def __bln_cut_expression(self, n0, n1, u0, u1, v0, v1, abs_value, delta):
    n = self.width
    dd = np.log(((2 * np.log(n)) / delta))
    v = self.variance
    m = ((1.0 / ((n0 - self.mint_min_window_length) + 1)) + (1.0 / ((n1 - self.mint_min_window_length) + 1)))
    epsilon = (np.sqrt((((2 * m) * v) * dd)) + ((((1.0 * 2) / 3) * dd) * m))
    return (np.absolute(abs_value) > epsilon)
def __bln_cut_expression(self, n0, n1, u0, u1, v0, v1, abs_value, delta):
    n = self.width
    dd = np.log(((2 * np.log(n)) / delta))
    v = self.variance
    m = ((1.0 / ((n0 - self.mint_min_window_length) + 1)) + (1.0 / ((n1 - self.mint_min_window_length) + 1)))
    epsilon = (np.sqrt((((2 * m) * v) * dd)) + ((((1.0 * 2) / 3) * dd) * m))
    return (np.absolute(abs_value) > epsilon)