def frequent_words_with_mismatch(text, kmers, d): count_dict = dict() max_count = 0 visited_kmers = set() for kmer in kmers: app = approx_pattern_count(text, kmer, d) + approx_pattern_count(text, reverse_dna(kmer), d) if app > 0 and kmer not in visited_kmers: if kmer not in count_dict: count_dict[kmer] = 0 count_dict[kmer] += app if count_dict[kmer] > max_count: max_count = count_dict[kmer] result = [key for key in count_dict if count_dict[key] == max_count] return result, max_count
def frequent_words_with_mismatch(text, kmers, d): count_dict = dict() max_count = 0 visited_kmers = set() for kmer in kmers: app = approx_pattern_count(text, kmer, d) + approx_pattern_count( text, reverse_dna(kmer), d) if app > 0 and kmer not in visited_kmers: if kmer not in count_dict: count_dict[kmer] = 0 count_dict[kmer] += app if count_dict[kmer] > max_count: max_count = count_dict[kmer] result = [key for key in count_dict if count_dict[key] == max_count] return result, max_count
def frequent_words_with_mismatch(text, kmers, d): count_dict = dict() max_count = 0 for kmer in kmers: app = approx_pattern_count(text, kmer, d) if app > 0: if kmer not in count_dict: count_dict[kmer] = 0 count_dict[kmer] += app if count_dict[kmer] > max_count: max_count = count_dict[kmer] result = [key for key in count_dict if count_dict[key] == max_count] return result, max_count
def frequent_words_with_mismatch(text, kmers, d): count_dict = dict() max_count = 0 for kmer in kmers: app = approx_pattern_count(text, kmer, d) if app > 0: if kmer not in count_dict: count_dict[kmer] = 0 count_dict[kmer] += app if count_dict[kmer] > max_count: max_count = count_dict[kmer] result = [key for key in count_dict if count_dict[key] == max_count] return result, max_count