brainpy.dyn.base.Network#

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

Base class to model network objects, an alias of Container.

Network instantiates a network, which is aimed to load neurons, synapses, and other brain objects.

Parameters
  • name (str, Optional) – The network name.

  • monitors (optional, list of str, tuple of str) – The items to monitor.

  • ds_tuple – A list/tuple container of dynamical system.

  • ds_dict – A dict container of dynamical 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.

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.

vars([method, level, include_self])

Collect all variables in this node and the children nodes.

Attributes

global_delay_targets

global_delay_vars

name

steps