brainpy.dyn.others.SpikeTimeGroup#

class brainpy.dyn.others.SpikeTimeGroup(size, times, indices, need_sort=True, keep_size=False, name=None)[source]#

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, np.ndarray, JaxArray, jax.numpy.ndarray) – The neuron indices at each time point to emit spikes.

  • times (list, tuple, np.ndarray, JaxArray, jax.numpy.ndarray) – The time points which generate the spikes.

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

__init__(size, times, indices, need_sort=True, keep_size=False, name=None)[source]#

Methods

__init__(size, times, indices[, need_sort, ...])

get_delay_data(name, delay_step, *indices)

Get delay data according to the provided delay steps.

ints([method])

Collect all integrators in this node and the children nodes.

load_states(filename[, verbose])

Load the model states.

nodes([method, level, include_self])

Collect all children nodes.

register_delay(name, delay_step, delay_target)

Register delay variable.

register_implicit_nodes(nodes)

register_implicit_vars(variables)

reset()

Reset function which reset the whole variables in the model.

save_states(filename[, variables])

Save the model states.

train_vars([method, level, include_self])

The shortcut for retrieving all trainable variables.

unique_name([name, type_])

Get the unique name for this object.

update(t, dt)

The function to specify the updating rule.

vars([method, level, include_self])

Collect all variables in this node and the children nodes.

Attributes

global_delay_targets

global_delay_vars

name

steps