def test_initialization_from_data(self):
n_e = 50
hs = N.ones(n_e) * 1. / n_e
n_cp = 3
nlp = NLPCollocationLagrangePolynomials(self.model, n_e, hs, n_cp)
nlp.set_initial_from_dymola(self.expected, hs, 0, 1)
nlp.export_result_dymola()
self.data = ResultDymolaTextual(
"NominalTests_NominalOptTest2_result.txt")
self.assert_all_trajectories(['x', 'der(x)', 'u'])
def test_init(self):
m = JMUModel(self.jn)
# Create a new collocation object
n_e = 30
coll = NLPCollocationLagrangePolynomials(m, n_e, N.ones(n_e) / n_e, 3)
# Initialize with optimization result
coll.set_initial_from_dymola(self.res.result_data, N.array([]), 0, 1)
# Write initial point to file
coll.export_result_dymola('Init_res.txt')
# Load result
res_init = ResultDymolaTextual('Init_res.txt')
# Load test fixture
res_init_fix = ResultDymolaTextual(
self.curr_dir + '/../files/Results/MinTimeInit_init_fix.txt')
# Extract trajectories
dx = res_init.get_variable_data('der(x)')
dv = res_init.get_variable_data('der(v)')
x = res_init.get_variable_data('x')
v = res_init.get_variable_data('v')
u = res_init.get_variable_data('u')
dx_fix = res_init_fix.get_variable_data('der(x)')
dv_fix = res_init_fix.get_variable_data('der(v)')
x_fix = res_init_fix.get_variable_data('x')
v_fix = res_init_fix.get_variable_data('v')
u_fix = res_init_fix.get_variable_data('u')
# Comparison tests
N.testing.assert_array_almost_equal(dx_fix.x, dx.x)
N.testing.assert_array_almost_equal(dv_fix.x, dv.x)
N.testing.assert_array_almost_equal(x_fix.x, x.x)
N.testing.assert_array_almost_equal(v_fix.x, v.x)
N.testing.assert_array_almost_equal(u_fix.x, u.x)
if False:
plt.figure(1)
plt.subplot(2, 1, 1)
plt.plot(x.t, x.x, 'r')
plt.hold(True)
plt.plot(v.t, v.x, 'r')
plt.grid(True)
plt.subplot(2, 1, 2)
plt.plot(u.t, u.x, 'r')
plt.grid(True)
def setUp(self):
resfile = os.path.join(get_files_path(), 'Results',
'BlockingInitPack_M_init_result.txt')
self.res_init = ResultDymolaTextual(resfile)
self.n_e = 5 # Number of elements
self.hs = N.ones(self.n_e)*1./self.n_e # Equidistant points
self.n_cp = 3; # Number of collocation points in each element
# Blocking factors for control parametrization
blocking_factors=N.ones(self.n_e,dtype=N.int)
self.nlp = NLPCollocationLagrangePolynomials(self.opt_model,
self.n_e,self.hs,self.n_cp,blocking_factors)
self.nlp.set_initial_from_dymola(self.res_init, self.hs, 0., 10.)
self.nlp.export_result_dymola("qwe.txt")
self.res_init2 = ResultDymolaTextual('qwe.txt')