def test_subsequences(self):
real_word = "which"
expected = [
'w', 'wh', 'whi', 'whic', 'which',
'h', 'hi', 'hic', 'hich',
'i', 'ic', 'ich',
'c', 'ch',
'h'
]
actual = [s for s in subsequences(real_word)]
self.assertEqual(len(expected), len(actual))
self.assertEqual(expected, actual)
def run(self):
errors = []
pbar = build_progressbar(self.real_words)
finder = EditFinder()
for i,word in enumerate(self.real_words):
pbar.update(i+1)
# Find all the edits we can make to this word.
possible_edits = list()
probs = list()
for subseq in subsequences(word):
# Probably delete this if statement as redundant.
for e in self.edit_db.edits(subseq):
_, error_subseq, count = e
possible_edit = (subseq, error_subseq)
if count > 0:
possible_edits.append(possible_edit)
probs.append(count)
if len(possible_edits) == 0:
continue
probs = np.array(probs)
probs = probs / float(probs.sum())
seen_edits = set()
errors_for_word = []
attempts = 0.
# Try to generate up to the requested number of errors per word.
while True:
try:
attempts += 1.
if self.enough_errors_for_word(word, errors_for_word):
# Generated enough errors for this word.
break
elif attempts > 10 and len(errors_for_word) / attempts < 0.1:
# Not finding many errors to apply. Break out.
break
# Sample the number of edits.
edit_sizes = np.arange(1, self.max_edits_per_error+1)
edit_size_probs = 1. / edit_sizes
edit_size_probs /= edit_size_probs.sum()
size = self.random_state.choice(edit_sizes, size=1, replace=False,
p=edit_size_probs)[0]
# Sample edits with probability proportional to the edit's frequency.
edit_idx = self.random_state.choice(len(probs), size=size, replace=False, p=probs)
edit = []
for i in edit_idx:
pe = possible_edits[i]
if pe in seen_edits:
continue
seen_edits.add(pe)
edit.append(pe)
if len(edit) == 0:
continue
# Avoid applying edits that result in unlikely errors.
for constraint in self.constraints:
for e in edit:
if constraint(word, e):
raise EditConstraintError("can't apply edit %s=>%s to word '%s'" % \
(e[0], e[1], word))
error = finder.apply(word, edit)
if error in self.blacklist:
# Skip blacklisted words (i.e. non-words in a corpus used to generate the
# edit patterns in the edit database).
continue
errors_for_word.append((word, len(possible_edits), edit, error))
except EditConstraintError as e:
if self.verbose:
print(e)
errors.extend(errors_for_word)
pbar.finish()
return errors
