def test_create_static_html():
# derive simple system
mass, stiffness, damping, gravity = symbols('m, k, c, g')
position, speed = me.dynamicsymbols('x v')
positiond = me.dynamicsymbols('x', 1)
ceiling = me.ReferenceFrame('N')
origin = me.Point('origin')
origin.set_vel(ceiling, 0)
center = origin.locatenew('center', position * ceiling.x)
center.set_vel(ceiling, speed * ceiling.x)
block = me.Particle('block', center, mass)
kinematic_equations = [speed - positiond]
total_force = mass * gravity - stiffness * position - damping * speed
forces = [(center, total_force * ceiling.x)]
particles = [block]
kane = me.KanesMethod(ceiling,
q_ind=[position],
u_ind=[speed],
kd_eqs=kinematic_equations)
kane.kanes_equations(forces, particles)
mass_matrix = kane.mass_matrix_full
forcing_vector = kane.forcing_full
constants = (mass, stiffness, damping, gravity)
coordinates = (position, )
speeds = (speed, )
system = (mass_matrix, forcing_vector, constants, coordinates, speeds)
# integrate eoms
evaluate_ode = generate_ode_function(*system)
x0 = array([0.1, -1.0])
args = {'constants': array([1.0, 1.0, 0.2, 9.8])}
t = linspace(0.0, 10.0, 100)
y = odeint(evaluate_ode, x0, t, args=(args, ))
# create visualization
sphere = Sphere()
viz_frame = VisualizationFrame(ceiling, block, sphere)
scene = Scene(ceiling, origin, viz_frame)
scene.generate_visualization_json([position, speed], list(constants), y,
args['constants'])
# test static dir creation
scene.create_static_html(overwrite=True)
assert os.path.exists('static')
assert os.path.exists('static/index.html')
assert os.path.exists('static/data.json')
# test static dir deletion
scene.remove_static_html(force=True)
assert not os.path.exists('static')
sys.initial_conditions = {
theta: np.deg2rad(90.0),
phi: np.deg2rad(0.5),
omega: 0,
alpha: 0
}
sys.times = np.linspace(0, 10, 500)
x = sys.integrate()
plt.plot(sys.times, x)
plt.legend([sym.latex(s, mode='inline') for s in sys.coordinates + sys.speeds])
# visualize
rod_shape = Cylinder(2 * lA, 0.005, color='red')
plate_shape = Plane(h, w, color='blue')
v1 = VisualizationFrame('rod', A.orientnew('rod', 'Axis', (sym.pi / 2, A.x)),
Ao, rod_shape)
v2 = VisualizationFrame(
'plate', B.orientnew('plate', 'Body', (sym.pi / 2, sym.pi / 2, 0), 'XZX'),
Bo, plate_shape)
scene = Scene(N, No, v1, v2, system=sys)
scene.display()
initial_conditions[6] = mean_of_gait_cycles['Left.Hip.Flexion.Angle'][0]
initial_conditions[7] = -mean_of_gait_cycles['Left.Knee.Flexion.Angle'][0]
initial_conditions[8] = -mean_of_gait_cycles['Left.Ankle.PlantarFlexion.Angle'][0] - np.pi / 2.0
initial_conditions[9] = mean_of_gait_cycles['RightBeltSpeed'][0]
initial_conditions[10] = mean_of_gait_cycles['RGTRO.VelY'][0]
initial_conditions[11] = mean_of_gait_cycles['Trunk.Somersault.Rate'][0]
initial_conditions[12] = mean_of_gait_cycles['Right.Hip.Flexion.Rate'][0]
initial_conditions[13] = -mean_of_gait_cycles['Right.Knee.Flexion.Rate'][0]
initial_conditions[14] = -mean_of_gait_cycles['Right.Ankle.PlantarFlexion.Rate'][0]
initial_conditions[15] = mean_of_gait_cycles['Left.Hip.Flexion.Rate'][0]
initial_conditions[16] = -mean_of_gait_cycles['Left.Knee.Flexion.Rate'][0]
initial_conditions[17] = -mean_of_gait_cycles['Left.Ankle.PlantarFlexion.Rate'][0]
initial_conditions = open_loop_states[:, 0]
# Integrate the equations of motion
trajectories = odeint(rhs, initial_conditions, time_vector, args=(args,))
# Visualize
scene = Scene(ground, origin, *visualization_frames)
scene.generate_visualization_json(coordinates + speeds, constants,
trajectories, args['constants'])
scene.display()
