Object used for specifying a neuronal network model. More...

#include <modelSpec.h>

Inheritance diagram for ModelSpec:

Public Types
typedef std::map< std::string, NeuronGroupInternal >::value_type	NeuronGroupValueType

typedef std::map< std::string, SynapseGroupInternal >::value_type	SynapseGroupValueType

Public Member Functions
	ModelSpec ()

	ModelSpec (const ModelSpec &)=delete

ModelSpec &	operator= (const ModelSpec &)=delete

	~ModelSpec ()

void	setName (const std::string &name)
	Method to set the neuronal network model name. More...

void	setPrecision (FloatType)
	Set numerical precision for floating point. More...

void	setTimePrecision (TimePrecision timePrecision)
	Set numerical precision for time. More...

void	setDT (double dt)
	Set the integration step size of the model. More...

void	setTiming (bool timingEnabled)
	Set whether timers and timing commands are to be included. More...

void	setSeed (unsigned int rngSeed)
	Set the random seed (disables automatic seeding if argument not 0). More...

void	setDefaultVarLocation (VarLocation loc)
	What is the default location for model state variables? More...

void	setDefaultExtraGlobalParamLocation (VarLocation loc)
	What is the default location for model extra global parameters? More...

void	setDefaultSparseConnectivityLocation (VarLocation loc)
	What is the default location for sparse synaptic connectivity? More...

void	setMergePostsynapticModels (bool merge)
	Should compatible postsynaptic models and dendritic delay buffers be merged? More...

const std::string &	getName () const
	Gets the name of the neuronal network model. More...

const std::string &	getPrecision () const
	Gets the floating point numerical precision. More...

std::string	getTimePrecision () const
	Gets the floating point numerical precision used to represent time. More...

double	getDT () const
	Gets the model integration step size. More...

unsigned int	getSeed () const
	Get the random seed. More...

bool	isTimingEnabled () const
	Are timers and timing commands enabled. More...

unsigned int	getNumLocalNeurons () const
	How many neurons are simulated locally in this model. More...

unsigned int	getNumRemoteNeurons () const
	How many neurons are simulated remotely in this model. More...

unsigned int	getNumNeurons () const
	How many neurons make up the entire model. More...

NeuronGroup *	findNeuronGroup (const std::string &name)
	Find a neuron group by name. More...

template<typename NeuronModel >
NeuronGroup *	addNeuronPopulation (const std::string &name, unsigned int size, const NeuronModel *model, const typename NeuronModel::ParamValues &paramValues, const typename NeuronModel::VarValues &varInitialisers, int hostID=0)
	Adds a new neuron group to the model using a neuron model managed by the user. More...

template<typename NeuronModel >
NeuronGroup *	addNeuronPopulation (const std::string &name, unsigned int size, const typename NeuronModel::ParamValues &paramValues, const typename NeuronModel::VarValues &varInitialisers, int hostID=0)
	Adds a new neuron group to the model using a singleton neuron model created using standard DECLARE_MODEL and IMPLEMENT_MODEL macros. More...

SynapseGroup *	findSynapseGroup (const std::string &name)
	Find a synapse group by name. More...

template<typename WeightUpdateModel , typename PostsynapticModel >
SynapseGroup *	addSynapsePopulation (const std::string &name, SynapseMatrixType mtype, unsigned int delaySteps, const std::string &src, const std::string &trg, const WeightUpdateModel wum, const typename WeightUpdateModel::ParamValues &weightParamValues, const typename WeightUpdateModel::VarValues &weightVarInitialisers, const typename WeightUpdateModel::PreVarValues &weightPreVarInitialisers, const typename WeightUpdateModel::PostVarValues &weightPostVarInitialisers, const PostsynapticModel psm, const typename PostsynapticModel::ParamValues &postsynapticParamValues, const typename PostsynapticModel::VarValues &postsynapticVarInitialisers, const InitSparseConnectivitySnippet::Init &connectivityInitialiser=uninitialisedConnectivity())
	Adds a synapse population to the model using weight update and postsynaptic models managed by the user. More...

template<typename WeightUpdateModel , typename PostsynapticModel >
SynapseGroup *	addSynapsePopulation (const std::string &name, SynapseMatrixType mtype, unsigned int delaySteps, const std::string &src, const std::string &trg, const typename WeightUpdateModel::ParamValues &weightParamValues, const typename WeightUpdateModel::VarValues &weightVarInitialisers, const typename PostsynapticModel::ParamValues &postsynapticParamValues, const typename PostsynapticModel::VarValues &postsynapticVarInitialisers, const InitSparseConnectivitySnippet::Init &connectivityInitialiser=uninitialisedConnectivity())
	Adds a synapse population to the model using singleton weight update and postsynaptic models created using standard DECLARE_MODEL and IMPLEMENT_MODEL macros. More...

