LinearCoupling

experimental.network_dynamics.coupling.LinearCoupling(
    incoming_states=None,
    local_states=None,
    **kwargs,
)

Simple linear coupling function.

Standard linear coupling with gain and offset parameters, implementing the transformation:

\[c = G \cdot \sum_{j} w_{ij} x_j + b\]

where \(w_{ij}\) are the graph weights, \(x_j\) are the incoming states, \(G\) is the global coupling strength, and \(b\) is an offset term.

Parameters

Name	Type	Description	Default
incoming_states	str or list of str	State name(s) to collect from connected nodes (required)	None
local_states	str or list of str	State name(s) from current node (default: [])	None

Attributes

Name	Type	Description
N_OUTPUT_STATES	int	Number of output coupling states: 1
DEFAULT_PARAMS	Bunch	Default parameters: G=1.0 (global coupling strength), b=0.0 (offset/bias)

Examples

>>> # Couple via 'x' state from connected nodes
>>> coupling = LinearCoupling(incoming_states='x', G=1.0)
>>>
>>> # With offset
>>> coupling = LinearCoupling(incoming_states='x', G=0.5, b=0.1)

Methods

Name	Description
post	Apply linear transformation to summed inputs.

post

experimental.network_dynamics.coupling.LinearCoupling.post(
    summed_inputs,
    local_states,
    params,
)

Apply linear transformation to summed inputs.

Parameters

Name	Type	Description	Default
summed_inputs	jnp.ndarray	Summed coupling inputs with shape [n_inputs, n_nodes]	required
local_states	jnp.ndarray	Local states (not used)	required
params	Bunch	Parameters with G (coupling strength) and b (offset)	required

Returns

Name	Type	Description
	jnp.ndarray	Transformed coupling with shape [n_inputs, n_nodes]