spynnaker.pyNN.models.neuron.plasticity.stdp.weight_dependence package¶
Module contents¶
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class
spynnaker.pyNN.models.neuron.plasticity.stdp.weight_dependence.
AbstractHasAPlusAMinus
[source]¶ Bases:
object
An object that has \(A^+\) and \(A^-\) properties.
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class
spynnaker.pyNN.models.neuron.plasticity.stdp.weight_dependence.
AbstractWeightDependence
[source]¶ Bases:
object
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get_parameters_sdram_usage_in_bytes
(n_synapse_types, n_weight_terms)[source]¶ Get the amount of SDRAM used by the parameters of this rule
Parameters: Return type:
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is_same_as
(weight_dependence)[source]¶ Determine if this weight dependence is the same as another
Parameters: weight_dependence (AbstractWeightDependence) – Return type: bool
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vertex_executable_suffix
¶ The suffix to be appended to the vertex executable for this rule
Return type: str
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weight_maximum
¶ The maximum weight that will ever be set in a synapse as a result of this rule
Return type: float
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write_parameters
(spec, global_weight_scale, synapse_weight_scales, n_weight_terms)[source]¶ Write the parameters of the rule to the spec
Parameters: - spec (DataSpecificationGenerator) – The specification to write to
- global_weight_scale (float) – The weight scale applied globally
- synapse_weight_scales (list(float)) – The total weight scale applied to each synapse including the global weight scale
- n_weight_terms (int) – The number of terms used by the synapse rule
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class
spynnaker.pyNN.models.neuron.plasticity.stdp.weight_dependence.
WeightDependenceAdditive
(w_min=0.0, w_max=1.0)[source]¶ Bases:
spynnaker.pyNN.models.neuron.plasticity.stdp.weight_dependence.abstract_has_a_plus_a_minus.AbstractHasAPlusAMinus
,spynnaker.pyNN.models.neuron.plasticity.stdp.weight_dependence.abstract_weight_dependence.AbstractWeightDependence
An additive weight dependence STDP rule.
Parameters: -
get_parameters_sdram_usage_in_bytes
(n_synapse_types, n_weight_terms)[source]¶ Get the amount of SDRAM used by the parameters of this rule
Parameters: Return type:
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is_same_as
(weight_dependence)[source]¶ Determine if this weight dependence is the same as another
Parameters: weight_dependence (AbstractWeightDependence) – Return type: bool
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vertex_executable_suffix
¶ The suffix to be appended to the vertex executable for this rule
Return type: str
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weight_maximum
¶ The maximum weight that will ever be set in a synapse as a result of this rule
Return type: float
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write_parameters
(spec, global_weight_scale, synapse_weight_scales, n_weight_terms)[source]¶ Write the parameters of the rule to the spec
Parameters: - spec (DataSpecificationGenerator) – The specification to write to
- global_weight_scale (float) – The weight scale applied globally
- synapse_weight_scales (list(float)) – The total weight scale applied to each synapse including the global weight scale
- n_weight_terms (int) – The number of terms used by the synapse rule
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class
spynnaker.pyNN.models.neuron.plasticity.stdp.weight_dependence.
WeightDependenceMultiplicative
(w_min=0.0, w_max=1.0)[source]¶ Bases:
spynnaker.pyNN.models.neuron.plasticity.stdp.weight_dependence.abstract_has_a_plus_a_minus.AbstractHasAPlusAMinus
,spynnaker.pyNN.models.neuron.plasticity.stdp.weight_dependence.abstract_weight_dependence.AbstractWeightDependence
A multiplicative weight dependence STDP rule.
Parameters: -
get_parameters_sdram_usage_in_bytes
(n_synapse_types, n_weight_terms)[source]¶ Get the amount of SDRAM used by the parameters of this rule
Parameters: Return type:
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is_same_as
(weight_dependence)[source]¶ Determine if this weight dependence is the same as another
Parameters: weight_dependence (AbstractWeightDependence) – Return type: bool
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vertex_executable_suffix
¶ The suffix to be appended to the vertex executable for this rule
Return type: str
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weight_maximum
¶ The maximum weight that will ever be set in a synapse as a result of this rule
Return type: float
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write_parameters
(spec, global_weight_scale, synapse_weight_scales, n_weight_terms)[source]¶ Write the parameters of the rule to the spec
Parameters: - spec (DataSpecificationGenerator) – The specification to write to
- global_weight_scale (float) – The weight scale applied globally
- synapse_weight_scales (list(float)) – The total weight scale applied to each synapse including the global weight scale
- n_weight_terms (int) – The number of terms used by the synapse rule
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class
spynnaker.pyNN.models.neuron.plasticity.stdp.weight_dependence.
WeightDependenceAdditiveTriplet
(w_min=0.0, w_max=1.0, A3_plus=0.01, A3_minus=0.01)[source]¶ Bases:
spynnaker.pyNN.models.neuron.plasticity.stdp.weight_dependence.abstract_has_a_plus_a_minus.AbstractHasAPlusAMinus
,spynnaker.pyNN.models.neuron.plasticity.stdp.weight_dependence.abstract_weight_dependence.AbstractWeightDependence
An triplet-based additive weight dependence STDP rule.
Parameters: -
default_parameters
= {'A3_minus': 0.01, 'A3_plus': 0.01, 'w_max': 1.0, 'w_min': 0.0}¶
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get_parameters_sdram_usage_in_bytes
(n_synapse_types, n_weight_terms)[source]¶ Get the amount of SDRAM used by the parameters of this rule
Parameters: Return type:
-
is_same_as
(weight_dependence)[source]¶ Determine if this weight dependence is the same as another
Parameters: weight_dependence (AbstractWeightDependence) – Return type: bool
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vertex_executable_suffix
¶ The suffix to be appended to the vertex executable for this rule
Return type: str
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weight_maximum
¶ The maximum weight that will ever be set in a synapse as a result of this rule
Return type: float
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write_parameters
(spec, global_weight_scale, synapse_weight_scales, n_weight_terms)[source]¶ Write the parameters of the rule to the spec
Parameters: - spec (DataSpecificationGenerator) – The specification to write to
- global_weight_scale (float) – The weight scale applied globally
- synapse_weight_scales (list(float)) – The total weight scale applied to each synapse including the global weight scale
- n_weight_terms (int) – The number of terms used by the synapse rule
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