template<typename WeightUpdateModel , typename PostsynapticModel >
SynapseGroup *	addSynapsePopulation (const std::string &name, SynapseMatrixType mtype, unsigned int delaySteps, const std::string &src, const std::string &trg, const typename WeightUpdateModel::ParamValues &weightParamValues, const typename WeightUpdateModel::VarValues &weightVarInitialisers, const typename WeightUpdateModel::PreVarValues &weightPreVarInitialisers, const typename WeightUpdateModel::PostVarValues &weightPostVarInitialisers, const typename PostsynapticModel::ParamValues &postsynapticParamValues, const typename PostsynapticModel::VarValues &postsynapticVarInitialisers, const InitSparseConnectivitySnippet::Init &connectivityInitialiser=uninitialisedConnectivity())
	Adds a synapse population to the model using singleton weight update and postsynaptic models created using standard DECLARE_MODEL and IMPLEMENT_MODEL macros. More...

CurrentSource *	findCurrentSource (const std::string &name)
	Find a current source by name. More...

template<typename CurrentSourceModel >
CurrentSource *	addCurrentSource (const std::string &currentSourceName, const CurrentSourceModel *model, const std::string &targetNeuronGroupName, const typename CurrentSourceModel::ParamValues &paramValues, const typename CurrentSourceModel::VarValues &varInitialisers)
	Adds a new current source to the model using a current source model managed by the user. More...

template<typename CurrentSourceModel >
CurrentSource *	addCurrentSource (const std::string &currentSourceName, const std::string &targetNeuronGroupName, const typename CurrentSourceModel::ParamValues &paramValues, const typename CurrentSourceModel::VarValues &varInitialisers)
	Adds a new current source to the model using a singleton current source model created using standard DECLARE_MODEL and IMPLEMENT_MODEL macros. More...

Protected Member Functions
void	finalize ()
	Finalise model. More...

std::string	scalarExpr (double) const
	Get the string literal that should be used to represent a value in the model's floating-point type. More...

bool	zeroCopyInUse () const
	Are any variables in any populations in this model using zero-copy memory? More...

const std::map< std::string, NeuronGroupInternal > &	getLocalNeuronGroups () const
	Get std::map containing local named NeuronGroup objects in model. More...

const std::map< std::string, NeuronGroupInternal > &	getRemoteNeuronGroups () const
	Get std::map containing remote named NeuronGroup objects in model. More...

const std::map< std::string, SynapseGroupInternal > &	getLocalSynapseGroups () const
	Get std::map containing local named SynapseGroup objects in model. More...

const std::map< std::string, SynapseGroupInternal > &	getRemoteSynapseGroups () const
	Get std::map containing remote named SynapseGroup objects in model. More...

const std::map< std::string, CurrentSourceInternal > &	getLocalCurrentSources () const
	Get std::map containing local named CurrentSource objects in model. More...

const std::map< std::string, CurrentSourceInternal > &	getRemoteCurrentSources () const
	Get std::map containing remote named CurrentSource objects in model. More...

Detailed Description

Object used for specifying a neuronal network model.

Member Typedef Documentation

◆ NeuronGroupValueType

typedef std::map<std::string, NeuronGroupInternal>::value_type ModelSpec::NeuronGroupValueType

◆ SynapseGroupValueType

typedef std::map<std::string, SynapseGroupInternal>::value_type ModelSpec::SynapseGroupValueType

Constructor & Destructor Documentation

◆ ModelSpec() [1/2]

ModelSpec::ModelSpec ( )

◆ ModelSpec() [2/2]

ModelSpec::ModelSpec ( const ModelSpec & )

delete

◆ ~ModelSpec()

ModelSpec::~ModelSpec ( )

Member Function Documentation

◆ addCurrentSource() [1/2]

template<typename CurrentSourceModel >

CurrentSource* ModelSpec::addCurrentSource	(	const std::string &	currentSourceName,
		const CurrentSourceModel *	model,
		const std::string &	targetNeuronGroupName,
		const typename CurrentSourceModel::ParamValues &	paramValues,
		const typename CurrentSourceModel::VarValues &	varInitialisers
	)

inline

Adds a new current source to the model using a current source model managed by the user.

