#include <spiking_utils.hpp>

Static Public Member Functions
template<typename T >
static PopulationBase	add_typed_population (Network &network, const NeuronParameter &neuronParams, const size_t size, const typename T::Signals &rec_signal=typename T::Signals().record_spikes())

template<typename T >
static cypress::PopulationBase	add_typed_population_no_record (Network &network, const NeuronParameter &neuronParams, const size_t size)

static const NeuronType &	detect_type (std::string neuron_type_str)

static cypress::PopulationBase	add_population (const std::string neuron_type_str, Network &network, const NeuronParameter &neuronParams, const size_t size, const std::string record_signal="")

static bool	rerun_fixed_number_trials (Network &network, Backend &backend, Real time, size_t n_trials=3)

static int	calc_num_spikes (const std::vector< cypress::Real > &spiketrain, const cypress::Real start=0.0, const cypress::Real end=0.0)
	Calculate the number of spikes of spiketrain in interval [start,stop]. More...

template<typename T >
static std::vector< int >	calc_num_spikes_vec (const cypress::Matrix< T > &spiketrains, const cypress::Real start=0.0, const cypress::Real end=std::numeric_limits< cypress::Real >::max())
	Calculate the number of spikes in a vector of spiketrains in intervall [start,stop]. More...

template<typename T >
static std::vector< T >	spike_time_binning (const Real &start, const Real &stop, const size_t &n_bins, const std::vector< cypress::Real > &spike_times)

static std::vector< Real >	spike_time_binning_TTFS (const Real &start, const Real &stop, const size_t &n_bins, const std::vector< cypress::Real > &spike_times)

Member Function Documentation

static cypress::PopulationBase cypress::SpikingUtils::add_population	(	const std::string	neuron_type_str,
		Network &	network,
		const NeuronParameter &	neuronParams,
		const size_t	size,
		const std::string	record_signal = `""`
	)

static

Runs SpikingUtils::add_typed_population, but gets a string containing the neuron type instead of a template argument

Parameters

neuron_type_str	string naming the neuron type
network	instace in wich the population is placed
neuronParams	Neuron parameters of the cell in the population
size	Number of neurons in the population
record_signal	string of the signal to be recorded by the backend, e.g. "spikes" or "v"

template<typename T >

static PopulationBase cypress::SpikingUtils::add_typed_population	(	Network &	network,
		const NeuronParameter &	neuronParams,
		const size_t	size,
		const typename T::Signals &	rec_signal = `typename T::Signals().record_spikes()`
	)

inlinestatic

Creates a population of type T and adds them to m_net

Parameters

network	instace in wich the population is placed
neuronParams	Neuron parameters of the cell in the population
size	Number of neurons in the population
rec_signal	signal to be recorded by the backend

Returns: Network containing the add Population (same as network)

template<typename T >

static cypress::PopulationBase cypress::SpikingUtils::add_typed_population_no_record	(	Network &	network,
		const NeuronParameter &	neuronParams,
		const size_t	size
	)

static

Creates a population of type T and adds them to m_net without recording

Parameters

network	instace in wich the population is placed
neuronParams	Neuron parameters of the cell in the population
size	Number of neurons in the population

Returns: Network containing the add Population (same as network)

static int cypress::SpikingUtils::calc_num_spikes	(	const std::vector< cypress::Real > &	spiketrain,
		const cypress::Real	start = `0.0`,
		const cypress::Real	end = `0.0`
	)

static

Calculate the number of spikes of spiketrain in interval [start,stop].

Parameters

spiketrain	The spiketrain for which the number of spikes should be calculated
start	Timepoint from which counting starts
end	Endpoint where counting stops

Returns: int returns the number of spikes in [start, stop]

template<typename T >

static std::vector<int> cypress::SpikingUtils::calc_num_spikes_vec	(	const cypress::Matrix< T > &	spiketrains,
		const cypress::Real	start = `0.0`,
		const cypress::Real	end = `std::numeric_limits<cypress::Real>::max()`
	)

inlinestatic

Calculate the number of spikes in a vector of spiketrains in intervall [start,stop].

Parameters

spiketrains	The vector of spiketrains for which the number of spikes should be calculated
start	Timepoint from which counting starts
end	Endpoint where counting stops, leave empty to count all

Returns: int returns the number of spikes in [start, stop]

static const NeuronType& cypress::SpikingUtils::detect_type ( std::string neuron_type_str )

static

Generates a NeuronType object from a string

Parameters

neuron_type_str string naming the neuron type

Returns: the corresponding NeuronType object

static bool cypress::SpikingUtils::rerun_fixed_number_trials	(	Network &	network,
		Backend &	backend,
		Real	time,
		size_t	n_trials = `3`
	)

static

Tries to run the simulation on given backend several times if backend produces an unexpected error (needed for e.g. BrainScaleS).

Parameters

network	network object to simulate
backend	target of the simulation
time	simulation time
n_trials	number of trials before giving up

Returns: true if simulation was succesful

template<typename T >

static std::vector<T> cypress::SpikingUtils::spike_time_binning	(	const Real &	start,
		const Real &	stop,
		const size_t &	n_bins,
		const std::vector< cypress::Real > &	spike_times
	)

inlinestatic

Calculate the number of spikes in given intervals (bins) of a single spike train. Size of bins is calculated from start, stop and the number of bins n_bins

Parameters

start	time for starting the binning. First bin is [start, start + bin_size]
stop	end time of last bin
n_bins	number of bins
spike_times	vector containing spike times as given by neuron.signals().data(0)

Returns: A vector with each entry representing a bin, containing the number of spikes that appeared in that bin

static std::vector<Real> cypress::SpikingUtils::spike_time_binning_TTFS	(	const Real &	start,
		const Real &	stop,
		const size_t &	n_bins,
		const std::vector< cypress::Real > &	spike_times
	)

static

Calculate the first spike in given intervals (bins) of a single spike train. Size of bins is calculated from start, stop and the number of bins n_bins

Parameters

start	time for starting the binning. First bin is [start, start + bin_size]
stop	end time of last bin
n_bins	number of bins
spike_times	vector containing spike times as given by neuron.signals().data(0)

Returns: A vector with each entry representing a bin, containing the first spike that appeared in that bin

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

cypress/util/spiking_utils.hpp

Static Public Member Functions

Member Function Documentation