def main(run_simulations=True, parallel=False):
"""Main function that runs all the exercises."""
save = save_plots()
pylog.info('Running network')
run_network(plot=not save)
pylog.info('Running simulation exercises')
arguments = []
arguments = (['example', '8b', '8c', '8d1', '8d2', '8e', '8f']
if run_simulations else [])
if parallel:
pool = Pool(processes=4)
pool.map(exercise_all, [[arg] for arg in arguments])
else:
exercise_all(arguments=arguments)
pylog.info('Plotting simulation results')
plot_results(plot=not save)
def main():
"""Main function that runs all the exercises."""
pylog.info('Running network')
save = save_plots()
run_network(plot=not save)
plt.figure("Positions")
plot_positions(times, link_data)
plt.figure("Trajectory")
plot_trajectory(link_data)
# Plot energy
plot_energy(listamplitude, listphaselag, energymat)
#plt.figure('efficiency')
plot_efficiency(listamplitude, listphaselag, matefficiency)
#Plot vitesse
#plt.figure('Vitesse')
plot_vitesse(listamplitude, listphaselag, vitessemat)
plot_spine_angle(times, joints_data)
# Show plots
if plot:
plt.show()
else:
save_figures()
if __name__ == '__main__':
main(36,
np.linspace(0.0, 0.4, 6),
np.linspace(0., 0.4, 6),
plot=not save_plots())
# Load data
# 8b
#efficient_index = exercise_8b_plot_gridsearch()
#plot_efficient_behaviour(efficient_index)
# 8c
#efficient_index = exercise_8c_plot_gridsearch()
#plot_efficient_behaviour_8c(efficient_index)
# 8d
#plot_phase_angle_trajectory('exercise_8d',1)
#plot_phase_angle_trajectory('exercise_8d',2)
# 8f
#plot_8f1()
#plot_8f2()
# 8g
#plot_8g()
# Show plots
if plot:
plt.show()
else:
save_figures()
if __name__ == '__main__':
main(plot=not save_plots())
with open('./logs/example/simulation_1.pickle', 'rb') as param_file:
parameters = pickle.load(param_file)
print(filename)
times = data.times
timestep = times[1] - times[0] # Or parameters.timestep
osc_phases = np.asarray(data.state.phases_all())
osc_amplitudes = np.asarray(data.state.amplitudes_all())
links_positions = np.asarray(data.sensors.gps.urdf_positions())
head_positions = np.asarray(links_positions[:, 0, :])
tail_positions = np.asarray(links_positions[:, 10, :])
joints_positions = np.asarray(
data.sensors.proprioception.positions_all())
joints_velocities = np.asarray(
data.sensors.proprioception.velocities_all())
joints_torques = np.asarray(
data.sensors.proprioception.motor_torques())
plt.figure("Exercise 8d2 - salamandra moves backwards")
plt.title("Exercise 8d2 - salamandra moves backwards")
plot_trajectory(head_positions)
# Show plots
if plot:
plt.show()
else:
save_figures()
if __name__ == '__main__':
main_2(plot=not save_plots())
