def vectorize_damping(params, damping=1.0, increase_list=[['psf-', 1e4]]):
    """
    Returns a non-constant damping vector, allowing certain parameters to be
    more strongly damped than others.

    Parameters
    ----------
        params : List
            The list of parameter names, in order.
        damping : Float
            The default value of the damping.
        increase_list: List
            A nested 2-element list of the params to increase and their
            scale factors. All parameters containing the string
            increase_list[i][0] are increased by a factor increase_list[i][1].
    Returns
    -------
        damp_vec : np.ndarray
            The damping vector to use.
    """
    damp_vec = np.ones(len(params)) * damping
    for nm, fctr in increase_list:
        for a in range(damp_vec.size):
            if nm in params[a]:
                damp_vec[a] *= fctr
    return damp_vec
def vectorize_damping(params, damping=1.0, increase_list=[['psf-', 1e4]]):
    """
    Returns a non-constant damping vector, allowing certain parameters to be
    more strongly damped than others.

    Parameters
    ----------
        params : List
            The list of parameter names, in order.
        damping : Float
            The default value of the damping.
        increase_list: List
            A nested 2-element list of the params to increase and their
            scale factors. All parameters containing the string
            increase_list[i][0] are increased by a factor increase_list[i][1].
    Returns
    -------
        damp_vec : np.ndarray
            The damping vector to use.
    """
    damp_vec = np.ones(len(params)) * damping
    for nm, fctr in increase_list:
        for a in range(damp_vec.size):
            if nm in params[a]:
                damp_vec[a] *= fctr
    return damp_vec
def vectorize_damping ( params , damping = 1.0 , increase_list = [ [ 'psf-' , 1e4 ] ] ) : damp_vec = np . ones ( len ( params ) ) * damping for nm , fctr in increase_list : for a in range ( damp_vec . size ) : if nm in params [ a ] : damp_vec [ a ] *= fctr return damp_vec
Returns a non-constant damping vector, allowing certain parameters to be
    more strongly damped than others.

    Parameters
    ----------
        params : List
            The list of parameter names, in order.
        damping : Float
            The default value of the damping.
        increase_list: List
            A nested 2-element list of the params to increase and their
            scale factors. All parameters containing the string
            increase_list[i][0] are increased by a factor increase_list[i][1].
    Returns
    -------
        damp_vec : np.ndarray
            The damping vector to use.
Returns a non - constant damping vector allowing certain parameters to be more strongly damped than others .