Class representing a synapse with Hill short term plasticity. More...

Namespaces
	names
	This namespace contains global Name objects.

Classes
class	AbstractLayer
	Abstract base class for Layers of unspecified dimension. More...

class	AbstractMask
	Abstract base class for masks with unspecified dimension. More...

class	ac_generator

class	aeif_cond_alpha

class	aeif_cond_alpha_multisynapse
	Conductance based exponential integrate-and-fire neuron model according to Brette and Gerstner (2005) with multiple ports. More...

class	aeif_cond_alpha_RK5

class	aeif_cond_exp

class	AllMask
	Mask which covers all of space. More...

class	AllToAllBuilder

class	amat2_psc_exp
	Non-resetting leaky integrate-and-fire neuron model with exponential PSCs and adaptive threshold. More...

class	AnchoredMask
	Mask shifted by an anchor. More...

class	AnchoredParameter
	Parameter class representing a parameter centered at an anchor position. More...

class	Archiving_Node
	a node which archives spike history for the purposes of timing dependent plasticity More...

class	ArrayParameter
	Array parameter, returning values in order. More...

class	BadDelay
	Exception to be thrown if an invalid delay is used in a connection. More...

class	BadParameter
	Exception to be thrown if a parameter cannot be set. More...

class	BadProperty
	Exception to be thrown if a status parameter is incomplete or inconsistent. More...

class	BallMask
	Mask defining a circular or spherical region. More...

class	BernoulliBuilder

class	binary_neuron
	Binary stochastic neuron with linear or sigmoidal gain function. More...

struct	Box
	A box is defined by the lower left corner (minimum coordinates) and the upper right corner (maximum coordinates). More...

class	BoxMask
	Mask defining a box region. More...

class	CommonPropertiesHomW
	Class containing the common properties for all synapses with common weight. More...

class	CommonSynapseProperties
	Class containing the common properties for all connections of a certain type. More...

class	Communicator

class	ConductanceEvent
	Event for electrical conductances. More...

class	ConnBuilder
	Abstract base class for ConnBuilders. More...

class	ConnBuilderFactory
	Factory class for generating objects of type ConnBuilder. More...

class	Connection
	Base class for representing connections. More...

class	ConnectionCreator
	This class is a representation of the dictionary of connection properties given as an argument to the ConnectLayers function. More...

class	ConnectionGeneratorModule

class	ConnectionID

class	ConnectionManager
	Manages the available connection prototypes and connections. More...

class	Connector

class	Connector< 1, ConnectionT >

class	Connector< K_cutoff, ConnectionT >

class	ConnectorBase

class	ConnectorModel

class	ConnParameter

class	ConnTestDummyNodeBase
	Base class for dummy nodes used in connection testing. More...

class	ConstantParameter
	Parameter with constant value. More...

class	ContDelayConnection

class	ConverseMask
	Mask oriented in the opposite direction. More...

class	ConverseParameter
	Parameter class for a parameter oriented in the opposite direction. More...

class	correlation_detector
	Correlation detector class. More...

class	correlomatrix_detector
	Correlomatrixdetector class. More...

class	CurrentEvent
	Event for electrical currents. More...

class	DataEvent
	Event for transmitting arbitrary data. More...

class	DataLoggingReply
	Provide logged data through request transmitting reference. More...

class	DataLoggingRequest
	Request data to be logged/logged data to be sent. More...

class	dc_generator
	DC current generator. More...

class	Device
	Class implementing common interface and properties common for all devices. More...

class	DifferenceMask
	Mask combining two masks with a minus operation, the difference. More...

class	DifferenceParameter
	Parameter class representing the difference of two parameters. More...

class	DimensionMismatch
	Exception to be thrown if the dimensions of two or more objects do not agree. More...

class	DistributionError
	Exception to be thrown if a problem with the distribution of elements is encountered. More...

class	DoubleDataEvent

class	DSCurrentEvent
	"Callback request event" for use in Device. More...

class	DSSpikeEvent
	"Callback request event" for use in Device. More...

class	DynamicLoaderModule
	SLI interface of the Ddynamic module loader. More...

class	Event
	Encapsulates information which is sent between Nodes. More...

class	EventPTRPriority

class	ExponentialParameter
	Exponential parameter p(d) = c + a*exp(-d/tau). More...

class	FixedInDegreeBuilder

class	FixedOutDegreeBuilder

class	FixedTotalNumberBuilder

class	FreeLayer
	Layer with free positioning of neurons, positions specified by user. More...

class	gainfunction_ginzburg

class	gainfunction_mcculloch_pitts

class	gamma_sup_generator
	Generator of the spike output of a population of gamma processes with integer shape parameter. More...

class	Gaussian2DParameter
	Bivariate Gaussian parameter p(x,y) = c + p_center*exp( -( (x-mean_x)^2/sigma_x^2 + (y-mean_y)^2/sigma_y^2. More...

class	GaussianParameter
	Gaussian parameter p(d) = c + p_centerexp(-(d-mean)^2/(2sigma^2)) More...

class	GenericConnBuilderFactory
	Generic factory class for ConnBuilder objects. More...

class	GenericConnectorModel

class	GenericFactory
	Generic Factory class for objects deriving from a base class BaseT. More...

class	GenericModel
	Generic Model template. More...

class	GIDCollection

class	GridLayer
	Layer with neurons placed in a grid. More...

class	GridMask
	Mask defined in terms of grid points rather than spacial coordinates. More...

class	GSLSolverFailure
	Exception to be thrown if a GSL solver does not return GSL_SUCCESS. More...

class	HetConnector

class	hh_cond_exp_traub

class	hh_psc_alpha

class	histentry

class	ht_neuron

class	HTConnection

class	iaf_chs_2007
	Neuron model used in Carandini et al 2007. More...

