diff options
| -rw-r--r-- | examples/sostools/sosdemo2.py | 2 | ||||
| -rw-r--r-- | sumofsquares/__init__.py | 6 | ||||
| -rw-r--r-- | sumofsquares/problems.py | 34 |
3 files changed, 19 insertions, 23 deletions
diff --git a/examples/sostools/sosdemo2.py b/examples/sostools/sosdemo2.py index d0cf81d..ece36b7 100644 --- a/examples/sostools/sosdemo2.py +++ b/examples/sostools/sosdemo2.py @@ -33,7 +33,7 @@ constraints = ( sos.make_sos_constraint(- (dV @ f)), ) -prob, result = sos.solve_problem(cost=None, constraints=constraints, solver=Solver.CVXOPT) +prob, state, result = sos.solve_problem(cost=None, constraints=constraints, solver=Solver.CVXOPT) print(prob) # TODO: create SolverStatus enumeration diff --git a/sumofsquares/__init__.py b/sumofsquares/__init__.py index bd5ec6a..58480fd 100644 --- a/sumofsquares/__init__.py +++ b/sumofsquares/__init__.py @@ -129,7 +129,7 @@ def maximize(cost, *args, **kwargs) -> SOSProblem: return make_problem(-cost, *args, **kwargs) -def solve_problem(*args, verbose: bool = True, state: ExpressionState | None = None, **kwargs) -> tuple[Problem, Result]: +def solve_problem(*args, state: ExpressionState | None = None, verbose: bool = True, **kwargs) -> tuple[Problem, ExpressionState, Result]: """ Solve a sum-of-squares optimization problem. This function is just a shorthand for @@ -139,4 +139,6 @@ def solve_problem(*args, verbose: bool = True, state: ExpressionState | None = N result = prob.solve(verbose) """ prob = make_problem(*args, **kwargs) - return prob, prob.solve(verbose=verbose, state=state) + if state is None: + state = poly.make_state() + return (prob,) + prob.solve(verbose=verbose, state=state) diff --git a/sumofsquares/problems.py b/sumofsquares/problems.py index 7bcd629..14618fe 100644 --- a/sumofsquares/problems.py +++ b/sumofsquares/problems.py @@ -65,7 +65,7 @@ class ConicProblem(Problem): constraints: dict[str, list[tuple[tuple[NDArray, ...], NDArray]]] """ Conic constraints are saved in a dictionary with the following form. - For the key we will use the following names to refer to various constraint + For the key we will use the following names to refer to various types of constraints :: @@ -162,12 +162,9 @@ class SOSProblem(Problem): return s @override - def solve(self, verbose: bool = False, state: ExpressionState | None = None) -> Result: - if state is None: - state = poly.make_state() - + def solve(self, state: ExpressionState, verbose: bool = False) -> tuple[ExpressionState, Result]: state, internal_prob = self.apply(state) - return internal_prob.solve(verbose) + return internal_prob.solve(state, verbose) def apply(self, state: ExpressionState) -> tuple[ExpressionState, InternalSOSProblem]: """ @@ -207,6 +204,7 @@ class SOSProblem(Problem): x = poly.v_stack((1,) + tuple( init_variable_expr(v, state.get_shape(v)) for v in polynomial_variables)) + for i, c in enumerate(self.constraints): if isinstance(c, EqualToZero): state, deg = c.expression.degree().apply(state) @@ -287,7 +285,7 @@ class SOSProblem(Problem): return state, InternalSOSProblem(cost, tuple(pm_constraints), tuple(variables), polynomial_variables, - self.solver, state) + self.solver) # FIXME: I hate this name, and the fact that this class needs to exist @@ -308,12 +306,9 @@ class InternalSOSProblem(Problem): polynomial_variables: Sequence[Symbol] solver: Solver - # TODO: remove state field from this class, it is redundant - state: ExpressionState - - def to_conic_problem(self, verbose: bool = False) -> ConicProblem: + def to_conic_problem(self, state: ExpressionState, verbose: bool = False) -> ConicProblem: """ - Conver the SOS problem into a Conic program. + Convert the SOS problem into a Conic program. """ cost = poly.to_affine(self.cost) if cost.degree > 2: @@ -336,7 +331,7 @@ class InternalSOSProblem(Problem): } # indices of variables in the optimization problem, sorted - variable_indices = sum(sorted(tuple(self.state.get_indices_as_variable_index(v)) + variable_indices = sum(sorted(tuple(state.get_indices_as_variable_index(v)) for v in self.variables), ()) # cost linear term @@ -357,9 +352,8 @@ class InternalSOSProblem(Problem): # see also polymatrix.index.MonomialIndex.__lt__ P[np.triu_indices(n)] = cost_coeffs[2] - # Make symmetric. There is no 0.5 factor because there it is already - # there in the canonical form, see docstring of ConicProblem - P = (P + P.T) + # Make symmetric + P = .5 * (P + P.T) else: P = None @@ -400,7 +394,7 @@ class InternalSOSProblem(Problem): else: raise NotImplementedError(f"Cannot convert constraint of type {type(c)} " - "into a conic constriant (yet).") + "into a conic constraint (yet).") if all(len(cl) == 0 for cl in constraints.values()): raise ValueError("Optimization problem is unconstrained!") @@ -414,11 +408,11 @@ class InternalSOSProblem(Problem): return ConicProblem(P=P, q=q, constraints=constraints, dims=dims, is_qp=is_qp, solver=self.solver, - variables={v : self.state.get_shape(v) + variables={v : state.get_shape(v) for v in self.variables }) @override - def solve(self, verbose: bool = False) -> Result: - return self.to_conic_problem(verbose).solve(verbose) + def solve(self, state: ExpressionState, verbose: bool = False) -> tuple[ExpressionState, Result]: + return state, self.to_conic_problem(state, verbose).solve(verbose) |