New answers tagged matrix
0
A couple of mistakes on sight:
def RECTSPA(A,grid):
""" description: what does this do ? """
m,n = A.shape
I = np.eye(n)
if m >= 2*n:
a = A[n+1:m,:] # ◀◀◀ A[n:], python is 0-origin
Q, R = np.linalg.qr(a)
T, U = schur(a,output='real')
R[0:n] # ◀◀◀...
1
I was fooling around with sparse representation of K_n (tridiagonal -1 2 -1)
which theoretically has a determinant of n+1. I ran across this old post.
Both SuperLU and CHOLMOD don't seem to have the precision to get the correct determinant once you get above n=1e6.
from scipy.sparse import diags
from scipy.sparse.linalg import splu
from sksparse.cholmod ...
2
The inverse of the (1,1) block of
$$
\begin{bmatrix}
A & B\\
C & D
\end{bmatrix}^{-1}
$$
is $A-BD^{-1}C$ (Schur complement). This is what you are trying to compute, if I understand correctly from your explanation ("marginalize" may be standard in your domain, but it is not standard linear algebra language). So at least you can reduce to ...
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