eqlm.py 文件源码

def eqe1(E, query, vocabulary, priors):
    """
    Arguments:
        E - word embedding
        Q - list of query terms
        vocabulary -- list of relevant words
        priors - precomputed priors with same indices as vocabulary
    >>> E = dict()
    >>> E['a'] = np.asarray([0.5,0.5])
    >>> E['b'] = np.asarray([0.2,0.8])
    >>> E['c'] = np.asarray([0.9,0.1])
    >>> E['d'] = np.asarray([0.8,0.2])
    >>> q = "a b".split()
    >>> vocabulary = "a b c".split()
    >>> priors = np.asarray([0.25,0.5,0.25])
    >>> posterior = eqe1(E, q, vocabulary, priors)
    >>> vocabulary[np.argmax(posterior)]
    'c'
    """
    posterior = [priors[i] *
                 np.product([delta(E[qi], E[w]) / priors[i] for qi in query])
                 for i, w in enumerate(vocabulary)]

    return np.asarray(posterior)