how to find the value of the objective function after lp is optimal?

[mohamed]

I have cvxopt installed on a ubuntu machine with version = '1.1.1' and
then all I have to do to find the objective function is read sol
['primal objective'], where sol is the dictionary returned by
solvers.lp(). However, I have cvxopt on another debian machine that
has version '1.0' and sol does not have that key in it. So, what is
the proper way to find the objective function? or how to get that
'primal objective' key into sol in version '1.0'?

Here is a dump of the sol dictionary from both versions (not for the
same problem).

1.1.1:
{'status': 'optimal', 'dual slack': 0.054557621285554726, 'residual as
primal infeasibility certificate': None, 'relative gap':
0.00031242509541014931, 'dual objective': -1000.2323902106706,
'residual as dual infeasibility certificate': None, 'gap':
0.31240009831336962, 's': <8x1 matrix, tc='d'>, 'primal
infeasibility': 6.4935966412888117e-17, 'dual infeasibility':
1.2949786542632828e-15, 'primal objective': -999.91999011235998,
'primal slack': 7.8088088910074751e-07, 'y': <4x1 matrix, tc='d'>,
'x': <6x1 matrix, tc='d'>, 'z': <8x1 matrix, tc='d'>}

1.0:
{'status': 'optimal', 'x': <1410x1 matrix, tc='d'>, 's': <1677x1
matrix, tc='d'>, 'z': <1677x1 matrix, tc='d'>, 'y': <45x1 matrix,
tc='d'>}

[mohamed]

ok, I guess I can always multiply the objective vector with the
solution vector to get the value I am looking for.