def test_results_gl_uncompressed(self):
p = ex_ssto_moon.ssto_moon('gauss-lobatto', num_seg=10, transcription_order=5,
top_level_jacobian='csc', compressed=False)
p.setup(check=True)
p['phase0.t_initial'] = 0.0
p['phase0.t_duration'] = 500.0
phase = p.model.phase0
p['phase0.states:x'] = phase.interpolate(ys=[0, 350000.0], nodes='state_input')
p['phase0.states:y'] = phase.interpolate(ys=[0, 185000.0], nodes='state_input')
p['phase0.states:vx'] = phase.interpolate(ys=[0, 1627.0], nodes='state_input')
p['phase0.states:vy'] = phase.interpolate(ys=[1.0E-6, 0], nodes='state_input')
p['phase0.states:m'] = phase.interpolate(ys=[50000, 50000], nodes='state_input')
p['phase0.controls:theta'] = phase.interpolate(ys=[1.5, -0.76], nodes='control_input')
p.run_driver()
# Ensure defects are zero
for state in ['x', 'y', 'vx', 'vy', 'm']:
assert_almost_equal(p['phase0.collocation_constraint.defects:{0}'.format(state)],
0.0, decimal=5)
# Ensure time found is the known solution
assert_almost_equal(p['phase0.t_duration'], 481.8, decimal=1)
# Ensure the tangent of theta is (approximately) linear
time = p.model.phase0.get_values('time').flatten()
tan_theta = np.tan(p.model.phase0.get_values('theta').flatten())
coeffs, residuals, _, _, _ = np.polyfit(time, tan_theta, deg=1, full=True)
assert_almost_equal(residuals**2, 0.0, decimal=4)
def test_plot(self):
import matplotlib.pyplot as plt
import dymos.examples.ssto.ex_ssto_moon as ex_ssto_moon
p = ex_ssto_moon.ssto_moon('gauss-lobatto', num_seg=10,
transcription_order=5, top_level_jacobian='csc')
p.setup(check=True)
p['phase0.t_initial'] = 0.0
p['phase0.t_duration'] = 500.0
phase = p.model.phase0
p['phase0.states:x'] = phase.interpolate(ys=[0, 350000.0], nodes='state_input')
p['phase0.states:y'] = phase.interpolate(ys=[0, 185000.0], nodes='state_input')
p['phase0.states:vx'] = phase.interpolate(ys=[0, 1627.0], nodes='state_input')
p['phase0.states:vy'] = phase.interpolate(ys=[1.0E-6, 0], nodes='state_input')
p['phase0.states:m'] = phase.interpolate(ys=[50000, 50000], nodes='state_input')
p['phase0.controls:theta'] = phase.interpolate(ys=[1.5, -0.76], nodes='control_input')
p.run_driver()
##############################
# quick check of the results
##############################
assert_rel_error(self, phase.get_values('y')[-1], 1.85E5, 1e-4)
assert_rel_error(self, phase.get_values('vx')[-1], 1627.0, 1e-4)
assert_rel_error(self, phase.get_values('vy')[-1], 0, 1e-4)
##############################
# Plot the trajectory
##############################
plt.figure(facecolor='white')
plt.plot(phase.get_values('x'), phase.get_values('y'), 'bo')
plt.xlabel('x, m')
plt.ylabel('y, m')
plt.grid()
fig = plt.figure(facecolor='white')
fig.suptitle('results for flat_earth_without_aero')
axarr = fig.add_subplot(2, 1, 1)
axarr.plot(phase.get_values('time'),
np.degrees(phase.get_values('theta')), 'bo')
axarr.set_ylabel(r'$\theta$, deg')
axarr.axes.get_xaxis().set_visible(False)
axarr = fig.add_subplot(2, 1, 2)
axarr.plot(phase.get_values('time'),
np.degrees(phase.get_values('vx')), 'bo', label='$v_x$')
axarr.plot(phase.get_values('time'),
np.degrees(phase.get_values('vy')), 'ro', label='$v_y$')
axarr.set_xlabel('time, s')
axarr.set_ylabel('velocity, m/s')
axarr.legend(loc='best')
plt.show()