replay_trajectory_classification.likelihoods.multiunit_likelihood_integer

Estimates a marked point process likelihood where the marks are features of the spike waveform. Mark features are int16.

Marks are converted to integers and KDE uses hash tables to compute Gaussian kernels.

Functions

estimate_intensity	Calculates intensity.
estimate_log_intensity	Calculates intensity in log space.
estimate_log_joint_mark_intensity	Finds the joint intensity of the marks and positions in log space.
estimate_multiunit_likelihood_integer	Estimates the likelihood of position bins given multiunit marks.
estimate_position_density	Estimates a kernel density estimate over position bins using Euclidean distances.
estimate_position_distance	Estimates the Euclidean distance between positions and position bins.
fit_multiunit_likelihood_integer	Fits the clusterless place field model.
gaussian_pdf	Compute the value of a Gaussian probability density function at x with given mean and sigma.
normal_pdf_integer_lookup	Fast density evaluation for integers by precomputing a hash table of values.