aima-python/tests/test_text.py at master · FuningTeng/aima-python · GitHub

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import pytest

import os

import random

from text import *

from utils import isclose, open_data

def test_text_models():

flatland = open_data("EN-text/flatland.txt").read()

wordseq = words(flatland)

P1 = UnigramWordModel(wordseq)

P2 = NgramWordModel(2, wordseq)

P3 = NgramWordModel(3, wordseq)

# Test top

assert P1.top(5) == [(2081, 'the'), (1479, 'of'),

(1021, 'and'), (1008, 'to'),

(850, 'a')]

assert P2.top(5) == [(368, ('of', 'the')), (152, ('to', 'the')),

(152, ('in', 'the')), (86, ('of', 'a')),

(80, ('it', 'is'))]

assert P3.top(5) == [(30, ('a', 'straight', 'line')),

(19, ('of', 'three', 'dimensions')),

(16, ('the', 'sense', 'of')),

(13, ('by', 'the', 'sense')),

(13, ('as', 'well', 'as'))]

# Test isclose

assert isclose(P1['the'], 0.0611, rel_tol=0.001)

assert isclose(P2['of', 'the'], 0.0108, rel_tol=0.01)

assert isclose(P3['so', 'as', 'to'], 0.000323, rel_tol=0.001)

# Test cond_prob.get

assert P2.cond_prob.get(('went',)) is None

assert P3.cond_prob['in', 'order'].dictionary == {'to': 6}

# Test dictionary

test_string = 'unigram'

wordseq = words(test_string)

P1 = UnigramWordModel(wordseq)

assert P1.dictionary == {('unigram'): 1}

test_string = 'bigram text'

wordseq = words(test_string)

P2 = NgramWordModel(2, wordseq)

assert P2.dictionary == {('bigram', 'text'): 1}

test_string = 'test trigram text here'

wordseq = words(test_string)

P3 = NgramWordModel(3, wordseq)

assert ('test', 'trigram', 'text') in P3.dictionary

assert ('trigram', 'text', 'here') in P3.dictionary

def test_char_models():

test_string = 'test unigram'

wordseq = words(test_string)

P1 = UnigramCharModel(wordseq)

expected_unigrams = {'n': 1, 's': 1, 'e': 1, 'i': 1, 'm': 1, 'g': 1, 'r': 1, 'a': 1, 't': 2, 'u': 1}

assert len(P1.dictionary) == len(expected_unigrams)

for char in test_string.replace(' ', ''):

assert char in P1.dictionary

test_string = 'alpha beta'

wordseq = words(test_string)

P1 = NgramCharModel(1, wordseq)

assert len(P1.dictionary) == len(set(test_string))

for char in set(test_string):

assert tuple(char) in P1.dictionary

test_string = 'bigram'

wordseq = words(test_string)

P2 = NgramCharModel(2, wordseq)

expected_bigrams = {(' ', 'b'): 1, ('b', 'i'): 1, ('i', 'g'): 1, ('g', 'r'): 1, ('r', 'a'): 1, ('a', 'm'): 1}

assert len(P2.dictionary) == len(expected_bigrams)

for bigram, count in expected_bigrams.items():

assert bigram in P2.dictionary

assert P2.dictionary[bigram] == count

test_string = 'bigram bigram'

wordseq = words(test_string)

P2 = NgramCharModel(2, wordseq)

expected_bigrams = {(' ', 'b'): 2, ('b', 'i'): 2, ('i', 'g'): 2, ('g', 'r'): 2, ('r', 'a'): 2, ('a', 'm'): 2}

assert len(P2.dictionary) == len(expected_bigrams)

for bigram, count in expected_bigrams.items():

assert bigram in P2.dictionary

assert P2.dictionary[bigram] == count

test_string = 'trigram'

wordseq = words(test_string)

P3 = NgramCharModel(3, wordseq)

expected_trigrams = {(' ', 't', 'r'): 1, ('t', 'r', 'i'): 1,

('r', 'i', 'g'): 1, ('i', 'g', 'r'): 1,

('g', 'r', 'a'): 1, ('r', 'a', 'm'): 1}

assert len(P3.dictionary) == len(expected_trigrams)

for bigram, count in expected_trigrams.items():

assert bigram in P3.dictionary

assert P3.dictionary[bigram] == count

test_string = 'trigram trigram trigram'

wordseq = words(test_string)

P3 = NgramCharModel(3, wordseq)

expected_trigrams = {(' ', 't', 'r'): 3, ('t', 'r', 'i'): 3,

('r', 'i', 'g'): 3, ('i', 'g', 'r'): 3,

('g', 'r', 'a'): 3, ('r', 'a', 'm'): 3}

assert len(P3.dictionary) == len(expected_trigrams)

for bigram, count in expected_trigrams.items():

assert bigram in P3.dictionary

assert P3.dictionary[bigram] == count

def test_samples():

story = open_data("EN-text/flatland.txt").read()

story += open_data("gutenberg.txt").read()

wordseq = words(story)

P1 = UnigramWordModel(wordseq)

P2 = NgramWordModel(2, wordseq)

P3 = NgramWordModel(3, wordseq)

s1 = P1.samples(10)

s2 = P3.samples(10)

s3 = P3.samples(10)

assert len(s1.split(' ')) == 10

assert len(s2.split(' ')) == 10

assert len(s3.split(' ')) == 10

def test_viterbi_segmentation():

flatland = open_data("EN-text/flatland.txt").read()

wordseq = words(flatland)