Template Parameters

CurrentSourceModel type of current source model (derived from CurrentSourceModels::Base).

Parameters

currentSourceName	string containing unique name of current source.
model	current source model to use for current source.
targetNeuronGroupName	string name of the target neuron group
paramValues	parameters for model wrapped in CurrentSourceModel::ParamValues object.
varInitialisers	state variable initialiser snippets and parameters wrapped in CurrentSource::VarValues object.

Returns: pointer to newly created CurrentSource

◆ addCurrentSource() [2/2]

template<typename CurrentSourceModel >

CurrentSource* ModelSpec::addCurrentSource	(	const std::string &	currentSourceName,
		const std::string &	targetNeuronGroupName,
		const typename CurrentSourceModel::ParamValues &	paramValues,
		const typename CurrentSourceModel::VarValues &	varInitialisers
	)

inline

Adds a new current source to the model using a singleton current source model created using standard DECLARE_MODEL and IMPLEMENT_MODEL macros.

Template Parameters

CurrentSourceModel type of neuron model (derived from CurrentSourceModel::Base).

Parameters

currentSourceName	string containing unique name of current source.
targetNeuronGroupName	string name of the target neuron group
paramValues	parameters for model wrapped in CurrentSourceModel::ParamValues object.
varInitialisers	state variable initialiser snippets and parameters wrapped in CurrentSourceModel::VarValues object.

Returns: pointer to newly created CurrentSource

◆ addNeuronPopulation() [1/2]

template<typename NeuronModel >

NeuronGroup* ModelSpec::addNeuronPopulation	(	const std::string &	name,
		unsigned int	size,
		const NeuronModel *	model,
		const typename NeuronModel::ParamValues &	paramValues,
		const typename NeuronModel::VarValues &	varInitialisers,
		int	hostID = `0`
	)

inline

Adds a new neuron group to the model using a neuron model managed by the user.

Template Parameters

NeuronModel type of neuron model (derived from NeuronModels::Base).

Parameters

name	string containing unique name of neuron population.
size	integer specifying how many neurons are in the population.
model	neuron model to use for neuron group.
paramValues	parameters for model wrapped in NeuronModel::ParamValues object.
varInitialisers	state variable initialiser snippets and parameters wrapped in NeuronModel::VarValues object.
hostID	if using MPI, the ID of the node to simulate this population on.

Returns: pointer to newly created NeuronGroup

◆ addNeuronPopulation() [2/2]

template<typename NeuronModel >

NeuronGroup* ModelSpec::addNeuronPopulation	(	const std::string &	name,
		unsigned int	size,
		const typename NeuronModel::ParamValues &	paramValues,
		const typename NeuronModel::VarValues &	varInitialisers,
		int	hostID = `0`
	)

inline

Adds a new neuron group to the model using a singleton neuron model created using standard DECLARE_MODEL and IMPLEMENT_MODEL macros.

Template Parameters

NeuronModel type of neuron model (derived from NeuronModels::Base).

Parameters

name	string containing unique name of neuron population.
size	integer specifying how many neurons are in the population.
paramValues	parameters for model wrapped in NeuronModel::ParamValues object.
varInitialisers	state variable initialiser snippets and parameters wrapped in NeuronModel::VarValues object.
hostID	if using MPI, the ID of the node to simulate this population on.

Returns: pointer to newly created NeuronGroup

◆ addSynapsePopulation() [1/3]

template<typename WeightUpdateModel , typename PostsynapticModel >

SynapseGroup* ModelSpec::addSynapsePopulation	(	const std::string &	name,
		SynapseMatrixType	mtype,
		unsigned int	delaySteps,
		const std::string &	src,
		const std::string &	trg,
		const WeightUpdateModel *	wum,
		const typename WeightUpdateModel::ParamValues &	weightParamValues,
		const typename WeightUpdateModel::VarValues &	weightVarInitialisers,
		const typename WeightUpdateModel::PreVarValues &	weightPreVarInitialisers,
		const typename WeightUpdateModel::PostVarValues &	weightPostVarInitialisers,
		const PostsynapticModel *	psm,
		const typename PostsynapticModel::ParamValues &	postsynapticParamValues,
		const typename PostsynapticModel::VarValues &	postsynapticVarInitialisers,
		const InitSparseConnectivitySnippet::Init &	connectivityInitialiser = `uninitialisedConnectivity()`
	)

inline

Adds a synapse population to the model using weight update and postsynaptic models managed by the user.

