Struct SynapseMatrix 

pub struct SynapseMatrix {
    pub n_pre: usize,
    pub n_post: usize,
    pub config: STDPConfig,
    /* private fields */
}

Matrix of synaptic connections

Fields

n_pre: usize

Number of pre-synaptic neurons

n_post: usize

Number of post-synaptic neurons

config: STDPConfig

STDP configuration

Implementations

impl SynapseMatrix

pub fn new(n_pre: usize, n_post: usize) -> Self

Create a new synapse matrix

pub fn with_config(n_pre: usize, n_post: usize, config: STDPConfig) -> Self

Create with custom STDP config

pub fn add_synapse(&mut self, pre: usize, post: usize, weight: f64)

Add a synapse

pub fn get_synapse(&self, pre: usize, post: usize) -> Option<&Synapse>

Get synapse if it exists

pub fn get_synapse_mut( &mut self, pre: usize, post: usize, ) -> Option<&mut Synapse>

Get mutable synapse if it exists

pub fn weight(&self, pre: usize, post: usize) -> f64

Get weight of a synapse (0 if doesn’t exist)

pub fn compute_weighted_sums(&self, pre_activations: &[f64]) -> Vec<f64>

Compute weighted sum for all post-synaptic neurons given pre-synaptic activations

This is optimized to iterate only over existing synapses, avoiding O(n²) lookups. pre_activations[i] is the activation of pre-synaptic neuron i. Returns vector of weighted sums for each post-synaptic neuron.

pub fn weighted_sum_for_post(&self, post: usize, pre_activations: &[f64]) -> f64

Compute weighted sum for a single post-synaptic neuron

pub fn set_weight(&mut self, pre: usize, post: usize, weight: f64)

Set weight of a synapse (creates if doesn’t exist)

pub fn on_pre_spike(&mut self, pre: usize, time: SimTime)

Record a pre-synaptic spike and perform STDP updates

pub fn on_post_spike(&mut self, post: usize, time: SimTime)

Record a post-synaptic spike and perform STDP updates

pub fn process_spikes(&mut self, spikes: &[Spike])

Process multiple spikes with STDP

pub fn decay_eligibility(&mut self, dt: f64)

Decay all eligibility traces

pub fn apply_reward(&mut self, reward: f64)

Apply reward-modulated learning to all synapses

pub fn iter(&self) -> impl Iterator<Item = (&(usize, usize), &Synapse)>

Get all synapses as an iterator

pub fn num_synapses(&self) -> usize

Get number of synapses

pub fn input_to(&self, post: usize, pre_activities: &[f64]) -> f64

Compute total synaptic input to a post-synaptic neuron

pub fn to_dense(&self) -> Vec<Vec<f64>>

Create dense weight matrix

pub fn from_dense(matrix: &[Vec<f64>]) -> Self

Initialize from dense matrix

pub fn sync_to_graph<F>(&self, graph: &mut DynamicGraph, neuron_to_vertex: F)

where F: Fn(usize) -> VertexId,

Synchronize weights with a DynamicGraph Maps neurons to vertices via a mapping function

pub fn sync_from_graph<F>(&mut self, graph: &DynamicGraph, vertex_to_neuron: F)

where F: Fn(VertexId) -> usize,

Load weights from a DynamicGraph

pub fn high_correlation_pairs(&self, threshold: f64) -> Vec<(usize, usize)>

Get high-correlation pairs (synapses with weight above threshold)

Trait Implementations

impl Clone for SynapseMatrix

fn clone(&self) -> SynapseMatrix

Returns a duplicate of the value.

fn clone_from(&mut self, source: &Self)

Performs copy-assignment from source.

impl Debug for SynapseMatrix

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.