#12832: Bug in cvxopt on power7
----------------------------+-----------------------------------------------
Reporter: fbissey | Owner: tbd
Type: defect | Status: new
Priority: major | Milestone: sage-5.7
Component: packages | Resolution:
Keywords: | Work issues:
Report Upstream: N/A | Reviewers:
Authors: | Merged in:
Dependencies: | Stopgaps:
----------------------------+-----------------------------------------------
Comment (by fbissey):
Building cvxopt with SAGE_CHECK=yes on OS X
{{{
Running the test suite for cvxopt-1.1.5.p0...
Testing in
/Users/frb15/Desktop/sage-5.7.beta0/spkg/build/cvxopt-1.1.5.p0/src/examples/doc/chap10
Testing l1svc.py ...
pcost dcost gap pres dres k/t
0: 1.9477e+02 8.3326e+02 4e+03 3e+00 1e+01 1e+00
1: 3.3601e+02 4.7283e+02 5e+02 6e-01 3e+00 2e+00
2: 3.2929e+02 3.6402e+02 1e+02 2e-01 7e-01 5e-01
3: 3.2989e+02 3.3991e+02 3e+01 5e-02 2e-01 1e-01
4: 3.3052e+02 3.3433e+02 1e+01 2e-02 7e-02 4e-02
5: 3.3073e+02 3.3233e+02 4e+00 8e-03 3e-02 1e-02
6: 3.3091e+02 3.3135e+02 1e+00 2e-03 9e-03 3e-03
7: 3.3097e+02 3.3108e+02 3e-01 5e-04 2e-03 3e-04
8: 3.3099e+02 3.3102e+02 1e-01 2e-04 7e-04 9e-05
9: 3.3099e+02 3.3101e+02 3e-02 6e-05 2e-04 3e-05
10: 3.3100e+02 3.3100e+02 1e-02 2e-05 8e-05 1e-05
11: 3.3100e+02 3.3100e+02 4e-03 7e-06 3e-05 4e-06
12: 3.3100e+02 3.3100e+02 4e-04 7e-07 3e-06 4e-07
13: 3.3100e+02 3.3100e+02 3e-05 6e-08 2e-07 3e-08
14: 3.3100e+02 3.3100e+02 4e-07 7e-10 3e-09 3e-10
Optimal solution found.
pcost dcost gap pres dres k/t
0: 1.9477e+02 8.3326e+02 4e+03 3e+00 1e+01 1e+00
1: 3.3601e+02 4.7283e+02 5e+02 6e-01 3e+00 2e+00
2: 3.2929e+02 3.6402e+02 1e+02 2e-01 7e-01 5e-01
3: 3.2989e+02 3.3991e+02 3e+01 5e-02 2e-01 1e-01
4: 3.3052e+02 3.3433e+02 1e+01 2e-02 7e-02 4e-02
5: 3.3073e+02 3.3233e+02 4e+00 8e-03 3e-02 1e-02
6: 3.3091e+02 3.3135e+02 1e+00 2e-03 9e-03 3e-03
7: 3.3097e+02 3.3108e+02 3e-01 5e-04 2e-03 3e-04
8: 3.3099e+02 3.3102e+02 1e-01 2e-04 7e-04 9e-05
9: 3.3099e+02 3.3101e+02 3e-02 6e-05 2e-04 3e-05
10: 3.3100e+02 3.3100e+02 1e-02 2e-05 8e-05 1e-05
11: 3.3100e+02 3.3100e+02 4e-03 7e-06 3e-05 4e-06
12: 3.3100e+02 3.3100e+02 4e-04 7e-07 3e-06 4e-07
13: 3.3100e+02 3.3100e+02 3e-05 6e-08 2e-07 3e-08
14: 3.3100e+02 3.3100e+02 4e-07 7e-10 3e-09 3e-10
Optimal solution found.