class	iaf_chxk_2008
	Integrate-and-fire neuron model with two conductance-based synapses. More...

class	iaf_cond_alpha
	Integrate-and-fire neuron model with two conductance-based synapses. More...

class	iaf_cond_alpha_mc

class	iaf_cond_exp

class	iaf_cond_exp_sfa_rr

class	iaf_neuron
	Leaky integrate-and-fire neuron. More...

class	iaf_psc_alpha
	Leaky integrate-and-fire neuron with alpha-shaped PSCs. More...

class	iaf_psc_alpha_canon
	Leaky iaf neuron, alpha PSC synapses, canonical implementation. More...

class	iaf_psc_alpha_multisynapse
	Leaky integrate-and-fire neuron with alpha-shaped PSCs. More...

class	iaf_psc_alpha_presc
	Leaky iaf neuron, alpha PSC synapses, canonical implementation. More...

class	iaf_psc_delta
	Leaky integrate-and-fire neuron with delta-shaped PSCs. More...

class	iaf_psc_delta_canon

class	iaf_psc_exp
	Leaky integrate-and-fire neuron with exponential PSCs. More...

class	iaf_psc_exp_multisynapse

class	iaf_psc_exp_ps
	Leaky iaf neuron, exponential PSC synapses, canonical implementation. More...

class	iaf_tum_2000
	Leaky integrate-and-fire neuron with exponential PSCs. More...

class	IllegalConnection
	To be thrown if a connection is not possible. More...

class	IncompatibleReceptorType
	Exception to be thrown if the specified receptor type does not accept the event type. More...

class	Instance
	Instance is a template is used to provide a pool-based management for arbitrary classes. More...

class	IntersectionMask
	Mask combining two masks with a Boolean AND, the intersection. More...

class	InvalidDefaultResolution
	Exception to be thrown on prototype construction if Time objects incompatible. More...

class	InvalidTimeInModel
	Exception to be thrown on instance construction if Time objects incompatible. More...

class	izhikevich

class	KernelException
	Base class for all Kernel exceptions. More...

class	Layer
	Abstract base class for Layer of given dimension (D=2 or 3). More...

class	LayerExpected
	Exception to be thrown if the wrong argument type is given to a function. More...

class	LinearParameter
	Linear (affine) parameter p(d) = c + a*d. More...

class	ListRingBuffer

class	LocalChildListIterator
	Iterator for traversal of all local immediate child nodes in a subnet. More...

class	LocalLeafListIterator
	Iterator for traversal of only local leaf nodes in a subnet. More...

class	LocalNodeExpected

class	LocalNodeListBase
	Template for list interface to network tree. More...

class	LocalNodeListIterator
	Iterator for post-order traversal of all local nodes in a subnet. More...

class	LognormalParameter
	Random parameter with lognormal distribution, optionally truncated to [min,max). More...

class	Mask
	Abstract base class for masks with given dimension. More...

class	MaskedLayer
	Class for applying masks to layers. More...

class	mat2_psc_exp
	Non-resetting leaky integrate-and-fire neuron model with exponential PSCs and adaptive threshold. More...

class	mip_generator
	class mip_generator More...

class	Model
	Base class for all Models. More...

class	ModelComp

class	ModelInUse
	Exception to be thrown if a (neuron/synapse) model with the the specified ID is used within the network and the providing module hence cannot be uninstalled. More...

class	modelrange

class	Modelrangemanager

class	ModelsModule
	Module supplying all models that are included in the NEST release. More...

class	MsgHandler

class	MultiIndex
	An index into a multidimensional array. More...

class	Multimeter
	General analog data recorder. More...

class	Multirange
	Class for sequences of ranges acting like a compressed vector. More...

class	MultRBuffer

class	music_cont_in_proxy
	Emit spikes at times received from another application via a MUSIC port. More...

class	music_event_in_proxy
	Emit spikes at times received from another application via a MUSIC port. More...

class	music_event_out_proxy

class	music_message_in_proxy
	Emit spikes at times received from another application via a MUSIC port. More...

class	MUSICChannelAlreadyMapped
	Exception to be thrown if the user tries to map a channel that exceeds the width of the MUSIC port. More...

class	MUSICChannelUnknown
	Exception to be thrown if the user tries to map a channel that exceeds the width of the MUSIC port. More...

class	MusicEventHandler
	Event handler for all events of a MUSIC port received on this process. More...

class	MUSICPortAlreadyPublished
	Exception to be thrown if the user tries to change the name of an already published port. More...

class	MUSICPortHasNoWidth
	Exception to be thrown if a music_event_out_proxy is generated, but the music port has no width. More...

class	MUSICPortUnconnected
	Exception to be thrown if a music_event_out_proxy is generated, but the music port is unmapped. More...

class	MUSICPortUnknown
	Exception to be thrown if the user tries to use a port that is not known to NEST. More...

class	MUSICSimulationHasRun
	Exception to be thrown if the user tries to change the name of an already published port. More...

class	NestModule
	SLI interface of the NEST kernel. More...

class	Network
	Main administrative interface to the network. More...

class	NewModelNameExists
	Exception to be thrown if a name requested for a user-defined model exist already. More...

class	Node
	Base class for all NEST network objects. More...

class	NodeWithProxiesExpected

class	noise_generator
	Gaussian white noise generator. More...

class	NormalParameter
	Random parameter with normal distribution, optionally truncated to [min,max). More...

class	NoThreadSiblingsAvailable
	Exception to be thrown if the specified Node does not exist. More...

class	Ntree
	A Ntree object represents a subtree or leaf in a Ntree structure. More...

