replay_trajectory_classification.likelihoods.multiunit_likelihood.estimate_position_density#

estimate_position_density(place_bin_centers: ndarray, positions: ndarray, position_std: ndarray, block_size: int = 100) → ndarray[source]#

Estimates a kernel density estimate over position bins using Euclidean distances.

Parameters:

place_bin_centers (np.ndarray, shape (n_position_bins, n_position_dims))
positions (np.ndarray, shape (n_time, n_position_dims))
position_std (float or array_like, shape (n_position_dims,))

Returns:

position_density

Return type:

np.ndarray, shape (n_position_bins,)