brainpy.dyn.rates.AdditiveCoupling
brainpy.dyn.rates.AdditiveCoupling#
- class brainpy.dyn.rates.AdditiveCoupling(coupling_var, target_var, conn_mat, delay_steps=None, initial_delay_data=None, name=None)[source]#
Additive coupling.
This class simulates the model of:
coupling = g * delayed_coupling_var1 output_var += coupling
- Parameters
coupling_var (Variable) – The coupling variable, used for delay.
target_var (Variable, sequence of Variable) – The target variables to output.
conn_mat (JaxArray, ndarray) – The connection matrix.
delay_steps (int, JaxArray, ndarray) – The matrix of delay time steps. Must be int.
initial_delay_data (Initializer, Callable) – The initializer of the initial delay data.
name (str) – The name of the model.
- __init__(coupling_var, target_var, conn_mat, delay_steps=None, initial_delay_data=None, name=None)[source]#
Methods
__init__
(coupling_var, target_var, conn_mat)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