Tue May 20 21:21:07 2025 condition_test(): python version: 3.10.12 numpy version: 1.26.4 Test condition() combin_test(): combin() computes the COMBIN matrix. COMBIN matrix: Col: 0 1 2 3 Row 0 : 13.8 4.2 4.2 4.2 1 : 4.2 13.8 4.2 4.2 2 : 4.2 4.2 13.8 4.2 3 : 4.2 4.2 4.2 13.8 conex1_test() conex1() computes the CONEX1 matrix. CONEX1 matrix: Col: 0 1 2 3 Row 0 : 1 -1 -188.151 0 1 : 0 1 94.0755 -94.0755 2 : 0 1 95.0755 -95.0755 3 : 0 0 0 94.0755 conex2_test() conex2() computes the CONEX2 matrix. CONEX2 matrix: Col: 0 1 2 Row 0 : 1 0.94686 -2 1 : 0 0.230522 -0.230522 2 : 0 0 1 conex3_test conex3 computes the CONEX3 matrix. CONEX3 matrix: Col: 0 1 2 3 4 Row 0 : 1 0 0 0 0 1 : -1 1 0 0 0 2 : -1 -1 1 0 0 3 : -1 -1 -1 1 0 4 : -1 -1 -1 -1 -1 conex4_test conex4 computes the CONEX4 matrix. CONEX4 matrix: Col: 0 1 2 3 Row 0 : 7 10 8 7 1 : 6 8 10 9 2 : 5 7 9 10 3 : 5 7 6 5 kahan_test() kahan() computes the KAHAN matrix. KAHAN matrix: Col: 0 1 2 3 4 Row 0 : 0.49849 -0.432139 -0.432139 -0.432139 -0.432139 1 : 0 0.248492 -0.215417 -0.215417 -0.215417 2 : 0 0 0.123871 -0.107383 -0.107383 3 : 0 0 0 0.0617483 -0.0535293 4 : 0 0 0 0 0.0307809 r8_sign_test(): r8_sign() returns the sign of an R8. R8 R8_SIGN(R8) -1.2500 -1 -0.2500 -1 0.0000 1 0.5000 1 9.0000 1 r8ge_fa_test01() r8ge_fa() computes the LU factors, r8ge_sl() solves a factored system. Matrix order N = 10 Solution: 0: 1 1: 2 2: 3 3: 4 4: 5 5: 6 6: 7 7: 8 8: 9 9: 10 Solution: 0: 1 1: 1 2: 1 3: 1 4: 1 5: 1 6: 1 7: 1 8: 1 9: 1 Solution of transposed system: 0: 1 1: 2 2: 3 3: 4 4: 5 5: 6 6: 7 7: 8 8: 9 9: 10 r8ge_fa_test02() r8ge_fa() computes the LU factors, r8ge_sl() solves a factored system. Matrix order N = 5 The matrix: Col: 0 1 2 3 4 Row 0 : 0.477711 0.679334 0.513384 0.376108 0.711758 1 : 0.585676 0.0374367 0.297789 0.151487 0.307871 2 : 0.191085 0.0790129 0.613586 0.0162279 0.542761 3 : 0.650726 0.25831 0.711132 0.920007 0.463165 4 : 0.609014 0.771802 0.41754 0.950442 0.870799 The compressed LU factors: Col: 0 1 2 3 4 Row 0 : 0.650726 0.25831 0.711132 0.920007 0.463165 1 : -0.900035 0.53005 -0.248008 0.0894081 0.437324 2 : -0.293649 -0.00596262 -0.433518 -0.64365 0.0519365 3 : -0.73412 -0.923882 0.508533 -0.857617 0.452815 4 : -0.935899 0.367987 0.937082 -0.826951 -0.380341 The pivot vector P: [3 4 4 4 4] Solution: 0: 1 1: 2 2: 3 3: 4 4: 5 r8vec_max_abs_index_test(): r8vec_max_abs_index(): index of entry of maximum absolute value Input vector: 0: 1.82834 1: 2.73406 2: -7.22675 3: 3.30866 4: 7.223 5: -5.21684 6: 8.45964 7: 6.24354 8: 6.27166 9: -5.74623 Maximum index: 6 r8vec_uniform_unit_test(): r8vec_uniform_unit() returns a random R8VEC on the surface of the unit M