class	NumericalInstability
	Exception to be thrown if numerical instabilities are detected. More...

class	OneToOneBuilder

class	Parameter
	Abstract base class for parameters. More...

class	parrot_neuron

class	parrot_neuron_ps

class	poisson_generator

class	poisson_generator_ps
	Poisson generator (with dead time) with precisely timed spikes. More...

class	Position

class	pp_pop_psc_delta
	Population of point process neurons with leaky integration of delta-shaped PSCs. More...

class	pp_psc_delta
	Point process neuron with leaky integration of delta-shaped PSCs. More...

class	ppd_sup_generator
	Generator of the spike output of a population of Poisson processes with dead time. More...

class	PreciseModule
	Module supplying models support precise spike timing. More...

class	ProductParameter
	Parameter class representing the product of two parameters. More...

class	proxynode
	Proxy Node to provide Nodes, where there aren't real Nodes to be. More...

class	PseudoRecordingDevice
	Base class for all pseudo recording devices. More...

class	pulsepacket_generator
	class pulsepacket_generator More...

class	Quantal_StpConnection

class	QuotientParameter
	Parameter class representing the quotient of two parameters. More...

class	RadialParameter
	Abstract base class for parameters only depending on distance. More...

class	RandomParameter
	Random scalar value. More...

class	RateEvent
	Event for firing rate information. More...

class	RecordablesMap
	Map names of recordables to data access functions. More...

class	RecordingDevice
	Base class for all recording devices. More...

class	relaxos_van_der_pol

class	RingBuffer
	Buffer Layout. More...

class	ScalarDoubleParameter
	Single double value. More...

class	ScalarIntegerParameter
	Single integer value. More...

class	Scheduler
	Schedule update of Nodes and Events during simulation. More...

struct	sDynModule

struct	Selector
	Contains rules for selecting nodes from a layer when connecting. More...

class	SiblingContainer
	SiblingContainer class. More...

class	SimulationError
	Exception to be thrown if the wrong argument type is given to a function. More...

class	sinusoidal_gamma_generator
	AC Gamma Generator. More...

class	sinusoidal_poisson_generator

class	sli_neuron
	neuron with state and dynamics defined as SLI code More...

class	SliceRingBuffer
	Queue for all spikes arriving into a neuron. More...

class	SparseNodeArray
	Provide sparse representation of local nodes. More...

class	spike_detector
	Spike detector class. More...

class	spike_generator
	Emit spikes at given times. More...

class	spikecounter

class	SpikeEvent
	Event for spike information. More...

class	spin_detector
	Spike detector class. More...

class	StaticConnection
	Class representing a static connection. More...

class	StaticConnectionHomW
	Class representing a static connection. More...

class	STDPConnection

class	STDPConnectionHom
	Class representing an STDP connection with homogeneous parameters, i.e. More...

class	STDPDopaCommonProperties
	Class containing the common properties for all synapses of type dopamine connection. More...

class	STDPDopaConnection
	Class representing an STDPDopaConnection with homogeneous parameters, i.e. More...

class	STDPFACETSHWConnectionHom
	Class representing an STDP connection with homogeneous parameters, i.e. More...

class	STDPFACETSHWHomCommonProperties
	Class containing the common properties for all synapses of type STDPFACETSHWConnectionHom. More...

class	STDPHomCommonProperties
	Class containing the common properties for all synapses of type STDPConnectionHom. More...

class	STDPPLConnectionHom
	Class representing an STDP connection with homogeneous parameters, i.e. More...

class	STDPPLHomCommonProperties
	Class containing the common properties for all synapses of type STDPConnectionHom. More...

class	step_current_generator

class	StepMultipleRequired
	Exception to be thrown if a Time object should be multiple of the resolution. More...

class	StimulatingDevice
	Base class for common properties of Stimulating Devices. More...

class	Stopwatch

class	Subnet
	Base class for all subnet nodes. More...

class	SubnetExpected
	Exception to be thrown if the wrong argument type is given to a function. More...

class	SumParameter
	Parameter class representing the sum of two parameters. More...

struct	SynIdDelay

class	TargetIdentifierIndex
	Class providing compact (hpc) target identified by index. More...

class	TargetIdentifierPtrRport
	Class providing classic target identified information with target pointer and rport. More...

class	Time

class	TimeConverter
	Class to convert times from one representation to another. More...

class	TimeModifier

class	TimeMultipleRequired
	Exception to be thrown if a Time object should be a multiple of another. More...

class	TopologyModule

class	Tsodyks2Connection

class	TsodyksConnection

class	UnexpectedEvent
	Exception to be thrown by the event handler of a node if it receives an event it cannot handle. More...

class	UniformParameter
	Random parameter with uniform distribution in [min,max) More...

class	UnionMask
	Mask combining two masks with a Boolean OR, the sum. More...

class	UnknownModelID
	Exception to be thrown if a model with the the specified ID does not exist. More...

class	UnknownModelName
	Exception to be thrown if a model with the the specified name does not exist. More...

class	UnknownNode
	Exception to be thrown if the specified Node does not exist. More...

class	UnknownPort
	To be thrown if a port does not exists. More...

class	UnknownReceptorType
	Exception to be thrown if the specified receptor type does not exist in the node. More...

class	UnknownSynapseType
	Exception to be thrown if the specified Synapse type does not exist. More...

class	UnknownThread
	Exception to be thrown if a thread id outside the range encountered. More...

class	UnsupportedEvent
	Exception to be thrown by a Connection object if a connection with an unsupported event type is attempted. More...

class	vector_like

class	volume_transmitter
	volume transmitter class. More...

class	Vose
	Vose's alias method for selecting a random number using a discrete probability distribution. More...

