Package: python-openopt Version: 0.38+svn1589-1.1 Severity: normal Dear Maintainer,
* What led up to the situation? I tested an example script that comes with the package named "python-openopt". It failed. I emailed the package's maintainer a few days ago. No reply. Yet. It occurred to me 1.) it may interesting to test all of the example scripts in the package, 2.) I can code, 3.) curse these good looks and 4.) ;-) * What exactly did you do (or not do) that was effective (or ineffective)? I wrote the following shell code to test all of the examples included in the python-openopt package $ for f in /usr/share/doc/python-openopt/examples/*.py ; do echo "===============" ; echo ; echo "$f" ; echo ; echo ; echo ; python "$f" ; done | tee /tmp/python-openopt_examples.log * What was the outcome of this action? The output file is attached. * What outcome did you expect instead? Less errors. Thanks, Kingsley -- System Information: Debian Release: stretch/sid APT prefers unstable-debug APT policy: (500, 'unstable-debug'), (500, 'unstable') Architecture: i386 (i686) Kernel: Linux 4.4.0-1-686-pae (SMP w/2 CPU cores) Locale: LANG=en_US.UTF-8, LC_CTYPE=en_US.UTF-8 (charmap=UTF-8) Shell: /bin/sh linked to /bin/bash Init: systemd (via /run/systemd/system) Versions of packages python-openopt depends on: ii python-numpy 1:1.16.2-1 ii python-setproctitle 1.1.10-1+b2 pn python:any <none> Versions of packages python-openopt recommends: ii python-cvxopt 1.1.9+dfsg-3+b1 ii python-matplotlib 2.2.3-6 ii python-scipy 0.19.1-1 Versions of packages python-openopt suggests: ii lp-solve 5.5.0.13-7+b1 -- no debconf information
=============== /usr/share/doc/python-openopt/examples/dfp_1.py ------------------------- OpenOpt 0.38 ------------------------- solver: ralg problem: unnamed type: DFP OpenOpt Error: To perform gradients check you should have DerApproximator installed, see http://openopt.org/DerApproximator =============== /usr/share/doc/python-openopt/examples/dfp_2.py ------------------------- OpenOpt 0.38 ------------------------- solver: ralg problem: unnamed type: DFP OpenOpt Error: To perform gradients check you should have DerApproximator installed, see http://openopt.org/DerApproximator =============== /usr/share/doc/python-openopt/examples/eig_1.py ------------------------- OpenOpt 0.38 ------------------------- solver: arpack problem: unnamed type: EIG goal: largest magnitude iter objFunVal 0 0.000e+00 istop: 0 Solver: Time Elapsed = 0.19 CPU Time Elapsed = 0.004887 objFunValue: 0 [ 0.14607289-0.19602952j -0.65372843+0.j 2.89776724+0.j ] [[ 0.56334829-0.10391145j 0.19592536+0.j 0.43733688+0.j ] [-0.1812288 -0.20999235j -0.03219327+0.j 0.49662623+0.j ] [-0.21648181-0.21334642j -0.55544796+0.j 0.42977207+0.j ] [-0.36295959+0.34828527j 0.62338178+0.j 0.38727512+0.j ] [ 0.49714496+0.0482076j -0.51327338+0.j 0.47687818+0.j ]] =============== /usr/share/doc/python-openopt/examples/eig_2.py ------------------------- OpenOpt 0.38 ------------------------- solver: numpy_eig problem: unnamed type: EIG goal: all eigenvectors and eigenvalues iter objFunVal 0 0.000e+00 istop: 0 Solver: Time Elapsed = 0.05 CPU Time Elapsed = 0.002157 objFunValue: 0 [ 2.89776724+0.j -0.65372843+0.j 0.14607289+0.19602952j 0.14607289-0.19602952j -0.08530815+0.j ] [[ 