Base_state Class Reference

Inheritance diagram for Base_state:

Collaboration diagram for Base_state:

Public Member Functions
def	__init__ (self, signal_number, state_number, signal_cache_limit=1000, state_cache_limit=1000, signal_names=[], state_names=[])
def	get_states (self)
def	measure (self, List cur_signals)
def	parse (self, cur_signals)
def	update (self, cur_signals, cur_states)
def	visualize_state_evolving (self, fh=None)
Public Member Functions inherited from Base
def	__init__ (self)
def	adapt (self)
def	correct (self)
def	measure (self, signal)
def	predict (self)
def	process (self, signal)

Public Attributes
	f_idx
	signal_cache_count
	signal_cache_limit
	signal_names
	signal_number
	signals_cache
	state_cache_count
	state_cache_limit
	state_names
	state_number
	states_cache
Public Attributes inherited from Base
	x

Detailed Description

The base class for the human state estimator.

@param[in]  signal_number               how many signals will be used as input
@param[in]  state_number                how many states will be estimated

@param[in]  signal_cache_limit            How many previous signals to be stored. Default:1000
@param[in]  state_cache_limit             How many previous states to be stored. Default:1000

@param[in]  signal_names                A list of signal names. If empty then will assign signal_1, signal_2, ...
@param[in]  state_names                 A list of state names. If empty then will assign state_1, state_2, ...

Constructor & Destructor Documentation

__init__()

def __init__	(		self,
			signal_number,
			state_number,
			signal_cache_limit = 1000,
			state_cache_limit = 1000,
			signal_names = [],
			state_names = []
	)

Member Function Documentation

get_states()

def get_states

(

self

)

Get the latest state.

Returns:
    latest_state (binary, (N_state, )).         The last binary states. N_states is the number of the state

measure()

def measure	(		self,
		List	cur_signals
	)

The workflow of the signal2state 

@param[in]  cur_signals.            An array of the signals, each element of which represents the new income of different signal types

parse()

def parse	(		self,
			cur_signals
	)

Parse the state out of the signals. Return the states

update()

def update	(		self,
			cur_signals,
			cur_states
	)

Update the cache states with new ones

visualize_state_evolving()

def visualize_state_evolving	(		self,
			fh = None
	)

Monitor the state process by plotting a line chart using the plt.
Will only display the cached states, which is the latest state_cache_limit states

@param[in] fh                   The figure handle. Default is None. When set to None then a new figure will be created
                                Note that the fh will be stored at the first time being used, and all future drawing will be on that figure

Member Data Documentation

f_idx

f_idx

signal_cache_count

signal_cache_count

signal_cache_limit

signal_cache_limit

signal_names

signal_names

signal_number

signal_number

signals_cache

signals_cache

state_cache_count

state_cache_count

state_cache_limit

state_cache_limit

state_names

state_names

state_number

state_number

states_cache

states_cache

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The documentation for this class was generated from the following file:

• /local/source/python/Surveillance/Surveillance/activity/state.py