Typedefs
typedef lockPTRDatum < ConnectionGenerator,&nest::ConnectionGeneratorModule::ConnectionGeneratorType >	ConnectionGeneratorDatum

typedef binary_neuron < nest::gainfunction_ginzburg >	ginzburg_neuron

typedef nest::binary_neuron < nest::gainfunction_mcculloch_pitts >	mcculloch_pitts_neuron

typedef std::vector< sDynModule >	vecDynModules

typedef std::vector< DynModule * >	vecLinkedModules

typedef long long	tic_t
	Type for Time tics. More...

typedef double	double_t
	Double precision floating point numbers. More...

typedef float	float_t
	Single precision floating point numbers. More...

typedef int	int_t
	Integer number with at least 16 bit. More...

typedef long	long_t
	Integer number with at least 32 bit. More...

typedef unsigned int	uint_t
	Unsigned int_t. More...

typedef unsigned long	ulong_t
	Unsigned long_t. More...

typedef size_t	index
	Unsigned long type for enumerations. More...

typedef unsigned char	synindex
	Unsigned char type for enumerations of synapse types. More...

typedef unsigned short	targetindex
	Unsigned short type for compact target representation. More...

typedef int_t	thread
	Thread index type. More...

typedef long_t	rport
	Connection port number to distinguish incoming connections, also called receiver port. More...

typedef long_t	port
	Connection port number to distinguis outgoing connections. More...

typedef double_t	weight
	Weight of a connection. More...

typedef long_t	delay
	Delay of a connection. More...

typedef lockPTR< Network >	NetPtr
	Functor to compare Models by their name. More...

typedef LocalNodeListBase < LocalNodeListIterator >	LocalNodeList
	List interface to subnet providing iteration over all local nodes. More...

typedef LocalNodeListBase < LocalChildListIterator >	LocalChildList
	List interface to subnet providing iteration over immediate local child nodes. More...

typedef LocalNodeListBase < LocalLeafListIterator >	LocalLeafList
	List interface to subnet providing iteration over local leaf nodes. More...

typedef Communicator::OffGridSpike	OffGridSpike

typedef lockPTRDatum < AbstractMask,&TopologyModule::MaskType >	MaskDatum

typedef lockPTRDatum < Parameter,&TopologyModule::ParameterType >	ParameterDatum

Functions
void	cg_connect (ConnectionGeneratorDatum &cg, RangeSet &sources, index source_offset, RangeSet &targets, index target_offset, DictionaryDatum params_map, index syn)

void	cg_connect (ConnectionGeneratorDatum &cg, RangeSet &sources, std::vector< long > &source_gids, RangeSet &targets, std::vector< long > &target_gids, DictionaryDatum params_map, index syn)

void	cg_set_masks (ConnectionGeneratorDatum &cg, RangeSet &sources, RangeSet &targets)
	Set the masks on the ConnectionGenerator cg. More...

void	cg_create_masks (std::vector< ConnectionGenerator::Mask > *masks, RangeSet &sources, RangeSet &targets)
	Create the masks for sources and targets based on the contiguous ranges given in sources and targets. More...

index	cg_get_right_border (index left, size_t step, std::vector< long > &gids)
	Calculate the right border of the contiguous range of gids starting at left. More...

void	cg_get_ranges (RangeSet &ranges, std::vector< long > &gids)
	Determine all contiguous ranges found in a given vector of gids and add the ranges to the given RangeSet. More...

std::ostream &	operator<< (std::ostream &os, const Stopwatch &stopwatch)

int	aeif_cond_alpha_dynamics (double, const double , double , void *)
	Function computing right-hand side of ODE for GSL solver. More...

int	aeif_cond_exp_dynamics (double, const double , double , void *)
	Function computing right-hand side of ODE for GSL solver. More...

int	hh_cond_exp_traub_dynamics (double, const double y[], double f[], void *pnode)

int	hh_cond_exp_traub_dynamics (double, const double , double , void *)
	Function computing right-hand side of ODE for GSL solver. More...

int	hh_psc_alpha_dynamics (double, const double y[], double f[], void *pnode)

int	hh_psc_alpha_dynamics (double, const double , double , void *)
	Function computing right-hand side of ODE for GSL solver. More...

int	ht_neuron_dynamics (double, const double y[], double f[], void *pnode)

int	ht_neuron_dynamics (double, const double , double , void *)
	Function computing right-hand side of ODE for GSL solver. More...

int	iaf_chxk_2008_dynamics (double, const double , double , void *)
	Function computing right-hand side of ODE for GSL solver. More...

int	iaf_cond_alpha_dynamics (double, const double , double , void *)
	Function computing right-hand side of ODE for GSL solver. More...

int	iaf_cond_alpha_mc_dynamics (double, const double , double , void *)
	Function computing right-hand side of ODE for GSL solver. More...

int	iaf_cond_exp_dynamics (double, const double , double , void *)
	Function computing right-hand side of ODE for GSL solver. More...

int	iaf_cond_exp_sfa_rr_dynamics (double, const double , double , void *)
	Function computing right-hand side of ODE for GSL solver. More...

bool	update_value_int (const DictionaryDatum &d, Name propname, int &prop)

template<class ConnectionT >
synindex	register_connection_model (Network &net, const std::string &name)
	Register a synape with default Connector and without any common properties. More...

bool	has_name (DynModule const *const m, const std::string n)

bool	operator< (const Event &, const Event &)

template<class ModelT >
index	register_model (Network &net, const std::string &name, bool private_model=false)
	Register a model prototype with the network. More...

template<class ModelT >
index	register_preconf_model (Network &net, const std::string &name, Dictionary &conf, bool private_model=false)
	Register a pre-configured model prototype with the network. More...

