refractoring

src/snn_utils.jl

@@ -289,13 +289,32 @@ end
     one may use bias = -5 to transform synaptic strength into range -5 to 5
     the return value is shifted back to original scale
 """
-function synapticConnStrength(currentStrength::AbstractFloat, bias::Number=0)
+function synapticConnStrength(currentStrength::AbstractFloat, updown::String, bias::Number=0)
     currentStrength += bias
-    updatedStrength - (1.0 - sigmoid(currentStrength))
+    if currentStrength > 0
+        Δstrength = (1.0 - sigmoid(currentStrength))
+    else
+        Δstrength = sigmoid(currentStrength)
+    end
+
+    if updown == "up"
+        updatedStrength = currentStrength + Δstrength
+    else
+        updatedStrength = currentStrength - Δstrength
+    end
     updatedStrength -= bias
     return updatedStrength
 end
 
+function synapticConnStrength(n::compute_neuron)
+    for connStrength in n.synapticStrength
+        
+        synapticConnStrength
+
+
+
+end
+
 
 
 
@@ -313,8 +332,6 @@ end
 
 
 
-
-
 
 
 end     # end module

src/types.jl

@@ -529,7 +529,7 @@ Base.@kwdef mutable struct linear_neuron <: output_neuron
     # previous timestep)
     z_i_t::Union{Array{Bool},Nothing} = nothing 
     synapticStrength::Union{Array{Float64},Nothing} = nothing
-    synapticStrengthLimit::Union{NamedTuple,Nothing} = (lowerlimit=(-5=>0), upperlimit=(5=>5))
+    synapticStrengthLimit::Union{NamedTuple,Nothing} = (lowerlimit=(-5=>-5), upperlimit=(5=>5))
 
     gammaPd::Union{Float64,Nothing} = 0.3      # γ_pd, discount factor, value from paper
     alpha::Union{Float64,Nothing} = nothing          # α, neuron membrane potential decay factor
@@ -630,10 +630,10 @@ function init_neuron!(id::Int64, n::lif_neuron, n_params::Dict, kfnParams::Dict)
     
     # prevent subscription to itself by removing this neuron id
     filter!(x -> x != n.id, n.subscriptionList)
-    n.synapticStrength = normalize!(rand(length(n.subscriptionList)), 1)
+    n.synapticStrength = rand(-5:0.1:-3, length(n.subscriptionList))
 
     n.epsilonRec = zeros(length(n.subscriptionList))
-    n.wRec = Random.rand(length(n.subscriptionList))
+    n.wRec = LinearAlgebra.normalize!(rand(length(n.subscriptionList)), 1)
     n.wRecChange = zeros(length(n.subscriptionList))
     n.alpha = calculate_α(n)
 end
@@ -649,10 +649,10 @@ function init_neuron!(id::Int64, n::alif_neuron, n_params::Dict,
 
     # prevent subscription to itself by removing this neuron id
     filter!(x -> x != n.id, n.subscriptionList)
-    n.synapticStrength = normalize!(rand(length(n.subscriptionList)), 1)
+    n.synapticStrength = rand(-5:0.1:-3, length(n.subscriptionList))
 
     n.epsilonRec = zeros(length(n.subscriptionList))
-    n.wRec = Random.rand(length(n.subscriptionList))
+    n.wRec = LinearAlgebra.normalize!(rand(length(n.subscriptionList)), 1)
     n.wRecChange = zeros(length(n.subscriptionList))
 
     # the more time has passed from the last time neuron was activated, the more 
@@ -671,9 +671,10 @@ function init_neuron!(id::Int64, n::linear_neuron, n_params::Dict, kfnParams::Di
     subscription_numbers = Int(floor(n_params[:synaptic_connection_number] * 
                             kfnParams[:total_compute_neuron] / 100.0))
     n.subscriptionList = [pop!(subscription_options) for i = 1:subscription_numbers]
-    n.synapticStrength = normalize!(rand(length(n.subscriptionList)), 1)
+    n.synapticStrength = rand(-5:0.1:-3, length(n.subscriptionList))
+
     n.epsilonRec = zeros(length(n.subscriptionList))
-    n.wRec = Random.rand(length(n.subscriptionList))
+    n.wRec = LinearAlgebra.normalize!(rand(length(n.subscriptionList)), 1)
     n.wRecChange = zeros(length(n.subscriptionList))
     n.alpha = calculate_k(n)
 end