Difference between two solutions: 2.871450e-12
Testing lp.py ...
pcost dcost gap pres dres k/t
0: -8.1000e+00 -1.8300e+01 4e+00 0e+00 8e-01 1e+00
1: -8.8055e+00 -9.4357e+00 2e-01 1e-16 4e-02 3e-02
2: -8.9981e+00 -9.0049e+00 2e-03 1e-16 5e-04 4e-04
3: -9.0000e+00 -9.0000e+00 2e-05 2e-16 5e-06 4e-06
4: -9.0000e+00 -9.0000e+00 2e-07 1e-16 5e-08 4e-08
Optimal solution found.
status: optimal
optimal value: -9.000000
optimal x: 1.000000
optimal y: 1.000000
optimal multiplier for 1st constraint: 1.000000
optimal multiplier for 2nd constraint: 2.000000
optimal multiplier for 3rd constraint: 0.000000
optimal multiplier for 4th constraint: 0.000000
pcost dcost gap pres dres k/t
0: -8.1000e+00 -1.8300e+01 4e+00 0e+00 8e-01 1e+00
1: -8.8055e+00 -9.4357e+00 2e-01 1e-16 4e-02 3e-02
2: -8.9981e+00 -9.0049e+00 2e-03 4e-16 5e-04 4e-04
3: -9.0000e+00 -9.0000e+00 2e-05 2e-16 5e-06 4e-06
4: -9.0000e+00 -9.0000e+00 2e-07 3e-16 5e-08 4e-08
Optimal solution found.
status: optimal
optimal value: -9.000000
optimal x:
[ 1.00e+00]
[ 1.00e+00]
optimal multiplier:
[ 1.00e+00]
[ 2.00e+00]
[ 2.87e-08]
[ 2.80e-08]
Testing normappr.py ...
pcost dcost gap pres dres k/t
0: 1.4360e-18 2.2335e-17 3e+00 4e+00 7e-16 1e+00
1: 7.7624e-01 5.0693e-01 1e+00 1e+00 3e-16 8e-02
2: 1.1214e+00 8.9119e-01 1e+00 1e+00 2e-15 4e-02
3: 1.4030e+00 1.3178e+00 4e-01 3e-01 1e-15 1e-02
4: 1.4925e+00 1.4550e+00 2e-01 1e-01 2e-15 3e-03
5: 1.5367e+00 1.5218e+00 7e-02 6e-02 3e-15 7e-04
6: 1.5622e+00 1.5582e+00 2e-02 1e-02 5e-15 1e-04
7: 1.5688e+00 1.5675e+00 6e-03 5e-03 9e-15 4e-05
8: 1.5710e+00 1.5705e+00 2e-03 2e-03 2e-14 1e-05
9: 1.5718e+00 1.5717e+00 6e-04 5e-04 3e-14 3e-06
10: 1.5721e+00 1.5721e+00 7e-05 6e-05 9e-14 3e-07
11: 1.5721e+00 1.5721e+00 1e-05 1e-05 2e-13 3e-08
12: 1.5721e+00 1.5721e+00 1e-07 1e-07 1e-12 3e-10
13: 1.5721e+00 1.5721e+00 1e-09 1e-09 4e-13 3e-12
Optimal solution found.
pcost dcost gap pres dres k/t
0: 0.0000e+00 -1.3323e-15 2e+03 4e+00 3e-15 1e+00
1: 1.7635e+02 1.7640e+02 3e+02 6e-01 5e-15 2e-01
2: 2.8098e+02 2.8100e+02 1e+02 2e-01 2e-14 7e-02
3: 3.1169e+02 3.1170e+02 4e+01 8e-02 2e-14 3e-02
4: 3.2086e+02 3.2086e+02 2e+01 3e-02 2e-14 1e-02
5: 3.2580e+02 3.2580e+02 5e+00 1e-02 5e-14 4e-03
6: 3.2711e+02 3.2711e+02 2e+00 5e-03 8e-14 2e-03
7: 3.2773e+02 3.2773e+02 8e-01 2e-03 7e-14 7e-04
8: 3.2798e+02 3.2798e+02 2e-01 4e-04 8e-14 2e-04
9: 3.2802e+02 3.2802e+02 9e-02 2e-04 9e-13 9e-05
10: 3.2805e+02 3.2805e+02 2e-02 5e-05 4e-13 2e-05
11: 3.2806e+02 3.2806e+02 6e-04 1e-06 4e-13 5e-07
12: 3.2806e+02 3.2806e+02 6e-06 1e-08 3e-13 5e-09
Optimal solution found.
