spynnaker.pyNN.models.neuron.structural_plasticity.synaptogenesis.elimination package

Module contents

class spynnaker.pyNN.models.neuron.structural_plasticity.synaptogenesis.elimination.AbstractElimination

Bases: object

A synaptic connection elimination rule.

abstract get_parameter_names()[source]

Return the names of the parameters supported by this rule.

Return type:

iterable(str)

abstract get_parameters_sdram_usage_in_bytes()[source]

Get the amount of SDRAM used by the parameters of this rule.

Return type:

int

abstract property vertex_executable_suffix

The suffix to be appended to the vertex executable for this rule.

Return type:

str

abstract write_parameters(spec, weight_scale)[source]

Write the parameters of the rule to the spec.

Parameters:

  • spec (DataSpecificationGenerator) –

  • weight_scale (float) –

class spynnaker.pyNN.models.neuron.structural_plasticity.synaptogenesis.elimination.RandomByWeightElimination(threshold, prob_elim_depressed=0.0245, prob_elim_potentiated=0.00013600000000000003)

Bases: AbstractElimination

Elimination Rule that depends on the weight of a synapse.

Parameters:

  • threshold (float) – Below this weight is considered depression, above or equal to this weight is considered potentiation (or the static weight of the connection on static weight connections)

  • prob_elim_depressed (float) – The probability of elimination if the weight has been depressed (ignored on static weight connections)

  • prob_elim_potentiated (float) – The probability of elimination of the weight has been potentiated or has not changed (and also used on static weight connections)

get_parameter_names()[source]

Return the names of the parameters supported by this rule.

Return type:

iterable(str)

get_parameters_sdram_usage_in_bytes()[source]

Get the amount of SDRAM used by the parameters of this rule.

Return type:

int

property vertex_executable_suffix

The suffix to be appended to the vertex executable for this rule.

Return type:

str

write_parameters(spec, weight_scale)[source]

Write the parameters of the rule to the spec.

Parameters:

  • spec (DataSpecificationGenerator) –

  • weight_scale (float) –