minor fix

src/learn.jl

@@ -198,9 +198,10 @@ function learn!(n::T, firedNeurons, nExInType) where T<:computeNeuron
     wSign_1 = sign.(n.wRec)   # check for fliped sign, 1 indicates non-fliped sign
     nonFlipedSign = isequal.(wSign_0, wSign_1)  # 1 not fliped, 0 fliped
     # normalize wRec peak to prevent input signal overwhelming neuron
-    # if sum(n.wRecChange) != 0
+    if sum(n.wRecChange) != 0
-    #     normalizePeak!(n.wRec, n.wRecChange, 2)
+        normRadius = Int(floor(0.1 * length(n.subscriptionList)))
-    # end
+        normalizePeak!(n.wRec, n.wRecChange, normRadius)
+    end
 
     # set weight that fliped sign to 0 for random new connection
     n.wRec .*= nonFlipedSign 

src/snn_utils.jl

@@ -322,6 +322,43 @@ end
 """ rewire of neuron synaptic connection that has 0 weight. Without connection's excitatory and 
     inhabitory ratio constraint.
 """
+# function neuroplasticity!(n::computeNeuron, firedNeurons::Vector,
+#                         nExInTypeList::Vector)
+#     # if there is 0-weight then replace it with new connection
+#     zeroWeightConnIndex = findall(iszero.(n.wRec))   # connection that has 0 weight
+#     if length(zeroWeightConnIndex)  != 0
+#         # new synaptic connection must sample fron neuron that fires
+#         nFiredPool = filter(x -> x ∉ [n.id], firedNeurons)  # exclude this neuron id from the id list
+#         filter!(x -> x ∉ n.subscriptionList, nFiredPool) # exclude this neuron's subscriptionList from the list
+
+#         nNonFiredPool = setdiff!([1:length(nExInTypeList)...], nFiredPool)
+#         filter!(x -> x ∉ [n.id], nNonFiredPool)  # exclude this neuron id from the id list
+#         filter!(x -> x ∉ n.subscriptionList, nNonFiredPool) # exclude this neuron's subscriptionList from the list
+
+#         w = randn(length(zeroWeightConnIndex)) / 10
+#         synapticStrength = rand(-4.5:0.1:-3.5, length(zeroWeightConnIndex))
+
+#         shuffle!(nFiredPool)
+#         shuffle!(nNonFiredPool)
+
+#         # add new synaptic connection to neuron
+#         for (i, connIndex) in enumerate(zeroWeightConnIndex)
+#             """ conn that is being replaced has to go into nNonFiredPool so 
+#             nNonFiredPool isn't empty """
+#             push!(nNonFiredPool, n.subscriptionList[connIndex])
+                
+#             if length(nFiredPool) != 0 
+#                 newConn = popfirst!(nFiredPool) 
+#             else
+#                 newConn = popfirst!(nNonFiredPool)
+#             end
+#             n.subscriptionList[connIndex] = newConn
+#             n.wRec[connIndex] = w[i] * nExInTypeList[newConn]
+#             n.synapticStrength[connIndex] = synapticStrength[i]
+#         end
+#     end
+# end
+
 function neuroplasticity!(n::computeNeuron, firedNeurons::Vector,
                         nExInTypeList::Vector)
     # if there is 0-weight then replace it with new connection
@@ -346,14 +383,14 @@ function neuroplasticity!(n::computeNeuron, firedNeurons::Vector,
             """ conn that is being replaced has to go into nNonFiredPool so 
             nNonFiredPool isn't empty """
             push!(nNonFiredPool, n.subscriptionList[connIndex])
-                
+            pool = GeneralUtils.randomChoiceWithProb([nFiredPool, nNonFiredPool],[0.5, 0.5])
-            if length(nFiredPool) != 0 
+            if length(pool) != 0 
-                newConn = popfirst!(nFiredPool) 
+                newConn = popfirst!(pool) 
             else
                 newConn = popfirst!(nNonFiredPool)
             end
             n.subscriptionList[connIndex] = newConn
-            n.wRec[connIndex] = w[i] #* nExInTypeList[newConn]
+            n.wRec[connIndex] = w[i] * nExInTypeList[newConn]
             n.synapticStrength[connIndex] = synapticStrength[i]
         end
     end