Opened 9 years ago

Closed 8 years ago

Last modified 8 years ago

#12832 closed defect (fixed)

Upgrade cvxopt to 1.1.6

Reported by: fbissey Owned by: tbd
Priority: major Milestone: sage-5.10
Component: packages: standard Keywords:
Cc: Merged in: sage-5.10.beta4
Authors: Jeroen Demeyer Reviewers: Volker Braun
Report Upstream: Fixed upstream, in a later stable release. Work issues:
Branch: Commit:
Dependencies: Stopgaps:

Description (last modified by jdemeyer)

There are two doctests related to cvxopt failing on power7

sage -t --long -force_lib "devel/sage/doc/en/numerical_sage/cvxopt.rst"
**********************************************************************
File "/hpc/scratch/frb15/sandbox/sage-5.7.beta4/devel/sage/doc/en/numerical_sage/cvxopt.rst", line 129:
    sage: print sol['x']      # ... below since can get -00 or +00 depending on architecture
Expected:
    [ 1.00e...00]
    [ 1.00e+00]
Got:
    [ 9.87e-01]
    [ 9.92e-01]
    <BLANKLINE>
**********************************************************************

and

sage -t -long "devel/sage-main/sage/numerical/optimize.py"  
**********************************************************************
File "/hpc/scratch/frb15/sandbox/sage-5.7.beta4/devel/sage-main/sage/numerical/optimize.py", line 515:
    sage: sol['x']
Expected:
    (0.999..., 1.000...)
Got nothing
**********************************************************************
File "/hpc/scratch/frb15/sandbox/sage-5.7.beta4/devel/sage-main/sage/numerical/optimize.py", line 525:
    sage: sol['x']
Expected:
    (45.000000..., 6.2499999...3, 1.00000000...)
Got nothing
GLPK Simplex Optimizer, v4.44
6 rows, 3 columns, 8 non-zeros
Preprocessing...
2 rows, 2 columns, 4 non-zeros
Scaling...
 A: min|aij| =  2.400e+01  max|aij| =  5.000e+01  ratio =  2.083e+00
GM: min|aij| =  8.128e-01  max|aij| =  1.230e+00  ratio =  1.514e+00
EQ: min|aij| =  6.606e-01  max|aij| =  1.000e+00  ratio =  1.514e+00
Constructing initial basis...
Size of triangular part = 2
*     0: obj =  -5.100000000e+01  infeas =  0.000e+00 (0)
*     1: obj =  -5.225000000e+01  infeas =  0.000e+00 (0)
OPTIMAL SOLUTION FOUND
**********************************************************************

This is now solved in cvxopt 1.1.6. The updated cvxopt spkg also fixes a blas path issue on Darwin and Cygwin.

spkg: http://boxen.math.washington.edu/home/jdemeyer/spkg/cvxopt-1.1.6.p0.spkg (spkg diff)

Attachments (1)

cvxopt-1.1.6.p0.diff (4.7 KB) - added by jdemeyer 8 years ago.
spkg diff

Download all attachments as: .zip

Change History (45)

comment:1 Changed 9 years ago by fbissey

I think they may be both upstream problems. I have tried to run test on a stock scipy-0.10.0 on power7 and several results indicate that at least some of the problems are in scipy itself

ERROR: test_linear_1d (test_fitpack.TestUnivariateSpline)
----------------------------------------------------------------------
Traceback (most recent call last):
  File "/hpc/scratch/frb15/work/scipy-0.10.0/test/lib/python/scipy/interpolate/tests/test_fitpack.py", line 49, in test_linear_1d
    assert_array_almost_equal(lut([1,1.5,2]),[0,1,2])
  File "scipy/interpolate/fitpack2.py", line 221, in __call__
    return fitpack.splev(x, self._eval_args, der=nu)
  File "scipy/interpolate/fitpack.py", line 550, in splev
    raise ValueError("Invalid input data")
ValueError: Invalid input data

======================================================================
ERROR: test_linear_constant (test_fitpack.TestUnivariateSpline)
----------------------------------------------------------------------
Traceback (most recent call last):
  File "/hpc/scratch/frb15/work/scipy-0.10.0/test/lib/python/scipy/interpolate/tests/test_fitpack.py", line 29, in test_linear_constant
    assert_array_almost_equal(lut([1,1.5,2]),[3,3,3])
  File "scipy/interpolate/fitpack2.py", line 221, in __call__
    return fitpack.splev(x, self._eval_args, der=nu)
  File "scipy/interpolate/fitpack.py", line 550, in splev
    raise ValueError("Invalid input data")
ValueError: Invalid input data

======================================================================
ERROR: test_preserve_shape (test_fitpack.TestUnivariateSpline)
----------------------------------------------------------------------
Traceback (most recent call last):
  File "/hpc/scratch/frb15/work/scipy-0.10.0/test/lib/python/scipy/interpolate/tests/test_fitpack.py", line 36, in test_preserve_shape
    assert_equal(shape(arg), shape(lut(arg)))
  File "scipy/interpolate/fitpack2.py", line 221, in __call__
    return fitpack.splev(x, self._eval_args, der=nu)
  File "scipy/interpolate/fitpack.py", line 550, in splev
    raise ValueError("Invalid input data")
ValueError: Invalid input data

======================================================================
ERROR: Regression test for #1375.
----------------------------------------------------------------------
Traceback (most recent call last):
  File "/hpc/scratch/frb15/work/scipy-0.10.0/test/lib/python/scipy/interpolate/tests/test_fitpack.py", line 82, in test_resize_regression
    assert_allclose(spl([0.1, 0.5, 0.9, 0.99]), desired, atol=5e-4)
  File "scipy/interpolate/fitpack2.py", line 221, in __call__
    return fitpack.splev(x, self._eval_args, der=nu)
  File "scipy/interpolate/fitpack.py", line 550, in splev
    raise ValueError("Invalid input data")
ValueError: Invalid input data

======================================================================
ERROR: Failure: AttributeError ('module' object has no attribute 'qhull')
----------------------------------------------------------------------
Traceback (most recent call last):
  File "/usr/local/pkg/python/version/lib/python2.7/site-packages/nose-1.1.2-py2.7.egg/nose/loader.py", line 390, in loadTestsFromName
    addr.filename, addr.module)
  File "/usr/local/pkg/python/version/lib/python2.7/site-packages/nose-1.1.2-py2.7.egg/nose/importer.py", line 39, in importFromPath
    return self.importFromDir(dir_path, fqname)
  File "/usr/local/pkg/python/version/lib/python2.7/site-packages/nose-1.1.2-py2.7.egg/nose/importer.py", line 86, in importFromDir
    mod = load_module(part_fqname, fh, filename, desc)
  File "/hpc/scratch/frb15/work/scipy-0.10.0/test/lib/python/scipy/interpolate/tests/test_interpnd.py", line 6, in <module>
    import scipy.spatial.qhull as qhull
AttributeError: 'module' object has no attribute 'qhull'

======================================================================
ERROR: test_interp2d (test_interpolate.TestInterp2D)
----------------------------------------------------------------------
Traceback (most recent call last):
  File "/hpc/scratch/frb15/work/scipy-0.10.0/test/lib/python/scipy/interpolate/tests/test_interpolate.py", line 14, in test_interp2d
    I = interp2d(x, y, z)
  File "scipy/interpolate/interpolate.py", line 160, in __init__
    self.tck = fitpack.bisplrep(self.x, self.y, self.z, kx=kx, ky=ky, s=0.)
  File "scipy/interpolate/fitpack.py", line 873, in bisplrep
    tx,ty,nxest,nyest,wrk,lwrk1,lwrk2)
ValueError: negative dimensions are not allowed

======================================================================
ERROR: test_interp2d_meshgrid_input (test_interpolate.TestInterp2D)
----------------------------------------------------------------------
Traceback (most recent call last):
  File "/hpc/scratch/frb15/work/scipy-0.10.0/test/lib/python/scipy/interpolate/tests/test_interpolate.py", line 25, in test_interp2d_meshgrid_input
    I = interp2d(x, y, z)
  File "scipy/interpolate/interpolate.py", line 160, in __init__
    self.tck = fitpack.bisplrep(self.x, self.y, self.z, kx=kx, ky=ky, s=0.)
  File "scipy/interpolate/fitpack.py", line 873, in bisplrep
    tx,ty,nxest,nyest,wrk,lwrk1,lwrk2)
ValueError: negative dimensions are not allowed

======================================================================
ERROR: test_construction (test_polyint.CheckPiecewise)
----------------------------------------------------------------------
Traceback (most recent call last):
  File "/hpc/scratch/frb15/work/scipy-0.10.0/test/lib/python/scipy/interpolate/tests/test_polyint.py", line 194, in setUp
    self.spline_ys = splev(self.test_xs, self.tck)
  File "scipy/interpolate/fitpack.py", line 550, in splev
    raise ValueError("Invalid input data")
ValueError: Invalid input data

======================================================================
ERROR: test_derivative (test_polyint.CheckPiecewise)
----------------------------------------------------------------------
Traceback (most recent call last):
  File "/hpc/scratch/frb15/work/scipy-0.10.0/test/lib/python/scipy/interpolate/tests/test_polyint.py", line 194, in setUp
    self.spline_ys = splev(self.test_xs, self.tck)
  File "scipy/interpolate/fitpack.py", line 550, in splev
    raise ValueError("Invalid input data")
ValueError: Invalid input data

======================================================================
ERROR: test_derivatives (test_polyint.CheckPiecewise)
----------------------------------------------------------------------
Traceback (most recent call last):
  File "/hpc/scratch/frb15/work/scipy-0.10.0/test/lib/python/scipy/interpolate/tests/test_polyint.py", line 194, in setUp
    self.spline_ys = splev(self.test_xs, self.tck)
  File "scipy/interpolate/fitpack.py", line 550, in splev
    raise ValueError("Invalid input data")
ValueError: Invalid input data

======================================================================
ERROR: test_incremental (test_polyint.CheckPiecewise)
----------------------------------------------------------------------
Traceback (most recent call last):
  File "/hpc/scratch/frb15/work/scipy-0.10.0/test/lib/python/scipy/interpolate/tests/test_polyint.py", line 194, in setUp
    self.spline_ys = splev(self.test_xs, self.tck)
  File "scipy/interpolate/fitpack.py", line 550, in splev
    raise ValueError("Invalid input data")
ValueError: Invalid input data

======================================================================
ERROR: test_scalar (test_polyint.CheckPiecewise)
----------------------------------------------------------------------
Traceback (most recent call last):
  File "/hpc/scratch/frb15/work/scipy-0.10.0/test/lib/python/scipy/interpolate/tests/test_polyint.py", line 194, in setUp
    self.spline_ys = splev(self.test_xs, self.tck)
  File "scipy/interpolate/fitpack.py", line 550, in splev
    raise ValueError("Invalid input data")
ValueError: Invalid input data

======================================================================
ERROR: test_shapes_scalarvalue (test_polyint.CheckPiecewise)
----------------------------------------------------------------------
Traceback (most recent call last):
  File "/hpc/scratch/frb15/work/scipy-0.10.0/test/lib/python/scipy/interpolate/tests/test_polyint.py", line 194, in setUp
    self.spline_ys = splev(self.test_xs, self.tck)
  File "scipy/interpolate/fitpack.py", line 550, in splev
    raise ValueError("Invalid input data")
ValueError: Invalid input data

======================================================================
ERROR: test_shapes_scalarvalue_derivative (test_polyint.CheckPiecewise)
----------------------------------------------------------------------
Traceback (most recent call last):
  File "/hpc/scratch/frb15/work/scipy-0.10.0/test/lib/python/scipy/interpolate/tests/test_polyint.py", line 194, in setUp
    self.spline_ys = splev(self.test_xs, self.tck)
  File "scipy/interpolate/fitpack.py", line 550, in splev
    raise ValueError("Invalid input data")
ValueError: Invalid input data

======================================================================
ERROR: test_shapes_vectorvalue (test_polyint.CheckPiecewise)
----------------------------------------------------------------------
Traceback (most recent call last):
  File "/hpc/scratch/frb15/work/scipy-0.10.0/test/lib/python/scipy/interpolate/tests/test_polyint.py", line 194, in setUp
    self.spline_ys = splev(self.test_xs, self.tck)
  File "scipy/interpolate/fitpack.py", line 550, in splev
    raise ValueError("Invalid input data")
ValueError: Invalid input data

======================================================================
ERROR: test_shapes_vectorvalue_1d (test_polyint.CheckPiecewise)
----------------------------------------------------------------------
Traceback (most recent call last):
  File "/hpc/scratch/frb15/work/scipy-0.10.0/test/lib/python/scipy/interpolate/tests/test_polyint.py", line 194, in setUp
    self.spline_ys = splev(self.test_xs, self.tck)
  File "scipy/interpolate/fitpack.py", line 550, in splev
    raise ValueError("Invalid input data")
ValueError: Invalid input data

======================================================================
ERROR: test_shapes_vectorvalue_derivative (test_polyint.CheckPiecewise)
----------------------------------------------------------------------
Traceback (most recent call last):
  File "/hpc/scratch/frb15/work/scipy-0.10.0/test/lib/python/scipy/interpolate/tests/test_polyint.py", line 194, in setUp
    self.spline_ys = splev(self.test_xs, self.tck)
  File "scipy/interpolate/fitpack.py", line 550, in splev
    raise ValueError("Invalid input data")
ValueError: Invalid input data

======================================================================
ERROR: test_vector (test_polyint.CheckPiecewise)
----------------------------------------------------------------------
Traceback (most recent call last):
  File "/hpc/scratch/frb15/work/scipy-0.10.0/test/lib/python/scipy/interpolate/tests/test_polyint.py", line 194, in setUp
    self.spline_ys = splev(self.test_xs, self.tck)
  File "scipy/interpolate/fitpack.py", line 550, in splev
    raise ValueError("Invalid input data")
ValueError: Invalid input data

======================================================================
ERROR: test_wrapper (test_polyint.CheckPiecewise)
----------------------------------------------------------------------
Traceback (most recent call last):
  File "/hpc/scratch/frb15/work/scipy-0.10.0/test/lib/python/scipy/interpolate/tests/test_polyint.py", line 194, in setUp
    self.spline_ys = splev(self.test_xs, self.tck)
  File "scipy/interpolate/fitpack.py", line 550, in splev
    raise ValueError("Invalid input data")
ValueError: Invalid input data

======================================================================
ERROR: Ticket #629
----------------------------------------------------------------------
Traceback (most recent call last):
  File "/hpc/scratch/frb15/work/scipy-0.10.0/test/lib/python/scipy/interpolate/tests/test_regression.py", line 11, in test_spalde_scalar_input
    res = interp.spalde(np.float64(1), tck)
  File "scipy/interpolate/fitpack.py", line 724, in spalde
    raise TypeError("Invalid input data. t(k)<=x<=t(n-k+1) must hold.")
TypeError: Invalid input data. t(k)<=x<=t(n-k+1) must hold.

