/usr/share/pyshared/openopt/solvers/CVXOPT/CVXOPT_LP_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 60 61 62 63 64 65 66 67 68 69 70 | from numpy import asarray, ones, all, isfinite, copy, nan, concatenate, array, dot
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
import os
def CVXOPT_LP_Solver(p, solverName):
#os.close(1); os.close(2)
if solverName == 'native_CVXOPT_LP_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)
#WholeRepr2LinConst(p)
f = copy(p.f).reshape(-1,1)
# CVXOPT have some problems with x0 so currently I decided to avoid using the one
#if p.x0.size>0 and p.x0.flatten()[0] != None and all(isfinite(p.x0)):
# sol= cvxopt_solvers.solvers.lp(Matrix(p.f), Matrix(p.A), Matrix(p.b), Matrix(p.Aeq), Matrix(p.beq), solverName)
#else:
if (len(p.intVars)>0 or len(p.binVars)>0) and solverName == 'glpk':
from cvxopt.glpk import ilp
c = Matrix(p.f)
A, b = Matrix(p.Aeq), Matrix(p.beq)
G, h = Matrix(p.A), Matrix(p.b)
if A is None:
A = matrix(0.0, (0, p.n))
b = matrix(0.0,(0,1))
if G is None:
G = matrix(0.0, (0, p.n))
h = matrix(0.0,(0,1))
(status, x) = ilp(c, G, h, A, b, set(p.intVars), B=set(p.binVars))
if status == 'optimal': p.istop = SOLVED_WITH_UNIMPLEMENTED_OR_UNKNOWN_REASON
elif status == 'maxiters exceeded': p.istop = IS_MAX_ITER_REACHED
elif status == 'time limit exceeded': p.istop = IS_MAX_TIME_REACHED
elif status == 'unknown': p.istop = UNDEFINED
else: p.istop = FAILED_WITH_UNIMPLEMENTED_OR_UNKNOWN_REASON
if x is None:
p.xf = nan*ones(p.n)
else:
p.xf = array(x).flatten()#w/o flatten it yields incorrect result in ff!
p.ff = sum(p.dotmult(p.f, p.xf))
p.msg = status
else:
# if len(p.b) != 0:
# s0 = matrix(p.b - dot(p.A, p.x0))
# else:
# s0 = matrix()
# primalstart = {'x': matrix(p.x0), 's': s0}
# sol = cvxopt_solvers.lp(Matrix(p.f), Matrix(p.A), Matrix(p.b), Matrix(p.Aeq), Matrix(p.beq), solverName, primalstart)
sol = cvxopt_solvers.lp(Matrix(p.f), Matrix(p.A), Matrix(p.b), 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()
# ! don't involve p.ff - it can be different because of goal and additional constant from FuncDesigner
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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