|
| | DECLARE_SNIPPET (InitSparseConnectivitySnippet::FixedNumberTotalWithReplacement, 1) |
| |
| | SET_ROW_BUILD_CODE ("if(c == 0) {\ " $(endRow);\" "}\" "const scalar u=$(gennrand_uniform);\" "x+=(1.0 - x) *(1.0 - pow(u, 1.0/(scalar) c));\" "unsigned int postIdx=(unsigned int)(x *$(num_post));\" "postIdx=(postIdx< $(num_post)) ? postIdx :($(num_post) - 1);\" "$(addSynapse, postIdx+$(id_post_begin));\" "c--;\") |
| |
| | SET_ROW_BUILD_STATE_VARS ({{"x", "scalar", 0.0},{"c", "unsigned int", "$(preCalcRowLength)[($(id_pre) * $(num_threads)) + $(id_thread)]"}}) |
| |
| virtual StringVec | getParamNames () const override |
| | Gets names of of (independent) model parameters. More...
|
| |
| virtual EGPVec | getExtraGlobalParams () const override |
| |
| | SET_HOST_INIT_CODE ("// Allocate pre-calculated row length array\ "$(allocatepreCalcRowLength, $(num_pre) *$(num_threads));\" "//Calculate row lengths\" "const size_t numPostPerThread=($(num_post)+$(num_threads) - 1)/$(num_threads);\" "const size_t leftOverNeurons=$(num_post) % numPostPerThread;\" "size_t remainingConnections=$(total);\" "size_t matrixSize=(size_t)$(num_pre) *(size_t)$(num_post);\" "uint16_t *subRowLengths=$(preCalcRowLength);\" "//Loop through rows\" "for(size_t i=0;i< $(num_pre);i++) {\" " const bool lastPre=(i==($(num_pre) - 1));\" "//Loop through subrows\" " for(size_t j=0;j< $(num_threads);j++) {\" " const bool lastSubRow=(j==($(num_threads) - 1));\" "//If this isn 't the last sub-row of the matrix\" " if(!lastPre||! lastSubRow) {\" "//Get length of this subrow\" " const unsigned int numSubRowNeurons=(leftOverNeurons !=0 &&lastSubRow) ? leftOverNeurons :numPostPerThread;\" "//Calculate probability\" " const double probability=(double) numSubRowNeurons/(double) matrixSize;\" "//Create distribution to sample row length\" " std::binomial_distribution< size_t > rowLengthDist(remainingConnections, probability);\" "//Sample row length;\" " const size_t subRowLength=rowLengthDist($(rng));\" "//Update counters\" " remainingConnections -=subRowLength;\" " matrixSize -=numSubRowNeurons;\" "//Add row length to array\" " assert(subRowLength< std::numeric_limits< uint16_t >::max());\" " *subRowLengths++=(uint16_t) subRowLength;\" " }\" " }\" "}\" "//Insert remaining connections into last sub-row\" " *subRowLengths=(uint16_t) remainingConnections;\" "//Push populated row length array\" "$(pushpreCalcRowLength, $(num_pre) *$(num_threads));\") |
| |
| | 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,(unsigned int) pars[0],(double) numPost/((double) numPre *(double) numPost));}) |
| |
| | 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,(unsigned int) pars[0],(double) numPre/((double) numPre *(double) numPost));}) |
| |
| virtual std::string | getRowBuildCode () const |
| |
| virtual ParamValVec | getRowBuildStateVars () const |
| |
| virtual std::string | getColBuildCode () const |
| |
| virtual ParamValVec | getColBuildStateVars () const |
| |
| virtual std::string | getHostInitCode () 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 CalcKernelSizeFunc | getCalcKernelSizeFunc () const |
| | Get function to calculate kernel size required for this conenctor based on its parameters. More...
|
| |
| boost::uuids::detail::sha1::digest_type | getHashDigest () const |
| | Update hash from snippet. More...
|
| |
| void | validate () const |
| | Validate names of parameters etc. More...
|
| |
| virtual | ~Base () |
| |
| virtual DerivedParamVec | getDerivedParams () const |
| |
| size_t | getExtraGlobalParamIndex (const std::string ¶mName) const |
| | Find the index of a named extra global parameter. More...
|
| |
Initialises connectivity with a total number of random synapses. The first stage in using this connectivity is to determine how many of the total synapses end up in each row. This can be determined by sampling from the multinomial distribution. However, this operation cannot be efficiently parallelised so must be performed on the host and the result passed as an extra global parameter array.
Once the length of each row is determined, the postsynaptic targets of the synapses can be initialised in parallel by sampling from the discrete uniform distribution. However, to sample connections in ascending order, we sample from the 1st order statistic of the uniform distribution – Beta[1, Npost] – essentially the next smallest value. In this special case this is equivalent to the exponential distribution which can be sampled in constant time using the inversion method.
Public Member Functions inherited from InitSparseConnectivitySnippet::Base
1.8.13