======================================================================

There are more error linked to failures to import modules which may be more related to the way test were run. As in the doctest a number of improper parameters or invalid data and negative dimensions problems.

comment:2 Changed 9 years ago by zimmerma

I investigated the first error in optimize.py:

c=vector(RDF,[-4,-5])
G=matrix(RDF,[[2,1],[1,2],[-1,0],[0,-1]])
h=vector(RDF,[3,3,0,0])
from cvxopt.base import matrix as m
from cvxopt import solvers
solvers.options['show_progress']=True
c_=m(c.base_extend(RDF).numpy())
G_=m(G.base_extend(RDF).numpy())
h_=m(h.base_extend(RDF).numpy())
sol=solvers.lp(c_,G_,h_,solver=None)

The first numerical difference comes from the call base.gemm(spmatrix(W['di'], list(range(ml)), list(range(ml))), G, F['Gs'], partial = True) in local/lib/python2.7/site-packages/cvxopt/misc.py, where the inputs are:

W['di']= [ 3.06e+00]
[ 3.32e+00]
[ 1.29e+00]
[ 1.05e+00]
ml= 4
G= [ 2.00e+00  1.00e+00]
[ 1.00e+00  2.00e+00]
[-1.00e+00  0.00e+00]
[ 0.00e+00 -1.00e+00]

and the expected output is:

F['Gs']= [ 6.11e+00  3.06e+00]
[ 3.32e+00  6.63e+00]
[-1.29e+00  0.00e+00]
[ 0.00e+00 -1.05e+00]

whereas we get:

 F['Gs']= [ 8.11e+00  4.06e+00]
[ 4.32e+00  8.63e+00]
[-2.29e+00  0.00e+00]
[ 0.00e+00 -2.05e+00]

Does anybody know where the base.gemm function is defined?

Paul

comment:3 Changed 9 years ago by zimmerma

I could reduce the issue to the following:

import numpy
from cvxopt.base import spmatrix
from cvxopt.base import matrix as m
from cvxopt import umfpack
RealNumber=float
W = [ 3.06e+00, 3.32e+00, 1.29e+00, 1.05e+00]
ml=4
W2 = spmatrix(W, list(range(ml)), list(range(ml)))
G= m([[2.00e+00,  1.00e+00, -1.00e+00,  0.00e+00],
      [1.00e+00,  2.00e+00,  0.00e+00, -1.00e+00]])
F = m([[0.0,0.0,0.0,0.0],[0.0,0.0,0.0,0.0]])
from cvxopt.base import gemm
import cvxopt
cvxopt.base.gemm(W2,G,F,partial = True)
print F
cvxopt.base.gemm(W2,G,F,partial = True)
print F

The expected output is twice the same matrix F:

[ 6.12e+00  3.06e+00]
[ 3.32e+00  6.64e+00]
[-1.29e+00  0.00e+00]
[ 0.00e+00 -1.05e+00]

[ 6.12e+00  3.06e+00]
[ 3.32e+00  6.64e+00]
[-1.29e+00  0.00e+00]
[ 0.00e+00 -1.05e+00]

On silius with sage-5.0.rc1 I get instead:

[ 6.12e+00  3.06e+00]
[ 3.32e+00  6.64e+00]
[-1.29e+00  0.00e+00]
[ 0.00e+00 -1.05e+00]

[ 1.22e+01  6.12e+00]
[ 6.64e+00  1.33e+01]
[-2.58e+00  0.00e+00]
[ 0.00e+00 -2.10e+00]

thus it seems the product is accumulated to F.

Paul

comment:4 Changed 9 years ago by fbissey

That's unexpected, It could be a cvxopt problem rather than a scipy problem. I may be able to check on Monday when I go back to work for real if there are more problems with cvxopt.

comment:5 Changed 9 years ago by fbissey

Yes I can confirm that with 5.1beta5 (and cvxopt-1.1.5 from #13160). Will look at the code.

comment:6 Changed 9 years ago by fbissey

If after that we do (http://abel.ee.ucla.edu/cvxopt/userguide/blas.html#level-3-blas)

F = m([[0.0,0.0,0.0,0.0],[0.0,0.0,0.0,0.0]])
cvxopt.base.gemm(W2,G,F,beta=0.5,partial = True)
print F
cvxopt.base.gemm(W2,G,F,beta=0.5,partial = True
print F

we get

[ 6.12e+00  3.06e+00]
[ 3.32e+00  6.64e+00]
[-1.29e+00  0.00e+00]
[ 0.00e+00 -1.05e+00]

[ 1.22e+01  6.12e+00]
[ 6.64e+00  1.33e+01]
[-2.58e+00  0.00e+00]
[ 0.00e+00 -2.10e+00]

Clearly the beta factor is always passed as "1" rather than the default zero or the value you want. I checked that passing a value for alpha works.

comment:7 Changed 9 years ago by fbissey

I am not completely sure of what is happening there. I need to have a control build locally to be sure. The evaluation eventually goes to sp_dgemm in C/sparse.c, more specifically this section

  else if (sp_a && !sp_b && !sp_c) {

    ccs *A = (tA == 'N' ? a : transpose(a, 0));
    double *B = b, *C = c;

    int j, l, mn_ = m*n, ib = (tB == 'N' ? k : 1);
    scal[DOUBLE](&mn_, &beta, C, (int *)&One[INT]);

    for (j=0; j<A->ncols; j++) {
      for (l=A->colptr[j]; l<A->colptr[j+1]; l++) {

        double a_ = alpha.d*((double *)A->values)[l];
        axpy[DOUBLE](&n, &a_, B + (tB == 'N' ? j : j*n), &ib,
            C + A->rowind[l], &m);
      }
    }
    if (A != a) free_ccs(A);
  }

  else if (!sp_a && sp_b && sp_c && partial){

Notice that in this particular case "partial" is ignored. The issue here is that we don't seem to go through scal[DOUBLE] (part of C/blas.c) at all. That particular call should replace our F input by beta.d*F where beta.d is 0 by default. The fact that this call seem completely bypassed explains why it is useless to give a value for beta.

comment:8 Changed 9 years ago by fbissey

I cannot see it going in scal[DOUBLE] on my x86_64 box either. I will have to dig it a bit more to find how to crack what is happening there.

comment:9 Changed 9 years ago by fbissey

cvxopt.base is not linked to cvxopt.blas which contains the interface to scal (it is working fine). So in the previous code this should be a direct call to dscal. I am guessing there is something about the declarations in that bit of code that I don't understand fully. But then why does it work on anything but power7?

comment:10 Changed 9 years ago by fbissey

Finally found out it is supposed to be a direct call to blas dscal_ but the declaration are all wrong for that I think. I may have to copy the declaration from base.c and see if it works.

comment:11 Changed 9 years ago by fbissey

I have no clue why the call to dscal_ either doesn't happen or return the wrong thing.

comment:12 follow-up: Changed 8 years ago by zimmerma

maybe this is due to the fact that the power7 is big endian, and some code is not endian-safe?

Paul

comment:13 in reply to: ↑ 12 Changed 8 years ago by fbissey

Replying to zimmerma:

maybe this is due to the fact that the power7 is big endian, and some code is not endian-safe?

No. We have some other big endian platforms: OS X ppc, arm and sparc. It would have shown up somewhere before.

Francois

comment:14 Changed 8 years ago by fbissey

  • Description modified (diff)
  • Summary changed from Bug in scipy on power7 to Bug in cvxopt on power7

comment:15 Changed 8 years ago 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.

comment:16 Changed 8 years ago by fbissey

And on power7:

