diff options
| -rw-r--r-- | sumofsquares/solver/cvxopt.py | 21 |
1 files changed, 16 insertions, 5 deletions
diff --git a/sumofsquares/solver/cvxopt.py b/sumofsquares/solver/cvxopt.py index e41633f..455ee5b 100644 --- a/sumofsquares/solver/cvxopt.py +++ b/sumofsquares/solver/cvxopt.py @@ -77,8 +77,11 @@ def solve_cone(prob: ConicProblem, verbose: bool = False, # Equality constraints A_rows, b_rows = [], [] for (linear, constant) in prob.constraints["z"]: - b_rows.append(constant) - A_rows.append(np.hstack(tuple(vectorize_matrix(m) for m in linear)).T) + b_rows.append(vectorize_matrix(constant)) + A_rows.append(np.hstack(tuple(vectorize_matrix(m) for m in linear))) + + # pprint(f"{A_rows = }") + # pprint(f"{b_rows = }") if A_rows: # b is multiplied by -1 because it is on the RHS @@ -90,12 +93,13 @@ def solve_cone(prob: ConicProblem, verbose: bool = False, for (linear, constant) in prob.constraints["l"]: h_rows.append(constant) - G_rows.append(np.hstack(tuple(m for m in linear)).T) + G_rows.append(np.hstack(tuple(m for m in linear))) if prob.constraints["q"]: raise NotImplementedError("SOC constraints are not implemented yet.") for (linear, constant) in prob.constraints["s"]: + # b is multiplied by -1 because it is on the RHS h_rows.append(vectorize_matrix(constant)) G_rows.append(np.hstack(tuple(vectorize_matrix(m) for m in linear))) @@ -104,10 +108,17 @@ def solve_cone(prob: ConicProblem, verbose: bool = False, if G_rows: # h is multiplied by -1 because it is on the RHS - h = cvxopt.matrix(np.vstack(h_rows).reshape((-1, 1))) * -1 + h = cvxopt.matrix(np.vstack(h_rows)) * -1 G = cvxopt.matrix(np.vstack(G_rows)) + # Format dims for CVXOPT + dims = { + "l": sum(prob.dims["l"]), + "q": prob.dims["q"], + "s": prob.dims["s"] + } + # Solve the problem # pprint({"A": A, "b": b, "G": G, "h": h}) @@ -115,7 +126,7 @@ def solve_cone(prob: ConicProblem, verbose: bool = False, if prob.is_qp: assert P is not None, "Solving LP with QP solver! Something has gone wrong" info = cvxopt.solvers.coneqp(P=P, q=q, G=G, h=h, A=A, b=b, - dims=prob.dims, *args, **kwargs) + dims=dims, *args, **kwargs) else: assert q is not None, "LP has no objective! Something is very wrong" info = cvxopt.solvers.conelp(c=q, G=G, h=h, A=A, b=b, |