def test_solve(self):
# Generate the code
self.model.codegen('code', python_ext_name='vec_emosqp',
force_rewrite=True)
sh.rmtree('code')
import vec_emosqp
# Solve problem
x, y, _, _, _ = vec_emosqp.solve()
# Assert close
nptest.assert_array_almost_equal(x, np.array([0., 5.]), decimal=5)
nptest.assert_array_almost_equal(
y, np.array([1.66666667, 0., 1.33333333, 0., 0.]), decimal=5)
def test_update_l(self):
import vec_emosqp
# Update lower bound
l_new = -100. * np.ones(self.m)
vec_emosqp.update_lower_bound(l_new)
x, y, _, _, _ = vec_emosqp.solve()
# Assert close
nptest.assert_array_almost_equal(x, np.array([0., 5.]), decimal=5)
nptest.assert_array_almost_equal(
y, np.array([1.66666667, 0., 1.33333333, 0., 0.]), decimal=5)
# Update lower bound to the original value
vec_emosqp.update_lower_bound(self.l)
def test_update_q(self):
import vec_emosqp
# Update linear cost and solve the problem
q_new = np.array([10., 20.])
vec_emosqp.update_lin_cost(q_new)
x, y, _, _, _ = vec_emosqp.solve()
# Assert close
nptest.assert_array_almost_equal(x, np.array([0., 5.]), decimal=5)
nptest.assert_array_almost_equal(
y, np.array([3.33333334, 0., 6.66666667, 0., 0.]), decimal=5)
# Update linear cost to the original value
vec_emosqp.update_lin_cost(self.q)
def test_update_u(self):
import vec_emosqp
# Update upper bound
u_new = 1000. * np.ones(self.m)
vec_emosqp.update_upper_bound(u_new)
x, y, _, _, _ = vec_emosqp.solve()
# Assert close
nptest.assert_array_almost_equal(
x, np.array([-1.51515152e-01, -3.33282828e+02]), decimal=4)
nptest.assert_array_almost_equal(
y, np.array([0., 0., 1.33333333, 0., 0.]), decimal=4)
# Update upper bound to the original value
vec_emosqp.update_upper_bound(self.u)
def test_update_bounds(self):
import vec_emosqp
# Update upper bound
l_new = -100. * np.ones(self.m)
u_new = 1000. * np.ones(self.m)
vec_emosqp.update_bounds(l_new, u_new)
x, y, _, _, _ = vec_emosqp.solve()
# Assert close
nptest.assert_array_almost_equal(
x, np.array([-0.12727273, -19.94909091]), decimal=4)
nptest.assert_array_almost_equal(
y, np.array([0., 0., 0., -0.8, 0.]), decimal=4)
# Update upper bound to the original value
vec_emosqp.update_bounds(self.l, self.u)