spynnaker.pyNN.models.neuron.structural_plasticity.synaptogenesis.formation package¶
Module contents¶
- class spynnaker.pyNN.models.neuron.structural_plasticity.synaptogenesis.formation.AbstractFormation¶
Bases:
object
A synaptic connection formation 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:
- abstract property vertex_executable_suffix¶
The suffix to be appended to the vertex executable for this rule.
- Return type:
- class spynnaker.pyNN.models.neuron.structural_plasticity.synaptogenesis.formation.DistanceDependentFormation(grid=(16, 16), p_form_forward=0.16, sigma_form_forward=2.5, p_form_lateral=1.0, sigma_form_lateral=1.0)¶
Bases:
AbstractFormation
Formation rule that depends on the physical distance between neurons.
- Parameters:
grid (tuple(int,int) or list(int) or ndarray(int)) – (x, y) dimensions of the grid of distance
p_form_forward (float) – The peak probability of formation on feed-forward connections
sigma_form_forward (float) – The spread of probability with distance of formation on feed-forward connections
p_form_lateral (float) – The peak probability of formation on lateral connections
sigma_form_lateral (float) – The spread of probability with distance of formation on lateral connections
- distance(x0, x1, metric)[source]¶
Compute the distance between points x0 and x1 place on the grid using periodic boundary conditions.
- generate_distance_probability_array(probability, sigma)[source]¶
Generate the exponentially decaying probability LUTs.
- 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:
- property vertex_executable_suffix¶
The suffix to be appended to the vertex executable for this rule.
- Return type: