simple.doctest

.. Copyright (C) 2001-2012 NLTK Project
.. For license information, see LICENSE.TXT

=================
EasyInstall Tests
=================

This file contains some simple tests that will be run by EasyInstall in
order to test the installation when NLTK-Data is absent.

    >>> from nltk.test.doctest_utils import *

------------
Tokenization
------------

    >>> from nltk import wordpunct_tokenize
    >>> s = ("Good muffins cost $3.88\nin New York.  Please buy me\n"
    ...      "two of them.\n\nThanks.")
    >>> wordpunct_tokenize(s) # doctest: +NORMALIZE_WHITESPACE
    ['Good', 'muffins', 'cost', '$', '3', '.', '88', 'in', 'New', 'York', '.',
    'Please', 'buy', 'me', 'two', 'of', 'them', '.', 'Thanks', '.']

-------
Metrics
-------

    >>> from nltk.metrics import precision, recall, f_measure
    >>> reference = 'DET NN VB DET JJ NN NN IN DET NN'.split()
    >>> test    = 'DET VB VB DET NN NN NN IN DET NN'.split()
    >>> reference_set = set(reference)
    >>> test_set = set(test)
    >>> precision(reference_set, test_set)
    1.0
    >>> float_equal(recall(reference_set, test_set), 0.8)
    True
    >>> float_equal(f_measure(reference_set, test_set), 0.88888888888888)
    True

------------------
Feature Structures
------------------

    >>> from nltk import FeatStruct
    >>> fs1 = FeatStruct(PER=3, NUM='pl', GND='fem')
    >>> fs2 = FeatStruct(POS='N', AGR=fs1)
    >>> print fs2
    [       [ GND = 'fem' ] ]
    [ AGR = [ NUM = 'pl'  ] ]
    [       [ PER = 3     ] ]
    [                       ]
    [ POS = 'N'             ]
    >>> print fs2['AGR']
    [ GND = 'fem' ]
    [ NUM = 'pl'  ]
    [ PER = 3     ]
    >>> print fs2['AGR']['PER']
    3

-------
Parsing
-------

    >>> from nltk import RecursiveDescentParser, parse_cfg
    >>> grammar = parse_cfg("""
    ... S -> NP VP
    ... PP -> P NP
    ... NP -> 'the' N | N PP | 'the' N PP
    ... VP -> V NP | V PP | V NP PP
    ... N -> 'cat' | 'dog' | 'rug'
    ... V -> 'chased'
    ... P -> 'on'
    ... """)
    >>> rd = RecursiveDescentParser(grammar)
    >>> sent = 'the cat chased the dog on the rug'.split()
    >>> for t in rd.nbest_parse(sent):
    ...     print t
    (S
      (NP the (N cat))
      (VP (V chased) (NP the (N dog) (PP (P on) (NP the (N rug))))))
    (S
      (NP the (N cat))
      (VP (V chased) (NP the (N dog)) (PP (P on) (NP the (N rug)))))