brainpy.dyn.base.Container#

class brainpy.dyn.base.Container(*ds_tuple, name=None, **ds_dict)[source]#

Container object which is designed to add other instances of DynamicalSystem.

Parameters

  • steps (tuple of function, tuple of str, dict of (str, function), optional) – The step functions.

  • monitors (tuple, list, Monitor, optional) – The monitor object.

  • name (str, optional) – The object name.

  • show_code (bool) – Whether show the formatted code.

  • ds_dict (dict of (str, )) – The instance of DynamicalSystem with the format of “key=dynamic_system”.

__init__(*ds_tuple, name=None, **ds_dict)[source]#

Methods

__init__(*ds_tuple[, name])

get_delay_data(name, delay_step, *indices)

Get delay data according to the provided delay steps.

has(**children_cls)

The aggressive operation to gather master and children classes.

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)

Step function of a network.

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