SpikeTimeGroup

class brainpy.dyn.SpikeTimeGroup(size, indices, times, spk_type=None, name=None, sharding=None, keep_size=False, mode=None, need_sort=True)

The input neuron group characterized by spikes emitting at given times.

>>> # Get 2 neurons, firing spikes at 10 ms and 20 ms.
>>> SpikeTimeGroup(2, times=[10, 20])
>>> # or
>>> # Get 2 neurons, the neuron 0 fires spikes at 10 ms and 20 ms.
>>> SpikeTimeGroup(2, times=[10, 20], indices=[0, 0])
>>> # or
>>> # Get 2 neurons, neuron 0 fires at 10 ms and 30 ms, neuron 1 fires at 20 ms.
>>> SpikeTimeGroup(2, times=[10, 20, 30], indices=[0, 1, 0])
>>> # or
>>> # Get 2 neurons; at 10 ms, neuron 0 fires; at 20 ms, neuron 0 and 1 fire;
>>> # at 30 ms, neuron 1 fires.
>>> SpikeTimeGroup(2, times=[10, 20, 20, 30], indices=[0, 0, 1, 1])

Parameters:

• size (int, tuple, list) – The neuron group geometry.

• indices (list, tuple, ArrayType) – The neuron indices at each time point to emit spikes.

• times (list, tuple, ArrayType) – The time points which generate the spikes.

• name (str, optional) – The name of the dynamic system.

reset_state(batch_size=None, **kwargs)

Reset function which resets local states in this model.

Simply speaking, this function should implement the logic of resetting of local variables in this node.

See https://brainpy.readthedocs.io/en/latest/tutorial_toolbox/state_resetting.html for details.

update()

The function to specify the updating rule.