gdprox 0.3

H2> GdPROX，近端梯度下降算法

实现了复合目标函数的近端梯度下降算法，即形式{{CD1>}的函数，其中F是光滑函数，G是一个可能的非光滑函数。

这个包的主要功能是gdprox.fmin_cgprox。此函数遵循与scipy.optimize中的函数相似的接口。此函数的定义是：

deffmin_cgprox(f,fprime,g_prox,x0,rtol=1e-6,maxiter=1000,verbose=0,default_step_size=1.):"""
    proximal gradient-descent solver for optimization problems of the form

                       minimize_x f(x) + g(x)

    where f is a smooth function and g is a (possibly non-smooth)
    function for which the proximal operator is known.

    Parameters
    ----------
    f : callable
        f(x) returns the value of f at x.

    f_prime : callable
        f_prime(x) returns the gradient of f.

    g_prox : callable of the form g_prox(x, alpha)
        g_prox(x, alpha) returns the proximal operator of g at x
        with parameter alpha.

    x0 : array-like
        Initial guess

    maxiter : int
        Maximum number of iterations.

    verbose : int
        Verbosity level, from 0 (no output) to 2 (output on each iteration)

    default_step_size : float
        Starting value for the line-search procedure.

    Returns
    -------
    res : OptimizeResult
        The optimization result represented as a
        ``scipy.optimize.OptimizeResult`` object. Important attributes are:
        ``x`` the solution array, ``success`` a Boolean flag indicating if
        the optimizer exited successfully and ``message`` which describes
        the cause of the termination. See `scipy.optimize.OptimizeResult`
        for a description of other attributes.
    """