pcost dcost gap pres dres k/t
0: -6.0000e+02 -6.0000e+02 2e+03 2e+00 3e-15 1e+00
1: -2.8064e+02 -2.8065e+02 6e+02 6e-01 5e-15 2e-01
2: 1.7442e+01 1.7439e+01 1e+02 1e-01 5e-15 6e-02
3: 6.8906e+01 6.8905e+01 5e+01 5e-02 1e-14 2e-02
4: 8.4723e+01 8.4723e+01 2e+01 2e-02 2e-14 7e-03
5: 9.0965e+01 9.0965e+01 6e+00 6e-03 4e-14 3e-03
6: 9.3530e+01 9.3530e+01 2e+00 2e-03 7e-14 9e-04
7: 9.4464e+01 9.4464e+01 8e-01 8e-04 7e-14 3e-04
8: 9.4800e+01 9.4800e+01 3e-01 3e-04 1e-13 1e-04
9: 9.4943e+01 9.4943e+01 1e-01 1e-04 5e-13 4e-05
10: 9.4977e+01 9.4977e+01 6e-02 6e-05 4e-13 2e-05
11: 9.5012e+01 9.5012e+01 1e-02 1e-05 1e-12 4e-06
12: 9.5017e+01 9.5017e+01 2e-03 2e-06 2e-12 1e-06
13: 9.5019e+01 9.5019e+01 7e-05 7e-08 1e-12 3e-08
Optimal solution found.
Testing roblp.py ...
pcost dcost gap pres dres k/t
0: 6.4689e-02 -2.5969e+02 1e+03 3e+00 5e+02 1e+00
1: -6.3206e-01 -1.5244e+01 7e+01 2e-01 3e+01 5e-02
2: -8.9622e-01 -5.2748e+00 2e+01 6e-02 9e+00 2e-02
3: -4.7107e-01 -2.0114e+00 4e+00 2e-02 3e+00 1e-02
4: -3.0885e-01 -9.9026e-01 2e+00 9e-03 1e+00 5e-03
5: -1.5746e-01 -5.0467e-01 8e-01 5e-03 7e-01 2e-03
6: -8.8994e-02 -2.1726e-01 3e-01 2e-03 3e-01 8e-04
7: -7.0477e-02 -1.5814e-01 2e-01 1e-03 2e-01 5e-04
8: -5.3775e-02 -1.0674e-01 1e-01 7e-04 1e-01 3e-04
9: -4.3274e-02 -7.8777e-02 9e-02 5e-04 7e-02 2e-04
10: -3.3888e-02 -5.6354e-02 6e-02 3e-04 5e-02 1e-04
11: -2.6815e-02 -4.0537e-02 4e-02 2e-04 3e-02 7e-05
12: -2.3512e-02 -3.2517e-02 3e-02 1e-04 2e-02 4e-05
13: -2.2136e-02 -2.9902e-02 2e-02 1e-04 2e-02 3e-05
14: -2.2603e-02 -3.0313e-02 2e-02 1e-04 2e-02 3e-05
15: -2.0466e-02 -2.6205e-02 2e-02 8e-05 1e-02 3e-05
16: -1.7460e-02 -2.0629e-02 1e-02 4e-05 7e-03 1e-05
17: -1.4571e-02 -1.5616e-02 4e-03 1e-05 2e-03 5e-06
18: -1.4181e-02 -1.4893e-02 3e-03 9e-06 1e-03 4e-06
19: -1.3328e-02 -1.3495e-02 6e-04 2e-06 3e-04 8e-07
20: -1.3093e-02 -1.3109e-02 6e-05 2e-07 3e-05 8e-08
21: -1.3077e-02 -1.3082e-02 2e-05 6e-08 9e-06 2e-08
22: -1.3070e-02 -1.3070e-02 2e-07 8e-10 1e-07 3e-10
23: -1.3070e-02 -1.3070e-02 2e-09 8e-12 1e-09 3e-12
Optimal solution found.
