[SciPy-User] Ax = b for symmetric positive definite matrix
Dag Sverre Seljebotn
Wed Dec 8 07:47:57 CST 2010
On 12/08/2010 02:38 PM, Mathieu Blondel wrote:
> Hi everyone,
> I want to solve equations of the form Ax = b or Ax = B where A is a
> dense symmetric positive definite matrix. I want to be able to support
> potentially large A so I find it convenient to store A as a 1d-vector
> containing the upper part of the matrix only. It's easy to convert
> this 1d representation to a 2d-representation, and vice-versa.
> I believe functions like linalg.solve (when passed sym_pos=True) and
> linalg.cholesky would benefit from accepting 1d-arrays of this kind.
> Is there a memory efficient way of solving my equations for a large A?
Perhaps not the answer you're looking for, but:
It is not supported in SciPy yet, but if you want to play with calling
LAPACK directly, this is supported through sppsv/dppsv/cppsv/zppsv. For
instance you could modify the scipy/linalg/*.pyf files to include the
function, rebuild SciPy. Or, search for "tokyo cython lapack" and play
More information about the SciPy-User