09 May 2025 9:19:55.819 PM minpack_test(): FORTRAN90 version Test minpack(). CHKDER_TEST CHKDER compares a user supplied jacobian and a finite difference approximation to it and judges whether the jacobian is correct. On the first test, use a correct jacobian. Evaluation point X: 1 0.50000000 2 0.50000000 3 0.50000000 4 0.50000000 5 0.50000000 Sampled function values F(X) and F(XP) 1 -3.00000 -3.00000 2 -3.00000 -3.00000 3 -3.00000 -3.00000 4 -3.00000 -3.00000 5 -0.968750 -0.968750 Computed jacobian 2.00000 1.00000 1.00000 1.00000 1.00000 1.00000 2.00000 1.00000 1.00000 1.00000 1.00000 1.00000 2.00000 1.00000 1.00000 1.00000 1.00000 1.00000 2.00000 1.00000 0.625000E-01 0.625000E-01 0.625000E-01 0.625000E-01 0.625000E-01 CHKDER gradient component error estimates: > 0.5, the component is probably correct. < 0.5, the component is probably incorrect. 1 1.00000 2 1.00000 3 1.00000 4 1.00000 5 1.00000 Repeat the test, but use a "bad" jacobian and see if the routine notices! Evaluation point X: 1 0.50000000 2 0.50000000 3 0.50000000 4 0.50000000 5 0.50000000 Sampled function values F(X) and F(XP) 1 -3.00000 -3.00000 2 -3.00000 -3.00000 3 -3.00000 -3.00000 4 -3.00000 -3.00000 5 -0.968750 -0.968750 Computed jacobian 2.02000 1.00000 1.00000 1.00000 1.00000 1.00000 2.00000 -1.00000 1.00000 1.00000 1.00000 1.00000 2.00000 1.00000 1.00000 1.00000 1.00000 1.00000 2.00000 1.00000 0.625000E-01 0.625000E-01 0.625000E-01 0.625000E-01 0.625000E-01 CHKDER gradient component error estimates: > 0.5, the component is probably correct. < 0.5, the component is probably incorrect. 1 0.354955 2 0.994216E-01 3 1.00000 4 1.00000 5 1.00000 HYBRD1_TEST HYBRD1 solves a nonlinear system of equations. Initial X: 1 3.0000000 2 0.0000000 Initial F(X): 1 -13.000000 2 11.000000 Returned value of INFO = 1 Final X: 1 1.0000000 2 1.0000000 Final F(X): 1 -0.96195052E-10 2 -0.12353851E-09 HYBRJ1_TEST HYBRJ1 solves a nonlinear system of equations. Initial X: 1 3.0000000 2 0.0000000 F(X): 1 -13.000000 2 11.000000 Returned value of INFO = 1 X: 1 1.0000000 2 1.0000000 F(X): 1 -0.96195052E-10 2 -0.12353851E-09 LMDER1_TEST LMDER1 minimizes M functions in N variables. Initial X: 1 0.0000000 2 5.0000000 F(X): 1 3.0000000 2 -6.0000000 3 -23.000000 4 -35.000000 Returned value of INFO = 3 X: 1 6.5500000 2 -12.500000 F(X): 1 -1.4000000 2 2.7000000 3 -1.2000000 4 -0.10000000 LMDER1_2_TEST LMDER1 minimizes M functions in N variables. Initial X: 1 0.0000000 2 5.0000000 3 1.3000000 F(X): 1 1.0000000 2 -0.68855587 3 -7.1441624 4 -18.685669 5 -35.483585 6 -57.646904 7 -85.252351 8 -118.35736 9 -157.00681 10 -201.23688 Returned value of INFO = 2 X: 1 1.0000000 2 3.0000000 3 2.0000000 F(X): 1 0.13233858E-12 2 0.33750780E-13 3 0.23803182E-12 4 0.85975671E-12 5 0.19895197E-11 6 0.36948222E-11 7 0.60822458E-11 8 0.90381036E-11 9 0.12818191E-10 10 0.17280399E-10 LMDIF1_TEST LMDIF1 minimizes M functions in N variables. Initial X: 1 0.0000000 2 5.0000000 F(X): 1 3.0000000 