Running the test suite for cvxopt-1.1.5.p0...
Testing in /hpc/scratch/frb15/sandbox/sage-5.7.beta4/spkg/build/cvxopt-1.1.5.p0/src/examples/doc/chap10
Testing l1svc.py ...
solver:chol2
     pcost       dcost       gap    pres   dres   k/t
 0:  1.9477e+02  8.3326e+02  4e+03  3e+00  1e+01  1e+00
 1:  2.1671e+04  4.2707e+04  1e+07  1e+02  9e+02  1e+02
 2:  3.2309e+02  9.3319e+02  2e+03  1e+00  1e+01  3e+02
 3:  4.6110e+02  1.2079e+03  4e+03  1e+00  2e+01  4e+02
 4:  9.1507e+02  2.1725e+03  8e+03  1e+00  4e+01  1e+03
 5:  7.0776e+04  1.6523e+05  7e+06  6e+02  3e+03  9e+04
 6:  7.8619e+04  1.8520e+05  8e+06  1e+03  4e+03  1e+05
 7:  3.9389e+05  1.0062e+06  1e+08  5e+04  2e+04  6e+05
 8:  3.7585e+05  9.4053e+05  1e+08  5e+04  2e+04  6e+05
 9:  3.2815e+05  7.3358e+05  8e+07  5e+04  1e+04  4e+05
10:  3.8380e+05  9.2250e+05  1e+08  5e+04  2e+04  5e+05
11:  4.4182e+05  9.2418e+05  1e+08  1e+05  2e+04  5e+05
12:  4.0964e+05  9.3672e+05  2e+08  2e+05  2e+04  5e+05
13:  5.1893e+05  1.2061e+06  2e+08  2e+05  2e+04  7e+05
14:  5.2093e+05  1.1989e+06  3e+08  3e+05  2e+04  7e+05
15:  5.2496e+05  1.1985e+06  3e+08  3e+05  2e+04  7e+05
16:  6.7271e+05  1.4883e+06  4e+08  4e+05  3e+04  8e+05
17:  6.3803e+05  1.3178e+06  5e+08  3e+05  2e+04  7e+05
18:  6.5847e+05  1.3667e+06  5e+08  3e+05  2e+04  7e+05
19:  6.6945e+05  1.3919e+06  6e+08  3e+05  2e+04  7e+05
20:  6.7820e+05  1.4086e+06  6e+08  3e+05  2e+04  7e+05
21:  1.1690e+06  2.5552e+06  1e+09  4e+05  4e+04  1e+06
22:  1.0766e+06  2.2177e+06  1e+09  4e+05  4e+04  1e+06
23:  1.0864e+06  2.1777e+06  1e+09  4e+05  4e+04  1e+06
24:  1.1089e+06  2.2182e+06  1e+09  4e+05  4e+04  1e+06
25:  1.2188e+06  2.4201e+06  1e+09  4e+05  4e+04  1e+06
26:  1.2510e+06  2.4658e+06  1e+09  4e+05  4e+04  1e+06
27:  1.3379e+06  2.6260e+06  2e+09  5e+05  4e+04  1e+06
28:  1.4050e+06  2.7217e+06  2e+09  7e+05  4e+04  1e+06
29:  1.4091e+06  2.6572e+06  2e+09  5e+06  4e+04  1e+06
30:  1.6232e+06  3.1751e+06  2e+09  7e+06  5e+04  2e+06
31:  1.4920e+06  2.7975e+06  2e+09  7e+06  4e+04  1e+06
32:  1.4601e+06  2.7053e+06  2e+09  7e+06  4e+04  1e+06
33:  1.4821e+06  2.5210e+06  2e+09  7e+06  4e+04  1e+06
34:  1.2872e+06  2.0611e+06  2e+09  6e+06  3e+04  8e+05
35:  1.0578e+06  1.6740e+06  1e+09  4e+06  2e+04  6e+05
36:  8.8749e+05  1.4419e+06  9e+08  2e+06  2e+04  6e+05
37:  8.5568e+05  1.3708e+06  9e+08  2e+06  2e+04  5e+05
38:  8.3081e+05  1.2872e+06  7e+08  2e+06  2e+04  5e+05
39:  7.9605e+05  1.2338e+06  7e+08  1e+06  2e+04  4e+05
40:  8.4066e+05  1.2950e+06  7e+08  1e+06  2e+04  5e+05
41:  8.0924e+05  1.2270e+06  6e+08  1e+06  2e+04  4e+05
42:  7.8398e+05  1.1791e+06  6e+08  9e+05  2e+04  4e+05
43:  8.6142e+05  1.3114e+06  6e+08  6e+05  2e+04  4e+05
44:  7.9760e+05  1.1713e+06  5e+08  5e+05  2e+04  4e+05
45:  1.0354e+06  1.4911e+06  6e+08  4e+05  2e+04  5e+05
46:  8.9185e+05  1.2212e+06  5e+08  3e+05  2e+04  3e+05
47:  8.4288e+05  1.1448e+06  5e+08  3e+05  2e+04  3e+05
48:  7.2704e+05  9.7125e+05  4e+08  3e+05  1e+04  2e+05
49:  6.5246e+05  8.7145e+05  4e+08  2e+05  1e+04  2e+05
50:  6.2542e+05  8.3219e+05  3e+08  2e+05  1e+04  2e+05
51:  5.8260e+05  7.8091e+05  3e+08  2e+05  1e+04  2e+05
52:  5.7354e+05  7.6536e+05  3e+08  2e+05  1e+04  2e+05
53:  5.6313e+05  7.4666e+05  2e+08  2e+05  1e+04  2e+05
54:  5.7419e+05  7.6792e+05  2e+08  2e+05  1e+04  2e+05
55:  5.4018e+05  6.9129e+05  2e+08  2e+05  1e+04  2e+05
56:  5.3573e+05  6.9811e+05  2e+08  4e+05  1e+04  2e+05
57:  4.4393e+05  5.2343e+05  1e+08  2e+05  8e+03  8e+04
58:  3.9541e+05  4.6454e+05  1e+08  2e+05  7e+03  7e+04
59:  3.0426e+05  3.5793e+05  7e+07  1e+05  5e+03  5e+04
60:  2.6895e+05  3.1626e+05  6e+07  1e+05  4e+03  5e+04
61:  2.3756e+05  2.7678e+05  4e+07  9e+04  4e+03  4e+04
62:  2.1585e+05  2.4768e+05  3e+07  1e+05  4e+03  3e+04
63:  1.8901e+05  2.1674e+05  2e+07  1e+05  3e+03  3e+04
64:  1.5122e+05  1.6612e+05  2e+07  1e+06  2e+03  1e+04
65:  1.4484e+05  1.5813e+05  1e+07  1e+06  2e+03  1e+04
66:  1.3844e+05  1.5066e+05  1e+07  1e+06  2e+03  1e+04
67:  1.3374e+05  1.4554e+05  1e+07  1e+06  2e+03  1e+04
68:  1.3280e+05  1.4396e+05  1e+07  7e+05  2e+03  1e+04
69:  1.3370e+05  1.4480e+05  1e+07  6e+05  2e+03  1e+04
70:  1.3076e+05  1.4073e+05  9e+06  5e+05  2e+03  1e+04
71:  1.4915e+05  1.6136e+05  9e+06  4e+05  2e+03  1e+04
72:  1.0138e+05  1.0656e+05  5e+06  4e+05  1e+03  5e+03
73:  7.6771e+04  7.7855e+04  2e+06  4e+05  1e+03  1e+03
74:  4.4844e+04  4.5085e+04  9e+05  2e+05  6e+02  2e+02
75:  1.3936e+04  1.3972e+04  1e+05  7e+04  2e+02  4e+01
76:  1.0789e+04  1.0860e+04  7e+04  5e+04  1e+02  7e+01
77:  8.6633e+03  8.8449e+03  5e+04  4e+04  1e+02  2e+02
78:  4.1464e+03  4.6260e+03  1e+04  2e+04  5e+01  5e+02
79:  2.1695e+03  2.7967e+03  4e+03  7e+03  3e+01  6e+02
80:  1.6795e+03  2.3059e+03  2e+03  5e+03  2e+01  6e+02
81:  1.2859e+03  1.8690e+03  1e+03  3e+03  2e+01  6e+02
82:  9.9216e+02  1.4128e+03  9e+02  2e+03  1e+01  4e+02
83:  7.7053e+02  9.3188e+02  5e+02  1e+03  1e+01  2e+02
84:  7.6994e+02  8.8787e+02  5e+02  1e+03  1e+01  1e+02
85:  7.5863e+02  8.3103e+02  4e+02  9e+02  1e+01  7e+01
86:  7.4180e+02  7.6764e+02  3e+02  6e+02  1e+01  3e+01
87:  7.4245e+02  7.6761e+02  3e+02  6e+02  1e+01  3e+01
88:  7.4385e+02  7.6336e+02  3e+02  6e+02  9e+00  2e+01
89:  7.4920e+02  7.6270e+02  2e+02  6e+02  1e+01  1e+01
90:  7.4941e+02  7.6215e+02  2e+02  6e+02  1e+01  1e+01
91:  7.5402e+02  7.6348e+02  2e+02  6e+02  9e+00  9e+00
92:  7.5762e+02  7.6424e+02  2e+02  6e+02  9e+00  7e+00
93:  7.6103e+02  7.6550e+02  2e+02  5e+02  1e+01  4e+00
94:  7.6086e+02  7.6428e+02  2e+02  5e+02  9e+00  3e+00
95:  7.6243e+02  7.6417e+02  2e+02  5e+02  1e+01  2e+00
96:  7.5774e+02  7.5924e+02  2e+02  2e+03  9e+00  1e+00
97:  7.5174e+02  7.5242e+02  1e+02  2e+03  9e+00  7e-01
98:  7.4654e+02  7.4717e+02  1e+02  2e+03  9e+00  6e-01
99:  7.4261e+02  7.4317e+02  2e+02  2e+03  9e+00  6e-01
100:  7.4022e+02  7.4073e+02  2e+02  2e+03  9e+00  5e-01
Terminated (maximum number of iterations reached).
solver:chol2
     pcost       dcost       gap    pres   dres   k/t
 0:  1.9477e+02  8.3326e+02  4e+03  3e+00  1e+01  1e+00
 1:  2.1671e+04  4.2707e+04  1e+07  1e+02  9e+02  1e+02
 2:  3.2309e+02  9.3319e+02  2e+03  1e+00  1e+01  3e+02
 3:  4.6110e+02  1.2079e+03  4e+03  1e+00  2e+01  4e+02
 4:  9.1507e+02  2.1725e+03  8e+03  1e+00  4e+01  1e+03
 5:  7.0776e+04  1.6523e+05  7e+06  6e+02  3e+03  9e+04
 6:  7.8619e+04  1.8520e+05  8e+06  1e+03  4e+03  1e+05
 7:  3.9389e+05  1.0062e+06  1e+08  5e+04  2e+04  6e+05
 8:  3.7585e+05  9.4053e+05  1e+08  5e+04  2e+04  6e+05
 9:  3.2815e+05  7.3358e+05  8e+07  5e+04  1e+04  4e+05
10:  3.8380e+05  9.2250e+05  1e+08  5e+04  2e+04  5e+05
11:  4.4182e+05  9.2418e+05  1e+08  1e+05  2e+04  5e+05
12:  4.0964e+05  9.3672e+05  2e+08  2e+05  2e+04  5e+05
13:  5.1893e+05  1.2061e+06  2e+08  2e+05  2e+04  7e+05
14:  5.2093e+05  1.1989e+06  3e+08  3e+05  2e+04  7e+05
15:  5.2496e+05  1.1985e+06  3e+08  3e+05  2e+04  7e+05
16:  6.7271e+05  1.4883e+06  4e+08  4e+05  3e+04  8e+05
17:  6.3803e+05  1.3178e+06  5e+08  3e+05  2e+04  7e+05
18:  6.5847e+05  1.3667e+06  5e+08  3e+05  2e+04  7e+05
19:  6.6945e+05  1.3919e+06  6e+08  3e+05  2e+04  7e+05
20:  6.7820e+05  1.4086e+06  6e+08  3e+05  2e+04  7e+05
21:  1.1690e+06  2.5552e+06  1e+09  4e+05  4e+04  1e+06
22:  1.0766e+06  2.2177e+06  1e+09  4e+05  4e+04  1e+06
23:  1.0864e+06  2.1777e+06  1e+09  4e+05  4e+04  1e+06
24:  1.1089e+06  2.2182e+06  1e+09  4e+05  4e+04  1e+06
25:  1.2188e+06  2.4201e+06  1e+09  4e+05  4e+04  1e+06
26:  1.2510e+06  2.4658e+06  1e+09  4e+05  4e+04  1e+06
27:  1.3379e+06  2.6260e+06  2e+09  5e+05  4e+04  1e+06
28:  1.4050e+06  2.7217e+06  2e+09  7e+05  4e+04  1e+06
29:  1.4091e+06  2.6572e+06  2e+09  5e+06  4e+04  1e+06
30:  1.6232e+06  3.1751e+06  2e+09  7e+06  5e+04  2e+06
31:  1.4920e+06  2.7975e+06  2e+09  7e+06  4e+04  1e+06
32:  1.4601e+06  2.7053e+06  2e+09  7e+06  4e+04  1e+06
33:  1.4821e+06  2.5210e+06  2e+09  7e+06  4e+04  1e+06
34:  1.2872e+06  2.0611e+06  2e+09  6e+06  3e+04  8e+05
35:  1.0578e+06  1.6740e+06  1e+09  4e+06  2e+04  6e+05
36:  8.8749e+05  1.4419e+06  9e+08  2e+06  2e+04  6e+05
37:  8.5568e+05  1.3708e+06  9e+08  2e+06  2e+04  5e+05
38:  8.3081e+05  1.2872e+06  7e+08  2e+06  2e+04  5e+05
39:  7.9605e+05  1.2338e+06  7e+08  1e+06  2e+04  4e+05
40:  8.4066e+05  1.2950e+06  7e+08  1e+06  2e+04  5e+05
41:  8.0924e+05  1.2270e+06  6e+08  1e+06  2e+04  4e+05
42:  7.8398e+05  1.1791e+06  6e+08  9e+05  2e+04  4e+05
43:  8.6142e+05  1.3114e+06  6e+08  6e+05  2e+04  4e+05
44:  7.9760e+05  1.1713e+06  5e+08  5e+05  2e+04  4e+05
45:  1.0354e+06  1.4911e+06  6e+08  4e+05  2e+04  5e+05
46:  8.9185e+05  1.2212e+06  5e+08  3e+05  2e+04  3e+05
47:  8.4288e+05  1.1448e+06  5e+08  3e+05  2e+04  3e+05
48:  7.2704e+05  9.7125e+05  4e+08  3e+05  1e+04  2e+05
49:  6.5246e+05  8.7145e+05  4e+08  2e+05  1e+04  2e+05
50:  6.2542e+05  8.3219e+05  3e+08  2e+05  1e+04  2e+05
51:  5.8260e+05  7.8091e+05  3e+08  2e+05  1e+04  2e+05
52:  5.7354e+05  7.6536e+05  3e+08  2e+05  1e+04  2e+05
53:  5.6313e+05  7.4666e+05  2e+08  2e+05  1e+04  2e+05
54:  5.7419e+05  7.6792e+05  2e+08  2e+05  1e+04  2e+05
55:  5.4018e+05  6.9129e+05  2e+08  2e+05  1e+04  2e+05
56:  5.3573e+05  6.9811e+05  2e+08  4e+05  1e+04  2e+05
57:  4.4393e+05  5.2343e+05  1e+08  2e+05  8e+03  8e+04
58:  3.9541e+05  4.6454e+05  1e+08  2e+05  7e+03  7e+04
59:  3.0426e+05  3.5793e+05  7e+07  1e+05  5e+03  5e+04
60:  2.6895e+05  3.1626e+05  6e+07  1e+05  4e+03  5e+04
61:  2.3756e+05  2.7678e+05  4e+07  9e+04  4e+03  4e+04
62:  2.1585e+05  2.4768e+05  3e+07  1e+05  4e+03  3e+04
63:  1.8901e+05  2.1674e+05  2e+07  1e+05  3e+03  3e+04
64:  1.5122e+05  1.6612e+05  2e+07  1e+06  2e+03  1e+04
65:  1.4484e+05  1.5813e+05  1e+07  1e+06  2e+03  1e+04
66:  1.3844e+05  1.5066e+05  1e+07  1e+06  2e+03  1e+04
67:  1.3374e+05  1.4554e+05  1e+07  1e+06  2e+03  1e+04
68:  1.3280e+05  1.4396e+05  1e+07  7e+05  2e+03  1e+04
69:  1.3370e+05  1.4480e+05  1e+07  6e+05  2e+03  1e+04
70:  1.3076e+05  1.4073e+05  9e+06  5e+05  2e+03  1e+04
71:  1.4915e+05  1.6136e+05  9e+06  4e+05  2e+03  1e+04
72:  1.0138e+05  1.0656e+05  5e+06  4e+05  1e+03  5e+03
73:  7.6764e+04  7.7848e+04  2e+06  4e+05  1e+03  1e+03
74:  4.4836e+04  4.5078e+04  9e+05  2e+05  6e+02  2e+02
75:  1.3935e+04  1.3972e+04  1e+05  7e+04  2e+02  4e+01
76:  1.0787e+04  1.0858e+04  7e+04  5e+04  1e+02  7e+01
77:  8.6610e+03  8.8429e+03  5e+04  4e+04  1e+02  2e+02
78:  4.1441e+03  4.6241e+03  1e+04  2e+04  5e+01  5e+02
79:  2.1680e+03  2.7956e+03  4e+03  7e+03  3e+01  6e+02
80:  1.6793e+03  2.3060e+03  2e+03  5e+03  2e+01  6e+02
81:  1.2855e+03  1.8687e+03  1e+03  3e+03  2e+01  6e+02
82:  9.9225e+02  1.4130e+03  9e+02  2e+03  1e+01  4e+02
83:  7.7025e+02  9.3138e+02  5e+02  1e+03  1e+01  2e+02
84:  7.6978e+02  8.8771e+02  5e+02  1e+03  1e+01  1e+02
85:  7.5829e+02  8.3024e+02  4e+02  9e+02  1e+01  7e+01
86:  7.4254e+02  7.6866e+02  3e+02  6e+02  1e+01  3e+01
87:  7.4320e+02  7.6860e+02  3e+02  6e+02  1e+01  3e+01
88:  7.4448e+02  7.6399e+02  3e+02  6e+02  9e+00  2e+01
89:  7.4951e+02  7.6304e+02  2e+02  6e+02  1e+01  1e+01
90:  7.4972e+02  7.6247e+02  2e+02  6e+02  1e+01  1e+01
91:  7.5417e+02  7.6364e+02  2e+02  6e+02  9e+00  9e+00
92:  7.5768e+02  7.6429e+02  2e+02  6e+02  9e+00  7e+00
93:  7.6096e+02  7.6544e+02  2e+02  5e+02  9e+00  4e+00
94:  7.6082e+02  7.6424e+02  2e+02  5e+02  9e+00  3e+00
95:  7.6227e+02  7.6405e+02  2e+02  5e+02  1e+01  2e+00
96:  7.5765e+02  7.5917e+02  2e+02  2e+03  9e+00  2e+00
97:  7.5189e+02  7.5259e+02  1e+02  2e+03  9e+00  7e-01
98:  7.4656e+02  7.4720e+02  1e+02  2e+03  9e+00  6e-01
99:  7.4356e+02  7.4414e+02  2e+02  2e+03  9e+00  6e-01
100:  7.4105e+02  7.4158e+02  2e+02  2e+03  9e+00  5e-01
Terminated (maximum number of iterations reached).

