/*
* pt_module.cpp
* This file is part of NEST.
*
* Copyright (C) 2008 by
* The NEST Initiative
*
* See the file AUTHORS for details.
*
* Permission is granted to compile and modify
* this file for non-commercial use.
* See the file LICENSE for details.
*
*/
// include necessary NEST headers
#include "config.h"
#include "network.h"
#include "model.h"
#include "dynamicloader.h"
#include "genericmodel.h"
#include "generic_connector.h"
#include "booldatum.h"
#include "integerdatum.h"
#include "tokenarray.h"
#include "exceptions.h"
#include "sliexceptions.h"
#include "nestmodule.h"
// include headers with your own stuff
#include "pt_module.h"
#include "bcpnn_connection.h"
#include "iaf_cond_alpha_bias.h"
#include "iaf_cond_exp_bias.h"
#include "aeif_cond_exp_multisynapse.h"
// -- Interface to dynamic module loader ---------------------------------------
/*
* The dynamic module loader must be able to find your module.
* You make the module known to the loader by defining an instance of your
* module class in global scope. This instance must have the name
*
* <modulename>_LTX_mod
*
* The dynamicloader can then load modulename and search for symbol "mod" in it.
*/
mynest::Pt_Module pt_module_LTX_mod;
// -- DynModule functions ------------------------------------------------------
mynest::Pt_Module::Pt_Module()
{
#ifdef LINKED_MODULE
// register this module at the dynamic loader
// this is needed to allow for linking in this module at compile time
// all registered modules will be initialized by the main app's dynamic loader
nest::DynamicLoaderModule::registerLinkedModule(this);
#endif
}
mynest::Pt_Module::~Pt_Module()
{
}
const std::string mynest::Pt_Module::name(void) const
{
return std::string("Pt NEST Module"); // Return name of the module
}
const std::string mynest::Pt_Module::commandstring(void) const
{
/* 1. Tell interpreter that we provide the C++ part of Ml_Module with the
current revision number.
2. Instruct the interpreter to check that ml_module-init.sli exists,
provides at least version 1.0 of the SLI interface to Ml_Module, and
to load it.
*/
return std::string(
// "(pt_module) run"
// FOR NEST 2.4.2 use only the upper one
// FOR NEST 2.2.2 use the lower two lines
"/pt_module /C++ ($Revision: 8512 $) provide-component "
"/pt_module /SLI (7165) require-component"
);
}
/* BeginDocumentation
Name: StepPatternConnect - Connect sources and targets with a stepping pattern
Synopsis:
[sources] source_step [targets] target_step synmod StepPatternConnect -> n_connections
Parameters:
[sources] - Array containing GIDs of potential source neurons
source_step - Make connection from every source_step'th neuron
[targets] - Array containing GIDs of potential target neurons
target_step - Make connection to every target_step'th neuron
synmod - The synapse model to use (literal, must be key in synapsedict)
n_connections - Number of connections made
Description:
This function subsamples the source and target arrays given with steps
source_step and target_step, beginning with the first element in each array,
and connects the selected nodes.
Example:
/first_src 0 /network_size get def
/last_src /iaf_neuron 20 Create def % nodes 1 .. 20
/src [first_src last_src] Range def
/last_tgt /iaf_neuron 10 Create def % nodes 21 .. 30
/tgt [last_src 1 add last_tgt] Range def
src 6 tgt 4 /drop_odd_spike StepPatternConnect
This connects nodes [1, 7, 13, 19] as sources to nodes [21, 25,
29] as targets using synapses of type drop_odd_spike, and
returning 12 as the number of connections. The following
command will print the connections (you must paste the SLI
command as one long line):
src { /s Set << /source s /synapse_type /static_synapse >> FindConnections { GetStatus /target get } Map dup length 0 gt { cout s <- ( -> ) <- exch <-- endl } if ; } forall
1 -> [21 25 29]
7 -> [21 25 29]
13 -> [21 25 29]
19 -> [21 25 29]
Remark:
This function is only provided as an example for how to write your own
interface function.
Author:
Hans Ekkehard Plesser
SeeAlso:
Connect, ConvergentConnect, DivergentConnect
*/
void mynest::Pt_Module::StepPatternConnect_Vi_i_Vi_i_lFunction::execute(SLIInterpreter *i) const
{
// Check if we have (at least) five arguments on the stack.
i->assert_stack_load(5);
// Retrieve source, source step, target, target step from the stack
const TokenArray sources = getValue<TokenArray> (i->OStack.pick(4)); // bottom
const long src_step = getValue<long> (i->OStack.pick(3));
const TokenArray targets = getValue<TokenArray> (i->OStack.pick(2));
const long tgt_step = getValue<long> (i->OStack.pick(1));
const Name synmodel_name = getValue<std::string>(i->OStack.pick(0)); // top
// Obtain synapse model index
const Token synmodel
= nest::NestModule::get_network().get_synapsedict().lookup(synmodel_name);
if ( synmodel.empty() )
throw nest::UnknownSynapseType(synmodel_name.toString());
const nest::index synmodel_id = static_cast<nest::index>(synmodel);
// Build a list of targets with the given step
TokenArray selected_targets;
for ( size_t t = 0 ; t < targets.size() ; t += tgt_step )
selected_targets.push_back(targets[t]);
// Now connect all appropriate sources to this list of targets
size_t Nconn = 0; // counts connections
for ( size_t s = 0 ; s < sources.size() ; s += src_step )
{
// We must first obtain the GID of the source as integer
const nest::long_t sgid = getValue<nest::long_t>(sources[s]);
// nest::network::divergent_connect() requires weight and delay arrays. We want to use
// default values from the synapse model, so we pass empty arrays.
nest::NestModule::get_network().divergent_connect(sgid, selected_targets,
TokenArray(), TokenArray(),
synmodel_id);
Nconn += selected_targets.size();
}
// We get here only if none of the operations above throws and exception.
// Now we can safely remove the arguments from the stack and push Nconn
// as our result.
i->OStack.pop(5);
i->OStack.push(Nconn);
// Finally, we pop the call to this functions from the execution stack.
i->EStack.pop();
}
//-------------------------------------------------------------------------------------
void mynest::Pt_Module::init(SLIInterpreter *i, nest::Network*)
{
/* Register a neuron or device model.
Give node type as template argument and the name as second argument.
The first argument is always a reference to the network.
Return value is a handle for later unregistration.
*/
/* nest::register_model<izhik_cond_exp>(nest::NestModule::get_network(),
"izhik_cond_exp"); */
nest::register_model<iaf_cond_exp_bias>(nest::NestModule::get_network(),
"iaf_cond_exp_bias");
nest::register_model<iaf_cond_alpha_bias>(nest::NestModule::get_network(),
"iaf_cond_alpha_bias");
nest::register_model<aeif_cond_exp_multisynapse>(nest::NestModule::get_network(),
"aeif_cond_exp_multisynapse");
/* Register a synapse type.
Give synapse type as template argument and the name as second argument.
The first argument is always a reference to the network.
*/
nest::register_prototype_connection<BCPNNConnection>(nest::NestModule::get_network(),
"bcpnn_synapse");
/* Register a SLI function.
The first argument is the function name for SLI, the second a pointer to
the function object. If you do not want to overload the function in SLI,
you do not need to give the mangled name. If you give a mangled name, you
should define a type trie in the ml_module-init.sli file.
*/
i->createcommand("StepPatternConnect_Vi_i_Vi_i_l",
&stepPatternConnect_Vi_i_Vi_i_lFunction);
} // Ml_Module::init()
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