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)