0.43733688+0.j -0.19592536+0.j 0.57285154+0.j 0.57285154-0.j 0.63764724+0.j ] [ 0.49662623+0.j 0.03219327+0.j -0.14013112+0.23938241j -0.14013112-0.23938241j -0.53642409+0.j ] [ 0.42977207+0.j 0.55544796+0.j -0.17419089+0.24907549j -0.17419089-0.24907549j 0.29171743+0.j ] [ 0.38727512+0.j -0.62338178+0.j -0.42011495-0.27666898j -0.42011495+0.27666898j -0.45403266+0.j ] [ 0.47687818+0.j 0.51327338+0.j 0.4801531 -0.13758665j 0.4801531 +0.13758665j 0.12004364+0.j ]] =============== /usr/share/doc/python-openopt/examples/glp_1.py ------------------------- OpenOpt 0.38 ------------------------- solver: de problem: unnamed type: GLP iter objFunVal 0 3.167e+03 10 1.788e+03 20 1.786e+03 30 1.786e+03 40 1.786e+03 50 1.786e+03 60 1.786e+03 70 1.786e+03 80 1.786e+03 90 1.786e+03 100 1.786e+03 110 1.786e+03 120 1.786e+03 130 1.786e+03 140 1.786e+03 150 1.786e+03 160 1.786e+03 170 1.786e+03 180 1.786e+03 190 1.786e+03 200 1.786e+03 210 1.786e+03 213 1.786e+03 istop: 11 (Non-Success Number > maxNonSuccess = 15) Solver: Time Elapsed = 0.6 CPU Time Elapsed = 0.450416 Plotting: Time Elapsed = 4.68 CPU Time Elapsed = 0.964513 objFunValue: 1785.6456 (feasible, MaxResidual = 0) =============== /usr/share/doc/python-openopt/examples/glp_2.py OpenOpt Error: incorrect solver is called, maybe the solver "pswarm" require its installation, check http://www.openopt.org/GLP or try p._solve() for more details =============== /usr/share/doc/python-openopt/examples/glp_3.py ------------------------- OpenOpt 0.38 ------------------------- solver: de problem: unnamed type: GLP iter objFunVal 0 8.332e+04 101 1.198e+04 istop: -10 (max objfunc evals limit has been reached) Solver: Time Elapsed = 9.04 CPU Time Elapsed = 6.548036 Plotting: Time Elapsed = 1.47 CPU Time Elapsed = 0.922315 objFunValue: 11983.955 (feasible, MaxResidual = 0) =============== /usr/share/doc/python-openopt/examples/glp_Ab_c.py OpenOpt Warning: incorrect parameter for prob.solve(): "mutationRate" - will be ignored (this one has been not found in neither prob nor de solver parameters) ------------------------- OpenOpt 0.38 ------------------------- solver: de problem: unnamed type: GLP iter objFunVal log10(maxResidual) 0 3.167e+03 -100.00 10 2.624e+03 -100.00 20 2.535e+03 -100.00 30 2.476e+03 -100.00 40 2.396e+03 -100.00 50 2.396e+03 -100.00 60 2.377e+03 -100.00 70 2.370e+03 -100.00 80 2.363e+03 -100.00 90 2.360e+03 -100.00 100 2.358e+03 -100.00 110 2.357e+03 -100.00 120 2.355e+03 -100.00 130 2.354e+03 -100.00 140 2.354e+03 -100.00 150 2.354e+03 -100.00 160 2.354e+03 -100.00 170 2.354e+03 -100.00 180 2.354e+03 -100.00 190 2.354e+03 -100.00 200 2.354e+03 -100.00 210 2.354e+03 -100.00 220 2.354e+03 -100.00 230 2.354e+03 -100.00 240 2.354e+03 -100.00 250 2.354e+03 -100.00 251 2.354e+03 -100.00 istop: -7 (Max Iter has been reached) Solver: Time Elapsed = 6.54 CPU Time Elapsed = 4.69474 Plotting: Time Elapsed = 4.74 CPU Time Elapsed = 3.278248 objFunValue: 2354.1304 (feasible, MaxResidual = 0) =============== /usr/share/doc/python-openopt/examples/GUI_1.py ------------------------- OpenOpt 0.38 ------------------------- solver: ralg problem: GUI_example type: NLP goal: minimum iter objFunVal log10(maxResidual) 0 1.277e+03 1.32 OpenOpt Error: For the problem you should have DerApproximator installed, see http://openopt.org/DerApproximator =============== /usr/share/doc/python-openopt/examples/__init__.py =============== /usr/share/doc/python-openopt/examples/lcp_1.py ------------------------- OpenOpt 0.38 ------------------------- solver: lcp problem: unnamed type: LCP iter objFunVal 0 1.094e+00 1 1.110e-16 istop: 1000 (success) Solver: Time Elapsed = 0.0 CPU Time Elapsed = 0.001799 objFunValue: 1.110223e-16 w: [0. 