有良好的C矩阵求逆程序 [英] Good matrix inversion routines in C

问题描述

作为一个Python code的数值计算的一部分，我必须有所反转大型（稀疏）矩阵（100×100〜）很多次。我真的想加快程序，方式之一向我建议是在C调用一个子程序矩阵求逆一步。

是否有任何建议的高效和完善的测试C例程完成这个任务？

感谢您。

解决方案

 ＆GT;＆GT;＆GT;从numpy的进口*
＆GT;＆GT;＆GT;从numpy.linalg进口INV
＆GT;＆GT;＆GT;从scipy.sparse进口csr_matrix
＆GT;＆GT;＆GT; M =矩阵（[3,1,5]，[1,0,8]，[2,1,4]]）
＆GT;＆GT;＆GT; S = csr_matrix（米）
＆GT;＆GT;＆GT; INVS = INV（一）＃逆稀疏矩阵
＆GT;＆GT;＆GT;点（A，INVA）＃检查的结果，应该是机器precision眼内（3）
csr_matrix（[[1.00000000e-00，2.77555756e-17，3.60822483e-16]，
           [0.00000000e + 00，+ 1.00000000e 00，0.00000000e + 00]
           [-1.11022302e-16，0.00000000e + 00，1.00000000e + 00]]）
 

难道真是你需要逆？您可能能够实现自己的目标，而不倒置：

  

在这里你的案例真的的需要逆是罕见的。此外，该
  稀疏矩阵的逆不一定稀疏。通常情况下，
  反相是比LU分解更加昂贵，而且容易
  舍入误差。

- http://mail.scipy.org/ pipermail / SciPy的用户/ 2007年10月/ 013936.html

- > <一href=\"http://docs.scipy.org/doc/scipy/reference/generated/scipy.sparse.linalg.factorized.html#scipy.sparse.linalg.factorized\" rel=\"nofollow\">http://docs.scipy.org/doc/scipy/reference/generated/scipy.sparse.linalg.factorized.html#scipy.sparse.linalg.factorized

As part of a python code for a numerical calculation, I must invert somewhat large (sparse) matrices (~100x100) many times. I would really like to speed up the program, and one of the ways suggested to me is to call to a subroutine in C for the matrix inversion step.

Are there any recommended efficient and well-tested C routines for this task?

Thank you.

解决方案

>>> from numpy import *
>>> from numpy.linalg import inv
>>> from scipy.sparse import csr_matrix
>>> m = matrix([[3,1,5],[1,0,8],[2,1,4]])
>>> s = csr_matrix(m)
>>> invs = inv(a) # Inverse sparse matrix
>>> dot(a,inva) # Check the result, should be eye(3) within machine precision
csr_matrix([[ 1.00000000e-00, 2.77555756e-17, 3.60822483e-16],
           [ 0.00000000e+00, 1.00000000e+00, 0.00000000e+00],
           [ -1.11022302e-16, 0.00000000e+00, 1.00000000e+00]])

Is it really the inverse you need? You may be able to achieve your goal without inversion:

Cases where you really need the inverse are rare. Moreover, the inverse of a sparse matrix is not necessarily sparse. Typically, inverting is more expensive than an LU factorization and prone to rounding errors.

-- http://mail.scipy.org/pipermail/scipy-user/2007-October/013936.html

--> http://docs.scipy.org/doc/scipy/reference/generated/scipy.sparse.linalg.factorized.html#scipy.sparse.linalg.factorized

这篇关于有良好的C矩阵求逆程序的文章就介绍到这了，希望我们推荐的答案对大家有所帮助，也希望大家多多支持IT屋！