spynnaker.pyNN.models.neuron.input_types package

Module contents

class spynnaker.pyNN.models.neuron.input_types.AbstractInputType(structs: List[Struct], units: Dict[str, str])

Bases: AbstractStandardNeuronComponent

Represents a possible input type for a neuron model (e.g., current).

Parameters:

  • structs – The structures of the component

  • units – The units to use for each parameter

abstractmethod get_global_weight_scale() → float[source]

Get the global weight scaling value.

Returns:

The global weight scaling value

class spynnaker.pyNN.models.neuron.input_types.InputTypeConductance(e_rev_E: float | Iterable[float] | RandomDistribution | ndarray[tuple[Any, ...], dtype[floating]], e_rev_I: float | Iterable[float] | RandomDistribution | ndarray[tuple[Any, ...], dtype[floating]])

Bases: AbstractInputType

The conductance input type.

Parameters:

  • e_rev_E – Reversal potential for excitatory input; \(E^{rev}_e\)

  • e_rev_I – Reversal potential for inhibitory input; \(E^{rev}_i\)

add_parameters(parameters: RangeDictionary[float]) → None[source]

Add the initial values of the parameters to the parameter holder.

Parameters:

parameters – A holder of the parameters

add_state_variables(state_variables: RangeDictionary[float]) → None[source]

Add the initial values of the state variables to the state variables holder.

Parameters:

state_variables – A holder of the state variables

property e_rev_E: float | Iterable[float] | RandomDistribution | ndarray[tuple[Any, ...], dtype[floating]]

\(E_{{rev}_e}\)

property e_rev_I: float | Iterable[float] | RandomDistribution | ndarray[tuple[Any, ...], dtype[floating]]

\(E_{{rev}_i}\)

get_global_weight_scale() → float[source]

Get the global weight scaling value.

Returns:

The global weight scaling value

class spynnaker.pyNN.models.neuron.input_types.InputTypeCurrent

Bases: AbstractInputType

The current input type.

Parameters:

  • structs – The structures of the component

  • units – The units to use for each parameter

add_parameters(parameters: RangeDictionary[float]) → None[source]

Add the initial values of the parameters to the parameter holder.

Parameters:

parameters – A holder of the parameters

add_state_variables(state_variables: RangeDictionary[float]) → None[source]

Add the initial values of the state variables to the state variables holder.

Parameters:

state_variables – A holder of the state variables

get_global_weight_scale() → float[source]

Get the global weight scaling value.

Returns:

The global weight scaling value

class spynnaker.pyNN.models.neuron.input_types.InputTypeDelta

Bases: AbstractInputType

The delta input type.

Parameters:

  • structs – The structures of the component

  • units – The units to use for each parameter

add_parameters(parameters: RangeDictionary[float]) → None[source]

Add the initial values of the parameters to the parameter holder.

Parameters:

parameters – A holder of the parameters

add_state_variables(state_variables: RangeDictionary[float]) → None[source]

Add the initial values of the state variables to the state variables holder.

Parameters:

state_variables – A holder of the state variables

get_global_weight_scale() → float[source]

Get the global weight scaling value.

Returns:

The global weight scaling value