pangeo_fish.hmm.estimator.EagerEstimator

pangeo_fish.hmm.estimator.EagerEstimator#

class pangeo_fish.hmm.estimator.EagerEstimator(predictor_factory: callable, sigma: float | None = None)#

Estimator to train and predict gaussian random walk hidden markov models

This estimator performs all calculations eagerly and assumes all data can fit into memory.

Parameters:

  • predictor_factory (callable) – Factory for the predictor class. It expects the parameter (“sigma”) as a keyword argument and returns the predictor instance.

  • sigma (float, optional) – The primary model parameter: the standard deviation of the distance per time unit traveled by the fish, in the same unit as the grid coordinates.

__init__(predictor_factory: callable, sigma: float | None = None) → None#

Methods

__init__(predictor_factory[, sigma])

decode(X[, states, mode, spatial_dims, ...])

Decode the state sequence from the selected model and the data

predict_proba(X, *[, spatial_dims, ...])

Predict the state probabilities

score(X, *[, spatial_dims, temporal_dims])

Score the fit of the selected model to the data

set_params(**params)

Set the parameters on a new instance

to_dict()

Attributes

predictor

sigma

predictor_factory

Contents