examples/example_24_large_scale_brian2_simulation/clusternet.py
def _build_model(self, traj, brian_list, network_dict):
        """Builds the neuron groups from `traj`.

        Adds the neuron groups to `brian_list` and `network_dict`.

        """

        model = traj.parameters.model

        # Create the equations for both models
        eqs_dict = self._build_model_eqs(traj)

        # Create inhibitory neurons
        eqs_i = eqs_dict['i']
        neurons_i = NeuronGroup(N=model.N_i,
                              model = eqs_i,
                              threshold=model.V_th,
                              reset=model.reset_func,
                              refractory=model.refractory,
                              method='Euler')

        # Create excitatory neurons
        eqs_e = eqs_dict['e']
        neurons_e = NeuronGroup(N=model.N_e,
                              model = eqs_e,
                              threshold=model.V_th,
                              reset=model.reset_func,
                              refractory=model.refractory,
                              method='Euler')


        # Set the bias terms
        neurons_e.mu =rand(model.N_e) * (model.mu_e_max - model.mu_e_min) + model.mu_e_min
        neurons_i.mu =rand(model.N_i) * (model.mu_i_max - model.mu_i_min) + model.mu_i_min

        # Set initial membrane potentials
        neurons_e.V = rand(model.N_e)
        neurons_i.V = rand(model.N_i)

        # Add both groups to the `brian_list` and the `network_dict`
        brian_list.append(neurons_i)
        brian_list.append(neurons_e)
        network_dict['neurons_e']=neurons_e
        network_dict['neurons_i']=neurons_i
def _build_model(self, traj, brian_list, network_dict):
        model = traj.parameters.model

        # Create the equations for both models
        eqs_dict = self._build_model_eqs(traj)

        # Create inhibitory neurons
        eqs_i = eqs_dict['i']
        neurons_i = NeuronGroup(N=model.N_i,
                              model = eqs_i,
                              threshold=model.V_th,
                              reset=model.reset_func,
                              refractory=model.refractory,
                              method='Euler')

        # Create excitatory neurons
        eqs_e = eqs_dict['e']
        neurons_e = NeuronGroup(N=model.N_e,
                              model = eqs_e,
                              threshold=model.V_th,
                              reset=model.reset_func,
                              refractory=model.refractory,
                              method='Euler')


        # Set the bias terms
        neurons_e.mu =rand(model.N_e) * (model.mu_e_max - model.mu_e_min) + model.mu_e_min
        neurons_i.mu =rand(model.N_i) * (model.mu_i_max - model.mu_i_min) + model.mu_i_min

        # Set initial membrane potentials
        neurons_e.V = rand(model.N_e)
        neurons_i.V = rand(model.N_i)

        # Add both groups to the `brian_list` and the `network_dict`
        brian_list.append(neurons_i)
        brian_list.append(neurons_e)
        network_dict['neurons_e']=neurons_e
        network_dict['neurons_i']=neurons_i
def _build_model ( self , traj , brian_list , network_dict ) : model = traj . parameters . model # Create the equations for both models eqs_dict = self . _build_model_eqs ( traj ) # Create inhibitory neurons eqs_i = eqs_dict [ 'i' ] neurons_i = NeuronGroup ( N = model . N_i , model = eqs_i , threshold = model . V_th , reset = model . reset_func , refractory = model . refractory , method = 'Euler' ) # Create excitatory neurons eqs_e = eqs_dict [ 'e' ] neurons_e = NeuronGroup ( N = model . N_e , model = eqs_e , threshold = model . V_th , reset = model . reset_func , refractory = model . refractory , method = 'Euler' ) # Set the bias terms neurons_e . mu = rand ( model . N_e ) * ( model . mu_e_max - model . mu_e_min ) + model . mu_e_min neurons_i . mu = rand ( model . N_i ) * ( model . mu_i_max - model . mu_i_min ) + model . mu_i_min # Set initial membrane potentials neurons_e . V = rand ( model . N_e ) neurons_i . V = rand ( model . N_i ) # Add both groups to the `brian_list` and the `network_dict` brian_list . append ( neurons_i ) brian_list . append ( neurons_e ) network_dict [ 'neurons_e' ] = neurons_e network_dict [ 'neurons_i' ] = neurons_i
Builds the neuron groups from `traj`.

        Adds the neuron groups to `brian_list` and `network_dict`.
Builds the neuron groups from traj .