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]