pcost dcost gap pres dres k/t
0: 6.4689e-02 -2.5969e+02 1e+03 3e+00 5e+02 1e+00
1: -6.3206e-01 -1.5244e+01 7e+01 2e-01 3e+01 5e-02
2: -8.9622e-01 -5.2748e+00 2e+01 6e-02 9e+00 2e-02
3: -4.7107e-01 -2.0114e+00 4e+00 2e-02 3e+00 1e-02
4: -3.0885e-01 -9.9026e-01 2e+00 9e-03 1e+00 5e-03
5: -1.5746e-01 -5.0467e-01 8e-01 5e-03 7e-01 2e-03
6: -8.8994e-02 -2.1726e-01 3e-01 2e-03 3e-01 8e-04
7: -7.0477e-02 -1.5814e-01 2e-01 1e-03 2e-01 5e-04
8: -5.3775e-02 -1.0674e-01 1e-01 7e-04 1e-01 3e-04
9: -4.3274e-02 -7.8777e-02 9e-02 5e-04 7e-02 2e-04
10: -3.3888e-02 -5.6354e-02 6e-02 3e-04 5e-02 1e-04
11: -2.6815e-02 -4.0537e-02 4e-02 2e-04 3e-02 7e-05
12: -2.3512e-02 -3.2517e-02 3e-02 1e-04 2e-02 4e-05
13: -2.2136e-02 -2.9902e-02 2e-02 1e-04 2e-02 3e-05
14: -2.2603e-02 -3.0313e-02 2e-02 1e-04 2e-02 3e-05
15: -2.0466e-02 -2.6205e-02 2e-02 8e-05 1e-02 3e-05
16: -1.7460e-02 -2.0629e-02 1e-02 4e-05 7e-03 1e-05
17: -1.4571e-02 -1.5616e-02 4e-03 1e-05 2e-03 5e-06
18: -1.4181e-02 -1.4893e-02 3e-03 9e-06 1e-03 4e-06
19: -1.3328e-02 -1.3495e-02 6e-04 2e-06 3e-04 8e-07
20: -1.3093e-02 -1.3109e-02 6e-05 2e-07 3e-05 8e-08
21: -1.3077e-02 -1.3082e-02 2e-05 6e-08 9e-06 2e-08
22: -1.3070e-02 -1.3070e-02 2e-07 8e-10 1e-07 3e-10
23: -1.3070e-02 -1.3070e-02 2e-09 8e-12 1e-09 3e-12
Optimal solution found.
Difference between two solutions 1.500933e-13
Testing in
/Users/frb15/Desktop/sage-5.7.beta0/spkg/build/cvxopt-1.1.5.p0/src/examples/doc/chap4
Testing acent.py ...
0. Newton decr. = 1.193e+01
1. Newton decr. = 8.441e+00
2. Newton decr. = 6.062e+00
3. Newton decr. = 4.284e+00
4. Newton decr. = 3.070e+00
5. Newton decr. = 2.296e+00
6. Newton decr. = 1.637e+00
7. Newton decr. = 1.185e+00
8. Newton decr. = 8.248e-01
9. Newton decr. = 5.477e-01
10. Newton decr. = 1.767e-01
11. Newton decr. = 5.559e-03
12. Newton decr. = 1.718e-07
13. Newton decr. = 7.985e-13
Testing in
/Users/frb15/Desktop/sage-5.7.beta0/spkg/build/cvxopt-1.1.5.p0/src/examples/doc/chap7
Testing covsel.py ...
500 rows/columns, 1741 nonzeros
Newton decrement squared: 5.01869e+08
Newton decrement squared: 1.29139e+08
Newton decrement squared: 3.26344e+07
Newton decrement squared: 1.14508e+02
Newton decrement squared: 2.68329e+01
Newton decrement squared: 1.52504e+00
Newton decrement squared: 5.25935e-03
Newton decrement squared: 6.89978e-08
Newton decrement squared: 1.34440e-17
number of iterations: 9
Testing in
/Users/frb15/Desktop/sage-5.7.beta0/spkg/build/cvxopt-1.1.5.p0/src/examples/doc/chap8
Testing conelp.py ...
