Veterby algorythm

def read_state_table(lines):
    states_transition = {}
    states_order = []
    for i in lines[0]:
        if i != ' ' and i != '\t':
            states_order.append(i)
    for row in lines[1:]:
        cells = [cell for cell in row.split() if cell != '']
        states_transition[cells[0]] = {}
        for idx, cell in enumerate(cells[1:]):
            states_transition[cells[0]][states_order[idx]] = float(cell)
    return states_transition

def read_letter_table(lines):
    letter_emission = {}
    letter_order = []
    for i in lines[0]:
        if i != ' ' and i != '\t':
            letter_order.append(i)
            letter_emission[i] = {}
    for row in lines[1:]:
        cells = [cell for cell in row.split() if cell != '']
        for idx, cell in enumerate(cells[1:]):
            letter_emission[letter_order[idx]][cells[0]] = float(cell)
    return letter_emission

s = []

def states_sequence_probability_first(first_letter, transitions_table, emission_table):
    s.append({})
    s[0][0] = 1
    for k in transitions_table:
        s[0][k] = emission_table[first_letter][k] * 1 / len(transitions_table)

def states_sequence_probability(string, transitions_table, emission_table):
    states_sequence_probability_first(string[0], transitions_table, emission_table)
    for i in range(1, len(string)):
        s.append({})
        for k in transitions_table:
            sum = 0
            for l in transitions_table:
                sum += s[i-1][l]*transitions_table[l][k]
            s[i][k] = emission_table[string[i]][k]*sum
    sum = 0
    for k in transitions_table:
        sum += s[len(string) - 1][k]
    return sum

def read_file(filename):
    file = ''
    with open(filename) as f:
        file = f.read()
    lines = file.split('\n')
    string = lines[0]
    letters = [x for x in lines[2].split('\t') if x != '']
    transitions_table = read_state_table(lines[6:6 + len(letters)])
    emission_table = read_letter_table(lines[6 + len(letters) + 1:])
    return string, transitions_table, emission_table

string, transitions_table, emission_table = read_file('rosalind_ba10d.txt')
print(states_sequence_probability(string, transitions_table, emission_table))