[A,xy] = cut_grid_data;
[n,m] = size(A);
[ w_fdla, rho_fdla ] = fdla(A);
[ w_fmmc, rho_fmmc ] = fmmc(A);
[ w_md, rho_md ] = max_deg(A);
[ w_bc, rho_bc ] = best_const(A);
[ w_mh, rho_mh ] = mh(A);
tau_fdla = 1/log(1/rho_fdla);
tau_fmmc = 1/log(1/rho_fmmc);
tau_md = 1/log(1/rho_md);
tau_bc = 1/log(1/rho_bc);
tau_mh = 1/log(1/rho_mh);
fprintf(1,'\nResults:\n');
fprintf(1,'FDLA weights:\t\t rho = %5.4f \t tau = %5.4f\n',rho_fdla,tau_fdla);
fprintf(1,'FMMC weights:\t\t rho = %5.4f \t tau = %5.4f\n',rho_fmmc,tau_fmmc);
fprintf(1,'M-H weights:\t\t rho = %5.4f \t tau = %5.4f\n',rho_mh,tau_mh);
fprintf(1,'MAX_DEG weights:\t rho = %5.4f \t tau = %5.4f\n',rho_md,tau_md);
fprintf(1,'BEST_CONST weights:\t rho = %5.4f \t tau = %5.4f\n',rho_bc,tau_bc);
figure(1), clf
plotgraph(A,xy,w_fdla);
text(0.425,1.05,'FDLA optimal weights')
figure(2), clf
plotgraph(A,xy,w_fmmc);
text(0.425,1.05,'FMMC optimal weights')
figure(3), clf
plotgraph(A,xy,w_md);
text(0.375,1.05,'Max degree optimal weights')
figure(4), clf
plotgraph(A,xy,w_bc);
text(0.375,1.05,'Best constant optimal weights')
figure(5), clf
plotgraph(A,xy,w_mh);
text(0.3,1.05,'Metropolis-Hastings optimal weights')
Warning: A non-empty cvx problem already exists in this scope.
It is being overwritten.
Calling sedumi: 4166 variables, 4070 equality constraints
------------------------------------------------------------
SeDuMi 1.21 by AdvOL, 2005-2008 and Jos F. Sturm, 1998-2003.
Alg = 2: xz-corrector, Adaptive Step-Differentiation, theta = 0.250, beta = 0.500
Split 6 free variables
eqs m = 4070, order n = 141, dim = 8205, blocks = 3
nnz(A) = 4765 + 0, nnz(ADA) = 8900020, nnz(L) = 4452055
it : b*y gap delta rate t/tP* t/tD* feas cg cg prec
0 : 2.15E-01 0.000
1 : 1.23E+01 1.38E-02 0.000 0.0641 0.9900 0.9900 -0.69 1 1 1.4E+00
2 : 3.45E+00 5.87E-03 0.000 0.4255 0.9000 0.9000 2.14 1 1 3.2E-01
3 : 1.14E+00 2.61E-03 0.000 0.4457 0.9000 0.9000 4.54 1 1 4.7E-02
4 : 1.02E+00 9.34E-04 0.000 0.3574 0.9000 0.9000 1.30 1 1 1.6E-02
5 : 1.00E+00 2.76E-04 0.000 0.2956 0.9000 0.9000 1.03 1 1 4.7E-03
6 : 9.92E-01 1.46E-05 0.000 0.0530 0.9082 0.9000 1.02 1 1 7.6E-04
7 : 9.89E-01 4.08E-06 0.000 0.2785 0.9000 0.8622 1.00 1 1 2.1E-04
8 : 9.89E-01 1.51E-06 0.000 0.3713 0.9000 0.9000 1.00 1 1 7.8E-05
9 : 9.88E-01 4.68E-07 0.000 0.3090 0.9000 0.9000 1.00 1 1 2.4E-05
10 : 9.88E-01 1.19E-07 0.000 0.2541 0.9000 0.9000 1.00 1 1 6.1E-06
11 : 9.88E-01 8.27E-09 0.160 0.0696 0.9904 0.9900 1.00 1 1 5.0E-07
12 : 9.88E-01 1.32E-09 0.000 0.1590 0.9199 0.9000 1.00 1 1 1.0E-07
13 : 9.88E-01 5.83E-11 0.246 0.0443 0.9900 0.9900 1.00 1 1 4.7E-09
iter seconds digits c*x b*y
13 82.9 Inf 9.8829189085e-01 9.8829190238e-01
|Ax-b| = 5.0e-09, [Ay-c]_+ = 2.0E-09, |x|= 1.4e+01, |y|= 1.3e+00
Detailed timing (sec)
Pre IPM Post
4.900E-01 8.287E+01 0.000E+00
Max-norms: ||b||=9.843750e-01, ||c|| = 1,
Cholesky |add|=0, |skip| = 0, ||L.L|| = 50.7171.
