t_elapse = 0.1 # Simulation time elapsed between each iteration
t_pause = 0.01 # Pause between each iteration
user_input = Sliders() # Instantiate Sliders class
simAnimation = Animation() # Instantiate Animate class
dynam = Dynamics() # Instantiate Dynamics class
t = t_start # Declare time variable to keep track of simulation time elapsed
while t < t_end:
plt.ion() # Make plots interactive
plt.figure(
user_input.fig.number) # Switch current figure to user_input figure
plt.pause(0.001) # Pause the simulation to detect user input
# The dynamics of the model will be propagated in time by t_elapse
# at intervals of t_Ts.
t_temp = t + t_elapse
while t < t_temp:
dynam.propagateDynamics( # Propagate the dynamics of the model in time
user_input.getInputValues())
t += t_Ts # Update time elapsed
plt.figure(
simAnimation.fig.number) # Switch current figure to animation figure
simAnimation.drawSystem( # Update animation with current user input
dynam.Outputs())
# time.sleep(t_pause)
# simAnimation = Animation() # Instantiate Animate class
dynam = Dynamics() # Instantiate Dynamics class
t = t_start # Declare time variable to keep track of simulation time elapsed
while t < t_end:
# Get referenced inputs from signal generators
ref_input = sig_gen.getRefInputs(t)
# The dynamics of the model will be propagated in time by t_elapse
# at intervals of t_Ts.
t_temp = t + t_elapse
while t < t_temp:
states = dynam.Outputs() # Get current states
u = ctrl.getForces(ref_input, states) # Calculate the forces
dynam.propagateDynamics(
u) # Propagate the dynamics of the model in time
t = round(t + t_Ts, 2) # Update time elapsed
# plt.figure(simAnimation.fig.number) # Switch current figure to animation figure
# simAnimation.drawSystem( # Update animation with current user input
# dynam.Outputs())
# plt.pause(0.0001)
# Organizes the new data to be passed to plotGen
new_data = [[ref_input[0], states[0]], [u[1], states[1]], [u[0]]]
plotGen.updateDataHistory(t, new_data)
plt.figure(plotGen.fig.number) # Switch current figure to plotGen figure
