python计算牛顿迭代多项式实例分析

本文实例讲述了python计算牛顿迭代多项式的方法。分享给大家供大家参考。具体实现方法如下：

    ''' p = evalPoly(a,xData,x).
      Evaluates Newton's polynomial p at x. The coefficient
      vector 'a' can be computed by the function 'coeffts'.
      a = coeffts(xData,yData).
      Computes the coefficients of Newton's polynomial.
    '''  
    def evalPoly(a,xData,x):
      n = len(xData) - 1 # Degree of polynomial
      p = a[n]
      for k in range(1,n+1):
        p = a[n-k] + (x -xData[n-k])*p
      return p
    def coeffts(xData,yData):
      m = len(xData) # Number of data points
      a = yData.copy()
      for k in range(1,m):
        a[k:m] = (a[k:m] - a[k-1])/(xData[k:m] - xData[k-1])
      return a

希望本文所述对大家的Python程序设计有所帮助。