crowd_model.py 文件源码

def expectation_binorm(rv, mu, var, x, M, C, w = 3):
    """
    Evaluate the expectation of log Norm(uv| M, C)
         x = u, v ~ Norm(mu, var) rv == 'v'
         x = v, u ~ Norm(mu, var) rv == 'u'
    """
    #print rv, mu, var, x, M, C
    if rv == 'v':
      f = lambda v: scipy.stats.norm.pdf(v, loc = mu, scale = np.sqrt(var) ) * \
        np.log(scipy.stats.multivariate_normal.pdf([x, v], mean = M, cov = C, allow_singular = True))
    else:
      f = lambda u: scipy.stats.norm.pdf(u, loc = mu, scale = np.sqrt(var) ) * \
        np.log(scipy.stats.multivariate_normal.pdf([u, x], mean = M, cov = C, allow_singular = True))

    #return f
    #print f(mu)
    std = np.sqrt(var)
    return scipy.integrate.quad(f, mu - w*std, mu + w*std)[0]