Monitors perception channels on the robot arms. More...

Public Member Functions
def	__init__
	Initializes the listeners on the perception topics.
def	begin_monitoring
	Begin monitoring peception data to make sure it doesn't deviate from the model provided.
def	clear_vars
	Initialize variables.
def	collision_detect
def	collision_filtering
def	collision_filtering_mal
def	create_max_min
def	end_monitoring
	Stop capturing perception data.
def	get_zeros
	Generates model functions of all the perceptions over several identical trajectories.
def	load
	Load training data as a pickle with given filename.
def	resample_and_thin_data
def	save
	Save training data as a pickle with given filename.
def	setup_monitoring
	Sets up monitoring parameters.
def	simulate_monitoring
def	start_training
	Begin capturing peception data for all of the listeners.
def	stop_training
	Stop capturing perception data.
Public Attributes
	active
	avg_list
	c
	collide
	collision_sums
	collision_times
	contingency
	cum_avg
	cur_col_time
	cur_mals
	cur_pt
	current_data
	current_zeros
	datasets
	dur_timer
	failure
	locks
	logger
	mals
	min_prob
	model_zeros
	models
	monitor
	noise_dev_default
	noise_dev_dict
	only_pressure
	perception_names
	perceptions
	rate
	sampling_rate
	std_dev_default
	std_dev_dict
	sum_data
	tol_thresh_dict
	transform_dict
	verbose
	window_size
	z_avg
	z_list
	z_rsum
	z_sum
Private Member Functions
def	_gather_perception
def	_monitor_data
def	_stable_summer
def	_sum_values
Private Attributes
	_n
	_zeros

Detailed Description

Monitors perception channels on the robot arms.

Important: rate must be the same for both training and monitoring. Values are gathered timestep by timestep.

Usecase: apm = ArmPerceptionMonitor(0) for trajectory in trajectories: apm.start_training() trajectory.run() trajectory.wait_for_completion() apm.stop_training() mean_function, variance_function = apm.generate_model(...)

Definition at line 302 of file src/kelsey_sandbox/perception_monitor.py.

Constructor & Destructor Documentation

def kelsey_sandbox.perception_monitor.ArmPerceptionMonitor.__init__	(	self,
		arm,
		tf_listener = `None`,
		rate = `0.001`,
		percept_mon_list = `None`,
		model_zeros = `None`
	)

Initializes the listeners on the perception topics.

Parameters:

arm	0 if right, 1 if left
rate	the rate at which the perception should capture states
percept_mon_list	list of perceptions to monitor; if None, do all

Definition at line 310 of file src/kelsey_sandbox/perception_monitor.py.

Member Function Documentation

def kelsey_sandbox.perception_monitor.ArmPerceptionMonitor._gather_perception ( self ) [private]

Definition at line 428 of file src/kelsey_sandbox/perception_monitor.py.

def kelsey_sandbox.perception_monitor.ArmPerceptionMonitor._monitor_data ( self ) [private]

Definition at line 764 of file src/kelsey_sandbox/perception_monitor.py.

def kelsey_sandbox.perception_monitor.ArmPerceptionMonitor._stable_summer	(	self,
		percept,
		data
	)	`[private]`

Definition at line 743 of file src/kelsey_sandbox/perception_monitor.py.

def kelsey_sandbox.perception_monitor.ArmPerceptionMonitor._sum_values ( self ) [private]

Definition at line 607 of file src/kelsey_sandbox/perception_monitor.py.

def kelsey_sandbox.perception_monitor.ArmPerceptionMonitor.begin_monitoring	(	self,
		models = `None`,
		model_zeros = `None`,
		std_dev_dict = `None`,
		noise_dev_dict = `None`,
		duration = `None`,
		std_dev_default = `2.0`,
		noise_dev_default = `0.25`,
		tol_thresh_dict = `None`,
		contingency = `None`,
		window_size = `70`,
		current_zeros = `None`,
		sampling_rate = `1`,
		only_pressure = `False`,
		transform_dict = `None`,
		verbose = `True`,
		collide = `True`
	)

Begin monitoring peception data to make sure it doesn't deviate from the model provided.