sphere. Vector: 0: 0.815451 1: 0.343792 2: 0.10343 3: 0.333844 4: -0.30773 Vector: 0: -0.519542 1: -0.302827 2: 0.0805951 3: -0.476508 4: -0.636252 Vector: 0: 0.916645 1: 0.257402 2: 0.056121 3: 0.0371409 4: 0.29829 Vector: 0: 0.939995 1: -0.0926196 2: 0.17278 3: -0.157007 4: -0.230928 Vector: 0: -0.11292 1: -0.134036 2: 0.211061 3: 0.938231 4: 0.210855 cond_test() cond() is the condition number estimator built into Python. Matrix Order Condition Estimate Combinatorial 4 10 10 CONEX1 4 80601 80601 CONEX2 3 601.97 601.97 CONEX3 5 80 80 CONEX4 4 4488 4488 KAHAN 4 646.712 646.712 RANDOM 4 12.8733 12.8733 RANDOM 4 19.6417 19.6417 RANDOM 4 41.8718 41.8718 RANDOM 4 22.1624 22.1624 RANDOM 4 14.4138 14.4138 condition_hager_test() condition_hager() estimates the L1 condition number for a matrix in general storage. Matrix Order Condition Hager Combinatorial 4 10 10 CONEX1 4 80601 810.02 CONEX2 3 601.97 601.97 CONEX3 5 80 80 CONEX4 4 4488 4488 KAHAN 4 646.712 646.712 RANDOM 4 244.088 244.088 RANDOM 4 55.4073 55.4073 RANDOM 4 24.5502 24.5502 RANDOM 4 49.6848 49.6848 RANDOM 4 16.3879 16.3879 condition_linpack_test(): condition_linpack() estimates the L1 condition number for a matrix in general storage. Matrix Order Condition Linpack Combinatorial 4 10 7 CONEX1 4 80601 565.586 CONEX2 3 601.97 7.50657 CONEX3 5 80 5 CONEX4 4 4488 3238.09 KAHAN 4 646.712 574.664 RANDOM 4 23.2917 20.6477 RANDOM 4 44.266 31.6756 RANDOM 4 77.8956 55.0803 RANDOM 4 42.9085 34.8235 RANDOM 4 253.716 223.26 condition_sample1_test() condition_sample1() estimates the L1 condition number using sampling for a matrix in general storage. Matrix Samples Order Condition Estimate Combinatorial 10 4 10 7 Combinatorial 1000 4 10 8.5934 Combinatorial 100000 4 10 9.81053 CONEX1 10 4 80601 6.05258 CONEX1 1000 4 80601 89.5643 CONEX1 100000 4 80601 388.639 CONEX2 10 3 601.97 5.58653 CONEX2 1000 3 601.97 86.3932 CONEX2 100000 3 601.97 264.554 CONEX3 10 5 80 4.41558 CONEX3 1000 5 80 16.3553 CONEX3 100000 5 80 38.0937 CONEX4 10 4 4488 10.6988 CONEX4 1000 4 4488 329.142 CONEX4 100000 4 4488 263.861 KAHAN 10 4 646.712 3.88874 KAHAN 1000 4 646.712 28.9261 KAHAN 100000 4 646.712 74.5733 RANDOM 10 4 28.959 10.7581 RANDOM 1000 4 28.959 19.4921 RANDOM 100000 4 28.959 24.9465 RANDOM 10 4 101.91 4.98495 RANDOM 1000 4 101.91 27.7742 RANDOM 100000 4 101.91 66.8623 RANDOM 10 4 223.641 5.4535 RANDOM 1000 4 223.641 18.4552 RANDOM 100000 4 223.641 99.396 RANDOM 10 4 14.3106 6.35953 RANDOM 1000 4 14.3106 9.68688 RANDOM 100000 4 14.3106 13.1137 RANDOM 10 4 10.8693 5.0283 RANDOM 1000 4 10.8693 8.55853 RANDOM 100000 4 10.8693 10.4099 condition_test(): Normal end of execution. Tue May 20 21:22:02 2025