def test_simple_sage_1(self):
"""
Solve a simple SAGE relaxation for a signomial minimization problem.
Do this without resorting to "Signomial" objects.
"""
alpha = np.array([[0, 0],
[1, 0],
[0, 1],
[1, 1],
[0.5, 0],
[0, 0.5]])
gamma = cl.Variable(shape=(), name='gamma')
c = cl.Expression([0 - gamma, 3, 2, 1, -4, -2])
expected_val = -1.8333331773244161
# with presolve
cl.presolve_trivial_age_cones(True)
con = cl.PrimalSageCone(c, alpha, None, 'test_con_name')
obj = gamma
prob = Problem(cl.MAX, obj, [con])
status, val = prob.solve(solver='ECOS', verbose=False)
assert abs(val - expected_val) < 1e-6
v = con.violation()
assert v < 1e-6
# without presolve
cl.presolve_trivial_age_cones(False)
con = cl.PrimalSageCone(c, alpha, None, 'test_con_name')
obj = gamma
prob = Problem(cl.MAX, obj, [con])
status, val = prob.solve(solver='ECOS', verbose=False)
assert abs(val - expected_val) < 1e-6
v = con.violation()
assert v < 1e-6
def primal_sage_cone(sig, name, X, expcovers=None):
con = cl.PrimalSageCone(sig.c, sig.alpha, X, name, covers=expcovers)
return con