jaxsnn.event.from_nir_data.TimeGriddedData

class jaxsnn.event.from_nir_data.TimeGriddedData(data: numpy.ndarray, dt: float)

Bases: object

Time gridded data of shape (n_samples, n_time_steps, n_neurons) with binary entries (0 or 1) indicating whether a neuron spiked at a particular time step dt.

Parameters

data – Array of shape (n_samples, n_time_steps, n_neurons) with binary entries
dt – Time step size

__init__(data: numpy.ndarray, dt: float): Initialize self. See help(type(self)) for accurate signature.

Methods

__init__(data, dt)

Initialize self.

to_event(n_spikes[, time_shift])

params n_spikes: Maximum number of spikes stored for each neuron.

Attributes

property shape

to_event(n_spikes: int, time_shift: float = 0.0)

Params n_spikes: Maximum number of spikes stored for each neuron.
Params time_shift: Shift the spike times by this value. Must be in interval [0, dt].