InitSparseConnectivitySnippet::FixedProbabilityNoAutapse Class Reference

#include <initSparseConnectivitySnippet.h>

Inheritance diagram for InitSparseConnectivitySnippet::FixedProbabilityNoAutapse:

Public Member Functions
	DECLARE_SNIPPET (InitSparseConnectivitySnippet::FixedProbabilityNoAutapse, 1)
	SET_ROW_BUILD_CODE ("int nextJ;\ "do {\" " const scalar u=$(gennrand_uniform);\" " nextJ=prevJ+(1+(int)(log(u) *$(probLogRecip)));\" "} while(nextJ==$(id_pre));\" "prevJ=nextJ;\" "if(prevJ< $(num_post)) {\" " $(addSynapse, prevJ);\" "}\" "else {\" " $(endRow);\" "}\")
Public Member Functions inherited from InitSparseConnectivitySnippet::FixedProbabilityBase
virtual std::string	getRowBuildCode () const override=0
	SET_ROW_BUILD_STATE_VARS ({{"prevJ", {"int", -1}}})
virtual StringVec	getParamNames () const override
	Gets names of of (independent) model parameters. More...
virtual DerivedParamVec	getDerivedParams () const override
	SET_CALC_MAX_ROW_LENGTH_FUNC ([](unsigned int numPre, unsigned int numPost, const std::vector< double > &pars) { const double quantile=pow(0.9999, 1.0/(double) numPre);return binomialInverseCDF(quantile, numPost, pars[0]);})
	SET_CALC_MAX_COL_LENGTH_FUNC ([](unsigned int numPre, unsigned int numPost, const std::vector< double > &pars) { const double quantile=pow(0.9999, 1.0/(double) numPost);return binomialInverseCDF(quantile, numPre, pars[0]);})
Public Member Functions inherited from InitSparseConnectivitySnippet::Base
virtual NameTypeValVec	getRowBuildStateVars () const
virtual CalcMaxLengthFunc	getCalcMaxRowLengthFunc () const
	Get function to calculate the maximum row length of this connector based on the parameters and the size of the pre and postsynaptic population. More...
virtual CalcMaxLengthFunc	getCalcMaxColLengthFunc () const
	Get function to calculate the maximum column length of this connector based on the parameters and the size of the pre and postsynaptic population. More...
virtual StringPairVec	getExtraGlobalParams () const
Public Member Functions inherited from Snippet::Base
virtual	~Base ()

Additional Inherited Members
Public Types inherited from InitSparseConnectivitySnippet::Base
typedef std::function< unsigned int(unsigned int, unsigned int, const std::vector< double > &)>	CalcMaxLengthFunc
Public Types inherited from Snippet::Base
typedef std::function< double(const std::vector< double > &, double)>	DerivedParamFunc
typedef std::vector< std::string >	StringVec
typedef std::vector< std::pair< std::string, std::string > >	StringPairVec
typedef std::vector< std::pair< std::string, std::pair< std::string, double > > >	NameTypeValVec
typedef std::vector< std::pair< std::string, DerivedParamFunc > >	DerivedParamVec

Detailed Description

Initialises connectivity with a fixed probability of a synapse existing between a pair of pre and postsynaptic neurons. This version ensures there are no autapses - connections between neurons with the same id so should be used for recurrent connections.

Whether a synapse exists between a pair of pre and a postsynaptic neurons can be modelled using a Bernoulli distribution. While this COULD br sampling directly by repeatedly drawing from the uniform distribution, this is innefficient. Instead we sample from the gemetric distribution which describes "the probability distribution of the number of Bernoulli trials needed to get one success" – essentially the distribution of the 'gaps' between synapses. We do this using the "inversion method" described by Devroye (1986) – essentially inverting the CDF of the equivalent continuous distribution (in this case the exponential distribution)

Member Function Documentation

DECLARE_SNIPPET()

InitSparseConnectivitySnippet::FixedProbabilityNoAutapse::DECLARE_SNIPPET	(	InitSparseConnectivitySnippet::FixedProbabilityNoAutapse	,
		1
	)

SET_ROW_BUILD_CODE()

InitSparseConnectivitySnippet::FixedProbabilityNoAutapse::SET_ROW_BUILD_CODE

(

)

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

• initSparseConnectivitySnippet.h