Fri Aug 12 16:11:47 2022 asa006_test(): Python version: 3.6.9 Test asa006() asa006_test01(): cholesky() computes the Cholesky factorization of a symmetric positive definite matrix. A compressed storage format is used. Here we look at the matrix A which is N+1 on the diagonal and N on the off diagonals. N Null RMS error 1 0 0.0000 2 0 0.0000 3 0 0.0000 4 0 0.0000 5 0 0.0000 6 0 0.0000 7 0 0.0000 8 0 0.0000 9 0 0.0000 10 0 0.0000 11 0 0.0000 12 0 0.0000 13 0 0.0000 14 0 0.0000 asa006_test02(): cholesky() computes the Cholesky factorization of a symmetric positive definite matrix. A compressed storage format is used. Here we look at the Hilbert matrix A(I,J) = 1 / ( I + J - 1 ) We expect errors to grow quickly with N. N Null RMS error 1 0 0.0000 2 0 0.0000 3 0 0.0000 4 0 0.0000 5 0 0.0000 6 0 0.0000 7 0 0.0000 8 0 0.0000 9 0 0.0000 10 1 0.0000 11 1 0.0000 12 1 0.2106 13 1 0.2917 14 1 0.3504 asa006_test03(): subchl() computes the Cholesky factor of a submatrix of a symmetric positive definite matrix. A compressed storage format is used. Here we look at the Hilbert matrix A(I,J) = 1/(I+J-1). For this particular matrix, we expect the errors to grow rapidly. N NSUB NULLTY DET RMS 15 1 0 1.0000e+00 0.0000e+00 15 2 0 8.3333e-02 0.0000e+00 15 3 0 4.6296e-04 0.0000e+00 15 4 0 1.6534e-07 0.0000e+00 15 5 0 3.7493e-12 1.3878e-17 15 6 0 5.3673e-18 1.3878e-17 15 7 0 4.8358e-25 2.4037e-17 15 8 0 2.7371e-33 3.1032e-17 15 9 0 9.7203e-43 3.8006e-17 15 10 1 0.0000e+00 2.2267e-11 15 11 Numerical singularity! 15 12 Numerical singularity! 15 13 Numerical singularity! 15 14 Numerical singularity! 15 15 Numerical singularity! asa006_test(): Normal end of execution. Fri Aug 12 16:11:47 2022