def search(self, subsequence, sequence, max_l_dist):
if max_l_dist >= len(subsequence):
self.skipTest(
'skipping ngram search with max_l_dist >= len(subsequence)')
return consolidate_overlapping_matches(
fnm_levenshtein_ngrams(subsequence, sequence, max_l_dist)
)
def search(self, subsequence, sequence, max_subs):
if max_subs >= len(subsequence):
self.skipTest("avoiding calling fnm_generic_ngrams() " +
"with max_subs >= len(subsequence)")
search_params = LevenshteinSearchParams(max_subs, 0, 0, max_subs)
return consolidate_overlapping_matches(
fnm_generic_ngrams(subsequence, sequence, search_params))
def search(self, pattern, sequence, max_subs, max_ins, max_dels,
max_l_dist=None):
search_params = LevenshteinSearchParams(max_subs, max_ins,
max_dels, max_l_dist)
return consolidate_overlapping_matches(
find_near_matches_generic(pattern, sequence, search_params)
)
def search(self, subsequence, sequence, max_l_dist):
if max_l_dist >= len(subsequence):
self.skipTest(
'skipping ngram search with max_l_dist >= len(subsequence)')
return consolidate_overlapping_matches(
fnm_levenshtein_ngrams(subsequence, sequence, max_l_dist)
)
def search(self, subsequence, sequence, max_subs):
if max_subs >= len(subsequence):
self.skipTest("avoiding calling fnm_generic_ngrams() " +
"with max_subs >= len(subsequence)")
search_params = LevenshteinSearchParams(max_subs, 0, 0, max_subs)
return consolidate_overlapping_matches(
fnm_generic_ngrams(subsequence, sequence, search_params)
)
def expectedOutcomes(self, search_results, expected_outcomes, *args, **kwargs):
consolidated_results = [
get_best_match_in_group(group)
for group in group_matches(search_results)
]
consolidated_expected_outcomes = \
consolidate_overlapping_matches(expected_outcomes)
return self.assertEqual(consolidated_results,
consolidated_expected_outcomes,
*args, **kwargs)
def consolidate_matches(cls, matches):
return consolidate_overlapping_matches(matches)
def search(self, subsequence, sequence, max_l_dist):
return consolidate_overlapping_matches(
find_near_matches_levenshtein(subsequence, sequence, max_l_dist)
)
def expectedOutcomes(self, search_results, expected_outcomes, *args,
**kwargs):
return self.assertEqual(
consolidate_overlapping_matches(search_results),
consolidate_overlapping_matches(expected_outcomes), *args,
**kwargs)
def search(self, subsequence, sequence, max_l_dist):
search_params = LevenshteinSearchParams(max_l_dist, max_l_dist,
max_l_dist, max_l_dist)
return consolidate_overlapping_matches(
fnm_generic_lp(subsequence, sequence, search_params))
def search(self, subsequence, sequence, max_l_dist):
return consolidate_overlapping_matches(
find_near_matches_levenshtein(subsequence, sequence, max_l_dist)
)
def expectedOutcomes(self, search_results, expected_outcomes, *args, **kwargs):
return self.assertEqual(
consolidate_overlapping_matches(search_results),
consolidate_overlapping_matches(expected_outcomes),
*args, **kwargs)
def search(self, subsequence, sequence, max_l_dist):
search_params = LevenshteinSearchParams(max_l_dist, max_l_dist,
max_l_dist, max_l_dist)
return consolidate_overlapping_matches(
fnm_generic_lp(subsequence, sequence, search_params)
)
def consolidate_matches(cls, matches):
return consolidate_overlapping_matches(matches)