0. 0.02167615 1.84666668 0. 0. ] z: [0.3 0.2 0. 0. 0.1 0.3] =============== /usr/share/doc/python-openopt/examples/llavp_1.py ------------------------- OpenOpt 0.38 ------------------------- solver: ralg problem: unnamed type: LLAVP ------------------------- OpenOpt 0.38 ------------------------- solver: ralg problem: unnamed type: NSP goal: minimum iter objFunVal log10(maxResidual) 0 7.945e+03 -0.00 100 1.017e+04 -2.57 200 1.012e+04 -3.32 300 1.011e+04 -100.00 400 1.011e+04 -0.88 500 1.011e+04 -3.96 600 1.011e+04 -100.00 700 1.011e+04 -100.00 800 1.011e+04 -4.44 900 1.011e+04 -3.92 1000 1.011e+04 -100.00 1001 1.011e+04 -100.00 istop: -7 (Max Iter has been reached) Solver: Time Elapsed = 5.81 CPU Time Elapsed = 4.118401 Plotting: Time Elapsed = 5.64 CPU Time Elapsed = 3.716412 objFunValue: 10109.131 (feasible, MaxResidual = 0) f_opt: 10109.131378 =============== /usr/share/doc/python-openopt/examples/llsp_1.py ------------------------- OpenOpt 0.38 ------------------------- solver: lsqr problem: unnamed type: LLSP iter objFunVal 0 1.690e+09 2 2.414e+06 istop: 1000 Solver: Time Elapsed = 0.13 CPU Time Elapsed = 0.079949 objFunValue: 2414291.2 f_opt: 2414291.185772 =============== /usr/share/doc/python-openopt/examples/llsp_2.py =============== /usr/share/doc/python-openopt/examples/lp_1.py ------------------------- OpenOpt 0.38 ------------------------- solver: pclp problem: unnamed type: LP goal: minimum iter objFunVal log10(maxResidual) 0 0.000e+00 2.90 1 2.045e+02 -13.37 istop: 1000 Solver: Time Elapsed = 0.0 CPU Time Elapsed = 0.003923 objFunValue: 204.48842 (feasible, MaxResidual = 4.26326e-14) objFunValue: 204.488416 x_opt: [ 9.89355041 -8. 1.5010645 ] =============== /usr/share/doc/python-openopt/examples/lunp_1.py =============== /usr/share/doc/python-openopt/examples/milp_1.py OpenOpt Error: incorrect solver is called, maybe the solver "lpSolve" require its installation, check http://www.openopt.org/MILP or try p._solve() for more details =============== /usr/share/doc/python-openopt/examples/minlp_1.py ------------------------- OpenOpt 0.38 ------------------------- solver: branb problem: minlp_1 type: MINLP goal: minimum iter objFunVal 0 9.305e+03 1 9.305e+03 istop: -101.0 Solver: Time Elapsed = 0.0 CPU Time Elapsed = 0.004279 NO FEASIBLE SOLUTION has been obtained (MaxResidual = 1.5, objFunc = 9305.3987) =============== /usr/share/doc/python-openopt/examples/miqcqp_1.py OpenOpt Error: incorrect solver is called, maybe the solver "cplex" require its installation, check http://www.openopt.org/QP or try p._solve() for more details =============== /usr/share/doc/python-openopt/examples/miqp_1.py OpenOpt Error: incorrect solver is called, maybe the solver "cplex" require its installation, check http://www.openopt.org/QP or try p._solve() for more details =============== /usr/share/doc/python-openopt/examples/mmp_1.py ------------------------- OpenOpt 0.38 ------------------------- solver: ipopt problem: unnamed type: MMP goal: minimax iter objFunVal log10(maxResidual) 0 1.196e+04 1.89 OpenOpt Error: you should have pyipopt installed =============== /usr/share/doc/python-openopt/examples/mmp_2.py OpenOpt Warning: incorrect parameter for prob.solve(): "NLPsolver" - will be ignored (this one has been not found in neither prob nor nsmm solver parameters) ------------------------- OpenOpt 0.38 ------------------------- solver: nsmm problem: unnamed type: MMP goal: minimax iter objFunVal log10(maxResidual) 0 6.466e+03 1.89 OpenOpt Error: For the problem you should have DerApproximator installed, see http://openopt.org/DerApproximator =============== /usr/share/doc/python-openopt/examples/nllsp_1.py OpenOpt Error: To perform gradients check you should have DerApproximator installed, see http://openopt.org/DerApproximator =============== /usr/share/doc/python-openopt/examples/nlp_11.py OpenOpt Error: To perform gradients check you should have DerApproximator installed, see http://openopt.org/DerApproximator =============== /usr/share/doc/python-openopt/examples/nlp_1.py OpenOpt Error: To perform gradients check you should have DerApproximator installed, see http://openopt.org/DerApproximator =============== /usr/share/doc/python-openopt/examples/nlp_2.py ------------------------- OpenOpt 0.38 ------------------------- solver: ralg problem: unnamed type: NLP goal: minimum iter objFunVal log10(maxResidual) 0 7.703e+02 1.97 10 6.947e+02 -4.74 20 2.315e+02 -6.39 30 1.242e+02 -7.42 40 8.819e+01 -5.95 50 6.953e+01 -6.30 60 6.108e+01 -6.00 70 5.891e+01 -5.98 80 6.062e+01 -6.10 90 5.774e+01 -6.10 100 5.719e+01 -6.08 110 5.617e+01 -6.04 120 5.570e+01 -6.02 130 5.556e+01 -5.01 140 5.545e+01 -5.97 150 5.543e+01 -5.97 160 5.542e+01 -4.48 170 5.679e+01 -6.10 171 5.679e+01 -6.10 istop: 3 (|| X[k] - X[k-1] || < xtol) Solver: Time Elapsed = 1.04 CPU Time Elapsed = 0.868169 Plotting: Time Elapsed = 1.73 CPU Time Elapsed = 1.278429 objFunValue: 56.792963 (feasible, MaxResidual = 7.88685e-07) =============== /usr/share/doc/python-openopt/examples/nlp_3.py ------------------------- OpenOpt 0.38 ------------------------- solver: ralg problem: nlp3 type: NLP goal: maximum iter objFunVal log10(maxResidual) 0 -1.640e+02 0.81 OpenOpt Error: For the problem you should have DerApproximator installed, see http://openopt.org/DerApproximator =============== /usr/share/doc/python-openopt/examples/nlp_4.py =============== /usr/share/doc/python-openopt/examples/nlp_5.py ------------------------- OpenOpt 0.38 ------------------------- solver: ralg problem: NLP_5 type: NLP goal: minimum iter objFunVal log10(maxResidual) 0 6.178e+02 1.46 OpenOpt Error: For the problem you should have DerApproximator installed, see http://openopt.org/DerApproximator =============== /usr/share/doc/python-openopt/examples/nlp_ALGENCAN.py OpenOpt Error: To perform gradients check you should have DerApproximator installed, see http://openopt.org/DerApproximator =============== /usr/share/doc/python-openopt/examples/nlp_bench_1.py ------------------------- OpenOpt 0.38 ------------------------- solver: gsubg problem: NLP_bench_1 type: NLP goal: minimum iter objFunVal log10(maxResidual) 