bsfit.nodes.models.utils.get_proba_percept¶

bsfit.nodes.models.utils.get_proba_percept(stim_mean: pandas.core.series.Series, params: dict, k_llh: numpy.ndarray, k_prior: numpy.ndarray, k_card: float, prior_tail: float, p_rand: float)[source]¶

get the percept probability density

Parameters

stim_mean (pd.Series) – the stimulus features

params (dict) –

the parameters:

params: {
    "task": {
        "fixed_params": the task fixed parameters
        },
    "model": {
        "fixed_params": the model fixed parameters
        "init_params": the model initial parameters
    }

k_llh (np.ndarray) – the likelihood concentrations
k_prior (np.ndarray) – the prior concentrations
k_card (float) – the cardinal prior concentration
prior_tail (float) – the tail of the prior
p_rand (float) – the probability of random lapse

Raises

ValueError – the percept probabilities do not sum to 1

Returns

the percept probabilities and calculated variables

Return type

(dict)