mip_generator.h

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/*
 *  mip_generator.h
 *
 *  This file is part of NEST.
 *
 *  Copyright (C) 2004 The NEST Initiative
 *
 *  NEST is free software: you can redistribute it and/or modify
 *  it under the terms of the GNU General Public License as published by
 *  the Free Software Foundation, either version 2 of the License, or
 *  (at your option) any later version.
 *
 *  NEST is distributed in the hope that it will be useful,
 *  but WITHOUT ANY WARRANTY; without even the implied warranty of
 *  MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
 *  GNU General Public License for more details.
 *
 *  You should have received a copy of the GNU General Public License
 *  along with NEST.  If not, see <http://www.gnu.org/licenses/>.
 *
 */
 
#ifndef MIP_GENERATOR_H
#define MIP_GENERATOR_H
 
// Includes from nestkernel:
#include "connection.h"
#include "device_node.h"
#include "event.h"
#include "nest_types.h"
#include "random_generators.h"
#include "stimulation_device.h"
 
namespace nest
{
 
/* BeginUserDocs: device, generator
 
Short description
+++++++++++++++++
 
Create spike trains as described by the MIP model
 
Description
+++++++++++
 
The ``mip_generator`` generates correlated spike trains using an Multiple
Interaction Process (MIP) as described in :footcite:p:`Kuhn2003`. Underlying principle is a
Poisson parent process with rate r, the spikes of which are copied into the
child processes with a certain probability p. Every node the mip_generator is
connected to receives a distinct child process as input, whose rate is `p*r`.
The value of the pairwise correlation coefficient of two child processes
created by a MIP process equals p.
 
The MIP generator may emit more than one spike through a child process
during a single time step, especially at high rates.  If this happens,
the generator does not actually send out n spikes.  Instead, it emits
a single spike with n-fold synaptic weight for the sake of efficiency.
Furthermore, note that as with the Poisson generator, different threads
have their own copy of a MIP generator. By using the same mother_seed
it is ensured that the mother process is identical for each of the
generators.
 
.. include:: ../models/stimulation_device.rst
 
rate
    Mean firing rate of the parent process, spikes/s
 
p_copy
    Copy probability
 
Set parameters from a stimulation backend
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
 
The parameters in this stimulation device can be updated with input
coming from a stimulation backend. The data structure used for the
update holds one value for each of the parameters mentioned above.
The indexing is as follows:
 
 0. rate
 1. p_copy
 
Sends
+++++
 
SpikeEvent
 
References
++++++++++
 
.. footbibliography::
 
See also
++++++++
 
poisson_generator
 
Examples using this model
+++++++++++++++++++++++++
 
.. listexamples:: mip_generator
 
EndUserDocs */
 
void register_mip_generator( const std::string& name );
 
class mip_generator : public StimulationDevice
{
 
public:
  mip_generator();
  mip_generator( const mip_generator& rhs );
 
  using Node::event_hook;
 
  size_t send_test_event( Node&, size_t, synindex, bool ) override;
 
  void get_status( Dictionary& ) const override;
  void set_status( const Dictionary& ) override;
 
  StimulationDevice::Type get_type() const override;
  void set_data_from_stimulation_backend( std::vector< double >& input_param ) override;
 
private:
  void init_state_() override;
  void init_buffers_() override;
  void pre_run_hook() override;
 
  void update( Time const&, const long, const long ) override;
 
  void event_hook( DSSpikeEvent& ) override;
 
  // ------------------------------------------------------------
 
  struct Parameters_
  {
    double rate_;    
    double p_copy_;  
 
    Parameters_();  
 
    void get( Dictionary& ) const;              
    void set( const Dictionary&, Node* node );  
  };
 
  // ------------------------------------------------------------
 
  struct Variables_
  {
    poisson_distribution poisson_dist_;  
  };
 
  // ------------------------------------------------------------
 
  Parameters_ P_;
  Variables_ V_;
};
 
inline size_t
mip_generator::send_test_event( Node& target, size_t receptor_type, synindex syn_id, bool dummy_target )
{
  StimulationDevice::enforce_single_syn_type( syn_id );
 
  if ( dummy_target )
  {
    DSSpikeEvent e;
    e.set_sender( *this );
    return target.handles_test_event( e, receptor_type );
  }
  else
  {
    SpikeEvent e;
    e.set_sender( *this );
    return target.handles_test_event( e, receptor_type );
  }
}
 
inline void
mip_generator::get_status( Dictionary& d ) const
{
  P_.get( d );
  StimulationDevice::get_status( d );
}
 
inline void
mip_generator::set_status( const Dictionary& d )
{
  Parameters_ ptmp = P_;  // temporary copy in case of errors
  ptmp.set( d, this );    // throws if BadProperty
 
  // We now know that ptmp is consistent. We do not write it back
  // to P_ before we are also sure that the properties to be set
  // in the parent class are internally consistent.
  StimulationDevice::set_status( d );
 
  // if we get here, temporaries contain consistent set of properties
  P_ = ptmp;
}
 
inline StimulationDevice::Type
mip_generator::get_type() const
{
  return StimulationDevice::Type::SPIKE_GENERATOR;
}
 
}  // namespace nest
 
#endif