pcost dcost gap pres dres k/t
0: 1.1431e+00 -2.3216e+02 5e+02 7e-01 8e+00 1e+00
1: 3.2291e+00 -7.6284e+01 1e+02 2e-01 3e+00 2e+00
2: -5.4057e+00 -7.5497e+01 1e+02 2e-01 2e+00 6e+00
3: -8.2526e+00 -5.0576e+01 7e+01 1e-01 1e+00 4e+00
4: 3.6383e+00 -4.2856e+01 9e+01 1e-01 2e+00 6e+00
5: -5.8339e+00 -2.2605e+01 4e+01 6e-02 7e-01 4e+00
6: -3.0169e+00 -1.5737e+01 2e+01 4e-02 5e-01 2e+00
7: -9.4177e+00 -1.6446e+01 1e+01 2e-02 3e-01 1e+00
8: -1.0564e+01 -1.1543e+01 2e+00 3e-03 4e-02 2e-01
9: -1.0930e+01 -1.1021e+01 2e-01 3e-04 4e-03 2e-02
10: -1.0948e+01 -1.0952e+01 8e-03 1e-05 2e-04 8e-04
11: -1.0949e+01 -1.0949e+01 1e-04 2e-07 3e-06 1e-05
12: -1.0949e+01 -1.0949e+01 1e-06 3e-09 3e-08 2e-07
Optimal solution found.
Status: optimal
x =
[-1.22e+00]
[ 9.66e-02]
[ 3.58e+00]
z =
[ 9.30e-02]
[ 1.06e-08]
[ 2.35e-01]
[ 1.33e-01]
[-4.73e-02]
[ 1.88e-01]
[ 1.25e-08]
[ 7.82e-11]
[-3.96e-10]
[-1.83e-09]
[ 1.26e-01]
[ 8.78e-02]
[-8.66e-02]
[ 8.78e-02]
[ 6.14e-02]
[-6.06e-02]
[-8.66e-02]
[-6.06e-02]
[ 5.98e-02]
Testing coneqp.py ...
pcost dcost gap pres dres
0: -1.0721e+00 -4.3040e+00 3e+00 0e+00 2e+00
1: -1.2240e+00 -1.5212e+00 3e-01 1e-15 2e-01
2: -1.4283e+00 -1.5409e+00 1e-01 1e-16 5e-02
3: -1.4300e+00 -1.4312e+00 1e-03 6e-15 5e-04
4: -1.4300e+00 -1.4300e+00 1e-05 2e-14 5e-06
5: -1.4300e+00 -1.4300e+00 1e-07 3e-14 5e-08
Optimal solution found.
x =
[ 7.26e-01]
[ 6.18e-01]
[ 3.03e-01]
Testing l1.py ...
pcost dcost gap pres dres k/t
0: 8.5089e+02 2.7294e+02 6e+02 8e-17 4e-15 1e+00
1: 8.7849e+02 4.1131e+02 5e+02 3e-16 2e-14 7e-01
2: 8.6797e+02 6.1491e+02 3e+02 3e-16 1e-14 3e-01
3: 8.0628e+02 7.0009e+02 1e+02 3e-16 8e-15 1e-01
4: 7.7503e+02 7.3246e+02 4e+01 4e-16 8e-15 4e-02
5: 7.6023e+02 7.4674e+02 1e+01 4e-16 7e-15 9e-03
6: 7.5524e+02 7.5092e+02 4e+00 5e-16 8e-15 3e-03
7: 7.5348e+02 7.5236e+02 1e+00 3e-16 2e-14 7e-04
8: 7.5315e+02 7.5264e+02 5e-01 6e-16 1e-14 3e-04
9: 7.5296e+02 7.5280e+02 2e-01 4e-16 2e-14 9e-05
10: 7.5289e+02 7.5286e+02 3e-02 3e-16 7e-14 2e-05
11: 7.5287e+02 7.5287e+02 2e-03 4e-16 1e-13 8e-07
12: 7.5287e+02 7.5287e+02 2e-05 3e-16 4e-14 8e-09
Optimal solution found.