Difference between two solutions: 1.726819e-03
Testing lp.py ...
solver:chol2
     pcost       dcost       gap    pres   dres   k/t
 0: -8.1000e+00 -1.8300e+01  4e+00  0e+00  8e-01  1e+00
 1: -8.2446e+00 -9.9047e+00  3e-01  8e-02  1e-01  6e-02
 2: -7.6587e+00 -8.5347e+00  9e-02  1e+00  5e-02  2e-02
 3: -7.0226e+00 -7.7110e+00  6e-02  1e+01  1e-01  1e-02
 4: -6.4985e+00 -7.0882e+00  5e-02  2e+01  2e-01  9e-03
 5: -5.5876e+00 -6.0350e+00  4e-02  2e+02  3e-01  5e-03
 6: -4.8663e+00 -5.2180e+00  3e-02  3e+02  4e-01  3e-03
 7: -4.1532e+00 -4.4125e+00  2e-02  2e+03  5e-01  2e-03
 8: -3.6054e+00 -3.8041e+00  2e-02  4e+03  6e-01  1e-03
 9: -3.1924e+00 -3.3415e+00  1e-02  2e+04  6e-01  8e-04
10: -2.8113e+00 -2.9258e+00  1e-02  4e+04  7e-01  5e-04
11: -2.5706e+00 -2.6588e+00  8e-03  2e+05  7e-01  4e-04
12: -2.2854e+00 -2.3535e+00  6e-03  4e+05  7e-01  3e-04
13: -2.1174e+00 -2.1709e+00  5e-03  2e+06  8e-01  3e-04
14: -1.9020e+00 -1.9438e+00  4e-03  4e+06  8e-01  2e-04
15: -1.7759e+00 -1.8093e+00  3e-03  2e+07  8e-01  2e-04
16: -1.6170e+00 -1.6435e+00  2e-03  4e+07  8e-01  1e-04
17: -1.5242e+00 -1.5457e+00  2e-03  2e+08  8e-01  1e-04
18: -1.4088e+00 -1.4261e+00  2e-03  4e+08  8e-01  1e-04
19: -1.3438e+00 -1.3581e+00  1e-03  2e+09  8e-01  1e-04
20: -1.2614e+00 -1.2731e+00  1e-03  5e+09  9e-01  8e-05
21: -1.2205e+00 -1.2303e+00  1e-03  2e+10  9e-01  8e-05
22: -1.1641e+00 -1.1723e+00  8e-04  5e+10  9e-01  7e-05
23: -1.1457e+00 -1.1526e+00  7e-04  3e+11  9e-01  6e-05
24: -1.1120e+00 -1.1178e+00  6e-04  6e+11  9e-01  5e-05
25: -1.1175e+00 -1.1225e+00  5e-04  3e+12  9e-01  5e-05
26: -1.1071e+00 -1.1114e+00  4e-04  7e+12  9e-01  5e-05
27: -1.1440e+00 -1.1477e+00  4e-04  3e+13  9e-01  5e-05
28: -1.1644e+00 -1.1676e+00  4e-04  8e+13  9e-01  4e-05
29: -1.2555e+00 -1.2584e+00  3e-04  3e+14  9e-01  4e-05
30: -1.3345e+00 -1.3370e+00  3e-04  1e+15  9e-01  4e-05
31: -1.5684e+00 -1.5705e+00  3e-04  4e+15  8e-01  5e-05
32: -1.8504e+00 -1.8522e+00  3e-04  1e+16  8e-01  5e-05
33: -3.2927e+00 -3.2940e+00  4e-04  5e+16  6e-01  6e-05
34: -7.2895e+00 -7.2897e+00  4e-04  1e+17  2e-01  6e-05
35: -8.2349e+00 -8.2350e+00  2e-04  2e+17  8e-02  3e-05
36: -8.1449e+00 -8.1450e+00  3e-04  3e+18  9e-02  2e-05
37: -8.1562e+00 -8.1563e+00  2e-04  5e+18  9e-02  3e-05
38: -8.5850e+00 -8.5850e+00  2e-04  4e+19  5e-02  1e-05
39: -8.7398e+00 -8.7398e+00  1e-04  7e+19  3e-02  7e-06
40: -8.5796e+00 -8.5796e+00  1e-04  2e+21  5e-02  9e-06
41: -8.5844e+00 -8.5844e+00  9e-05  2e+21  5e-02  1e-05
42: -8.7635e+00 -8.7635e+00  5e-05  1e+22  3e-02  4e-06
43: -8.6210e+00 -8.6210e+00  6e-05  3e+23  4e-02  5e-06
44: -8.6127e+00 -8.6127e+00  4e-05  5e+23  4e-02  6e-06
45: -8.7308e+00 -8.7308e+00  4e-05  4e+24  3e-02  3e-06
46: -8.8323e+00 -8.8323e+00  2e-05  7e+24  2e-02  2e-06
47: -8.7174e+00 -8.7174e+00  3e-05  2e+26  3e-02  2e-06
48: -8.6973e+00 -8.6973e+00  3e-05  2e+26  3e-02  3e-06
49: -8.8058e+00 -8.8058e+00  2e-05  2e+27  2e-02  1e-06
50: -8.8546e+00 -8.8546e+00  1e-05  4e+27  2e-02  9e-07
51: -8.7514e+00 -8.7514e+00  2e-05  1e+29  3e-02  1e-06
52: -8.7405e+00 -8.7405e+00  1e-05  1e+29  3e-02  1e-06
53: -8.8161e+00 -8.8161e+00  1e-05  1e+30  2e-02  7e-07
54: -8.8781e+00 -8.8781e+00  7e-06  2e+30  1e-02  5e-07
55: -8.7917e+00 -8.7917e+00  1e-05  5e+31  2e-02  6e-07
56: -8.7732e+00 -8.7732e+00  7e-06  7e+31  3e-02  8e-07
57: -8.8288e+00 -8.8288e+00  7e-06  7e+32  2e-02  5e-07
58: -8.9006e+00 -8.9006e+00  4e-06  1e+33  1e-02  3e-07
59: -8.8275e+00 -8.8275e+00  6e-06  2e+34  2e-02  3e-07
60: -8.8035e+00 -8.8035e+00  4e-06  3e+34  2e-02  4e-07
61: -8.8360e+00 -8.8360e+00  5e-06  3e+35  2e-02  3e-07
62: -8.9251e+00 -8.9251e+00  1e-06  4e+35  8e-03  1e-07
63: -8.8661e+00 -8.8661e+00  3e-06  8e+36  1e-02  2e-07
64: -8.8364e+00 -8.8364e+00  3e-06  1e+37  2e-02  2e-07
65: -8.8262e+00 -8.8262e+00  4e-06  2e+38  2e-02  2e-07
66: -8.9471e+00 -8.9471e+00  6e-07  2e+38  6e-03  8e-08
67: -8.9304e+00 -8.9304e+00  7e-07  3e+38  8e-03  8e-08
68: -8.8850e+00 -8.8850e+00  1e-06  5e+39  1e-02  9e-08
69: -8.8583e+00 -8.8583e+00  1e-06  1e+40  2e-02  1e-07
70: -8.8071e+00 -8.8071e+00  3e-06  2e+41  2e-02  1e-07
71: -8.9334e+00 -8.9334e+00  6e-07  2e+41  7e-03  1e-07
72: -8.9106e+00 -8.9106e+00  6e-07  3e+41  1e-02  1e-07
73: -8.8518e+00 -8.8518e+00  1e-06  5e+42  2e-02  9e-08
74: -8.8289e+00 -8.8289e+00  9e-07  8e+42  2e-02  1e-07
75: -8.8345e+00 -8.8345e+00  1e-06  1e+44  2e-02  8e-08
76: -8.9464e+00 -8.9464e+00  2e-07  1e+44  6e-03  3e-08
77: -8.9337e+00 -8.9337e+00  2e-07  3e+44  7e-03  3e-08
78: -8.9037e+00 -8.9037e+00  4e-07  4e+45  1e-02  3e-08
79: -8.8830e+00 -8.8830e+00  4e-07  8e+45  1e-02  4e-08
80: -8.8372e+00 -8.8372e+00  8e-07  2e+47  2e-02  4e-08
81: -8.8227e+00 -8.8227e+00  7e-07  2e+47  2e-02  6e-08
82: -8.8756e+00 -8.8756e+00  8e-07  3e+48  1e-02  5e-08
83: -8.9450e+00 -8.9450e+00  2e-07  3e+48  6e-03  2e-08
84: -8.9070e+00 -8.9070e+00  4e-07  5e+49  1e-02  2e-08
85: -8.8860e+00 -8.8860e+00  4e-07  9e+49  1e-02  3e-08
86: -8.8551e+00 -8.8551e+00  9e-07  2e+51  2e-02  4e-08
87: -8.9474e+00 -8.9474e+00  2e-07  1e+51  6e-03  2e-08
88: -8.9284e+00 -8.9284e+00  2e-07  2e+51  8e-03  3e-08
89: -8.8779e+00 -8.8779e+00  5e-07  4e+52  1e-02  3e-08
90: -8.8629e+00 -8.8629e+00  4e-07  7e+52  2e-02  4e-08
91: -8.9035e+00 -8.9035e+00  4e-07  6e+53  1e-02  3e-08
92: -8.9482e+00 -8.9482e+00  2e-07  9e+53  6e-03  1e-08
93: -8.9126e+00 -8.9126e+00  3e-07  2e+55  1e-02  2e-08
94: -8.8957e+00 -8.8957e+00  2e-07  3e+55  1e-02  2e-08
95: -8.8812e+00 -8.8812e+00  5e-07  4e+56  1e-02  2e-08
96: -8.9608e+00 -8.9608e+00  9e-08  4e+56  4e-03  1e-08
97: -8.9479e+00 -8.9479e+00  1e-07  7e+56  6e-03  1e-08
98: -8.9145e+00 -8.9145e+00  2e-07  1e+58  9e-03  1e-08
99: -8.8975e+00 -8.8975e+00  2e-07  2e+58  1e-02  2e-08
100: -8.8768e+00 -8.8768e+00  4e-07  4e+59  1e-02  2e-08
Terminated (maximum number of iterations reached).

status: unknown
optimal value: -8.876807
optimal x: 0.983171
optimal y: 0.988825
optimal multiplier for 1st constraint: 0.979554
optimal multiplier for 2nd constraint: 1.979382
optimal multiplier for 3rd constraint: 0.000000
optimal multiplier for 4th constraint: 0.000000

solver:chol2
     pcost       dcost       gap    pres   dres   k/t
 0: -8.1000e+00 -1.8300e+01  4e+00  0e+00  8e-01  1e+00
 1: -8.2446e+00 -9.9047e+00  3e-01  8e-02  1e-01  6e-02
 2: -7.6587e+00 -8.5347e+00  9e-02  1e+00  5e-02  2e-02
 3: -7.0226e+00 -7.7110e+00  6e-02  1e+01  1e-01  1e-02
 4: -6.4985e+00 -7.0882e+00  5e-02  2e+01  2e-01  9e-03
 5: -5.5876e+00 -6.0350e+00  4e-02  2e+02  3e-01  5e-03
 6: -4.8663e+00 -5.2180e+00  3e-02  3e+02  4e-01  3e-03
 7: -4.1532e+00 -4.4125e+00  2e-02  2e+03  5e-01  2e-03
 8: -3.6054e+00 -3.8041e+00  2e-02  4e+03  6e-01  1e-03
 9: -3.1924e+00 -3.3415e+00  1e-02  2e+04  6e-01  8e-04
10: -2.8113e+00 -2.9258e+00  1e-02  4e+04  7e-01  5e-04
11: -2.5706e+00 -2.6588e+00  8e-03  2e+05  7e-01  4e-04
12: -2.2854e+00 -2.3535e+00  6e-03  4e+05  7e-01  3e-04
13: -2.1174e+00 -2.1709e+00  5e-03  2e+06  8e-01  3e-04
14: -1.9020e+00 -1.9438e+00  4e-03  4e+06  8e-01  2e-04
15: -1.7759e+00 -1.8093e+00  3e-03  2e+07  8e-01  2e-04
16: -1.6170e+00 -1.6435e+00  2e-03  4e+07  8e-01  1e-04
17: -1.5242e+00 -1.5457e+00  2e-03  2e+08  8e-01  1e-04
18: -1.4088e+00 -1.4261e+00  2e-03  4e+08  8e-01  1e-04
19: -1.3438e+00 -1.3581e+00  1e-03  2e+09  8e-01  1e-04
20: -1.2614e+00 -1.2731e+00  1e-03  5e+09  9e-01  8e-05
21: -1.2205e+00 -1.2303e+00  1e-03  2e+10  9e-01  8e-05
22: -1.1641e+00 -1.1723e+00  8e-04  5e+10  9e-01  7e-05
23: -1.1457e+00 -1.1526e+00  7e-04  3e+11  9e-01  6e-05
24: -1.1120e+00 -1.1178e+00  6e-04  6e+11  9e-01  5e-05
25: -1.1175e+00 -1.1225e+00  5e-04  3e+12  9e-01  5e-05
26: -1.1071e+00 -1.1114e+00  4e-04  7e+12  9e-01  5e-05
27: -1.1440e+00 -1.1477e+00  4e-04  3e+13  9e-01  5e-05
28: -1.1644e+00 -1.1676e+00  4e-04  8e+13  9e-01  4e-05
29: -1.2555e+00 -1.2584e+00  3e-04  3e+14  9e-01  4e-05
30: -1.3345e+00 -1.3370e+00  3e-04  1e+15  9e-01  4e-05
31: -1.5684e+00 -1.5705e+00  3e-04  4e+15  8e-01  5e-05
32: -1.8504e+00 -1.8522e+00  3e-04  1e+16  8e-01  5e-05
33: -3.2927e+00 -3.2940e+00  4e-04  5e+16  6e-01  6e-05
34: -7.2895e+00 -7.2897e+00  4e-04  1e+17  2e-01  6e-05
35: -8.2349e+00 -8.2350e+00  2e-04  2e+17  8e-02  3e-05
36: -8.1449e+00 -8.1450e+00  3e-04  3e+18  9e-02  2e-05
37: -8.1562e+00 -8.1563e+00  2e-04  5e+18  9e-02  3e-05
38: -8.5850e+00 -8.5850e+00  2e-04  4e+19  5e-02  1e-05
39: -8.7398e+00 -8.7398e+00  1e-04  7e+19  3e-02  7e-06
40: -8.5796e+00 -8.5796e+00  1e-04  2e+21  5e-02  9e-06
41: -8.5844e+00 -8.5844e+00  9e-05  2e+21  5e-02  1e-05
42: -8.7635e+00 -8.7635e+00  5e-05  1e+22  3e-02  4e-06
43: -8.6210e+00 -8.6210e+00  6e-05  3e+23  4e-02  5e-06
44: -8.6127e+00 -8.6127e+00  4e-05  5e+23  4e-02  6e-06
45: -8.7308e+00 -8.7308e+00  4e-05  4e+24  3e-02  3e-06
46: -8.8323e+00 -8.8323e+00  2e-05  7e+24  2e-02  2e-06
47: -8.7174e+00 -8.7174e+00  3e-05  2e+26  3e-02  2e-06
48: -8.6973e+00 -8.6973e+00  3e-05  2e+26  3e-02  3e-06
49: -8.8058e+00 -8.8058e+00  2e-05  2e+27  2e-02  1e-06
50: -8.8546e+00 -8.8546e+00  1e-05  4e+27  2e-02  9e-07
51: -8.7514e+00 -8.7514e+00  2e-05  1e+29  3e-02  1e-06
52: -8.7405e+00 -8.7405e+00  1e-05  1e+29  3e-02  1e-06
53: -8.8161e+00 -8.8161e+00  1e-05  1e+30  2e-02  7e-07
54: -8.8781e+00 -8.8781e+00  7e-06  2e+30  1e-02  5e-07
55: -8.7917e+00 -8.7917e+00  1e-05  5e+31  2e-02  6e-07
56: -8.7732e+00 -8.7732e+00  7e-06  7e+31  3e-02  8e-07
57: -8.8288e+00 -8.8288e+00  7e-06  7e+32  2e-02  5e-07
58: -8.9006e+00 -8.9006e+00  4e-06  1e+33  1e-02  3e-07
59: -8.8275e+00 -8.8275e+00  6e-06  2e+34  2e-02  3e-07
60: -8.8035e+00 -8.8035e+00  4e-06  3e+34  2e-02  4e-07
61: -8.8360e+00 -8.8360e+00  5e-06  3e+35  2e-02  3e-07
62: -8.9251e+00 -8.9251e+00  1e-06  4e+35  8e-03  1e-07
63: -8.8661e+00 -8.8661e+00  3e-06  8e+36  1e-02  2e-07
64: -8.8364e+00 -8.8364e+00  3e-06  1e+37  2e-02  2e-07
65: -8.8262e+00 -8.8262e+00  4e-06  2e+38  2e-02  2e-07
66: -8.9471e+00 -8.9471e+00  6e-07  2e+38  6e-03  8e-08
67: -8.9304e+00 -8.9304e+00  7e-07  3e+38  8e-03  8e-08
68: -8.8850e+00 -8.8850e+00  1e-06  5e+39  1e-02  9e-08
69: -8.8583e+00 -8.8583e+00  1e-06  1e+40  2e-02  1e-07
70: -8.8071e+00 -8.8071e+00  3e-06  2e+41  2e-02  1e-07
71: -8.9335e+00 -8.9335e+00  6e-07  2e+41  7e-03  1e-07
72: -8.9106e+00 -8.9106e+00  6e-07  3e+41  1e-02  1e-07
73: -8.8518e+00 -8.8518e+00  1e-06  5e+42  2e-02  9e-08
74: -8.8289e+00 -8.8289e+00  9e-07  8e+42  2e-02  1e-07
75: -8.8343e+00 -8.8343e+00  1e-06  1e+44  2e-02  8e-08
76: -8.9463e+00 -8.9463e+00  2e-07  1e+44  6e-03  3e-08
77: -8.9336e+00 -8.9336e+00  2e-07  3e+44  7e-03  3e-08
78: -8.9035e+00 -8.9035e+00  4e-07  4e+45  1e-02  3e-08
79: -8.8828e+00 -8.8828e+00  4e-07  8e+45  1e-02  4e-08
80: -8.8369e+00 -8.8369e+00  8e-07  2e+47  2e-02  4e-08
81: -8.8225e+00 -8.8225e+00  7e-07  2e+47  2e-02  7e-08
82: -8.8762e+00 -8.8762e+00  8e-07  3e+48  1e-02  5e-08
83: -8.9445e+00 -8.9445e+00  2e-07  3e+48  6e-03  2e-08
84: -8.9062e+00 -8.9062e+00  4e-07  5e+49  1e-02  2e-08
85: -8.8852e+00 -8.8852e+00  4e-07  9e+49  1e-02  3e-08
86: -8.8567e+00 -8.8567e+00  9e-07  2e+51  2e-02  4e-08
87: -8.9491e+00 -8.9491e+00  2e-07  1e+51  6e-03  2e-08
88: -8.9309e+00 -8.9309e+00  2e-07  2e+51  8e-03  2e-08
89: -8.8818e+00 -8.8818e+00  5e-07  4e+52  1e-02  3e-08
90: -8.8660e+00 -8.8660e+00  4e-07  7e+52  1e-02  4e-08
91: -8.8989e+00 -8.8989e+00  4e-07  7e+53  1e-02  3e-08
92: -8.9524e+00 -8.9524e+00  1e-07  9e+53  5e-03  1e-08
93: -8.9187e+00 -8.9187e+00  2e-07  1e+55  9e-03  1e-08
94: -8.9004e+00 -8.9004e+00  2e-07  3e+55  1e-02  2e-08
95: -8.8722e+00 -8.8722e+00  5e-07  5e+56  1e-02  2e-08
96: -8.9530e+00 -8.9530e+00  1e-07  4e+56  5e-03  1e-08
97: -8.9359e+00 -8.9359e+00  1e-07  6e+56  7e-03  2e-08
98: -8.8923e+00 -8.8923e+00  3e-07  1e+58  1e-02  2e-08
99: -8.8786e+00 -8.8786e+00  2e-07  2e+58  1e-02  2e-08
100: -8.9075e+00 -8.9075e+00  3e-07  2e+59  1e-02  2e-08
Terminated (maximum number of iterations reached).

