def __init__(self,
n_neurons,
max_delay_per_neuron,
source_vertex,
machine_time_step,
timescale_factor,
constraints=None,
label="DelayExtension"):
"""
Creates a new DelayExtension Object.
"""
AbstractPartitionableVertex.__init__(self,
n_atoms=n_neurons,
constraints=constraints,
label=label,
max_atoms_per_core=256)
AbstractDataSpecableVertex.__init__(
self,
machine_time_step=machine_time_step,
timescale_factor=timescale_factor)
AbstractProvidesIncomingEdgeConstraints.__init__(self)
AbstractOutgoingEdgeSameContiguousKeysRestrictor.__init__(self)
self._max_delay_per_neuron = max_delay_per_neuron
self._max_stages = 0
self._source_vertex = source_vertex
joint_constrant = PartitionerSameSizeAsVertexConstraint(source_vertex)
self.add_constraint(joint_constrant)
def __init__(self, n_neurons, max_delay_per_neuron, source_vertex,
machine_time_step, timescale_factor, constraints=None,
label="DelayExtension"):
"""
Creates a new DelayExtension Object.
"""
AbstractPartitionableVertex.__init__(self, n_atoms=n_neurons,
constraints=constraints,
label=label,
max_atoms_per_core=256)
AbstractDataSpecableVertex.__init__(
self, machine_time_step=machine_time_step,
timescale_factor=timescale_factor)
AbstractProvidesIncomingEdgeConstraints.__init__(self)
AbstractProvidesNKeysForEdge.__init__(self)
self._max_delay_per_neuron = max_delay_per_neuron
self._max_stages = 0
self._source_vertex = source_vertex
joint_constrant = PartitionerSameSizeAsVertexConstraint(source_vertex)
self.add_constraint(joint_constrant)
def __init__(
self, n_neurons, binary, label, max_atoms_per_core,
machine_time_step, timescale_factor, spikes_per_second,
ring_buffer_sigma, model_name, neuron_model, input_type,
synapse_type, threshold_type, additional_input=None,
constraints=None):
ReceiveBuffersToHostBasicImpl.__init__(self)
AbstractPartitionableVertex.__init__(
self, n_neurons, label, max_atoms_per_core, constraints)
AbstractDataSpecableVertex.__init__(
self, machine_time_step, timescale_factor)
AbstractSpikeRecordable.__init__(self)
AbstractVRecordable.__init__(self)
AbstractGSynRecordable.__init__(self)
AbstractProvidesOutgoingEdgeConstraints.__init__(self)
AbstractProvidesIncomingEdgeConstraints.__init__(self)
AbstractPopulationInitializable.__init__(self)
AbstractPopulationSettable.__init__(self)
AbstractMappable.__init__(self)
self._binary = binary
self._label = label
self._machine_time_step = machine_time_step
self._timescale_factor = timescale_factor
self._model_name = model_name
self._neuron_model = neuron_model
self._input_type = input_type
self._threshold_type = threshold_type
self._additional_input = additional_input
# Set up for recording
self._spike_recorder = SpikeRecorder(machine_time_step)
self._v_recorder = VRecorder(machine_time_step)
self._gsyn_recorder = GsynRecorder(machine_time_step)
self._spike_buffer_max_size = config.getint(
"Buffers", "spike_buffer_size")
self._v_buffer_max_size = config.getint(
"Buffers", "v_buffer_size")
self._gsyn_buffer_max_size = config.getint(
"Buffers", "gsyn_buffer_size")
self._buffer_size_before_receive = config.getint(
"Buffers", "buffer_size_before_receive")
self._time_between_requests = config.getint(
"Buffers", "time_between_requests")
# Set up synapse handling
self._synapse_manager = SynapticManager(
synapse_type, machine_time_step, ring_buffer_sigma,
spikes_per_second)
# Get buffering information for later use
self._receive_buffer_host = config.get(
"Buffers", "receive_buffer_host")
self._receive_buffer_port = config.getint(
"Buffers", "receive_buffer_port")
self._enable_buffered_recording = config.getboolean(
"Buffers", "enable_buffered_recording")
# bool for if state has changed.
self._change_requires_mapping = True