Testing l1regls.py ...
pcost dcost gap pres dres
0: -6.2156e+02 -1.2128e+02 1e+03 7e+01 9e-13
1: -1.4192e+02 -1.2103e+02 4e+01 3e+00 4e-14
2: -1.2350e+02 -1.1783e+02 2e+01 1e+00 1e-14
3: -1.1628e+02 -1.1681e+02 1e+01 4e-01 6e-15
4: -1.1482e+02 -1.1634e+02 4e+00 1e-01 3e-15
5: -1.1523e+02 -1.1616e+02 2e+00 3e-02 2e-15
6: -1.1563e+02 -1.1611e+02 7e-01 1e-02 2e-15
7: -1.1589e+02 -1.1608e+02 3e-01 3e-03 4e-15
8: -1.1599e+02 -1.1607e+02 1e-01 9e-04 6e-15
9: -1.1605e+02 -1.1606e+02 8e-03 3e-16 2e-14
10: -1.1606e+02 -1.1606e+02 5e-04 3e-16 9e-14
11: -1.1606e+02 -1.1606e+02 1e-05 3e-16 4e-13
Optimal solution found.
Testing lp.py ...
pcost dcost gap pres dres k/t
0: -8.1000e+00 -1.8300e+01 4e+00 0e+00 8e-01 1e+00
1: -8.8055e+00 -9.4357e+00 2e-01 1e-16 4e-02 3e-02
2: -8.9981e+00 -9.0049e+00 2e-03 4e-16 5e-04 4e-04
3: -9.0000e+00 -9.0000e+00 2e-05 2e-16 5e-06 4e-06
4: -9.0000e+00 -9.0000e+00 2e-07 3e-16 5e-08 4e-08
Optimal solution found.
x =
[ 1.00e+00]
[ 1.00e+00]
Testing mcsdp.py ...
pcost dcost gap pres dres k/t
0: 2.0201e+03 -2.2102e+00 2e+03 1e-16 0e+00 1e+00
1: 2.6322e+03 7.5634e+02 2e+03 2e-14 9e-16 5e+00
2: 1.8364e+03 1.3265e+03 5e+02 8e-15 1e-15 2e+00
3: 1.8146e+03 1.4724e+03 3e+02 9e-15 1e-15 2e+00
4: 1.7423e+03 1.7172e+03 3e+01 6e-15 2e-15 2e-01
5: 1.7382e+03 1.7340e+03 4e+00 6e-15 2e-15 3e-02
6: 1.7378e+03 1.7370e+03 9e-01 7e-15 2e-15 7e-03
7: 1.7378e+03 1.7377e+03 1e-01 7e-15 2e-15 1e-03
8: 1.7378e+03 1.7378e+03 1e-02 6e-15 1e-15 9e-05
9: 1.7378e+03 1.7378e+03 1e-03 8e-15 5e-13 1e-05
Optimal solution found.
Testing portfolio.py ...
Testing qcl1.py ...
pcost dcost gap pres dres k/t
0: 0.0000e+00 -1.0000e+00 5e+02 3e+00 2e+00 1e+00
1: 1.2547e+01 1.5524e+01 2e+02 1e+00 1e+00 4e+00
2: 1.0595e+01 1.3428e+01 4e+01 4e-01 3e-01 3e+00
3: 1.5912e+01 1.6324e+01 4e+00 5e-02 4e-02 4e-01
4: 1.7157e+01 1.7212e+01 6e-01 8e-03 6e-03 6e-02
5: 1.7290e+01 1.7307e+01 2e-01 3e-03 2e-03 2e-02
6: 1.7356e+01 1.7359e+01 7e-02 9e-04 7e-04 4e-03
7: 1.7373e+01 1.7373e+01 2e-02 2e-04 2e-04 6e-04
8: 1.7378e+01 1.7378e+01 2e-03 3e-05 2e-05 7e-05
9: 1.7379e+01 1.7379e+01 3e-04 4e-06 3e-06 7e-06
10: 1.7379e+01 1.7379e+01 3e-05 4e-07 3e-07 6e-07
11: 1.7379e+01 1.7379e+01 7e-06 9e-08 7e-08 1e-07
Optimal solution found.