status: unknown
optimal value: -8.907507
optimal x: 

[ 9.87e-01]
[ 9.92e-01]

optimal multiplier: 

[ 9.83e-01]
[ 1.99e+00]
[ 9.31e-68]
[ 7.12e-32]

Testing normappr.py ...
solver:chol2
     pcost       dcost       gap    pres   dres   k/t
 0:  2.7283e-18 -3.0526e-18  4e+00  4e+00  7e-16  1e+00
 1:  4.3656e-02  1.6651e+00  4e+01  8e+00  4e+00  3e+00
 2:  1.1346e-01  4.6003e+00  8e+01  9e+00  1e+01  6e+00
 3:  1.1814e-01  4.8418e+00  9e+01  9e+00  1e+01  6e+00
 4:  1.1985e-01  4.3189e+00  8e+01  9e+00  2e+01  5e+00
 5:  2.1206e-01  5.0456e+00  1e+02  1e+01  1e+02  6e+00
 6:  1.0410e-01  1.8553e+00  1e+01  5e+00  2e+01  2e+00
 7:  1.1523e-01  2.2374e+00  2e+01  6e+00  2e+01  3e+00
 8:  1.5709e-01  3.0471e+00  3e+01  8e+00  3e+01  3e+00
 9:  3.5083e-01  5.3368e+00  1e+02  2e+01  6e+01  6e+00
10:  7.0734e-01  1.0724e+01  4e+02  3e+01  1e+02  1e+01
11:  1.4744e+00  2.4373e+01  9e+02  6e+01  2e+02  2e+01
12:  1.3603e+00  2.0292e+01  7e+02  6e+01  2e+02  2e+01
13:  1.8642e+00  4.0784e+01  1e+03  8e+01  4e+02  4e+01
14:  1.8697e+00  4.1692e+01  2e+03  8e+01  3e+02  4e+01
15:  1.2962e+00  1.8015e+01  9e+02  6e+01  4e+02  2e+01
16:  1.0822e+00  8.1429e+01  8e+02  5e+01  9e+02  8e+01
17:  1.6351e+00  9.3758e+01  2e+03  7e+01  8e+02  9e+01
18:  3.0015e+00  1.6223e+02  6e+03  1e+02  1e+03  2e+02
19:  3.9064e+00  2.5220e+02  1e+04  2e+02  2e+03  3e+02
20:  4.7167e+00  2.9213e+02  1e+04  2e+02  2e+03  3e+02
21:  4.6758e+00  2.8055e+02  1e+04  2e+02  2e+03  3e+02
22:  5.1372e+00  3.3104e+02  2e+04  2e+02  3e+03  3e+02
23:  3.8694e+00  1.6817e+02  1e+04  2e+02  5e+03  2e+02
24:  7.8923e+00  5.9695e+02  5e+04  3e+02  2e+04  6e+02
25:  8.1122e+00  5.9720e+02  6e+04  4e+02  2e+04  6e+02
26:  9.5940e+00  7.4592e+02  8e+04  4e+02  3e+04  7e+02
27:  9.2392e+00  6.1067e+02  7e+04  6e+02  2e+04  6e+02
28:  9.1926e+00  4.7873e+02  7e+04  5e+02  2e+04  5e+02
29:  1.0635e+01  5.7376e+02  1e+05  6e+02  2e+04  6e+02
30:  8.2154e+00  1.8383e+03  8e+04  5e+02  3e+04  2e+03
31:  1.1103e+01  2.6771e+03  2e+05  8e+02  5e+04  3e+03
32:  1.7641e+01  4.2653e+03  5e+05  5e+03  8e+04  4e+03
33:  1.7765e+01  3.7103e+03  5e+05  1e+04  7e+04  4e+03
34:  2.0866e+01  4.7228e+03  7e+05  3e+04  9e+04  5e+03
35:  3.0278e+01  7.3137e+03  2e+06  3e+06  1e+05  7e+03
36:  3.2148e+01  7.6734e+03  2e+06  5e+06  1e+05  8e+03
37:  4.6174e+01  1.1640e+04  4e+06  2e+08  2e+05  1e+04
38:  5.5519e+01  1.2094e+04  6e+06  2e+10  2e+05  1e+04
39:  5.9170e+01  1.2725e+04  7e+06  3e+10  2e+05  1e+04
40:  6.3246e+01  1.3662e+04  9e+06  3e+10  3e+05  1e+04
41:  6.5872e+01  1.3991e+04  1e+07  3e+10  3e+05  1e+04
42:  7.5879e+01  1.6088e+04  1e+07  6e+10  3e+05  2e+04
43:  8.0754e+01  1.6957e+04  1e+07  9e+10  3e+05  2e+04
44:  8.2233e+01  1.6973e+04  2e+07  2e+11  3e+05  2e+04
45:  8.6041e+01  1.7044e+04  2e+07  1e+11  3e+05  2e+04
46:  1.0118e+02  2.0031e+04  2e+07  3e+11  4e+05  2e+04
47:  1.0278e+02  1.9935e+04  2e+07  3e+12  4e+05  2e+04
48:  1.0766e+02  2.0614e+04  2e+07  6e+12  4e+05  2e+04
49:  1.1740e+02  2.2200e+04  2e+07  2e+13  4e+05  2e+04
50:  1.1872e+02  2.1795e+04  2e+07  3e+14  4e+05  2e+04
51:  1.4069e+02  2.5771e+04  3e+07  5e+14  5e+05  3e+04
52:  1.4791e+02  2.6736e+04  3e+07  1e+15  5e+05  3e+04
53:  1.5786e+02  2.8471e+04  3e+07  3e+15  6e+05  3e+04
54:  1.5717e+02  2.7858e+04  3e+07  8e+15  6e+05  3e+04
55:  1.5724e+02  2.7563e+04  3e+07  8e+16  5e+05  3e+04
56:  1.5806e+02  2.7246e+04  3e+07  2e+17  5e+05  3e+04
57:  1.5978e+02  2.6835e+04  3e+07  4e+18  5e+05  3e+04
58:  1.9631e+02  3.2880e+04  4e+07  5e+18  7e+05  3e+04
59:  2.0509e+02  3.3390e+04  4e+07  3e+18  7e+05  3e+04
60:  2.3551e+02  3.7267e+04  5e+07  7e+18  8e+05  4e+04
61:  2.3707e+02  3.6674e+04  5e+07  6e+19  8e+05  4e+04
62:  2.3610e+02  3.5694e+04  5e+07  1e+20  8e+05  4e+04
63:  2.4638e+02  3.6669e+04  5e+07  3e+20  8e+05  4e+04
64:  2.4717e+02  3.6110e+04  5e+07  9e+20  8e+05  4e+04
65:  2.4355e+02  3.4671e+04  5e+07  3e+22  8e+05  3e+04
66:  2.5107e+02  3.4958e+04  5e+07  4e+22  8e+05  3e+04
67:  2.6708e+02  3.6582e+04  5e+07  5e+22  9e+05  4e+04
68:  2.6155e+02  3.5353e+04  5e+07  4e+22  8e+05  4e+04
69:  3.1006e+02  4.0512e+04  6e+07  9e+22  1e+06  4e+04
70:  2.9966e+02  3.7843e+04  6e+07  1e+23  9e+05  4e+04
71:  2.9808e+02  3.6853e+04  6e+07  2e+23  9e+05  4e+04
72:  2.8462e+02  3.4223e+04  6e+07  1e+23  9e+05  3e+04
73:  2.9342e+02  3.3022e+04  6e+07  3e+23  9e+05  3e+04
74:  2.7522e+02  2.9109e+04  5e+07  6e+24  8e+05  3e+04
75:  2.6949e+02  2.8048e+04  5e+07  7e+24  8e+05  3e+04
76:  2.5757e+02  2.5771e+04  5e+07  1e+25  8e+05  3e+04
77:  2.5100e+02  2.4735e+04  5e+07  3e+25  8e+05  2e+04
78:  2.3832e+02  2.2689e+04  4e+07  9e+26  7e+05  2e+04
79:  2.2492e+02  2.0555e+04  4e+07  1e+27  7e+05  2e+04
80:  2.1965e+02  1.9037e+04  4e+07  2e+27  6e+05  2e+04
81:  2.0464e+02  1.7109e+04  3e+07  1e+27  6e+05  2e+04
82:  1.9015e+02  1.4566e+04  3e+07  2e+27  6e+05  1e+04
83:  1.7348e+02  1.2353e+04  2e+07  5e+28  5e+05  1e+04
84:  1.6333e+02  1.1121e+04  2e+07  6e+28  5e+05  1e+04
85:  1.5143e+02  8.1735e+03  2e+07  8e+28  4e+05  8e+03
86:  1.0515e+02  4.2515e+03  9e+06  6e+28  3e+05  4e+03
87:  6.2517e+01  1.4309e+03  3e+06  8e+28  2e+05  1e+03
88:  2.2673e+01  3.5062e+02  4e+05  6e+29  6e+04  3e+02
89:  1.7408e+01  2.7113e+02  2e+05  5e+29  5e+04  3e+02
90:  6.5896e+00  1.0405e+02  4e+04  3e+29  2e+04  1e+02
91:  5.4096e+00  1.0050e+02  2e+04  3e+29  1e+04  1e+02
92:  3.5495e+00  6.2382e+01  1e+04  3e+29  1e+04  6e+01
93:  2.7931e+00  5.0819e+01  7e+03  4e+29  7e+03  5e+01
94:  2.8346e+00  6.1595e+01  7e+03  2e+29  7e+03  6e+01
95:  2.0238e+00  3.0599e+01  3e+03  4e+29  5e+03  3e+01
96:  2.1234e+00  3.3760e+01  3e+03  4e+30  6e+03  3e+01
97:  2.1666e+00  3.6910e+01  4e+03  1e+31  6e+03  3e+01
98:  2.4261e+00  4.5744e+01  5e+03  2e+32  6e+03  4e+01
99:  2.1233e+00  3.5735e+01  3e+03  2e+32  6e+03  3e+01
100:  2.3308e+00  4.1526e+01  4e+03  3e+32  6e+03  4e+01
Terminated (maximum number of iterations reached).
solver:chol2
     pcost       dcost       gap    pres   dres   k/t
 0:  0.0000e+00  1.4558e-15  2e+03  4e+00  3e-15  1e+00
 1:  3.0119e+02  3.0372e+02  5e+03  3e+00  3e+00  3e+00
 2:  1.0740e+03  1.0801e+03  8e+03  3e+00  8e+00  6e+00
 3:  1.1024e+03  1.1087e+03  8e+03  4e+00  9e+00  6e+00
 4:  1.3627e+03  1.3713e+03  1e+04  5e+00  1e+01  9e+00
 5:  1.7028e+03  1.7138e+03  1e+04  7e+00  1e+01  1e+01
 6:  3.3272e+03  3.3467e+03  2e+04  5e+01  3e+01  2e+01
 7:  3.3392e+03  3.3588e+03  2e+04  6e+01  3e+01  2e+01
 8:  3.2751e+03  3.2940e+03  2e+04  5e+01  3e+01  2e+01
 9:  3.4354e+03  3.4561e+03  2e+04  6e+01  4e+01  2e+01
10:  3.2885e+03  3.3071e+03  2e+04  3e+02  3e+01  2e+01
11:  3.6993e+03  3.7223e+03  3e+04  7e+02  1e+02  2e+01
12:  3.5638e+03  3.5854e+03  3e+04  2e+03  1e+02  2e+01
13:  3.4908e+03  3.5121e+03  3e+04  3e+03  1e+02  2e+01
14:  3.4127e+03  3.4331e+03  3e+04  4e+03  1e+02  2e+01
15:  3.4225e+03  3.4429e+03  3e+04  8e+03  1e+02  2e+01
16:  3.2956e+03  3.3143e+03  3e+04  8e+03  1e+02  2e+01
17:  3.2435e+03  3.2614e+03  2e+04  8e+03  1e+02  2e+01
18:  3.2522e+03  3.2702e+03  3e+04  8e+03  1e+02  2e+01
19:  3.1921e+03  3.2094e+03  2e+04  8e+03  1e+02  2e+01
20:  3.2044e+03  3.2217e+03  3e+04  7e+03  9e+01  2e+01
21:  3.0822e+03  3.0981e+03  2e+04  7e+03  1e+02  2e+01
22:  2.9956e+03  3.0090e+03  2e+04  6e+03  9e+01  1e+01
23:  2.5004e+03  2.5105e+03  2e+04  4e+03  8e+01  1e+01
24:  2.4095e+03  2.4193e+03  2e+04  4e+03  8e+01  1e+01
25:  2.3725e+03  2.3824e+03  2e+04  4e+03  8e+01  1e+01
26:  2.2476e+03  2.2571e+03  2e+04  3e+03  7e+01  1e+01
27:  2.1135e+03  2.1232e+03  2e+04  3e+03  7e+01  1e+01
28:  1.9136e+03  1.9222e+03  2e+04  3e+03  7e+01  9e+00
29:  1.7632e+03  1.7706e+03  1e+04  3e+03  7e+01  7e+00
30:  1.6682e+03  1.6754e+03  1e+04  2e+03  7e+01  7e+00
31:  1.6329e+03  1.6399e+03  1e+04  2e+03  7e+01  7e+00
32:  1.4866e+03  1.4926e+03  8e+03  2e+03  6e+01  6e+00
33:  1.3847e+03  1.3897e+03  7e+03  2e+03  6e+01  5e+00
34:  1.3792e+03  1.3842e+03  7e+03  2e+03  6e+01  5e+00
35:  1.3821e+03  1.3871e+03  7e+03  2e+03  6e+01  5e+00
36:  1.3580e+03  1.3629e+03  7e+03  2e+03  6e+01  5e+00
37:  1.2850e+03  1.2887e+03  5e+03  1e+03  6e+01  4e+00
38:  1.2632e+03  1.2667e+03  5e+03  2e+03  6e+01  4e+00
39:  1.2494e+03  1.2529e+03  5e+03  2e+03  6e+01  3e+00
40:  1.2342e+03  1.2370e+03  4e+03  2e+03  7e+01  3e+00
41:  1.2179e+03  1.2207e+03  4e+03  3e+03  7e+01  3e+00
42:  1.1950e+03  1.1977e+03  4e+03  3e+03  7e+01  3e+00
43:  1.1692e+03  1.1712e+03  3e+03  4e+03  7e+01  2e+00
44:  1.1428e+03  1.1446e+03  3e+03  6e+03  7e+01  2e+00
45:  1.1234e+03  1.1253e+03  3e+03  7e+03  7e+01  2e+00
46:  1.1334e+03  1.1353e+03  3e+03  7e+03  7e+01  2e+00
47:  1.1034e+03  1.1053e+03  3e+03  7e+03  7e+01  2e+00
48:  1.1174e+03  1.1194e+03  3e+03  8e+03  7e+01  2e+00
49:  1.0806e+03  1.0823e+03  3e+03  1e+04  7e+01  2e+00
50:  1.0927e+03  1.0943e+03  3e+03  1e+04  7e+01  2e+00
51:  1.0801e+03  1.0812e+03  2e+03  2e+04  8e+01  1e+00
52:  1.0723e+03  1.0734e+03  2e+03  4e+04  7e+01  1e+00
53:  1.0408e+03  1.0420e+03  2e+03  7e+04  7e+01  1e+00
54:  1.0326e+03  1.0337e+03  2e+03  7e+04  7e+01  1e+00
55:  1.0211e+03  1.0223e+03  2e+03  7e+04  7e+01  1e+00
56:  1.0044e+03  1.0056e+03  2e+03  7e+04  7e+01  1e+00
57:  9.7888e+02  9.8006e+02  2e+03  7e+04  7e+01  1e+00
58:  9.7130e+02  9.7249e+02  2e+03  7e+04  7e+01  1e+00
59:  9.6842e+02  9.6963e+02  2e+03  7e+04  7e+01  1e+00
60:  9.5679e+02  9.5800e+02  2e+03  7e+04  7e+01  1e+00
61:  9.4425e+02  9.4546e+02  2e+03  6e+04  6e+01  1e+00
62:  9.2585e+02  9.2704e+02  2e+03  6e+04  6e+01  1e+00
63:  9.3031e+02  9.3137e+02  2e+03  6e+04  7e+01  1e+00
64:  9.1397e+02  9.1506e+02  2e+03  6e+04  6e+01  1e+00
65:  9.2168e+02  9.2281e+02  2e+03  6e+04  6e+01  1e+00
