/usr/share/pyshared/openopt/solvers/CVXOPT/CVXOPT_SDP_Solver.py is in python-openopt 0.34+svn1146-1build1.
This file is owned by root:root, with mode 0o644.
The actual contents of the file can be viewed below.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 | from numpy import asarray, ones, all, isfinite, copy, nan, concatenate, array, asfarray, zeros
from openopt.kernel.ooMisc import WholeRepr2LinConst, xBounds2Matrix
from cvxopt_misc import *
import cvxopt.solvers as cvxopt_solvers
from cvxopt.base import matrix
from openopt.kernel.setDefaultIterFuncs import SOLVED_WITH_UNIMPLEMENTED_OR_UNKNOWN_REASON, IS_MAX_ITER_REACHED, IS_MAX_TIME_REACHED, FAILED_WITH_UNIMPLEMENTED_OR_UNKNOWN_REASON, UNDEFINED
def converter_to_CVXOPT_SDP_Matrices_from_OO_SDP_Class(OO_SDP_Class_2D_Dict_S, nVars):
# nVars can be extracted from OO_SDP_Class_2D_Dict_S but it's easier just to pass as param
a = OO_SDP_Class_2D_Dict_S
#r = []
R = {}
for i, j in a.keys():
if i not in R.keys():
R[i] = zeros((nVars, asarray(a[i, 0]).size))
R[i][j] = asfarray(a[i, j]).flatten()
r = []
for i in R.keys():
r.append(Matrix(R[i].T))
return r
def DictToList(d):
i = 0
r = []
while i in d.keys():
r.append(matrix(d[i], tc = 'd'))
i += 1
return r
def CVXOPT_SDP_Solver(p, solverName):
if solverName == 'native_CVXOPT_SDP_Solver': solverName = None
cvxopt_solvers.options['maxiters'] = p.maxIter
cvxopt_solvers.options['feastol'] = p.contol
cvxopt_solvers.options['abstol'] = p.ftol
if p.iprint <= 0:
cvxopt_solvers.options['show_progress'] = False
cvxopt_solvers.options['LPX_K_MSGLEV'] = 0
#cvxopt_solvers.options['MSK_IPAR_LOG'] = 0
xBounds2Matrix(p)
#FIXME: if problem is search for MAXIMUM, not MINIMUM!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!
f = copy(p.f).reshape(-1,1)
# CVXOPT have some problems with x0 so currently I decided to avoid using the one
sol = cvxopt_solvers.sdp(Matrix(p.f), Matrix(p.A), Matrix(p.b), \
converter_to_CVXOPT_SDP_Matrices_from_OO_SDP_Class(p.S, p.n), \
DictToList(p.d), Matrix(p.Aeq), Matrix(p.beq), solverName)
p.msg = sol['status']
if p.msg == 'optimal' : p.istop = SOLVED_WITH_UNIMPLEMENTED_OR_UNKNOWN_REASON
else: p.istop = -100
if sol['x'] is not None:
p.xf = asarray(sol['x']).flatten()
p.ff = sum(p.dotmult(p.f, p.xf))
#p.duals = concatenate((asarray(sol['y']).flatten(), asarray(sol['z']).flatten()))
else:
p.ff = nan
p.xf = nan*ones(p.n)
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