05 October 2018 08:53:01 PM CLAPACK_TEST C++ version Test the CLAPACK library. CLAPACK is a C translation of the FORTRAN77 BLAS and LAPACK libraries. DGBTRF_TEST Demonstrate the use of DGBTRF to factor a banded matrix and DGBTRS to solve an associated linear system using double precision real arithmetic. Coefficient matrix: 2 -1 0 0 -1 2 -1 0 0 -1 2 -1 0 0 -1 2 Right hand side: 0 0 0 5 Computed solution: 1 2 3 4 DGESV_TEST Demonstrate the use of DGESV to solve a linear system using double precision real arithmetic. Coefficient matrix A: Col: 0 1 2 3 Row 0: 1 -1 2 -1 1: 2 -2 3 -3 2: 1 1 1 0 3: 1 -1 4 3 Right hand side B: 0: -8 1: -20 2: -2 3: 4 Return value of error flag INFO = 0 Computed solution X: 0: -7 1: 3 2: 2 3: 2 DGESVD_TEST Demonstrate the use of DGESVD to compute the singular value decomposition A = U * S * V', using double precision real arithmetic. Coefficient matrix A: Col: 0 1 2 3 Row 0: 16 2 3 13 1: 5 11 10 8 2: 9 7 6 12 3: 4 14 15 1 Error flag INFO = 0 Singular values: 0: 34 1: 17.8885 2: 4.47214 3: 4.17281e-16 DGETRF_TEST Demonstrate the use of: DGETRF to factor a general matrix A, DGETRS to solve A*x=b after A has been factored, using double precision real arithmetic. Coefficient matrix A: Col: 0 1 2 3 Row 0: 1 -1 2 -1 1: 2 -2 3 -3 2: 1 1 1 0 3: 1 -1 4 3 Return value of DGETRF error flag INFO = 0 Right hand side B: 0: -8 1: -20 2: -2 3: 4 Return value of DGETRS error flag INFO = 0 Computed solution X: 0: -7 1: 3 2: 2 3: 2 DGETRI_TEST For a double precision real matrix (D) in general storage mode (GE): DGETRF factors a general matrix; DGETRI computes the inverse. The matrix A: Col: 0 1 2 Row 0: 1 2 3 1: 4 5 6 2: 7 8 0 The inverse matrix: Col: 0 1 2 Row 0: -1.77778 0.888889 -0.111111 1: 1.55556 -0.777778 0.222222 2: -0.111111 0.222222 -0.111111 DNRM2_TEST DNRM2 computes the Euclidean norm of a double precision real vector. The vector X: 0: 1 1: 2 2: 3 VALUE = 3.74166 DSYEV_TEST For a double precision real matrix (D) in symmetric storage mode (SY): For a symmetric matrix in general storage, DSYEV computes eigenvalues and eigenvectors; The matrix A: Col: 0 1 2 3 4 Row 0: 0 2.44949 0 0 0 1: 2.44949 0 3.16228 0 0 2: 0 3.16228 0 3.4641 0 3: 0 0 3.4641 0 3.4641 4: 0 0 0 3.4641 0 5: 0 0 0 0 3.16228 6: 0 0 0 0 0 Col: 5 6 Row 0: 0 0 1: 0 0 2: 0 0 3: 0 0 4: 3.16228 0 5: 0 2.44949 6: 2.44949 0 The eigenvalues: 0: -6 1: -4 2: -2 3: -6.70723e-16 4: 2 5: 4 6: 6 The eigenvector matrix: Col: 0 1 2 3 4 Row 0: -0.125 0.306186 0.484123 -0.559017 -0.484123 1: 0.306186 -0.5 -0.395285 -3.15775e-16 -0.395285 2: -0.484123 0.395285 -0.125 0.433013 0.125 3: 0.559017 3.36779e-16 0.433013 -8.62557e-17 0.433013 4: -0.484123 -0.395285 -0.125 -0.433013 0.125 5: 0.306186 0.5 -0.395285 1.57289e-16 -0.395285 6: -0.125 -0.306186 0.484123 0.559017 -0.484123 Col: 5 6 Row 0: -0.306186 0.125 1: -0.5 0.306186 2: -0.395285 0.484123 3: 1.04083e-17 0.559017 4: 0.395285 0.484123 5: 0.5 0.306186 6: 0.306186 0.125 ZGESV_TEST Demonstrate the use of ZGESV to solve a linear system using double precision complex arithmetic. Coefficient matrix A: -0.707107 + 0.587785 i -0.707107 + 0.951057 i -1.83697e-16 + 0.587785 i -1.83697e-16 + 0.951057 i Right hand side B: 1 + 1 i 2 + 3 i Return value of error flag INFO = 0 Computed solution X: -4.55583 + 12.9104 i 5.97005 + -10.082 i CLAPACK_TEST: Normal end of execution. 05 October 2018 08:53:01 PM