注册 登录
  • 欢迎访问开心洋葱网站,在线教程,推荐使用最新版火狐浏览器和Chrome浏览器访问本网站,欢迎加入开心洋葱 QQ群
  • 为方便开心洋葱网用户,开心洋葱官网已经开启复制功能!
  • 欢迎访问开心洋葱网站,手机也能访问哦~欢迎加入开心洋葱多维思维学习平台 QQ群
  • 如果您觉得本站非常有看点,那么赶紧使用Ctrl+D 收藏开心洋葱吧~~~~~~~~~~~~~!
  • 由于近期流量激增,小站的ECS没能经的起亲们的访问,本站依然没有盈利,如果各位看如果觉着文字不错,还请看官给小站打个赏~~~~~~~~~~~~~!

N lowest eigenvalues of the tridiagonal matrix in python

python 水墨上仙 2939次浏览 已收录 手机上查看

N lowest eigenvalues of the tridiagonal matrix in python

''' r = lamRange(d,c,N).
    Returns the sequence {r[0],r[1],...,r[N]} that
    separates the N lowest eigenvalues of the tridiagonal
    matrix [A] = [c\d\c]; that is, r[i] < lam[i] < r[i+1].
'''
from numpy import ones
from sturmSeq import *
from gerschgorin import *
 
def lamRange(d,c,N):
    lamMin,lamMax = gerschgorin(d,c)
    r = ones(N+1)
    r[0] = lamMin
  # Search for eigenvalues in descending order  
    for k in range(N,0,-1):
      # First bisection of interval(lamMin,lamMax)
        lam = (lamMax + lamMin)/2.0
        h = (lamMax - lamMin)/2.0
        for i in range(1000):
          # Find number of eigenvalues less than lam
            p = sturmSeq(d,c,lam)
            numLam = numLambdas(p)
          # Bisect again & find the half containing lam 
            h = h/2.0
            if numLam < k: lam = lam + h
            elif numLam > k: lam = lam - h
            else: break
      # If eigenvalue located, change the upper limit
      # of search and record it in [r]
        lamMax = lam
        r[k] = lam
    return r


开心洋葱 , 版权所有丨如未注明 , 均为原创丨未经授权请勿修改 , 转载请注明N lowest eigenvalues of the tridiagonal matrix in python
喜欢 (0)
[开心洋葱]
分享 (0)
关于作者:
水墨上仙
……
加载中……