TODO DOCS

Parameters:

duration If None, continue capturing until stop is called. Else, stop capturing after duration seconds have passed.

Definition at line 694 of file src/kelsey_sandbox/perception_monitor.py.

def kelsey_sandbox.perception_monitor.ArmPerceptionMonitor.clear_vars ( self )

Initialize variables.

Definition at line 439 of file src/kelsey_sandbox/perception_monitor.py.

def kelsey_sandbox.perception_monitor.ArmPerceptionMonitor.collision_detect	(	self,
		avg_dict
	)

Definition at line 882 of file src/kelsey_sandbox/perception_monitor.py.

def kelsey_sandbox.perception_monitor.ArmPerceptionMonitor.collision_filtering	(	self,
		z
	)

Definition at line 939 of file src/kelsey_sandbox/perception_monitor.py.

def kelsey_sandbox.perception_monitor.ArmPerceptionMonitor.collision_filtering_mal	(	self,
		mal
	)

Definition at line 920 of file src/kelsey_sandbox/perception_monitor.py.

def kelsey_sandbox.perception_monitor.ArmPerceptionMonitor.create_max_min ( self )

Definition at line 662 of file src/kelsey_sandbox/perception_monitor.py.

def kelsey_sandbox.perception_monitor.ArmPerceptionMonitor.end_monitoring ( self )

Stop capturing perception data.

Store output data in datasets list for later statistics. TODO DOCS

Definition at line 853 of file src/kelsey_sandbox/perception_monitor.py.

def kelsey_sandbox.perception_monitor.ArmPerceptionMonitor.get_zeros	(	self,
		time = `4.`
	)

Generates model functions of all the perceptions over several identical trajectories.

Each of the parameters is a dictionary directing perceptions to their parameters.

Parameters:

smooth_wind_dict	the window size of the smoothing function
var_wind_dict	window size of the variance function
var_smooth_wind_dict	window size of the smoothing function on the variance

Returns:: mean function, variance function def generate_models(self, smooth_wind_dict=None, var_wind_dict=None):

Definition at line 592 of file src/kelsey_sandbox/perception_monitor.py.

def kelsey_sandbox.perception_monitor.ArmPerceptionMonitor.load	(	self,
		filename
	)

Load training data as a pickle with given filename.

Parameters:

filename name of the pickle

Definition at line 490 of file src/kelsey_sandbox/perception_monitor.py.

def kelsey_sandbox.perception_monitor.ArmPerceptionMonitor.resample_and_thin_data	(	self,
		monitor_data,
		sample_rate
	)

Definition at line 1088 of file src/kelsey_sandbox/perception_monitor.py.

def kelsey_sandbox.perception_monitor.ArmPerceptionMonitor.save	(	self,
		filename
	)

Save training data as a pickle with given filename.

Parameters:

filename name of the pickle

Definition at line 483 of file src/kelsey_sandbox/perception_monitor.py.

def kelsey_sandbox.perception_monitor.ArmPerceptionMonitor.setup_monitoring	(	self,
		models,
		std_dev_dict = `None`,
		noise_dev_dict = `None`,
		duration = `None`,
		std_dev_default = `2.0`,
		noise_dev_default = `0.25`,
		tol_thresh_dict = `None`,
		contingency = `None`,
		window_size = `70`,
		current_zeros = `None`,
		sampling_rate = `1`,
		transform_dict = `None`,
		verbose = `True`,
		collide = `True`
	)

Sets up monitoring parameters.

Definition at line 618 of file src/kelsey_sandbox/perception_monitor.py.

def kelsey_sandbox.perception_monitor.ArmPerceptionMonitor.simulate_monitoring	(	self,
		monitor_data,
		models = `None`,
		model_zeros = `None`,
		std_dev_dict = `None`,
		noise_dev_dict = `None`,
		duration = `None`,
		std_dev_default = `2.0`,
		noise_dev_default = `0.25`,
		tol_thresh_dict = `None`,
		contingency = `None`,
		window_size = `70`,
		current_zeros = `None`,
		transform_dict = `None`,
		verbose = `True`,
		collide = `True`
	)