spynnaker.pyNN.models package¶
Subpackages¶
- spynnaker.pyNN.models.abstract_models package
- Submodules
- spynnaker.pyNN.models.abstract_models.abstract_accepts_incoming_synapses module
- spynnaker.pyNN.models.abstract_models.abstract_contains_units module
- spynnaker.pyNN.models.abstract_models.abstract_filterable_edge module
- spynnaker.pyNN.models.abstract_models.abstract_population_initializable module
- spynnaker.pyNN.models.abstract_models.abstract_population_settable module
- spynnaker.pyNN.models.abstract_models.abstract_read_parameters_before_set module
- spynnaker.pyNN.models.abstract_models.abstract_settable module
- spynnaker.pyNN.models.abstract_models.abstract_weight_updatable module
- Module contents
- spynnaker.pyNN.models.common package
- Submodules
- spynnaker.pyNN.models.common.abstract_neuron_recordable module
- spynnaker.pyNN.models.common.abstract_spike_recordable module
- spynnaker.pyNN.models.common.eieio_spike_recorder module
- spynnaker.pyNN.models.common.multi_spike_recorder module
- spynnaker.pyNN.models.common.neuron_recorder module
- spynnaker.pyNN.models.common.recording_utils module
- spynnaker.pyNN.models.common.simple_population_settable module
- Module contents
- spynnaker.pyNN.models.neural_projections package
- Subpackages
- spynnaker.pyNN.models.neural_projections.connectors package
- Submodules
- spynnaker.pyNN.models.neural_projections.connectors.abstract_connector module
- spynnaker.pyNN.models.neural_projections.connectors.abstract_generate_connector_on_machine module
- spynnaker.pyNN.models.neural_projections.connectors.all_to_all_connector module
- spynnaker.pyNN.models.neural_projections.connectors.array_connector module
- spynnaker.pyNN.models.neural_projections.connectors.csa_connector module
- spynnaker.pyNN.models.neural_projections.connectors.distance_dependent_probability_connector module
- spynnaker.pyNN.models.neural_projections.connectors.fixed_number_post_connector module
- spynnaker.pyNN.models.neural_projections.connectors.fixed_number_pre_connector module
- spynnaker.pyNN.models.neural_projections.connectors.fixed_probability_connector module
- spynnaker.pyNN.models.neural_projections.connectors.from_list_connector module
- spynnaker.pyNN.models.neural_projections.connectors.index_based_probability_connector module
- spynnaker.pyNN.models.neural_projections.connectors.kernel_connector module
- spynnaker.pyNN.models.neural_projections.connectors.multapse_connector module
- spynnaker.pyNN.models.neural_projections.connectors.one_to_one_connector module
- spynnaker.pyNN.models.neural_projections.connectors.small_world_connector module
- Module contents
- spynnaker.pyNN.models.neural_projections.connectors package
- Submodules
- spynnaker.pyNN.models.neural_projections.delay_afferent_application_edge module
- spynnaker.pyNN.models.neural_projections.delay_afferent_machine_edge module
- spynnaker.pyNN.models.neural_projections.delayed_application_edge module
- spynnaker.pyNN.models.neural_projections.delayed_machine_edge module
- spynnaker.pyNN.models.neural_projections.projection_application_edge module
- spynnaker.pyNN.models.neural_projections.projection_machine_edge module
- spynnaker.pyNN.models.neural_projections.synapse_information module
- Module contents
- Subpackages
- spynnaker.pyNN.models.neural_properties package
- spynnaker.pyNN.models.neuron package
- Subpackages
- spynnaker.pyNN.models.neuron.additional_inputs package
- spynnaker.pyNN.models.neuron.builds package
- Submodules
- spynnaker.pyNN.models.neuron.builds.eif_cond_alpha_isfa_ista module
- spynnaker.pyNN.models.neuron.builds.hh_cond_exp module
- spynnaker.pyNN.models.neuron.builds.if_cond_alpha module
- spynnaker.pyNN.models.neuron.builds.if_cond_exp_base module
- spynnaker.pyNN.models.neuron.builds.if_cond_exp_stoc module
- spynnaker.pyNN.models.neuron.builds.if_curr_alpha module
- spynnaker.pyNN.models.neuron.builds.if_curr_delta module
- spynnaker.pyNN.models.neuron.builds.if_curr_dual_exp_base module
- spynnaker.pyNN.models.neuron.builds.if_curr_exp_base module
- spynnaker.pyNN.models.neuron.builds.if_curr_exp_ca2_adaptive module
- spynnaker.pyNN.models.neuron.builds.if_curr_exp_semd_base module
- spynnaker.pyNN.models.neuron.builds.if_facets_hardware1 module
- spynnaker.pyNN.models.neuron.builds.izk_cond_exp_base module