template<class ModelT >
index	register_private_model (Network &net, const std::string &name)
	Register a private model prototype with the network. More...

template<class N >
N	time_abs (const N n)
	Class to handle simulation time and realtime. More...

template<>
long long	time_abs (long long n)

bool	operator== (const Time &t1, const Time &t2)

bool	operator!= (const Time &t1, const Time &t2)

bool	operator< (const Time &t1, const Time &t2)

bool	operator> (const Time &t1, const Time &t2)

bool	operator<= (const Time &t1, const Time &t2)

bool	operator>= (const Time &t1, const Time &t2)

Time	operator+ (const Time &t1, const Time &t2)

Time	operator- (const Time &t1, const Time &t2)

Time	operator* (const long_t factor, const Time &t)

Time	operator* (const Time &t, long_t factor)

template<int D>
static bool	gid_less (const std::pair< Position< D >, index > &a, const std::pair< Position< D >, index > &b)

static double_t	mod (double_t x, double_t p)

template<int D, class T >
std::ostream &	operator<< (std::ostream &os, const Position< D, T > &pos)

static AbstractMask *	create_doughnut (const DictionaryDatum &d)

Variables
const double_t	KNa_D_EQ = 0.001

const tic_t	tic_t_max = LONG_LONG_MAX

const tic_t	tic_t_min = LONG_LONG_MIN

const long_t	long_t_max = LONG_MAX

const long_t	long_t_min = LONG_MIN

const index	invalid_index = std::numeric_limits<index>::max()

const synindex	invalid_synindex = std::numeric_limits<synindex>::max()

const targetindex	invalid_targetindex = std::numeric_limits<targetindex>::max()

const index	max_targetindex = invalid_targetindex - 1

const thread	invalid_thread_ = -1
	Value for invalid connection port number. More...

const rport	invalid_port_ = -1
	Value for invalid connection port number. More...

const long_t	delay_max = long_t_max

const long_t	delay_min = long_t_min

const Time	TimeZero

Detailed Description

Class representing a synapse with Hill short term plasticity.

Namespace for the NEST simulation kernel.

Base class for parameters provided to connection routines.

Class managing flexible connection creation.

Class representing a synapse with Tsodyks short term plasticity.

Class representing a synapse with Tsodyks short term plasticity, based on the iterative formula A suitable Connector containing these connections can be obtained from the template GenericConnector.

A suitale Connector containing these connections can be obtained from the template GenericConnector.

A suitable Connector containing these connections can be obtained from the template GenericConnector.

This is a very first draft, a very much stripped-down version of the Topology connection_creator.

Principles for these parameters are

Each parameter is a single scalar value.
The parameter will be returned as type double.
The parameter values can be given either as
- a single scalar: the same value is returned for each call
- a random deviate generator: a new random values is returned for each call
- an array of scalars: values are returned in order

Typedef Documentation

typedef lockPTRDatum<ConnectionGenerator, &nest::ConnectionGeneratorModule::ConnectionGeneratorType> nest::ConnectionGeneratorDatum

typedef long_t nest::delay

Delay of a connection.

The delay defines the number of simulation steps which elapse before an Event arrives at the receiving Node. Delays must be equal or larger than one.

typedef double nest::double_t

Double precision floating point numbers.

typedef float nest::float_t

Single precision floating point numbers.

typedef binary_neuron<nest::gainfunction_ginzburg> nest::ginzburg_neuron

typedef size_t nest::index

Unsigned long type for enumerations.

typedef int nest::int_t

Integer number with at least 16 bit.

typedef LocalNodeListBase<LocalChildListIterator> nest::LocalChildList

List interface to subnet providing iteration over immediate local child nodes.

typedef LocalNodeListBase<LocalLeafListIterator> nest::LocalLeafList

List interface to subnet providing iteration over local leaf nodes.

Note: Leaf nodes are those children that are not subnets. Empty subnets are not considered leaves.

typedef LocalNodeListBase<LocalNodeListIterator> nest::LocalNodeList

List interface to subnet providing iteration over all local nodes.

typedef long nest::long_t

Integer number with at least 32 bit.

typedef lockPTRDatum<AbstractMask, &TopologyModule::MaskType> nest::MaskDatum

typedef nest::binary_neuron<nest::gainfunction_mcculloch_pitts> nest::mcculloch_pitts_neuron

typedef lockPTR<Network> nest::NetPtr

Functor to compare Models by their name.

typedef Communicator::OffGridSpike nest::OffGridSpike

typedef lockPTRDatum<Parameter, &TopologyModule::ParameterType> nest::ParameterDatum

typedef long_t nest::port

Connection port number to distinguis outgoing connections.

Connections between Nodes are assigned port numbers. Valid port numbers start at zero (0). The value -1 is used for invalid or unassigned ports.

typedef long_t nest::rport

Connection port number to distinguish incoming connections, also called receiver port.

Connections between Nodes are assigned port numbers. Valid port numbers start at zero (0). The value -1 is used for invalid or unassigned ports.

typedef unsigned char nest::synindex

Unsigned char type for enumerations of synapse types.

typedef unsigned short nest::targetindex

Unsigned short type for compact target representation.

See Kunkel et al, Front Neuroinform 8:78 (2014).target index into thread local node vector

typedef int_t nest::thread

Thread index type.

NEST threads are assigned non-negative numbers for identification. For invalid or undefined threads, the value -1 is used.

typedef long nest::tic_t

Type for Time tics.

typedef unsigned int nest::uint_t

Unsigned int_t.

typedef unsigned long nest::ulong_t

Unsigned long_t.

typedef std::vector<sDynModule> nest::vecDynModules

typedef std::vector<DynModule*> nest::vecLinkedModules

typedef double_t nest::weight

Weight of a connection.

