Wed Aug 17 19:59:14 2022 r83t_test(): Python version: 3.6.9 Test r83t(). r83t_cg_test r83t_cg applies CG to an R83T matrix. Number of variables N = 10 Norm of residual ||Ax-b|| = 2.278663452567752e-15 Norm of error ||x1-x2|| = 1.4572503233590227e-15 R83T_DIF2_TEST R83T_DIF2 sets an R83T matrix to the second difference. R83T matrix: Col: 0 1 2 3 4 Row --- 0: 2 -1 1: -1 2 -1 2: -1 2 -1 3: -1 2 -1 4: -1 2 r83t_gs_sl_test r83t_gs_sl solves a linear system using Gauss-Seidel iteration, with R83T matrix storage. Matrix order N = 10 Iterations per call = 25 Current solution estimate: 0: 0.634606 1: 1.3265 2: 2.09566 3: 2.95451 4: 3.90741 5: 4.95088 6: 6.07442 7: 7.2619 8: 8.4933 9: 9.74665 Current solution estimate: 0: 0.953567 1: 1.9145 2: 2.88533 3: 3.86757 4: 4.86173 5: 5.86733 6: 6.88302 7: 7.90675 8: 8.93599 9: 9.968 Current solution estimate: 0: 0.994126 1: 1.98918 2: 2.98549 3: 3.98325 4: 4.98251 5: 5.98322 6: 6.9852 7: 7.9882 8: 8.9919 9: 9.99595 R83T_INDICATOR_TEST R83T_INDICATOR sets an R83T indicator matrix. We check three cases, MN. R83T indicator matrix: Col: 0 1 2 3 4 Row --- 0: 11 12 1: 21 22 23 2: 32 33 34 R83T indicator matrix: Col: 0 1 2 3 4 Row --- 0: 11 12 1: 21 22 23 2: 32 33 34 3: 43 44 45 4: 54 55 R83T indicator matrix: Col: 0 1 2 Row --- 0: 11 12 1: 21 22 23 2: 32 33 3: 43 r83t_jac_sl_test r83t_jac_sl solves a linear system using Jacobi iteration, with R83T matrix storage. Matrix order N = 10 Iterations per call = 25 Current solution estimate: 0: 0.315171 1: 0.727797 2: 1.14042 3: 1.82758 4: 2.51474 5: 3.59047 6: 4.6662 7: 6.1282 8: 7.5902 9: 9.2951 Current solution estimate: 0: 0.757545 1: 1.51509 2: 2.34936 3: 3.18363 4: 4.14729 5: 5.11094 6: 6.21581 7: 7.32068 8: 8.53366 9: 9.74665 Current solution estimate: 0: 0.910021 1: 1.83432 2: 2.75863 3: 3.72124 4: 4.68386 5: 5.69666 6: 6.70946 7: 7.76839 8: 8.82731 9: 9.91366 R83T_MTV_TEST R83T_MTV multiplies an R83T matrix transposed times a vector. M = 5 N = 6 The R83T matrix A: Col: 0 1 2 3 4 Row --- 0: 11 12 1: 21 22 23 2: 32 33 34 3: 43 44 45 4: 54 55 Col: 5 Row --- 4: 56 The vector x: 0: 1 1: 2 2: 3 3: 4 4: 5 The product b = A*x: 0: 53 1: 152 2: 317 3: 548 4: 455 5: 280 R83T_MV_TEST R83T_MV multiplies an R83T matrix times a vector. M = 5 N = 6 The R83T matrix A: Col: 0 1 2 3 4 Row --- 0: 11 12 1: 21 22 23 2: 32 33 34 3: 43 44 45 4: 54 55 Col: 5 Row --- 4: 56 The vector x: 0: 1 1: 2 2: 3 3: 4 4: 5 5: 6 The product b = A*x: 0: 35 1: 134 2: 299 3: 530 4: 827 R83T_PRINT_TEST R83T_PRINT prints an R83T matrix. We check three cases, MN. R83T matrix: Col: 0 1 2 3 4 Row --- 0: 11 12 1: 21 22 23 2: 32 33 34 R83T matrix: Col: 0 1 2 3 4 Row --- 0: 11 12 1: 21 22 23 2: 32 33 34 3: 43 44 45 4: 54 55 R83T matrix: Col: 0 1 2 Row --- 0: 11 12 1: 21 22 23 2: 32 33 3: 43 R83T_PRINT_SOME_TEST R83T_PRINT_SOME prints some of an R83T matrix. M = 9 N = 9 Rows 3:6, Cols 5:8: Col: 5 6 7 8 Row --- 4: 56 5: 66 67 6: 76 77 78 R83T_RANDOM_TEST R83T_RANDOM returns a random R83T matrix. R83T matrix: Col: 0 1 2 3 4 Row --- 0: 0.0171212 0.528337 1: 0.663756 0.822474 0.89032 2: 0.318918 0.0145654 0.338242 3: 0.594969 0.757417 0.852499 4: 0.116183 0.809452 R83T_RES_TEST R83T_RES evaluates the residual given an approximate solution of a linear system A*x=b. M = 5 N = 5 The R83T matrix A: Col: 0 1 2 3 4 Row --- 0: 2 -1 1: -1 2 -1 2: -1 2 -1 3: -1 2 -1 4: -1 2 The right hand side B: 0: 0 1: 0 2: 0 3: 0 4: 6 The solution X: 0: 1 1: 2 2: 3 3: 4 4: 5 The residual b-A*x: 0: 2.22045e-16 1: -4.44089e-16 2: 8.88178e-16 3: 0 4: 0 R83T_TO_R8GE_TEST R83T_TO_R8GE converts an R83T matrix to R8GE format. M = 5 N = 5 The R83T indicator matrix: Col: 0 1 2 3 4 Row --- 0: 11 12 1: 21 22 23 2: 32 33 34 3: 43 44 45 4: 54 55 The R8GE format matrix: [[11. 12. 0. 0. 0.] [21. 22. 23. 0. 0.] [ 0. 32. 33. 34. 0.] [ 0. 0. 43. 44. 45.] [ 0. 0. 0. 54. 55.]] R83T_ZEROS_TEST R83T_ZEROS sets an R83T matrix to zero. R83T matrix: Col: 0 1 2 3 4 Row --- 0: 0 0 1: 0 0 0 2: 0 0 0 3: 0 0 0 4: 0 0 r83t_test(): Normal end of execution. Wed Aug 17 19:59:14 2022