pangeo_fish.hmm.estimator.EagerEstimator.predict_proba

pangeo_fish.hmm.estimator.EagerEstimator.predict_proba#

EagerEstimator.predict_proba(X, *, spatial_dims=None, temporal_dims=None)#

Predict the state probabilities

This is done by applying the forward-backward algorithm to the data.

Parameters:

  • X (xarray.Dataset) – The emission probability maps. The dataset should contain these variables:

    • initial, the initial probability map

    • pdf, the emission probabilities

    • mask, a mask to select ocean pixels

    Due to the convolution method we use today, we can’t pass np.nan, thus we send x.fillna(0), but drop the values whihch are less than 0 and put them back to np.nan when we return the value.

  • spatial_dims (list of hashable, optional) – The spatial dimensions of the dataset.

  • temporal_dims (list of hashable, optional) – The temporal dimensions of the dataset.

Returns:

state_probabilities (xarray.DataArray) – The computed state probabilities

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