牛顿迭代法，与传统意义上的迭代法类似，只是将f(x)进行泰勒级数展开，只保留前两项，然后进行迭代。其迭代方程为x_(k+1)=x_k-(f(x_k))/(f^' (x_k))。
从编程上来讲，以上述方程对固定范围的复数域中的每个点作为初始点进行迭代，每个点都会收敛到该方程的一个解，对不同的解涂抹不同的颜色，就会看出其收敛范围。如果想得到其精确解所在位置，可通过到达给定精度的迭代次数进行判断，因为该点越接近精确解，其迭代速度越快。以下对老师提供的程序和自己写的程序进行一下对比，选用方程为：y=x^d-1。其中d=3。(Newton iterative method, similar to the traditional iterative method, only f (x) expansion of the Taylor series, only retain the first two terms, and then iterative. The iterative equation is x_ (k+1) =x_k- (f (x_k) (f^') / (x_k)).

From the programming of speaking, in the above equation in the complex domain to a fixed range of each point as the starting point for each iteration will converge to a solution of the equation, to apply different colors to different solution, you will see that the convergence range. If we want to get the exact location of the solution, we can judge by the number of iterations to the given precision, because the closer the point is to the exact solution, the faster the iteration rate is. The following provides a comparison between the program provided by the teacher and the program written by himself, and the equation is: y=x^d-1. Among them, d=3.)