print
print "Last 10 hidden states in the second-best MAP estimate:"
for time_step in range(num_time_steps - 10, num_time_steps):
if estimated_states2[time_step] is None:
print 'Missing'
else:
print estimated_states2[time_step]
print
print "Number of differences between MAP estimate and true hidden " + \
"states:", \
robot.compute_number_of_differences(estimated_states,
hidden_states)
print "Number of differences between second-best MAP estimate and " + \
"true hidden states:", \
robot.compute_number_of_differences(estimated_states2,
hidden_states)
print "Number of differences between MAP and second-best MAP " + \
"estimates:", \
robot.compute_number_of_differences(estimated_states,
estimated_states2)
# display
if use_graphics:
app = graphics.playback_positions(hidden_states,
observations,
estimated_states)
app.mainloop()
print "Last 10 hidden states in the MAP estimate:"
for time_step in range(num_time_steps - 10, num_time_steps):
if estimated_states[time_step] is None:
print 'Missing'
else:
print estimated_states[time_step]
print
difference = 0
for time_step in range(num_time_steps):
if estimated_states[time_step] != hidden_states[time_step]:
difference += 1
print "Number of differences between MAP estimate and true hidden " + \
"states:", difference
mse = robot.compute_average_distance_between(estimated_states,
hidden_states)
print "Mean distance between MAP estimate and true hidden states:", mse
# display
if use_graphics:
# Don't run the GUI for too long
gui_limit_steps = 100
app = graphics.playback_positions(hidden_states[:gui_limit_steps],
observations[:gui_limit_steps],
estimated_states[:gui_limit_steps],
marginals[:gui_limit_steps])
app.mainloop()
rover.observation_model,
observations)
print('\n')
print("Last 10 hidden states in the MAP estimate:")
for time_step in range(num_time_steps - 10, num_time_steps):
print(estimated_states[time_step], "for z",time_step)
fb_error = Pe_fb(marginals,hidden_states)
v_error = Pe_v(estimated_states,hidden_states)
print(" Error due to forward-backward is",fb_error)
print(" Error due to viterbi is",v_error)
#check for invalid sequence
# for time_step in range(1, num_time_steps):
# print(marginals[time_step].get_mode(), "for z",time_step)
# if you haven't complete the algorithms, to use the visualization tool
# let estimated_states = [None]*num_time_steps, marginals = [None]*num_time_steps
# estimated_states = [None]*num_time_steps
# marginals = [None]*num_time_steps
if enable_graphics:
app = graphics.playback_positions(hidden_states,
observations,
estimated_states,
marginals)
app.mainloop()
def main():
# flags
make_some_observations_missing = False
use_graphics = True
need_to_generate_data = True
# parse command line arguments
for arg in sys.argv[1:]:
if arg == '--missing':
make_some_observations_missing = True
elif arg == '--nographics':
use_graphics = False
elif arg.startswith('--load='):
filename = arg[7:]
hidden_states, observations = robot.load_data(filename)
need_to_generate_data = False
num_time_steps = len(hidden_states)
# if no data is loaded, then generate new data
if need_to_generate_data:
num_time_steps = 100
hidden_states, observations = \
generate_data(num_time_steps,
make_some_observations_missing)
print('Running forward-backward...')
marginals = forward_backward(observations)
print("\n")
timestep = 2
print("Most likely parts of marginal at time %d:" % (timestep))
if marginals[timestep] is not None:
print(
sorted(marginals[timestep].items(),
key=lambda x: x[1],
reverse=True)[:10])
else:
print('*No marginal computed*')
print("\n")
print('Running Viterbi...')
estimated_states = Viterbi(observations)
print("\n")
print("Last 10 hidden states in the MAP estimate:")
for time_step in range(num_time_steps - 10 - 1, num_time_steps):
if estimated_states[time_step] is None:
print('Missing')
else:
print(estimated_states[time_step])
print("\n")
print('Finding second-best MAP estimate...')
estimated_states2 = second_best(observations)
print("\n")
print("Last 10 hidden states in the second-best MAP estimate:")
for time_step in range(num_time_steps - 10 - 1, num_time_steps):
if estimated_states2[time_step] is None:
print('Missing')
else:
print(estimated_states2[time_step])
print("\n")
difference = 0
difference_time_steps = []
for time_step in range(num_time_steps):
if estimated_states[time_step] != hidden_states[time_step]:
difference += 1
difference_time_steps.append(time_step)
print(
"Number of differences between MAP estimate and true hidden " +
"states:", difference)
if difference > 0:
print("Differences are at the following time steps: " + ", ".join(
["%d" % time_step for time_step in difference_time_steps]))
print("\n")
difference = 0
difference_time_steps = []
for time_step in range(num_time_steps):
if estimated_states2[time_step] != hidden_states[time_step]:
difference += 1
difference_time_steps.append(time_step)
print(
"Number of differences between second-best MAP estimate and " +
"true hidden states:", difference)
if difference > 0:
print("Differences are at the following time steps: " + ", ".join(
["%d" % time_step for time_step in difference_time_steps]))
print("\n")
difference = 0
difference_time_steps = []
for time_step in range(num_time_steps):
if estimated_states[time_step] != estimated_states2[time_step]:
difference += 1
difference_time_steps.append(time_step)
print(
"Number of differences between MAP and second-best MAP " +
"estimates:", difference)
if difference > 0:
print("Differences are at the following time steps: " + ", ".join(
["%d" % time_step for time_step in difference_time_steps]))
print("\n")
# display
if use_graphics:
app = graphics.playback_positions(hidden_states, observations,
estimated_states, marginals)
app.mainloop()