elephant.spike_train_generation.NonStationaryGammaProcess¶

class elephant.spike_train_generation.NonStationaryGammaProcess(rate_signal: AnalogSignal, shape_factor: float)[source]¶

Generates spike trains whose spikes are realizations of a non-stationary Gamma process with the given rate-signal.

Parameters:

rate_signalneo.AnalogSignal: A neo.AnalogSignal representing the rate profile evolving over time.Its values have all to be >=0. The generated spike trains will have t_start = rate.t_start and t_stop = rate.t_stop
shape_factorfloat: The shape parameter of the gamma distribution.

Raises:

ValueError: If rate_signal is not a neo AnalogSignal If rate_signal contains a negative value. If rate_signal is empty.

Methods

`__init__`(rate_signal, shape_factor)
`generate_n_spiketrains`(n_spiketrains[, as_array])	Generates a list of spike trains.
`generate_spiketrain`([as_array])	Generates a single spike train.

Attributes

`t_start`	t_start quantity; there are no spike times below this value.
`t_stop`	t_stop quantity; there are no spike times above this value.