Testing sdp.py ...
pcost dcost gap pres dres k/t
0: -1.2037e+00 -1.8539e+02 2e+02 2e-16 8e+00 1e+00
1: -1.2937e+00 -6.8551e+00 5e+00 5e-16 3e-01 3e-02
2: -2.8964e+00 -3.7331e+00 7e-01 4e-16 4e-02 5e-02
3: -3.0150e+00 -3.2556e+00 2e-01 5e-16 1e-02 2e-02
4: -3.1389e+00 -3.1932e+00 5e-02 3e-16 3e-03 5e-03
5: -3.1533e+00 -3.1547e+00 1e-03 1e-15 7e-05 1e-04
6: -3.1535e+00 -3.1536e+00 5e-05 8e-16 3e-06 6e-06
7: -3.1535e+00 -3.1535e+00 1e-06 9e-16 7e-08 2e-07
Optimal solution found.
x =
[-3.68e-01]
[ 1.90e+00]
[-8.88e-01]
zs[0] =
[ 3.96e-03 -4.34e-03]
[-4.34e-03 4.75e-03]
zs[1] =
[ 5.58e-02 -2.41e-03 2.42e-02]
[-2.41e-03 1.04e-04 -1.05e-03]
[ 2.42e-02 -1.05e-03 1.05e-02]
Testing socp.py ...
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
Optimal solution found.
x =
[-5.01e+00]
[-5.77e+00]
[-8.52e+00]
zq[0] =
[ 1.34e+00]
[-7.63e-02]
[-1.34e+00]
zq[1] =
[ 1.02e+00]
[ 4.02e-01]
[ 7.80e-01]
[-5.17e-01]
Testing in
/Users/frb15/Desktop/sage-5.7.beta0/spkg/build/cvxopt-1.1.5.p0/src/examples/doc/chap9
Testing acent.py ...
pcost dcost gap pres dres
0: 0.0000e+00 0.0000e+00 1e+00 1e+00 1e+00
1: 4.0905e+01 1.5122e+02 6e-01 7e-01 8e-01
2: 1.8012e+02 2.4780e+02 6e-03 8e-01 7e-01
3: 2.2830e+02 2.3794e+02 6e-05 1e-01 1e-01
4: 2.3605e+02 2.3697e+02 6e-07 1e-02 8e-03
5: 2.3692e+02 2.3695e+02 6e-09 4e-04 3e-04
6: 2.3695e+02 2.3695e+02 6e-11 4e-06 5e-06
7: 2.3695e+02 2.3695e+02 6e-13 4e-08 5e-08
Optimal solution found.
Testing acent2.py ...
pcost dcost gap pres dres
0: 0.0000e+00 -1.1600e+02 5e+00 1e+00 1e+00
1: 6.1083e-03 -3.2919e+01 4e+00 1e+00 1e+00
2: 6.5547e-02 -1.3272e+01 3e+00 9e-01 9e-01
3: 4.5177e-01 -5.8044e-01 2e+00 6e-01 7e-01
4: 5.8869e-01 9.1517e-01 1e+00 5e-01 5e-01
5: 9.4434e-01 2.4680e+00 1e+00 4e-01 6e-01
6: 8.2046e-01 1.3892e+00 1e+00 3e-01 4e-01
7: 8.5287e-01 1.4594e+00 4e-01 1e-01 2e-01
8: 1.0036e+00 1.4560e+00 4e-01 1e-01 2e-01
9: 1.1380e+00 1.2097e+00 1e-01 8e-03 3e-02
10: 1.2575e+00 1.2716e+00 3e-02 1e-03 8e-03
11: 1.2837e+00 1.2841e+00 1e-02 4e-04 2e-03
12: 1.2896e+00 1.2896e+00 2e-03 5e-05 8e-04
13: 1.2899e+00 1.2898e+00 1e-03 4e-05 6e-04
14: 1.2905e+00 1.2904e+00 3e-04 7e-06 3e-04
15: 1.2905e+00 1.2905e+00 3e-04 6e-06 2e-04
16: 1.2906e+00 1.2906e+00 5e-05 1e-06 8e-05
17: 1.2906e+00 1.2906e+00 5e-05 8e-07 7e-05
18: 1.2906e+00 1.2906e+00 1e-05 2e-07 3e-05
19: 1.2906e+00 1.2906e+00 1e-05 1e-07 1e-05
20: 1.2906e+00 1.2906e+00 3e-06 3e-08 7e-06
21: 1.2906e+00 1.2906e+00 2e-06 2e-08 8e-06
22: 1.2906e+00 1.2906e+00 7e-07 7e-09 3e-06
23: 1.2906e+00 1.2906e+00 6e-07 5e-09 1e-06
24: 1.2906e+00 1.2906e+00 2e-07 1e-09 7e-07
25: 1.2906e+00 1.2906e+00 2e-07 1e-09 1e-06
26: 1.2906e+00 1.2906e+00 6e-08 3e-10 5e-07
27: 1.2906e+00 1.2906e+00 5e-08 2e-10 1e-07
28: 1.2906e+00 1.2906e+00 2e-08 7e-11 9e-08
Optimal solution found.
x =
[ 4.11e-01]
[ 5.59e-01]
[-7.20e-01]
Testing floorplan.py ...