Connections have a weight which is used to scale the influence of an event. A weight of 0 should have the same influence on the receiving node as a non-existing connection. Otherwise, there is no default range for connection weights.

Function Documentation

int nest::aeif_cond_alpha_dynamics	(	double	,
		const double *	,
		double *	,
		void *
	)

Function computing right-hand side of ODE for GSL solver.

Note: Must be declared here so we can befriend it in class.; Must have C-linkage for passing to GSL. Internally, it is a first-class C++ function, but cannot be a member function because of the C-linkage.; No point in declaring it inline, since it is called through a function pointer.

Parameters

void* Pointer to model neuron instance.

Referenced by nest::aeif_cond_alpha::init_buffers_().

int nest::aeif_cond_exp_dynamics	(	double	,
		const double *	,
		double *	,
		void *
	)

Function computing right-hand side of ODE for GSL solver.

Note: Must be declared here so we can befriend it in class.; Must have C-linkage for passing to GSL. Internally, it is a first-class C++ function, but cannot be a member function because of the C-linkage.; No point in declaring it inline, since it is called through a function pointer.

Parameters

void* Pointer to model neuron instance.

Referenced by nest::aeif_cond_exp::init_buffers_().

void nest::cg_connect	(	ConnectionGeneratorDatum &	cg,
		RangeSet &	sources,
		index	source_offset,
		RangeSet &	targets,
		index	target_offset,
		DictionaryDatum	params_map,
		index	syn
	)

References cg_set_masks(), nest::Network::connect(), nest::names::delay, nest::ConnectionGeneratorModule::get_network(), nest::Network::get_node(), nest::Node::get_thread(), nest::Network::is_local_gid(), SLIInterpreter::M_ERROR, nest::Network::message(), nest::names::source, nest::names::target, nest::names::target_thread, and nest::names::weight.

Referenced by nest::ConnectionGeneratorModule::CGConnect_cg_i_i_D_lFunction::execute(), and nest::ConnectionGeneratorModule::CGConnect_cg_iV_iV_D_lFunction::execute().

void nest::cg_connect	(	ConnectionGeneratorDatum &	cg,
		RangeSet &	sources,
		std::vector< long > &	source_gids,
		RangeSet &	targets,
		std::vector< long > &	target_gids,
		DictionaryDatum	params_map,
		index	syn
	)

References cg_set_masks(), nest::Network::connect(), nest::names::delay, nest::ConnectionGeneratorModule::get_network(), nest::Network::get_node(), nest::Node::get_thread(), nest::Network::is_local_gid(), SLIInterpreter::M_ERROR, nest::Network::message(), nest::names::source, nest::names::target, nest::names::target_thread, and nest::names::weight.

void nest::cg_create_masks	(	std::vector< ConnectionGenerator::Mask > *	masks,
		RangeSet &	sources,
		RangeSet &	targets
	)

Create the masks for sources and targets based on the contiguous ranges given in sources and targets.

We need to do some index translation here, as the CG expects indices from 0..n for both source and target populations, while the RangeSets sources and targets contain NEST global indices (gids).

The masks for the sources must contain all nodes (local+remote). The skip of the mask was set to 1 in cg_set_masks(). The same source mask is stored n_proc times on each process.

The masks for the targets must only contain local nodes. This is achieved by first setting skip to num_processes upon creation of the mask in cg_set_masks(), and second by the fact that for each contiguous range of nodes in a mask, each of them contains the index-translated id of the first local neuron as the first entry. If this renders the range empty (i.e. because the first local id is beyond the last element of the range), the range is not added to the mask.

Parameters

masks	The std::vector of Masks to populate
sources	The source ranges to create the source masks from
targets	The target ranges to create the target masks from

Note: Each process computes the full set of source and target masks, i.e. one mask per rank will be created on each rank.; Setting the masks for all processes on each process might become a memory bottleneck when going to very large numbers of processes. Especially so for the source masks, which are all the same. This could be solved by making the ConnectionGenerator interface MPI aware and communicating the masks during connection setup.

References nest::Communicator::get_num_processes(), Name::insert(), nest::names::source, and nest::names::target.

Referenced by cg_set_masks().

void nest::cg_get_ranges	(	RangeSet &	ranges,
		std::vector< long > &	gids
	)

Determine all contiguous ranges found in a given vector of gids and add the ranges to the given RangeSet.

Parameters

ranges	A reference to the RangeSet to add to
gids	The std::vector<long> of gids

Note: We do not store the indices into the given range, but instead we store the actual gids. This allows us to use CG generated indices as indices into the ranges spanned by the RangeSet. Index translation is done in cg_create_masks().

References cg_get_right_border().

Referenced by nest::ConnectionGeneratorModule::CGConnect_cg_iV_iV_D_lFunction::execute(), and nest::ConnectionGeneratorModule::CGSetMask_cg_iV_iVFunction::execute().

index nest::cg_get_right_border	(	index	left,
		size_t	step,
		std::vector< long > &	gids
	)

Calculate the right border of the contiguous range of gids starting at left.

The element is found using a binary search with stepsize step.

Parameters

left	The leftmost element of the range
step	The step size for the binary search
gids	The std::vector<long> of gids to search in

References assert().

Referenced by cg_get_ranges().

void nest::cg_set_masks	(	ConnectionGeneratorDatum &	cg,
		RangeSet &	sources,
		RangeSet &	targets
	)

Set the masks on the ConnectionGenerator cg.

This function also creates the masks from the given RangeSets sources and targets.

Parameters

cg	The ConnectionGenerator to set the masks on
sources	The source ranges to create the source masks from
targets	The target ranges to create the target masks from

References cg_create_masks(), nest::Communicator::get_num_processes(), and nest::Communicator::get_rank().

