pdfs.py 文件源码

def __div__(self, other):
        """Divide by a single gaussian."""

        assert isinstance(other, Gaussian)

        ys = [x / other for x in self.xs]

        lcs = np.empty_like(self.a)

        for i, (x, y) in enumerate(izip(self.xs, ys)):

            lcs[i] = x.logdetP - other.logdetP - y.logdetP
            lcs[i] -= np.dot(x.m, np.dot(x.P, x.m)) - np.dot(other.m, np.dot(other.P, other.m)) - np.dot(y.m, np.dot(y.P, y.m))
            lcs[i] *= 0.5

        la = np.log(self.a) + lcs
        la -= scipy.misc.logsumexp(la)
        a = np.exp(la)

        return MoG(a=a, xs=ys)