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 list( fnm_generic_lp(pattern, sequence, search_params) )
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, subsequence, sequence, max_subs): return [ get_best_match_in_group(group) for group in group_matches( c_fnm_generic_ngrams( subsequence, sequence, LevenshteinSearchParams(max_subs, 0, 0, max_subs))) ]
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): return [ get_best_match_in_group(group) for group in group_matches( fnm_generic_lp( subsequence, sequence, LevenshteinSearchParams(max_l_dist, max_l_dist, max_l_dist, max_l_dist))) ]
def search(self, subsequence, sequence, max_subs): if max_subs >= len(subsequence): self.skipTest("avoiding calling c_fnm_generic_ngrams() " + "with max_subs >= len(subsequence)") return [ get_best_match_in_group(group) for group in group_matches( c_fnm_generic_ngrams( subsequence, sequence, LevenshteinSearchParams(max_subs, 0, 0, max_subs))) ]
def search(self, pattern, sequence, max_subs, max_ins, max_dels, max_l_dist=None): return hnm_generic_ngrams( pattern, sequence, LevenshteinSearchParams(max_subs, max_ins, max_dels, max_l_dist))
def search(self, pattern, sequence, max_subs, max_ins, max_dels, max_l_dist=None): return list( find_near_matches_generic( pattern, sequence, LevenshteinSearchParams(max_subs, max_ins, max_dels, max_l_dist)))
def search(self, pattern, sequence, max_subs, max_ins, max_dels, max_l_dist=None): return list( c_fnm_generic_lp( pattern, sequence, LevenshteinSearchParams( max_subs, max_ins, max_dels, max_l_dist, )))
def search(self, pattern, sequence, max_subs, max_ins, max_dels, max_l_dist=None): return [ get_best_match_in_group(group) for group in group_matches( c_fnm_generic_ngrams( pattern, sequence, LevenshteinSearchParams( max_subs, max_ins, max_dels, max_l_dist, ))) ]
def find_near_matches(subsequence, sequence, max_substitutions=None, max_insertions=None, max_deletions=None, max_l_dist=None): """search for near-matches of subsequence in sequence This searches for near-matches, where the nearly-matching parts of the sequence must meet the following limitations (relative to the subsequence): * the maximum allowed number of character substitutions * the maximum allowed number of new characters inserted * and the maximum allowed number of character deletions * the total number of substitutions, insertions and deletions (a.k.a. the Levenshtein distance) """ search_params = LevenshteinSearchParams(max_substitutions, max_insertions, max_deletions, max_l_dist) search_func = choose_search_func(search_params) return search_func(subsequence, sequence, search_params)
def find_near_matches_in_file(subsequence, sequence_file, max_substitutions=None, max_insertions=None, max_deletions=None, max_l_dist=None, _chunk_size=2**20): """search for near-matches of subsequence in a file This searches for near-matches, where the nearly-matching parts of the sequence must meet the following limitations (relative to the subsequence): * the maximum allowed number of character substitutions * the maximum allowed number of new characters inserted * and the maximum allowed number of character deletions * the total number of substitutions, insertions and deletions (a.k.a. the Levenshtein distance) """ search_params = LevenshteinSearchParams(max_substitutions, max_insertions, max_deletions, max_l_dist) search_class = choose_search_class(search_params) if ('b' in getattr(sequence_file, 'mode', '') or isinstance(sequence_file, io.RawIOBase)): matches = _search_binary_file(subsequence, sequence_file, search_params, search_class, _chunk_size=_chunk_size) else: matches = _search_unicode_file(subsequence, sequence_file, search_params, search_class, _chunk_size=_chunk_size) return search_class.consolidate_matches(matches)
def search(self, subsequence, sequence, max_subs): return hnm_generic_ngrams( subsequence, sequence, LevenshteinSearchParams(max_subs, 0, 0, max_subs))
def search(self, subsequence, sequence, max_subs): search_params = LevenshteinSearchParams(max_subs, 0, 0, max_subs) return list(fnm_generic_lp(subsequence, sequence, search_params))
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 fnm_generic_ngrams( subsequence, sequence, LevenshteinSearchParams(max_l_dist, max_l_dist, max_l_dist, max_l_dist))
def fnm_nodels_ngrams(sequence, subsequence, max_substitutions, max_insertions, max_l_dist=None): return find_near_matches_no_deletions_ngrams( sequence, subsequence, LevenshteinSearchParams( max_substitutions, max_insertions, 0, max_l_dist, ) )
def search(self, subsequence, sequence, max_subs): return list( c_fnm_generic_lp( subsequence, sequence, LevenshteinSearchParams(max_subs, 0, 0, max_subs)))