Referenced by cg_connect(), and nest::ConnectionGeneratorModule::CGSetMask_cg_iV_iVFunction::execute().

static AbstractMask* nest::create_doughnut ( const DictionaryDatum & d )

static

References nest::names::anchor, nest::names::center, nest::names::d, getValue(), nest::names::inner_radius, and nest::names::outer_radius.

Referenced by nest::TopologyModule::init().

template<int D>

static bool nest::gid_less	(	const std::pair< Position< D >, index > &	a,
		const std::pair< Position< D >, index > &	b
	)

static

References nest::names::a, and nest::names::b.

bool nest::has_name	(	DynModule const *const	m,
		const std::string	n
	)

References nest::names::n, and DynModule::name().

Referenced by nest::DynamicLoaderModule::LoadModuleFunction::execute().

int nest::hh_cond_exp_traub_dynamics	(	double	,
		const double *	,
		double *	,
		void *
	)

Function computing right-hand side of ODE for GSL solver.

Note: Must be declared here so we can befriend it in class.; Must have C-linkage for passing to GSL. Internally, it is a first-class C++ function, but cannot be a member function because of the C-linkage.; No point in declaring it inline, since it is called through a function pointer.

Parameters

void* Pointer to model neuron instance.

int nest::hh_cond_exp_traub_dynamics	(	double	,
		const double	y[],
		double	f[],
		void *	pnode
	)

int nest::hh_psc_alpha_dynamics	(	double	,
		const double *	,
		double *	,
		void *
	)

Function computing right-hand side of ODE for GSL solver.

Note: Must be declared here so we can befriend it in class.; Must have C-linkage for passing to GSL. Internally, it is a first-class C++ function, but cannot be a member function because of the C-linkage.; No point in declaring it inline, since it is called through a function pointer.

Parameters

void* Pointer to model neuron instance.

int nest::hh_psc_alpha_dynamics	(	double	,
		const double	y[],
		double	f[],
		void *	pnode
	)

int nest::ht_neuron_dynamics	(	double	,
		const double	y[],
		double	f[],
		void *	pnode
	)

inline

Referenced by nest::ht_neuron::init_buffers_().

int nest::ht_neuron_dynamics	(	double	,
		const double *	,
		double *	,
		void *
	)

Function computing right-hand side of ODE for GSL solver.

Note: Must be declared here so we can befriend it in class.; Must have C-linkage for passing to GSL. Internally, it is a first-class C++ function, but cannot be a member function because of the C-linkage.; No point in declaring it inline, since it is called through a function pointer.

Parameters

void* Pointer to model neuron instance.

int nest::iaf_chxk_2008_dynamics	(	double	,
		const double *	,
		double *	,
		void *
	)

Function computing right-hand side of ODE for GSL solver.

Note: Must be declared here so we can befriend it in class.; Must have C-linkage for passing to GSL. Internally, it is a first-class C++ function, but cannot be a member function because of the C-linkage.; No point in declaring it inline, since it is called through a function pointer.

Parameters

void* Pointer to model neuron instance.

Referenced by nest::iaf_chxk_2008::init_buffers_().

int nest::iaf_cond_alpha_dynamics	(	double	,
		const double *	,
		double *	,
		void *
	)

Function computing right-hand side of ODE for GSL solver.

Note: Must be declared here so we can befriend it in class.; Must have C-linkage for passing to GSL. Internally, it is a first-class C++ function, but cannot be a member function because of the C-linkage.; No point in declaring it inline, since it is called through a function pointer.

Parameters

void* Pointer to model neuron instance.

Referenced by nest::iaf_cond_alpha::init_buffers_().

int nest::iaf_cond_alpha_mc_dynamics	(	double	,
		const double *	,
		double *	,
		void *
	)

Function computing right-hand side of ODE for GSL solver.

Note: Must be declared here so we can befriend it in class.; Must have C-linkage for passing to GSL.; No point in declaring it inline, since it is called through a function pointer.

Referenced by nest::iaf_cond_alpha_mc::init_buffers_().

int nest::iaf_cond_exp_dynamics	(	double	,
		const double *	,
		double *	,
		void *
	)

Function computing right-hand side of ODE for GSL solver.

Note: Must be declared here so we can befriend it in class.; Must have C-linkage for passing to GSL. Internally, it is a first-class C++ function, but cannot be a member function because of the C-linkage.; No point in declaring it inline, since it is called through a function pointer.

Parameters

void* Pointer to model neuron instance.

Referenced by nest::iaf_cond_exp::init_buffers_().

int nest::iaf_cond_exp_sfa_rr_dynamics	(	double	,
		const double *	,
		double *	,
		void *
	)

Function computing right-hand side of ODE for GSL solver.

Note: Must be declared here so we can befriend it in class.; Must have C-linkage for passing to GSL. Internally, it is a first-class C++ function, but cannot be a member function because of the C-linkage.; No point in declaring it inline, since it is called through a function pointer.

Parameters

void* Pointer to model neuron instance.

Referenced by nest::iaf_cond_exp_sfa_rr::init_buffers_().

static double_t nest::mod	(	double_t	x,
		double_t	p
	)

inlinestatic

References nest::names::p, and nest::names::x.

Referenced by nest::Network::add_node(), nest::Ntree< D, T, max_capacity, max_depth >::masked_iterator::masked_iterator(), and nest::Network::memory_info().

bool nest::operator!=	(	const Time &	t1,
		const Time &	t2
	)

inline

References nest::Time::tics.

