human
I wrote the below code

    (x, x_min, x_max, x_n) = (None, None, None, None)
    (y, y_min, y_max, y_n) = (None, None, None, None)
    try:
        f = sympify(f)
    except SympifyError:
        raise ValueError('f    could    not    be    interpreted    as    a    SymPy    function')
    try:
        (x, x_min, x_max, x_n) = x_args
        (y, y_min, y_max, y_n) = y_args
    except AttributeError:
        raise ValueError('x_args    and    y_args    must    be    tuples    of    the    form    (var,    min,    max,    intervals)')
    x_l = float((x_max - x_min))
    x_d = (x_l / float(x_n))
    x_a = np.arange(float(x_min), (float(x_max) + x_d), x_d)
    y_l = float((y_max - y_min))
    y_d = (y_l / float(y_n))
    y_a = np.arange(float(y_min), (float(y_max) + y_d), y_d)
    def meshgrid(x, y):
        '\n                                Taken    from    matplotlib.mlab.meshgrid.\n                                '
        x = np.array(x)
        y = np.array(y)
        (numRows, numCols) = (len(y), len(x))
        x.shape = (1, numCols)
        X = np.repeat(x, numRows, 0)
        y.shape = (numRows, 1)
        Y = np.repeat(y, numCols, 1)
        return (X, Y)
    (X, Y) = np.meshgrid(x_a, y_a)
    Z = np.ndarray((len(X), len(X[0])))
    for j in range(len(X)):
        for k in range(len(X[0])):
            try:
                Z[j][k] = float(f.subs(x, X[j][k]).subs(y, Y[j][k]))
            except (TypeError, NotImplementedError):
                Z[j][k] = 0
    return (X, Y, Z)

What's a good function header?
 Here's a good function header?
assistant
#Here's a good function header.

def sample3d(f, x_args, y_args):