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
