pynn_brainscales.brainscales2.standardmodels.cells.SpikeSourcePoisson

class pynn_brainscales.brainscales2.standardmodels.cells.SpikeSourcePoisson(start, rate, duration)

Bases: pynn_brainscales.brainscales2.standardmodels.cells_base.ExternalNeuron, pyNN.standardmodels.cells.SpikeSourcePoisson

Spike source, generating spikes according to a Poisson process.

__init__(start, rate, duration)

Initialize self. See help(type(self)) for accurate signature.

Methods

__init__(start, rate, duration)	Initialize self.
can_record(variable[, location])
generate_input_data(population, experiment, …)	Generate input data for this population.
generate_vertex(population)	Generate vertex representation for this population.
get_spike_times()	When this function is called for the first time, the spike times for a Poisson stimulation are calculated and saved, so that all neurons connected to it receive the same stimulation.

Attributes

recordable
translations

can_record(variable: str, location=None) → bool

generate_input_data(population: pyNN.common.populations.Population, experiment: pygrenade_vx.network.abstract.frontend.ExperimentSnippet, snippet_begin_time: float, snippet_end_time: float) → Dict[int, pygrenade_common.PortData]

Generate input data for this population. :param population: Population featuring this cell’s celltype :param experiment: Experiment snippet to generate data for :param snippet_begin_time: Begin time of snippet :param snippet_end_time: End time of snippet :return: Population input data

static generate_vertex(population: pyNN.common.populations.Population) → pygrenade_common.Population

Generate vertex representation for this population. :param population: Population featuring this cell’s celltype :return: Population vertex

get_spike_times() → List[numpy.ndarray]

When this function is called for the first time, the spike times for a Poisson stimulation are calculated and saved, so that all neurons connected to it receive the same stimulation. When a parameter was changed (compared to the last calculation of the spike time), the times are recalculated.

Returns

(unsorted) spike times for each neuron in the population.

recordable: Final[List[str]] = ['spikes']

translations = {'duration': {'forward_transform': 'duration', 'reverse_transform': 'duration', 'translated_name': 'duration', 'type': 'simple'}, 'rate': {'forward_transform': 'rate', 'reverse_transform': 'rate', 'translated_name': 'rate', 'type': 'simple'}, 'start': {'forward_transform': 'start', 'reverse_transform': 'start', 'translated_name': 'start', 'type': 'simple'}}