66:  9.0883e+02  9.0990e+02  2e+03  6e+04  6e+01  1e+00
67:  9.2208e+02  9.2316e+02  2e+03  7e+04  6e+01  1e+00
68:  9.0515e+02  9.0613e+02  2e+03  7e+04  6e+01  1e+00
69:  9.1335e+02  9.1430e+02  2e+03  8e+04  7e+01  9e-01
70:  8.8599e+02  8.8695e+02  1e+03  8e+04  6e+01  1e+00
71:  8.9688e+02  8.9788e+02  2e+03  8e+04  6e+01  1e+00
72:  8.8824e+02  8.8913e+02  1e+03  9e+04  6e+01  9e-01
73:  9.0167e+02  9.0256e+02  1e+03  1e+05  7e+01  9e-01
74:  8.8236e+02  8.8314e+02  1e+03  1e+05  6e+01  8e-01
75:  8.6491e+02  8.6569e+02  1e+03  1e+05  6e+01  8e-01
76:  8.5212e+02  8.5289e+02  1e+03  1e+05  6e+01  8e-01
77:  8.8624e+02  8.8677e+02  9e+02  2e+05  7e+01  5e-01
78:  8.7199e+02  8.7257e+02  1e+03  3e+05  7e+01  6e-01
79:  8.6452e+02  8.6507e+02  9e+02  3e+05  7e+01  6e-01
80:  8.1861e+02  8.1924e+02  9e+02  3e+05  6e+01  6e-01
81:  8.1663e+02  8.1727e+02  9e+02  3e+05  6e+01  6e-01
82:  8.1447e+02  8.1510e+02  9e+02  3e+05  6e+01  6e-01
83:  8.0941e+02  8.1008e+02  1e+03  3e+05  6e+01  7e-01
84:  7.7504e+02  7.7566e+02  9e+02  3e+05  6e+01  6e-01
85:  7.6355e+02  7.6413e+02  9e+02  3e+05  6e+01  6e-01
86:  7.5094e+02  7.5151e+02  9e+02  3e+05  6e+01  6e-01
87:  7.3890e+02  7.3943e+02  8e+02  3e+05  6e+01  5e-01
88:  7.5386e+02  7.5428e+02  7e+02  3e+05  6e+01  4e-01
89:  7.4867e+02  7.4909e+02  7e+02  3e+05  6e+01  4e-01
90:  7.4951e+02  7.4994e+02  7e+02  3e+05  6e+01  4e-01
91:  7.4212e+02  7.4255e+02  7e+02  3e+05  6e+01  4e-01
92:  7.4461e+02  7.4505e+02  7e+02  3e+05  6e+01  4e-01
93:  7.3410e+02  7.3453e+02  7e+02  3e+05  6e+01  4e-01
94:  7.3910e+02  7.3951e+02  7e+02  4e+05  6e+01  4e-01
95:  7.2736e+02  7.2778e+02  7e+02  4e+05  6e+01  4e-01
96:  7.2532e+02  7.2574e+02  7e+02  4e+05  6e+01  4e-01
97:  7.1987e+02  7.2024e+02  6e+02  4e+05  6e+01  4e-01
98:  7.1436e+02  7.1472e+02  6e+02  5e+05  6e+01  4e-01
99:  7.0127e+02  7.0163e+02  6e+02  5e+05  6e+01  4e-01
100:  6.8361e+02  6.8397e+02  6e+02  6e+05  6e+01  4e-01
Terminated (maximum number of iterations reached).
solver:chol2
     pcost       dcost       gap    pres   dres   k/t
 0: -6.0000e+02 -6.0000e+02  3e+03  3e+00  5e-15  1e+00
 1: -4.6937e+04 -4.6857e+04  6e+06  1e+02  8e+01  1e+02
 2: -4.5501e+06 -4.5159e+06  5e+10  1e+04  8e+03  4e+04
 3: -4.3673e+04 -3.9246e+04  2e+06  7e+01  8e+01  4e+03
 4: -4.4452e+04 -3.9802e+04  2e+06  7e+01  9e+01  5e+03
 5: -5.2367e+04 -4.5149e+04  2e+06  8e+01  1e+02  7e+03
 6: -1.1401e+05 -8.4581e+04  8e+06  2e+02  5e+02  3e+04
 7: -1.1051e+05 -7.9331e+04  8e+06  4e+02  5e+02  3e+04
 8: -1.1097e+05 -7.7391e+04  8e+06  2e+04  5e+02  3e+04
 9: -1.2690e+05 -7.3045e+04  1e+07  4e+04  1e+03  5e+04
10: -1.2692e+05 -6.7989e+04  1e+07  5e+05  1e+03  6e+04
11: -1.2709e+05 -6.4683e+04  1e+07  9e+05  1e+03  6e+04
12: -1.6086e+05 -6.0256e+04  3e+07  3e+06  2e+03  1e+05
13: -1.7040e+05 -6.0476e+04  4e+07  6e+06  2e+03  1e+05
14: -1.9853e+05 -7.0259e+04  7e+07  1e+07  2e+03  1e+05
15: -2.8726e+05 -8.7729e+04  2e+08  3e+07  4e+03  2e+05
16: -3.0286e+05 -9.6870e+04  2e+08  3e+07  4e+03  2e+05
17: -3.6108e+05 -1.2413e+05  3e+08  4e+07  5e+03  2e+05
18: -5.5738e+05 -1.9631e+05  7e+08  1e+08  1e+04  4e+05
19: -5.6579e+05 -1.9863e+05  7e+08  1e+08  1e+04  4e+05
20: -5.7782e+05 -2.0215e+05  8e+08  2e+08  1e+04  4e+05
21: -6.1483e+05 -2.1575e+05  9e+08  2e+08  1e+04  4e+05
22: -6.4976e+05 -2.3035e+05  1e+09  2e+08  1e+04  4e+05
23: -6.5728e+05 -2.3238e+05  1e+09  2e+08  1e+04  4e+05
24: -7.2197e+05 -2.5836e+05  1e+09  3e+08  1e+04  5e+05
25: -7.2798e+05 -2.5878e+05  1e+09  3e+08  1e+04  5e+05
26: -7.4930e+05 -2.7208e+05  1e+09  3e+08  1e+04  5e+05
27: -7.4629e+05 -2.7718e+05  1e+09  3e+08  1e+04  5e+05
28: -8.9412e+05 -3.3517e+05  2e+09  4e+08  2e+04  6e+05
29: -8.8790e+05 -3.3537e+05  2e+09  4e+08  2e+04  6e+05
30: -8.9454e+05 -3.4129e+05  2e+09  4e+08  3e+04  6e+05
31: -9.3586e+05 -3.6106e+05  2e+09  5e+08  4e+04  6e+05
32: -9.8116e+05 -3.8152e+05  2e+09  5e+08  4e+04  6e+05
33: -9.5163e+05 -3.8237e+05  2e+09  5e+08  4e+04  6e+05
34: -9.4547e+05 -3.9667e+05  2e+09  5e+08  5e+04  5e+05
35: -8.5582e+05 -3.7561e+05  2e+09  5e+08  4e+04  5e+05
36: -1.1084e+06 -5.6729e+05  2e+09  9e+08  8e+04  5e+05
37: -9.8636e+05 -5.4872e+05  2e+09  8e+08  6e+04  4e+05
38: -8.4170e+05 -5.6107e+05  1e+09  8e+08  6e+04  3e+05
39: -4.8168e+05 -3.9182e+05  5e+08  5e+08  3e+04  9e+04
40: -1.1994e+05 -1.1972e+05  3e+07  1e+08  9e+03  2e+02
41: -2.7971e+04 -2.5267e+04  2e+06  3e+07  2e+03  3e+03
42: -2.6554e+04 -2.3887e+04  2e+06  3e+07  2e+03  3e+03
43: -2.2627e+04 -2.0184e+04  1e+06  2e+07  2e+03  2e+03
44: -2.1462e+04 -1.9073e+04  1e+06  2e+07  2e+03  2e+03
45: -1.8644e+04 -1.6493e+04  9e+05  2e+07  1e+03  2e+03
46: -1.7275e+04 -1.5241e+04  7e+05  1e+07  1e+03  2e+03
47: -1.2480e+04 -1.1279e+04  3e+05  1e+07  1e+03  1e+03
48: -1.1269e+04 -1.0173e+04  3e+05  9e+06  1e+03  1e+03
49: -9.2116e+03 -8.4223e+03  2e+05  7e+06  8e+02  8e+02
50: -9.3143e+03 -8.5014e+03  2e+05  7e+06  8e+02  8e+02
51: -9.5460e+03 -8.6815e+03  2e+05  7e+06  9e+02  9e+02
52: -7.5024e+03 -6.9215e+03  1e+05  6e+06  7e+02  6e+02
53: -6.6969e+03 -6.1884e+03  9e+04  5e+06  6e+02  5e+02
54: -6.0194e+03 -5.5815e+03  7e+04  5e+06  6e+02  4e+02
55: -5.3693e+03 -4.9984e+03  6e+04  4e+06  6e+02  4e+02
56: -4.7779e+03 -4.4586e+03  5e+04  3e+06  5e+02  3e+02
57: -3.8667e+03 -3.6250e+03  3e+04  2e+06  5e+02  2e+02
58: -3.3263e+03 -3.1448e+03  3e+04  2e+06  4e+02  2e+02
59: -3.3160e+03 -3.1349e+03  3e+04  2e+06  4e+02  2e+02
60: -3.2878e+03 -3.1085e+03  3e+04  2e+06  4e+02  2e+02
61: -3.2812e+03 -3.1026e+03  3e+04  2e+06  4e+02  2e+02
62: -3.2819e+03 -3.1044e+03  3e+04  2e+06  4e+02  2e+02
63: -3.3661e+03 -3.1817e+03  3e+04  2e+06  4e+02  2e+02
64: -3.1974e+03 -3.0365e+03  3e+04  3e+06  4e+02  2e+02
65: -3.5494e+03 -3.3632e+03  4e+04  4e+06  5e+02  2e+02
66: -3.7413e+03 -3.5366e+03  4e+04  4e+06  5e+02  2e+02
67: -3.8404e+03 -3.6254e+03  5e+04  4e+06  5e+02  2e+02
68: -4.0132e+03 -3.7798e+03  5e+04  5e+06  6e+02  2e+02
69: -4.0475e+03 -3.8093e+03  6e+04  5e+06  6e+02  2e+02
70: -4.0773e+03 -3.8349e+03  6e+04  5e+06  6e+02  2e+02
71: -4.0742e+03 -3.8318e+03  6e+04  5e+06  6e+02  2e+02
72: -4.0054e+03 -3.7711e+03  6e+04  5e+06  6e+02  2e+02
73: -3.9129e+03 -3.6867e+03  6e+04  5e+06  6e+02  2e+02
74: -3.7735e+03 -3.5610e+03  6e+04  5e+06  5e+02  2e+02
75: -3.7128e+03 -3.5064e+03  6e+04  5e+06  5e+02  2e+02
76: -3.3122e+03 -3.1492e+03  5e+04  5e+06  5e+02  2e+02
77: -3.1277e+03 -2.9850e+03  5e+04  5e+06  5e+02  1e+02
78: -2.6150e+03 -2.5298e+03  3e+04  6e+06  4e+02  9e+01
79: -2.5254e+03 -2.4548e+03  3e+04  7e+06  4e+02  7e+01
80: -2.5048e+03 -2.4372e+03  3e+04  7e+06  4e+02  7e+01
81: -2.4773e+03 -2.4144e+03  3e+04  7e+06  4e+02  6e+01
82: -2.4601e+03 -2.4007e+03  3e+04  7e+06  4e+02  6e+01
83: -2.4459e+03 -2.3938e+03  3e+04  8e+06  4e+02  5e+01
84: -2.4663e+03 -2.4182e+03  4e+04  9e+06  4e+02  5e+01
85: -2.6915e+03 -2.6472e+03  4e+04  1e+07  5e+02  4e+01
86: -2.8666e+03 -2.8188e+03  5e+04  1e+07  5e+02  5e+01
87: -2.8340e+03 -2.7877e+03  5e+04  1e+07  5e+02  5e+01
88: -2.7438e+03 -2.7048e+03  5e+04  1e+07  5e+02  4e+01
89: -2.5726e+03 -2.5398e+03  5e+04  1e+07  5e+02  3e+01
90: -3.0533e+03 -3.0101e+03  7e+04  1e+07  6e+02  4e+01
91: -2.9341e+03 -2.8933e+03  7e+04  1e+07  6e+02  4e+01
92: -2.2193e+03 -2.1995e+03  5e+04  9e+06  4e+02  2e+01
93: -2.0622e+03 -2.0450e+03  4e+04  8e+06  4e+02  2e+01
94: -1.9746e+03 -1.9586e+03  4e+04  7e+06  4e+02  2e+01
95: -1.9533e+03 -1.9376e+03  4e+04  7e+06  4e+02  2e+01
96: -1.8268e+03 -1.8133e+03  4e+04  7e+06  4e+02  1e+01
97: -1.8089e+03 -1.7956e+03  4e+04  7e+06  4e+02  1e+01
98: -1.6596e+03 -1.6490e+03  3e+04  7e+06  4e+02  1e+01
99: -1.6323e+03 -1.6220e+03  3e+04  7e+06  4e+02  1e+01
100: -1.5146e+03 -1.5064e+03  3e+04  8e+06  4e+02  8e+00
Terminated (maximum number of iterations reached).
Testing roblp.py ...
solver:chol2
     pcost       dcost       gap    pres   dres   k/t
 0:  6.4689e-02 -2.5969e+02  1e+03  3e+00  5e+02  1e+00
 1: -7.4543e-02 -1.3742e+02  6e+02  2e+00  4e+02  1e+01
 2: -5.1016e-02 -2.3269e+01  3e+01  3e-01  9e+01  9e+00
 3: -6.6962e-02 -1.6294e+01  2e+01  3e-01  7e+01  6e+00
 4: -6.8501e-02 -1.0314e+01  9e+00  5e-01  5e+01  3e+00
 5: -6.7752e-02 -6.5583e+00  5e+00  7e-01  4e+01  2e+00
 6: -6.7114e-02 -5.4254e+00  5e+00  5e-01  3e+01  2e+00
 7: -5.3948e-02 -3.9727e+00  3e+00  5e-01  2e+01  1e+00
 8: -5.0431e-02 -3.6476e+00  3e+00  6e-01  2e+01  1e+00
 9: -4.5741e-02 -2.9531e+00  3e+00  6e-01  2e+01  8e-01
10: -4.1919e-02 -2.3521e+00  2e+00  6e-01  1e+01  6e-01
11: -3.8736e-02 -2.1538e+00  2e+00  5e-01  1e+01  4e-01
12: -3.6823e-02 -2.0890e+00  2e+00  5e-01  1e+01  4e-01
13: -3.6818e-02 -1.9774e+00  2e+00  5e-01  1e+01  3e-01
14: -3.5527e-02 -1.8736e+00  1e+00  5e-01  9e+00  3e-01
15: -3.2271e-02 -1.5725e+00  1e+00  5e-01  8e+00  2e-01
16: -2.6178e-02 -1.2475e+00  1e+00  6e-01  6e+00  1e-01
17: -2.2123e-02 -8.5096e-01  8e-01  5e-01  4e+00  6e-02
18: -1.8460e-02 -5.4317e-01  5e-01  5e-01  3e+00  3e-02
19: -1.6418e-02 -4.3774e-01  4e-01  5e-01  2e+00  2e-02
20: -1.3166e-02 -2.6326e-01  2e-01  4e-01  2e+00  1e-02
21: -1.1239e-02 -1.8785e-01  1e-01  4e-01  1e+00  1e-02
22: -9.7261e-03 -1.5031e-01  1e-01  4e-01  1e+00  9e-03
23: -8.1065e-03 -1.0740e-01  9e-02  4e-01  1e+00  6e-03
24: -7.3111e-03 -9.1272e-02  8e-02  4e-01  1e+00  6e-03
25: -6.5382e-03 -7.6890e-02  7e-02  4e-01  1e+00  5e-03
26: -4.9009e-03 -5.0176e-02  4e-02  5e-01  1e+00  3e-03
27: -3.7667e-03 -3.4545e-02  3e-02  4e-01  1e+00  2e-03
28: -3.5807e-03 -3.3019e-02  3e-02  4e-01  1e+00  2e-03
29: -2.9508e-03 -2.4282e-02  2e-02  3e-01  1e+00  1e-03
30: -2.7718e-03 -2.2106e-02  2e-02  3e-01  1e+00  1e-03
31: -2.2758e-03 -1.4550e-02  1e-02  3e-01  1e+00  7e-04
