imhr.r33._nslr_hmm¶

@purpose: Eyetracking classification Module.   
@date: Created on Sat May 1 15:12:38 2019   
@author: Semeon Risom   
@email: semeon.risom@gmail.com   
@url: https://semeon.io/d/R33-analysis   

Classes

ObservationModel(dists) Include this - Semeon

Functions

`gaze_observation_model`()	Include this - Semeon
`gaze_transition_model`()	Include this - Semeon
`safelog`(x)	Include this - Semeon
`viterbi`(initial_probs, transition_probs, …)	Include this - Semeon
`forward_backward`(transition_probs, observations)	Include this - Semeon
`dataset_features`(data, \\nslrargs)
`transition_estimates`(obs, trans, forward, …)
`reestimate_observations_baum_welch`((sessions)	Include this - Semeon
`reestimate_observations_viterbi_robust`((sessions)	Include this - Semeon
`segment_features`(segments[, outliers])	Include this - Semeon
`classify_segments`((segments[, …])	Include this - Semeon
`classify_gaze`(ts, xs, \\kwargs)	Include this - Semeon

class imhr.r33._nslr_hmm.ObservationModel(dists)[source]¶

Bases: object

Include this - Semeon

Methods

Methods

`classify`(self, d)	Include this - Semeon
`dist`(self, cls)	Include this - Semeon
`liks`(self, d)	Include this - Semeon

`classify`(self, d)	Include this - Semeon
`dist`(self, cls)	Include this - Semeon
`liks`(self, d)	Include this - Semeon

liks(self, d)[source]¶: Include this - Semeon

classify(self, d)[source]¶: Include this - Semeon

dist(self, cls)[source]¶: Include this - Semeon

imhr.r33._nslr_hmm.gaze_observation_model()[source]¶: Include this - Semeon

imhr.r33._nslr_hmm.gaze_transition_model()[source]¶: Include this - Semeon

imhr.r33._nslr_hmm.safelog(x)[source]¶: Include this - Semeon

imhr.r33._nslr_hmm.viterbi(initial_probs, transition_probs, emissions)[source]¶: Include this - Semeon

imhr.r33._nslr_hmm.forward_backward(transition_probs, observations, initial_probs=None)[source]¶: Include this - Semeon

imhr.r33._nslr_hmm.dataset_features(data, **nslrargs)[source]¶

imhr.r33._nslr_hmm.transition_estimates(obs, trans, forward, backward)[source]¶

reestimate_observations_baum_welch(sessions, transition_probs=array([[0.4 , 0.4 , 0. , 0.2 ],
[0.25 , 0.25 , 0.25 , 0.25 ],
[0.33333333, 0. , 0.33333333, 0.33333333],
[0.2 , 0.4 , 0. , 0.4 ]]), observation_model=<imhr.r33._nslr_hmm.ObservationModel object at 0x1a2c452978>, initial_probs=None, estimate_observation_model=True, estimate_transition_model=True, n_iterations=30, plot_process=False): Include this - Semeon

reestimate_observations_viterbi_robust(sessions, transition_probs=array([[0.4 , 0.4 , 0. , 0.2 ],
[0.25 , 0.25 , 0.25 , 0.25 ],
[0.33333333, 0. , 0.33333333, 0.33333333],
[0.2 , 0.4 , 0. , 0.4 ]]), observation_model=<imhr.r33._nslr_hmm.ObservationModel object at 0x1a2c452978>, initial_probs=None, estimate_observation_model=True, estimate_transition_model=True, n_iterations=30, plot_process=False): Include this - Semeon

imhr.r33._nslr_hmm.segment_features(segments, outliers=None)[source]¶: Include this - Semeon

classify_segments(segments, observation_model=<imhr.r33._nslr_hmm.ObservationModel object at 0x1a2c452978>, transition_model=array([[0.4 , 0.4 , 0. , 0.2 ],
[0.25 , 0.25 , 0.25 , 0.25 ],
[0.33333333, 0. , 0.33333333, 0.33333333],
[0.2 , 0.4 , 0. , 0.4 ]]), initial_probabilities=None): Include this - Semeon

imhr.r33._nslr_hmm.classify_gaze(ts, xs, **kwargs)[source]¶: Include this - Semeon