Then you have to dig in deeper: import numarray import numarray.linear_algebra import numarray.linear_algebra.lapack_lite2 as lapack_lite piv = numarray.zeros((n,), "l") outcome = lapack_lite.dgesv(n, nrhs, a, lda, piv, b, ldb, 0) outcome['info'] is the 'info' parameter set by LAPACK. You have to make sure that 'a' and 'b' are in Fortran order because you're calling Fortran code. Here is a sample code:
a=numarray.array([[1,2,3],[4,5,6]], 'd') a.is_fortran_contiguous() 0 a.is_c_array() True a.is_f_array() 0 a.transpose() a.is_fortran_contiguous() 1 a.is_c_array() False a.is_f_array() True
Call to 'transpose()' made it a Fortran array but it transposed the array too. Piotr meng@are.berkeley.edu wrote:
Thanks, Piotr!
What I actually want is the lower (L) and upper triangular matrix (U) from matrix 'a'. How to get it?
Xiangyi
At 15:14 2005-10-4 -0400, you wrote:
You would have to be more specific. If you just want to solve a system of linear equations with matrix 'a' and right-hand-side 'b':
import numarray.linear_algebra as LA
x = LA.solve_linear_equations(a, b)
Unlike LAPACK, the above will leave your 'a' untouched. So, if you have another right hand side 'b1' and the same matrix 'a' you'll have to pay the cost of factorization all over again.
There is a way around it but I don't know what you really need.
Piotr
meng@are.berkeley.edu wrote:
Hi there- Can someone help me on this? Thanks! Best, Xiangyi Xiangyi Meng Department of Agricultural and Resource Economics Room 303, Giannini Hall #3310 University of California, Berkeley Berkeley, CA 94720-3310 Tel: (510) 643-4124 Fax: (510) 643-8911 Email: meng@are.berkeley.edu
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Best, Xiangyi
Xiangyi Meng Department of Agricultural and Resource Economics Room 303, Giannini Hall #3310 University of California, Berkeley Berkeley, CA 94720-3310 Tel: (510) 643-4124 Fax: (510) 643-8911 Email: meng@are.berkeley.edu