2 -6.0000000 3 -23.000000 4 -35.000000 Returned value of INFO = 3 X: 1 6.5500000 2 -12.500000 F(X): 1 -1.4000000 2 2.7000000 3 -1.2000000 4 -0.10000000 LMDIF1_2_TEST LMDIF1 minimizes M functions in N variables. X: 1 0.0000000 2 5.0000000 3 1.3000000 F(X): 1 1.0000000 2 -0.68855587 3 -7.1441624 4 -18.685669 5 -35.483585 6 -57.646904 7 -85.252351 8 -118.35736 9 -157.00681 10 -201.23688 Returned value of INFO = 2 X: 1 1.0000000 2 3.0000000 3 2.0000000 F(X): 1 0.18918200E-12 2 0.42632564E-13 3 0.26290081E-12 4 0.99475983E-12 5 0.23732127E-11 6 0.44337867E-11 7 0.72759576E-11 8 0.10970780E-10 9 0.15546675E-10 10 0.21032065E-10 LMSTR1_TEST LMSTR1 minimizes M functions in N variables. Initial X: 1 0.0000000 2 5.0000000 F(X): 1 3.0000000 2 -6.0000000 3 -23.000000 4 -35.000000 Returned value of INFO = 2 X: 1 6.5500000 2 -12.500000 F(X): 1 -1.4000000 2 2.7000000 3 -1.2000000 4 -0.10000000 LMSTR1_2_TEST LMSTR1 minimizes M functions in N variables. Initial X: 1 0.0000000 2 5.0000000 3 1.3000000 F(X): 1 1.0000000 2 -0.68855587 3 -7.1441624 4 -18.685669 5 -35.483585 6 -57.646904 7 -85.252351 8 -118.35736 9 -157.00681 10 -201.23688 Returned value of INFO = 2 X: 1 1.0000000 2 3.0000000 3 2.0000000 F(X): 1 0.13322676E-12 2 0.33750780E-13 3 0.24158453E-12 4 0.85975671E-12 5 0.19895197E-11 6 0.36948222E-11 7 0.60822458E-11 8 0.90381036E-11 9 0.12818191E-10 10 0.17280399E-10 QFORM_TEST: QFORM constructs the Q factor explicitly after the use of QRFAC. Matrix A: Col 1 2 3 4 5 Row 1: 0.981128 0.725839 0.892762 0.574428 0.855192 2: 0.181920 0.425486 0.634774 0.374948 0.153673 3: 0.686051 0.222896 0.281775 0.479296 0.399416 4: 0.190509 0.314032 0.513920 0.670689 0.564089 5: 0.426692 0.670082 0.834234 0.609550 0.860606 Col 6 7 Row 1: 0.747213 0.151524 2: 0.860957 0.693980 3: 0.774105 0.372939E-01 4: 0.592080 0.886642 5: 0.400513 0.202050 Matrix R: Col 1 2 3 4 5 Row 1: -1.29797 -0.992477 -1.26241 -1.03891 -1.24479 2: 0. -0.565843 -0.792405 -0.479423 -0.518759 3: 0. 0. -0.133566 -0.356719 0.811560E-02 4: 0. 0. 0. -0.291918 -0.356854 5: 0. 0. 0. 0. 0.165261 Col 6 7 Row 1: -1.31321 -0.428072 2: -0.410376 -0.711409 3: -0.652397 -0.796604 4: 0.100985 -0.444720E-01 5: -0.284684 0.837390E-01 Matrix Q: Col 1 2 3 4 5 Row 1: -0.755893 0.430637E-01 0.204838 0.401362 0.472992 2: -0.140157 -0.506118 -0.425174 0.565141 -0.473333 3: -0.528556 0.533157 -0.277002 -0.297922 -0.520466 4: -0.146775 -0.297541 -0.695224 -0.436956 0.464391 5: -0.328737 -0.607621 0.466049 -0.489731 -0.256302 Matrix A2 = Q * R: Col 1 2 3 4 5 Row 1: 0.981128 0.725839 0.892762 0.574428 0.855192 2: 0.181920 0.425486 0.634774 0.374948 0.153673 3: 0.686051 0.222896 0.281775 0.479296 0.399416 4: 0.190509 0.314032 0.513920 0.670689 0.564089 5: 0.426692 0.670082 0.834234 0.609550 0.860606 Col 6 7 Row 1: 0.747213 0.151524 2: 0.860957 0.693980 3: 0.774105 0.372939E-01 4: 0.592080 0.886642 5: 0.400513 0.202050 minpack_test(): Normal end of execution. 09 May 2025 9:19:55.819 PM