117 lines
4.8 KiB
Python
117 lines
4.8 KiB
Python
import random
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from fuzzysearch import find_near_matches
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from fuzzysearch.levenshtein import \
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find_near_matches_levenshtein_linear_programming
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from fuzzysearch.levenshtein_ngram import \
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find_near_matches_levenshtein_ngrams as fnm_levenshtein_ngrams
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from fuzzysearch.substitutions_only import \
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find_near_matches_substitutions_ngrams as fnm_substitutions_ngrams, \
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find_near_matches_substitutions_lp, \
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has_near_match_substitutions_ngrams
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from fuzzysearch._substitutions_only import \
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substitutions_only_has_near_matches_lp_byteslike, \
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substitutions_only_has_near_matches_ngrams_byteslike
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from fuzzysearch.generic_search import \
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find_near_matches_generic_linear_programming, \
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find_near_matches_generic_ngrams, has_near_match_generic_ngrams
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from fuzzysearch._generic_search import \
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c_find_near_matches_generic_linear_programming as \
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find_near_matches_generic_linear_programming_cython
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def fnm_levenshtein_lp(subsequence, sequence, max_l_dist):
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return list(find_near_matches_levenshtein_linear_programming(
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subsequence, sequence, max_l_dist))
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def fnm_substitutions_lp(subsequence, sequence, max_substitutions):
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return list(find_near_matches_substitutions_lp(
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subsequence, sequence, max_substitutions))
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def fnm_generic_lp(subsequence, sequence, max_l_dist):
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return list(find_near_matches_generic_linear_programming(
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subsequence, sequence, max_l_dist, max_l_dist, max_l_dist, max_l_dist))
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def fnm_generic_lp_cython(subsequence, sequence, max_l_dist):
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return list(find_near_matches_generic_linear_programming_cython(
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subsequence, sequence, max_l_dist, max_l_dist, max_l_dist, max_l_dist))
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def fnm_generic_ngrams(subsequence, sequence, max_l_dist):
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return list(find_near_matches_generic_ngrams(
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subsequence, sequence, max_l_dist, max_l_dist, max_l_dist, max_l_dist))
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def hnm_generic_ngrams(subsequence, sequence, max_l_dist):
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return has_near_match_generic_ngrams(
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subsequence, sequence, max_l_dist, max_l_dist, max_l_dist, max_l_dist)
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def hnm_substitutions_ngrams(subsequence, sequence, max_substitutions):
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return has_near_match_substitutions_ngrams(
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subsequence, sequence, max_substitutions)
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def hnm_substitutions_byteslike(subsequence, sequence, max_substitutions):
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return substitutions_only_has_near_matches_lp_byteslike(
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subsequence, sequence, max_substitutions)
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def hnm_substitutions_ngrams_byteslike(subsequence, sequence, max_substitutions):
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return substitutions_only_has_near_matches_ngrams_byteslike(
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subsequence, sequence, max_substitutions)
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search_functions = {
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'fnm': find_near_matches,
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'levenshtein_lp': fnm_levenshtein_lp,
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'levenshtein_ngrams': fnm_levenshtein_ngrams,
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'substitutions_lp': fnm_substitutions_lp,
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'substitutions_ngrams': fnm_substitutions_ngrams,
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'generic_lp': fnm_generic_lp,
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'generic_lp_cython': fnm_generic_lp_cython,
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'generic_ngrams': fnm_generic_ngrams,
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'has_match_generic_ngrams': hnm_generic_ngrams,
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'has_match_substitutions_ngrams': hnm_substitutions_ngrams,
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'has_match_substitutions_byteslike': hnm_substitutions_byteslike,
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'has_match_substitutions_ngrams_byteslike': hnm_substitutions_ngrams_byteslike,
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}
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benchmarks = {
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'dna_no_match': dict(
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subsequence = 'GCTAGCTAGCTA',
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sequence = "ATCG" * (10**3),
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max_dist = 1,
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),
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'dna_no_match2': dict(
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subsequence = 'ATGATGATG',
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sequence = 'ATCG' * (10**3),
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max_dist = 2,
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),
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'random_kevin': dict(
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subsequence = ''.join(random.choice('ATCG') for _i in xrange(36)),
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sequence = ''.join(random.choice('ATCG' * 5 + 'N') for _i in xrange(90)),
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max_dist = 3,
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),
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'random_kevin_partial_match': dict(
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subsequence = 'AAGTCTAGT' + ''.join(random.choice('ATCG') for _i in xrange(36-9)),
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sequence = 'AAGTCTAGT' + ''.join(random.choice('ATCG' * 5 + 'N') for _i in xrange(90-9)),
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max_dist = 3,
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),
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}
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def get_benchmark(search_func_name, benchmark_name):
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search_func = search_functions[search_func_name]
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search_args = dict(benchmarks[benchmark_name])
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if search_func in (find_near_matches,):
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search_args['max_l_dist'] = search_args.pop('max_dist')
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elif search_func in (fnm_levenshtein_ngrams, fnm_levenshtein_lp, fnm_generic_lp, fnm_generic_lp_cython, fnm_generic_ngrams, hnm_generic_ngrams):
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search_args['max_l_dist'] = search_args.pop('max_dist')
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elif search_func in (fnm_substitutions_ngrams, fnm_substitutions_lp, hnm_substitutions_ngrams, hnm_substitutions_byteslike, hnm_substitutions_ngrams_byteslike):
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search_args['max_substitutions'] = search_args.pop('max_dist')
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else:
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raise Exception('Unsupported search function: %r' % search_func)
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return search_func, search_args
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def run_benchmark(search_func, search_args):
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return search_func(**search_args)
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