I am solving a QP using OSQP solver. The QP is solved at a particular time instance, but I get this error immediately
Traceback (most recent call last):
File "C:\Users\SPA18\Anaconda3\lib\site-packages\cvxpy\expressions\constants\constant.py", line 243, in extremal_eig_near_ref
ev = SA_eigsh(sigma)
File "C:\Users\SPA18\Anaconda3\lib\site-packages\cvxpy\expressions\constants\constant.py", line 238, in SA_eigsh
return eigsh(A, k=1, sigma=sigma, return_eigenvectors=False)
File "C:\Users\SPA18\Anaconda3\lib\site-packages\scipy\sparse\linalg\eigen\arpack\arpack.py", line 1687, in eigsh params.iterate() File "C:\Users\SPA18\Anaconda3\lib\site-packages\scipy\sparse\linalg\eigen\arpack\arpack.py", line 573, in iterate raise ArpackError(self.info, infodict=self.iterate_infodict) scipy.sparse.linalg.eigen.arpack.arpack.ArpackError: ARPACK error 3: No shifts could be applied during a cycle of the Implicitly restarted Arnoldi iteration. One possibility is to increase the size of NCV relative to NEV. During handling of the above exception, another exception occurred:
.....
File "C:\Users\SPA18\Anaconda3\lib\site-packages\cvxpy\expressions\constants\constant.py", line 238, in SA_eigsh
return eigsh(A, k=1, sigma=sigma, return_eigenvectors=False)
File "C:\Users\SPA18\Anaconda3\lib\site-packages\scipy\sparse\linalg\eigen\arpack\arpack.py", line 1687, in eigsh
params.iterate()
File "C:\Users\SPA18\Anaconda3\lib\site-packages\scipy\sparse\linalg\eigen\arpack\arpack.py", line 573, in iterate raise ArpackError(self.info, infodict=self.iterate_infodict) scipy.sparse.linalg.eigen.arpack.arpack.ArpackError: ARPACK error 3: No shifts could be applied during a cycle of the Implicitly restarted Arnoldi iteration. One possibility is to increase the size of NCV relative to NEV
I am getting this error quite often. Looks like the problem is originating by cvxpy problem setup. There are few questions about this on stack exchange but no clear solution. What should I change to solve this? Until the point it fails, the simulation runs quite smooth without any abrupt changes in optimal value. After that, it suddenly fails. My problem setup looks like this: