brainpy.dyn.base.TwoEndConn

class brainpy.dyn.base.TwoEndConn(pre, post, conn=None, name=None)

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)

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.
reset_delay(name, delay_target)	Reset the delay variable.
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.
update_delay(name, delay_data)	Update the delay according to the delay data.
vars([method, level, include_self])	Collect all variables in this node and the children nodes.

Attributes

global_delay_vars
name
steps