Template Parameters

WeightUpdateModel	type of weight update model (derived from WeightUpdateModels::Base).
PostsynapticModel	type of postsynaptic model (derived from PostsynapticModels::Base).

Parameters

name	string containing unique name of neuron population.
mtype	how the synaptic matrix associated with this synapse population should be represented.
delaySteps	integer specifying number of timesteps delay this synaptic connection should incur (or NO_DELAY for none)
src	string specifying name of presynaptic (source) population
trg	string specifying name of postsynaptic (target) population
wum	weight update model to use for synapse group.
weightParamValues	parameters for weight update model wrapped in WeightUpdateModel::ParamValues object.
weightVarInitialisers	weight update model state variable initialiser snippets and parameters wrapped in WeightUpdateModel::VarValues object.
weightPreVarInitialisers	weight update model presynaptic state variable initialiser snippets and parameters wrapped in WeightUpdateModel::VarValues object.
weightPostVarInitialisers	weight update model postsynaptic state variable initialiser snippets and parameters wrapped in WeightUpdateModel::VarValues object.
psm	postsynaptic model to use for synapse group.
postsynapticParamValues	parameters for postsynaptic model wrapped in PostsynapticModel::ParamValues object.
postsynapticVarInitialisers	postsynaptic model state variable initialiser snippets and parameters wrapped in NeuronModel::VarValues object.
connectivityInitialiser	sparse connectivity initialisation snippet used to initialise connectivity for SynapseMatrixConnectivity::SPARSE or SynapseMatrixConnectivity::BITMASK. Typically wrapped with it's parameters using `initConnectivity` function

Returns: pointer to newly created SynapseGroup

◆ addSynapsePopulation() [2/3]

template<typename WeightUpdateModel , typename PostsynapticModel >

SynapseGroup* ModelSpec::addSynapsePopulation	(	const std::string &	name,
		SynapseMatrixType	mtype,
		unsigned int	delaySteps,
		const std::string &	src,
		const std::string &	trg,
		const typename WeightUpdateModel::ParamValues &	weightParamValues,
		const typename WeightUpdateModel::VarValues &	weightVarInitialisers,
		const typename PostsynapticModel::ParamValues &	postsynapticParamValues,
		const typename PostsynapticModel::VarValues &	postsynapticVarInitialisers,
		const InitSparseConnectivitySnippet::Init &	connectivityInitialiser = `uninitialisedConnectivity()`
	)

inline

Adds a synapse population to the model using singleton weight update and postsynaptic models created using standard DECLARE_MODEL and IMPLEMENT_MODEL macros.

Template Parameters

WeightUpdateModel	type of weight update model (derived from WeightUpdateModels::Base).
PostsynapticModel	type of postsynaptic model (derived from PostsynapticModels::Base).

Parameters

name	string containing unique name of neuron population.
mtype	how the synaptic matrix associated with this synapse population should be represented.
delaySteps	integer specifying number of timesteps delay this synaptic connection should incur (or NO_DELAY for none)
src	string specifying name of presynaptic (source) population
trg	string specifying name of postsynaptic (target) population
weightParamValues	parameters for weight update model wrapped in WeightUpdateModel::ParamValues object.
weightVarInitialisers	weight update model state variable initialiser snippets and parameters wrapped in WeightUpdateModel::VarValues object.
postsynapticParamValues	parameters for postsynaptic model wrapped in PostsynapticModel::ParamValues object.
postsynapticVarInitialisers	postsynaptic model state variable initialiser snippets and parameters wrapped in NeuronModel::VarValues object.
connectivityInitialiser	sparse connectivity initialisation snippet used to initialise connectivity for SynapseMatrixConnectivity::SPARSE or SynapseMatrixConnectivity::BITMASK. Typically wrapped with it's parameters using `initConnectivity` function

Returns: pointer to newly created SynapseGroup

◆ addSynapsePopulation() [3/3]

template<typename WeightUpdateModel , typename PostsynapticModel >

SynapseGroup* ModelSpec::addSynapsePopulation	(	const std::string &	name,
		SynapseMatrixType	mtype,
		unsigned int	delaySteps,
		const std::string &	src,
		const std::string &	trg,
		const typename WeightUpdateModel::ParamValues &	weightParamValues,
		const typename WeightUpdateModel::VarValues &	weightVarInitialisers,
		const typename WeightUpdateModel::PreVarValues &	weightPreVarInitialisers,
		const typename WeightUpdateModel::PostVarValues &	weightPostVarInitialisers,
		const typename PostsynapticModel::ParamValues &	postsynapticParamValues,
		const typename PostsynapticModel::VarValues &	postsynapticVarInitialisers,
		const InitSparseConnectivitySnippet::Init &	connectivityInitialiser = `uninitialisedConnectivity()`
	)

inline

Adds a synapse population to the model using singleton weight update and postsynaptic models created using standard DECLARE_MODEL and IMPLEMENT_MODEL macros.