Testing gp.py ...
pcost dcost gap pres dres
0: 0.0000e+00 -1.2899e+01 7e+00 1e+00 7e-01
1: -3.1612e+00 -7.7955e+00 3e+00 5e-01 4e-01
2: -4.0448e+00 -6.3257e+00 2e+00 3e-01 2e-01
3: -5.0956e+00 -5.3372e+00 2e-01 5e-03 5e-03
4: -5.2276e+00 -5.2772e+00 5e-02 8e-04 2e-03
5: -5.2594e+00 -5.2637e+00 8e-03 4e-04 1e-03
6: -5.2598e+00 -5.2608e+00 2e-03 9e-05 4e-04
7: -5.2598e+00 -5.2601e+00 5e-04 2e-05 1e-04
8: -5.2598e+00 -5.2599e+00 1e-04 6e-06 3e-05
9: -5.2598e+00 -5.2599e+00 3e-05 1e-06 7e-06
10: -5.2598e+00 -5.2598e+00 8e-06 4e-07 2e-06
11: -5.2598e+00 -5.2598e+00 2e-06 9e-08 4e-07
12: -5.2598e+00 -5.2598e+00 5e-07 2e-08 1e-07
13: -5.2598e+00 -5.2598e+00 1e-07 6e-09 3e-08
Optimal solution found.
h = 2.887313, w = 5.774627, d = 11.542511.
Testing l2ac.py ...
pcost dcost gap pres dres
0: 0.0000e+00 6.0818e+04 1e+00 1e+00 1e+00
1: -6.0090e+04 6.9652e+01 1e-02 1e+00 1e-02
2: -5.4418e+02 6.3439e+01 1e-04 1e-02 1e-04
3: 5.7361e+01 6.3438e+01 1e-06 1e-04 1e-06
4: 6.3377e+01 6.3438e+01 1e-08 1e-06 1e-08
5: 6.3437e+01 6.3438e+01 1e-10 1e-08 1e-10
Optimal solution found.
Testing robls.py ...
pcost dcost gap pres dres
0: 0.0000e+00 4.4597e+02 1e+00 1e+00 1e+00
1: 3.3120e+02 4.5345e+02 1e-02 3e-01 1e+00
2: 3.0883e+02 4.5353e+02 1e-04 3e-01 1e+00
3: 3.1732e+02 4.6375e+02 1e-06 3e-01 1e+00
4: 2.4984e+02 5.0981e+02 1e-08 6e-01 1e+00
5: 1.3818e+02 6.3080e+02 1e-10 1e+00 2e+00
6: -8.9948e+02 1.8021e+03 1e-12 6e+00 2e+00
7: -1.1605e+05 1.2083e+05 1e-14 5e+02 2e+00
8: -3.2180e+10 3.2196e+10 1e-16 1e+08 2e+00
9: 2.6140e+02 4.1484e+02 1e-04 3e-01 4e-01
10: 4.0355e+02 4.1004e+02 1e-06 1e-02 9e-02
11: 4.0955e+02 4.0983e+02 1e-08 6e-04 4e-03
12: 4.0982e+02 4.0982e+02 1e-10 7e-06 6e-05
13: 4.0982e+02 4.0982e+02 1e-12 7e-08 6e-07
14: 4.0982e+02 4.0982e+02 1e-14 7e-10 6e-09
Optimal solution found.
}}}
--
Ticket URL: <http://trac.sagemath.org/sage_trac/ticket/12832#comment:15>
Sage <http://www.sagemath.org>
Sage: Creating a Viable Open Source Alternative to Magma, Maple, Mathematica,
and MATLAB
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