Detecting of returning error in CVX

2

You can do it using MATLAB’s try catch .https://www.mathworks.com/help/matlab/ref/try.html .

Here is a crude version which demonstrates it. After a CVX error, it will execute cvx_clear and go on to the next CVX problem.

The first time through the for loop, produces a DCP error in the minimize. The 2nd time through,CVX solves the problem.

for i = -1:2:1
try
cvx_begin
variable x
minimize(i*x^2)
x>=0
cvx_end
catch
disp('Whoops')
cvx_clear
end
end

Output is:

Whoops
 
Calling SDPT3 4.0: 4 variables, 2 equality constraints
------------------------------------------------------------

 num. of constraints =  2
 dim. of sdp    var  =  2,   num. of sdp  blk  =  1
 dim. of linear var  =  1
*******************************************************************
   SDPT3: Infeasible path-following algorithms
*******************************************************************
 version  predcorr  gam  expon  scale_data
   HKM      1      0.000   1        0    
it pstep dstep pinfeas dinfeas  gap      prim-obj      dual-obj    cputime
-------------------------------------------------------------------
 0|0.000|0.000|6.7e+00|8.4e+00|3.0e+02| 1.000000e+01  0.000000e+00| 0:0:00| chol  1  1 
 1|1.000|1.000|2.2e-06|8.7e-02|1.9e+01| 9.019569e+00 -9.098563e+00| 0:0:00| chol  1  1 
 2|1.000|1.000|5.6e-07|8.7e-03|2.8e+00| 1.410751e+00 -1.318898e+00| 0:0:00| chol  1  1 
 3|1.000|1.000|1.3e-07|8.7e-04|1.1e+00| 5.109862e-01 -5.983815e-01| 0:0:00| chol  1  1 
 4|0.919|0.919|2.2e-08|1.5e-04|1.1e-01| 5.314692e-02 -5.323401e-02| 0:0:00| chol  1  1 
 5|1.000|1.000|3.7e-09|8.7e-06|4.4e-02| 2.232379e-02 -2.166095e-02| 0:0:00| chol  1  1 
 6|0.919|0.918|7.9e-10|1.5e-06|4.2e-03| 2.079518e-03 -2.074893e-03| 0:0:00| chol  1  1 
 7|1.000|1.000|2.4e-09|8.7e-08|1.7e-03| 8.610391e-04 -8.672553e-04| 0:0:00| chol  1  1 
 8|0.919|0.919|4.7e-10|1.5e-08|1.6e-04| 8.128190e-05 -8.128799e-05| 0:0:00| chol  1  1 
 9|1.000|1.000|1.3e-09|9.6e-10|6.8e-05| 3.385876e-05 -3.380255e-05| 0:0:00| chol  1  1 
10|0.919|0.919|1.1e-10|2.2e-10|6.4e-06| 3.181334e-06 -3.181032e-06| 0:0:00| chol  1  1 
11|1.000|1.000|7.2e-16|2.1e-11|2.6e-06| 1.324601e-06 -1.324868e-06| 0:0:00| chol  1  1 
12|1.000|1.000|2.7e-20|1.0e-12|3.8e-07| 1.893805e-07 -1.893516e-07| 0:0:00| chol  1  1 
13|1.000|1.000|2.7e-20|1.0e-12|7.7e-08| 3.835028e-08 -3.835660e-08| 0:0:00| chol  1  1 
14|1.000|1.000|1.1e-16|1.0e-12|1.4e-08| 7.157999e-09 -7.156403e-09| 0:0:00|
  stop: max(relative gap, infeasibilities) < 1.49e-08
-------------------------------------------------------------------
 number of iterations   = 14
 primal objective value =  7.15799934e-09
 dual   objective value = -7.15640325e-09
 gap := trace(XZ)       = 1.43e-08
 relative gap           = 1.43e-08
 actual relative gap    = 1.43e-08
 rel. primal infeas (scaled problem)   = 1.11e-16
 rel. dual     "        "       "      = 1.00e-12
 rel. primal infeas (unscaled problem) = 0.00e+00
 rel. dual     "        "       "      = 0.00e+00
 norm(X), norm(y), norm(Z) = 1.0e+00, 1.2e-04, 1.0e+00
 norm(A), norm(b), norm(C) = 2.6e+00, 2.0e+00, 2.0e+00
 Total CPU time (secs)  = 0.13  
 CPU time per iteration = 0.01  
 termination code       =  0
 DIMACS: 1.1e-16  0.0e+00  1.0e-12  0.0e+00  1.4e-08  1.4e-08
-------------------------------------------------------------------
 
------------------------------------------------------------
Status: Solved
Optimal value (cvx_optval): +7.158e-09
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