Template Parameters

WeightUpdateModel	type of weight update model (derived from WeightUpdateModels::Base).
PostsynapticModel	type of postsynaptic model (derived from PostsynapticModels::Base).

Parameters

name	string containing unique name of neuron population.
mtype	how the synaptic matrix associated with this synapse population should be represented.
delaySteps	integer specifying number of timesteps delay this synaptic connection should incur (or NO_DELAY for none)
src	string specifying name of presynaptic (source) population
trg	string specifying name of postsynaptic (target) population
weightParamValues	parameters for weight update model wrapped in WeightUpdateModel::ParamValues object.
weightVarInitialisers	weight update model per-synapse state variable initialiser snippets and parameters wrapped in WeightUpdateModel::VarValues object.
weightPreVarInitialisers	weight update model presynaptic state variable initialiser snippets and parameters wrapped in WeightUpdateModel::VarValues object.
weightPostVarInitialisers	weight update model postsynaptic state variable initialiser snippets and parameters wrapped in WeightUpdateModel::VarValues object.
postsynapticParamValues	parameters for postsynaptic model wrapped in PostsynapticModel::ParamValues object.
postsynapticVarInitialisers	postsynaptic model state variable initialiser snippets and parameters wrapped in NeuronModel::VarValues object.
connectivityInitialiser	sparse connectivity initialisation snippet used to initialise connectivity for SynapseMatrixConnectivity::SPARSE or SynapseMatrixConnectivity::BITMASK. Typically wrapped with it's parameters using `initConnectivity` function

Returns: pointer to newly created SynapseGroup

◆ finalize()

void ModelSpec::finalize ( )

protected

Finalise model.

◆ findCurrentSource()

CurrentSource * ModelSpec::findCurrentSource ( const std::string & name )

Find a current source by name.

This function attempts to find an existing current source.

◆ findNeuronGroup()

NeuronGroup* ModelSpec::findNeuronGroup ( const std::string & name )

inline

Find a neuron group by name.

◆ findSynapseGroup()

SynapseGroup * ModelSpec::findSynapseGroup ( const std::string & name )

Find a synapse group by name.

◆ getDT()

double ModelSpec::getDT ( ) const

inline

Gets the model integration step size.

◆ getLocalCurrentSources()

const std::map<std::string, CurrentSourceInternal>& ModelSpec::getLocalCurrentSources ( ) const

inlineprotected

Get std::map containing local named CurrentSource objects in model.

◆ getLocalNeuronGroups()

const std::map<std::string, NeuronGroupInternal>& ModelSpec::getLocalNeuronGroups ( ) const

inlineprotected

Get std::map containing local named NeuronGroup objects in model.

◆ getLocalSynapseGroups()

const std::map<std::string, SynapseGroupInternal>& ModelSpec::getLocalSynapseGroups ( ) const

inlineprotected

Get std::map containing local named SynapseGroup objects in model.

◆ getName()

const std::string& ModelSpec::getName ( ) const

inline

Gets the name of the neuronal network model.

◆ getNumLocalNeurons()

unsigned int ModelSpec::getNumLocalNeurons ( ) const

How many neurons are simulated locally in this model.

◆ getNumNeurons()

unsigned int ModelSpec::getNumNeurons ( ) const

inline

How many neurons make up the entire model.

◆ getNumRemoteNeurons()

unsigned int ModelSpec::getNumRemoteNeurons ( ) const

How many neurons are simulated remotely in this model.

◆ getPrecision()

const std::string& ModelSpec::getPrecision ( ) const

inline

Gets the floating point numerical precision.

◆ getRemoteCurrentSources()

const std::map<std::string, CurrentSourceInternal>& ModelSpec::getRemoteCurrentSources ( ) const

inlineprotected

Get std::map containing remote named CurrentSource objects in model.

◆ getRemoteNeuronGroups()

const std::map<std::string, NeuronGroupInternal>& ModelSpec::getRemoteNeuronGroups ( ) const

inlineprotected

Get std::map containing remote named NeuronGroup objects in model.

