shared.py 文件源码

def normal_density_at_zero(m, c):
    """ Compute the normal density with given mean and covariance at zero. 

    Parameters
    ----------    
    m : vector
        Mean.
    c : ndarray
        Covariance matrix. Assumption: c is square matrix and its size is 
        compatible with that of m.

    Returns
    -------
    g : float
        Computed density value.

    """

    dim = len(m)
    g = 1 / ((2 * pi)**(dim / 2) * sqrt(absolute(det(c)))) *\
        exp(-1/2 * dot(dot(m, inv(c)), m))

    return g