class pygenn::genn_model::GeNNModel

Overview

GeNNModel class This class helps to define, build and run a GeNN model from python. More…

class GeNNModel: public object
{
public:
    // fields

     use_backend;
     default_var_location;
     model_name;
     neuron_populations;
     synapse_populations;
     current_sources;
     dT;
     T;

    // methods

    def __init__();
    def use_backend();
    def default_var_location();
    def default_sparse_connectivity_location();
    def model_name();
    def t();
    def timestep();
    def dT();
    def add_neuron_population();
    def add_synapse_population();
    def add_current_source();
    def build();
    def load();
    def reinitialise();
    def step_time();
    def pull_state_from_device();
    def pull_spikes_from_device();
    def pull_current_spikes_from_device();
    def pull_connectivity_from_device();
    def pull_var_from_device();
    def push_state_to_device();
    def push_spikes_to_device();
    def push_current_spikes_to_device();
    def push_connectivity_to_device();
    def push_var_to_device();
    def end();
};

Detailed Documentation

GeNNModel class This class helps to define, build and run a GeNN model from python.

Methods

def __init__()

Init GeNNModel.

Parameters:

precision	string precision as string (“float”, “double” or “long double”). defaults to float.
model_name	string name of the model. Defaults to “GeNNModel”.
enable_debug	boolean enable debug mode. Disabled by default.
backend	string specifying name of backend module to use Defaults to None to pick ‘best’ backend for your system

def default_var_location()

Default variable location - defines where state variables are initialised.

def default_sparse_connectivity_location()

Default sparse connectivity mode - where connectivity is initialised.

def model_name()

Name of the model.

def t()

Simulation time in ms.

def timestep()

Simulation time step.

def dT()

Step size.

def add_neuron_population()

Add a neuron population to the GeNN model.

Parameters:

pop_name	name of the new population
num_neurons	number of neurons in the new population
neuron	type of the NeuronModels class as string or instance of neuron class derived from pygenn.genn_wrapper.NeuronModels.Custom (see also pygenn.genn_model.create_custom_neuron_class)
param_space	dict with param values for the NeuronModels class
var_space	dict with initial variable values for the NeuronModels class

def add_synapse_population()

Add a synapse population to the GeNN model.

Parameters:

pop_name	name of the new population
matrix_type	type of the matrix as string
delay_steps	delay in number of steps
source	source neuron group
target	target neuron group
w_update_model	type of the WeightUpdateModels class as string or instance of weight update model class derived from pygenn.genn_wrapper.WeightUpdateModels.Custom (see also pygenn.genn_model.create_custom_weight_update_class)
wu_param_space	dict with param values for the WeightUpdateModels class
wu_var_space	dict with initial values for WeightUpdateModels state variables
wu_pre_var_space	dict with initial values for WeightUpdateModels presynaptic variables
wu_post_var_space	dict with initial values for WeightUpdateModels postsynaptic variables
postsyn_model	type of the PostsynapticModels class as string or instance of postsynaptic model class derived from pygenn.genn_wrapper.PostsynapticModels.Custom (see also pygenn.genn_model.create_custom_postsynaptic_class)
ps_param_space	dict with param values for the PostsynapticModels class
ps_var_space	dict with initial variable values for the PostsynapticModels class
connectivity_initialiser	InitSparseConnectivitySnippet::Init for connectivity

def add_current_source()

Add a current source to the GeNN model.

Parameters:

cs_name	name of the new current source
current_source_model	type of the CurrentSourceModels class as string or instance of CurrentSourceModels class derived from pygenn.genn_wrapper.CurrentSourceModels.Custom (see also pygenn.genn_model.create_custom_current_source_class)
pop_name	name of the population into which the current source should be injected
param_space	dict with param values for the CurrentSourceModels class
var_space	dict with initial variable values for the CurrentSourceModels class

def build()

Finalize and build a GeNN model.

Parameters:

path_to_model

path where to place the generated model code. Defaults to the local directory.

def load()

import the model as shared library and initialize it

def reinitialise()

reinitialise model to its original state without re-loading

def pull_state_from_device()

Pull state from the device for a given population.

def pull_spikes_from_device()

Pull spikes from the device for a given population.

def pull_current_spikes_from_device()

Pull spikes from the device for a given population.

def pull_connectivity_from_device()

Pull connectivity from the device for a given population.

def pull_var_from_device()

Pull variable from the device for a given population.

def push_state_to_device()

Push state to the device for a given population.

def push_spikes_to_device()

Push spikes to the device for a given population.

def push_current_spikes_to_device()

Push current spikes to the device for a given population.

def push_connectivity_to_device()

Push connectivity to the device for a given population.

def push_var_to_device()

Push variable to the device for a given population.

def end()

Free memory.