OR

This section shows all the code relative to the OR block.

class sPyBlocks.neural_or.MultipleNeuralOr(n_components, sim, global_params, neuron_params, std_conn)

This class allows to create multiple OR blocks of the same type.

__init__(n_components, sim, global_params, neuron_params, std_conn)

Constructor of the class.

Parameters
  • n_components (int) – The number of blocks to create.

  • sim – The simulator package.

  • global_params (dict) – A dictionary of type str:int which must include the “min_delay” keyword. This keyword is likely to have the time period associated with it as a value.

  • neuron_params (dict) – A dictionary of type str:int containing the neuron parameters.

  • std_conn (sim.StaticSynapse) – The connection to be used for the construction of the blocks. Commonly, its weight is 1.0 and its delay is equal to the timestep.

connect_inputs(input_population, conn=None, conn_all=True, rcp_type='excitatory', ini_pop_indexes=None, end_pop_indexes=None, component_indexes=None)

Connects an input population to the input neurons of the blocks.

Parameters
  • input_population (sim.Population, sim.PopulationView, sim.Assembly, list) – A PyNN object or a list of PyNN objects containing the population to connect to the input neurons.

  • conn (sim.StaticSynapse) – The connection to use. std_conn (class parameter) by default.

  • conn_all – Unused.

  • rcp_type (str) – A string indicating the receptor type of the connections (excitatory or inhibitory). “Excitatory” by default.

  • ini_pop_indexes (list) – A list of indices used to select objects from the input population.

  • end_pop_indexes – Unused.

  • component_indexes (list) – A list of indices used to select components from the list of components.

Returns

The number of connections that have been created.

Return type

int

connect_outputs(output_population, conn=None, conn_all=True, rcp_type='excitatory', ini_pop_indexes=None, end_pop_indexes=None, component_indexes=None)

Connects the output neurons of the blocks to an output population.

Parameters
  • output_population (sim.Population, sim.PopulationView, sim.Assembly, list) – A PyNN object or a list of PyNN objects containing the population to connect the output neurons to.

  • conn (sim.StaticSynapse) – The connection to use. std_conn (class parameter) by default.

  • conn_all – Unused.

  • rcp_type (str) – A string indicating the receptor type of the connections (excitatory or inhibitory). “Excitatory” by default.

  • ini_pop_indexes (list) – Unused.

  • end_pop_indexes – A list of indices used to select objects from the output population.

  • component_indexes (list) – A list of indices used to select components from the list of components.

Returns

The number of connections that have been created.

Return type

int

get_input_neurons(flat=False)

Gets a list containing all the input neurons of the block.

Parameters

flat (bool) – A boolean value indicating whether or not to flatten the list. False by default.

Returns

The flattened or unflattened list containing all the input neurons of the block

Return type

list

get_output_neurons(flat=False)

Gets a list containing all the output neurons of the block.

Parameters

flat (bool) – A boolean value indicating whether or not to flatten the list. False by default.

Returns

The list containing all the output neurons of the block

Return type

list

class sPyBlocks.neural_or.NeuralOr(sim, global_params, neuron_params, std_conn)

This class defines the OR block.

__init__(sim, global_params, neuron_params, std_conn)

Constructor of the class.

Parameters
  • sim – The simulator package.

  • global_params (dict) – A dictionary of type str:int which must include the “min_delay” keyword. This keyword is likely to have the time period associated with it as a value.

  • neuron_params (dict) – A dictionary of type str:int containing the neuron parameters.

  • std_conn (sim.StaticSynapse) – The connection to be used for the construction of the block. Commonly, its weight is 1.0 and its delay is equal to the timestep.

connect_inputs(input_population, conn=None, conn_all=True, rcp_type='excitatory', ini_pop_indexes=None, end_pop_indexes=None)

Connects an input population to the input neurons of the block.

Parameters
  • input_population (sim.Population, sim.PopulationView, sim.Assembly, list) – A PyNN object or a list of PyNN objects containing the population to connect to the input neurons.

  • conn (sim.StaticSynapse) – The connection to use. std_conn (class parameter) by default.

  • conn_all – Unused.

  • rcp_type (str) – A string indicating the receptor type of the connections (excitatory or inhibitory). “Excitatory” by default.

  • ini_pop_indexes (list) – A list of indices used to select objects from the input population.

  • end_pop_indexes – Unused.

Returns

The number of connections that have been created.

Return type

int

connect_outputs(output_population, conn=None, conn_all=True, rcp_type='excitatory', ini_pop_indexes=None, end_pop_indexes=None)

Connects the output neurons of the block to an output population.

Parameters
  • output_population (sim.Population, sim.PopulationView, sim.Assembly, list) – A PyNN object or a list of PyNN objects containing the population to connect the output neurons to.

  • conn (sim.StaticSynapse) – The connection to use. std_conn (class parameter) by default.

  • conn_all – Unused.

  • rcp_type (str) – A string indicating the receptor type of the connections (excitatory or inhibitory). “Excitatory” by default.

  • ini_pop_indexes (list) – Unused.

  • end_pop_indexes – A list of indices used to select objects from the output population.

Returns

The number of connections that have been created.

Return type

int

get_input_neuron(flat=False)

Gets a list containing all the input neurons of the block.

Parameters

flat (bool) – Unused.

Returns

The flattened or unflattened list containing all the input neurons of the block

Return type

list

get_output_neuron(flat=False)

Gets a list containing all the output neurons of the block.

Parameters

flat (bool) – Unused.

Returns

The list containing all the output neurons of the block

Return type

list