tree:

Class Method	`fromlist`	Convert nested lists to a NLTK Tree
Class Method	`fromstring`	Read a bracketed tree string and return the resulting tree. Trees are represented as nested brackettings, such as:
Method	`__add__`	Undocumented
Method	`__copy__`	Undocumented
Method	`__deepcopy__`	Undocumented
Method	`__delitem__`	Undocumented
Method	`__getitem__`	Undocumented
Method	`__mul__`	Undocumented
Method	`__radd__`	Undocumented
Method	`__rmul__`	Undocumented
Method	`__setitem__`	Undocumented
Method	`chomsky_normal_form`	This method can modify a tree in three ways:
Method	`collapse_unary`	Collapse subtrees with a single child (ie. unary productions) into a new non-terminal (Tree node) joined by 'joinChar'. This is useful when working with algorithms that do not allow unary productions, and completely removing the unary productions would require loss of useful information...
Method	`draw`	Open a new window containing a graphical diagram of this tree.
Method	`flatten`	Return a flat version of the tree, with all non-root non-terminals removed.
Method	`freeze`	Undocumented
Method	`height`	Return the height of the tree.
Method	`label`	Return the node label of the tree.
Method	`leaf_treeposition`	No summary
Method	`leaves`	Return the leaves of the tree.
Method	`pformat`	No summary
Method	`pformat_latex_qtree`	Returns a representation of the tree compatible with the LaTeX qtree package. This consists of the string `\Tree` followed by the tree represented in bracketed notation.
Method	`pos`	Return a sequence of pos-tagged words extracted from the tree.
Method	`pprint`	Print a string representation of this Tree to 'stream'
Method	`pretty_print`	Pretty-print this tree as ASCII or Unicode art. For explanation of the arguments, see the documentation for `nltk.treeprettyprinter.TreePrettyPrinter`.
Method	`productions`	Generate the productions that correspond to the non-terminal nodes of the tree. For each subtree of the form (P: C1 C2 ... Cn) this produces a production of the form P -> C1 C2 ... Cn.
Method	`set_label`	Set the node label of the tree.
Method	`subtrees`	Generate all the subtrees of this tree, optionally restricted to trees matching the filter function.
Method	`treeposition_spanning_leaves`	No summary
Method	`treepositions`	No summary
Method	`un_chomsky_normal_form`	This method modifies the tree in three ways:
Class Variable	`__ge__`	Undocumented
Class Variable	`__gt__`	Undocumented
Class Variable	`__le__`	Undocumented
Class Variable	`__ne__`	Undocumented
Class Variable	`node`	Undocumented
Class Method	`_parse_error`	Display a friendly error message when parsing a tree string fails. :param s: The string we're parsing. :param match: regexp match of the problem token. :param expecting: what we expected to see instead.
Method	`_get_node`	Outdated method to access the node value; use the label() method instead.
Method	`_pformat_flat`	Undocumented
Method	`_repr_png_`	Draws and outputs in PNG for ipython. PNG is used instead of PDF, since it can be displayed in the qt console and has wider browser support.
Method	`_set_node`	Outdated method to set the node value; use the set_label() method instead.
Instance Variable	`_label`	Undocumented

Inherited from ProbabilisticMixIn (via Tree):

Method	`logprob`	Return `log(p)`, where `p` is the probability associated with this object.
Method	`prob`	Return the probability associated with this object.
Method	`set_logprob`	Set the log probability associated with this object to `logprob`. I.e., set the probability associated with this object to `2**(logprob)`.
Method	`set_prob`	Set the probability associated with this object to `prob`.
Instance Variable	`__logprob`	Undocumented
Instance Variable	`__prob`	Undocumented

@classmethod
def convert(cls, val): (source) ¶

overrides nltk.tree.Tree.convert

Convert a tree between different subtypes of Tree. cls determines which class will be used to encode the new tree.

Parameters
val	Undocumented
tree:Tree	The tree that should be converted.
Returns
The new Tree.

def __eq__(self, other): (source) ¶

overrides nltk.tree.Tree.__eq__

Undocumented

def __init__(self, node, children=None, **prob_kwargs): (source) ¶

overrides nltk.tree.Tree.__init__

Initialize this object's probability. This initializer should be called by subclass constructors. prob should generally be the first argument for those constructors.

Parameters
node	Undocumented
children	Undocumented
prob:float	The probability associated with the object.
logprob:float	The log of the probability associated with the object.
**prob_kwargs	Undocumented

def __lt__(self, other): (source) ¶

overrides nltk.tree.Tree.__lt__

Undocumented

def __repr__(self): (source) ¶

overrides nltk.tree.Tree.__repr__

Undocumented

def __str__(self): (source) ¶

overrides nltk.tree.Tree.__str__

Undocumented

def copy(self, deep=False): (source) ¶

overrides nltk.tree.Tree.copy

Undocumented

def _frozen_class(self): (source) ¶

overrides nltk.tree.Tree._frozen_class

Undocumented