- spynnaker.pyNN.models.neuron.builds.izk_curr_exp_base module
- Module contents
- spynnaker.pyNN.models.neuron.implementations package
- Submodules
- spynnaker.pyNN.models.neuron.implementations.abstract_neuron_impl module
- spynnaker.pyNN.models.neuron.implementations.abstract_standard_neuron_component module
- spynnaker.pyNN.models.neuron.implementations.neuron_impl_standard module
- spynnaker.pyNN.models.neuron.implementations.ranged_dict_vertex_slice module
- spynnaker.pyNN.models.neuron.implementations.struct module
- Module contents
- spynnaker.pyNN.models.neuron.input_types package
- Submodules
- spynnaker.pyNN.models.neuron.input_types.abstract_input_type module
- spynnaker.pyNN.models.neuron.input_types.input_type_conductance module
- spynnaker.pyNN.models.neuron.input_types.input_type_current module
- spynnaker.pyNN.models.neuron.input_types.input_type_current_semd module
- Module contents
- spynnaker.pyNN.models.neuron.master_pop_table_generators package
- spynnaker.pyNN.models.neuron.neuron_models package
- spynnaker.pyNN.models.neuron.plasticity package
- Subpackages
- spynnaker.pyNN.models.neuron.plasticity.stdp package
- Subpackages
- spynnaker.pyNN.models.neuron.plasticity.stdp.common package
- spynnaker.pyNN.models.neuron.plasticity.stdp.synapse_structure package
- Submodules
- spynnaker.pyNN.models.neuron.plasticity.stdp.synapse_structure.abstract_synapse_structure module
- spynnaker.pyNN.models.neuron.plasticity.stdp.synapse_structure.synapse_structure_weight_accumulator module
- spynnaker.pyNN.models.neuron.plasticity.stdp.synapse_structure.synapse_structure_weight_only module
- Module contents
- spynnaker.pyNN.models.neuron.plasticity.stdp.timing_dependence package
- Submodules
- spynnaker.pyNN.models.neuron.plasticity.stdp.timing_dependence.abstract_timing_dependence module
- spynnaker.pyNN.models.neuron.plasticity.stdp.timing_dependence.timing_dependence_pfister_spike_triplet module
- spynnaker.pyNN.models.neuron.plasticity.stdp.timing_dependence.timing_dependence_recurrent module
- spynnaker.pyNN.models.neuron.plasticity.stdp.timing_dependence.timing_dependence_spike_nearest_pair module
- spynnaker.pyNN.models.neuron.plasticity.stdp.timing_dependence.timing_dependence_spike_pair module
- spynnaker.pyNN.models.neuron.plasticity.stdp.timing_dependence.timing_dependence_vogels_2011 module
- Module contents
- spynnaker.pyNN.models.neuron.plasticity.stdp.weight_dependence package
- Submodules
- spynnaker.pyNN.models.neuron.plasticity.stdp.weight_dependence.abstract_has_a_plus_a_minus module
- spynnaker.pyNN.models.neuron.plasticity.stdp.weight_dependence.abstract_weight_dependence module
- spynnaker.pyNN.models.neuron.plasticity.stdp.weight_dependence.weight_dependence_additive module
- spynnaker.pyNN.models.neuron.plasticity.stdp.weight_dependence.weight_dependence_additive_triplet module
- spynnaker.pyNN.models.neuron.plasticity.stdp.weight_dependence.weight_dependence_multiplicative module
- Module contents
- Module contents
- Subpackages
- spynnaker.pyNN.models.neuron.plasticity.stdp package
- Module contents
- Subpackages
- spynnaker.pyNN.models.neuron.synapse_dynamics package
- Submodules
- spynnaker.pyNN.models.neuron.synapse_dynamics.abstract_generate_on_machine module
- spynnaker.pyNN.models.neuron.synapse_dynamics.abstract_plastic_synapse_dynamics module
- spynnaker.pyNN.models.neuron.synapse_dynamics.abstract_static_synapse_dynamics module
- spynnaker.pyNN.models.neuron.synapse_dynamics.abstract_synapse_dynamics module
- spynnaker.pyNN.models.neuron.synapse_dynamics.abstract_synapse_dynamics_structural module
- spynnaker.pyNN.models.neuron.synapse_dynamics.pynn_synapse_dynamics module
- spynnaker.pyNN.models.neuron.synapse_dynamics.structural_dynamics module
- spynnaker.pyNN.models.neuron.synapse_dynamics.synapse_dynamics_static module
- spynnaker.pyNN.models.neuron.synapse_dynamics.synapse_dynamics_stdp module
- spynnaker.pyNN.models.neuron.synapse_dynamics.synapse_dynamics_structural_common module
- spynnaker.pyNN.models.neuron.synapse_dynamics.synapse_dynamics_structural_static module
- spynnaker.pyNN.models.neuron.synapse_dynamics.synapse_dynamics_structural_stdp module
- Module contents
- spynnaker.pyNN.models.neuron.synapse_io package
- spynnaker.pyNN.models.neuron.synapse_types package
- Submodules
- spynnaker.pyNN.models.neuron.synapse_types.abstract_synapse_type module
