| import numpy as np | |
| from scipy import sparse | |
| import utils.codegen_utils as cu | |
| P = sparse.triu([[2., 5.], [5., 1.]], format='csc') | |
| q = np.array([3., 4.]) | |
| A = sparse.csc_matrix([[-1., 0.], [0., -1.], [-1., 3.], [2., 5.], [3., 4]]) | |
| l = -np.inf * np.ones(A.shape[0]) | |
| u = np.array([0., 0., -15., 100., 80.]) | |
| sols_data = {'sigma_new': 5} | |
| # Generate problem data | |
| cu.generate_problem_data(P, q, A, l, u, 'non_cvx', sols_data) |