aima/text.py
def viterbi_segment(text, P):
    """Find the best segmentation of the string of characters, given the
    UnigramTextModel P."""
    # best[i] = best probability for text[0:i]
    # words[i] = best word ending at position i
    n = len(text)
    words = [''] + list(text)
    best = [1.0] + [0.0] * n
    ## Fill in the vectors best, words via dynamic programming
    for i in range(n+1):
        for j in range(0, i):
            w = text[j:i]
            if P[w] * best[i - len(w)] >= best[i]:
                best[i] = P[w] * best[i - len(w)]
                words[i] = w
    ## Now recover the sequence of best words
    sequence = []; i = len(words)-1
    while i > 0:
        sequence[0:0] = [words[i]]
        i = i - len(words[i])
    ## Return sequence of best words and overall probability
    return sequence, best[-1]
def viterbi_segment(text, P):
    """Find the best segmentation of the string of characters, given the
    UnigramTextModel P."""
    # best[i] = best probability for text[0:i]
    # words[i] = best word ending at position i
    n = len(text)
    words = [''] + list(text)
    best = [1.0] + [0.0] * n
    ## Fill in the vectors best, words via dynamic programming
    for i in range(n+1):
        for j in range(0, i):
            w = text[j:i]
            if P[w] * best[i - len(w)] >= best[i]:
                best[i] = P[w] * best[i - len(w)]
                words[i] = w
    ## Now recover the sequence of best words
    sequence = []; i = len(words)-1
    while i > 0:
        sequence[0:0] = [words[i]]
        i = i - len(words[i])
    ## Return sequence of best words and overall probability
    return sequence, best[-1]
Find the best segmentation of the string of characters, given the
    UnigramTextModel P.