03 January 2018 12:53:51.665 PM MINPACK_TEST FORTRAN90 version Test the MINPACK library. 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 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 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: 0.218418 0.661187E-01 0.617272E-01 0.183837E-02 0.859097 2: 0.956318 0.257578 0.449539 0.897504 0.840847 3: 0.829509 0.109957 0.401306 0.350752 0.123104 4: 0.561695 0.438290E-01 0.754673 0.945448E-01 0.751236E-02 5: 0.415307 0.633966 0.797287 0.136169E-01 0.260303 Col 6 7 Row 1: 0.912484 0.692066 2: 0.113664 0.561662 3: 0.351629 0.861216 4: 0.822887 0.453794 5: 0.267132 0.911977 Matrix R: Col 1 2 3 4 5 Row 1: -1.46230 -0.437590 -1.04718 -0.826379 -0.824866 2: 0. 0.543284 0.449661 -0.145361 0.168092 3: 0. 0. -0.522842 0.331765 0.469999 4: 0. 0. 0. -0.351522 0.269413E-01 5: 0. 0. 0. 0. 0.773147 Col 6 7 Row 1: -0.802049 -1.39255 2: -0.317990E-01 0.503999 3: -0.491420 -0.488110E-01 4: 0.557348 0.564840 5: 0.721989 0.243141 Matrix Q: Col 1 2 3 4 5 Row 1: -0.149366 0.139434E-02 0.182298 0.517385 0.822659 2: -0.653982 -0.526396E-01 0.404763 -0.611992 0.176547 3: -0.567264 -0.254512 0.149713 0.582292 -0.501954 4: -0.384118 -0.228715 -0.870775 -0.932054E-01 0.182224 5: -0.284010 0.938158 -0.149232 0.100139 -0.830665E-01 Matrix A2 = Q * R: Col 1 2 3 4 5 Row 1: 0.218418 0.661187E-01 0.617272E-01 0.183837E-02 0.859097 2: 0.956318 0.257578 0.449539 0.897504 0.840847 3: 0.829509 0.109957 0.401306 0.350752 0.123104 4: 0.561695 0.438290E-01 0.754673 0.945448E-01 0.751236E-02 5: 0.415307 0.633966 0.797287 0.136169E-01 0.260303 Col 6 7 Row 1: 0.912484 0.692066 2: 0.113664 0.561662 3: 0.351629 0.861216 4: 0.822887 0.453794 5: 0.267132 0.911977 MINPACK_TEST Normal end of execution. 03 January 2018 12:53:51.666 PM