Time nest::operator*	(	const long_t	factor,
		const Time &	t
	)

inline

References nest::Time::LIM_NEG_INF, nest::Time::LIM_POS_INF, nest::names::n, nest::Time::tic, and nest::Time::tics.

Time nest::operator*	(	const Time &	t,
		long_t	factor
	)

inline

Time nest::operator+	(	const Time &	t1,
		const Time &	t2
	)

inline

References nest::Time::tic, and nest::Time::tics.

Time nest::operator-	(	const Time &	t1,
		const Time &	t2
	)

inline

References nest::Time::tic, and nest::Time::tics.

bool nest::operator<	(	const Event &	e1,
		const Event &	e2
	)

inline

References nest::Event::get_delay(), nest::Event::get_stamp(), and nest::Time::get_steps().

bool nest::operator<	(	const Time &	t1,
		const Time &	t2
	)

inline

References nest::Time::tics.

std::ostream& nest::operator<<	(	std::ostream &	os,
		const Stopwatch &	stopwatch
	)

References nest::Stopwatch::print(), and nest::Stopwatch::SECONDS.

template<int D, class T >

std::ostream & nest::operator<<	(	std::ostream &	os,
		const Position< D, T > &	pos
	)

bool nest::operator<=	(	const Time &	t1,
		const Time &	t2
	)

inline

References nest::Time::tics.

bool nest::operator==	(	const Time &	t1,
		const Time &	t2
	)

inline

References nest::Time::tics.

bool nest::operator>	(	const Time &	t1,
		const Time &	t2
	)

inline

References nest::Time::tics.

bool nest::operator>=	(	const Time &	t1,
		const Time &	t2
	)

inline

References nest::Time::tics.

template<class ConnectionT >

synindex nest::register_connection_model	(	Network &	net,
		const std::string &	name
	)

Register a synape with default Connector and without any common properties.

References nest::Network::register_synapse_prototype().

template<class ModelT >

index nest::register_model	(	Network &	net,
		const std::string &	name,
		bool	private_model = `false`
	)

Register a model prototype with the network.

This function must be called exactly once for each model class to make it known to the network. The natural place for a call to this function is in a *module.cpp file.

Parameters

reference	to network
name	under which model is to be known in simulator

Returns: Model ID assigned by network

See also: register_private_prototype_model, register_prototype_connection

References assert(), and nest::Network::register_model().

template<class ModelT >

index nest::register_preconf_model	(	Network &	net,
		const std::string &	name,
		Dictionary &	conf,
		bool	private_model = `false`
	)

Register a pre-configured model prototype with the network.

This function must be called exactly once for each model class to make it known to the network. The natural place for a call to this function is in a *module.cpp file.

Pre-configured models are models based on the same class, as another model, but have different parameter settings; e.g., voltmeter is a pre-configured multimeter.

Parameters

reference	to network
name	under which model is to be known in simulator
dictionary	to use to pre-configure model
register	as private model if true

Returns: Model ID assigned by network

See also: register_private_prototype_model, register_prototype_connection

References Dictionary::all_accessed(), assert(), Dictionary::clear_access_flags(), nest::Network::register_model(), and nest::Model::set_status().

template<class ModelT >

index nest::register_private_model	(	Network &	net,
		const std::string &	name
	)

Register a private model prototype with the network.

Private model prototypes differ from normal ones in that they are not visible in the modeldict. This is important for node types that serve only as in-/output elements of layers, but cannot "live" independently.

Parameters

reference	to network
name	under which model is to be known in simulator

Returns: Model ID assigned by network

See also: register_prototype_model, register_prototype_connection, layerdc_node, layerdc_generator

template<class N >

N nest::time_abs ( const N n )

inline

Class to handle simulation time and realtime.

Main idea:

All times given in multiples of "tics": A "tic" is a microsecond by default, but may be changed through the option –with-tics_per_ms to configure.

User access to time only through accessor functions:

Times can be added, subtracted, and multiplied by ints
All real world time is given in ms as double
All computation is done based on tics

Three time variables are kept: #- time in tics #- time in ms #- time in steps

The largest representable time is available through Time::max().

The time base (tics per millisecond) can only be set at compile time and by the TimeModifier class.
Times in ms are rounded up to the next tic interval. This ensures that the time intervals (0, h] are open at the left point and closed at the right point. It also ensures compatibility with precise timing, namely that the offset u fulfills -h > u >= 0.
The resolution (tics per step) can only be set before the first node is created and before the simulation starts. The resolution can be changed after the network has been deleted and the time reset.
Implementers of models or methods containing persistent (member variable) Time objects, must ensure that these are recalibrated before the simulation starts. This is necessary to ensure that step values are updated after a change in resolution.
The default resolution can be changed using the –with-tics_per_step option to configure.

The step-time counter is NOT changed when the resolution is changed. This is of no consequence, since changes in resolution are permitted at t=0 only.

Neurons update themselves in min-delay intervals. During such a min-delay update step, time is in a sense undefined, since it is up to the model how it takes its dynamics across the interval. Any spikes emitted and voltage information returned must be fixed to time grid points.
One may later consider to introduce per-tread simulation time variables.

Is this entire setup still compatible with different step lengths in different subnets, or have we abandoned that idea?

Delays must be added to current time, and moduloed each time a spike is inserted into a ring buffer. That operation must be very fast, and there is no time for conversions. Thus, delays must be stored in steps. Given the large number of delays in a system, we cannot use class Time with its three member variables to store delays. Delays must thus be stored explicitly as delay steps.

Markus Diesmann, 2008-01-25 Hans Ekkehard Plesser, 2004-01-25, 2006-12-18 Marc-Oliver Gewaltig, 2004-01-27

Referenced by nest::Time::range().

template<>

long long nest::time_abs ( long long n )

inline