- spynnaker.pyNN.models.neuron.synapse_types.synapse_type_alpha module
- spynnaker.pyNN.models.neuron.synapse_types.synapse_type_delta module
- spynnaker.pyNN.models.neuron.synapse_types.synapse_type_dual_exponential module
- spynnaker.pyNN.models.neuron.synapse_types.synapse_type_exponential module
- Module contents
- spynnaker.pyNN.models.neuron.threshold_types package
- Submodules
- spynnaker.pyNN.models.neuron.abstract_population_vertex module
- spynnaker.pyNN.models.neuron.abstract_pynn_neuron_model module
- spynnaker.pyNN.models.neuron.abstract_pynn_neuron_model_standard module
- spynnaker.pyNN.models.neuron.connection_holder module
- spynnaker.pyNN.models.neuron.generator_data module
- spynnaker.pyNN.models.neuron.population_machine_vertex module
- spynnaker.pyNN.models.neuron.synaptic_manager module
- Module contents
- Subpackages
- spynnaker.pyNN.models.spike_source package
- Submodules
- spynnaker.pyNN.models.spike_source.spike_source_array module
- spynnaker.pyNN.models.spike_source.spike_source_array_vertex module
- spynnaker.pyNN.models.spike_source.spike_source_from_file module
- spynnaker.pyNN.models.spike_source.spike_source_poisson module
- spynnaker.pyNN.models.spike_source.spike_source_poisson_machine_vertex module
- spynnaker.pyNN.models.spike_source.spike_source_poisson_vertex module
- Module contents
- spynnaker.pyNN.models.utility_models package
- Subpackages
- spynnaker.pyNN.models.utility_models.delays package
- Submodules
- spynnaker.pyNN.models.utility_models.delays.delay_block module
- spynnaker.pyNN.models.utility_models.delays.delay_extension_machine_vertex module
- spynnaker.pyNN.models.utility_models.delays.delay_extension_vertex module
- spynnaker.pyNN.models.utility_models.delays.delay_generator_data module
- Module contents
- spynnaker.pyNN.models.utility_models.spike_injector package
- spynnaker.pyNN.models.utility_models.synapse_expander package
- spynnaker.pyNN.models.utility_models.delays package
- Module contents
- Subpackages
Submodules¶
spynnaker.pyNN.models.abstract_pynn_model module¶
-
class
spynnaker.pyNN.models.abstract_pynn_model.
AbstractPyNNModel
[source]¶ Bases:
object
A Model that can be passed in to a Population object in PyNN
-
create_vertex
(n_neurons, label, constraints)[source]¶ Create a vertex for a population of the model
Parameters: - n_neurons (int) – The number of neurons in the population
- label (str) – The label to give to the vertex
- constraints (list or None) – A list of constraints to give to the vertex, or None
Returns: An application vertex for the population
Return type:
-
default_initial_values
= {}¶
-
default_parameters
= {}¶
-
default_population_parameters
¶ - Get the default values for the parameters at the population level
- These are parameters that can be passed in to the Population constructor in addition to the standard PyNN options
Return type: dict(str, object)
-
classmethod
get_max_atoms_per_core
()[source]¶ Get the maximum number of atoms per core for this model
Return type: int
-
classmethod
get_parameter_names
()[source]¶ Get the names of the parameters of the model
Return type: list(str)
-
spynnaker.pyNN.models.defaults module¶
-
spynnaker.pyNN.models.defaults.
default_initial_values
(state_variables)[source]¶ Specifies arguments which are state variables. Only works on the __init__ method of a class that is additionally decorated with
defaults`()
Parameters: state_variables (set of str) – The names of the arguments that are state variables
-
spynnaker.pyNN.models.defaults.
default_parameters
(parameters)[source]¶ Specifies arguments which are parameters. Only works on the __init__ method of a class that is additionally decorated with
defaults`()
Parameters: parameters (set of str) – The names of the arguments that are parameters
-
spynnaker.pyNN.models.defaults.
defaults
(cls)[source]¶ Get the default parameters and state variables from the arguments to the __init__ method. This uses the decorators
default_parameters()
anddefault_initial_values()
to determine the parameters and state variables respectively. If only one is specified, the other is assumed to be the remaining arguments. If neither are specified, it is assumed that all default arguments are parameters.
spynnaker.pyNN.models.pynn_population_common module¶
-
class
spynnaker.pyNN.models.pynn_population_common.
