def PatternToNumber(Pattern): l = len(Pattern) condensed_k_mer_list = condensed_list(l) index = condensed_k_mer_list.index(Pattern) return index
def median_string(strings, k): distance = float("inf") #initialize distance as zero possibles = condensed_list(k) median = "none" for p in possibles: if string_scores(p, strings) < distance: distance = string_scores(p, strings) median = p return median
def ComputingFrequencies(text, k): condensed_k_mer_list = condensed_list(k) janky_seq_counter = {} for k_mer in condensed_k_mer_list: count = 0 for i, bp in enumerate(text): end_index = i+k - 1 # if you haven't gone too far down the pattern (possibility of finding k_mer still exists) if end_index < len(text): if k_mer == text[i:i+k]: # checks that k_mer matches pattern count += 1 janky_seq_counter[k_mer] = count return janky_seq_counter.values()
def ComputingFrequencies(text, k): condensed_k_mer_list = condensed_list(k) janky_seq_counter = {} for k_mer in condensed_k_mer_list: count = 0 for i, bp in enumerate(text): end_index = i + k - 1 # if you haven't gone too far down the pattern (possibility of finding k_mer still exists) if end_index < len(text): if k_mer == text[i:i + k]: # checks that k_mer matches pattern count += 1 janky_seq_counter[k_mer] = count return janky_seq_counter.values()
def NumberToPattern(index, k): condensed_k_mer_list = condensed_list(k) pattern = condensed_k_mer_list[index] return pattern