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nikcleju@65
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1
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2 import numpy
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3 import cvxopt
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4 import cvxopt.solvers
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5 import cvxopt.msk
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6 import mosek
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7
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8 def cvxopt_lp(y, A):
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9
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10 N = A.shape[1]
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11 AA = numpy.hstack((A, -A))
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12 c = numpy.ones((2*N, 1))
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13
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14 G = numpy.vstack((numpy.zeros((2*N,2*N)), -numpy.eye(2*N)))
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15 h = numpy.zeros((4*N,1))
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16
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17 # Convert numpy arrays to cvxopt matrices
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18 cvx_c = cvxopt.matrix(c)
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19 cvx_G = cvxopt.matrix(G)
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20 cvx_h = cvxopt.matrix(h)
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21 cvx_AA = cvxopt.matrix(AA)
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22 cvx_y = cvxopt.matrix(y.reshape(y.size,1))
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23
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24 # Options
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25 cvxopt.solvers.options['show_progress'] = False
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26 #cvxopt.solvers.options['MOSEK'] = {mosek.iparam.log: 0}
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27
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28 # Solve
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29 #res = cvxopt.solvers.lp(cvx_c, cvx_G, cvx_h, A=cvx_AA, b=cvx_y, solver='mosek')
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30 res = cvxopt.solvers.lp(cvx_c, cvx_G, cvx_h, A=cvx_AA, b=cvx_y)
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31
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32 primal = numpy.squeeze(numpy.array(res['x']))
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33 gamma = primal[:N] - primal[N:]
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34 return gamma
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35
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36 #lb = zeros(2*N,1);
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37 #ub = Inf*ones(2*N,1);
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38 ##[primal,obj,exitflag,output2,dual] = linprog(c,[],[],A,y,lb,ub,[],opt);
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39 ##[primal,~,~,~,~] = linprog(c,[],[],A,aggy,lb,ub);
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40 #[primal,obj,exitflag,output2,dual] = linprog(c,[],[],A,aggy,lb,ub);
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41 #gamma = primal(1:N) - primal((N+1):(2*N)); |