PyNNPopulationCommon
(spinnaker_control, size, label, constraints, model, structure, initial_values, additional_parameters=None)[source]¶ Bases:
object
-
add_placement_constraint
(x, y, p=None)[source]¶ Add a placement constraint
Parameters: - x (int) – The x-coordinate of the placement constraint
- y (int) – The y-coordinate of the placement constraint
- p (int) – The processor ID of the placement constraint (optional)
-
can_record
(variable)[source]¶ Determine whether variable can be recorded from this population.
Note: This is supported by sPyNNaker8
-
conductance_based
¶ True if the population uses conductance inputs
-
first_id
¶
-
get
(parameter_names, gather=False)[source]¶ Get the values of a parameter for every local cell in the population.
Parameters: parameter_names – Name of parameter. This is either a single string or a list of strings Returns: A single list of values (or possibly a single value) if paramter_names is a string, or a dict of these if parameter names is a list. Return type: str or list(str) or dict(str,str) or dict(str,list(str))
-
get_by_selector
(selector, parameter_names)[source]¶ Get the values of a parameter for the selected cell in the population.
Parameters: - parameter_names – Name of parameter. This is either a single string or a list of strings
- selector – a description of the subrange to accept. Or None for all. See: _selector_to_ids in SpiNNUtils.spinn_utilities.ranged.abstract_sized.py
Returns: A single list of values (or possibly a single value) if paramter_names is a string or a dict of these if parameter names is a list.
Return type: str or list(str) or dict(str,str) or dict(str,list(str))
-
id_to_index
(id)[source]¶ Given the ID(s) of cell(s) in the Population, return its (their) index (order in the Population).
-
id_to_local_index
(cell_id)[source]¶ Given the ID(s) of cell(s) in the Population, return its (their) index (order in the Population), counting only cells on the local MPI node.
-
index_to_id
(index)[source]¶ Given the index (order in the Population) of cell(s) in the Population, return their ID(s)
-
label
¶ The label of the population
-
last_id
¶
-
local_size
¶ The number of local cells
-
positions
¶ Return the position array for structured populations.
-
requires_mapping
¶
-
set
(parameter, value=None)[source]¶ Set one or more parameters for every cell in the population.
param can be a dict, in which case value should not be supplied, or a string giving the parameter name, in which case value is the parameter value. value can be a numeric value, or list of such (e.g. for setting spike times):
p.set("tau_m", 20.0). p.set({'tau_m':20, 'v_rest':-65})
Parameters: - parameter (str or dict) – the parameter to set
- value – the value of the parameter to set.
-
set_by_selector
(selector, parameter, value=None)[source]¶ Set one or more parameters for selected cell in the population.
param can be a dict, in which case value should not be supplied, or a string giving the parameter name, in which case value is the parameter value. value can be a numeric value, or list of such (e.g. for setting spike times):
p.set("tau_m", 20.0). p.set({'tau_m':20, 'v_rest':-65})
Parameters: - selector – See RangedList.set_value_by_selector as this is just a pass through method
- parameter – the parameter to set
- value – the value of the parameter to set.
-
set_constraint
(constraint)[source]¶ Apply a constraint to a population that restricts the processor onto which its atoms will be placed.
-
set_mapping_constraint
(constraint_dict)[source]¶ Add a placement constraint - for backwards compatibility
Parameters: constraint_dict (dict(str, int)) – A dictionary containing “x”, “y” and optionally “p” as keys, and ints as values
-
set_max_atoms_per_core
(max_atoms_per_core)[source]¶ Supports the setting of this population’s max atoms per core
Parameters: max_atoms_per_core – the new value for the max atoms per core.
-
size
¶ The number of neurons in the population
-
structure
¶ Return the structure for the population.
-
spynnaker.pyNN.models.pynn_projection_common module¶
-
class
spynnaker.pyNN.models.pynn_projection_common.
PyNNProjectionCommon
(spinnaker_control, connector, synapse_dynamics_stdp, target, pre_synaptic_population, post_synaptic_population, rng, machine_time_step, user_max_delay, label, time_scale_factor)[source]¶ Bases:
object
A container for all the connections of a given type (same synapse type and plasticity mechanisms) between two populations, together with methods to set parameters of those connections, including of plasticity mechanisms.
-
requires_mapping
¶
-