------------------------------------------------------------
Status: Solved
Optimal value (cvx_optval): +0.988292
Calling sedumi: 4320 variables, 4224 equality constraints
------------------------------------------------------------
SeDuMi 1.21 by AdvOL, 2005-2008 and Jos F. Sturm, 1998-2003.
Alg = 2: xz-corrector, Adaptive Step-Differentiation, theta = 0.250, beta = 0.500
Split 1 free variables
eqs m = 4224, order n = 290, dim = 8354, blocks = 3
nnz(A) = 4990 + 0, nnz(ADA) = 9346884, nnz(L) = 4677453
it : b*y gap delta rate t/tP* t/tD* feas cg cg prec
0 : 1.04E-01 0.000
1 : 2.53E-01 3.65E-02 0.000 0.3506 0.9000 0.9000 2.57 1 1 1.4E+00
2 : 8.76E-01 8.73E-03 0.000 0.2389 0.9000 0.9000 1.70 1 1 2.3E-01
3 : 9.98E-01 3.01E-04 0.000 0.0345 0.9900 0.9900 1.21 1 1 7.0E-03
4 : 9.93E-01 8.37E-05 0.000 0.2778 0.9000 0.9000 1.04 1 1 1.9E-03
5 : 9.91E-01 2.21E-05 0.000 0.2640 0.9000 0.9000 1.01 1 1 5.0E-04
6 : 9.91E-01 4.64E-06 0.108 0.2101 0.9000 0.0000 1.03 1 1 3.1E-04
7 : 9.91E-01 9.58E-07 0.000 0.2063 0.9373 0.9000 1.02 1 1 9.0E-05
8 : 9.89E-01 2.78E-07 0.000 0.2897 0.9000 0.9017 1.02 1 1 2.6E-05
9 : 9.89E-01 1.15E-07 0.000 0.4157 0.9000 0.9084 1.01 1 1 1.1E-05
10 : 9.89E-01 6.19E-08 0.000 0.5369 0.9469 0.9000 1.01 1 1 5.5E-06
11 : 9.89E-01 2.70E-08 0.000 0.4366 0.0000 0.9000 1.01 1 1 2.5E-06
12 : 9.89E-01 6.99E-09 0.000 0.2586 0.9000 0.8076 1.01 1 1 7.0E-07
13 : 9.89E-01 2.99E-09 0.000 0.4277 0.7937 0.9000 1.00 1 2 3.0E-07
14 : 9.89E-01 1.07E-09 0.000 0.3593 0.9000 0.9000 1.00 1 1 1.1E-07
15 : 9.89E-01 4.24E-10 0.000 0.3949 0.9000 0.9000 1.00 2 2 4.2E-08
16 : 9.89E-01 1.54E-10 0.000 0.3640 0.9000 0.9000 1.00 2 2 1.5E-08
17 : 9.89E-01 6.42E-11 0.000 0.4160 0.9000 0.9000 1.00 2 2 6.4E-09
iter seconds digits c*x b*y
17 131.2 Inf 9.8882630019e-01 9.8882630233e-01
|Ax-b| = 4.6e-09, [Ay-c]_+ = 2.9E-09, |x|= 1.4e+01, |y|= 1.4e+00
Detailed timing (sec)
Pre IPM Post
7.100E-01 1.312E+02 1.000E-02
Max-norms: ||b||=9.843750e-01, ||c|| = 1,
Cholesky |add|=0, |skip| = 0, ||L.L|| = 61.2408.
------------------------------------------------------------
Status: Solved
Optimal value (cvx_optval): +0.988826
Results:
FDLA weights: rho = 0.9883 tau = 84.9099
FMMC weights: rho = 0.9888 tau = 88.9949
M-H weights: rho = 0.9917 tau = 120.2442
MAX_DEG weights: rho = 0.9927 tau = 136.7523
BEST_CONST weights: rho = 0.9921 tau = 126.3450