Module se :: Class StateEstimator

Class StateEstimator

sm.SM --+
        |
       StateEstimator

Known Subclasses:

StateEstimatorTriggered

A state machine that performs state estimation, based on an input stream of (observation, input) pairs)and a stochastic state-machine model. The output at time t is a dist.DDist object, representing the 'belief' distribution P(s | i_0, ... i_t, o_0, ..., o_t)

Instance Methods

__init__(self, model, verbose=False)

getNextValues(self, state, inp)
Default version of this method.

Inherited from sm.SM: check, doTraceTasks, done, getStartState, guaranteeName, isDone, printDebugInfo, run, start, step, transduce, transduceF

Class Variables
Inherited from `sm.SM`: `legalInputs`, `name`

Instance Variables
	startState The state of this machine is the same as its output: the distribution over states of the subject machine given the input sequence so far; the start state of this machine is the starting distribution of the subject machine.

Method Details

init(self, model, verbose=False)
(Constructor)

Parameters:

model - a ssm.StochasticStateMachine object
verbose - if True, prints out intermediate values

getNextValues(self, state, inp)

Default version of this method. If a subclass only defines getNextState, then we assume that the output of the machine is the same as its next state.

Parameters:

state - Distribution over states of the subject machine, represented as a dist.Dist object
inp - A pair (o, i) of the observation (output) and input of the subject machine on this time step.

Overrides: sm.SM.getNextValues

Class StateEstimator

__init__(self, model, verbose=False) (Constructor)

getNextValues(self, state, inp)

init(self, model, verbose=False)
(Constructor)