brainpy.dyn.channels.leaky.IL#

class brainpy.dyn.channels.leaky.IL(size, keep_size=False, g_max=0.1, E=- 70.0, method=None, name=None, mode=NormalMode)[source]#

The leakage channel current.

Parameters
  • g_max (float) – The leakage conductance.

  • E (float) – The reversal potential.

__init__(size, keep_size=False, g_max=0.1, E=- 70.0, method=None, name=None, mode=NormalMode)[source]#

Methods

__init__(size[, keep_size, g_max, E, ...])

clear_input()

current(V)

get_delay_data(identifier, delay_step, *indices)

Get delay data according to the provided delay steps.

load_states(filename[, verbose])

Load the model states.

nodes([method, level, include_self])

Collect all children nodes.

offline_fit(target, fit_record)

offline_init()

online_fit(target, fit_record)

online_init()

register_delay(identifier, delay_step, ...)

Register delay variable.

register_implicit_nodes(*nodes, **named_nodes)

register_implicit_vars(*variables, ...)

reset(V[, batch_size])

Reset function which reset the whole variables in the model.

reset_local_delays([nodes])

Reset local delay variables.

reset_state(V[, batch_size])

Reset function which reset the states 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(tdi, V)

The function to specify the updating rule.

update_local_delays([nodes])

Update local delay variables.

vars([method, level, include_self])

Collect all variables in this node and the children nodes.

Attributes

global_delay_data

mode

Mode of the model, which is useful to control the multiple behaviors of the model.

name

Name of the model.

varshape