0 6.115e+01 0.81 OpenOpt Warning: Handling of constraints is not implemented properly for the solver gsubg yet OpenOpt Error: For the problem you should have DerApproximator installed, see http://openopt.org/DerApproximator =============== /usr/share/doc/python-openopt/examples/nlp_bench_2.py ------------------------- OpenOpt 0.38 ------------------------- solver: ralg problem: bench2 type: NLP goal: minimum iter objFunVal log10(maxResidual) 0 8.048e+01 5.69 10 4.797e+01 -1.24 20 4.764e+01 -5.42 30 3.377e+01 0.27 40 2.845e+01 -0.49 50 2.710e+01 -1.80 60 2.687e+01 -1.08 70 2.671e+01 -2.86 80 2.622e+01 -6.29 90 2.597e+01 -6.20 100 2.579e+01 -6.10 110 2.584e+01 -2.90 120 2.574e+01 -2.79 130 2.573e+01 -4.33 140 2.571e+01 -6.02 150 2.569e+01 -6.09 160 2.560e+01 -6.11 170 2.542e+01 -6.12 180 2.528e+01 -6.07 190 2.527e+01 -6.07 200 2.527e+01 -6.08 210 2.527e+01 -6.11 220 2.527e+01 -6.11 230 2.527e+01 -6.12 240 2.527e+01 -6.12 250 2.623e+01 -0.72 260 2.580e+01 -4.63 270 2.539e+01 -6.11 280 2.538e+01 -6.14 290 2.536e+01 -6.13 300 2.528e+01 -6.15 310 2.526e+01 -1.38 320 3.043e+01 2.54 330 6.419e+01 2.33 340 3.429e+01 -0.73 350 3.672e+01 -0.14 360 3.189e+01 -7.12 370 2.635e+01 -6.09 380 2.577e+01 -6.27 390 2.720e+01 -6.21 400 2.592e+01 -6.00 410 2.540e+01 -0.70 420 2.534e+01 -1.76 430 2.531e+01 -6.09 440 2.652e+01 -6.37 450 2.644e+01 -6.16 460 2.607e+01 -6.14 470 2.524e+01 0.26 480 2.529e+01 -6.19 490 2.528e+01 -2.18 500 2.568e+01 -3.57 510 2.855e+01 -1.15 520 5.484e+01 4.48 530 3.883e+01 1.30 540 5.170e+01 0.78 550 4.447e+01 0.64 560 3.360e+01 -7.65 570 3.133e+01 -7.81 580 2.987e+01 -8.27 590 2.928e+01 -1.48 600 2.899e+01 -3.95 610 2.891e+01 -6.43 620 2.887e+01 -6.30 630 2.887e+01 -6.01 640 2.886e+01 -5.92 650 2.885e+01 -6.06 660 2.884e+01 -4.65 670 2.882e+01 -6.18 680 2.880e+01 -6.37 690 3.129e+01 -5.87 700 3.093e+01 -4.84 710 3.046e+01 -6.27 720 2.965e+01 -6.14 730 2.776e+01 -0.28 740 2.777e+01 -6.20 750 2.776e+01 -6.21 760 2.775e+01 -5.29 770 2.775e+01 -6.23 774 2.527e+01 -6.12 istop: 4 (|| F[k] - F[k-1] || < ftol) Solver: Time Elapsed = 6.02 CPU Time Elapsed = 4.327925 Plotting: Time Elapsed = 5.03 CPU Time Elapsed = 3.414497 objFunValue: 25.27201 (feasible, MaxResidual = 7.62698e-07) ------------------------- OpenOpt 0.38 ------------------------- solver: scipy_cobyla problem: bench2 type: NLP goal: minimum iter objFunVal log10(maxResidual) 0 8.048e+01 5.69 10 2.442e+01 -0.95 20 2.530e+01 -5.34 30 2.545e+01 -7.50 40 2.550e+01 -8.90 50 2.552e+01 -10.66 60 2.554e+01 -12.98 70 2.554e+01 -15.28 80 2.555e+01 -17.70 90 2.555e+01 -19.36 100 2.555e+01 -22.10 110 2.555e+01 -23.51 118 2.555e+01 -22.73 istop: 1000 Solver: Time Elapsed = 1.2 CPU Time Elapsed = 0.965151 Plotting: Time Elapsed = 1.19 CPU Time Elapsed = 0.83853 objFunValue: 25.547068 (feasible, MaxResidual = 1.87537e-23) =============== /usr/share/doc/python-openopt/examples/nlp_d2f.py ------------------------- OpenOpt 0.38 ------------------------- solver: scipy_ncg problem: unnamed type: NLP goal: minimum iter objFunVal 0 2.104e+05 10 2.259e-02 =============== /usr/share/doc/python-openopt/examples/nlsp_1.py ------------------------- OpenOpt 0.38 ------------------------- solver: nssolve problem: unnamed type: SNLE iter objFunVal 0 3.878e+03 10 1.528e+01 20 3.236e-01 30 