brainpy.dyn.base.TwoEndConn#

class brainpy.dyn.base.TwoEndConn(pre, post, conn=None, name=None)[source]#

Base class to model two-end synaptic connections.

Parameters
  • pre (NeuGroup) – Pre-synaptic neuron group.

  • post (NeuGroup) – Post-synaptic neuron group.

  • conn (optional, ndarray, JaxArray, dict, TwoEndConnector) – The connection method between pre- and post-synaptic groups.

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

__init__(pre, post, conn=None, name=None)[source]#

Methods

__init__(pre, post[, conn, name])

check_post_attrs(*attrs)

Check whether post group satisfies the requirement.

check_pre_attrs(*attrs)

Check whether pre group satisfies the requirement.

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