P = UnigramWordModel(wordseq)

text = "itiseasytoreadwordswithoutspaces"

s, p = viterbi_segment(text, P)

assert s == [

'it', 'is', 'easy', 'to', 'read', 'words', 'without', 'spaces']

def test_shift_encoding():

code = shift_encode("This is a secret message.", 17)

assert code == 'Kyzj zj r jvtivk dvjjrxv.'

def test_shift_decoding():

flatland = open_data("EN-text/flatland.txt").read()

ring = ShiftDecoder(flatland)

msg = ring.decode('Kyzj zj r jvtivk dvjjrxv.')

assert msg == 'This is a secret message.'

def test_permutation_decoder():

gutenberg = open_data("gutenberg.txt").read()

flatland = open_data("EN-text/flatland.txt").read()

pd = PermutationDecoder(canonicalize(gutenberg))

assert pd.decode('aba') in ('ece', 'ete', 'tat', 'tit', 'txt')

pd = PermutationDecoder(canonicalize(flatland))

assert pd.decode('aba') in ('ded', 'did', 'ece', 'ele', 'eme', 'ere', 'eve', 'eye', 'iti', 'mom', 'ses', 'tat', 'tit')

def test_rot13_encoding():

code = rot13('Hello, world!')

assert code == 'Uryyb, jbeyq!'

def test_rot13_decoding():

flatland = open_data("EN-text/flatland.txt").read()

ring = ShiftDecoder(flatland)

msg = ring.decode(rot13('Hello, world!'))

assert msg == 'Hello, world!'

def test_counting_probability_distribution():

D = CountingProbDist()

for i in range(10000):

D.add(random.choice('123456'))

ps = [D[n] for n in '123456']

assert 1 / 7 <= min(ps) <= max(ps) <= 1 / 5

def test_ir_system():

from collections import namedtuple

Results = namedtuple('IRResults', ['score', 'url'])

uc = UnixConsultant()

def verify_query(query, expected):

assert len(expected) == len(query)

for expected, (score, d) in zip(expected, query):

doc = uc.documents[d]

assert "{0:.2f}".format(

expected.score) == "{0:.2f}".format(score * 100)

assert os.path.basename(expected.url) == os.path.basename(doc.url)

return True

q1 = uc.query("how do I remove a file")

assert verify_query(q1, [

Results(76.83, "aima-data/MAN/rm.txt"),

Results(67.83, "aima-data/MAN/tar.txt"),

Results(67.79, "aima-data/MAN/cp.txt"),

Results(66.58, "aima-data/MAN/zip.txt"),

Results(64.58, "aima-data/MAN/gzip.txt"),

Results(63.74, "aima-data/MAN/pine.txt"),

Results(62.95, "aima-data/MAN/shred.txt"),

Results(57.46, "aima-data/MAN/pico.txt"),

Results(43.38, "aima-data/MAN/login.txt"),

Results(41.93, "aima-data/MAN/ln.txt"),

])

q2 = uc.query("how do I delete a file")

assert verify_query(q2, [

Results(75.47, "aima-data/MAN/diff.txt"),

Results(69.12, "aima-data/MAN/pine.txt"),

Results(63.56, "aima-data/MAN/tar.txt"),

Results(60.63, "aima-data/MAN/zip.txt"),

Results(57.46, "aima-data/MAN/pico.txt"),

Results(51.28, "aima-data/MAN/shred.txt"),

Results(26.72, "aima-data/MAN/tr.txt"),

])

q3 = uc.query("email")

assert verify_query(q3, [

Results(18.39, "aima-data/MAN/pine.txt"),

Results(12.01, "aima-data/MAN/info.txt"),

Results(9.89, "aima-data/MAN/pico.txt"),

Results(8.73, "aima-data/MAN/grep.txt"),

Results(8.07, "aima-data/MAN/zip.txt"),

])

q4 = uc.query("word count for files")

assert verify_query(q4, [

Results(128.15, "aima-data/MAN/grep.txt"),

Results(94.20, "aima-data/MAN/find.txt"),

Results(81.71, "aima-data/MAN/du.txt"),

Results(55.45, "aima-data/MAN/ps.txt"),

Results(53.42, "aima-data/MAN/more.txt"),

Results(42.00, "aima-data/MAN/dd.txt"),

Results(12.85, "aima-data/MAN/who.txt"),

])

q5 = uc.query("learn: date")

assert verify_query(q5, [])

q6 = uc.query("2003")

assert verify_query(q6, [

Results(14.58, "aima-data/MAN/pine.txt"),

Results(11.62, "aima-data/MAN/jar.txt"),

])

def test_words():

assert words("``EGAD!'' Edgar cried.") == ['egad', 'edgar', 'cried']

def test_canonicalize():

assert canonicalize("``EGAD!'' Edgar cried.") == 'egad edgar cried'

def test_translate():

text = 'orange apple lemon '

func = lambda x: ('s ' + x) if x ==' ' else x

assert translate(text, func) == 'oranges apples lemons '

def test_bigrams():

assert bigrams('this') == ['th', 'hi', 'is']

assert bigrams(['this', 'is', 'a', 'test']) == [['this', 'is'], ['is', 'a'], ['a', 'test']]

if __name__ == '__main__':

pytest.main()

aima-python/tests/test_text.py at master · FuningTeng/aima-python · GitHub

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