1.298e-02 40 4.257e-04 50 1.334e-05 59 8.339e-07 istop: 10 Solver: Time Elapsed = 0.22 CPU Time Elapsed = 0.087684 Plotting: Time Elapsed = 1.09 CPU Time Elapsed = 0.679059 objFunValue: 8.3386479e-07 solution: [ 1.00000074 1.99999981 80.63421087] max residual: 8.338648e-07 =============== /usr/share/doc/python-openopt/examples/nlsp_constrained.py ------------------------- OpenOpt 0.38 ------------------------- solver: ralg problem: unnamed type: SNLE iter objFunVal log10(maxResidual) 0 3.878e+03 3.64 10 7.573e-01 -100.00 20 1.735e-02 -100.00 30 3.002e-04 -100.00 40 3.879e-05 -100.00 50 1.411e-05 -100.00 60 1.483e-06 -100.00 70 2.550e-07 -100.00 80 5.727e-09 -100.00 81 5.727e-09 -100.00 istop: 15 (solution with required ftol and contol has been reached) Solver: Time Elapsed = 0.55 CPU Time Elapsed = 0.375706 Plotting: Time Elapsed = 1.58 CPU Time Elapsed = 0.935908 objFunValue: 5.7270562e-09 (feasible, MaxResidual = 0) solution: [ 1. 2. 145.56045962] max residual: 5.727056e-09 =============== /usr/share/doc/python-openopt/examples/nsp_1.py ------------------------- OpenOpt 0.38 ------------------------- solver: ralg problem: unnamed type: NSP goal: minimum iter objFunVal 0 2.825e+06 10 6.791e+05 20 2.086e+05 30 1.210e+05 40 5.002e+04 50 1.760e+04 60 1.172e+04 70 1.105e+04 80 8.449e+03 90 8.303e+03 100 7.641e+03 110 7.389e+03 120 6.603e+03 130 5.762e+03 140 5.300e+03 150 4.790e+03 160 4.351e+03 170 3.655e+03 180 3.224e+03 190 2.862e+03 200 2.349e+03 210 1.980e+03 220 1.791e+03 230 1.554e+03 240 1.217e+03 250 1.094e+03 260 9.513e+02 270 7.430e+02 280 6.608e+02 290 5.712e+02 300 4.863e+02 310 4.219e+02 320 3.580e+02 330 3.085e+02 340 2.764e+02 350 2.407e+02 360 1.946e+02 370 1.761e+02 380 1.567e+02 390 1.366e+02 400 1.190e+02 410 1.001e+02 420 8.997e+01 430 8.277e+01 440 7.290e+01 450 6.331e+01 460 5.715e+01 470 5.035e+01 480 4.452e+01 490 3.917e+01 500 3.403e+01 510 3.167e+01 520 2.826e+01 530 2.444e+01 540 2.093e+01 550 1.892e+01 560 1.710e+01 570 1.506e+01 580 1.301e+01 590 1.084e+01 600 9.195e+00 610 8.617e+00 620 8.248e+00 630 7.189e+00 640 5.925e+00 650 5.160e+00 660 4.173e+00 670 3.417e+00 680 2.834e+00 690 2.449e+00 700 1.942e+00 710 1.511e+00 720 1.008e+00 730 8.815e-01 740 6.586e-01 750 5.402e-01 760 4.561e-01 770 3.718e-01 780 2.926e-01 790 2.671e-01 800 1.003e-01 810 4.587e-02 820 1.664e-02 830 9.348e-03 840 4.628e-03 850 3.189e-03 860 4.531e-04 870 4.667e-04 880 4.621e-04 890 3.994e-04 900 2.039e-04 istop: 4 (|| F[k] - F[k-1] || < ftol) Solver: Time Elapsed = 2.63 CPU Time Elapsed = 1.835749 objFunValue: 0.00020394193 x_opt: [-7.55515251e-06 -3.96390338e-07 -1.60870663e-06 -7.57389565e-07 -3.47059039e-06 -3.24945583e-07 -7.65371472e-07 4.60230372e-07 -1.82152293e-07 -3.81281939e-07 -2.67741544e-08 -8.80715183e-08 9.40934595e-08 -8.24416270e-07 -2.73087912e-08 1.14628020e-07 -1.16286091e-07 1.98934862e-07 -2.98076539e-08 -5.78804767e-08 7.96725017e-10 2.53660118e-08 4.33727091e-08 -8.13159481e-08 6.84091986e-08 3.77676635e-08 -5.33017752e-10 -4.78834500e-08 -4.30667806e-08 -1.10386524e-08 -1.59509779e-08 1.75660337e-09 -4.41552607e-10 1.44923528e-09 1.42874337e-08 -5.19043574e-09 3.09432063e-09 4.26378239e-10 5.13923713e-09 -3.36279860e-09 -1.95131638e-10 1.06130186e-09 -5.36717179e-11 -1.19797962e-09 8.31146687e-10 