32: -1.8336e-03 -1.0147e-02  7e-03  3e-01  1e+00  5e-04
33: -1.6014e-03 -8.0852e-03  6e-03  3e-01  1e+00  4e-04
34: -1.5984e-03 -8.0708e-03  6e-03  3e-01  1e+00  4e-04
35: -1.4259e-03 -6.5851e-03  5e-03  3e-01  1e+00  3e-04
36: -1.2168e-03 -4.6092e-03  3e-03  4e-01  1e+00  2e-04
37: -1.1591e-03 -4.3351e-03  3e-03  4e-01  1e+00  2e-04
38: -1.1843e-03 -4.5038e-03  3e-03  3e-01  1e+00  2e-04
39: -1.1597e-03 -4.3183e-03  3e-03  3e-01  1e+00  2e-04
40: -1.1217e-03 -4.0327e-03  3e-03  3e-01  1e+00  2e-04
41: -1.0462e-03 -3.5785e-03  2e-03  3e-01  1e+00  1e-04
42: -9.1678e-04 -2.7685e-03  2e-03  4e-01  1e+00  8e-05
43: -8.6520e-04 -2.5220e-03  1e-03  4e-01  9e-01  6e-05
44: -8.1183e-04 -2.2701e-03  1e-03  4e-01  9e-01  5e-05
45: -7.9508e-04 -2.1691e-03  9e-04  4e-01  9e-01  4e-05
46: -7.2379e-04 -1.8452e-03  7e-04  5e-01  9e-01  3e-05
47: -6.6384e-04 -1.5608e-03  6e-04  5e-01  9e-01  2e-05
48: -6.3890e-04 -1.3844e-03  5e-04  5e-01  9e-01  1e-05
49: -6.3249e-04 -1.3070e-03  5e-04  5e-01  9e-01  8e-06
50: -6.4713e-04 -1.3630e-03  6e-04  5e-01  9e-01  8e-06
51: -6.5600e-04 -1.3942e-03  6e-04  5e-01  9e-01  8e-06
52: -6.8158e-04 -1.4059e-03  6e-04  5e-01  9e-01  8e-06
53: -6.7407e-04 -1.4011e-03  6e-04  4e-01  9e-01  7e-06
54: -6.3421e-04 -1.2893e-03  5e-04  5e-01  9e-01  6e-06
55: -7.9492e-04 -1.3911e-03  7e-04  4e-01  9e-01  3e-06
56: -8.7825e-04 -1.4965e-03  9e-04  4e-01  1e+00  2e-06
57: -1.2175e-03 -1.7296e-03  1e-03  3e-01  1e+00  2e-06
58: -1.5849e-03 -2.0418e-03  1e-03  3e-01  1e+00  2e-06
59: -1.5891e-03 -1.9713e-03  1e-03  4e-01  1e+00  1e-06
60: -1.6960e-03 -2.0290e-03  1e-03  4e-01  1e+00  1e-06
61: -1.7330e-03 -2.0644e-03  1e-03  4e-01  1e+00  1e-06
62: -1.7312e-03 -2.0611e-03  1e-03  4e-01  1e+00  1e-06
63: -2.3860e-03 -2.6339e-03  1e-03  4e-01  1e+00  1e-06
64: -2.6873e-03 -2.9201e-03  1e-03  4e-01  1e+00  1e-06
65: -2.8487e-03 -3.0902e-03  1e-03  4e-01  1e+00  1e-06
66: -2.8624e-03 -3.0986e-03  1e-03  4e-01  2e+00  1e-06
67: -2.9968e-03 -3.2307e-03  1e-03  4e-01  2e+00  1e-06
68: -2.9981e-03 -3.2271e-03  1e-03  4e-01  2e+00  1e-06
69: -2.8604e-03 -3.0765e-03  1e-03  4e-01  2e+00  1e-06
70: -3.7727e-03 -3.9728e-03  1e-03  4e-01  2e+00  2e-06
71: -4.3321e-03 -4.5298e-03  2e-03  4e-01  2e+00  2e-06
72: -5.6575e-03 -5.8275e-03  2e-03  3e-01  3e+00  2e-06
73: -5.8794e-03 -6.0538e-03  2e-03  9e-01  3e+00  2e-06
74: -6.1329e-03 -6.3069e-03  2e-03  1e+00  3e+00  2e-06
75: -6.0812e-03 -6.2515e-03  2e-03  9e-01  3e+00  2e-06
76: -5.9876e-03 -6.1545e-03  2e-03  9e-01  3e+00  2e-06
77: -6.2715e-03 -6.4283e-03  2e-03  1e+00  3e+00  2e-06
78: -6.3596e-03 -6.5181e-03  2e-03  8e-01  3e+00  2e-06
79: -6.3673e-03 -6.5251e-03  3e-03  8e-01  3e+00  2e-06
80: -6.1084e-03 -6.2579e-03  3e-03  6e-01  3e+00  2e-06
81: -6.8495e-03 -6.9980e-03  4e-03  6e-01  4e+00  2e-06
82: -8.6311e-03 -8.7670e-03  5e-03  9e-01  5e+00  4e-06
83: -8.6106e-03 -8.7461e-03  5e-03  9e-01  5e+00  4e-06
84: -8.6144e-03 -8.7499e-03  5e-03  9e-01  5e+00  4e-06
85: -8.8242e-03 -8.9629e-03  6e-03  1e+00  5e+00  4e-06
86: -8.6739e-03 -8.8074e-03  6e-03  2e+00  5e+00  4e-06
87: -8.2531e-03 -8.3778e-03  6e-03  2e+00  5e+00  4e-06
88: -8.0186e-03 -8.1394e-03  6e-03  2e+00  5e+00  4e-06
89: -8.1079e-03 -8.2170e-03  7e-03  3e+00  5e+00  5e-06
90: -9.1148e-03 -9.2075e-03  1e-02  3e+00  6e+00  7e-06
91: -9.4499e-03 -9.5373e-03  1e-02  3e+00  7e+00  8e-06
92: -1.1146e-02 -1.1222e-02  2e-02  3e+00  8e+00  9e-06
93: -1.1569e-02 -1.1644e-02  2e-02  3e+00  9e+00  1e-05
94: -1.2588e-02 -1.2661e-02  2e-02  3e+00  1e+01  1e-05
95: -1.3313e-02 -1.3386e-02  2e-02  3e+00  1e+01  2e-05
96: -1.7712e-02 -1.7750e-02  3e-02  7e+00  1e+01  2e-05
97: -1.6085e-02 -1.6108e-02  2e-02  6e+00  1e+01  2e-05
98: -1.7586e-02 -1.7602e-02  2e-02  8e+00  1e+01  2e-05
99: -1.6197e-02 -1.6213e-02  2e-02  7e+00  1e+01  2e-05
100: -1.7087e-02 -1.7102e-02  2e-02  1e+01  1e+01  2e-05
Terminated (maximum number of iterations reached).
solver:chol2
     pcost       dcost       gap    pres   dres   k/t
 0:  6.4689e-02 -2.5969e+02  1e+03  3e+00  5e+02  1e+00
 1: -7.4543e-02 -1.3742e+02  6e+02  2e+00  4e+02  1e+01
 2: -5.1016e-02 -2.3269e+01  3e+01  3e-01  9e+01  9e+00
 3: -6.6962e-02 -1.6294e+01  2e+01  3e-01  7e+01  6e+00
 4: -6.8501e-02 -1.0314e+01  9e+00  5e-01  5e+01  3e+00
 5: -6.7752e-02 -6.5583e+00  5e+00  7e-01  4e+01  2e+00
 6: -6.7114e-02 -5.4254e+00  5e+00  5e-01  3e+01  2e+00
 7: -5.3948e-02 -3.9727e+00  3e+00  5e-01  2e+01  1e+00
 8: -5.0431e-02 -3.6476e+00  3e+00  6e-01  2e+01  1e+00
 9: -4.5741e-02 -2.9531e+00  3e+00  6e-01  2e+01  8e-01
10: -4.1919e-02 -2.3521e+00  2e+00  6e-01  1e+01  6e-01
11: -3.8736e-02 -2.1538e+00  2e+00  5e-01  1e+01  4e-01
12: -3.6823e-02 -2.0890e+00  2e+00  5e-01  1e+01  4e-01
13: -3.6818e-02 -1.9774e+00  2e+00  5e-01  1e+01  3e-01
14: -3.5527e-02 -1.8736e+00  1e+00  5e-01  9e+00  3e-01
15: -3.2271e-02 -1.5725e+00  1e+00  5e-01  8e+00  2e-01
16: -2.6178e-02 -1.2475e+00  1e+00  6e-01  6e+00  1e-01
17: -2.2123e-02 -8.5096e-01  8e-01  5e-01  4e+00  6e-02
18: -1.8460e-02 -5.4317e-01  5e-01  5e-01  3e+00  3e-02
19: -1.6418e-02 -4.3774e-01  4e-01  5e-01  2e+00  2e-02
20: -1.3166e-02 -2.6326e-01  2e-01  4e-01  2e+00  1e-02
21: -1.1239e-02 -1.8785e-01  1e-01  4e-01  1e+00  1e-02
22: -9.7261e-03 -1.5031e-01  1e-01  4e-01  1e+00  9e-03
23: -8.1065e-03 -1.0740e-01  9e-02  4e-01  1e+00  6e-03
24: -7.3111e-03 -9.1272e-02  8e-02  4e-01  1e+00  6e-03
25: -6.5382e-03 -7.6890e-02  7e-02  4e-01  1e+00  5e-03
26: -4.9009e-03 -5.0176e-02  4e-02  5e-01  1e+00  3e-03
27: -3.7667e-03 -3.4545e-02  3e-02  4e-01  1e+00  2e-03
28: -3.5807e-03 -3.3019e-02  3e-02  4e-01  1e+00  2e-03
29: -2.9508e-03 -2.4282e-02  2e-02  3e-01  1e+00  1e-03
30: -2.7718e-03 -2.2106e-02  2e-02  3e-01  1e+00  1e-03
31: -2.2758e-03 -1.4550e-02  1e-02  3e-01  1e+00  7e-04
32: -1.8336e-03 -1.0147e-02  7e-03  3e-01  1e+00  5e-04
33: -1.6014e-03 -8.0852e-03  6e-03  3e-01  1e+00  4e-04
34: -1.5984e-03 -8.0708e-03  6e-03  3e-01  1e+00  4e-04
35: -1.4259e-03 -6.5851e-03  5e-03  3e-01  1e+00  3e-04
36: -1.2168e-03 -4.6092e-03  3e-03  4e-01  1e+00  2e-04
37: -1.1591e-03 -4.3351e-03  3e-03  4e-01  1e+00  2e-04
38: -1.1843e-03 -4.5038e-03  3e-03  3e-01  1e+00  2e-04
39: -1.1597e-03 -4.3183e-03  3e-03  3e-01  1e+00  2e-04
40: -1.1217e-03 -4.0327e-03  3e-03  3e-01  1e+00  2e-04
41: -1.0462e-03 -3.5785e-03  2e-03  3e-01  1e+00  1e-04
42: -9.1678e-04 -2.7685e-03  2e-03  4e-01  1e+00  8e-05
43: -8.6520e-04 -2.5220e-03  1e-03  4e-01  9e-01  6e-05
44: -8.1183e-04 -2.2701e-03  1e-03  4e-01  9e-01  5e-05
45: -7.9508e-04 -2.1691e-03  9e-04  4e-01  9e-01  4e-05
46: -7.2379e-04 -1.8452e-03  7e-04  5e-01  9e-01  3e-05
47: -6.6384e-04 -1.5608e-03  6e-04  5e-01  9e-01  2e-05
48: -6.3890e-04 -1.3844e-03  5e-04  5e-01  9e-01  1e-05
49: -6.3249e-04 -1.3070e-03  5e-04  5e-01  9e-01  8e-06
50: -6.4713e-04 -1.3630e-03  6e-04  5e-01  9e-01  8e-06
51: -6.5600e-04 -1.3942e-03  6e-04  5e-01  9e-01  8e-06
52: -6.8158e-04 -1.4059e-03  6e-04  5e-01  9e-01  8e-06
53: -6.7407e-04 -1.4011e-03  6e-04  4e-01  9e-01  7e-06
54: -6.3421e-04 -1.2893e-03  5e-04  5e-01  9e-01  6e-06
55: -7.9492e-04 -1.3911e-03  7e-04  4e-01  9e-01  3e-06
56: -8.7818e-04 -1.4965e-03  9e-04  4e-01  1e+00  2e-06
57: -1.2177e-03 -1.7298e-03  1e-03  3e-01  1e+00  2e-06
58: -1.5858e-03 -2.0427e-03  1e-03  3e-01  1e+00  2e-06
59: -1.5904e-03 -1.9725e-03  1e-03  4e-01  1e+00  1e-06
60: -1.6976e-03 -2.0306e-03  1e-03  4e-01  1e+00  1e-06
61: -1.7328e-03 -2.0642e-03  1e-03  4e-01  1e+00  1e-06
62: -1.7310e-03 -2.0609e-03  1e-03  4e-01  1e+00  1e-06
63: -2.3889e-03 -2.6372e-03  1e-03  4e-01  1e+00  1e-06
64: -2.7020e-03 -2.9345e-03  1e-03  4e-01  1e+00  1e-06
65: -2.8650e-03 -3.1062e-03  1e-03  4e-01  1e+00  1e-06
66: -2.8759e-03 -3.1118e-03  1e-03  4e-01  2e+00  1e-06
67: -3.0097e-03 -3.2434e-03  1e-03  4e-01  2e+00  1e-06
68: -3.0113e-03 -3.2401e-03  1e-03  4e-01  2e+00  1e-06
69: -2.8686e-03 -3.0841e-03  1e-03  4e-01  2e+00  1e-06
70: -3.7728e-03 -3.9736e-03  1e-03  4e-01  2e+00  2e-06
71: -4.3818e-03 -4.5785e-03  2e-03  4e-01  2e+00  2e-06
72: -8.3938e-03 -8.5047e-03  2e-03  4e-01  4e+00  2e-06
73: -8.4214e-03 -8.5283e-03  2e-03  3e-01  4e+00  2e-06
74: -8.3363e-03 -8.4395e-03  2e-03  3e-01  4e+00  2e-06
75: -7.7416e-03 -7.8362e-03  2e-03  3e-01  4e+00  2e-06
76: -7.8626e-03 -7.9569e-03  2e-03  3e-01  4e+00  2e-06
77: -8.0288e-03 -8.1222e-03  3e-03  3e-01  4e+00  2e-06
78: -8.0399e-03 -8.1334e-03  3e-03  3e-01  4e+00  2e-06
79: -8.0063e-03 -8.0993e-03  3e-03  3e-01  4e+00  2e-06
80: -7.9714e-03 -8.0636e-03  3e-03  2e-01  4e+00  2e-06
81: -7.5381e-03 -7.6212e-03  4e-03  3e-01  4e+00  2e-06
82: -7.9879e-03 -8.0654e-03  5e-03  2e-01  4e+00  3e-06
83: -9.6597e-03 -9.7285e-03  6e-03  3e-01  5e+00  4e-06
84: -1.1028e-02 -1.1094e-02  8e-03  4e-01  6e+00  6e-06
85: -1.4248e-02 -1.4299e-02  9e-03  6e-01  7e+00  6e-06
86: -1.4623e-02 -1.4672e-02  9e-03  9e-01  8e+00  7e-06
87: -1.6910e-02 -1.6948e-02  1e-02  2e+00  9e+00  8e-06
88: -1.6749e-02 -1.6786e-02  1e-02  2e+00  9e+00  8e-06
89: -1.7286e-02 -1.7317e-02  1e-02  3e+01  9e+00  1e-05
90: -2.0062e-02 -2.0079e-02  1e-02  2e+01  1e+01  1e-05
91: -2.0214e-02 -2.0228e-02  1e-02  2e+01  1e+01  1e-05
92: -2.0114e-02 -2.0124e-02  1e-02  3e+01  1e+01  8e-06
93: -2.0479e-02 -2.0488e-02  1e-02  5e+01  1e+01  9e-06
94: -2.0936e-02 -2.0940e-02  2e-02  2e+02  1e+01  1e-05
95: -2.1187e-02 -2.1188e-02  2e-02  9e+02  1e+01  1e-05
96: -2.1500e-02 -2.1498e-02  1e-02  9e+02  1e+01  1e-05
97: -2.1447e-02 -2.1444e-02  1e-02  1e+03  1e+01  1e-05
98: -2.1342e-02 -2.1338e-02  1e-02  1e+03  1e+01  1e-05
99: -2.1078e-02 -2.1073e-02  1e-02  2e+03  1e+01  1e-05
100: -2.0770e-02 -2.0766e-02  1e-02  2e+03  1e+01  9e-06
Terminated (maximum number of iterations reached).