◆ getRemoteSynapseGroups()

const std::map<std::string, SynapseGroupInternal>& ModelSpec::getRemoteSynapseGroups ( ) const

inlineprotected

Get std::map containing remote named SynapseGroup objects in model.

◆ getSeed()

unsigned int ModelSpec::getSeed ( ) const

inline

Get the random seed.

◆ getTimePrecision()

std::string ModelSpec::getTimePrecision ( ) const

Gets the floating point numerical precision used to represent time.

◆ isTimingEnabled()

bool ModelSpec::isTimingEnabled ( ) const

inline

Are timers and timing commands enabled.

◆ operator=()

ModelSpec& ModelSpec::operator= ( const ModelSpec & )

delete

◆ scalarExpr()

std::string ModelSpec::scalarExpr ( double val ) const

protected

Get the string literal that should be used to represent a value in the model's floating-point type.

◆ setDefaultExtraGlobalParamLocation()

void ModelSpec::setDefaultExtraGlobalParamLocation ( VarLocation loc )

inline

What is the default location for model extra global parameters?

Historically, this was just left up to the user to handle

◆ setDefaultSparseConnectivityLocation()

void ModelSpec::setDefaultSparseConnectivityLocation ( VarLocation loc )

inline

What is the default location for sparse synaptic connectivity?

Historically, everything was allocated on both the host AND device

◆ setDefaultVarLocation()

void ModelSpec::setDefaultVarLocation ( VarLocation loc )

inline

What is the default location for model state variables?

Historically, everything was allocated on both the host AND device

◆ setDT()

void ModelSpec::setDT ( double dt )

inline

Set the integration step size of the model.

◆ setMergePostsynapticModels()

void ModelSpec::setMergePostsynapticModels ( bool merge )

inline

Should compatible postsynaptic models and dendritic delay buffers be merged?

This can significantly reduce the cost of updating neuron population but means that per-synapse group inSyn arrays can not be retrieved

◆ setName()

void ModelSpec::setName ( const std::string & name )

inline

Method to set the neuronal network model name.

◆ setPrecision()

void ModelSpec::setPrecision ( FloatType floattype )

Set numerical precision for floating point.

This function sets the numerical precision of floating type variables. By default, it is GENN_GENN_FLOAT.

◆ setSeed()

void ModelSpec::setSeed ( unsigned int rngSeed )

inline

Set the random seed (disables automatic seeding if argument not 0).

◆ setTimePrecision()

void ModelSpec::setTimePrecision ( TimePrecision timePrecision )

inline

Set numerical precision for time.

◆ setTiming()

void ModelSpec::setTiming ( bool timingEnabled )

inline

Set whether timers and timing commands are to be included.

◆ zeroCopyInUse()

bool ModelSpec::zeroCopyInUse ( ) const

protected

Are any variables in any populations in this model using zero-copy memory?

The documentation for this class was generated from the following files:

Public Types

Public Member Functions

Protected Member Functions

Detailed Description

Member Typedef Documentation

◆ NeuronGroupValueType

◆ SynapseGroupValueType

Constructor & Destructor Documentation

◆ ModelSpec() [1/2]

◆ ModelSpec() [2/2]

◆ ~ModelSpec()

Member Function Documentation

◆ addCurrentSource() [1/2]

◆ addCurrentSource() [2/2]

◆ addNeuronPopulation() [1/2]

◆ addNeuronPopulation() [2/2]

◆ addSynapsePopulation() [1/3]

◆ addSynapsePopulation() [2/3]

◆ addSynapsePopulation() [3/3]

◆ finalize()

◆ findCurrentSource()

◆ findNeuronGroup()

◆ findSynapseGroup()

◆ getDT()

◆ getLocalCurrentSources()

◆ getLocalNeuronGroups()

◆ getLocalSynapseGroups()

◆ getName()

◆ getNumLocalNeurons()

◆ getNumNeurons()

◆ getNumRemoteNeurons()

◆ getPrecision()

◆ getRemoteCurrentSources()

◆ getRemoteNeuronGroups()

◆ getRemoteSynapseGroups()

◆ getSeed()

◆ getTimePrecision()

◆ isTimingEnabled()

◆ operator=()

◆ scalarExpr()

◆ setDefaultExtraGlobalParamLocation()

◆ setDefaultSparseConnectivityLocation()

◆ setDefaultVarLocation()

◆ setDT()

◆ setMergePostsynapticModels()

◆ setName()

◆ setPrecision()

◆ setSeed()

◆ setTimePrecision()

◆ setTiming()

◆ zeroCopyInUse()