1.77032407e-09 -5.83003306e-10 4.02466726e-10 4.99034191e-10 -1.90363153e-10 -3.09415080e-10 -5.26824819e-10 1.69651869e-10 -5.54353370e-11 -6.92393221e-11 1.12404642e-11 1.59302212e-12 -1.99207398e-11 -3.17137953e-11 5.42336540e-11 2.03336453e-11 -7.05853401e-11 -2.55030037e-11 2.15473351e-11 2.37522012e-11 2.10295420e-12 -1.25425968e-11 -1.45602291e-11 8.69765658e-12 -2.09666542e-11 2.52402705e-11 -2.33730501e-11 4.76775533e-12 -9.03988720e-12 -8.99018718e-13] f_opt: 0.000204 =============== /usr/share/doc/python-openopt/examples/nssolveVSfsolve_1.py ---------------------------------- desired ftol: 1e-06 objFunc noise: 1e-08 ---------- fsolve fails ---------- N log10(MaxResidual) MaxResidual OpenOpt Error: For the problem you should have DerApproximator installed, see http://openopt.org/DerApproximator =============== /usr/share/doc/python-openopt/examples/qcqp_1.py OpenOpt Error: incorrect solver is called, maybe the solver "cplex" require its installation, check http://www.openopt.org/QP or try p._solve() for more details =============== /usr/share/doc/python-openopt/examples/qp_1.py ------------------------- OpenOpt 0.38 ------------------------- solver: cvxopt_qp problem: unnamed type: QP istop: 1000 (optimal) Solver: Time Elapsed = 0.04 CPU Time Elapsed = 0.007605 objFunValue: -1190.35 (feasible, MaxResidual = 0) =============== /usr/share/doc/python-openopt/examples/sdp_1.py =============== /usr/share/doc/python-openopt/examples/sle_1.py ------------------------- OpenOpt 0.38 ------------------------- solver: defaultSLEsolver problem: unnamed type: SLE iter objFunVal 0 8.150e+01 1 1.809e-08 istop: 10 (solved) Solver: Time Elapsed = 1.38 CPU Time Elapsed = 0.793461 objFunValue: 1.8094923e-08 max residual: 1.809492e-08 =============== /usr/share/doc/python-openopt/examples/snle_1.py ------------------------- OpenOpt 0.38 ------------------------- solver: ralg problem: unnamed type: SNLE iter objFunVal 0 3.878e+03 10 1.167e+00 20 4.816e-02 30 4.978e-03 40 3.733e-04 50 3.083e-05 60 4.430e-06 69 4.780e-07 istop: 15 (solution with required ftol has been reached) Solver: Time Elapsed = 0.22 CPU Time Elapsed = 0.174172 Plotting: Time Elapsed = 1.01 CPU Time Elapsed = 0.722561 objFunValue: 4.7804211e-07 solution: [ 1.00000023 1.99999993 70.16223675] max residual: 4.780421e-07 =============== /usr/share/doc/python-openopt/examples/socp_1.py ------------------------- OpenOpt 0.38 ------------------------- solver: cvxopt_socp problem: unnamed type: SOCP goal: minimum pcost dcost gap pres dres k/t 0: 4.9969e+00 -1.7285e+01 6e+01 3e-01 4e+00 1e+00 1: -1.6732e+00 -7.0431e+00 1e+01 7e-02 1e+00 6e-01 2: -1.6221e+01 -3.5417e+01 2e+02 3e-01 5e+00 7e+00 3: -2.1832e+01 -2.2849e+01 3e+01 4e-02 6e-01 2e+00 4: -3.5265e+01 -3.5594e+01 1e+01 1e-02 2e-01 9e-01 5: -3.8303e+01 -3.8314e+01 3e-01 4e-04 6e-03 2e-02 6: -3.8342e+01 -3.8342e+01 1e-02 1e-05 2e-04 7e-04 7: -3.8346e+01 -3.8346e+01 9e-04 1e-06 2e-05 7e-05 8: -3.8346e+01 -3.8346e+01 4e-05 6e-08 9e-07 4e-06 9: -3.8346e+01 -3.8346e+01 2e-06 3e-09 4e-08 2e-07 10: -3.8346e+01 -3.8346e+01 3e-07 4e-10 6e-09 3e-08 Optimal solution found. istop: 1000 (optimal) Solver: Time Elapsed = 0.04 CPU Time Elapsed = 0.012048 objFunValue: -38.346368 f_opt: -38.346368 x_opt: [-5.01469912 -5.76690749 -8.52177183]