Difference between two solutions 8.264479e-04
Testing in /hpc/scratch/frb15/sandbox/sage-5.7.beta4/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. = 1.602e-12
Testing in /hpc/scratch/frb15/sandbox/sage-5.7.beta4/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 /hpc/scratch/frb15/sandbox/sage-5.7.beta4/spkg/build/cvxopt-1.1.5.p0/src/examples/doc/chap8
Testing conelp.py ...
solver:qr
     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  2e-15  2e-01
 2: -1.4283e+00 -1.5409e+00  1e-01  2e-16  5e-02
 3: -1.4300e+00 -1.4312e+00  1e-03  3e-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  6e-13  5e-08
Optimal solution found.

x = 

[ 7.26e-01]
[ 6.18e-01]
[ 3.03e-01]

Testing l1.py ...
solver:<function Fkkt at 0x102afae0>
     pcost       dcost       gap    pres   dres   k/t
 0:  8.4409e+02  2.3550e+02  6e+02  9e-17  4e-15  1e+00
Traceback (most recent call last):
  File "l1.py", line 126, in <module>
    x, y = l1(P,q)
  File "l1.py", line 120, in l1
    primalstart={'x': x0, 's': s0}, dualstart={'z': z0})
  File "/hpc/scratch/frb15/sandbox/sage-5.7.beta4/local/lib/python2.7/site-packages/cvxopt/coneprog.py", line 1086, in conelp
    raise ValueError("Rank(A) < p or Rank([G; A]) < n")
ValueError: Rank(A) < p or Rank([G; A]) < n
Error: test /hpc/scratch/frb15/sandbox/sage-5.7.beta4/spkg/build/cvxopt-1.1.5.p0/src/examples/doc/chap8/l1.py failed

comment:17 Changed 8 years ago by fbissey

OK from there we get that

1) the chol2 solver is behaving badly and that's the one involved in all the failing doctests. 2) the l1.py is broken. It appears to want a non-existing solver.

That's an interesting starting point.

Last edited 8 years ago by fbissey (previous) (diff)

comment:18 Changed 8 years ago by fbissey

  • Report Upstream changed from N/A to Reported upstream. No feedback yet.

I am pinging upstream to see if they have a clue on where things go wrong.

comment:19 Changed 8 years ago by fbissey

Very similar results if I use openblas instead of atlas. There are some slight differences after 100 iterations - possibly a test of iterative precision of a sort. But still fails to converge.

comment:20 Changed 8 years ago by fbissey

I am currently in contact to figure out where things go wrong. I doesn't quite fit any of the given options.

comment:21 Changed 8 years ago by fbissey

  • Report Upstream changed from Reported upstream. No feedback yet. to Reported upstream. Developers acknowledge bug.

I have an unstable release to test to see if it fixes the problem.

comment:22 Changed 8 years ago by zimmerma

Francois, who is "upstream" here? Scipy?

Paul

comment:23 Changed 8 years ago by fbissey

No cvxopt: http://abel.ee.ucla.edu/cvxopt/ in particular Lieven Vandenberghe has been in contact with me regularly to find the problem.

comment:24 Changed 8 years ago by fbissey

  • Report Upstream changed from Reported upstream. Developers acknowledge bug. to Fixed upstream, but not in a stable release.

The beta provided by upstream fix the bug. I need to polish it a little bit before even thinking of posting it here. I have to rebase the solaris patch and fix spkg-check for the changes in 1.1.6 but the doctests pass and one test upstream devised to find the problem now passes too.

comment:25 Changed 8 years ago by fbissey

  • Description modified (diff)
  • Report Upstream changed from Fixed upstream, but not in a stable release. to Fixed upstream, in a later stable release.

Upstream has released 1.1.6 with power7 fix included. spkg when I have time or someone else has it.

comment:26 Changed 8 years ago by jdemeyer

  • Authors set to Jeroen Demeyer

I'm on it.

comment:27 Changed 8 years ago by jdemeyer

  • Description modified (diff)

comment:28 Changed 8 years ago by jdemeyer

  • Description modified (diff)
  • Status changed from new to needs_review

comment:29 Changed 8 years ago by jdemeyer

  • Status changed from needs_review to needs_work

I'm including the fix from #10508.

comment:30 Changed 8 years ago by jdemeyer

  • Summary changed from Bug in cvxopt on power7 to Upgrade cvxopt to 1.1.6

comment:31 Changed 8 years ago by jdemeyer

  • Description modified (diff)
  • Status changed from needs_work to needs_review

Changed 8 years ago by jdemeyer

spkg diff

comment:32 Changed 8 years ago by zimmerma

I'll review that ticket on silius. Now downloading Sage 5.9 source...

Paul

comment:33 Changed 8 years ago by vbraun

Isn't that silly, building stuff manually so we don't have to trouble the buildbot? I thought skynet is there to serve us, not the other way 'round ;-)

comment:34 Changed 8 years ago by zimmerma

Volker, what is wrong in testing a patch with the latest Sage release?

Paul

comment:35 follow-up: Changed 8 years ago by fbissey

Does spkg-check works? I thought it would need work when I checked the rc sent to me by upstream.

comment:36 Changed 8 years ago by fbissey

Also from my point of view it works on power7, it needs checking against #10508 and other platforms.

comment:37 in reply to: ↑ 35 Changed 8 years ago by jdemeyer

Replying to fbissey:

Does spkg-check works?

I works for me, I tested it on silius and also on OS X 10.6.

comment:38 Changed 8 years ago by fbissey

OK there may have been special testing code in the rc I was sent. spkg-check definitely didn't work with it. I had to run various tests manually after install.

comment:39 Changed 8 years ago by vbraun

  • Reviewers set to Volker Braun
  • Status changed from needs_review to positive_review

Works with #10508 and fixes the power7 issue. So I guess its good to go.

comment:40 Changed 8 years ago by jdemeyer

  • Merged in set to sage-5.10.beta4
  • Resolution set to fixed
  • Status changed from positive_review to closed

comment:41 Changed 8 years ago by leif

As reported on sage-release by Steven Trogdon, this fails to build if SAGE_SPKG_INSTALL_DOCS=yes, because the (pre-built) HTML docs have moved from src/doc/build/html/ to src/doc/html/.

Last edited 8 years ago by leif (previous) (diff)

comment:42 Changed 8 years ago by leif

P.S.: Some more environment variables ($CFLAG64 and $SAGE_LOCAL) should be quoted as well.

if [ "x$SAGE_SPKG_INSTALL_DOCS" = xyes ] ; then
   cd doc
# This part would be used to build the documentation with sphinx.
# cvxopt would then have to depend on sphinx.
# in 1.1.5 the documentation is shipped already built and up to date.
#   ${MAKE} -B html
#   if [ $? -ne 0 ]; then
#      echo "Error building the documentation"
#      exit 1
#   fi
# checking to see if there is previously installed documentation.
   if [ -d $SAGE_LOCAL/share/doc/cvxopt/html ] ; then
      rm -rf $SAGE_LOCAL/share/doc/cvxopt/html
   fi
   mkdir -p $SAGE_LOCAL/share/doc/cvxopt/html
   cp -r build/html/* $SAGE_LOCAL/share/doc/cvxopt/html/
fi

And some (more) error messages should get redirected to stderr.

comment:43 Changed 8 years ago by leif

P.P.S.: Perhaps also s|$SAGE_LOCAL/share|$SAGE_SHARE|.

And add error checks w.r.t. doc installation.

comment:44 Changed 8 years ago by leif

Follow-up is #14645, new spkg on the way...

Note: See TracTickets for help on using tickets.