I'm using osqp-eigen v0.7.0, wondering if Hessian Matrix is supporting only symmetric matrix, rather than upper triangular matrix.
ZhiDaoYongYuan opened this issue · comments
My partial code as follows:
// symmetric matrix
for (int i = 0; i < n - 1; ++i)
{
hessian.insert(i, i + 1) = 1.0;
hessian.insert(i + 1, i) = 1.0;
}
// upper triangular matrix
for (int i = 0; i < n - 1; ++i)
{
hessian.insert(i, i + 1) = 2.0;
}
When I used the symmetric matrix, I got the true solution(I guess). Instead, solver return
status: problem non convex
while using upper triangular matrix.
Strictly speaking according to the documentation the hessian matrix is required to be symmetric, but looking in the code actually only an upper triangular view is used (see
osqp-eigen/include/OsqpEigen/Data.tpp
Lines 40 to 44 in a752c5e
Are you sure that in your example you are actually passing the two matrices in the two cases? Can you provide a full example in the two cases, instead an incomplete snippet of code? Thanks!
Hi @ZhiDaoYongYuan, did you fill the diagonal as well? If
whose eigenvalues are +2 and -2. Hence the matrix would not be positive semidefinite. So I would say that the error message is correct. I am not sure why it did not print it in the first case.